Advancement in Crop Improvement Techniques [1 ed.] 0128185813, 9780128185810

Table of contents :
Cover
Advancement in Crop
Improvement Techniques
Copyright
Dedication
Dedicated to Ph.D. students and collaborators of Dr. Tuteja
Contributors
Editors biography
Foreword
Preface
Views and visions
References
Views and visions
Combination of DNA markers and eQTL information for introgression of multiple salt-tolerance traits in rice
Introduction
DNA markers for rice breeding
SSR markers
SNP markers
Fluorescent markers
Illumina´s BeadArray platform
Taqman
TaqMan principle for SNP detection
KASP technology: An efficient approach for breeding applications
Chemistry of KASP technology
Reaction mechanism
KASP as a better choice
Use of markers
Mapping, QTL information, and use
Mapping population
Linkage mapping
QTL detection
Identified QTLs
Candidate genes cosegregating with QTL regions
RNAseq, eQTL information, and use
Discovering the expression polymorphism
Linking expression polymorphism to genetic polymorphism
Significance of studying eQTLs
Case studies on plant eQTLs
Salt stress responsive eQTL study on Horkuch/IR29 cross population
Challenges in studying eQTLs
GWAS
Breeding
Computational analysis and technology advancement
Mapping populations
Phenotyping strategies
High-throughput automated image-based phenotyping
Genotyping strategies
High-throughput DNA isolation methods
Genotyping by sequencing
Functional/diagnostic markers
Computational tools for linkage and QTL mapping
Breeding strategies
GS is a way forward for MAS
Rapid generation advance and transforming rice breeding
Targeting induced local lesions in genome (TILLING)
Marker-assisted gene pyramiding
Conclusion and future perspectives
References
The scope of transformation and genome editing for quantitative trait improvements in rice
Introduction
Transformation technologies
Agrobacterium-mediated
Biolistics
In planta methods
Genome editing
Target quantitative traits
Biotic and abiotic stress
Conventional transformation
Crop improvement through CRISPR-CAS
Yield stability under stress
Conventional transformation
Crop improvement through CRISPR
Computational analysis
Technology advancement
Conclusion and future perspectives
References
Tweaking microRNA-mediated gene regulation for crop improvement
Introduction
Contribution of miRNA-mediated regulation in plant growth and development
miRNA-mediated regulation of shoot meristem maintenance
miRNA-mediated regulation of leaf growth and development
miRNA-mediated regulation of root growth and development
miRNA-mediated regulation of the vegetative-to-reproductive phase transition
miRNA-mediated regulation of reproductive development and its improvement
miRNA-mediated regulation of seed development and germination
Role of miRNAs in improving crop yield and other agronomic traits
miRNA-mediated regulation involved in plant architecture improvement
Role of miRNAs in acclimatization of plant growth to diverse environmental stresses
miRNA-mediated regulation of host-partner relationships in crop plants
miRNA-mediated regulation of disease resistance in crop plants
Use of computational biology in advancing plant miRNA research in crop plants
Technology advancements
Recent advancements in miRNA profiling and validation
Applications of genome editing technology in miRNA-mediated crop improvement
Conclusion and future perspectives
References
Modern tools in improving rice production
Introduction
Bioinformatic tools
Genome-wide association studies (GWAS)
Use of molecular markers in rice yield improvement
Genome editing tools
Installing C4 photosynthetic pathways into C3 rice plants to enhance the crop yield
Rice yield and MAPK signaling
Conclusion and future perspectives
References
Molecular aspects of seed priming as a means of progress in crop improvement
Introduction
Seed priming in the context of current challenges facing agriculture and crop production
Priming agents and treatments: An overview
Seed priming versus seed aging in the context of seed bank storage
Seed priming as a tool to limit aging-associated damage
The molecular know-how of seed priming and its implications in promoting new advances in the sectors of seed biology a ...
The redox context of the pregerminative metabolism and the harmful oxidative damage
Active DNA repair during the pregerminative metabolism: a molecular know-how for seed priming
Technology advancement
Multilevel approaches to understand seed biology and assess seed quality
Conclusion and future perspectives
References
Further Reading
Plant histidine kinases: Targets for crop improvement
Introduction
Plant histidine kinases (HKs) and the multistep phosphorelay (MSP)
Histidine kinases for crop improvement in dicots
Ethylene receptors
Nonethylene receptors and cytokinin receptors
Targeting histidine kinases to improve cereal productivity
Genome-wide analysis: Histidine kinases from other plant species
Technology advancement
Conclusion and future perspectives
References
Recent efforts in developing high-yield, drought-tolerant rice varieties
Introduction
Historical famines and food shortages in the world
Food security and malnutrition
Climate change and its effect on food production
Drought
Biology of drought tolerance
Trait characterization and phenotyping as selection criteria
Physiological, morphological, and biochemical response and derivations to tolerance
Breeding strategies
Population development and improvement
Conventional breeding
Marker-assisted breeding
Fine mapping of identified genetic regions
Deployment of genetic loci: QTL pyramiding
Interaction among QTLs, and with background and environment
Transgenic approaches
High-throughput novel genotypic strategies and techniques
Computational analysis
Drought policies
Conclusion and future perspectives
References
Further reading
Advances in genomics and molecular breeding for legume improvement
Introduction
Evolution of molecular marker technologies and genotyping assays
Genetic resources and molecular mapping of agriculturally important traits
Whole genome sequencing of the reference genotypes
Resequencing multiple genomes to better understand genetic variation
Genomics-assisted breeding in legume crops: From MAS to GS and sequence-based breeding
Speed breeding in legume crops for accelerating genetic gains
Genomic technologies to accelerate hybrid breeding
Conclusion and perspectives
References
Advancements in plant disease control strategies
Introduction
Plant immune system
Marker-assisted breeding for crop improvement
Genome editing approaches for disease-resistant plants
Emergence of CRISPR technology
CRISPR-Cas system: A brief overview
Application of CRISPR/Cas9 for plant defense
Resistance against viruses
Resistance against fungi
Resistance against bacteria
Limitations of CRISPR/cas9 system
Current status of CRISPR-Cas technology
RNA interference as a tool for plant defense
Mechanism of RNA silencing
RNAi for plant resistance
Exosome-like vesicle-mediated RNAi silencing: an emerging approach
Biological control agents for efficient disease management
Mechanisms of pathogen antagonism by BCA
Hyperparasitism
Predation
Competition
Metabolite production
Induction of resistance
Biological control of fungal pathogens
Computational tools
Conclusion and future perspectives
References
How Crisp is CRISPR? CRISPR-Cas-mediated crop improvement with special focus on nutritional traits
Overview of CRISPR-Cas technology
An array of CRISPR-Cas-mediated genome editing systems
Cas9
Cpf1
Cas13a
Cas14a
Advancements in genome editing for crop improvement: stress and nutritional traits
Gene knockout
Precise editing via gene targeting
Base editing
Prime editing
Molecular farming
Molecular domestication via CRISPR-Cas9-based breeding
Editing for simple and complex traits
Multiplex genome editing and applications
Approaches in genome editing for crop improvement
Strategies for reducing off-target effects of the CRISPR-Cas system
Modulating Cas9 activity
Optimization of sgRNA design
Cas9 and Cpf1 variants
DNA-free genome editing/Cas9 protein RNP complexes in vitro
Enhancing HDR pathway efficiency by reducing the NHEJ pathway
High-throughput screening of plant mutant libraries
Chimeric fusion of catalytic domains
Employing anti-CRISPR protein activities
CRISPR-Cas9 mediated antiviral breeding approaches
Employing differential CRISPR-Cas delivery systems
CRISPR achievements in plants that cater to nutrition
Foods developed employing CRISPR as a means to revolutionize agriculture
Inclusion of GWAS into the CRISPR domain for additive nutrition
Value rendered by CRISPR toward the promotion of food security
Technological influx and CRISPR-Cas technology
Machine learning and CRISPR-Cas9 genome editing
Social acceptance of genome-edited (GE) plants using CRISPR technology
Policy and government perspectives on the regulation of GE crops
Conclusion
References
Targeted genome editing using CRISPR-Cas9: Applications in fruit quality and stress resilience
Introduction
Improvement of traits associated with fruit quality
Mitigation of climate change effects on agricultural productivity
Computational analysis
Technology advancement
Conclusions and future perspectives
References
Chapter 13 - Systems biology of crop improvement: Drought tolerance as a model to integrate molecular biology, physiology, and breeding
Introduction
The complex physiological response to drought
ROS production and antioxidants as a means for drought tolerance
Phytohormones in drought stress response
Connecting physiological and molecular responses to drought
Drought-inducible proteins
Transcription factors
Kinases
Micro-RNAs
Role of epigenetic response to abiotic stress
Novel molecular targets and processes for drought tolerance
Breeding for drought tolerance
The case of the QTL qDTY12.1
Big data analytics for efficient breeding
The WISH project: A case study
Wonder Rice Initiative for Food Security and Health
Addressing common breeding bottlenecks under the WISH program
Speed and cost of varietal improvement
Quality of improved rice cultivars
Acceptability of improved varieties by farmers
Conclusions
References
The microbial symbionts: Potential for crop improvement in changing environments
Introduction
Diversity of soil- and plant-associated microorganisms isolated from environments
The endophytic microbes associated with plant symbionts and their functions
Rhizobium (Rhizobiaceae)
Arbuscular mycorrhizal fungi
Trichoderma
Serendipita indica
Significance of microorganisms for agriculture and inoculants in the future
Technological advancement
Conclusion and future perspectives
References
Reactive oxygen species (ROS) management in engineered plants for abiotic stress tolerance
Introduction
Abiotic stresses
Reactive oxygen species and its scavenging machinery
Role of ion transporters
Role of osmolytes/osmoprotectants
Role of transcription factors
Genetic engineering approaches to develop salinity tolerance
To increase crop production
To increase nutrition values
Genomewide perspective of ROS scavenging machinery in plants
References
Further reading
Metabolomics-assisted crop improvement
Plant metabolome and metabolic pathways
Metabolomics
Practical approaches in metabolomics
Targeted metabolomics
Nontargeted metabolomics
Metabolomics at the cellular and subcellular levels
Integration of metabolomics with other ``omics´´
Integration of metabolomics with transcriptomics
Integration of metabolomics with proteomics
Metabolomics-assisted crop improvement
Computational analysis
Technological advancements and limitations
Conclusion and future prospects
References
Improving medicinal crops through phytochemical perspective: Withania somnifera (Ashwagandha)
Introduction
Diverse species of W. somnifera
Ethnobotany of W. somnifera
Withanolides: The signature molecules of W. somnifera
Development of improved varieties of W. somnifera
Improvement in W. somnifera by conventional approaches
Improvement by nonconventional approaches
Technical advancement of W. somnifera
Application of metabolic engineering
Functional characterization of enzymes involved in early biosynthetic steps
Enzymes involved in the modification of the terpene backbone in withanolide biosynthesis
Application of computational and in silico studies
Computational analysis in W. somnifera
Transcriptome-wide analysis to identify genes involved in withanolide biosynthesis
EST and transcriptome analysis to identify genes involved in withanolide biosynthesis
Application of in vitro methods
Marker-based approaches
Conclusions and future perspectives
References
Approaches for conservation and improvement of Himalayan plant genetic resources
Introduction
Strategies for the conservation and improvement of plant genetic resources
Geospatial and imaging technologies
Geographic information system technologies
Remote sensing technologies
Thermal imaging for species discrimination
Functional trait-based approach for conservation of threatened species
Micropropagation as a method for sustainable resource generation
Importance of adventitious roots and hairy roots in conservation
In vitro production of quality medicinal and aromatic plant ingredients
Hydroponic and aeroponic cultivation of medicinal plants
Picrorhiza kurroa Royle ex Benth: A case study
Importance of genetic diversity in conservation of biodiversity
Genomic resource creation and genetic diversity analysis in Himalayan plants
Gene banks, captive cultivation, and varietal improvement of threatened medicinal plants
Metabolic engineering for modulating primary and secondary metabolisms
Technological advancements
Conclusion
References
Molecular markers as tools to improve date palms
Introduction
Role of molecular markers in the assessment of genetic diversity
DNA markers
Restriction fragment length polymorphism (RFLP)
Amplified fragment length polymorphism (AFLP)
Random amplified polymorphic DNA (RAPD)
Microsatellites
Intersimple sequence repeats (ISSR)
Expressed sequence tags (EST)
Single nucleotide polymorphisms (SNPs)
Combined methods
Molecular markers linked to sex in the date palm
Computational analysis
Conclusion and future perspectives
References
Transgenic approach in crop improvement
Introduction
Classification of crop improvement methods
Plant breeding
Transgenic approach
Genetically modification via genetic tools
Journey of plant transformation
Plant transformation methods
Agrobacterium-mediated transformation
Microinjection
Agro-infection
Chloroplast transformation
Electroporation
Biolistic (gene gun) method
Chemical method of gene transfer
PEG-mediated gene transfer
Calcium-phosphate coprecipitation-mediated transfer
DEAE dextran-mediated transfer
Pollen transformation
Direct DNA uptake by mature zygotic embryos
Need for transgenic approach in crop improvement
Acceptance of transgenic crops
Transgenic cotton
Transgenic brinjal
Transgenic Approval Committee in India
Risk assessment of GM crops
Role of transgenics in crop improvement
Abiotic stress
Biotic stress
Role of transgenics in phytoremediation
Conclusion
References
In planta transformation: A smart way of crop improvement
Introduction
Methods of plant transformation
Non-biological transformation methods
Biological transformation method
Tissue culture-based transformation
In planta transformation
In planta transformation: a general scenario
Methods for in planta transformation
Vacuum infiltration method
Floral dip method
Floral drop method
Embryo transformation
Rice transformation: in planta method
Importance of in planta transformation in crop improvement
Conclusion
References
Fiber crop, jute improvement by using genomics and genetic engineering
Introduction
Genomic studies of jute
Phylogenetic study
Cytological study
Molecular maps of jute
Genome sequencing of jute
Studies on genes and expressed sequence tags (EST) of jute
Genetic engineering of jute: An immediate necessity
Useful techniques for modification of the jute genome
Conventional breeding
Mutagenesis
RNAi technology
T-DNA transformation
CRISPR/Cas9
Genetic transformation of jute
Agronomic trait development
Insect-resistant (IR) jute
Fungus-resistant (FR) jute
Herbicide-tolerant (HT) jute
Jute improvement-Future possibilities
Exploring the unique qualities of wild jute
Better genetic transformation system for jute
Low lignin jute for industrial application
Development of multitrait transgenic jute
Commercialization of transgenic jute
References
Harnessing protein posttranslational modifications for plant improvement
Introduction
Protein posttranslational modifications and their roles in gene regulatory networks
Phosphorylation
Ubiquitination
SUMOylation
S-Nitrosylation
Lipid modification
N-Myristoylation
S-Acylation/S-palmitoylation
Prenylation
Methylation
Acetylation
Glycosylation
Modeling kinetics and improving cellular system efficiencies through gene editing
Conclusions
References
Index
Back Cover

Citation preview

Advancement in Crop Improvement Techniques

Advancement in Crop Improvement Techniques

Edited by

Narendra Tuteja International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi

Renu Tuteja International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi

Nishat Passricha Biotechnology Industry Research Assistance Council (BIRAC), New Delhi

Shabnam K. Saifi National Institute of Immunology, New Delhi

An imprint of Elsevier

Woodhead Publishing is an imprint of Elsevier The Officers’ Mess Business Centre, Royston Road, Duxford, CB22 4QH, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States The Boulevard, Langford Lane, Kidlington, OX5 1GB, United Kingdom © 2020 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library ISBN: 978-0-12-818581-0 (print) ISBN: 978-0-12-818582-7 (online) For information on all Woodhead publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Charlotte Cockle Acquisitions Editor: Nancy Maragioglio Editorial Project Manager: Kelsey Connors Production Project Manager: Anitha Sivaraj Cover Designer: Christian Bilbow Typeset by SPi Global, India

Dedication

Professor Satish C. Maheshwari (October 4, 1933–June 12, 2019)

Prof. Satish C. Maheshwari was an Indian botanist known for his contributions to the fields of plant physiology and plant molecular biology. He had his early education in Jaipur and Dhaka but later moved to Delhi, along with his father, Prof. Panchanan Maheshwari, FRS, in 1949. He studied at the St. Stephens College, New Delhi, and earned his M.Sc. in Botany and later completed his Ph.D. under Prof. B.M. Johri on the embryology of duckweeds. This work was published in Nature. He also worked at Yale University (with Arthur Galston), the California Institute of Technology (with James Bonner and Robert Bandurski), Oxford University (with Daphne Osborne), and Harvard University (with L. Bogorad). He was the founder of the Department of Plant Molecular Biology at Delhi University, South Campus. His research mainly focused on understanding the mechanism of flowering, cytokinins from pumpkin seeds, methods for making haploids and dihaploids, and the characterization of phytochrome in wheat. His work is documented in more than 200 publications. His honors and awards include the Shanti Swaroop Bhatnagar Prize from CSIR; the Goyal Prize; the J.C. Bose Medal; the Birbal Sahni Gold Medal of the Indian Botanical Society, which also elected him its president; the J.J. Chenoy Award from the Indian Society of Plant Physiology; the Homo Bhabha and Jawaharlal Nehru Fellowships; and a D.Sc. (Honoris Causa) from the University of Hyderabad. He was elected a Fellow of the Indian National Science Academy, Delhi; the Indian Academy of Sciences, Bangalore; and the National Academy of Sciences, Allahabad. This book is dedicated to the memory of Prof. Maheshwari as a token of our appreciation and respect for him and his achievements.

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Dedication

Dedicated to Ph.D. students and collaborators of Dr. Tuteja With proper guidance, freedom, and encouragement, students can make much better progress, as evidenced by all my students. Practicing science and publishing research are team sports, where the scientific team essentially plays a significant role in being productive and successful. Therefore, Prof. Narendra Tuteja dedicates this book to his excellent Ph.D. students: Pham Xuan Hoi from Vietnam (awarded 2001), Yuliang Wu from China (2002), Tran Quang Ngoc from Vietnam (2005), Ajay K. Vashisht (2005), Shilpi Mahajan (2005), Shikha Misra (2007), Dang Quang Hung from Vietnam (2009), Marjan M. Tajrishi from Iran (2011), Neha Vaid (2012), Dipesh K. Trivedi (2013), Deepak Bhardwaj (2014), Kamrul Huda from Bangladesh (2014), Sufara A. Banu from Bangladesh (2014), Vineet K. Srivastava (2015), Sandep Yadav (2016), Durga M. Swain (2017), Nishat Passricha (2017), Shabnam Saifi (2017), and Israt Ara from Bangladesh (2019). Prof. Tuteja also dedicates this book to his esteemed active collaborators, namely Renu Tuteja (ICGEB, New Delhi), Tuan Nghia Phan (VNU University of Science, Hanoi, Vietnam), Sarvajeet S. Gill (MDU, Rohtak), Zeba I. Seraj (University of Dhaka, Dhaka, Bangladesh), S.M. Shahinul Islam (University of Rajshahi, Rajshahi, Bangladesh), Anca Macovei (University of Pavia, Pavia, Italy), M.K. Misra (Lucknow University, Lucknow), Mohammad Wahid Ansari (Zakir Husain Delhi College, New Delhi), Ranjan K. Sahoo (Centurion University of Technology and Management, Bhubaneswar, Odisha), Maryam Sarwat (Amity University, Noida), Surender Khatodi (Amity University, Haryana), Gopaljee Jha (NIPGR, New Delhi), A.K. Johri (JNU, New Delhi), Mukul Das and Manoj Kumar (CSIR-IITR, Lucknow), Surendra C. Sabat (Institute of Life Sciences, Bhubaneswar, Odisha), N. Subramonian (Sugarcane Breeding Institute, Coimbatore, Tamil Nadu), Benoit Lecombe (Univ. Montpellier, CNRS, INRA, SupAgro, Montpellier, France), Udayakumar (GKVK, Bangalore), Pushpa Kharb (CCS Haryana Agricultural University, Hisar, Haryana), and E.V. Soniya (RGCB, Thiruvananthapuram, Kerala. Overall, the research work performed with the dedicated efforts of our active team of students, postdoctoral fellows, and collaborators led us to important success that indicates the great potential for improving crop production at normal and suboptimal conditions.

Contributors Numbers in parentheses indicate the pages on which the authors’ contributions begin.

Ruchi Agarrwal (263), Plant-Insect Interaction Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Rosalyn B. Angeles-Shim (209), Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, United States Alma Balestrazzi (77,89), Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, Pavia, Italy Jyotsna Bharti (159), Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Amita Bhattacharya (297), CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India Shashi Bhushan (297), CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India Sudip Biswas (23), Plant Biotechnology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh; Department of Soil and Crop Sciences, Texas A&M University, College Station, TX, United States

Sabrina M. Elias (1,23), Plant Biotechnology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka; School of Life Sciences, Independent University Bangladesh, Dhaka, Bangladesh Murugesh Eswaran (159), Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Ana Margarida Fortes (199), Universidade de Lisboa, Faculdade de Ci^encias de Lisboa, BioISI, Campo Grande, Lisboa, Portugal Chiara Forti (77,89), Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, Pavia, Italy Maraeva Gianella (89), Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, Pavia, Italy Ritu Gill (241), Centre for Biotechnology, MD University, Rohtak, Haryana, India Sarvajeet Singh Gill (233,241), Centre for Biotechnology, MD University, Rohtak, Haryana, India Carla Gualtieri (77), Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, Pavia, Italy Priyanka Gupta (101), Stress Physiology and Molecular Biology Laboratory, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India

Abhishek Bohra (129), Crop Improvement Division, ICAR-Indian Institute of Pulses Research (IIPR), Kanpur, India

Filippo Guzzon (89), Department of Environment and Earth Sciences, University of Pavia, Pavia, Italy; International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico

Amit Chawla (297), CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India

Umme Habiba (23), Plant Biotechnology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh

Sagar Chhabra (233), Department of Biotechnology, Invertis University, Bareilly, India Karabi Datta (363), Laboratory of Translational Research on Transgenic Crops, University of Calcutta, Kolkata, India

Taslima Haque (1), Plant Biotechnology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh; Department of Integrative Biology, University of Texas, Austin, TX, United States

Swapan K. Datta (363), Laboratory of Translational Research on Transgenic Crops, University of Calcutta, Kolkata, India

Mirza Hasanuzzaman (241), Department of Agronomy, Faculty of Agriculture, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh

xv

xvi

Contributors

Nurnabi A. Jewel (1), Plant Biotechnology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka; Department of Genetic engineering and Biotechnology, Shahjalal University of Science and Technology, Sylhet, Bangladesh Gopaljee Jha (141), Plant Microbe Interactions Laboratory, National Institute of Plant Genome Research, New Delhi, India Rintu Jha (129), Crop Improvement Division, ICARIndian Institute of Pulses Research (IIPR), Kanpur, India Rashmi Kaul (159), Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Tanushri Kaul (159), Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Pushpa Kharb (319,351), Department of Molecular Biology, Biotechnology and Bioinformatics, College of Basic Sciences and Humanities, CCS Haryana Agricultural University, Hisar, Haryana, India Ajay Kohli (209,385), Strategic Innovation Platform, International Rice Research Institute, Metro Manila, Philippines Amit Kumar (297), CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India Arvind Kumar (111), Rice Breeding Platform, International Rice Research Institute, Metro Manila, Philippines; IRRI South Asia Regional Centre (ISARC), Varanasi, Uttar Pradesh, India Pramod Kumar (45), National Institute of Plant Genome Research, New Delhi, India Sanjay Kumar (297), CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India

Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Jammu and Kashmir, India Vishnu Mishra (45), National Institute of Plant Genome Research, New Delhi, India Andrea Mondoni (89), Department of Environment and Earth Sciences, University of Pavia, Pavia, Italy Khaled Fathy Abdel Motelb (159), Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Suresh Nair (263), Plant-Insect Interaction Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Himani Negi (329), Plant Molecular Biology Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Ashima Nehra (241), Centre for Biotechnology, MD University, Rohtak, Haryana, India Ramsong C. Nongpiur (101), Stress Physiology and Molecular Biology Laboratory, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India Isaiah Catalino M. Pabuayon (209,385), Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, United States Andrea Pagano (77,89), Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, Pavia, Italy Ashwani Pareek (101), Stress Physiology and Molecular Biology Laboratory, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India Nishat Passricha (329,351), Plant Molecular Biology Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India

Punam Kundu (241), Centre for Biotechnology, MD University, Rohtak, Haryana, India

Diana Pimentel (199), Universidade de Lisboa, Faculdade de Ci^encias de Lisboa, BioISI, Campo Grande, Lisboa, Portugal

Anca Macovei (77,89), Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, Pavia, Italy

Arul T. Prakash (159), Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India

Shuvobrata Majumder (363), Laboratory of Translational Research on Transgenic Crops, University of Calcutta, Kolkata, India

Ram Prasad (233,241), Department of Botany, Mahatma Gandhi Central University, Motihari, Bihar, India; School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China

Alok Kumar Maurya (129), Crop Improvement Division, ICAR-Indian Institute of Pulses Research (IIPR), Kanpur, India Reyazul Rouf Mir (129), Division of Genetics and Plant Breeding, Sher-e-Kashmir University of Agricultural

Nitya Meenakshi Raman (159), Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India

Contributors xvii

Mamta Rani (141), Plant Microbe Interactions Laboratory, National Institute of Plant Genome Research, New Delhi, India Prosanta Saha (363), Laboratory of Translational Research on Transgenic Crops, University of Calcutta, Kolkata, India Shabnam K. Saifi (329,351), Plant Molecular Biology Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Nitika Sandhu (111), Rice Breeding Platform, International Rice Research Institute, Metro Manila, Philippines; Punjab Agricultural University, Ludhiana, Punjab, India Neelam S. Sangwan (275), CSIR-Central Institute of Medicinal and Aromatic Plants (CIMAP), Lucknow, UP; Department of Biochemistry, Central University of Haryana, Jant-Pali, Mahendergarh, Haryana, India Ananda K. Sarkar (45), National Institute of Plant Genome Research, New Delhi, India Shabari Sarkar Das (45), Department of Botany and Forestry, Vidyasagar University, Midnapore, West Bengal, India Zeba I. Seraj (1,23), Plant Biotechnology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh Mohammad Umer Sharif Shohan (23), Plant Biotechnology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh Krishan Kant Sharma (241), Department of Microbiology, MD University, Rohtak, Haryana, India Ram Kumar Sharma (297), CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India Pramod Kumar Singh (45,233), Department of Botany, Udai Pratap College, Varanasi, India Rakshita Singh (319), Department of Molecular Biology, Biotechnology and Bioinformatics, College of Basic Sciences and Humanities, CCS Haryana Agricultural University, Hisar, Haryana, India Sanatsujat Singh (297), CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India Sneh Lata Singla-Pareek (101), Plant Stress Biology, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India

Alok Krishna Sinha (67), National Institute of Plant Genome Research, New Delhi, India Sonia Khan Sony (159), Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Susana de Sousa Arau´jo (77,89), Institute of Chemical and Biological Technology Anto´nio Xavier, New University of Lisbon (ITQB-NOVA), Oeiras, Portugal Yashdeep Srivastava (275), CSIR-Central Institute of Medicinal and Aromatic Plants (CIMAP), Lucknow, UP, India Tabassum R. Sunfi (1), Plant Biotechnology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka; Department of Mathematics and Natural Sciences, BRAC University, Dhaka, Bangladesh Jennylyn L. Trinidad (209,385), Strategic Innovation Platform, International Rice Research Institute, Metro Manila, Philippines Narendra Tuteja (23,233,241,329,351), Plant Molecular Biology Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Renu Tuteja (351,329), Plant Molecular Biology Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Kriti Tyagi (141), Plant Microbe Interactions Laboratory, National Institute of Plant Genome Research, New Delhi, India Rajeev K. Varshney (129), International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana, India Neetu Verma (67), National Institute of Plant Genome Research, New Delhi, India Rachana Verma (159), Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India Ashish Warghat (297), CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India Sandeep Yadav (45), National Institute of Plant Genome Research, New Delhi, India Shailesh Yadav (111), Rice Breeding Platform, International Rice Research Institute, Metro Manila, Philippines

Editors’ biography Prof. Dr. Narendra Tuteja is an elected fellow of numerous national and international academies. He is currently a visiting scientist at the International Center for Genetic Engineering and Biotechnology (ICGEB), New Delhi. He is the former group leader at ICGEB and professor and Director at the Amity Institute of Microbial Technology, Noida. He has made significant contributions to crop improvement under adverse conditions through genetic engineering and microbial approaches, reporting the first helicase from plant and human cells and demonstrating new roles for the Ku autoantigen, nucleolin, and eIF4A as DNA helicases. Furthermore, he discovered novel functions of helicases, G-proteins, CBL-CIPK, forisome, and LecRLK in plant stress tolerance, and PLC and MAP-kinase as effectors for Gα and Gβ G-proteins. Tuteja also reported several high-salinity stress-tolerant genes from plants and fungi and developed salt- and drought-tolerant crops, including rice, groundnut, sugarcane, chili, pigeon pea, etc. He also developed a marker-free and reporter-free salt-tolerant GM rice crop. He has also made significant contributions in the fields of mango malformation and plant-microbe interactions. Total publications: >400; Books: >20; Citations >24,000; h-index: >63; i-10: >237. Dr. Renu Tuteja is senior scientist and group leader at ICGEB in New Delhi, India. She is well known for her work in the fields of plant molecular biology, parasite biology, and biochemistry. She has made significant contributions to understanding DNA and RNA metabolisms in plants, malaria parasites, and human systems. She reported the genome-wide analysis of helicases from plants and the malaria parasite, the translation initiation factor 4A as a dual helicase, and the function of RNA helicase in splicing. She unraveled the protein translocation and mRNA transport pathways. A double-strand break repair model has been proposed in many textbooks on the basis of her discovery of the Ku autoantigen as a DNA helicase. In collaboration with Dr. Narendra Tuteja, she has contributed significantly to crop improvement under normal and stress conditions. Total publications: >160; Books: >10; Citations >6255; h-index: >40; i-10: >109.

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Dr. Nishat Passricha is currently an independent Principle Investigator (PI) in the BIG-BIRAC project funded by the Department of Biotechnology, New Delhi. He has made significant contributions in understanding abiotic stress tolerance in plants at the molecular level, especially in deciphering the unique function of lectin receptorlike kinase (Lec-RLK) in salt stress tolerance, which helps improve crop productivity under suboptimal conditions. Passricha has also developed the in-planta rice transformation technique. After Passricha’s significant contributions in abiotic stress, Tuteja gave him this opportunity to cooperate in editing this book, Advancement of Techniques for Crop Improvement.

Dr. Shabnam K. Saifi is currently working at the National Institute of Immunology, New Delhi. She has made significant contributions in understanding the role of helicases in providing abiotic stress tolerance in plants. Together with Dr. Narendra Tuteja, she identified and characterized a new plant helicase, RuvB, which is an important member of the chromatin remodeling complex and helps the plant in both biotic and abiotic stress tolerance. The majority of her research work is focused on the advancement of techniques for crop improvement and the importance of helicases in plant stress tolerance. After Saifi’s significant contributions in abiotic stress, Dr. Tuteja gave her this opportunity to cooperate in editing this book, Advancement of Techniques for Crop Improvement.

Foreword Food crop production is essential for the well-being of humanity, but the frequently changing global environmental conditions pose a serious threat to crop production due to the unexpected occurrence of biotic and abiotic stress variables, which cause considerable crop loss and thus challenge global food security. Therefore, it is the responsibility of plant scientists to improve food crops to withstand adverse environmental conditions for significantly higher yields. Now, it is mandatory to increase crop production by 50% to feed the ever-increasing global population. “Smart” and/or “tough” crop varieties that can yield more under challenging conditions with fewer inputs will be the key to success to achieve food security. The advancement in crop improvement techniques with the use of scientific and technological tools such as molecular breeding, genetic engineering, gene editing, etc., will be pivotal in developing these smart and tough designer crops with exclusive properties to enhance the value addition in terms of food quality, nutritional status, fiber content, medicinal properties, and industrial uses. Dr. Narendra Tuteja and team did a commanding job to compile a comprehensive volume on the very important and challenging area, “Advancement of Crop Improvement Techniques.” The editors have nicely teamed the global subject experts to cover a variety of chapters on genetic engineering, genome editing (Crispr-Cas9), sequencing technologies, molecular markers and eQTL, micro-RNA, seed priming, microbial approaches, and proteometabolomic and metabolomic approaches for crop improvement under a variety of abiotic stress factors. I am really happy to see the exclusive vision article by Prof. M.S. Swaminathan, Founder, MSSRF, India, and Prof. Nina Fedoroff, Emeritus Evan Pugh Professor at Penn State University, United States, on global food security issues and concerns. The contributors of chapters reflect a diversity of expertise and this volume is a well-organized and forward-looking publication that will provide an excellent opportunity to academicians, plant scientists, postgraduate students, and Ph.D. scholars. I feel honored and privileged to have this opportunity to write a foreword to Dr. Tuteja’s book. The challenges of abiotic stress on crop productivity are visible and I heartily appreciate the contributing authors’ dedication to developing smart and/ or tough crop varieties that can yield more under challenging conditions with fewer inputs. Trilochan Mohapatra, Secretary (DARE) and Director General (ICAR) Krishi Bhavan, New Delhi, India

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Preface Because of the integration of powerful technologies along with new concepts and methods derived from the inclusion of molecular biology, plant biology, agriculture science, and bioinformatics, research on crop improvement is in the midst of a revolutionary change. Crop improvement is the oldest science, beginning about 10,000 years ago when our ancestors began cultivating crops. The first method developed for crop improvement was artificial selection, as humans selected those plants that only produce more beneficial traits such as seeds, fiber, and food. In the 19th century, George John Mendel performed a breeding experiment that laid the foundation for crop improvement. Several breeding techniques emerged in the 20th century, and one of the most spectacular successes was the development of hybrids. In the 1930s, hybrid corn was developed that quickly doubled corn yields. In the 1950s and 1960s, semidwarf wheat and rice varieties were developed, which became the basis of the Green Revolution. This revolution was due to the use of applied genetics (in agriculture, this is now called plant breeding), which was the first biological revolution. In 1983, the first successful transformation of a plant (tobacco) was reported, which opened a new door for crop evolution. Current crop improvement techniques will remain unable to feed the growing population after 2030, so it’s time to advance crop improvement techniques. We can do that through computer technology or next-generation techniques. This book, Advancement in Crop Improvement Techniques, features 25 chapters written by many global experts in the fields of plant biology and crop improvement. The chapters provide a state-of-the-art account of the information available on recent techniques in plant biotechnology for crop improvement and stress tolerance in the era of changing climatic conditions for sustainable development. This book covers the approaches used for crop improvement from ancient times to recent times. The chapters written by experts in their fields from six countries provide vast coverage of the areas, including the latest developments in crop improvement. The whole book is categorized into five different sections to make it more attractive for the audience. The sections are: Sections I: Views and Visions for Food Security; Section II: Various Agricultural Techniques for Crop Improvement; Section III: Genomic Approaches for Crop Improvement; Section IV: Genome Editing Approaches for Crop Improvement; and Section V: Molecular Approaches for Crop Improvement. The first section is exclusively designed and covers two commentaries from global leaders in plant sciences. Prof. M.S. Swaminathan discusses the prospects of “Harnessing Scientific Progress for Health and Food Security” and Prof. Nina Fedoroff covers “The GMO Wars.” Section I of the book will broaden the reader’s understanding of global food security and the status of genetically modified organisms. Section II has seven chapters dealing with various agricultural techniques for crop improvement. The readers will enjoy understanding microbial approaches for crop improvement; approaches to enhance the nutritional traits in crops; plant disease control strategies; seed designing to improve the crop yield; the improvement of the phytochemical traits of medicinal plants; the conservation of Himalayan plants; and drought tolerance. Section III of the book covers five chapters and deals with molecular approaches for crop improvement under harsh conditions. This section of the book allow readers to understand molecular tools for the improvement of the date palm; the combination of DNA markers and eQTL information for the introgression of multiple salt tolerance traits in rice; his kinases as tools for crop improvement; and genomic approaches for the improvement of rice and legumes under stress conditions. Section IV covers four chapters exclusively dealing with genome editing approaches for quality improvement and stress resilience. This section of the book will help readers understand the importance of Crispr-Cas9 for fruit quality improvement and stress resilience; the importance of genome editing approaches to improve seed quality; and the scope of transformation and genome editing for quantitative trait improvements in rice and fiber crops. The last and fifth section of the book covers eight chapters dealing with molecular approaches for crop improvement and stress resilience in crops of economic importance. Section V will allow readers to understand the recent advances in in planta transformation for crop improvement; the management of reactive oxygen species for abiotic stress tolerance; the involvement of transgenic approaches for crop improvement; micro-RNA mediated gene regulation for crop improvement; seed priming as a means of progress in crop improvement; understanding plant responses against abiotic stress with metabolomic approaches: and challenges, achievements, and the role of posttranslational modification for plant improvement.

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Most of the chapters also contain technical advancement and computational analysis, which will be very useful for Ph.D. students. The editors and contributing authors of this book make an excellent attempt to bring together a deep understanding of all the techniques from the primitive age to the next generation under a single cover for crop improvement. This will provide an update on our knowledge of crop improvement and stress resilience. Moreover, this book will lead to new discussions and efforts in using various tools to improve various crops. This volume is expected to attract students, scientists, academicians, and professionals from all over the world. We are highly thankful to Dr. Trilochan Mohapatra, Secretary and Director General, Indian Council of Agriculture Research, Govt. of India, New Delhi, for writing the foreword for this book. The editors are also thankful to Nancy Maragioglio, Sr. Acquiring Editor, and Laura Okidi, Editorial Project Manager, Elsevier. Also thanks to Dr. Sarvjeet Singh Gill for his valuable help in formatting and incorporating editorial changes in the manuscripts. Narendra Tuteja Renu Tuteja Nishat Passricha Shabnam K. Saifi

Views and visions

The GMO Wars Nina Fedoroff Emeritus Evan Pugh Professor, Penn State University, University Park, PA, United States

Public opinion versus scientific consensus. There are many issues on which the public’s views diverge markedly from those of scientists. Few contemporary issues are more important—and more controversial—than climate change, vaccination, and genetically modified organisms (GMOs). Among these, the greatest divergence between public opinion and scientific consensus exists for GMOs. According to the results of a recent PEW poll, only 37% of the public thinks GMO foods are safe, in stark contrast to almost 90% of a broad sample of scientists (Funk et al., 2015). Part of the reason for this wide disparity lies in the very abundance and low cost of our contemporary food supply. While the impact of climate warming is increasingly perceptible to everyone, as is the public health menace of declining immunization rates, we live in a time of cheap and plentiful food. It is difficult for citizens of the wealthy, developed world to view the consumption of foods with genetically modified (GM) ingredients as other than a personal choice, one often made based on hearsay about the negative impacts of GMOs. In the half-century following the development of the molecular methods and knowledge needed to modify the genetic composition of organisms in predictable ways, society has become ever more polarized on the subject of genetic modification, with pro-GMO and anti-GMO campaigners and organizations squaring off through demonstrations, publications, lectures, websites, social media, litigation, and legislation. These altercations—often dubbed the “GMO wars”—have reached career-destroying and even life-threatening proportions on occasion. Public opinion remains divided on the safety of GMOs (Funk and Kennedy, 2016; Lucht, 2015). Politicians everywhere have responded to public anti-GMO pressure by interfering with the adoption of GMOs in agriculture (Maixner, 2018; Paarlberg, 2009, 2014; San-Epifanio, 2017). Regulation. The abiding impact of societal polarization on GMOs has been the development and persistence of burdensome regulatory regimes in many countries, including the United States, targeted exclusively to organisms modified by modern molecular techniques (McHughen, 2007; McHughen and Smyth, 2008). Europe has erected virtually insurmountable barriers to the introduction of GMOs into agriculture, as have many African countries under European influence (Paarlberg, 2009; San-Epifanio, 2017). Today, it costs upward of $100 million to bring a single new GM crop to market. xxvii

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The result is that we have just a few GM crops (and no GM animals), almost all of which are widely grown commodity crops developed by biotech companies (McDougall, 2011). Do we need GMOs? It is becoming inescapable that the wide availability and use of modern molecular techniques in agriculture will be critical to maintaining our ability to produce the abundance of safe and nutritious food we now enjoy. The reasons are these. The human population explosion is not yet over and technology is increasing affluence worldwide. Hence, the demand for food, both in general and in resource-intensive animal proteins in particular, continues to grow. But the effects of climate warming are already exerting a negative impact on agriculturally productive land in many places. Some of our best agricultural land is coastal and either at risk of being submerged or already plagued by periodic crop-destroying inundations (Wennersten and Robbins, 2017). As well, agriculture-depressing weather extremes, be they drought, wind, or rain, are already widely manifest and expected to increase in severity as the climate continues to warm. Weather extremes in lands distant from each other have already conspired to drive up food prices globally (Werrell and Femia, 2013). Spiking food prices disproportionately impact poor people and engender social instability in poor countries. Indeed, the riots that sparked both the Arab Spring and the ongoing Syrian conflict have their roots in rising food prices and historic droughts (Lagi et al., 2011). Also, the adverse impacts of climate warming on agriculture are driving increasing numbers of African farmers off the land to join the tide of refugees flowing into Europe (Friedman, 2016; Wennersten and Robbins, 2017). Because the climate is warming at a historically unprecedented rate, it is outstripping the ability of conventional methods to increase agricultural yields (Ray et al., 2013). Capitalizing on the last century’s revolutionary expansion of knowledge about organismal biochemistry and genetics, molecular methods can vastly speed up the improvement of agricultural organisms. Humanity’s ability to meet the coming challenges to the global food supply will demand rapid, knowledge-based genetic interventions to adapt agricultural crops, animals, and microorganisms to new climate realities. Why does the outcome of the GMO wars matter? Public attitudes and belief systems are strong determinants of societal choices effected through political processes, be they democratic or autocratic. Public beliefs about GMOs are largely negative today everywhere in the world. Anti-GMO attitudes are, in some measure, an unanticipated consequence of the extraordinary scientific and technological advances that have revolutionized agriculture over the past two centuries. These have both increased productivity and made agriculture much less labor intensive. The result has been a deep demographic shift of people from farms to cities, where they have little notion of how food is produced. Also, the predominantly negative views of GMOs reflect the effectiveness of the fear-based tactics used by anti-GMO activists, motivated by their own individual and organizational objectives, often pecuniary. Psychological research into belief formation has revealed that beliefs are formed intuitively, often based on information (and misinformation) received from family and friends and derived from an individual’s underlying moral values, with little rational analysis or evaluation of factual information (Haidt, 2012; Shermer, 2011). As on issues such as climate change and vaccination that have important individual and societal implications, it is increasingly imperative to understand how to effectively encourage people to reevaluate their beliefs about GMOs in the light of factual information. Yet the results of many psychological studies reveal that the simple delivery of factual information is remarkably ineffective in changing beliefs based on misinformation, particularly if they were derived from an individual’s immediate social network or arrived at through moral reasoning (Chan et al., 2017; Dickinson et al., 2016; Lewandowsky and Oberauer, 2016). A common defense against countervailing information is confirmation bias, the tendency to assimilate only information that conforms to an individual’s prior beliefs (Ecker et al., 2014). Nonetheless, we know that public views on issues important to individuals and to society change over time. Smallpox vaccination was broadly resisted, even ridiculed, when it was first promulgated widely, yet two centuries later the global elimination of smallpox is viewed as a public health success story (World Health Organization, 1980; Riedel, 2005). Also, public opinion about smoking has gradually changed over time, largely due to government intervention in the advertising practices of tobacco companies, policies on the sale of cigarettes, and information about the deleterious health effects of smoking emanating from authoritative governmental sources, such as the US Surgeon General (Hoffman and Tan, 2015). Unfortunately, the US government has, to date, not been an effective proponent of modern molecular methods of genetic modification in agriculture. Early uncertainty on the part of scientists about unforeseen dangers of recombinant organisms led to the establishment, in 1976, of the Recombinant DNA Advisory Committee (RAC) within the National Institutes of Health (NIH) to advise the NIH director on the containment conditions under which recombinant DNA research should be carried out in US laboratories (Wivel, 2014). The early recommendations for containment conditions developed by RAC were quite restrictive, but were gradually relaxed as the new molecular recombinant DNA (rDNA) methods became extremely popular and experience with their use accumulated with no evidence of feared deleterious impacts (Fedoroff, 2017).

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In time, the broadening of research to include the modification of organisms for use outside laboratories attracted the attention of regulatory agencies. In response, the US President’s Office of Science and Technology Policy (OSTP) brought together representatives of the Food and Drug Administration (FDA), the US Department of Agriculture (USDA), and the Environmental Protection Agency (EPA) to develop a framework for the regulation of recombinant organisms, now widely known as GMOs (Fedoroff, 2017). Upon the framework’s release in 1986 (OSTP, 1986), the OSTP directed the relevant agencies to find existing statutes under which they could regulate GM organisms and endorsed the recommendations of scientists that GM organisms should be regulated based on their traits and on the environments into which they were to be introduced, not on the process through which they were developed (Kelman, 1987). But that is not what happened. The USDA and EPA did, indeed, find statutes under which they could plausibly regulate GMOs, ones that had been used to regulate plant pests and toxic chemicals. This immediately created an aura of danger around GM organisms. The FDA later took on the regulatory scrutiny of GM animals as “new animal drugs.” Making no effort to confine regulatory scrutiny to the small subset of new traits that might prove problematic to human or animal health or to the environment, the agencies developed complex evaluation protocols and applied them to all GMOs, irrespective of the trait, the organism, and the environment (McHughen, 2007; McHughen and Smyth, 2008). The resulting complexity and cost of the regulatory process have both inhibited innovation and perpetuated the public’s perception that GMOs are dangerous. Changing public perceptions about GMOs. Because beliefs influence both individual choices and government policy, our ability to realize the potential of GM technology for food security and environmental protection will require changing public perceptions about GMOs. Easier said than done. Because the regulatory regime for GMOs in the United States and elsewhere has not changed substantially in response to the many decades of uneventful integration of GM crops into agriculture, the suspicion lingers that there remains uncertainty about their safety. There are promising signs that the advent of genome-editing technologies will change the regulatory environment for plants and perhaps for microorganisms in agriculture in the United States. Early in 2018, the US Secretary of Agriculture announced that the USDA would not regulate genome-edited crop plants with traits that could have been derived by older, unregulated plant-breeding technologies (https://www.usda.gov/media/press-releases/2018/03/28/secretary-perdueissues-usda-statement-plant-breeding-innovation). Extending this approach, the USDA’s Biotechnology Regulatory Service is proposing to shift its focus from the methodology used in genetic modification to the traits introduced into plants and microorganisms, importantly confining all regulatory scrutiny to traits that affect organisms that fall under the jurisdiction of the Plant Protection Act (https:// www.agri-pulse.com/articles/11344-opinion-trait-based-regulation-of-gm-plants-is-on-the-horizon-at-last). The very designation by the USDA of the new methods as “plant-breeding innovations” is a move toward recognizing that molecular approaches are simply the next step in the more than 10,000-year history of plant improvement in agriculture. Also, the US Congress has appropriated resources for regulatory agencies to engage in public educational efforts about the nature and benefits of biotechnology and genetic modification (https://www.fda.gov/Food/ResourcesForYou/ Consumers/ucm579348.htm). While the resources are modest, their investment in research may help to identify more effective approaches to countering misinformation, an increasing problem in the era of Twitter, Facebook, and YouTube. Several broadly influential science commentators, websites, and films are now providing a more fact-based representation of GMOs on the Internet. A 2017 documentary film titled “Food Evolution” (https://www.youtube.com/watch? v¼9nc6Q94WTnw&t¼3311s) has emerged as influential, in part through the efforts of its producer, Scott Kennedy, and his collaborators at Black Valley Films to bring the film to a wide audience. The film provides insights into the societal controversies surrounding GMOs as well as into the scientific advances, giving voice to both adamantly anti-GMO crusaders and pro-GMO scientists, with poignant glimpses of the benefits still just out of reach of poor farmers. Two of the most popular American contemporary science commentators, Neil deGrasse Tyson (https://en.wikipedia.org/wiki/Neil_ deGrasse_Tyson) and Bill Nye, aka The Science Guy (https://en.wikipedia.org/wiki/Bill_Nye_the_Science_Guy), are increasingly vocal about the benefits of GMOs. Educational outreach programs, such as the Cornell Alliance for Science (https://allianceforscience.cornell.edu/about/ funders/), funded by foundations and the USDA, seeks to provide accurate information about GMOs as well as train and network professionals. GMO Answers is another site that provides substantive information about GMOs, although its funding by major biotechnology firms has in some measure undermined its claim to objectivity (https://gmoanswers. com). The Genetic Literacy Project is a foundation- and donation-supported site that offers both substantive articles about a broad range of biotechnology issues and educational materials (https://geneticliteracyproject.org). Also, the Academics Review website, whose stated objective is to test “popular claims against peer-reviewed science,” provides detailed analyses of false claims rampant in anti-GMO films, books, and other publications (http://academicsreview.org).

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Because the authoritative voice of the US government is still lacking and may never become a positive force contributing to the wider acceptance of GMOs in agriculture, it is imperative that individual scientists with knowledge of molecular techniques increase their participation in the public dialog. Scientists can contribute to changing public perception of GMOs both indirectly through research on communication strategies and directly through increased dialogue with both the public and with governmental decision makers. Despite the difficulty of countering the kinds of negative beliefs fostered by false information, it is farmers and scientists who have success stories to tell—and they must tell them—in person, through films and social media as well as through special venues with wide reach, such as TED talks. To end on a hopeful note, research shows that those who know the most about GMOs are also the most positive about them (https://psyarxiv.com/h5dpb/).

References Chan, M.-P.S., Jones, C.R., Hall Jamieson, K., Albarracı´n, D., 2017. Debunking: a meta-analysis of the psychological efficacy of messages countering misinformation. Psychol. Sci. 28, 1531–1546. Dickinson, J.L., McLeod, P., Bloomfield, R., Allred, S., 2016. Which moral foundations predict willingness to make lifestyle changes to avert climate change in the USA? PLoS One 11. Ecker, U.K., Swire, B., Lewandowsky, S., 2014. Correcting misinformation—a challenge for education and cognitive science. In: Rapp, D.N., Braasch, J.L.G. (Eds.), Processing Inaccurate Information: Theoretical and Applied Perspectives From Cognitive Science and the Educational Sciences. MIT Press, Cambridge, pp. 13–38. Fedoroff, N., 2017. From maize transposons to the GMO wars. In: Women in Sustainable Agriculture and Food Biotechnology. Springer, pp. 39–58. Friedman, T.L., 2016. Out of Africa. New York Times, New York. Funk, C., Kennedy, B., 2016. Public Opinion About Genetically Modified Foods and Trust in Scientists Connected With These Foods. Pew Research Center. Funk, C., Rainie, L., Page, D., 2015. Public and Scientists’ Views on Science and Society. Pew Research Center. Haidt, J., 2012. The Righteous Mind: Why Good People Are Divided by Politics and Religion. Pantheon, New York. Hoffman, S.J., Tan, C., 2015. Overview of systematic reviews on the health-related effects of government tobacco control policies. BMC Public Health 15, 744. Kelman, A., 1987. Introduction of Recombinant DNA-Engineered Organisms Into the Environment: Key Issues. National Academies. Lagi, M., Bertrand, K.Z., Bar-Yam, Y., 2011. The food crises and political instability in North Africa and the Middle East. SSRN. Lewandowsky, S., Oberauer, K., 2016. Motivated rejection of science. Curr. Dir. Psychol. Sci. 25, 217–222. Lucht, J.M., 2015. Public acceptance of plant biotechnology and GM crops. Viruses 7, 4254–4281. Maixner, E., 2018. GMO salmon swimming slowly to US market. In: Wyant, S. (Ed.), Agri-Pulse. McDougall, P., 2011. The Cost and Time Involved in the Discovery, Development and Authorisation of a New Plant Biotechnology Derived Trait. Crop Life International. McHughen, A., 2007. Fatal flaws in agbiotech regulatory policies. Nat. Biotechnol. 25, 725. McHughen, A., Smyth, S., 2008. US regulatory system for genetically modified [genetically modified organism (GMO), rDNA or transgenic] crop cultivars. Plant Biotechnol. J. 6, 2–12. OSTP, 1986. Coordinated framework for regulation of biotechnology. Fed. Regist. 51, 23–350. Paarlberg, R., 2009. Starved for Science: How Biotechnology Is Being Kept Out of Africa. Harvard University Press. Paarlberg, R., 2014. Consequences of the anti-GMO campaigns. In: Bread and Brain, Education and Poverty. Pontifical Academy of Sciences, Vatican. Ray, D.K., Mueller, N.D., West, P.C., Foley, J.A., 2013. Yield trends are insufficient to double global crop production by 2050. PLoS One 8. Riedel, S., 2005. Edward Jenner and the history of smallpox and vaccination. In: Baylor University Medical Center Proceedings. Taylor & Francis, pp. 21–25. San-Epifanio, L.E., 2017. Towards a New Regulatory Framework for GM Crops in the European Union: Scientific, Ethical, Social and Legal Issues and the Challenges Ahead. Wageningen Academic Publishers, Wageningen. Shermer, M., 2011. The Believing Brain: From Ghosts and Gods to Politics and Conspiracies—How We Construct Beliefs and Reinforce Them as Truths. Macmillan. Wennersten, J., Robbins, D., 2017. Rising Tides: Climate Refugees in the Twenty-First Century. Indiana University Press. Werrell, C.E., Femia, F., 2013. The Arab Spring and Climate Change: A Climate and Security Correlations Series. Center for American Progress, Washington, DC. Wivel, N.A., 2014. Historical perspectives pertaining to the NIH recombinant DNA advisory committee. Hum. Gene Ther. 25, 19–24. World Health Organization, 1980. The Global Eradication of Smallpox. Final Report of the Global Commission for the Certification of Smallpox Eradication. WHO, Geneva, Switzerland.

Views and visions

Harnessing scientific progress for health and food security Prof. M.S. Swaminathan Founder Chairman of the M.S. Swaminathan Research Foundation (MSSRF), Chennai, India; Agriculture scientist who played a key role in India’s green revolution.

Progress in science is today taking place at a fast pace, particularly in the genetic and medical fields. Investment in new discoveries of both knowledge and technologies will happen all the time if there is enough public and private sector concern. For example, the birth of genetics has been followed by a number of developments such as polyploidy, mutation, recombinant DNA (GMOs), and currently gene editing through CRISPR (Clustered Regulatory Interspaced Short Palindromic Repeats). Obviously, science progresses at a rapid rate. We should ensure that our regulatory mechanisms to assess risks and benefits also make corresponding progress. For example, stem-cell therapy has raised many concerns, both about opportunities and risks. There is now very active research on understanding how to grow plants in space, including the moon. This will make a large difference in agriculture. There is also concern about the health risks of a lack of agreement in Brexit. The science of gene editing is making very rapid progress. The late Sir T.S. Venkatraman once told me that man is becoming Brahma or the God of Creation. He further mentioned that this power imposes a heavy responsibility with reference to the ethical aspects of experimentation. It is therefore not surprising that scientists were shocked when the Chinese scientist He Jiankui announced about 3 months ago that he has created the world’s first genome-edited babies. This emphasizes the urgency of having well-defined rules for measuring risks and benefits in relation to new technology. I would suggest that the Indian Council of Agricultural Research (ICAR), the Council of Scientific and Industrial Research (CSIR), and the Indian Council of Medical Research (ICMR) should take the lead in developing guidelines for assessing the ethics of such work. What is now important is the development of regulatory mechanisms that can help to promote benefits and avoid risks. There is a detailed article in Science (25th January 2019) on the evidence given by David Egilman with reference to public health and corrupting science. There are many other examples for emphasizing the need for integrating ethical considerations into medical research involving new technologies. I hope the World Health Organization can lead in this matter. In agriculture, there is yet no effective regulatory mechanism, with the result that controversies on risks and benefits continue. We need consensus on public policies designed to promote the public good, as pointed out by Margaret Hamburg in a recent article in Science that stated, “There are many things that serve to divide us. Science should not be among them.” xxv

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If regulatory systems that are acceptable to professionals as well as political leaders exist, many recent scientific advances can be capitalized for dealing with chronic health problems. For example, capsules that internally inject insulin and other medicines could do away with daily injections. Generally, it takes years to complete safety and efficacy studies for any new technology. Therefore, there should be well-equipped and competent institutions that can undertake this job. We should also ensure that all genetic variability relevant to health and food security is conserved. For example, climate change will seriously affect the yield of crops such as wheat, rice, and potatoes. Breeders in Peru have now achieved a breakthrough in potatoes to help farmers facing an uncertain future. Jawaharlal Nehru used to mention that the “Future belongs to science and to those who make friendship with science.” Changes in temperature, precipitation, and sea level will provide new challenges to scientists. The more recent estimation of the impact of climate change indicates that a rise in the mean temperature of 1.5ºC may be unavoidable. This will involve the loss of 4–5 million tons of wheat every year. The challenge now is getting timely advice to farmers and consumers on what needs to be done when there are changes in temperature and precipitation. The M.S. Swaminathan Research Foundation (MSSRF) established for this purpose the Village Knowledge Centres (VKCs), beginning with Puducherry, to convey timely information on not only likely climate impacts, but also on methods to overcome the problem of unfavorable changes in climate. This is where new technologies are helpful. Currently, our Indian Prime Minster (Narendra Modi) has placed considerable emphasis on the use of digital technology in village professions. Also, ending the digital divide helps to minimize the gender divide because women are not only able to master new information technology, but also relate it to daily life. The next 10 years will mark significant changes in technologies particularly relevant to agriculture, medicine, and health. It is important therefore that agriculture, nutrition, and health are considered in an integrated manner. Studies have been initiated at MSSRF on methods of integrating nutrition and health with reference to tuberculosis and leprosy. In both these cases, in spite of the best efforts of government, the diseases persist. By linking nutrition and health, some of these chronic diseases can be controlled more effectively.

Chapter 1

Combination of DNA markers and eQTL information for introgression of multiple salt-tolerance traits in rice Zeba I. Seraja, Sabrina M. Eliasa,b, Taslima Haquea,c, Nurnabi A. Jewela,d and Tabassum R. Sunfia,e a

Plant Biotechnology Laboratory, Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, Bangladesh,

b

School of Life Sciences, Independent University Bangladesh, Dhaka, Bangladesh, c Department of Integrative Biology, University of Texas, Austin,

TX, United States, d Department of Genetic engineering and Biotechnology, Shahjalal University of Science and Technology, Sylhet, Bangladesh, e

Department of Mathematics and Natural Sciences, BRAC University, Dhaka, Bangladesh

1 Introduction Cereal crops are mostly glycophytes that cannot withstand salinity stress, although they might vary in their tolerance level. On the other hand, halophytes utilize high salt conditions for their benefit and can grow in soil with substantial amounts of salt. In the prevailing climate change conditions, sea level rise due to increased thermal expansion has resulted in the intrusion of salt into agricultural lands adjacent to coastal areas. Therefore, food shortages, particularly for vulnerable farmers living in coastal areas, is inevitable. Despite being a glycophyte, rice (Oryza sativa) has cultivars within that have adapted to the saline soils of coastal areas, but produce very low yields. Since these cultivars can survive salt stress and even produce some grains, they have the potential to be donors of salt-tolerance traits in breeding approaches for producing salttolerant and high-yielding rice in combination with commercial cultivars. So, several strategies are being adopted to develop salt-tolerant cereals with high yields as well as other economically important crops. Two main strategies that are being utilized are marker-assisted selection (MAS) followed by backcross breeding (MABC) and transgenic approaches by overexpressing a desired gene, which is usually regulatory in nature (Wilson et al., 2005). Markers are like a flag in the genome that helps locate certain regions that are inherited from the parents to the progenies. This linked inheritance is due to the markers and the region of interest (ROI) being so close together with respect to their position in the genome, that meiotic recombination between them does not occur during generation advancement. Where conventional breeding often takes about 10–15 years to select the best plants for releasing a stable new variety, MAS-based precision breeding needs less than half that time by tracking and selecting plants with the desired loci by using linked markers. Advancement in sequencing technologies has led to a sufficiently large repertoire of SNP markers to allow accurate quantitative trait loci (QTL) identification and introgression for precision breeding. Large-scale sequencing of important crops and their natural variants have also provided enough SNP sequence information to conduct genome-wide association mapping. Any identified associations between the SNPs and tolerance phenotypes can be validated by QTL mapping and then incorporated into fine-tuned breeding programs. Genome sequences and improved bioinformatics may also enable cross-matching of target sequences with known QTLs in association mapping programs. Another strategy referred to as marker-assisted backcrossing (MABC) ensures that the background parental high-yielding quality is preserved in addition to the desired trait from the donor. Consumer nonpreference and nonacceptance of food from genetically modified plants containing single transgenes and the polygenic nature of salinity tolerance traits have shifted the focus from the former toward QTL mapping, QTL cloning, and MAS. Markers can be designed for multiple QTLs as well. The full complement of genes that are differentially regulated can be captured by technologies such as microarray or RNAseq. With sequencing information available for major crops as well as their related genotypes, the specific loci responsible for salinity tolerance can be narrowed down. Adaptation of statistical models during recombinant inbred line (RIL) production and selection has allowed mapping using the F2:3 population without the need to wait for homozygous progenies to be produced. The integration of SNP genotyping information and expression variation by mapping expression QTLs (eQTL) as well as genome-wide association studies Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00001-2 © 2020 Elsevier Inc. All rights reserved.

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(GWAS) has added a deeper level of precision. The latter facilitates identification of specific and targeted regions in the genome. This in turn makes the practice of laborious and expensive fine mapping redundant. The goals of some of the emerging technologies are to combine the MAB and transgenic approaches to incorporate significant regions of the genome responsible for the desired traits and to pyramid genes to get high-yielding salt-tolerant varieties. A list of salt-tolerant varieties released in Bangladesh, India, and the Philippines has been provided by Ismail and Horie (2017). To date, about 32 salt-tolerant high-yielding rice varieties with good grain quality have been developed and released for farmers (Aala and Gregorio, 2019). These varieties were developed using conventional breeding tools and took 10–15 years for varietal release, where the salt-tolerant donors were mainly Pokkali or Nonabokra. Numerous studies have identified salinity-tolerant QTLs. Of those, Saltol (derived from Pokkali) and SKC1 (derived from Nona bokra) came into the limelight and later, SKC1 was found to be associated with shoot potassium concentration, controlled by OsHKT1;5, which resides in the Saltol region. A study of the genes in the Saltol region has identified clusters of genes involved in salinity tolerance (Walia et al., 2005; Nutan et al., 2017). Interestingly, breeding lines from Pokkali were also found to have the SKC1 locus and were reported to have high shoot potassium and low Na+/K+ ratios (Thomson et al., 2010). They also reported that a high level of salt tolerance could only be achieved with multiple QTLs. More divergent salt-tolerance donors with wider genetic bases therefore need to be identified for more efficient MAS-based breeding programs. Due to the lack of precision breeding, the varieties already released show low to moderate tolerance and some of them possess undesired traits such as shattering, long awn, poor grain quality, etc. Pyramiding multiple QTL loci from multiple developmental stages along with information on the underlying phenotype and the gene expression pattern upon which it is based or eQTLs can narrow down specific regions for precise selection and introgression of multiple salt-tolerance traits in a highyielding background.

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DNA markers for rice breeding

2.1 SSR markers Microsatellites or simple sequence repeats (SSR) are the preferred molecular markers due to their technical efficiency, high polymorphic rate, and potential for multiplexing. These are second-generation markers widely used in MAS due to their easy availability and low cost because all major crop species have already been sequenced and the information is readily available in accessible databases. In addition, due to their high polymorphic nature, they can be used in studying closely related genotypes. SSR markers are codominant as well as multiallelic and have been reliably used to analyze both indica and japonica germplasms as well as other Oryza species of the AA genome. This has resulted in greater accuracy due to the integration of results from different studies. The international rice microsatellite initiative (IRMI) was formed to increase the density and utility of the SSR map in rice. In 2001, about 6655 sequences were released that consisted of perfect repeat motifs (
24 bp in length) flanked by 100 bp of a unique sequence on either side of the SSR (Temnykh et al., 2000; McCouch et al., 2002). A second source of SSR-containing nucleotides is genomic DNA sequences released by the IRGSP (IRGSP, 2005). Experiments for determining QTLs for salt tolerance in rice were conducted using AFLP, RFLP, and microsatellite markers in different populations. In breeding for salt-tolerant rice, SSRs were used to map QTLs for tolerance and a major QTL named Saltol was mapped on chromosome 1 using F8 RILs of Pokkali/IR29 cross (Gregorio, 1997). A follow-up study mapped the position of Saltol between RM23 and RM140 (10.7–12.2 Mb on Chromosome 1) and confirmed the effect of the shoot Na+-K+ ratio using 54 RILs (Bonilla et al., 2002). Haq et al. (2010) identified a QTL for the Na+-K+ ratio between 11.1–14.6 Mb on chromosome 1 from a japonica rice Moroberekan, indicating the occurrence of the Saltol region in both indica and japonica rice. Additional SSR markers for the Saltol QTL were reported by Thomson et al. (2010) from the original RIL population. However, both Thomson et al. (2010) and Alam et al. (2011) showed that specific QTLs in different chromosomes, along with Saltol, were responsible for a higher level of salt tolerance. SSRs of chromosome 1 for salt tolerance were extensively studied and many groups individually identified markers in different populations. Mohammadi-Nejad et al. (2008) studied the impact of chromosome 1 for tolerance to salinity at the seedling stage in rice, where they found 18 different haplotypes based on the Saltol QTL. The haplotypes possessing RM8094 and RM10745 markers were found to discriminate the tolerant genotype and therefore are useful for the MAS of the Saltol QTL. In another study, Davla et al. (2013) characterized rice genotypes for salt tolerance with 39 SSR and a total of 185 alleles were detected; 16 of these SSRs were found in the Saltol region. The tolerant cultivar Nona bokra was mapped as having the SKC1 allele near the Saltol region and was found to preserve K+ ion homeostasis under salinity stress (Ren et al., 2005; Das et al., 2015). Therefore, the markers RM8094, RM140, RM10745, and RM10772 used for the Saltol region were common with the SKC1 locus (Das and Rao, 2015). Krishnamurthy et al. (2016) analyzed genomic region spanning Saltol

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using SSR markers in rice genotypes showing differential seedling stage salt tolerance. They found RM3412 as a diagnostic of salinity tolerance and associated with salinity tolerance at the seedling stage. They also found it closely linked to the SKC1 gene, even though the latter is associated with K+ homeostasis. Eight polymorphic SSR markers (RM10793, RM10748, RM3412, RM493, RM19852, RM10713, RM10871, and RM10843) showed different combinations of alleles (haplotypes) in 94 rice genotypes and covered a 3.3-Mb region of the Saltol locus. Their study also demonstrated that many tolerant varieties such as CSR31, 38, etc., could not be identified as tolerant based on RM3412, which suggested that QTLs other than Saltol might be controlling their salinity tolerance. Most of the reported studies emphasized SSR markers from the Saltol region. However, Lisa et al. (2004) studied the genome-wide diversity analysis of coastal region landraces using 60 SSRs and could group six potential salt-tolerant donors along with tolerant Pokkali, Capsule, etc. This was a simple but informative study to search for diverse salt-tolerance donors in breeding programs. In another SSR diversity study, Yesmin et al. (2014) identified SSR markers as unique identifiers for some salt-tolerant landraces. To be specific, these were RM3412, RM7075, RM28746 for Pokkali; RM27933 for Binnatoa, Ranisalute, and Capsule; RM101 for Boilam; RM28746 for Pokkali and Shakkarkhar 1605; and RM180 for Horkuch. In another study, Horkuch and its cross-breeding population with IR29 was studied with SSR markers (Razzaque et al., 2016) and associated with salt tolerance and yield QTLs (Noor et al., 2019). The RM25789 of chromosome 10 was found to be associated with SES QTL, and RM26974 and RM27027 of chromosome 11 were found to be associated with yield-related QTL clusters. SSR markers in protein coding and microRNA genic regions were also studied (Mondal and Ganie, 2014). These scientists mined SSR markers from 130 members of salt-responsive miRNA genes of rice and validated these among contrasting panels of tolerant and sensitive genotypes. They found 12 miR-SSRs to be polymorphic but only miR1726 SSR was reported to differentiate the tolerant and sensitive genotypes into two different groups. Molla et al. (2015) selected 220 different salt-responsive genes of rice. Some 106 genes out of these were found to contain 180 microsatellite loci. Maximum loci were found in the coding sequence (37.2%) followed by 50 UTR (26%), intron (21.6%), and 30 UTR (15%). These studies show the importance of the salt-responsive candidate gene-based SSR (cgSSR) markers for utilization as candidates for diversity analysis among rice genotypes differing in salinity response. Due to their reproducibility, despite this era being that of third-generation markers, SSRs still are the marker of choice in many evaluation studies.

2.2 SNP markers SNP or single nucleotide polymorphism refers to alterations in a single nucleotide in the genome, which are found in the coding and mostly noncoding regions. The advantage of using SNPs as genetic markers is their abundance in the genome. SNPs are biallelic in nature and less polymorphic compared to SSR but due to their abundance, ubiquity, and highthroughput applicability, this marker is currently the most popular choice in breeding studies. SNPs allow the assessment of a range of diverse alleles in a germplasm and can help monitor which allele combinations result in better performance. SNP markers can identify favorable recombinants that break any possible linkage drag. They can be used to pyramid useful alleles and identify positive transgressive-variation in backcrossed populations. Prior to the invention of next-generation sequencing (NGS) technologies, SNPs were discovered by mining EST databases or resequencing gene amplicons using Sanger sequencing. These primarily allowed the detection of gene-based SNPs and those from intergenic, intron, or regulatory regions were left out (even though the latter are more abundant). SNPs were also not being used extensively in breeding programs due to the difficulty in their detection. Allele-specific PCR or restriction enzyme-based systems such as cleaved amplified polymorphic sequence (CAPS) were mainly being used. Resequencing of diverse germplasms made SNP identification much easier where the specific cultivar is purified through one or two generations of inbreeding (via single seed descent) followed by high-quality DNA extraction and sequencing by a second- or third-generation platform. At first, 1.7 million SNPs were identified by comparing the japonica rice Nipponbare and the indica rice 9311 genome (Shen et al., 2004) and a set of 384,431 high-quality SNPs (Feltus et al., 2004). Affymetrix’s custom designed 44K and 1M SNP genotyping array and Illumina’s custom designed SNP oligonucleotide pool assays (OPAs) were the most commonly used SNP detection platforms. A novel technology called Golden Gate Technology was adopted, which is based on allele-specific extension and ligation and can genotype 1536 SNPs on 96 samples in its original format. The 1536 array was designed by detecting polymorphism within and between five major subpopulations of O. sativa (Zhao et al., 2010). Another low-resolution 384 SNP assay was very reliable in detecting SNPs (Thomson, 2014). These diversity data with both high and low resolution SNP detection platforms are of high quality and will retain their value by complementation with newer and more advanced sequencing-based technologies. Genome-wide SNP discovery is facilitated by genome complexity reduction techniques coupled with NGS. Earlier, high Cot selection, methylation filtering, and microarray-based genomic selections (GSs) were used that lacked the power

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to eliminate duplicated sequences and cases of false discovery. The latest methods such as complexity reduction of polymorphic sequence (CRoPS) and restriction site associated DNA (RAD) are computationally robust and also can filter out duplicated SNPs. With the current advancements in technology, whole genome sequencing is not a big challenge. Nevertheless, sequencing each and every individual’s whole genome is expensive and often unnecessary. A more logical and easier solution is to reduce the genome complexity and sequence it to identify genetic polymorphism through markers. Reduction of genome complexity can be performed using restriction enzymes to cut the genomic DNA in specific positions and sequencing from the ends that are generated, as in both RADseq and CRoPS (Scheben et al., 2017). In recent studies, the physical shearing of DNA is eliminated and it is digested with two restriction enzymes for strict size selection. This procedure is termed double RAD (Bruneaux et al., 2013) or double digest RAD or ddRAD (Peterson et al., 2012). The restriction site associated DNA (RAD) method typically consists of restriction enzyme digestion, first adapter ligation, shearing, end repair, second adapter ligation, and size selection (Pukk et al., 2015). After digestion, fragments are increased in number by PCR (polymerase chain reaction), multiple samples are pooled using different adaptors from different samples, and finally sequences are generated using next-generation technology. In the ddRAD method, one rare cutter and one frequent cutter restriction enzyme are used while RADseq uses only one cutter. These approaches can be referred to as a one-step procedure of SNP discovery and genotyping and constitute a rapid, high-throughput, and costeffective tool for a genome-wide analysis of genetic diversity, especially for nonmodel species and germplasm sets. Among the many processes that have been advanced to cut down genome complexity, the DArTseq or diversity arrays technology-based sequencing method has brought significant improvement via intelligent selection of the genome fraction to correspond mainly with polymorphic regions associated with gene-rich regions. Selection is achieved by using a combination of restriction enzymes that separates low copy sequences (most informative for marker discovery and typing) from the repetitive fraction of the genome. DArT was implemented initially on the microarray platform, which involved fluorescent labeling of representations and hybridization to dedicated DArT arrays. DArT offers an inexpensive and highthroughput whole-genome genotyping technique, as initially shown for rice ( Jaccoud et al., 2001). Classic DArT markers have been substituted by DArTseq markers based on genotyping by sequencing (GBS). DArTseq for a new organism starts with the optimization of complexity reduction using a combination of restriction enzymes. This is advantageous over the array version when high marker densities (tens of thousands of markers) are required. DArTseq and SNP markers based on GBS technology have been successfully applied for linkage mapping, QTL identification in a biparental mapping population, genome-wide association studies (GWAS), genetic diversity studies in wheat (Akbari et al., 2006; Baloch et al., 2017) and many other crops (Grzebelus, 2015), and for marker-assisted and GS.

2.3 Fluorescent markers The development of SNP markers generally consists of two parts: SNP discovery and SNP validation. For SNP validation, fluorescence-based techniques are preferable due to their ease of detection. Contemporary genotyping assays and platforms differ from each other in chemistry, cost, and throughput of samples as well as the number of SNPs that need to be validated.

2.3.1 Illumina’s BeadArray platform Illumina’s BeadArray platform (Fan et al., 2006) is capable of validating a large number of SNPs in parallel by combining several technologies. The basis of this technology is a multicore optical “imaging” fiber, which has micron-sized etched wells on its tip in which appropriate beads can fit. Various oligonucleotide sequences are attached to each bead, and thousands of beads can be self-assembled on the fiber bundle. Successive decoding processes can then determine which bead occupies which well. Complementary oligonucleotides present in test samples bind to the beads. Finally, bound oligonucleotides are measured by fluorescent labels.

2.3.2 Taqman The TaqMan method was first reported by Karry Mullis in 1991 at Cetus Corporation (Holland et al., 1991). This assay involves the use of 50 –30 exonuclease activity of Taq polymerase to cleave a dual-labeled probe during hybridization to a complementary target sequence and uses a fluorophore-based detection system (Shi et al., 2006). This assay has already been used worldwide for SNP genotyping and is performed concurrently with a PCR reaction where the results can be read in real time as the PCR reaction proceeds (McGuigan and Ralston, 2002).

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2.3.2.1 TaqMan principle for SNP detection The TaqMan assay requires two PCR primers (one forward and one reverse) that will amplify a region containing the SNP polymorphic site. Allelic discrimination is achieved by the use of one or two allele-specific probes combined with FRET (fluorescence resonance energy transfer) where the probes will bind to the SNP polymorphic site. TaqMan probes consist of a fluorophore at the 50 end of the oligonucleotide probe and a quencher at the 30 end (Klein, 2002). Different fluorophores (such as 6-carboxyfluorescein, acronym: FAM, or tetrachlorofluorescein, acronym: TET) and quenchers (such as tetramethylrhodamine, acronym: TAMRA) are available (Kutyavin et al., 2000). The quencher remains in close proximity to the fluorophore when the probe is intact. During the PCR amplification step, if the allele-specific probe finds its perfect complement to the SNP allele, it will bind to the target DNA strand. However, it will get degraded by the 50 -nuclease activity of the Taq polymerase as the latter extends the DNA from the PCR primers and encounters the probe. The degradation of the probe results in the separation of the fluorophore from the quencher molecule and generates a detectable signal. If the allele-specific probe is not perfectly complementary, it will not bind as efficiently and be out of reach of the nuclease activity of the Taq polymerase (McGuigan et al., 2002) (Fig. 1).

Fluorophore

Quencher TaqMan probe

Forward PCR primer

Reverse PCR primer

Amplification assay

Polymerization

Probe displacement and cleavage Fluorescence

Result Fluorescence

PCR products Cleavage products FIG. 1 Principle of TaqMan assay.

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2.3.3 KASP technology: An efficient approach for breeding applications In addition to the above platforms, KASP (kompetitive (competitive) allele specific PCR) (http://www.lgcgroup.com) is widely used in SNP validation. This PCR-based technology involves fluorescence resonance energy transfer (FRET) for signal generation. 2.3.3.1 Chemistry of KASP technology A KASP genotyping assay uses a technique based on allele-specific oligo extension and FRET for signal generation. The fluorescent reporting system consists of four single-labeled oligonucleotides that hybridize to one another in free solution to form a fluorescent quenched pair that, upon introduction of complementary sequences, creates a measurable signal. Besides the sample, the DNA-KASP kit contains two more components, the assay mix (a mixture of three unlabeled primers that consists of two allele-specific oligos and one common reverse locus-specific oligo) and the reaction mix (the other components required for PCR, including the universal fluorescent reporting system and Taq polymerase) (Kumpatla et al., 2012). The two mixtures are assembled with the sample DNA in an appropriate ratio and then run in a real-time PCR machine with filters to detect the fluorophores. Within a few hours, the result can be generated and extracted for analysis. 2.3.3.2 Reaction mechanism In the first round of PCR, a KASP primer mix containing the two allele-specific forward primers and the single reverse primer is added to the mixture. The specific forward primers bind solely at the SNP of interest due to its specificity, allowing the DNA polymerase to complete the reaction with the rest of the complementary nucleotides. Meanwhile, the common reverse primer begins adding complementary nucleotides on the opposite strand of DNA. This ends the first round of PCR and then starts the next round (Semagn et al., 2014) (Fig. 2). In the second round of PCR, the complementary strand to the allele-specific forward primer is generated and the common reverse primer binds to the amplicon that is formed in the first round of PCR. Finally, the thermo cycling of the PCR reaction continues, causing the initiation of the third portion of the KASP method (Fig 2). A fluorescently labeled primer is present in the master mix that is quenched due to hybridization to a complement that contains a quencher. The fluorescent-labeled primer, when added to the PCR mix, now complements the tail sequence of the allele-specific forward primer, hybridizes with it, and allows elongation to occur. During this hybridization, it automatically separates from its complementary base and is no longer quenched. This occurs multiple times throughout the thermal cycle settings. The fluorescent signal becomes stronger as more fluorescent primers are used in the amplification process. FAM and HEX are normally used as fluorescent tags (Steele et al., 2018) (Fig. 3). 2.3.3.3 KASP as a better choice For many reasons, KASP genotyping technology is a suitable technology for SNP marker detection and validation. Some key features are: l

l

l

3

One of the most attractive features of KASP is that it is a cost-effective ($15 per assay) single-step genotyping technology that is cheaper than SSRs and can be adapted to high-throughput SNP marker validation technologies ($50 per assay) (Semagn et al., 2014). In the case of TaqMan, the cost is much higher as each allele-specific probe has to be custom-labeled with fluorescence. KASP is more flexible than genotyping by sequencing (GBS) or array-based genotyping when used in selection programs. Another advantageous aspect of KASP is that it can be performed in a short time. Results can be generated within 2–3 h and allele calls made immediately (Kumpatla et al., 2012).

Use of markers

3.1 Mapping, QTL information, and use Because DNA markers represent genetic differences between individuals and species, polymorphic markers can identify a specific individual/organism. Thus, the identification of polymorphic markers by genotyping and locating them on chromosomes in an orderly manner is the basis of genetic map construction. The various components of salinity tolerance are polygenically controlled, making it a quantitative trait. The locus responsible for these quantitative traits is termed QTL, and QTL detection or mapping is the association of plant phenotypes with their polymorphic marker genotypes (Collard et al., 2005). QTL mapping requires a mapping population where the genes are inherited and segregated in

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FIG. 2 Three rounds of PCR reaction in KASP.

different combinations from their parents. Genetic polymorphism of the mapping population in the form of a genetic map or linkage map and subsequent QTL mapping can then define both genotyping and phenotypic polymorphism among the parents by correlation.

3.1.1 Mapping population A mapping population is a group of sibling progenies where the trait of interest actually shows a continuous distribution comprising extreme ends as well as intermediate characteristics. The first step is crossing two genetically divergent parents

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FIG. 3 In this figure, the blue and red dots represents two homo alleles and the green dots represent the hetero allele of SNP. The black one represents no template control. The clusters in the graph clearly species the detection of SNP alleles in sample DNA.

with clear differences for one or more traits of interest, but too much divergence leading to sterility and segregation distortion is also not desired. Progenies from the second filial generation (F2), backcross (BC), recombinant inbred lines (RIL), double haploids (DHs), and near isogenic lines (NIL) can be used for genetic mapping in self-pollinating species (Burr et al., 1988; Doerge, 2002). F2s are derived by selfing F1 hybrids originated by crossing two parents while the BC population is produced by crossing the F1 with one of the parents as the recipient. If selected progenies with the trait of interest are repeatedly backcrossed with the same recipient, 99% of the recurrent parent genome is recovered. These NILs are thus produced in 6–7 generations. RILs are developed by single-seed selections from individual plants of an F2 population; such selections continue for 6–8 generations (Babu et al., 2004). In the case of NILs, selfing of selected BC7F1 individuals produces BC7F2, which is homozygous for target genes, and nearly isogenic with the recipient parent (NILs). A DH population is produced by doubling the gametes of the F1 or F2 population followed by regeneration using tissue culture. The choice of mapping population affects the linkage analysis and size of the genetic map. RILs, NILs, and DHs are permanent populations and homozygous while F2 and BC2 are temporary. The size of the mapping population can exert an influence on the accuracy of the genetic maps (Ferreira et al., 2006). Sometimes in QTL studies, reciprocally crossed mapping populations are used that can show differences in the inheritance of maternally supplied growth factors, nutrients, and episomes such as mitochondrial DNA, uniparental epigenetic marks, and the inheritance of sex chromosomes.

3.1.2 Linkage mapping A segregating population contains a mixture of parental and recombinant genotypes. The frequency of these recombinant genotypes can be used to calculate recombination fractions and ultimately to predict the genetic distance between the markers. Mapping functions are used to convert recombination fractions into map units called centimorgans (cM). So, the linkage map basically indicates the position of the polymorphic markers in the genome available from the genotyping assay. Linkage between markers is usually calculated using odds ratios, that is, the ratio of linkage versus no linkage, and expressed as a logarithm value (LOD). A LOD (logarithm of odd) value of 3 between two markers indicates that the linkage is 1000 times more likely than no linkage (Collard et al., 2005). Mapping functions are required to convert recombination fractions into cM as the recombination frequency and the frequency of crossing over are not linearly related (Hartl, 2001). The most commonly used mapping functions are the kosambi (assumes recombination events influence the occurrence of adjacent recombination events) and the Haldane (assumes no interference between crossover events) (Hartl, 2001). The distance in a linkage map is also not directly related to a physical distance between genetic markers. It depends on the genotype, plant genome size, and recombination hotspots and cold spots. The commonly used software programs are Mapmaker, MapManager, Joinmap, R/QTL, etc. Linked markers cluster together to make linkage groups representing chromosomal segments.

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3.1.3 QTL detection The closer a marker is from a QTL, the lower the chance of recombination between the marker and QTL. Three widely used methods for detecting QTLs are single-marker analysis, simple interval mapping, and composite interval mapping (Tanksley, 1993; Lin et al., 1998; Liu, 2017). Single-marker analysis (also single-point analyses) is the simplest method for detecting QTLs associated with single markers. For single marker analysis, normally t-tests, analysis of variance (ANOVA), and linear regression are used. The coefficient of determination (R2) from the marker explains the phenotypic variation arising from the QTL in linear regression. However, a major disadvantage of this method is the further a QTL is from a marker, the less likely its detection. This is because recombination may occur between the marker and the QTL. This causes the magnitude of the effect of a QTL to be underestimated (Tanksley, 1993). The use of a large number of segregating DNA markers covering the entire genome (usually at intervals less than 15 cM) may minimize both problems (Tanksley, 1993). In this context, composite interval mapping (CIM) is statistically much more powerful as it combines interval mapping with linear regression and includes additional genetic markers in the model ( Jansen, 1993).

3.1.4 Identified QTLs Several salt tolerance-related quantitative trait loci (QTLs) associated with parameters such as Na+ and K+ ion uptake, ionic concentration, and Na+/K+ ratio have been reported in rice (Koyama et al., 2001; Lin et al., 2004; Singh et al., 2007; Haq et al., 2010). These QTLs are detected repeatedly on chromosomes 1, 4, 6, and 7. None have been found on chromosomes 8 and 11 and very few on chromosomes 2, 3, 5, 9, 10, and 12 (Negra˜o et al., 2011). However, it should be noted that most of these studies have been conducted under hydroponic conditions and only one used field conditions (Takehisa et al., 2004). Salinity stress was shown to have a different impact in plants grown under hydroponic and soil systems. A segment of the short arm of chromosome 1 has been reported to have a number of QTLs. A major QTL Saltol has been identified from a cross of IR29/Pokkali on chromosome 1 in rice, associated with seedling-stage salt tolerance and Na+/K+ ratio, explaining 43%–70% of phenotypic variation (Gregorio, 1997; Bonilla et al., 2002). There are reports of introgression of this Saltol QTL into rice varieties such as BR11, BRRIdhan28, Q5DB, IR64, AS996, and PBI121 (Gregorio et al., 2013; Huyen et al., 2013; Hasan et al., 2015; Babu et al., 2017). However, because the advantage gained was mainly at the seedling stage, a considerable loss in grain yield under salt stress was observed. A 60 kb using a binary bacterial artificial chromosome system in rice (He et al., 2010). Common binary vectors in use have been described in detail by Komari and coworkers (Komari et al., 2006). Most cereals besides rice, including maize, wheat, barley, and sorghum, have been shown to be transformed by Agrobacterium-mediated methods (Hiei et al., 2014). While rice and maize Agrobacterium-mediated transformation have almost become routine, reports for the others are fewer. However, the low efficiency of transformation persists for many indica rice genotypes and the optimization of transformation and regeneration conditions remains time consuming. The common explant used for rice transformation is calli, raised from the scutella of mature embryos (Hiei et al., 1994). The efficiency of transformation can be increased further by the use of immature embryos (Hiei and Komari, 2008). The quality of the latter can, however, be highly variable depending on the growth conditions of the plant and the time of collections of the embryos (Hiei et al., 2014). Therefore, for routine transformation, calli from mature embryos are preferred. It has been reported that calli derived from suspension culture can be transformed more efficiently (Ozawa and Takaiwa, 2010). Silver nitrate has sometimes been used to prevent Agrobacterium-induced necrosis and callus browning during coculture with bacteria (Singh and Prasad, 2016). There are only limited reports of rice transformation using shoot apex or inflorescence (Hiei et al., 2014).

2.2 Biolistics The main advantage of the biolistic method of gene transformation is that it is genotype independent because it uses physical force to insert DNA into plant tissues, such as mature or immature embryos or callus tissue (Cho et al., 2004; Ismagul et al., 2018). Another tissue that has been commonly used for biolistic transformation is the apical meristem. The latter has been successfully used for genome editing in wheat (Hamada et al., 2018). The other advantage is that it is the only method that can be used to transform organelle DNA such as that of chloroplasts and mitochondria (Hanson et al., 2013; Montanari et al., 2015). DNA is precipitated on to gold or tungsten dust-like particles, which are then propelled by high speed using a gene gun or in a vacuum chamber where helium gas is used to propel and bombard the particles with such force as to penetrate the skin/cell walls. The Helios Gene Gun or the PDS-1000/He are reportedly the most used systems for gene gun or chamber delivery of DNA into tissues, respectively (Helenius et al., 2000; Sparks and Jones, 2014). One more advantage for biolistic delivery is that the gene of interest does not need to be cloned into a specialized transformation vector in order to be integrated into plant cells and subsequently inherited (Herrera-Estrella et al., 2004; Kikkert et al., 2004).

2.3 In planta methods In planta methods of transformation involve the use of actively growing parts of a plant, such as germinating seeds or inflorescences, for infection by Agrobacteria or bombardment by DNA. The use of germinating or imbibed seeds is

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not only more common, but also more efficient for rice, in the case where Agrobacterium-mediated transformation is used (Supartana et al., 2005; Lin et al., 2009; Ahmed et al., 2018). Even in the case of in planta biolistic transformation, bombarded apical meristems from imbibed mature seeds showed high efficiencies of transformation (Hamada et al., 2017). After the infection procedure or DNA delivery, the seeds are directly allowed to germinate and transferred to soil. Because the apical meristem of the germinating seeds is the targeted tissue for transformation, the flag leaves of the individual panicles are tested for the presence of the transgene. Seeds from only those panicles from the T0 plants, whose corresponding flag leaves show positive for a reporter gene or specific PCR product, are used for subsequent germination in the selective agent (Ahmed et al., 2018). The whole procedure thus avoids the use of any tissue culture or regeneration, which can be problematic in indica rice or other monocots that show genotype-dependent efficiency of transformation (Ahmed et al., 2018). For the Agrobacterium-mediated infection, the overnight soaked seeds are injected with the bacterial suspension in the area where the plumule or shoot would later appear, taking care to avoid injury to the apical meristem (Lin et al., 2009). Efficiencies of transformation have been shown to be enhanced by the use of vacuum infiltration (Lin et al., 2009) after infection or the use of acetosyringone (Ahmed et al., 2018). The authors have successfully used in planta Agrobacterium-mediated transformation for a number of recalcitrant Bangladeshi rice genotypes (Parvin et al., 2015; Faisal et al., 2017; Ahmed et al., 2018). Previously, we had to use tissue culture-responsive genotypes for transformation and then perform tedious backcrossing to insert the transgene into the farmer-popular genotypes (Biswas et al., 2015, 2018). Therefore, the use of in planta methods has resulted in genotype-independent transformation efficiencies of up to 25% in the case of Agrobacterium-mediated techniques for indica rice. Lower efficiencies of in planta rice transformation have been reported for Agrobacterium-mediated transformation of inflorescence tissue such as immature spikelets (Ratanasut et al., 2017) or rice leaf tissue for transient assays (Andrieu et al., 2012). Other recent work reporting on various methods and efficiencies of in planta transformation include those in maize (Abhishek et al., 2016), wheat (Hamada et al., 2017, 2018), and cotton (Kalbande and Patil, 2016). It may be mentioned here that in planta transformation is very common for dicots such as Arabidopsis thaliana, where inflorescences are used for floral-dip methods (Chang et al., 1994; Zhang et al., 2006).

2.4 Genome editing Genome editing technology has become very crucial in revolutionizing the field of agricultural production and functional genomics (Zaman et al., 2019). Currently under use are TALEN (transcription activator-like effector nucleases) and ZFN (zinc finger nuclease) mega nucleases. These technologies can produce double-strand break (DSB) to disrupt a gene or produce a premature stop codon by nonhomologous end joining (NHEJ) or homology-directed repair HDR with an incomplete template. However, these systems are complex and success was reported only in well-equipped labs (Gaj et al., 2013; Bi and Yang, 2017; Jung et al., 2018). Currently, a new but simple technology has been developed called CRISPR (clustered regularly interspaced short palindromic repeats)/Cas (CRISPR-associated systems), which is a multipurpose technology for genetic engineering using endonuclease activity. The advent of this technology has widened the agricultural research area and brought opportunities to develop novel plant varieties with new traits to fight diseases or different abiotic stress conditions. The ability to do precise modification, multiplex genome engineering, and the activation or repression of genes via knockouts has made CRISPR/Cas9 a groundbreaking and constantly advancing technology. Until now, the CRISPR/Cas system has been successfully applied to efficient genome editing in many eukaryotic organisms including humans, mice, zebra fish, flies, worms, yeast, rice, Arabidopsis, Nicotiana, and wheat (Zaman et al., 2019). In the following section, genome editing technologies and advances as well as different methods of CRISPR/Cas9 technologies that have revolutionized the field of rice research will be discussed. Methods of genome editing and targeting: The process of genome editing relies mainly on the process of DNA repair. There are many reasons for DNA damage, including UV radiation, metabolic products, free radicals, etc. Among several types of DNA damage, the double-strand break is known to be the most disastrous and therefore requires repair before any replication can take place. Evolution has resulted in two types of DNA repair processes in eukaryotes: nonhomologous end joining (NHEJ) and homology-directed repair (HDR). The NHEJ process is much faster in action and repairs the DNA imprecisely, leading to errors. Different proteins (e.g., Ku70 and Ku80) bind to the broken DNA ends and are joined together by a ligase that can result in the insertion or deletion (InDel) of nucleotides in the classical NHEJ process. These deletions or insertions can lead to frameshift mutations causing premature stop codon and nonfunctional genes (Fig. 1A) (Steinert et al., 2016). Multiple yield-related genes have been targeted in rice using NHEJ. Disease-resistant traits have been developed by knocking out a host gene in rice. These and other CRISPR-Cas9 mediated chromosomal deletions have been reported to be very efficient in rice and Arabidopsis (Zhou et al., 2014).

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FIG. 1 Sequential process of DNA repair. (A) Nonhomologous end joining (NHEJ) and (B) homology-directed repair (HDR).

Another DNA repair pathway is HDR, which relies on template DNA. The most common conservative HDR mechanism in plants, which repairs almost all DSBs in somatic cells, is the synthesis-dependent strand annealing (SDSA) pathway. When a break occurs in the DNA, an extension of the 30 overhangs occurs from the break site. A 50 end recombines to the homologous strand forming a D-loop. Then the synthesis process begins, leading to gap filling using the homologous DNA sequence as a template and the 30 end reanneals with the second 30 end without crossover. This whole process results in the integration of DNA from the donor DNA strand (Fig. 1B). This HDR process has several applications in plants, including the production of herbicide-resistant tobacco (Endo et al., 2016; Sun et al., 2016). In one of the experiments, an ig4 (Ig-like module 4) mutation was shown with an 0.147% and 1% efficiency of targeting and biallelic mutation, respectively (Endo et al., 2016). In the other study, researchers provided two gRNAs for removing the target gene by using plasmid or double-stranded DNA (Sun et al., 2016). In recent times, zinc-finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs) have been used as powerful tools for elucidating gene function and facilitating genetic improvement in various plants, including rice. These chimeric nucleases are composed of many programmable sequence-specific DNA-binding modules linked to a nonspecific DNA cleavage domain (Gaj et al., 2013) (Fig. 2A). Both these methods have paved the way for a wide range of gene modifications by introducing a DSB that further causes HDR or NHEJ at specific genomic locations. One study on rice utilized ZFNs to induce a DSB in SSIVa, a soluble starch biosynthesis gene involved in the starch biosynthesis pathway causing SSIVa expression regulation. The engineered ZFNs can cleave and stimulate mutation at the SSIVa locus in rice to affect the plant height, grain filling, and starch content ( Jung et al., 2018). TALENs have been used to do targeted mutagenesis in various plant species, including rice (Fig. 2B). The earliest use of TALEN-modified rice was done by targeted mutagenesis of the OsSWEET14 promoter in order to create better resistance to blight disease and heritability. TALEN has also been used in mutagenizing lipoxygenase LOX3 to improve the seed storage environment and knock out OsBADH2 (betaine aldehyde dehydrogenase 2) to increase 2-acetyl-1-pyrroline, which is a fragrant compound in rice grain. TALEN has been used in the introduction of DSBs in transgenes and endogenous

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Zinc finger nucleases (ZFNs) 9 nt Fok I

(A)

9 nt TAL effector nucleases (TALENs) 14–16 nt Fok I

14–16 nt

Double stranded breaks

(B) CRISPR/Cas9

Cas9 PAM motif NGG

5′

(C)

sgRNA 20 nt +PAM motif

3′

FIG. 2 Three types of genome editing tools. (A) Zinc finger nucleases that function as a dimer where each monomer contains a DNA binding domain (DBD) and a nuclease domain. This DBD consists of a series of 3–6 zinc finger repeats that recognize 9–18 nucleotides. The nuclease domain consists of type II restriction endonuclease Fok1. (B) Transcription activator-like nucleases (TALENs) are dimeric enzymes in which each subunit consists of a DBD contains highly conserved 33–34 amino acid sequence specific for each nucleotide and binding domain (highly conserved 33–34 amino acid sequence specific for each nucleotide) and Fok1 nuclease domain. (C) CRISPR/Cas9: Cas9 endonuclease is guided by sgRNA (single guide RNA: crRNA and tracrRNA) for target-specific cleavage. Twenty nucleotide recognition sites are present upstream of the protospacer adjacent motif (PAM). The gRNA or sgRNA is a short synthetic RNA composed of a scaffold sequence necessary for Cas-binding and a user-defined
20 nucleotide spacer that defines the genomic target to be modified. Thus, one can change the genomic target of the Cas protein by simply changing the target sequence present in the gRNA (Arora and Narula, 2017).

genes, which helps to understand the importance of DSB and abundantly transcribed mRNA in double-strand break interacting RNAs (diRNA) (Wei et al., 2012). Thus, TALENs have been of abundant use in facilitating HDR-mediated gene editing or gene replacement in rice (Bi and Yang, 2017). CRISPR/Cas9 mediated plant genome editing components for targeted mutagenesis: Although CRISPR/Cas9 has been used in various model organisms (Fig. 2), for plants it was necessary to do plant-specific modifications of commonly used CRISPR plasmids. Similar to other models, Cas9 from Streptococcus pyogenes or another Cas9 variant and a single stranded guide RNA is sufficient for editing the genome in plant cells. The gRNA is seen to be consistent among plants and other organisms. It is composed of approximately 20 nucleotide targeting sequences and approximately 75 nucleotide scaffold sequences, but the difference lies in the promoter that is used. This promoter depends on the type of cells, whether

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FIG. 3 (A) Agrobacterium can be used to transform plant cells with the gene of interest (GOI). This system contains Ti plasmid and Ti helper plasmid. (B) The Ti plasmid and helper are transformed into Agrobacterium tumefaciens and exposed to plant cells. The region in between the T-DNA is recognized by Vir genes of the helper Ti plasmid, which helps in the transfer of this GOI into plant cells. (C) RNP-mediated genome editing. Cas9 RNP is delivered to cells as preassembled Cas9-gRNA complexes and is free to interact with target DNA.

plant or another type. In plants, the most commonly used promoters to drive gene expression of small RNAs are AtU6, TaU6, OsU6, or OsU3 and the Cauliflower Mosaic Virus 35S promoter (CaMV 35S) (Bortesi and Fischer, 2015). Agrobacterium-mediated transformation of gene-editing components in plant cells: Agrobacterium can be used as a way to transfer a specific gene (gene of interest or GOI) into plant cells. See Section 2.1 for details of Agrobacteriummediated transformation (Fig. 3A and B) (Gelvin, 2003). RNP-mediated genome editing: One of the major drawbacks of the wide adaptation of Agrobacterium-mediated transformation of the CRISPR-Cas9 genome editing process is the adverse effects caused by constitutive expression and the lengthy process of constructing vectors to express each gRNA. An alternative process for this is a direct transfer of an RNP containing Cas9 that is also complexed with gRNA (guide RNA) for a specific target cell. This complex is at first assembled in vitro and then transfected in cells using the electroporation technique (Fig. 3C). This complex is capable of cleaving a target region with similar efficacy when compared to the plasmid-based method. Besides, this method limits the off-target effects as it does not require the delivery of foreign DNA. Moreover, the Cas9-gRNA RNP complex gets degraded over time, creating minimal off-target effects. Thus, this method generates single- or multigene knockouts in plant cell edits through HDR or even larger deletions (Foster et al., 2018). Demonstration of CRISPR/Cas9 genome editing in rice: Several studies conducted to improve the biotic and abiotic stress tolerance in rice using CRISPR-based techniques have shown promise, paving the way to the future. The whole genome analysis of 12 rice reference chromosomes has shown the presence of a total of 3.89  107 PAM motifs. The protospacer adjacent motif (or PAM for short) is a short DNA sequence (usually 2–6 base pairs in length) that follows the DNA region targeted for cleavage by the CRISPR system. The PAM is required for a Cas nuclease to cut and is generally found 3–4 nucleotides downstream from the cut site. This abundance of PAM (1 in 10) sites leads to the easy use of CRISPR Cas9 for editing sites in rice (Xie and Yang, 2013). For this reason, CRISPR technology will be one of the major players in the future for rice genome and trait improvement. The overall process of targeted mutagenesis in rice using CRISPR/Cas9 is shown in Fig. 4.

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FIG. 4 Targeted mutagenesis of the rice plant. Cas9 nuclease and the sgRNA matching the gene of interest are coexpressed using Agrobacterium tumefaciens as a vector in the plant embryonic calli or transfected into the protoplast from rice. Then the extraction of the DNA from the leaves of the protoplast is done. This is then subjected to PCR amplification with primer flanking the target site. The presence of Cas9 sgRNA-induced mutation can be easily detected using the restriction enzyme site loss method. The RE resistant band can be cloned and the exact nature of the mutations can then easily be revealed by sequencing the individual clone (Belhaj et al., 2013).

Validation of CRISPR/Cas9 genome editing: CRISPR genome editing often shows a phenotype caused by an off-target mutation rather than an edit in the target gene. So, validation methods are required for confirmation of the correct edit, which varies by species and the type of edit. When Cas9 introduces a double-stranded break (DSB), cellular machinery tends to repair it by HDR or NHEJ. The HDR pathway needs an additional repair template. Variations can also be seen in allele editing, where one, both, or none of the alleles is edited. Short heterogeneous insertion and the deletion of nucleic

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acid are observed at the DSB site in the case of NHEJ. In addition to the heterogeneity of InDels, allelic editing frequencies may also vary at Cas9-induced DSBs. We will discuss major validation methods to assess the precision of genome editing as described below. 1. Phenotypic screening: Visual observation by phenotypic screening often gives an indication of successful editing if the gene knockout shows an observable phenotypic effect, narrowing down the initial samples to test. For example, fluorescence activated cell sorting (FACS) can also be used to sort edited cell populations if the gene being edited produces a cell surface receptor or exterior-facing membrane protein. 2. Mismatch cleavage assay: This mostly used method relies on pairing between the wild type and edited version of the host DNA strand. The CRISPR-edited DNA is used as a template for PCR amplification of the target region of interest. The amplified product is then denatured and rehybridized with subsequent slow cooling, producing a mismatch in the double-stranded DNA. A special detection enzyme then recognizes and cleaves the hetero-duplex DNA strand 30 to the mismatch site, producing two bands detectable by gel analysis. T7 endonuclease (T7E1) is such a structure-selective enzyme that detects structural deformities in hetero-duplexed DNA. When an aberrant NHEJ event occurs after Cas9 cleavage, the hetero-duplex formed between amplicons of different lengths will be recognized and cleaved by T7E1. A single band at WT size indicates no editing has occurred and two smaller bands adding up to the length of WT indicates editing has taken place. The banding patterns and band intensity are then compared to determine the percentage of cleaved/uncleaved DNA, which gives a rough estimate of editing efficiency. The limitation of this method is it cannot reliably detect editing events occurring in less than 5% of the population and does not give any sequence information. 3. Sanger sequencing: PCR amplification spanning the target region followed by Sanger sequencing is an easy way to assess how many target sequences are knocked out. Sequencing the PCR product followed by analyzing the Sanger sequencing traces is a popular way to analyze the editing specifics. It is recommended to sequence the PCR product after cloning into a vector, as it is quite challenging to analyze the results from direct sequencing of the PCR product. The sequencing results are aligned with the reference/wildtype alongside the sgRNA sequence. Tools such as inference of CRISPR Edits (ICE) (Hsiau et al., 2018) and tracking of InDels by decomposition (TIDE) (Brinkman et al., 2014) can be used in this analysis. Insertions or deletions at the sgRNA target site causing a frameshift mutation can introduce early stop codon and knock out the gene. To check the presence of early stop codon, the mutated sequence is translated using any translation tool. One can also determine the overall InDel frequency and the percentage of sequences leading to putative knockouts reported as the knockout (KO) score. High KO scores have a high likelihood of containing InDels. However, this method is laborious, low throughput, and biased, as only the putative edited region is taken under consideration. A minimum of 10 sequencing results needs to be analyzed for confirmation. 4. Next-generation sequencing: To analyze a large number of samples, NGS is the best validation option. It enables rapid and precise sequencing results at an affordable cost. It can also detect if any fraction of the WT genotypes is left in the sample and the proportions of InDels. NGS can provide a picture not only of the on-target cleavage but also the offtarget effects throughout the genome, which makes it the most advantageous tool for analysis of the edit. However, utilizing an unbiased approach, that is, whole genome sequencing (WGS), to check the off-target edits will require sequencing of both the pre- and postedits of the whole genome, which is challenging due to natural variations in genotype. Targeted amplicon sequencing: This is a more practical but biased approach where NGS is performed on targeted amplicons throughout the genome where there is a high probability of off-target effects. Also, target amplicon deep sequencing is more affordable than WGS. GuideSeq (Tsai et al., 2015) is a genome-wide method for identifying double-stranded breaks, which are quite sensitive, and relies on erroneous NHEJ-mediated DNA repair. It captures cointroduced blunt-ended double-stranded oligonucleotides (dsODNs) at CRISPR/Cas9-induced breakpoints within the genome. These oligonucleotides are inserted at the DSBs caused by Cas9 in high frequency and thus tag the edited loci. In the next stage, dsODN integration sites are precisely mapped using unbiased amplification and NGS. Cameron et al. (2017) reported on Site-seq, which is a biochemical off-target cleavage assay that comprehensively lists Cas9 cleavage sites in a sample genome followed by probing of those sites for cellular off-target editing. This is a biased but high-throughput technique for validating CRISPR mutations within target and off-target sites. It reports the guide cutting efficiency and specificity, size, frequency, and distribution of InDel mutations by combining targeted amplicon sequencing and bioinformatics predictions.

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3

Target quantitative traits

Quantitative traits such as grain yield, stress tolerance, and broad spectrum defense responses are controlled by polygenes, hence transformation to overexpress specific genes often does not result in the desired improvement. Therefore, upstream regulatory genes are often targeted for modification to achieve the necessary downstream effects, as explained in the following paragraphs. Among abiotic stresses, developing tolerance to salinity, drought, heat, cold, and submergence has been the major focus for crop improvement. Among biotic stresses, bacterial and fungal blast and blight disease resistance are the common targets for the engineering of plants to adapt to adverse conditions.

3.1 Biotic and abiotic stress 3.1.1 Conventional transformation (a) Biotic stress: A number of transgenic crops with durable resistance to bacterial diseases (Horvath et al., 2012), viral diseases, fungal diseases (Rivero et al., 2012), insect pests, and herbicides (Green, 2011) have been developed. Sometimes, single-gene transformation results in insufficient or narrow spectrum disease resistance, so a combination of resistance genes can be a good choice. Pyramiding multiple resistant genes/QTLs is one of the targeted strategies being adopted. Crops such as rice, potatoes, maize, and cotton have been transformed with the Cry protein to kill certain insects that feed on the plants. Also, the gene pyramiding strategy was employed to produce two or more Bt toxins with dissimilar modes of action against the same target pest. Bundo´ and Coca (2016) constitutively overexpressed a calciumdependent protein kinase (OsCPK4) showing a rapid response to blast resistance, ROS production, callose deposition, and defense gene expression, conferring tolerance against both biotic and abiotic stress in a broad-spectrum response. (b) Abiotic stress: When considering the whole plant, all abiotic stresses induce a cascade of physiological and molecular events resulting in similar responses in some cases. Excessive heat introduces dehydration in drought-prone areas. Drought, high salinity, and cold can be exhibited as osmotic stress. For salinity tolerance, extensive works have been done in altering ion transporters, transcription factors, signaling molecules, ion pumps, and other regulatory genes such as helicase as well as artificial microRNA-based transformation. The overexpression of transcription factors such as DREB/CF and NAC has enhanced salt, drought, and cold tolerance in rice. Sub1A, a variant of the ERF family genes, could confer submergence tolerance to lowland rice. Rice transgenic plants overexpressing miR393 showed an increment in tillering and early flowering, together with decreased tolerance to salt (Xia et al., 2012). Overexpression of heat shock proteins such as sHSP17.7 and OsHSP50 (Xiang et al., 2018) could increase drought tolerance in transgenic rice seedlings. Transgenic BR55 lines with the overexpressed Rice G protein beta subunit showed significantly enhanced salinity and heat tolerance by exhibiting better growth, lower MDA and H2O2, lower leaf damage, etc., compared to the wild-type plant. Also, these showed a higher expression of genes involved in defending against multiple stresses (Seraj et al., unpublished). Alteration of genes in metabolic pathways (i) Signaling: As the first step in the response to salt, a transient increase in cytosolic Ca2+ has been recorded. Major groups of calcium-binding proteins include calmodulin (CaM), CAM-like proteins (CML), Ca2+-dependent protein kinase (CDPKs), and calcineurin B-like proteins (CBLs) (DeFalco et al., 2010). Rice CBL interacting protein kinase (OsCIPk15) overexpression enhanced tolerance to salinity in rice (Xiang et al., 2007). Mitogenactivated protein kinase (MAPK) cascades are composed of three types of kinases; the overexpression of OsMAP5a led to salt, drought, and cold stress tolerance as well as disease resistance (Xiong and Yang, 2003), indicative of the role of signaling molecules in the crosstalk between biotic and abiotic stress. A Na+-dependent receptor-like kinase (RLK), OsSIK1, was found to be involved in the scavenging and detoxification of ROS, and the overexpression of this induced salinity and drought tolerance by increasing antioxidant activity (Ouyang et al., 2010). (ii) Ion homeostasis: Membrane transport proteins regulate fluxes of ions, nutrients, and other molecules across the membrane. The selective uptake of K+ over Na+ by the root system often acts as a tolerance mechanism in some genotypes. The HKT (high-affinity K+ transporter) family resides at the plasma membrane and is permeable to either K+ or Na+ or to Na+ only (Rodrı´guez-Navarro and Rubio, 2006). Miyamoto et al. (2015) found that OsHKT2:1 overexpression promotes shoot Na+ accumulation under low K+ supply, but under sufficient K+ supply, OsHKT2;1-overexpressing rice accumulated Na+ in roots but not in shoots. Rice SOS1 was isolated and shown to be phosphorylated and activated by the SOS2/SOS3 protein kinase complex (Martı´nez-Atienza et al., 2007). This pathway also requires N-myristoylation of SOS3 to function,

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which is an example of cotranslational protein modification in the N-terminal glycine residue of some proteins. Constitutive overexpression of SOS1 in rice lines has been shown to increase tolerance to salinity (Yasmin et al., 2015). Increased expression of antiporter genes by salt stress has been reported for both glycophytes and halophytes (Blumwald and Poole, 1985; Gaxiola et al., 1999; Hamada et al., 2001). The acidic environment inside membrane-bound vacuoles in plant cells allows the efficient compartmentalization of Na+ in the vacuole through the vacuolar Na+/H+ antiporter (Apse et al., 1999). Vacuolar sequestration lowers the Na+ concentration in the cytoplasm as well as contributes to osmotic adjustment in the cytoplasm to maintain water uptake from saline solutions (Zhu, 2003). Fukuda et al. (2004) and Biswas et al. (2015) demonstrated that the overexpression of OsNHX1 improved salt tolerance and Amin et al. (2016) demonstrated that the inclusion of regulatory sequences such as UTR enhanced the tolerance even more. Both tonoplast and plasma membrane antiporters exclude Na+ from the cytosol by proton motive force generated by the plasma membrane H+ ATPase as well as the vacuolar membrane H+ ATPase and H+-pyrophosphatase. It has been shown that the activity of these proteins responds to as well as provides tolerance to salinity stress (Liu et al., 2010). (iii) Transcription regulators: In plants, AP2/EREBP (apetala2/ethylene responsive element binding protein), NAC (NAM, ATAF, and CUC), ZF-HD (zinc finger homeodomain), AREB/ABF(ABA-responsive element binding protein), AREB/ABF (ABA-responsive element binding protein/ABA binding factor), and MYC (myelocytomatosis oncogene)/ MYB (myeloblastosis oncogene) have been the most responsive to abiotic stresses. OsDREB1A and OsDREB1F are induced by high salinity and cold but OsDREB2A is induced by salt drought and temperature but not cold (Matsukura et al., 2010). Overexpression of OsbZIP23 showed improved salt tolerance whereas OsABI5 overexpression led to high salt sensitivity, indicative of its negative regulatory function (Zou et al., 2008). Other TFs such as OsMYB3R-2, OsGTγ-1, and OsHsfA2e genes are induced by high salinity and showed improved tolerance in Arabidopsis after overexpression (Fang et al., 2010). Overexpression of OsMYB3R-2 also increased tolerance to low temperature and drought, showing it to be a master switch in stress tolerance (Dai et al., 2007). Negra˜o et al. (2011) indicated that OsNAC genes are normally expressed at low levels but can be induced when plants are subjected to adverse environmental conditions. Transgenic plants overexpressing SNAC1 are more sensitive to ABA and close more stomatal pores to avoid the loss of water (Hu et al., 2006; Parvin et al., 2015). The SNAC2 gene was found to be associated with blast disease resistance apart from salt. A subset of the NAC members OsNTL2 to OsNTL6 (Kim et al., 2010) is induced by high salinity and mannitol and is responsive at the transcriptional level. (iv) Other regulatory genes: PDH45, a DEAD box helicase, is involved in the regulation of the Na+ level, ROS production, Ca2+ homeostasis, cell viability, and cation transporters in the roots of PDH45 transgenic rice and consequently provides salt tolerance (Amin et al., 2012). Nath et al. (2016) showed tolerance in IR64 and (Biswas et al., 2018) showed enhanced tolerance to salinity in high-yielding BR28 and BR47. Transgenic rice plants with a transformed coda showed the synthesis of glycine betaine and concomitant enhanced salt tolerance (Su et al., 2006). (Li et al., 2011) demonstrated that the overexpression of OsTPS1 in rice enhances salt tolerance by increasing the amount of trehalose and proline. Cotransformation allows the transformation of two or more transgenes. These can be in separate constructs and delivered to the plant simultaneously. Plants can also be retransformed, that is, a plant harboring a transgene can be transformed with additional transgenes. A multigene cassette consisting of a cassette harboring two or more linked genes can also be introduced in plants. The simultaneous overexpression of OsGS1;1 and OsGS2 isoforms could enhance tolerance and agronomic performance under abiotic stress conditions acting through multiple routes ( James et al., 2018). In an unpublished work by the authors, PDH45 (from the pea) and the HARDY gene (from Arabidopsis) could confer better tolerance in farmer-popular rice BRRI dhan27 under stress than the single gene. Similar works are under way with the transformation of two splice variants of OsNHX1 and another construct with a combination of SOS1 and NHX1 genes that showed promising results under stress (Seraj et al., unpublished). Stress-inducible and tissue-specific promoter transformation also can show better survival under stress. Sarker et al. (2016) reported the enhanced performance of the Arabidopsis rd29A promoter in transformed rice. This promoter subsequently resulted in the better performance of the HARDY gene in comparison to the same gene driven by the 35S CaMV one (Seraj et al., unpublished). Also, the Adh promoter was cloned from Arabidopsis because this gene is induced by hypoxia, drought, and cold stress. The transformed rice with this promoter showed selective expression of GUS gene activity up to two-fold in roots compared to the control (Ashraf et al., 2014). We are currently transforming high-yielding rice cultivars with candidate genes from the wild rice relative, the halophytic Porteresia coarctata. So far, MT3 (metallothionein transferase), ASR (abscisic acid stress ripening), PVA1 (porteresia VATPase), NHX1, and calcium ATPase genes have been transformed. Both BRRI dhan75 and BRRI dhan 81 transformed with the PVA1 gene and BRRI dhan75 transformed with the ASR1 gene showed better tolerance under 140 mM salt stress for 48 h.

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3.1.2 Crop improvement through CRISPR-CAS The first ever CRISPR/Cas9-mediated genome editing in rice was done using both the particle-mediated rice calli system and the protoplast of three rice genes: phytoene desaturase (OsPDS), betaine aldehyde dehydrogenase (OsBADH2), and mitogen-activated protein kinase (OsMPK2), which are involved in controlling the response against abiotic stress stimuli (Shan et al., 2013). OsMPK5, which negatively regulates abiotic and biotic stress genes, was targeted in rice using three specific types of gRNA. In the study, two new suitable vectors, namely pRGE3 and pRGE6, for rice genome editing were developed that allowed more efficiency and a low level of off-target effects (Xie and Yang, 2013). In rice, several studies have attempted to map quantitative regions (quantitative trait loci—QTL) controlling agronomically important traits that will eventually be used for introgression into elite lines for developing improved cultivars. However, the process has some potential drawbacks as many traits are closely linked, leading to some deleterious effect on plants. This allows for the use of the CRISPR/Cas9 system as a potent tool to introduce and study rare mutations in crop plants. The expression of OsSWEET genes is vital for the infection leading to bacterial blight disease (BLB). CRISPR/Cas9 techniques have been developed to delete nine and seven nucleotides of the OsSWEET14 and OsSWEET11 promoters, and has shown promise in the reduction of BLB ( Jiang et al., 2013). OsSWEET11, OsSWEET12, OsSWEET13, and OsSWEET14 sugar transporter genes were targeted using CRISPR/Cas9, which caused the chromosomal deletion of nuclease-targeted loci (Zhou et al., 2014). In another study on BLB resistance, CRISPR/Cas9 was used to develop knockout mutants in improving BLB resistance in IR24 (Zhou et al., 2015). Targeted mutation and improved heritability using CRISPR/Cas9: Several studies on OsDERF1 (drought-responsive ethylene responsive factor), OsPMS3 (photo-period sensitive male sterile), OsEPSPS (5-enolpyruvylshikimate 3-phosphate synthase), OsMSH1 (DNA mismatch repair protein), and OsMYB5 (myeloblast transcription factor) have proved the efficiency of the CRISPR/Cas9 system in creating specific mutations and better heritability in mutant lines (Zhang et al., 2014). In T0 generation, 21%–66% mutation rates were observed and in T2 generation, 11% homozygous mutants were found. Some studies have also been developed to do base editing without introducing DSB. C287, a herbicidal gene, was targeted for base editing where Cas9 was fused with cytidine deaminase (also known as activation-induced cytidine deaminase (target-AID) and then used for base editing without the need of DSBs (Shimatani et al., 2017). A base-editing method, ME3, used in editing the rice Phytoene desaturase OsPDS and the starch-branching enzyme OsSBEIIb gene, has demonstrated an incredibly precise editing ability and application of CRISPR/Cas9 system in rice. Moreover, multiplex genome editing has been developed in rice where eight agronomical genes were edited by only one vector (Shen et al., 2017).

3.2 Yield stability under stress 3.2.1 Conventional transformation Enhancements in grain yield and nutrition to feed people are the ultimate goals of food crop biotechnology. Both overexpression and the disruption of certain genes through transformation could lead to high yields. Low tiller number, more grains per panicle, and a thick and sturdy stem refers to ideal plant architecture (IPA). Jiao et al. (2010) showed that a point mutation in SPL14, a TF encoded by the IPA1 quantitative trait locus, disrupted binding of OsmiR156 to it, resulting in the IPA phenotype. Ambavaram et al. (2014) has narrowed down a master regulator directly affecting yield, calling it higher-yield rice (HYR). Under water deprivation, in the HYR lines higher relative water content was observed and they related it with the accumulation of soluble carbohydrates, leading to osmotic adjustment. Functional analysis of the HYR protein activities revealed its involvement in the direct transcriptional activation of multiple photosynthesis-related processes and the activation of auxin-responsive TFs. The overexpression of OsGASR9 (gibberellic acid stimulated transcript related) could increase plant height and grain size, which is a positive regulator of responses to GA (gibberellic acid) in rice (Li et al., 2019). Zhou et al. (2017) cloned a novel DHHC-type zinc finger protein gene and its alternative splice variant DHHC1 that regulates yield by altering tiller; a 10% increase in yield was observed. Nitrogen determines the productivity and biomass of a crop. (Wang et al., 2018a) showed that the overexpression of OSNRT1.1A (OsNPF6.3), a member of the rice nitrate transporter family, could confer high yield and early maturation and is actually involved in N utilization and the regulation of flowering. Faisal et al. (2017) showed an enhanced yield in rice by knocking out the DST gene using artificial microRNA. According to Li et al. (2016b), the Gn1α, IPA1, DEP1I, and GS3 genes have the most potential to manipulate the yield.

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3.2.2 Crop improvement through CRISPR Extensive studies have demonstrated that CRISPR/Cas technology can achieve efficient targeted mutagenesis in rice, paving the way for large-scale genome editing and enabling quality improvement and yield increase. The major determinates of the yield are panicles per plant, the number of grains per panicle, and the grain weight (Xing and Zhang, 2010). The main idea is to knock out genes that negatively regulate the major yield components. Grain size 3 (GS3), dense and erect panicle 1 (DEP1), grain size 5 (GS5), grain weight 2 (GW2), grain number 1a (Gn1a), and TGW6 have been knocked out. In some studies, they have been independently edited to improve phenotypes such as higher grain number, dense erect panicles, and larger grain size, leading to an increase in yield (Zhang et al., 2014). Growth and yield are also regulated by several phytohormones and their signaling pathways. CRISPR/Cas9 has also been used to edit the Badh2 gene of the rice line Zhonghua 11, creating its fragrant version by its downregulation (Shan et al., 2015). All the CRISPR Cas9-mediated gene editing using HDR or NHEJ in rice is shown in Table 1. These studies using CRIPSR/Cas9 indicate the efficacy of this system in chromosomal engineering as well as the production of insertion, deletion, substitution, and translocation, leading to the development of cultivars with new traits. This easy and straightforward genome editing technique is set to revolutionize the field of rice research and greatly improve the specific traits of the rice plant. This system is set to also explore the more complicated genomes of wheat and maize in order to improve their traits.

TABLE 1 CRISPR/Cas9-mediated gene editing in rice.

Gene

NHEJ/ HDR

Myb-domain protein 1 (MYB1)

NHEJ

Study role of MYB1 (involved in Pi uptake and accumulation)

Protoplast transformation, Agrobacteriummediated

Zhang et al. (2014)

DERF1, 5-enolpyruvylshikimate-3phosphate synthase (EPSPS), MSH1, phytoene desaturase (PDS), PM3

NHEJ

Drought tolerance

Agrobacteriummediated

Zhang et al. (2014)

SWEET11

NHEJ

Early stage grain filling

Agrobacteriummediated

Collard et al. (2017)

SWEET11, SWEET14

NHEJ

Bacterial blight disease resistance

Agrobacteriummediated

Jiang et al. (2013)

Chlorophyll A oxygenase 1 (CAO1), LAZY1

NHEJ

Short life cycle

Agrobacteriummediated

Miao et al. (2013)

Bentazon sensitive lethal (BEL)

NHEJ

Herbicide resistance

Agrobacteriummediated

Xu et al. (2014)

SWEET11, SWEET13, SWEET1a, SWEET1b, CPS4, CYP9A2, CYP76M5, KO1, KOL5

NHEJ

Bacterial blight disease resistance

Agrobacteriummediated

Zhou et al. (2014)

Cyclin-dependent kinase (CDKA2, CDKB1, CDKB2)

NHEJ

Confirming multigene knockout using off-target mutations in rice

Agrobacteriummediated

Endo et al. (2015)

Mitogen-activated protein kinase (MPK1, MPK5, MPK6), phytoene desaturase (PDS)

NHEJ

Various biotic and abiotic stress resistance through signaling pathways

Protoplast transformation

Xie et al. (2015)

Glutathione S-transferase (GSTU), MRP15, ANP, WAXY, 7FTL genes, and 21 other genes

NHEJ

Study multiple gene, gene family, and heritability test

Agrobacteriummediated

Ma et al. (2015)

Alternative oxidase (AOX1a, AOX1b, AOX1c), bentazon sensitive lethal (BEL)

NHEJ

Various abiotic stress tolerance

Agrobacteriummediated

Xu et al. (2015)

Study target

Transformation method

Reference

Continued

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TABLE 1 CRISPR/Cas9-mediated gene editing in rice—cont’d

Gene

NHEJ/ HDR

Study target

Transformation method

Reference

DsRed (transgene), young seedling albin (YSA), phytoene desaturase (PDS), DL

NHEJ

Compare CRISPR construct or parameters for efficient mutagenesis

Agrobacteriummediated

Mikami et al. (2015)

P450, double WAP domain (DWD1)

NHEJ

DNA free genome editing with CRISPR-RNP

RNP-mediated

Woo et al. (2015)

RAV2

NHEJ

Salt stress tolerance

Agrobacteriummediated

Duan et al. (2016)

Disrupted meiotic cDNA (DMC1A, DMC1B)

NHEJ

Evaluation of precision of targeted mutagenesis

Agrobacteriummediated

Mikami et al. (2016)

Narrow leaf 1 (NAL1), Lysophosphatidic acid receptor 1 (LPA1), leucine rich glioma inactivated 1 (LGI), glabrous leaf and hull 1-1 (GL1-1)

NHEJ

Expanding range of CRISPR techniques in plants with loss of cuticular wax, laminar joint, auricle, and ligule

Agrobacteriummediated

Hu et al. (2016b)

Dense and erect panicle 1 (DEP1), rice outermost cell-specific 5 (ROC5)

NHEJ

Demonstrating single-strand conformation polymorphismbased genotyping

Agrobacteriummediated

Zheng et al. (2016)

Grain number 1a (Gn1a), dense and erect panicle 1 (DEP1), grain size 3 (GS3), ideal plant architecture1 (IPA1)

NHEJ

Plants with enhanced grain number, dense erect panicles, larger grain size, semidwarf, and grain with long awn, phenotypes

Agrobacteriummediated

Li et al. (2016b)

ETS2 repressor factor (ERF922)

NHEJ

Blast resistance

Agrobacteriummediated

Wang et al. (2016)

Carbon starved anther (CSA)

NHEJ

Developing photosensitive genic male sterile lines

Agrobacteriummediated, protoplastmediated transformation

Li et al. (2016a)

Ruptured pollen tube (RUPO)

NHEJ

Regulate K+ homeostasis for pollen tube growth and integrity

Agrobacteriummediated

Li et al. (2016c)

Tryptophan 2-monooxygenase (TMS5)

NHEJ

Developing thermosensitive genic male sterile line for hybrid rice breeding

Agrobacteriummediated

Zhou et al. (2016)

Pollen mitosis relative (PMR)

NHEJ

Study of role of PMR (regulate male gametophyte development)

Agrobacteriummediated

Liu et al. (2017)

Maternally expressed genes (MEGs), paternally expressed genes (PEGs)

NHEJ

Increase yield

Agrobacteriummediated

Yuan et al. (2017)

Starch-branching enzyme (SBEI, SBEIIB)

NHEJ

Amylose-rich rice

Agrobacteriummediated

Sun et al. (2017)

Respiratory burst oxidase homolog (RBOHH)

NHEJ

Survival in oxygen-deficient condition

Agrobacteriummediated

Yamauchi et al. (2017)

Epidermal patterning factor (EPFL9)

NHEJ

Decrease stomatal development

Agrobacteriummediated

Yin et al. (2017)

High-affinity K+ transporter (HAK-1)

NHEJ

Low cesium accumulation

Agrobacteriummediated

Nieves-Cordones et al. (2017)

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TABLE 1 CRISPR/Cas9-mediated gene editing in rice—cont’d

Gene

NHEJ/ HDR

Study target

Transformation method

Peroxiredoxins (PRX2)

NHEJ

Potassium deficiency tolerance through stomatal closure

Agrobacteriummediated

Mao et al. (2018)

Rice outermost cell-specific gene5 (ROC5), stromal processing peptidase (SPP), young seedling albin (YSA)

NHEJ

Increase plant growth

Agrobacteriummediated

Zhang et al. (2014)

5-Enolpyruvylshikimate-3-phosphate synthase (EPSPS)

NHEJ, HDR

Glyphosate resistance in rice

Protoplast transformation

Li et al. (2016b)

Phytoene desaturase (PDS), betaine aldehyde dehydrogenase (BADH2)

NHEJ, HDR

Involved in various abiotic stresses

Protoplast transformation

Shan et al. (2013)

Mitogen-activated protein kinase (MPK2), dense and erect panicle1 (DEP1)

NHEJ, HDR

Yield under stress

Protoplast transformation

Shan et al. (2014)

Acetolactate synthase (ALS)

HDR

Herbicide resistance

Particle bombardment and Agrobacteriummediated transformation

Endo et al. (2016) and Sun et al. (2016)

Actin-1 glutathione S-transferase (ACT), glutathione S-transferase(GST)

HDR

Establishing knock in frequency in rice

Agrobacteriummediated

Wang et al. (2017)

Reference

4 Computational analysis Whole genome sequencing of rice and other next-generation sequencing platforms have created a huge summation of data and further development of databases for specialized purposes. They also provide bioinformatics tools for organizing, analyzing, and visually representing the huge amounts of data so far generated. Despite the fact that there are many databases with open source data, their exploration has not been efficiently carried out by the majority of researchers. The sequencing of 3000 globally distributed rice varieties has opened an era of better understanding of the genetic and functional diversity of rice (Li et al., 2014). The MSU Rice Genome Annotation Project (Ouyang et al., 2006), the International Rice Genome Sequencing Project’s (IRGSP) rice RAPdb (Sakai et al., 2013), and the Oryza Genome Evolution (OGE) project (http://oge.gramene.org) have been developed that include integrated web resources for rice that provide information on genome assembly, annotation, and associated information such as alignment, SNP data (3000 rice genome sequence project), genetic and physical maps, EST, and QTL locations. Besides, RiceCyc and Rice Reactome provide pathway databases of rice and other oryza species (Dharmawardhana et al., 2013; Naithani et al., 2016). The largest dataset of all is the RiceSNP-Seek Database, which houses approximately 29 million SNP data of rice variants that originated from the 3000 rice genome project (Mansueto et al., 2016). The improvement of rice for tolerance to multiple stresses, including salinity, will require assistance from these datasets and tools. First, the gene expression databases provide information regarding the expression pattern of genes under specific conditions, which are collected using RNAseq, microarray, and real-time PCR experiments. The Diurnal (Mockler et al., 2007), GENEVESTIGATOR (Hruz et al., 2008) and EMBL-EBI Gene Expression Atlas (Petryszak et al., 2015) resources could be used to identify the expression patterns of genes under different stress conditions with varying time intervals and rice genotypes. Second, to understand the overall pattern of tolerance, we require information on coexpression profiling, which can be obtained through RiceFREND (Sato et al., 2012a), RiceXPro (Sato et al., 2012b), and RiceNet (Lee et al., 2015). The analysis of the large amount of available data is an important task. CyVerse (Devisetty et al., 2016) and Galaxy (Afgan et al., 2016) are two web-based platforms that provide tools for various analyses. It is important to have a Linux/ Unix platform for analyzing big data. Statistical programming languages such as R are also important because they contain many packages to handle such data. Familiarizing oneself with these online platforms, software, and programming languages will provide the ability not only for data storage, but also its dissemination. This will maximize the use of available

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data and resources and avoid redundancy, paving the way for high-throughput bioinformatics analysis and subsequent targeted crop improvement programs.

5

Technology advancement

Genome editing using the CRISPR/Cas9 system is the latest and simplest system for targeted genome modification using NHEJ or HDR using a template with the desired modifications (Shan et al., 2014). Examples of both, that is, the use of NHEJ, where the desired gene is mutated to reduce its efficacy, or HDR, where an efficient version of a gene has been introduced, have been provided in the paragraph on CRISPR/Cas9 above (Table 1). One of the best advantages of the CRISPR/Cas9 technology is that any of the foreign genes inserted for achieving either NHEJ or HDR can be selected for without any “transgenic” tag. The repair in the host cell DNA is performed by endogenous enzymes using the help of external gene constructs. When the transformation is done using biolistic gene bombardment, electroporation, or RNP-mediated gene delivery, the latter machinery is degraded once the repair is accomplished, leaving only the modified DNA in place. No traces of the foreign DNA will be found if tested for their presence ( Jones, 2015; Khatodia et al., 2016). When Agrobacterium-mediated transformation is used, it can take 2–4 generations to select for only those plants that have the mutation but none of the remnants of selectable markers and reporter genes (Khatodia et al., 2016). In short, CRISPR/Cas technology gives us the means to do targeted gene editing in plants with deletions and insertions, but without the stigma of genetically modified organisms because no traces of foreign DNA can be found and the plants are similar to mutated plants. Mutated plants produced by radiation of chemicals are not traditionally subjected to regulatory oversight ( Jones, 2015). CRISPR technology has yet to be fully explored to its potential. Methods need to be explored to increase the efficiency, specificity, and range of accessible targets. Editing efficiency can be increased by changing the fourth T of a polyT sequence to C or G (Dang et al., 2015) or the PAM recognizing domain of Cas9 can be changed to catch other PAM motifs (Hu et al., 2016b). Also, the inclusion of gene activation or repression domains can regulate the expression of Cas9. Some inducible strategies for CRISPR/Cas9-based genome editing have been reported recently. Among these, knock-in techniques to introduce doxycycline (DOX) inducible Cas9 (iCas9) is notable. Besides, Tet-off controlled sgRNA (depends on tetracycline controlled transcription activators), heat-shock inducible Cas9, photoactivatable or chemiactivatable Cas9, and split Cas9 are important technological improvements. The simultaneous disruption of multiple genes can be performed by expressing multiple single guide RNA carrying different direct sequences. It can be done by using a single plasmid to deliver multiple sgRNAs into one plasmid. Each gRNA needs to be expressed from its own promoter. Several groups have developed methods to clone sgRNA cassettes and have described multiplexing strategies, for example, the works of Kabadi et al. (2014) and Ma et al. (2015). Xie et al. (2015) showed polycystronic tRNA-gRNA (PTG) where the sgRNA flanked with the tRNA precursor sequence can target multiple regions of the genome after transcription and release of pre-tRNA. Thus, the simultaneous editing of multiple genomic sites can facilitate studying multiple genes or knockouts. Another technology advancement leading to the quick production of improved genotypes in rice and other crops is the establishment of tissue culture-independent in planta transformation systems, especially using Agrobacterium. While the floral dip method is established for Arabidopsis and other dicots (Fauser et al., 2012), seed/embryo-based systems for Agrobacterium-based infection have been shown to work better for rice and other cereals (Risacher et al., 2009; Ahmed et al., 2018).

6

Conclusion and future perspectives

With the advent of next-generation sequencing technologies, greater effort at mining biodiversity in genebanks (Kilian and Graner, 2012) as well as in worldwide collections (Wang et al., 2018b) is being made. Genome-wide association technologies using identified single nucleotide polymorphisms (SNPs) are generating information on hitherto unknown loci associated with abiotic stress such as salinity tolerance (Patishtan et al., 2018). Rising sea levels have resulted in larger areas of coastline being affected by high salt levels with a concomitant necessity of the production of rice and other crops tolerant of higher levels of salinity (Gupta and Huang, 2014). At the same time, many halophytic resources are being studied and sequenced (Mondal et al., 2017). So on the one hand, genes and loci associated with salinity and other stresses are available, and on the other, transformation technologies have advanced considerably in their ease and genotypic independence. Moreover, targeted gene editing technologies that are able to avoid the transgenic label have paved the way for tailor-made crops, which will be important in ensuring food security in the near and distant future.

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Chapter 3

Tweaking microRNA-mediated gene regulation for crop improvement Sandeep Yadava, Shabari Sarkar Dasb, Pramod Kumara, Vishnu Mishraa and Ananda K. Sarkara a

National Institute of Plant Genome Research, New Delhi, India, b Department of Botany and Forestry, Vidyasagar University, Midnapore,

West Bengal, India

1 Introduction In the last decade, the role of many small noncoding RNAs had been deciphered in both plants and animals (ArteagaVazquez et al., 2006). Pioneering studies during the 1980s and 1990s demonstrated that the expression of the short viral genome could provide immunity against viruses, and transgenes can be utilized to silence selected endogenous genes based on sequence homology (Napoli et al., 1990; Prins et al., 2008; van der Krol et al., 1988). However, the mechanism behind the transgene silencing was not known. This riddle was first solved by Fire and coworkers in 1998 while working with Caenorhabditis elegans. They reported that double-stranded RNAs (dsRNAs) could silence the endogenous genes based on their sequence complementarity, and named this process RNA silencing or RNA interference (Fire et al., 1998). In plants, Hamilton and Baulcombe showed similar silencing of target genes against small RNAs (Hamilton and Baulcombe, 1999). Such studies in both plants and animals demonstrated that the small RNAs derived from the long dsRNAs could guide the cleavage of the corresponding target gene (reviewed in Hannon, 2002; Singh et al., 2018). Based on the precursor sequence and function, a hierarchical classification system of endogenous small noncoding RNAs was proposed, in which small RNAs were primarily classified into two groups: hairpin RNAs (hpRNAs) and small interfering RNAs (siRNAs) (Axtell, 2013a). Small RNAs belong to the hpRNA family if the precursor sequence is a singlestranded RNA that forms a self-complementary hairpin loop structure. The secondary classification of hpRNAs divides them into two groups: miRNAs and other hpRNAs (reviewed in Axtell, 2013a). The miRNAs represent a class of small noncoding RNA molecules about 20–24 nucleotide (nt) long that are naturally found in plants and animals. In plants, MIRNA genes are distributed in both intragenic and intergenic regions throughout the genome (Rajagopalan et al., 2006; Reinhart et al., 2002). The transcripts encoded by an MIRNA gene are known as pri-miRNA, which attain a hairpin conformation by complementary base pairing. Unlike animals, plants lack Drosha-like enzymes, and both pri-miRNA to pre-miRNA conversion and mature miRNA processing are directed by DICER-LIKE (DCL) endonucleases (Bernstein et al., 2001; Jacobsen et al., 1999). The stem-loop structure obtained after the first cleavage event is called precursor miRNA (pre-miRNA). DCL family genes direct a subsequent second cleavage event primarily based on the secondary features present in the stem-loop region of the pre-miRNA, usually after 20–24 nt from the first cleavage event, thus yielding a 20–24 nt miRNA/miRNA* duplex (Liu et al., 2012). The miRNA/miRNA* form is exported from the nucleus to the cytoplasm for further processing where it complexes with an ARGONAUTE (AGO) protein, and possibly the lessstable strand is retained by the AGO protein while the other strand is released for degradation. The single strand of 20–24 nt RNA (miRNA) and AGO protein forms a complex called the RNA silencing complex (RISC). The AGO protein possesses slicer activity and the target mRNA is either cleaved or repressed translationally based on the sequence complementarity with the mature miRNA sequence (Baumberger and Baulcombe, 2005; Bartel, 2004). miRNAs posttranscriptionally regulate the expression of several key transcription factors (TFs) whose activity is required for organ growth and development (Llave et al., 2002; Rhoades et al., 2002). The immense potential of miRNAs in gene regulation has prompted many researchers to study their role in diverse developmental processes such as leaf morphogenesis, phase transition, pattern formation, flower development, meristem maintenance, disease resistance, and stress responses across diverse plant species, summarized in Table 1 (Singh et al., 2018; D’Ario et al., 2017; Kamthan et al., 2015; Chen, 2009).

Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00003-6 © 2020 Elsevier Inc. All rights reserved.

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TABLE 1 Compendium of the role of miRNAs in diverse plant species. Targets miRNA

Plant

miR156

Arabidopsis thaliana

miR157

miR159

miR160

Target family

Name

Functional importance

References

SPL

AtSPL2/3/4/5/9/10/11/ 13A/13B/15

Vegetative to reproductive phase transition, LR development, heat stress

Rhoades et al. (2002), Wu and Poethig (2006), Cardon et al. (1997) Schwab et al. (2006), Yu et al. (2015), and Stief et al. (2014)

Oryza sativa

SPL

OsSPL13/14/16

Plant architecture, panicle branching, grain shape and size

Miura et al. (2010), Jiao et al. (2010), Wang et al. (2012b), and Si et al. (2016)

Zea mays

SPL

TGA1, tsh4, etc.

Phase transition, bract development, and meristem boundary establishment

Chuck et al. (2007, 2010)

Glycine max

SPL

GmSPL1/2

Level of nodulation

Yan et al. (2013)

Solanum tuberosum

SPL

StSPL3/6/9/13 and StLG1

Plant architecture and tuber yield

Bhogale et al. (2014)

Solanum lycopersicum

SPL

SlySBP genes

Plant architecture and phase transition

Zhang et al. (2011a) and Ferreira e Silva et al. (2014)

Lotus japonicus

SPL

AU089181, TC70253

Plant architecture and nodulation

Wang et al. (2015c)

Arabidopsis thaliana

SPL

AthSPL2/3/4/5/9/10/ 11/13A/13B/15

Phase transition

He et al. (2018)

Gossypium hirsutum

SPL

GhA10G2217/ A13G0749/ A01G2095/ A01G1281/ A11G0344

Floral organ size and ovule

Liu et al. (2017)

Solanum lycopersicum

SPL

LeSPL-CNR

Fruit ripening

Chen et al. (2015)

Arabidopsis thaliana

GAMYB

AtMYB33/65/101

Floral development, embryo development, programmed cell death, phase change

Alonso-Peral et al. (2010), Achard et al. (2004), Csukasi et al. (2012), Zhao et al. (2018), and Guo et al. (2017)

Triticum aestivum

GAMYBlike

TaGAMYB1

Anther development and heat stress tolerance

Wang et al. (2012a)

Fragaria ananassa

GAMYB

FaGAMYB

Fruit development

Csukasi et al. (2012)

Arabidopsis thaliana

ARF

AtARF10/16/17

Auxin response, anther development, root cap development, seed germination, heat stress, seed dormancy

Wang et al. (2005, 2017); Mallory et al. (2005), Lin et al. (2018), and Liu et al. (2013)

Solanum lycopersicum

ARF

SlARF10A/10B/17

Leaf, early fruit development, maintaining water balance

Hendelman et al. (2012), Damodharan et al. (2016), and Liu et al. (2016)

Glycine max

Not studied

Not studied

Nodule development

Turner et al. (2013) and Nizampatnam et al. (2015)

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TABLE 1 Compendium of the role of miRNAs in diverse plant species—cont’d Targets Target family

Name

Functional importance

References

Manihot esculenta

ARF

MeARF10

Immunity against Colletotrichum gloeosporioides fungus

Pinweha et al. (2015)

Dimocarpus longan

ARF

DlARF10/16/17

Somatic embryogenesis

Lin et al. (2015)

Oryza sativa

ARF

OsARF18

Auxin signaling

Huang et al. (2016)

Gossypium hirsutum

ARF

Gh_D05G0978

Male sterility under high temperature condition

Ding et al. (2017)

Beta vulgaris

ARF

BvARF17/18

Salt stress

Cui et al. (2018)

Arabidopsis thaliana

NAC

AtCUC1/CUC2/ NAC1/NAC4/ORE1/ At5g61430/ At5g39610

Boundary size control, vegetative and flower development, petal number, axillary meristem, pathogen response, cell death

Rhoades et al. (2002), Mallory et al. (2004), Raman et al. (2008), Laufs et al. (2004), Lee et al. (2017), Kasschau et al. (2003), Baker et al. (2005), Sieber et al. (2007), Peaucelle et al. (2007), and Kim et al. (2009)

Solanum tuberosum

NAC

StNAC262

LR development

Zhang et al. (2018a)

Zea mays

NAC

ZmNAC1

LR development

Li et al. (2012)

Beta vulgaris

NAC

BvNAC21/100

Salt stress

Cui et al. (2018)

Triticum aestivum

NAC

TaNAC21/22

Stripe rust

Feng et al. (2014)

Oryza sativa

NAC

OsOMTN1/2/3/4/5/6

Drought tolerance

Fang et al. (2014)

miR165/ 166

Arabidopsis thaliana

HD-ZIP III

AtPHB/PHV/REV/ ATHB8/ATHB15

Shoot apical meristem, vascular patterning, leaf, flower, and root development, drought tolerance

Jung and Park (2007), Zhou et al. (2007), Liu et al. (2009a), Carlsbecker et al. (2010), Singh et al. (2014), and Tatematsu et al. (2015)

miR166

Oryza sativa

HD-ZIP III

OsHB4

Drought resistance

Zhang et al. (2018b)

Zea mays

HD-ZIP III

ZmRLD1

Leaf polarity

Juarez et al. (2004a,b)

Glycine max

HD-ZIP III

Gm07g01940, Gm06g21620

Cold-responsive

Zhang et al. (2014)

Arabidopsis thaliana

ARF

AtARF6/ARF8/IAR3

Flower development, lateral and adventitious root development, osmotic stress, nitrateresponsive, embryo development

Gutierrez et al. (2009, 2012), Wu et al. (2006), Yao et al. (2019), and Kinoshita et al. (2012)

Solanum lycopersicum

ARF

SpARF6/ARF8A/ ARF8B

Flower development, high temperature stress

Liu et al. (2014a) and Jodder et al. (2018)

Glycine max

ARF

GmARF8a/ARF8b

Nodule and LR development

Wang et al. (2015a)

miRNA

miR164

miR167

Plant

Continued

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TABLE 1 Compendium of the role of miRNAs in diverse plant species—cont’d Targets Target family

Name

Functional importance

References

Arabidopsis thaliana

NF-YA

AtNF-YA2/5/10

Nitrogen starvation, drought tolerance, root architecture

Zhao et al. (2011), Li et al. (2008), and Sorin et al. (2014)

Oryza sativa

NF-YA

OsNF-YA10, Os03g29760

Immunity, salt stress

Li et al. (2017a), and Zhao et al. (2009)

Medicago truncatula

NF-YA

MtHAP2-1

Nodulation

Combier et al. (2006)

Glycine max

NF-YA

GmNFYA3

Drought tolerance

Ni et al. (2013)

Solanum lycopersicum

NF-YA

SlNF-YA1/2/3

Drought tolerance

Zhang et al. (2011b)

Arabidopsis thaliana

GRAS

AtSCL6-II/6-III/6-IV/ 22/27

Shoot branching, chlorophyll biosynthesis

Wang et al. (2010a) and Ma et al. (2014)

Solanum lycopersicum

GRAS

SlGRAS24

Multiple agronomic traits

Huang et al. (2017) and Kravchik et al. (2019)

Oryza sativa

GRAS

OsSCL21, OsSCL6IIa/IIb/IIc, OsHAM1/2/ 3/4

Root development, rice stripe virus, vegetative phase change transition, SAM maintenance

Fan et al. (2015), Tong et al. (2017), and Cho and Paszkowski (2017)

Medicago truncatula

GRAS

MtNSP2, MtLOM1

Arbuscular mycorrhizal colonization

Lauressergues et al. (2012) and Couzigou et al. (2017)

Hordeum vulgare

GRAS

HvSCL

Floral meristem and phase transition

Curaba et al. (2013)

Arabidopsis thaliana

AP2

AtAP2/SNZ/SMZ/ TOE1/TOE2/TOE3

Flower development, phase change transition

Chen (2004), Aukerman and Sakai (2003), Mathieu et al. (2009), Wu et al. (2009), and Jung et al. (2014)

Jatropha curcas

AP2

JcAP2/TOE1/TOE2/ TOE3

Vegetative and reproductive development

Tang et al. (2018)

Rosa chinensis

AP2

RcAP2L

Flower development

Francois et al. (2018)

Oryza sativa

AP2

Os04g55560/ Os06g43220/ Os07g13170/SNB/ IDS1

Rice floret development, culm and panicle development

Zhu et al. (2009) and Zhang et al. (2017a)

Phaseolus vulgaris

AP2

PvAP2-1

Nitrogen fixation

Nova-Franco et al. (2015)

Glycine max

AP2

GmAP2-2/NNC1

Nodulation

Yan et al. (2013) and Wang et al. (2014a)

Solanum tuberosum

AP2

StRAP1

Tuber development

Martin et al. (2009)

Actinidia deliciosa

AP2

AdAP2

Flower development

Varkonyi-Gasic et al. (2012)

Lotus japonicus

AP2

LjAP2-like1/2, LjRAP2-7-like1/2/3

Bacterial symbiosis in root

Holt et al. (2015)

miRNA

Plant

miR169

miR171

miR172

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TABLE 1 Compendium of the role of miRNAs in diverse plant species—cont’d Targets miRNA

Plant

miR319

Arabidopsis thaliana

miR393

miR394

miR395

miR396

Target family

Name

Functional importance

References

TCP

AtTCP2/3/4/10/ MYB33/MYB65

Leaf and petal growth, senescence, secondary cell wall biosynthesis

Palatnik et al. (2003, 2007), Nag et al. (2009), Schommer et al. (2008), Koyama et al. (2017), and Sun et al. (2017)

Solanum lycopersicum

TCP

SlLA

Compound leaf development

Ori et al. (2007)

Antirrhinum

TCP

CIN

Leaf development

Nath et al. (2003)

Saccharum officinarum

MYB and TCP

SoTC94752 and SoTC111376

Cold stress

Thiebaut et al. (2012)

Arabidopsis thaliana

bHLH

AtAFB3, TIR1, MEMB12

Nitrogen-responsive root growth, development, promotes glucosinolate accumulation, innate immunity, salt stress

Zhang et al. (2011c), Vidal et al. (2010), Chen et al. (2011, 2014), and RobertSeilaniantz et al. (2011)

Oryza sativa

bHLH

OsTIR1/AFB2/ Os02g06260/ Os05g41010

Flag leaf inclination, primary, lateral, and crown root development, tiller number, flower timing, alkaline, salt and salinity stress

Bian et al. (2012), Xia et al. (2012), Gao et al. (2011), and Lu et al. (2018)

Hordeum vulgare

bHLH

HvTIR1/AFB2

Root growth in aluminum stress

Bai et al. (2017)

Glycine max

bHLH

GmTIR1/AFB3

Nodulation

Cai et al. (2017)

Arabidopsis thaliana

F-box

AtLCR

Leaf morphology, SAM maintenance, drought and salt stress, resistance to Botrytis cinerea

Song et al. (2012, 2013), Knauer et al. (2013), and Tian et al. (2018)

Allium sativum

F-box and CYP450

Contig_Asa_3126, Contig_Asa_2307

Fusarium oxysporum f. sp. cepae (FOC) resistance

Chand et al. (2016)

Oryza sativa

F-box

OsLC4

Leaf inclination

Qu et al. (2018)

Arabidopsis thaliana

SULTR and APS

AtSULTR2;1/APS1/3/4

Sulfur assimilation, SO2 stress, seed germination

Kawashima et al. (2009), Kim et al. (2010), Liang et al. (2010), and Li et al. (2017b)

Malus domestica

WRKY

MdWRKY26

Alternaria alternaria f. sp. mali (leaf spot disease) resistance

Zhang et al. (2017b)

Nicotiana tabacum

SULTR

NtSULTR2

Sulfur metabolism

Yuan et al. (2016)

Arabidopsis thaliana

GRF and bHLH

AtGRF1/2/3/5/6/ bHLH74

Leaf growth, root growth, pistil development, and innate immunity

Rodriguez et al. (2010, 2015), Jones-Rhoades and Bartel (2004), Liu et al. (2009b), Bao et al. (2014), Liang et al. (2014), and Soto-Suarez et al. (2017) Continued

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TABLE 1 Compendium of the role of miRNAs in diverse plant species—cont’d Targets miRNA

Plant

Target family

Oryza sativa

Name

Functional importance

References

GRF

LOC_Os01g32750, LOC_Os02g45570, LOC_Os04g51190, OsGRF6/7/8/9

Alkali and salt stress, floral organogenesis, inflorescence architecture, resistance to Magnaporthe oryzae

Gao et al. (2010, 2015), Liu et al. (2014b), and Chandran et al. (2018)

Medicago truncatula

GRF and bHLH

MtGRF1/2/3/4/5/6 and MtbHLH79

Mycorrhization and root development

Bazin et al. (2013)

Arabidopsis thaliana

LAC

AtLAC4

Lignin content and seed number

Wang et al. (2014b)

Oryza sativa

LAC

OsLAC

Panicle branching and yield

Zhang et al. (2013) and Swetha et al. (2018)

Populus trichocarpa

LAC

PtLAC1/2/13/18/21/ 26/30

Lignin content

Lu et al. (2013)

Salicornia europaea

LAC

Unigene16755

Salt tolerance

Feng et al. (2015)

Arabidopsis thaliana

SOD

AtCDS1/2

Oxidative, salt, ABA, and heat stress tolerance

Sunkar et al. (2006), Jagadeeswaran et al. (2009), Jia et al. (2009), and Guan et al. (2013)

Vitis vinifera

SOD

VvCSD1/2

Oxidative stress tolerance

Leng et al. (2017)

Medicago truncatula

COX5

MtCOX5b

Water-deficit responsive

Trindade et al. (2010)

Arabidopsis thaliana

PHO2

AtPHO2

Phosphate homeostasis

Bari et al. (2006) and Chiou et al. (2006)

Zea mays

PHO2

ZmPHO2

Phosphate homeostasis

Du et al. (2018)

Hordeum vulagre

PHO2

HvPHO2

Phosphate homeostasis

Hackenberg et al. (2013)

Triticum aestivum

PHO2

TaPHO2-A1

Phosphate homeostasis

Ouyang et al. (2016)

miR408

Triticum aestivum

TOC and CLP

TaTOC1/TaCLP1

Heading time and stripe rust resistance

Feng et al. (2013) and Zhao et al. (2016a)

miR444

Oryza sativa

MADS

OsMADS57

Tillering, nitrate signaling, and phosphate response

Guo et al. (2013) and Yan et al. (2014)

miR528

Oryza sativa

AO

OsAO

Antiviral defense

Wu et al. (2017)

miR529

Oryza sativa

SPL

OsSPL14/17

Vegetative and reproductive development

Wang et al. (2015b)

miR827

Oryza sativa

SPX

OsSPX-MFS1/2

Phosphate starvation

Lin et al. (2010)

miR1848

Oryza sativa

CYP and WS

OsCYP51G3 and OsWS1

Phytosterol, brassinosteroid, and wax biosynthesis

Xia et al. (2015a,b)

miR7695

Oryza sativa

NRAMP

OsNRAMP6

Pathogen resistance

Campo et al. (2013)

miR9863

Hordeum vulgare

MLA

HvMLA1

Disease resistance

Liu et al. (2014c)

miR397

miR398

miR399

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2 Contribution of miRNA-mediated regulation in plant growth and development 2.1 miRNA-mediated regulation of shoot meristem maintenance The activity of a few meristematic stem cells present in the shoot apical meristem (SAM) region results in the continuous production of new cells, which undergo differentiation over a period of time to produce different aerial parts of the plant (Laux and Mayer, 1998; Mayer et al., 1998; Barton, 2010). The role of protein-coding genes and phytohormonal crosstalk has been illustrated in maintaining the meristem function (Barton, 2010). Recently, the molecular role of some miRNAs has been shown to regulate SAM maintenance in plants (D’Ario et al., 2017). The function of two miRNAs (miR165/166 and miR394) has been shown in SAM maintenance in Arabidopsis thaliana (Emery et al., 2003; Prigge et al., 2005; Tang et al., 2003; Kim et al., 2005). In maize, miR166 cleaves ROLLED LEAF1, a HOMEODOMAIN-LEUCINE ZIPPER III (HD-ZIP III) family gene, on the adaxial side, and thus plays an important role in adaxial/abaxial patterning ( Juarez et al., 2004a,b). In rice, the proper activity of SHOOT ORGANIZATION (SHO) family genes, namely SHO1 and SHO2, is required for SAM formation during embryonic growth (Nagasaki et al., 2007). The altered spatial abundance and the expression of OsmiR166 and Os-HD-ZIP III in sho1-1 and sho2, respectively, primarily contributed to the abnormal embryonic growth (Nagasaki et al., 2007).

2.2 miRNA-mediated regulation of leaf growth and development miRNAs play key roles in regulating organ boundary establishment during the early stages of development. In this process, the miR164-mediated regulation of the NAC family CUP-SHAPED COTYLEDON1 (CUC1) and CUC2 plays a vital role (Aida et al., 1997; Takada et al., 2001; Mallory et al., 2004). NAC is a plant-specific TF family, and the name is derived from the NO APICAL MERISTEM (NAM) gene from Petunia hybrida and genes from Arabidopsis ATAF1/ATAF2 and CUC2. Seven genes of the GROWTH-REGULATING FACTOR (GRF) family are targeted by miR396 in Arabidopsis. GRFs show synergistic interaction with CUC genes to establish the organ boundary (Lee et al., 2015). Cells in the organ primordia undergo successive divisions and elongation, and finally, differentiate into specific cell types. Leaf morphogenesis is broadly classified into two main processes: leaf lamina outgrowth and leaf margin specification. miR319 targets TEOSINTE BRANCHED1, CYCLOIDEA, and PROLIFERATING CELL NUCLEAR ANTIGEN BINDING FACTOR (TCP) genes and plays a key role in modulating leaf morphogenesis. Seedlings with loss-of-function mutants of multiple TCP genes or constitutive expression of miR319 develop enlarged leaves with curly margins while the miR319-resistant version of TCP4 (mTCP4) transgenic seedlings produced smaller leaves (Efroni et al., 2008; Koyama et al., 2007, 2010). In a classic semidominant mutant lanceolate1 (la), the leaf shapes of tomato leaves change from large compound leaves to small simple leaves. The miR319-LA module imparts morphogenetic competence, which is required for leaf expansion along the developing leaf margin (Ori et al., 2007). The miR319-TCP module affects leaf growth further via regulating the activities of the miR164-CUC pathway. Leaf margins are primarily formed by the activity of CUC family genes (Bilsborough et al., 2011; Blein et al., 2008; Nikovics et al., 2006; Raman et al., 2008). Besides miR164, miR396 acts downstream of TCP genes. GRFs regulate cell proliferation and adaxial-abaxial polarity. A steady increase in miR396 levels and reductions in GRF levels were shown to reduce the growth rate from the proximal to the distal end of a leaf, which is primarily due to the reduced cell proliferation rates (Das Gupta and Nath, 2015; Rodriguez et al., 2010). So, fine-tuning the miR164-miR319-miR396 module holds great promise in optimizing the leaf shape and size across diverse crop plants.

2.3 miRNA-mediated regulation of root growth and development miRNAs play essential roles in regulating various aspects of root development (Meng et al., 2010). DCL1 and SE are key genes involved in miRNA biogenesis. In both null dcl and se mutants, the root meristematic fate is not established, thus highlighting the functional importance of miRNAs in regulating root development (Lobbes et al., 2006; Nodine and Bartel, 2010). In potatoes, fewer LRs are observed in the St-miR164 overexpression lines (Zhang et al., 2018a). Similarly, miR164 affects the abundance of ZmNAC1 in maize and contributes to the altered lateral root phenotype (Li et al., 2012). The phytohormone auxin plays an essential role in regulating diverse developmental processes across diverse plant species. AUXIN RESPONSE FACTORS (ARFs) are the key mediators of auxin response. During evolution, some members of the ARF family became targets of miRNAs, thus providing an additional layer of regulation to fine-tune the auxin response (Mutte et al., 2018). miR160 activity decides ARF10, ARF16, and ARF17 abundance while miR167 activity decides ARF6 and ARF8 levels to regulate adventitious root formation in Arabidopsis. The constitutive expression of miR160 leads to a shorter PR length, an increased LR number, and a defective root cap (Wang et al., 2005; Gutierrez et al., 2009). ARF6

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and ARF8 primarily affect flowering and the LR number (Wu et al., 2006; Gutierrez et al., 2012). miR167-mediated regulation of Gm-ARF6/8 is involved in LR development and nodulation in soybeans (Wang et al., 2015a). Auxin signaling is also affected by miR393 as its target genes, namely TRANSPORT INHIBITOR RESPONSE1 (TIR1), AUXIN SIGNALING F-BOX1 (AFB1), AFB2, and AFB3, play key roles in auxin perception. This module fine-tunes the auxin response in Arabidopsis, rice, barley, and sorghum. Ectopic overexpression of MIR393b results in altered primary and crown root architecture and flag leaf inclination in rice (Bian et al., 2012). The conserved role of miR160-miR167-miR393 and their targets in different crops indicates that tweaking the abundance of these miRNA(s) or selected target(s) is an excellent choice for those cultivars that show perturbed auxin response characteristics.

2.4 miRNA-mediated regulation of the vegetative-to-reproductive phase transition The transition from the vegetative to the reproductive phase is one of the key events during plant growth. The balanced activity of many protein-coding genes, miRNAs, and phytohormonal crosstalk directs the conversion of vegetative SAM to the floral meristem (Aichinger et al., 2012; Curaba et al., 2014; Pidkowich et al., 1999). The miR156-miR172 module plays a key role in phase transition. miR156 shows the highest expression during the juvenile phase and shows a steady decrease as plants mature while miR172 expression increases as plants progress from the juvenile stage to maturity (Luo et al., 2013; Poethig, 2009; Wu and Poethig, 2006). In Arabidopsis, the overexpression of miR156 stretches the juvenile growth phase, and thus, the plants show late flowering (Huijser and Schmid, 2011). In rice, Os-MIR171c affects the phase transition from the vegetative to the reproductive state by regulating the expression of HAM family (OsHAM1/2/3/4) genes (Fan et al., 2015). The constitutive overexpression of Hv-MIR171a causes late flowering, and thus, alters the vegetative to reproductive phase change progression in barley. Interestingly, the abundance of miR156 is also found to be elevated in Hv-MIR171a overexpression lines (Curaba et al., 2013). In the Brassicaceae family, miR824 regulates floral transition by regulating the abundance of AGAMOUS-LIKE16 (AGL16) (Hu et al., 2014). These reports highlight the functional importance of these miRNAs and their crosstalk with other miRNAs to regulate the phase transition in plants.

2.5 miRNA-mediated regulation of reproductive development and its improvement Reproductive development is a key phase of plant life where the genetic makeup is transferred to descendants. The role of many miRNAs has been shown in flower and seed development. The identities of four concentric whorls of organs (carpel, stamen, petal, and sepal) are specified by the activities of the floral homeotic TFs of A, B, and C-classes (Bowman et al., 1991; Coen and Meyerowitz, 1991). miR172 posttranscriptionally regulates the expression of APETALA2 (AP2), which is one of the key B-class genes (Chen, 2004). The constitutive expression of miR172 leads to the development of reproductive organs in places of the perianth tissue. Interestingly, ap2 mutants also show a similar phenotype, thus highlighting the functional importance of the miR172-AP2 module in floral patterning. AP2 and AGOMOUS (AG) act antagonistically, and reduced AP2 expression promotes the activity of AG (Wollmann et al., 2010). Functional studies in A. thaliana, Oryza sativa, Rosa chinensis, and Jatropha curcas show that miR172 plays a key role in flower development (Aukerman and Sakai, 2003; Zhu et al., 2009; Zhang et al., 2017a; Francois et al., 2018; Tang et al., 2018). The slow progression from spikelet meristem to floret meristem is observed in Os-MIR172b overexpression lines, thus affecting the floret development in rice (Zhu et al., 2009). Three miRNAs, namely Os-miR156, Os-miR172, and Os-miR529, regulate vegetative and reproductive development (Wang et al., 2015b). The ectopic overexpression of Gh-MIR157 resulted in smaller floral organs and decreased seed size in cotton (Liu et al., 2017). In rice, miR159 plays a vital role in floral organ development by posttranscriptionally regulating the expression of OsGAMYB and OsGAMYB-Like1 (Tsuji et al., 2006). In barley, HvGAMYB plays a key role in anther development (Murray et al., 2003). Apart from the regulation of heat stress response, the Ta-miR159TaGAMYB1 module plays a key role in anther development (Wang et al., 2012a). It has also been shown that the floral organs in carpels (foc) mutant has reduced expression of MIR160a, which leads to reduced fertility, irregular spacing between flowers, and narrow petal formation in Arabidopsis. Apart from vegetative growth, miR164 also regulates floral organ boundary establishment and seed development, as the constitutive expression of miR164 leads to the absence of petals as well as fused stamen and sepals (Laufs et al., 2004). The miR167-mediated regulation of ARF6 and ARF8 is quintessential for flower development in Arabidopsis and tomato (Wu et al., 2006; Liu et al., 2014a). The constitutive expression of miR167 leads to arrested ovule development, and thus imparts sterility (Wu et al., 2006). Recently, Yao and coworkers demonstrated the maternal control of miR167 in embryonic growth and development (Yao et al., 2019). Gao and coworkers reported that OsMIM396 lines produced altered inflorescence architecture, and OsGRF6 was found to be significantly upregulated in these lines (Gao et al., 2015). These reports show the importance of various

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miRNA-target modules in reproductive development and highlight the immense scope of utilizing this information for developing crop plants with improved reproductive traits.

2.6 miRNA-mediated regulation of seed development and germination Recent studies have shown that several miRNAs and their target genes have a function in seed development and germination across the major crop plants, including rice, wheat, maize, tomato, mustard, barley, and soybean. The miR159 family also has a profound effect on seed development, germination, dormancy, and seed size. The seeds of the miR159ab double mutant are of reduced size and asymmetrical shape. The miR159-mediated regulation of GAMYB-like genes, MYB33 and MYB65, plays a key role in floral development, fertility, and seed germination (Tsuji et al., 2006; Reyes and Chua, 2007; Sarkar Das et al., 2018; Alonso-Peral et al., 2010; Allen et al., 2007). miR172 positively regulates seed size through the downregulation of its target, AP2 in Arabidopsis. AP2 acts through the maternal genome to control seed weight, possibly by altering the sugar metabolism during seed development (Ohto et al., 2005). On the contrary, in rice, reduced seed weight was observed in the MIR172b overexpression lines (Zhu et al., 2009). Os-miR172, along with other miRNAs, also regulates panicle branching (Miura et al., 2010). miR156 enables proper embryonic patterning by preventing the precocious activity of the SQUAMOSA PROMOTER BINDING PROTEIN-LIKE10 (SPL10) and SPL11 transcription factors, which are known to promote differentiation (Nodine and Bartel, 2010). Os-miR156 regulates grain size, panicle branching, and tillering in rice by targeting multiple SPL genes such as OsSPL13, OsSPL14, and OsSPL16 (Miura et al., 2010; Jiao et al., 2010; Wang et al., 2012b). Both miR172 and miR156 have significant roles in seed germination and dormancy in studied crop species. These reports indicate the immense potential of the above-mentioned miRNA(s) and their target(s) in fine-tuning seed development in crops.

2.7 Role of miRNAs in improving crop yield and other agronomic traits In potatoes, the St-miR156-StSPL and St-miR172-StRAP1 modules regulate tuber development, and thus hold great promise in enhancing tuber yield (Bhogale et al., 2014). Wang and coworkers found that Os-miR156-mediated regulation of OsSPL16 plays an important role in controlling the grain shape, size, and quality in rice (Wang et al., 2012b). Quite interestingly, more tillers are produced in the ectopic overexpression lines of Os-miR393; however, these seedlings are less tolerant to salt and drought stresses (Xia et al., 2012). Gao and coworkers reported that OsMIM396 lines have an altered inflorescence architecture and OsGRF6 is found to be significantly upregulated in these lines (Gao et al., 2015). When OsmiR397 is overexpressed, the panicle branching and grain size are found to be increased, thus increasing the rice yield by 25% in field trials (Zhang et al., 2013). Because yield enhancement is one of the primary objectives of most plant breeding programs, there exists huge potential to generate high-yielding cultivars by specifically manipulating the activity of one or more MIRNA or target genes using precise genome editing technologies.

2.8 miRNA-mediated regulation involved in plant architecture improvement In rice, a quantitative trait locus called Ideal Plant Architecture1 (IPA1) dramatically improves the plant architecture. It was recently shown that Os-miR156 modulates the expression of OsSPL14 in the IPA1 locus ( Jiao et al., 2010). Maize architecture depends on repeating units called phytomers, which consist of the recurring units of the axillary meristem, leaf, and internode. miR156 plays an essential role in restricting the abundance of tasselsheath4 (tsh4), a SPB-box TF, to the bract region during early maize inflorescence patterning (Chuck et al., 2010). miR156 acts as a mobile signal and targets StSPL3/ 6/9/13 and StLIGULELESS1 to regulate plant architecture in potatoes (Bhogale et al., 2014). Tomato plants overexpressing miR156 have numerous leaves, reduced plant stature, and smaller fruit size. Based on these results, Zhang et al. hypothesized that tomato cultivars with reduced miR156 abundance could be developed for a shorter ripening period (Zhang et al., 2011a). In tomatoes, Sl-miR160 plays a vital role in controlling the blade outgrowth and early fruit development by inhibiting SlARF10 abundance (Hendelman et al., 2012). In rice, Os-miR160 targets OsARF18 and the rice seedlings expressing the resistant version of OsARF18 show many pleiotropic growth defects such as short stature, rolled leaves, and smaller seeds with less starch content (Huang et al., 2016). The overexpression of miR171 in tomatoes affects multiple agronomic traits such as plant height, leaf shape, root architecture, flowering time, and fruit development (Huang et al., 2017). The above reports suggest that tweaking the miRNA-mediated regulation of target genes can be used to improve the desired agronomic trait.

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2.9 Role of miRNAs in acclimatization of plant growth to diverse environmental stresses The functional importance of many miRNAs has also been studied in crop plants in response to various abiotic stresses. In wheat, Ta-miR159 overexpression lines showed more sensitivity to heat stress (Wang et al., 2012a). So, heat-tolerant wheat cultivars could be generated by decreasing the abundance of miR159 without curtailing the normal growth and development. In beetroot, Bv-miR160-BvARF17/18 and Bv-miR164-BvNAC21 modules are involved in salt stress adaptation (Cui et al., 2018). The miR160-ARF10 module plays a key role in maintaining water balance in the tomato leaf, as the leaf shape, stomata size, and number are changed in the mSlARF10 lines (Damodharan et al., 2016; Liu et al., 2016). Viral and fungal infections and cold stress result in increased Sl-MIR167a levels while heat, drought, and salt decrease their abundance in tomatoes ( Jodder et al., 2018). In another report, Zhang and coworkers demonstrated that miR169 overexpression lines showed better tolerance to drought stress conditions in tomatoes (Zhang et al., 2011b). These reports suggest that the miR160-miR167-miR169 module could be selectively modulated to generate better tomato cultivars. In rice, OsmiR164-OsOMTN and Os-miR166-OsHB4 modules are involved in drought stress, and the Os-miR169-OsNUCLEAR FACTOR-YA (OsNF-YA) module imparts immunity and provides tolerance to salt stress (Fang et al., 2014; Zhang et al., 2018b). Os-miR393-Os-TIR1/AFB and Os-miR396-OsGRFs modules are involved in modulating alkaline, salt, and salinity stress responses (Gao et al., 2011, 2010). Interestingly, the Hv-miR393-HvTIR1/AFB2 module alters RSA in response to aluminum stress in barley (Bai et al., 2017). In soybeans, the Gm-miR166-GmHD-ZIP III module imparts cold acclimatization while Gm-miR169-GmNF-YA3 imparts drought tolerance (Zhang et al., 2014; Ni et al., 2013). In glasswort, the Se-miR397-LAC module confers salt stress tolerance (Feng et al., 2015). In grapes, the Vv-miR398VvCOPPER SUPEROXIDE DISMUTASE1/2 (VvCSD1/2) module regulates the oxidative stress tolerance response while in Medicago trunculata, the abundance of Mt-miR398 was upregulated in water deficit conditions (Leng et al., 2017; Trindade et al., 2010). The miR399-PHO2 module regulates phosphate homeostasis in maize, barley, and wheat (Bari et al., 2006; Du et al., 2018; Hackenberg et al., 2013; Ouyang et al., 2016). These studies indicate that it is possible to improve the stress adaptation of diverse crop plants by altering the tissue-specific transcriptome signature through the miRNA-mediated modulation of target genes.

2.10 miRNA-mediated regulation of host-partner relationships in crop plants Multiple miRNA-target modules are shown to be involved in enhancing the host-partner relationship. In the common bean, MIR172c expression increased after rhizobium infection, continued to increase until the nodule maturation stage, and started to decrease in the senescing nodules (Nova-Franco et al., 2015). In soybeans, miR156, miR160, miR167, and miR172 play key roles in regulating nodulation by regulating their target genes (Wang et al., 2014a, 2015a; Yan et al., 2013; Turner et al., 2013; Nizampatnam et al., 2015). In M. trunculata, Mt-miR169 activity restricts the MtHAP2-1 expression to the nodule meristematic zone, and thus plays a key role in regulating nodule cell differentiation (Combier et al., 2006). Apart from nodulation, the functional relevance of miR171 and miR396 has been linked with the mycorrhization processes in M. trunculata (Lauressergues et al., 2012; Couzigou et al., 2017). The ectopic expression of miR156 not only resulted in plant architecture changes but also repressed the nodule formation in Lotus japonicus (Wang et al., 2015c). Interestingly, miR172 showed expression in the epidermal cells primed for bacterial infection and was thus involved in the nodulation process (Holt et al., 2015). The activities of the miR156-miR172 module offer the possibility to fine-tune their interplay to improve the plant architecture and nitrogen fixation in L. japonicus and beyond. Altogether, these reports highlight the prospects of engineering the activity of selected miRNA(s)-target(s) modules for improving the symbiotic nitrogen fixation efficiency in legumes.

2.11 miRNA-mediated regulation of disease resistance in crop plants The infection of a cell or tissue by a pathogen often alters the expression of the selected TFs and phytohormone response, which in turn changes the transcriptome signature of that cell/tissue. Many miRNAs have also been reported to be involved in this process. In Arabidopsis, the miR164-NAC4 module is involved in promoting pathogen-induced cell death (Lee et al., 2017). A novel target of Ta-miR164 called TaNAC21/22 has been identified, and it negatively regulates stripe rust virus resistance in wheat (Feng et al., 2014). In rice, higher Os-MIR171a levels likely provide tolerance to the rice stripe virus (RSP) infection (Tong et al., 2017). Apart from miRNAs, the AGO protein shows some specificity to certain miRNAs and is involved in innate immunity responses. Upon Pseudomonas syringae pv. tomato (Pst) infection, AGO2 loads mature miR393 produced from the MIR393b gene and directs the cleavage of MEMBRIN12 (MEMB12) (Zhang et al., 2011c). When infected by apple leaf spot fungus, Alternaria alternaria f. sp. mali (ALT1), many miRNAs are induced in the apple,

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and it has been shown that improved resistance against ALT1 could be achieved by decreasing the abundance of two miRNAs, Md-miR156 and Md-miR395 (Zhang et al., 2017b). In rice, miR528 negatively regulates the viral response by cleaving L-ascorbate oxidase (AO), resulting in low AO-dependent accumulation of reactive oxygen species (ROS). Upon viral infection, miR528 gets selectively bound to the RISC complex constituting AGO18, which is a cleavagedefective AGO protein, thus elevating the ROS response and providing higher antiviral resistance (Wu et al., 2017). This suggests the importance of identifying such specific interactions underlying disease resistance and fine-tuning the modules to achieve tolerance to plant pathogens.

3 Use of computational biology in advancing plant miRNA research in crop plants Several machine-learning approaches have been developed for the identification of novel miRNAs starting from experimental data obtained through next-generation sequencing (NGS). A generalized strategy for miRNA analysis involves the retrieval of datasets, a search of background knowledge, alignment, identification, and the characterization of known and novel miRNAs, followed by target prediction and downstream analyses. Initially, homology searches were used in phylogenetically close species to identify orthologs and paralogs of known miRNA genes. In plants, this was specifically in vogue, and comparative systemic analyses of miRNomes were conducted among the related species A. thaliana and A. lyrata using whole genomes as well as small RNA sequencing data. Such approaches further reveal the limitations of homology searches for novel miRNA identification due to the lack of overlapping miRNomes, even in closely related species (Chavez Montes et al., 2014). The focus of computational methods thus shifted to the identification of miRNA precursors, made possible through advanced machine-learning-based approaches such as Mireval and MirPara, which could fold the input sequence to determine if the folding structure could be an miRNA precursor (Ritchie et al., 2008; Wu et al., 2011). The next step was the utilization of NGS in the programs miR-BAG and miRDeep, which could map the NGS reads back to the potential precursor ( Jha et al., 2012; Friedlander et al., 2008). Recently, miRDeep has been upgraded to miRDeep-P2, which has updated annotation criteria as well as better scoring and analysis speed (Kuang et al., 2018). Extensive datasets of plant small RNAs can indeed be obtained from NGS; however, these produce abundant miRNA annotations, which may be questionable due to the erroneous annotation of siRNAs as miRNAs (Axtell and Meyers, 2018). Hence, the “big data era” requires a trustworthy web-based ensemble that emphasizes the criteria of minimal false positives. ShortStack provides such comprehensive annotation by analyzing a reference-aligned small RNA-seq sample by defining de novo small RNA clusters and annotating hairpin-associated loci. It involves “phasing” to check for the repetitive arrangement of aligned small RNAs, thus allowing a flexible, user-friendly interface for the analysis of small RNA size composition, strandedness, and repetitiveness (Axtell, 2013b). Various bioinformatic tools used in miRNA research have been listed in Table 2.

4 Technology advancements 4.1 Recent advancements in miRNA profiling and validation Owing to the immense potential of miRNAs in key developmental aspects of both animals and plants, miRNA detection and quantification is an exciting area of research. Recently, the multiplexed northern technique has been reported, where two DNA hairpins (HP1 and HP2) were used that coexist in the metastable state in the absence of the nucleic acid (NA) initiator TABLE 2 Compendium of bioinformatic tools used in miRNA research. Tool name

Application in plant miRNA analysis

Link

References

MiPred

Classification of real and pseudo miRNA precursors

http://server.malab.cn/MiPred/

Jiang et al. (2007)

miRCat2

Entropy-based detection of miRNA loci from NGS

http://srna-workbench.cmp.uea.ac.uk/ mircat2/

Paicu et al. (2017)

miRanalyzer

Prediction of novel miRNAs, analysis of deep sequencing

http://bioinfo2.ugr.es/miRanalyzer/ standalone.html

Hackenberg et al. (2009) Continued

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TABLE 2 Compendium of bioinformatic tools used in miRNA research—cont’d Tool name

Application in plant miRNA analysis

Link

References

MicroPC

Exclusive resource of plant miRNA and their targets from EST analysis

http://www3a.biotec.or.th/micropc/

Mhuantong and Wichadakul (2009)

miRDeep-P

miRNA transcriptome analysis in plants

https://sourceforge.net/projects/mirdp/

Kuang et al. (2018) and Yang and Li (2011)

miRNAFold

miRNA precursor identification, hairpin structure prediction

https://evryrna.ibisc.univ-evry.fr/ evryrna/mirnafold/mirnafold_home

Tav et al. (2016)

miRDeep∗

Pre-miRNA secondary structure calculation, precise identification from RNAseq

http://www.australianprostatecentre. org/research/software/mirdeep-star

An et al. (2013)

miReader

Mature miRNA detection without genomic sequence reference

http://scbb.ihbt.res.in/2810-12/ miReader.php

Jha and Shankar (2013)

miRPlex

miRNA prediction from sRNA dataset

https://www.uea.ac.uk/computing/ mirplex

Mapleson et al. (2013)

miRPlant

Exclusive plant miRNA detection from RNAseq

https://sourceforge.net/projects/ mirplant/

An et al. (2014)

Mirnovo

Identification of novel miRNA from small RNAseq

http://wwwdev.ebi.ac.uk/enright-dev/ mirnovo/

Vitsios et al. (2017)

microRPM

Identification of novel miRNA from NGS without overfitting

http://microrpm.itps.ncku.edu.tw/

Tseng et al. (2018)

miRDeep-P2

Filterning strategy in miRNA transcriptome analysis in plants

https://sourceforge.net/projects/ mirdp2/

Kuang et al. (2018)

Shortstack

Identification of novel miRNA from small RNAseq

https://github.com/MikeAxtell/ ShortStack

Axtell (2013b)

TargetFinder

Prediction of small RNA binding sites on target transcripts

https://github.com/carringtonlab/ TargetFinder

Bo and Wang (2005)

miRTarBase

Extensive database of miRNA-target interactions

http://mirtarbase.mbc.nctu.edu.tw/php/ index.php

Hsu et al. (2011)

psRNATarget

Exclusive plant sRNA target analysis through target site accessibility

http://plantgrn.noble.org/psRNATarget/

Dai and Zhao (2011)

ViennaRNA

Prediction of RNA secondary structure

http://rna.tbi.univie.ac.at/

Lorenz et al. (2011)

miRBase

Archive of miRNA sequence and annotation

http://www.mirbase.org/

Griffiths-Jones et al. (2006)

Bowtie

Short-read aligner

http://bowtie-bio.sourceforge.net/

Langmead (2010)

Transmir

Database of transcription factor-miRNA regulations

http://www.cuilab.cn/transmir

Wang et al. (2010b)

miRNEST

Integrative resource of miRNA-associated data

http://rhesus.amu.edu.pl/mirnest/copy/

Szczesniak et al. (2012)

Chimira

Detection of miRNA modification

http://wwwdev.ebi.ac.uk/enright-dev/ chimira/

Vitsios and Enright (2015)

sequence. This technique is called hybridization chain reaction (HCR), and it uses fluorescence chemistry to detect multiple miRNAs in a single reaction (Schwarzkopf and Pierce, 2016). MicroRNA profiling using the miR-microarray provides poor selectivity because of the small size of mature miRNA and the high sequence resemblance. Alhasan et al. reported a novel technique called Scanometric MicroRNA (Scano-miR) array profiling in which miRNAs are enzymatically ligated to the universal linker probe onto which binds the universal SNA-functionalized gold nanoparticle

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conjugates (SNA-AuNPs) (Alhasan et al., 2012). In a recent review, recent advancements in miRNA profiling and detection have been discussed (Cheng et al., 2018). The routinely used, real-time quantitative reverse transcription PCR (qRT-PCR) technique is slightly modified to study the expression profiling of mature miRNAs, as the size of mature miRNAs is very small (20–24 nt). A stem-loop primer was designed in such a way that 5–6 nt of this primer had perfect complementarity with the 30 -end of the targeted mature miRNA (Chen et al., 2005). Until now, this method was widely used to study the expression profiling of candidate miRNAs across diverse plant and animal species. Recently, the ligation-based PCR assay has been shown to detect miRNAs with high specificity. In this method, the PCR template is generated by using T4 RNA ligase 2, which ligates the two DNA probes that bind to the target miRNA. The ligation-dependent method does not require reverse transcription components and is cost-effective (Zhang et al., 2011d).

4.2 Applications of genome editing technology in miRNA-mediated crop improvement Unlike protein-coding genes, the small size of functional miRNAs (20–22 nt), their biogenesis mostly from multiple similar gene transcripts, and the strong correlation of their sensitivity to the target sequence with sequence variation pose technical challenges in the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9-based genome editing of miRNA regulation. Three derivative strategies have been designed to overcome these problems. In the first strategy, Li and coworkers used a pair of sgRNAs that targets the adjacent intronic region and a donor DNA template that possesses the same pair of sgRNA sites to replace the desired stretch using the nonhomologous end joining (NHEJ)-based CRISPR-Cas9 system. This approach can be used to replace the targeted region and insert exogenous DNA sequences into specific genomic positions (Li et al., 2016). In the second strategy, the CRISPR-Cas9 nickase-cytidine deaminase fusion is used to specifically change cytosine to thymine, present in the 3–9 nt spanning region from the PAM site (Zong et al., 2017). In the third strategy, two guide RNAs (gRNA) are used in which the first gRNA targets the promoter region of the targeted MIRNA and the other gRNA targets the downstream region of the stem-loop, thereby deleting the targeted MIRNA gene (Gao et al., 2016). Some examples where the CRISPR/Cas9 approach has been used to modify the functionality of selected miRNA(s) are discussed to demonstrate the strength and practical limitations of this method to generate stable miRNA knock out/down plants. By using the first strategy, Zhao and coworkers removed MIR169a and MIR827a by designing sgRNAs that target the two ends (50 and 30 ) of these miRNAs and found stable mutant plants in Arabidopsis (Zhao et al., 2016b). In another study, the functional importance of some key genes involved in grain number, grain size, panicle, and plant architecture modulation have been reevaluated by using the CRISPR-Cas9 approach. Quite interestingly, it was observed that if the CRISPR-Cas9 directed mutation disrupts the Os-miR156 binding site, then fewer tillers were developed in the ipa1 mutant, and when CRISPR-Cas9 directed mutation does not disrupt the Os-miR156 binding site, then more tillers were produced in the ipa1 mutant (Li et al., 2016). Such studies show the immense potential of miRNA-mediated regulation in modulating tiller architecture in rice. Similar relationships might also be present in other crop plants, meaning that the CRISPR-Cas9 approach holds great promise in designing better crop plants. Although CRISPR-Cas9-based genome editing is a technological breakthrough in the present scenario, proper care should be taken while designing sgRNAs, as off-targets pose a major limitation and not every gene or region can be efficiently targeted due to the lack of highly specific sgRNAs in the desired location (Tang and Chu, 2017; Zhou et al., 2017).

5 Conclusion and future perspectives The continuous increase in food demand and unpredictable variations in environmental conditions due to climate change have increased the depletion rate of natural resources, as we have to add more fertilizers (mainly enriched in nitrogen, phosphorus, and potassium) to maintain the continuous supply of food. In such a scenario, plant scientists are exploiting every possible approach to increase the yield and improve plant fitness against pathogenic invasions and harsh environmental conditions. Based on the above reports, we infer that miRNAs act as an additional layer of regulation to fine-tune the expression of their target gene(s). It has been shown that miRNAs play key roles in modulating diverse processes such as plant architecture modulation, organ growth, and phase yield improvement. In many instances, altered miRNA activity causes several pleiotropic defects. Therefore, it becomes imperative to use precise genome editing technologies such as CRISPR-Cas9 to fine-tune the abundance of miRNA(s) and their target(s). Because many miRNAs are produced from multiple independent genes, the CRISPR-Cas9 based approach can be used to selectively alter the activity of one or more MIRNA gene(s). By doing so, the transcript abundance of their target gene(s) can be specifically fine-tuned, thus affecting the expression dynamics of downstream pathway genes. However, there exist some practical challenges of precise gene editing through CRISPR-Cas9 in most crop plants such as the lack of an efficient transformation protocol and functional

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reports highlighting the role of specific miRNAs across diverse crop plants (Altpeter et al., 2016). So, further functional studies highlighting the role of uncharacterized miRNAs in different crops should be undertaken to decipher their molecular role. miRNAs or target edited engineered plants can be introgressed into desired crop cultivars for their improvement. Additionally, miRNA-based markers can be developed for better marker-assisted selection of desired agronomic traits in crop plants.

Acknowledgments We would like to acknowledge Dr. Soumitra Paul and Dr. Mehanathan Muthamilarasan for critical reading of the manuscript and valuable comments. The research in the AKS laboratory is supported by the SERB-DST project (EMR/2016/002438), the DBT project (BT/PR12766/BPA/ 188/63/2015), and internal funding from NIPGR. SY, PK, and VM are thankful to UGC, CSIR, and DBT, respectively, for financial assistance. We would also like to acknowledge DELCON for providing access to research articles.

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Xia, K., Ou, X., Gao, C., Tang, H., Jia, Y., Deng, R., Xu, X., Zhang, M., 2015b. OsWS1 involved in cuticular wax biosynthesis is regulated by osamiR1848. Plant Cell Environ. 38, 2662–2673. Yan, Z., Hossain, M.S., Wang, J., Valdes-Lopez, O., Liang, Y., Libault, M., Qiu, L., Stacey, G., 2013. miR172 regulates soybean nodulation. Mol. PlantMicrobe Interact. 26, 1371–1377. Yan, Y., Wang, H., Hamera, S., Chen, X., Fang, R., 2014. miR444a has multiple functions in the rice nitrate-signaling pathway. Plant J. 78, 44–55. Yang, X., Li, L., 2011. miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants. Bioinformatics 27, 2614–2615. Yao, X., Chen, J., Zhou, J., Yu, H., Ge, C., Zhang, M., Gao, X., Dai, X., Yang, Z.N., Zhao, Y., 2019. An essential role for miRNA167 in maternal control of embryonic and seed development. Plant Physiol. Yu, N., Niu, Q.W., Ng, K.H., Chua, N.H., 2015. The role of miR156/SPLs modules in Arabidopsis lateral root development. Plant J. 83, 673–685. Yuan, N., Yuan, S., Li, Z., Li, D., Hu, Q., Luo, H., 2016. Heterologous expression of a rice miR395 gene in Nicotiana tabacum impairs sulfate homeostasis. Sci. Rep. 6, 28791. Zhang, X., Zou, Z., Zhang, J., Zhang, Y., Han, Q., Hu, T., Xu, X., Liu, H., Li, H., Ye, Z., 2011a. Over-expression of sly-miR156a in tomato results in multiple vegetative and reproductive trait alterations and partial phenocopy of the sft mutant. FEBS Lett. 585, 435–439. Zhang, X., Zou, Z., Gong, P., Zhang, J., Ziaf, K., Li, H., Xiao, F., Ye, Z., 2011b. Over-expression of microRNA169 confers enhanced drought tolerance to tomato. Biotechnol. Lett. 33, 403–409. Zhang, X., Zhao, H., Gao, S., Wang, W.C., Katiyar-Agarwal, S., Huang, H.D., Raikhel, N., Jin, H., 2011c. Arabidopsis Argonaute 2 regulates innate immunity via miRNA393(*)-mediated silencing of a Golgi-localized SNARE gene, MEMB12. Mol. Cell 42, 356–366. Zhang, J., Li, Z., Wang, H., Wang, Y., Jia, H., Yan, J., 2011d. Ultrasensitive quantification of mature microRNAs by real-time PCR based on ligation of a ribonucleotide-modified DNA probe. Chem. Commun. (Camb.) 47, 9465–9467. Zhang, Y.C., Yu, Y., Wang, C.Y., Li, Z.Y., Liu, Q., Xu, J., Liao, J.Y., Wang, X.J., Qu, L.H., Chen, F., et al., 2013. Overexpression of microRNA OsmiR397 improves rice yield by increasing grain size and promoting panicle branching. Nat. Biotechnol. 31, 848–852. Zhang, S., Wang, Y., Li, K., Zou, Y., Chen, L., Li, X., 2014. Identification of cold-responsive miRNAs and their target genes in nitrogen-fixing nodules of soybean. Int. J. Mol. Sci. 15, 13596–13614. Zhang, H., Zhang, J., Yan, J., Gou, F., Mao, Y., Tang, G., Botella, J.R., Zhu, J.K., 2017a. Short tandem target mimic rice lines uncover functions of miRNAs in regulating important agronomic traits. Proc. Natl. Acad. Sci. U. S. A. 114, 5277–5282. Zhang, Q., Li, Y., Zhang, Y., Wu, C., Wang, S., Hao, L., Wang, S., Li, T., 2017b. Md-miR156ab and Md-miR395 target WRKY transcription factors to influence apple resistance to leaf spot disease. Front. Plant Sci. 8, 526. Zhang, L., Yao, L., Zhang, N., Yang, J., Zhu, X., Tang, X., Calderon-Urrea, A., Si, H., 2018a. Lateral root development in potato is mediated by Stu-mi164 regulation of NAC transcription factor. Front. Plant Sci. 9, 383. Zhang, J., Zhang, H., Srivastava, A.K., Pan, Y., Bai, J., Fang, J., Shi, H., Zhu, J.K., 2018b. Knockdown of rice MicroRNA166 confers drought resistance by causing leaf rolling and altering stem Xylem development. Plant Physiol. 176, 2082–2094. Zhao, B., Ge, L., Liang, R., Li, W., Ruan, K., Lin, H., Jin, Y., 2009. Members of miR-169 family are induced by high salinity and transiently inhibit the NFYA transcription factor. BMC Mol. Biol. 10, 29. Zhao, M., Ding, H., Zhu, J.K., Zhang, F., Li, W.X., 2011. Involvement of miR169 in the nitrogen-starvation responses in Arabidopsis. New Phytol. 190, 906–915. Zhao, X.Y., Hong, P., Wu, J.Y., Chen, X.B., Ye, X.G., Pan, Y.Y., Wang, J., Zhang, X.S., 2016a. The tae-miR408-mediated control of TaTOC1 genes transcription is required for the regulation of heading time in wheat. Plant Physiol. 170, 1578–1594. Zhao, Y., Zhang, C., Liu, W., Gao, W., Liu, C., Song, G., Li, W.X., Mao, L., Chen, B., Xu, Y., et al., 2016b. An alternative strategy for targeted gene replacement in plants using a dual-sgRNA/Cas9 design. Sci. Rep. 6, 23890. Zhao, Y., Wang, S., Wu, W., Li, L., Jiang, T., Zheng, B., 2018. Clearance of maternal barriers by paternal miR159 to initiate endosperm nuclear division in Arabidopsis. Nat. Commun. 9, 5011. Zhou, G.K., Kubo, M., Zhong, R., Demura, T., Ye, Z.H., 2007. Overexpression of miR165 affects apical meristem formation, organ polarity establishment and vascular development in Arabidopsis. Plant Cell Physiol. 48, 391–404. Zhou, J., Deng, K., Cheng, Y., Zhong, Z., Tian, L., Tang, X., Tang, A., Zheng, X., Zhang, T., Qi, Y., et al., 2017. CRISPR-Cas9 based genome editing reveals new insights into microRNA function and regulation in rice. Front. Plant Sci. 8, 1598. Zhu, Q.H., Upadhyaya, N.M., Gubler, F., Helliwell, C.A., 2009. Over-expression of miR172 causes loss of spikelet determinacy and floral organ abnormalities in rice (Oryza sativa). BMC Plant Biol. 9, 149. Zong, Y., Wang, Y., Li, C., Zhang, R., Chen, K., Ran, Y., Qiu, J.L., Wang, D., Gao, C., 2017. Precise base editing in rice, wheat and maize with a Cas9cytidine deaminase fusion. Nat. Biotechnol. 35, 438–440.

Chapter 4

Modern tools in improving rice production Neetu Verma and Alok Krishna Sinha National Institute of Plant Genome Research, New Delhi, India

1 Introduction Rice (Oryza sativa L.) is a staple food crop that is an important source of energy supply for more than half the world’s population. The rice crop is cultivated worldwide due to its ability to survive in diverse geographical locations. India and China are the largest producers of rice and account for 50% of the rice grown worldwide. Rice is considered the world’s strategic crop in terms of food security, as it provides 50% of the dietary caloric supply for millions of people living in poverty in Asia (Perez et al., 2014). The increase in crop productivity provided by the green revolution fulfilled the food demand of a booming world population for many decades after World War II. Since then, the yield potential of recent rice cultivars has been increased a little. Approximate 450–480 million tons of rice are produced annually while the demand is expected to exceed 650 million tons in 2050 (Mosleh et al., 2015). In the recent time of increasing world population, improvement in rice crop yield is the biggest challenge to save the world, especially the third world, from famine. In addition to that, climate change is also a factor that threatens to decrease the crop yield due to more instances of natural calamity such as droughts and floods. In this scenario, there is an urgent requirement for modern tools and technologies that could enable plant biologists to develop new varieties with improved yields and higher resistance against biotic and abiotic stresses. This chapter compiles recent updates as well as the potential of some new tools and techniques that could be applied to improve rice production in the future.

2 Bioinformatic tools Bioinformatic tools and different web databases provide a vast array of information about the plant genome, which is required for designing a good research methodology for crop improvement. The genome sequencing projects of agronomically important crops, including rice, have been completed and can be utilized as gateways to advanced research. Comparisons of genome sequences of different crops can detect the conserved regions among crops. Thus, this information can be utilized to design a common strategy to improve crop yield. A number of bioinformatic databases are available in rice such as genome sequences, genome annotation, gene expression, transcriptomes, proteomes, and metabolomes (Table 1). These databases could be used to dissect the functional genes and related regulatory pathways associated with important agronomic traits in rice. For example, the rice genome assembly and annotation information can be extracted from the MSU Rice Genome Annotation Project (Ouyang et al., 2007; Yuan et al., 2005), the Oryza Genome Evolution (OGE) Project (http://oge.gramene.org), and the International Rice Genome Sequencing Project (IRGSP) (Ohyanagi et al., 2006; Sakai et al., 2013). A database of T-DNA gene activation (AC)/gain-of-function and knock out (KO)/loss of function mutant populations was developed (http://signal.salk.edu/RiceGE/Rice). It can be used as a powerful genetic tool for functional characterization and trait identification by a forward genetic approach, offering valuable platforms for high-throughput functional genomics research in rice (Lo et al., 2016). Some web-based bioinformatic tools can be used to analyze large datasets, thus enabling one to design further experiments. Two widely used tools for high-throughput bioinformatics analysis are CyVerse (Devisetti et al., 2016) and Galaxy (Afgan et al., 2016; Børnich et al., 2016). Another platform to perform a comparative genomics study is CoGe, in which an open-ended network of interconnected tools is available to analyze the next-generation sequencing data (https:// genomevolution.org/coge/) (Lyons et al., 2008).

Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00004-8 © 2020 Elsevier Inc. All rights reserved.

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TABLE 1 Genomic databases and bioinformatic tools used to extract information about the rice genome. Database name

Description

URL

Rice Genome Knowledge Base (RGKBase)

Annotation database for rice comparative genomics

http://rgkbase.big.ac.cn/RGKBase

IC4R

Comprehensive database

http://ic4r.org/

MSU Rice Genome Annotation Project

Sequences and annotation data for the rice genome

http://rice.plantbiology.msu.edu

RiceGeneThresher

Comprehensive database

http://rice.kps.ku.ac.th/

RICD

Rice indica cDNA database

http://202.127.18.221/ricd/index.html

RiceFREND

Gene coexpression database

http://ricefrend.dna.affrc.go.jp/

TIGR

Genome annotation

http://rice.plantbiology.msu.edu/

BGI-RIS

Genome annotation

http://rise2.genomics.org.cn/

RAP-DB

Genome annotation

http://rapdb.dna.affrc.go.jp/

RIGW

Genome annotation

http://rice.hzau.edu.cn/rice/

OGRO

Genome annotation

http://qtaro.abr.affrc.go.jp/ogro

OGE Gramene

Displays the most updated version of Oryza Genome Evolution (OGE)

http://oge.gramene.org

RiceNet

Genome-scale gene network

http://www.inetbio.org/ricenet/

IRRI

Germplasm and natural variation of rice

http://irri.org/

MCDRP

Rice protein database

http://www.genomeindia.org/ biocuration/

RiceCye

Information about metabolic pathways

http://pathway.gramene.org/gramene/ ricecyc.shtml

PmiRKB

MiRNA databases

http://bis.zju.edu.cn/pmirkb/

Oryzabase

Phenotype description and classification of rice

http://shigen.nig.ac.jp/rice/oryzabase/

PRIN

Protein interaction databases

http://bis.zju.edu.cn/prin/

RKD

Protein kinase database

http://ricephylogenomics.ucdavis.edu/ kinase/

RiceXPro

Rice expression profile database

http://ricexpro.dna.affrc.go.jp/

ROAD

Rice expression profile database

http://www.ricearray.org/

CREP

Rice expression profile database

http://crep.ncpgr.cn/

RiceVarMap

Rice genomic variations database

http://ricevarmap.ncpgr.cn/

OryGenesDB

Rice mutant resource database

http://orygenesdb.cirad.fr/

POSTECH RISD

Rice mutant resource database

http://www.postech.ac.kr/life/pfg/risd/

RMD

Rice mutant resource database

http://rmd.ncpgr.cn/

RPAN

Rice pan-genome database

http://cgm.sjtu.edu.cn/3kricedb/

Oryza PG-DB

Rice proteogenomic database

http://oryzapg.iab.keio.ac.jp/

Phospho Rice

Rice-specific phosphorylation sites

http://bioinformatics.fafu.edu.cn/ PhosphoRice

HapRice

SNP haplotype database

http://qtaro.abr.affrc.go.jp/

RiTE-db

Transposon database

http://www.genome.arizona.edu/cgibin/rite/index.cgi

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3 Genome-wide association studies (GWAS) Tremendous efforts have been made in the past decades to resolve the individual QTLs into their contributing genes. Although, dissecting these QTLs using linkage mapping has been a great challenge because the mapping populations of random rice accessions have much higher recombination frequencies. With the onset of high-throughput sequencing technologies, GWAS can be used as a new and promising tool for dissecting these QTLs of complex agronomic traits of rice. Genetically diverse germplasms are used to perform association analysis between important agronomic traits and whole genome genotypes. The genotypes that are frequently used to dissect complex agronomic traits in rice are classified into SNP array genotypes and resequenced SNP genotypes. A total of 3.6 million SNPs were identified by sequencing 517 japonica and indica rice cultivars (Huang et al., 2010). GWAS was conducted with 950 varieties to identify 32 new loci for the flowering time and grain-related traits (Huang et al., 2012). A total of 1495 elite hybrid rice varieties and their inbred parental lines were used for a large-scale GWAS to identify 130 associated loci for 38 agronomic traits (Huang et al., 2015). This study provided a comprehensive view of heterosis from different hybrid combinations. Whole genome sequencing of the 176 varieties was carried out to generate a set of 426,337 SNPs and 67,544 InDels (Yano et al., 2016). The GWAS performed on this SNP set identified four new genes associated with agronomic traits. An association study was performed to dissect the four traits—amylose content (AC), gel consistency (GC), gelatinization temperature (GT), and protein content (PC)—using a diverse panel of 258 accessions from the 3K Rice Genome Project (Wang et al., 2017). A GWAS study performed with 22,488 high-quality SNPs identified 19 QTLs associated with these four traits. Nine candidate genes affecting four important QTL regions controlling AC, GC, GT, and PC were identified by combining gene-based association study and haplotype analyses (Wang et al., 2017). This work presents a good example of dissecting agronomically important complex traits into individual candidate genes by GWAS and gene-based association analysis, followed by haplotype analysis. Recently, GWAS was performed on a multiparent advanced generation intercross (MAGIC) population that was generated by a cross between multiple parents (Zhou et al., 2018). Two main rice varieties, indica and japonica, were used to generate a MAGIC population in rice (Bandillo et al., 2013). Higher genotypic diversity and reduced linkage drag are the advantages of using MAGIC populations over the biparental populations (Zhou et al., 2018). The accumulation of new genomic sequencing data and the development of several statistical methods will enable us to identify more and more loci associated with agronomically important traits by GWAS. The identified genes will serve as a valuable source for the functional characterization and genetic improvement of rice agronomic qualities.

4 Use of molecular markers in rice yield improvement Molecular markers are DNA sequences that can be identified by analyzing the polymorphism in the nucleotide sequences of different plants. Various types of DNA molecular markers were identified and used successfully in breeding many agricultural crops. An earlier rice breeding using molecular markers was the introgression of the Submergence 1A (Sub1A) gene into high-yielding rice varieties (Septiningsih et al., 2009; Iftekharuddaula et al., 2012). The Sub1A gene encodes an ethylene response factor that provides tolerance to submergence by restricting shoot elongation (Singh and Sinha, 2016). Drought stress is one of the major abiotic stresses that decreases the rice yield significantly. Molecular breeding strategies have not been very effective to generate drought-resistant rice varieties to date. Sahebi et al. (2018) proposed the use of three approaches—population development, physiological analysis, and the use of marker-assisted selection—to screen QTLs for drought tolerance. With the advancement of genome sequencing and large-scale EST analysis tools in rice, molecular markers associated with agronomic traits can be extracted very efficiently and used in breeding to enhance the crop yield. Genomes of japonica and indica rice were aligned to generate DNA polymorphism datasets (Han and Xue, 2003; Shen et al., 2004). Many databases are available to provide information on the molecular markers of various plant species. Plant marker databases store the information of predicted molecular markers such as SSR and SNP markers of different plant species (Heesacker et al., 2008). High yield is the most important criteria of a rice breeding program. Rice breeding to enhance the yield using molecular markers will be the main focus of rice breeders in the future. Several molecular markers associated with yield were identified (Table 2) and can be used for molecular breeding in the future to improve the yield.

5 Genome editing tools The application of genome editing tools can provide a new expansion to rice research by replacing the time-consuming traditional breeding methods to develop new varieties of rice with better yields and qualities. Genome editing technology has enabled us to precisely modify the genome sequence at a specific location to achieve the desired trait.

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TABLE 2 Molecular markers developed in rice for yield improvement. Trait

Molecular marker

Encoded protein

Citation

Panicle

EUI1

Cytochrome P450 monooxygenase

Zhang et al. (2008)

DEP1/qPE9-1

PEBP-like domain protein

Huang et al. (2009)

DTH8/Ghd8

OsHAP3 subunit of a CCAAT-box-binding protein

Wei et al. (2010)

LAX2

Nuclear protein with a plant-specific conserved domain

Hiroaki et al. (2011)

LAZY1

Specific herb protein

Chen et al. (2012)

OsPIN2

Auxin efflux transporter

Chen et al. (2012)

GW2

RING-type E3 ubiquitin ligase

Song et al. (2007)

GW5

Novel nuclear protein

Weng et al. (2008)

GS3

Transmembrane protein

Yang et al. (2010)

GS5

Serine carboxypeptidase

Li et al. (2011)

GW8

Squamosa promoter binding protein-like 16

Wang et al. (2012)

MOC1

GRAS family nuclear protein

Li et al. (2003)

TAC1

Unknown

Jiang et al. (2012)

Grain weight

HGW

Ubiquitin-associated domain protein

Li et al. (2012a)

Grain filling

GIF1

Cell wall invertase

Wang et al. (2010)

Grain quality

Tiller

Contrary to the transgenic approach that causes random integration leading to random phenotypes, genome editing technology generates defined mutants that carry their edited genes for the required trait, therefore befitting a strong tool in crop engineering. The site-specific nucleases (SSNs) such as transcriptional activator-like effector nucleases (TALENs), zinc finger nucleases (ZFNs), and the clustered regularly interspaced short palindromic repeat (CRISPR)-associated endonuclease Cas9 (CRISPR/Cas9) are various genome editing tools that break the targeted DNA. The breaks are repaired by homologous recombination (HR) or nonhomologous end joining (NHEJ) through natural repair mechanisms (Miglani, 2017). The first targeted rice mutant was reported in 2012 when the gene Os11N3 (also known as OsSWEET14) susceptible for bacterial blight was modified by a TALEN-based gene editing tool to generate disease-resistant plant lines (Li et al., 2012b). In further studies, TALEN was used for modifying multiple blight-susceptible genes in rice plants (Hutin et al., 2015; Blanvillain et al., 2017; Cai et al., 2017). These resistant rice plants showed enhanced grain yield. TALEN technology was also used for the quality improvement of rice grains by the enhancement of fragrance (Shan et al., 2015). In this study, the O. sativa betaine aldehyde dehydrogenase 2 (OsBADH2) gene was modified using a TALEN-based genome editing tool. With the advent of the CRISPR/Cas9 genome editing tool, research in animal and plant biology has been revolutionized. The CRISPR gene editing system involves designing a guide RNA (gRNA) of about 20 nucleotides complementary to the 20 bp DNA sequence of the target gene. This system is more straightforward in comparison to ZFNs and TALENs. The CRISPR/Cas9-based genome editing technology was used to modify target genes in rice for the first time in 2013 (Feng et al., 2013; Jiang et al., 2013; Shan et al., 2015; Miao et al., 2018). In this report, a single modified sgRNA was used to induce mutations in three target genes of rice, OsMPK2, Os02g23823, and OsBADH2, which are involved in various abiotic stress pathways. In the same year, three rice genes, young seedling albino (YSA), stromal processing peptidase (SPP), and rice outmost cell-specific gene 5 (ROC5), were targeted by the CRISPR/Cas9 system to generate homozygous mutants, which showed mutation frequencies up to 84% in the T0 and T1 lines (Feng et al., 2013). Furthermore, with new developments and improvements in the CRISPR/Cas9 system, the knockout screening of the whole rice genome can be performed with the development of sgRNA libraries for mutant rice populations. This study can unravel new facets in the functional genomics of rice crops. The information could be utilized for the generation of new cultivars with better novel traits.

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6 Installing C4 photosynthetic pathways into C3 rice plants to enhance the crop yield Three pathways of atmospheric CO2 fixation exist in the plant kingdom. Most crops of agronomic importance such as rice, wheat, tomatoes, and barley are C3 plants in which photosynthetic CO2 fixation starts with the carboxylation of ribulose 1,5- bisphosphate (RuBP), catalyzed by ribulose 1,5-bisphosphate carboxylase oxygenase (Rubisco), to yield two molecules of 3-phosphoglycerate (3PGA), which play a central role in the plant metabolism by providing intermediates for starch and sucrose biosynthesis. However, the competition of O2 with CO2 at the active Rubisco site results in a useless side reaction of the oxygenation of RuBP to produce one molecule of 3PGA and one molecule of 2-phosphoglycolate (2PG). A process known as photorespiration recycles the two molecules of 2PG into one molecule of 3PGA and one carbon atom is lost as CO2, resulting in a loss of up to 50% of the carbon fixed. Recycling of 2PG into 3PG imposes a high energy (12.5 ATP per molecule of 2PG produced) cost on the plant metabolism (Peterh€ansel et al., 2010). This is why photorespiration is considered a target for the metabolic engineering of C3 crop plants to enhance the yield. Further, environmental stress such as heat and drought enhances the Rubisco oxygenation, thus increasing the rate of photorespiration (Walker et al., 2016). In addition to the C3 cycle, two metabolic pathways, C4 (the first stable compound produced is a C4 acid oxaloacetate) and crassulacean acid metabolism (CAM), have evolved in some plants to reduce photorespiration by concentrating CO2 near Rubisco. C4 and CAM plants use phosphoenolpyruvate carboxylase (PEP carboxylase) for CO2 assimilation. As CO2 enters the leaf air space and then into the mesophyll cells, it is transformed into bicarbonate by the enzyme PEP carboxylase. The first product of PEP carboxylation is oxaloacetate (OAA), which is then converted to a more 4-carbon organic acid, malate, or aspartic acid. Malate or aspartic acid then diffuses to the bundle sheath cells (Gowik and Westhoff, 2011) and undergoes decarboxylation to release CO2 near Rubisco for refixation in the Calvin-Benson cycle. C4 plants reduce the useless oxygenase reaction of Rubisco due to the presence in the bundle sheath cells; and the release of CO2 in the vicinity of Rubisco allows the carboxylation of ribulose 1,5-bisphosphate. Therefore, due to the higher efficiency of C4 photosynthesis, many efforts are in progress to install C4 photosynthesis in the C3 photosynthetic plants such as rice and other crops. Modification of the photosynthetic system is difficult and time consuming, as the C4 photosynthetic system is very intricate and requires knowledge of various disciplines such as biochemistry, genetic engineering, plant physiology and molecular biology, bioinformatics, genomics, proteomics, and metabolomics. To solve this, the C4 rice consortium was established in 2009 (http://photosynthome.irri.org/C4rice/). The first and foremost requirement to introduce C4 photosynthesis into C3 rice plants is to increase the number and size of chloroplasts in the bundle sheath cells of rice (Karki et al., 2013). More than 90% of the chloroplasts are confined in mesophyll cells in rice while C4 plants possess an equal number of chloroplasts in the mesophyll and bundle sheath cells (Yoshimura et al., 2004). This is why C4 plants reduce the useless oxygenase reaction of Rubisco due to the presence of more chloroplasts in the bundle sheath cells. Installing a C4 pathway into rice requires the presence of more photosynthetic chloroplasts in the bundle sheath cells. This could be achieved by the overexpression of genes involved in chloroplast development in a bundle sheath-specific manner. Golden2-like (GLK) genes and the GARP family of MYB transcription factors were reported to be involved in chloroplast development in Arabidopsis, Zea mays, and the moss Physcomitrella patens (Chen et al., 2016). GLK genes could be expressed under the phosphoenol pyruvate carboxykinase (PCK) promoter (Nomura et al., 2005) for bundle sheath-specific expression in rice. Another way to transform C3 photosynthesis into the C4 cycle could be achieved by reducing the Rubisco activity in the mesophyll cells while enhancing in the bundle sheath cells (Karki et al., 2013). This could restrict the Calvin cycle to the bundle sheath cells of rice, thus simulating the C4 system. In addition to that, genes involved in the synthesis of C4 enzymes such as PEPC and β carbonic anhydrase (CA) can be overexpressed in the mesophyll cells using a phosphoenol pyruvate carboxylase (PEPC) promoter to promote primary CO2 fixation, followed by its release in the vicinity of Rubisco in the bundle sheath cells. Despite the CO2 fixation, the extensive movement of the C4 cycle intermediates between the mesophyll and bundle sheath cells is also very important for the successful implantation of the C4 cycle into C3 plants. Therefore, along with the main C4 enzymes such as PEPC, CA, pyruvate orthophosphate (Pi) dikinase (PPDK), NADP-dependent malic enzyme (NADP-ME), and NADP-dependent malate dehydrogenase (NADP-MDH), the installation of metabolite transporters for oxaloacetate, malate, triose-phosphate, and pyruvate can increase the efficiency of the C4 cycle in the bundle sheath cells (Weber and von Caemmerer, 2010). The photosynthetic potential of rice can also be increased by reducing the photorespiration, which in turn can enhance the yield. Photorespiration can be reduced by decreasing the glycine decarboxylase (GDC) enzyme in mesophyll cells and restricting its accumulation in bundle sheath cells, which limits the decarboxylation of glycine to occur only in bundle sheath cells. This approach was already tested by the C4 rice consortium by designing artificial micro-RNA for the rice GDC-H subunit downstream to the ZmPEPC promoter (Kajala et al., 2011). However, this approach again requires an increase in the chloroplast number in the rice bundle sheath cells to assimilate the CO2 released by glycine decarboxylation (Ueno, 2011).

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Thus, efficient photosynthesis in crop plants will improve the crop yield in a sustainable manner. The efforts of the C4 rice consortium to install the C4 photosynthetic mechanism in rice are underway to develop new varieties of rice that will produce more, even under high-temperature conditions and decreasing water accessibility. This challenging approach requires a good understanding of the regulatory networks controlling the C4 photosynthetic pathway and their insertion into the rice genome in a systematic manner.

7

Rice yield and MAPK signaling

The involvement of MAPK cascades has been reported in many signaling pathways related to growth, development, and defense responses. MAPK cascades are composed of three MAPK modules, MAP3Ks (MAPK kinase kinase), MAP2Ks (MAPK kinase), and MAPKs (Sinha et al., 2011). MAPK signaling was also reported to be linked with grain size (Duan et al., 2014; Liu et al., 2015). Grain size is an important factor that influences the grain yield in rice. Loss of function mutant of OsMKK4 was shown to produce small grains in rice (Duan et al., 2014). Rice mutant dwarf and small grain1 (dsg1) were reported to generate small grains (Liu et al., 2015). Liu et al. (2015) reported that DSG1 encodes the mitogen-activated protein kinase, OsMAPK6. In the same report, OsMAPK6 was revealed to interact with OsMKK4. Recently, an upstream MAPK module of OsMKK4 was revealed by Xu et al. (2018). Loss of function of MAP3K and OsMKKK10 in rice resulted in short panicles and small grains while the overexpression of OsMKKK10 resulted in long panicles and heavy grains (Xu et al., 2018). Biotic and abiotic stresses affect the crop yield significantly. There are several reports of the involvement of MAPK signaling in the stress response in rice. Xanthomonas oryzae causes leaf blight, which is the most critical disease in rice affecting the seed yield. MPKKK1 (EDR1) was reported to be involved in a pathway regulating the resistance of rice to X. oryzae-driven bacterial blight (Shen et al., 2011; Yang et al., 2015). MPKKK6 (DSM1) was reported to be involved in providing tolerance to drought stress in rice (Ning et al., 2010). OsMPK3, an ortholog of AtMPK3, was found to be involved in both biotic and abiotic signaling pathways (Xiong and Yang, 2003; Singh and Sinha, 2016). OsMPK3 negatively regulates the rice resistance against blast caused by Magnaporthe oryzae while in the case of drought and submergence tolerance, OsMPK3 acts as a positive regulator. Ma et al. (2017) showed that rice MPKK10.2 is involved in imparting resistance to Xanthomonas oryzae pv. oryzicola (Xoc) and drought. Genetic and biochemical studies revealed that MPKK10.2 activates MPK3 and MPK6 by phosphorylation (Ma et al., 2017). A group C MAPK of rice, OsMPK7 and its upstream MAPK kinase, OsMKK3, were reported to provide resistance against X. oryzae ( Jalmi and Sinha, 2016). The knowledge of the members of MAPK signaling cascades involved in grain size determination and stress response pathways could be utilized to enhance the crop yield by a breeding program and the genetic modification of MAPK signaling in rice plants. Although, an investigation of the upstream and downstream MAPK modules of the already reported seed size MAPK regulators will be one of the future challenges to explore MAPK signaling further in rice yield enhancement.

8

Conclusion and future perspectives

New tools and techniques enable scientists to insert important traits into rice more precisely and rapidly than with conventional breeding. A good example is the CRISPR/Cas9-based genome editing tool, which has been proven to be a breakthrough technique in crop improvement. The advent of new bioinformatic tools provides valuable information that could be utilized as a basis to start our research plan in crop improvement. These new tools are being used in many plant systems for the functional characterization of many genes related to agronomic traits and several stresses. But research involving these tools is in its preliminary stage and needs further improvement. A good research strategy for yield improvement can be designed by the combination of traditional research tools and high-throughput modern tools such as genome-wide association studies, phenomics, proteomics, and metabolomics. Genome editing using these new tools can revolutionize the research involved in crop improvement.

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Chapter 6

Molecular aspects of seed priming as a means of progress in crop improvement Maraeva Gianellaa, Andrea Paganoa, Chiara Fortia, Filippo Guzzonb,c, Andrea Mondonib, Susana de Sousa Arau´jod, Anca Macoveia and Alma Balestrazzia a

Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, Pavia, Italy, b Department of Environment and Earth Sciences,

University of Pavia, Pavia, Italy, c International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico, d Institute of Chemical and Biological Technology Anto´nio Xavier, New University of Lisbon (ITQB-NOVA), Oeiras, Portugal

1 Introduction Seed vigor is defined as “the sum of those properties that determine the activity and performance of seed lots of acceptable germination in a wide range of environments” (Finch-Savage and Bassel, 2016; ISTA, 2019). It is quantified by parameters such as germination speed and rates, long-term and after-storage viability, seed lot homogeneity and purity, resistance to mechanical damage, and the lack of biological and chemical contaminants (Finch-Savage and Bassel, 2016). The notion that seed germination could be enhanced through specific treatments was historically attested by Theophrastus (371–287 BCE) and Gaius Plinius Secundus (23–79 CE), then later by Oliver de Serres (1539–1619) and Charles Darwin (1809–1882). Nowadays, seed industries widely use priming on vegetables (Everari, 1984; Parera and Cantliffe, 1994; Paparella et al., 2015), ornamental species, herbs, and endangered species (Di Girolamo and Barbanti, 2012; Momin, 2013; Paparella et al., 2015). Different priming protocols have been optimized that vary temperature, aeration, oxygenation, and integrating protocols with additional treatments to maximize and homogenize the priming effect and improve stress resistance (Paparella et al., 2015). Because seed viability and vigor are strongly influenced by deterioration during storage, aging is an issue in terms of seed lot quality, field establishment, and crop productivity. Different priming methods have been used to overcome agingassociated damage by improving the germination rate, uniformity, and percentage. The promising availability of multiple kinds of “omics” provides researchers with global views of their experimental systems at the genome, epigenome, transcriptome, proteome, metabolome, ionome, and lipidome levels. This is also true in the field of seed biology, where extensive studies are currently carried out to define the molecular profiles of seed priming.

2 Seed priming in the context of current challenges facing agriculture and crop production The development of techniques to improve germination rates, speed, consistency, and viability under stress conditions has evolved in the modern concept of “seed priming,” which is broadly defined as any “treatment that improves seed quality” (Osburn and Schroth, 1989; Paparella et al., 2015; Finch-Savage and Bassel, 2016). The temporal window useful for effective priming corresponds to the early stages of the seed pregerminative metabolism of desiccation-tolerant seeds. Indeed, an advanced or complete transition toward full germination leads to the loss of desiccation tolerance and makes desiccation deleterious for seed viability. Priming should be administered before the loss of desiccation tolerance and optimized according to the species or seed lot (Paparella et al., 2015).

2.1 Priming agents and treatments: An overview From a historical perspective, hydropriming was the first protocol that was developed. It consists of controlled preimbibition treatments particularly effective in improving water uptake and germination in crops cultivated in dry areas. The main challenge of this technique is the selection of the best temperature and humidity values to avoid radicle protrusion, Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00006-1 © 2020 Elsevier Inc. All rights reserved.

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considering that water uptake depends mainly on seed affinity for water (Taylor et al., 1998). Osmopriming involves the administration of solutions containing osmotic agents (e.g., polyethylene glycol, PEG) to delay water uptake. PEG is not able to enter the seed due to its large molecular size (6000–8000 Da), avoiding any cytotoxic effects (Michel and Kauffmann, 1973; Heydecker and Coolbear, 1977; Zhang et al., 2015). The use of PEG implies high costs and the extremely high viscosity reduces the oxygen transfer within the priming solution. Other compounds can be used such as the inorganic salts of sodium, magnesium, or potassium (e.g., NaCl, NaNO3, MnSO4, MgCl2, K3PO4, and KNO3); this is known as “halopriming” (Gholami et al., 2015). It overcomes the viscosity and aeration issues caused by PEG, despite the possible cytotoxic effects of excessive salt dosages. However, it is essential to assess the levels of ion accumulation that could result in cytotoxic effects and nutritional imbalance within the seed (Bradford, 1995; Balestrazzi et al., 2011a,b). Physical treatments can be used to improve germination and stress resistance. Thermopriming consists of presowing at specific temperatures to reduce the thermoinhibition of germination. Its positive effects have been demonstrated, especially for crops adapted to warm environments (Huang et al., 2008). Other physical techniques have been successfully utilized for seed invigoration. Magnetic fields, microwaves, and electromagnetic radiation (UV rays, γ-rays, and x-rays) applied at specific intensities enhance the response to abiotic stresses in many model and crop species (Arau´jo et al., 2016a,b). Chemopriming involves the administration of disinfectants (e.g., sodium hypochlorite or hydrochloric acid), fungicides, or pesticides to avoid growth impairments due to contamination (Paparella et al., 2015). Conversely, “biopriming” integrates biologically active molecules such as phytohormones involved in germination control and stress response (abscisic acid-ABA, gibberellins-GAs, salicylic acid-SA) (Hamayun et al., 2010; Radhakrishnan et al., 2013). Microbial strains, including Bacillus, Enterobacter, Pseudomonas, and Trichoderma, are also utilized in biopriming because of their ability to establish an endophytic relationship with the host plant, promoting its growth, stress resistance, and hormone production (Niranjan et al., 2004; Waller et al., 2005). Despite the diffusion and effectiveness of priming techniques in the seed industry, protocols need to be specifically optimized and the stress occurring during postpriming dehydration and under suboptimal storage conditions still represents a common critical point.

3

Seed priming versus seed aging in the context of seed bank storage

The term “seed bank” usually refers to a facility endowed with a system of collecting, cleaning, packing, storing, testing, and distributing seeds. Conventional seed banking exploits conditions of low temperature and moisture content to slow the seed aging rate in order to extend the conservation time of collections (Hay, 2017). Ex situ conservation through seed banks allows medium- and long-term seed storage and is a powerful tool to preserve large amounts of plant genetic resources both for ecological and economic purposes (Hong and Ellis, 1996; Walters et al., 2004). Although ex situ conservation is economically more convenient than in situ conservation, it presents some technical challenges for correct and long-lasting storage, due to the nature of the conserved seeds (Li and Pritchard, 2009). They can be classified on the basis of the storage behavior, namely on their response to dehydration: desiccation-tolerant seeds are longer-lived and are called orthodox while desiccation-sensitive and shorter-lived seeds are called recalcitrant. Because orthodox seeds tolerate a higher degree of water loss than recalcitrant seeds (0.2 g H2O gDW 1 versus less than 0.07), they can be stored for longer periods under seed bank conventional conditions, that is, at the dry state and at low temperatures (0°C and 20°C). With drying and cooling, the aqueous matrix inside seeds becomes glassy and this viscosity reduces or abates metabolic processes, thus seed longevity results are extended (Ballesteros and Walters, 2011). Conversely, recalcitrant seeds cannot be preserved under conventional storage and cryopreservation is the safest approach, which is far less expensive than tissue culture or in situ conservation (Black and Pritchard, 2003; Walters et al., 2013). Some seeds present an intermediate behavior, as they are desiccation-tolerant but short-lived if stored at low temperatures (Roberts, 1973; Ellis et al., 1990; Pritchard, 2004). Seed longevity is defined as the viability, or ability to germinate, retained by seeds over a period of dry storage. Although cryptobiotic organisms (they do not carry processes usually associated with living systems), seeds are exceptional examples of long-lived eukaryotes: radiocarbon dating sets the age of some still viable seeds at about 2000 or 1300 years ago (Phoenix dactylifera L. and Nelumbo nucifera Gaertn., respectively) (Walters, 1998; Rajjou and Debeaujon, 2008). Seed longevity is strongly influenced by several external factors, such as storage temperature and relative humidity (RH), but also by intrinsic features that determine seed quality and vigor (Walters, 1998; Walters et al., 2005). These factors vary among species but also among seed lots because different genotypes within the same species can differ in longevity, even if stored under the same conditions (Probert et al., 2009; Nagel et al., 2010). The assessment of seed longevity is functional to guarantee the viability of a seed collection over time, mainly predicting when collections should be regenerated and avoiding repetitive viability assays when the seed number is low

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(Niedzielski et al., 2009). Viability data are usually obtained through artificial aging (AA) or controlled deterioration (CD) tests. These tests exploit high temperatures (40–60°C) and RH (75%–100%) to accelerate the natural processes of aging. The resulting data can be used to compare the estimated storage periods of different species and seed lots (Delouche and Baskin, 1973; Powell and Matthews, 1981; Newton et al., 2009). The electrical conductivity (EC) test for seed quality is based on the leakage of solutes caused by damage to lipidic membranes, which can be measured through electrodes. It is used to assess damage during aging, as EC is known to be negatively correlated with seed vigor (Powell, 1986). Elevated partial pressure of oxygen (EPPO) storage is another method that mimics aging under seed bank conservation. It has been developed to avoid the use of high temperature and RH, thereby reducing their effect on seed deterioration (Groot et al., 2012). “Aging in all organisms is the sum total of the deteriorative processes that eventually lead to death” (Matthews, 1985). The aging progress can be observed through survival curves, described by the viability equation by Ellis and Roberts (1980). Samples of the stored seed population are withdrawn at established time points and tested, then germination percentages are plotted against time. Seeds usually show two types of aging trends: some species present an initial phase of low mortality followed by a subsequent phase of decrease in viability while other species present only one phase of viability loss with a sigmoidal shape (Bernal-Iugo and Leopold, 1998). Apart from the decline in germination rate, other phenotypical signs of aging can also be: (i) production within aged seed lots of smaller seedlings when compared with those produced by unaged seed lots; and (ii) even if viable, that is, seeds able to produce a radical protrusion, seedlings show abnormal phenotypes (Matthews, 1985). The primary processes of seed deterioration during aging are thought to be oxidative and peroxidative reactions. Free radicals form spontaneously, and because water tends to quench these reactions and maintain antioxidant activity, they have major effects when seeds are at the dry state or at low moisture levels. Lipid peroxidation is one of the main processes triggered by ROS and causes the breakdown of lipids and the formation of byproducts that can damage other macromolecules such as proteins and nucleic acids (Bewley et al., 2013). Because seed viability and vigor are strongly influenced by deterioration during storage, thus aging is an issue in terms of seed lot quality, field establishment, and crop productivity. Identifying effective aging hallmarks is therefore necessary to predict seed longevity and evaluate seed lots. Besides standard methods (AA, CD, EC tests, and seedling establishment evaluations), new technologies from molecular biology, biotechnology, biophysics, and seedling imaging analysis have been exploited to detect aging hallmarks and processes (Marcos-Filho, 2015). Several markers of quantitative trait loci (QTLs), detected after AA tests, are associated with stress response and aging. In barley (Hordeum vulgare L.), it has been demonstrated that longevity is associated with different traits such as floral and seed development, the ethylene and jasmonate pathways, and antifungal activity (Nagel et al., 2009). In both barley and Arabidopsis thaliana (L.) Heynh., the role of DNA repair during aging has been underlined with crucial players such as DNA ligase 4 and 6 (Waterworth et al., 2010). In maize (Zea mays L.), some QTLs identified after AA are linked to the energy metabolism, stress response, signal transduction, and protein degradation pathways (Wang et al., 2016). One of the main processes occurring during aging is lipid peroxidation. It can be assessed with an EC test and biochemical assays that measure its byproducts, such as malondialdehyde (MDA) and proline, or tocopherols, which help prevent lipid peroxidation and decrease during aging. Oxidative reactions can also be indirectly measured through gene expression analysis: the upregulation of genes encoding antioxidant enzymes can be viewed as a stress hallmark. Other genes related to stress response are involved in aging processes, such as those coding for heat shock proteins and other defense proteins that prevent misfolding and protein aggregation (Bailly, 2004; Sattler et al., 2004; Rajjou and Debeaujon, 2008; Wang et al., 2018a,b). Seed deterioration is also marked by the reduction of α-amylase activity and total soluble sugar content because the reduction in the starch metabolism observed in aged seeds can impair germination (Wang et al., 2018a,b; Pandey et al., 2017).

3.1 Seed priming as a tool to limit aging-associated damage Different priming methods have been used to overcome aging-associated damage by improving the germination rate, uniformity, and percentage. Seeds of different species have been submitted to several priming techniques. It has been suggested that the effectiveness of these treatments depends on repair mechanisms activated during the hydration phase, namely nucleic acids, lipids, protein repair, and the reactivation of transcription and antioxidant enzyme scavenging activity (Probert et al., 1991; Kibinza et al., 2006; Parmoon et al., 2013; Pandey et al., 2017). For instance, it has been reported that halopriming with KH2PO4 and K2HPO4 in cucumber seeds (Cucumis sativus L.) enhances repair by stabilizing membrane integrity, as the seed leachate measured through EC tests is reduced after the treatment (Pandey et al., 2017). However, it is not clear whether the damage repaired with priming is already present in aged seeds or the priming plays a preventive role by recovering antioxidant and repair enzymes before the onset of germination and subsequent

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damage caused by ROS release. Although hydropriming and osmopriming are the most used treatments, other compounds such as salicylic acid or metallic nanoparticles have been used in aged seed priming treatments with positive effects both on germination and the seedling phenotype (Mahakham et al., 2017; Siavash Moghaddam et al., 2018). In some cases, seeds submitted to a priming treatment show a delayed loss of viability when stored, probably because the repair mechanisms activated by imbibition allow seeds to maintain germinability for longer periods (Dearman et al., 1986; Probert et al., 1991; Butler et al., 2009). Other studies report that primed seeds present reduced longevity when submitted to CD and AA tests (Chiu et al., 2002; Hill et al., 2007; Hussain et al., 2015). This loss of viability probably depends on the effects of high temperature and moisture content in aerobic conditions more than on the priming treatment per se. In fact, when the longevity of primed rice seeds stored under different conditions was tested, seeds stored in an anaerobic environment remained viable for a longer period than seeds submitted to the same treatment but stored in aerobic conditions (Wang et al., 2018a,b). The viability of primed stored seeds can be partially restored with poststorage treatments, namely repriming and heat shock, thereby maintaining the priming treatment benefits and allowing longer storage (Rao et al., 1987; Bruggink et al., 1999).

4 The molecular know-how of seed priming and its implications in promoting new advances in the sectors of seed biology and technology The dynamics of water uptake and metabolic reactivation during seed imbibition have been proposed in the form of a triphasic temporal pattern (Bewley, 1997; Bewley et al., 2013). During seed dormancy, metabolic pathways are deactivated to prevent the accumulation of damage and germination in unsuitable conditions. Cytoplasm is dehydrated to a “glassy” state unsuitable for enzymatic reactions (Buitink et al., 2000; Buitink and Leprince, 2008). The first phase, imbibition, is characterized by a rapid water uptake physically driven by seed coat permeability and tissue capillarity (Beweley, 1997; Kranner et al., 2010). Subsequently, water absorption slows down and the water content remains constant, marking the starting point of the second phase. With rehydration, the optimal conditions for enzymatic reactions to occur are set, thus allowing processes essential for seed viability and germination, including DNA and membrane repair, protein synthesis, and mitochondrial respiration. To fulfill these functions, new mRNAs must be transcribed and translated, although the dry seeds are endowed with residual maternal mRNAs (Beweley et al., 1997; Rajjou et al., 2006; Weitbrecht et al., 2011). More than 10,000 mRNAs able to resist desiccation during seed maturation have been identified in Arabidopsis, rice, and other species. The most represented functions within the dry seed transcriptome include storage proteins and late embryogenesis abundant proteins (LEA) (Weitbrecht et al., 2011). A small percentage of the dry seed transcriptome is involved in protein synthesis, protein degradation, and hormonal responses (Holdsworth et al., 2008a,b). The third stage culminates in the radicle emergence and features a new increase in water uptake and reserve consumption as cell division and elongation start (Bewley et al., 2013).

4.1 The redox context of the pregerminative metabolism and the harmful oxidative damage The production and accumulation of ROS (reactive oxygen species) and NRS (nitrogen reactive species) in seeds has been documented in all developmental stages. These chemically reactive molecules have double-faced effects over seed viability and germination, causing oxidative damage to biological macromolecules but playing fundamental roles in several physiological processes. The recent scientific literature annotated the specific roles of the most abundant ROS and NRS, including hydroxyl radicals (OH
), hydrogen peroxide (H2O2), superoxide radicals (O2 ), nitric oxide (NO), and other reactive molecules involved in the seed and seedling metabolism (Bailly et al., 2002, 2008; Bailly, 2004; Morohashi, 2002; Sarath et al., 2007). Additional ROS sources are found in seeds, such as oxidative reactions occurring in peroxisomes and glyoxysomes during the mobilization of seed reservoirs. ROS production, particularly at the mitochondrial level, is prominent in seed-specific developmental stages. Besides the physiological routes of ROS production, the occurrence of stress conditions can impair ROS homeostasis and elicit different ROS production and distribution patterns (stressassociated ROS signatures) (Choudhury et al., 2017; Farooq et al., 2018; Rosbakh et al., 2018). The occurrence of ROS-induced oxidative damage to different classes of biological macromolecules and cellular compartments has been reported (Osborne et al., 1984; Osborne, 1994; Bailly, 2004; Rajjou and Debeaujon, 2008; Rajjou et al., 2008) along with its negative effects on seed longevity and viability (Groot et al., 2012). In seeds, lipid oxidation can affect both membrane lipids and reservoir fatty acids in different contexts. In particular, lipid peroxidation taking place in peroxisomes and glyoxysomes is a major ROS source in metabolically active oily seeds that are degrading their lipidic reservoirs before seedling establishment (Del Rı´o et al., 2002; Corpas et al., 2001). Furthermore, self-oxidation processes such as Amadori and Maillard reactions can lead to oxidative damage of lipids in dormant or stored seeds, affecting seed long-term viability and shelf life (Sun and Leopold, 1995; Murthy and Sun, 2000; Buitink and Leprince, 2008). Antioxidant

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molecules such as tocopherol (vitamin E) and tocotrienols are involved in protection from lipid peroxidation (Horvath et al., 2006). The functional groups of amino acids are particularly exposed to the oxidation caused by hydroxyl radicals and hydrogen peroxide, and the accumulation of functionally impaired proteins ultimately leads to irreversible cell damage (Charles and Halliwell, 1980). Besides the oxidation of functional groups, the specific redox state of each cellular compartment determines the stability of the disulfide bonds necessary to maintain protein tertiary structure. Important changes in the redox state and overall protein oxidation have been observed in both the embryo and endosperm of imbibed seeds (Buchanan and Balmer, 2005). In this context, the preferential oxidation of specific classes of reserve proteins, such as globulins and cruciferins, has been interpreted as ROS-scavenging activity to prevent or limit oxidative damage to other classes of proteins (Arc et al., 2011; Job et al., 2005; Rajjou et al., 2012). Specialized enzymes are involved in maintaining protein structure and integrity, in particular during hydration-dehydration cycles. Among them, thioredoxins, methionine sulfoxide reductases, and protein L-isoaspartyl methyltransferases are correlated with seed longevity in many species. Besides their main role, certain classes of seed storage proteins, in particular 12S globulins, are particularly prone to oxidation, suggesting a possible role as ROS scavengers, as demonstrated in Arabidopsis (El-Maarouf-Bouteau et al., 2013; Nguyen et al., 2015). The presence of antioxidant enzymes has been documented both in dry mature seeds and in germinating seeds and constitutes an essential trait participating in seed vigor. Among them, ascorbate peroxidase, catalase, dehydroascorbate reductase, glutathione peroxidase, glutathione reductase, monodehydroascorbate reductase, and superoxide dismutase contribute to the seed detoxification potential (Oracz et al., 2007). Besides them, reduced glutathione plays a pivotal role in maintaining the overall cytoplasmic redox state and preventing protein oxidation (Kranner et al., 2006; Nagel et al., 2015). ROS accumulation is particularly deleterious for DNA integrity and genome stability. The oxidative damage of purines, pyrimidines, and deoxyribose units is a primary cause of DNA strand breaks (Bray and West, 2005). One of the most common base modifications is guanine hydroxylation to 7,8-dihydro-8-oxoguanine (8-oxoG), whose mutagenic effects have been documented (Biedermann et al., 2011). The established correlation between the accumulation of strand breaks, genome instability, and seed vigor impairment makes the role of ROS a long-lasting and prolific field of study within seed biology and biotechnology. Also, RNA can undergo oxidative damage and translational impairment due to these processes, which has been correlated to reduced seed longevity (Rajjou et al., 2008; Bazin et al., 2011).

4.2 Active DNA repair during the pregerminative metabolism: a molecular know-how for seed priming Maintaining genome integrity during the dry state is crucial for long-term seed survival. A significant reduction in the nucleus size and a notable chromatin condensation have been observed in dehydrated Arabidopsis seeds, suggesting an adaptive response to dehydration also at the DNA level (van Zanten et al., 2011; Waterworth et al., 2015). The activation of DNA repair pathways, such as BER and NER, has been reported cross-specifically (Waterworth et al., 2010; Balestrazzi et al., 2011a,b; Macovei et al., 2010). Base excision repair is a multistep pathway that is able to recognize and repair many kinds of nucleotide modifications, including oxidative damage, alkylation, deamination, apurinic/ apyrimidinic (AP) sites, and single-strand breaks. The first step of the process involves specific glycosylases that recognize the damaged deoxynucleoside and hydrolyze its N-glycosidic bond, thus removing the modified base. For example, 8-oxoguanine DNA glycosylase (OGG1), formamidopyrimidine DNA glycosylase (FPG), and uracil DNA glycosylase (UDG) are three enzymes specifically involved in this concern (Co´rdoba-Can˜ero et al., 2009). The resulting apurinic/apyrimidinic site is then processed by two alternative subpathways. The short-patch repair pathway is performed by the DNA polymerase β that inserts a single nucleotide whose ends are joined to the rest of the DNA strand by the DNA ligase III enzyme, whereas the long-patch repair pathway is carried out by the replicative DNA polymerases δ or ε that insert several nucleotides with the final intervention of the DNA ligase I that eventually repairs the DNA filament. The long-patch repair subpathway also requires the displacement and removal of adjacent nucleotides while the synthesis occurs. This function is performed by the flap structure-specific endonuclease 1 (FEN-1) in association with the proliferating cell nuclear antigen (PCNA) (Wu et al., 1996; Tsai et al., 2017). The involvement of BER components in stress response was confirmed in many plant tissues. Indeed, the expression levels of the genes encoding OGG1 and FPG were increased in response to copper- and polyethylene glycol (PEG)-induced stress in Medicago truncatula roots and aerial parts while it was delayed in rehydrating seeds in the presence of PEG, whose osmotic effects slow down water uptake and the subsequent metabolism reactivation (Macovei et al., 2011a,b). DNA ligase VI is essential to maintain seed longevity in Arabidopsis thaliana both under physiological and stress conditions (Waterworth et al., 2010). Other enzymes cover specific functions in the context of BER, such as tyrosyl-DNA phosphodiesterases (TDPs) (Pommier et al., 2014) that prevent lesions caused by the stabilized covalent complexes

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FIG. 1 Seed vigor and the underlying molecular mechanisms, particularly DNA repair and antioxidant defense, play crucial roles in maintaining highstandard seeds for both market and conservation purposes. The beneficial effects of seed priming range from enhanced/synchronized germination to increased robustness or stress tolerance of seedlings, essential features for breeding. High vigor also supports seed longevity. In this context, novel molecular hallmarks useful to predict seed quality will be provided by high-throughput “omics” technologies.

DNA/topoisomerase, thus preventing genotoxic effects occurring during transcription and replication as well as under oxidative stress (El-Khamisy et al., 2005). The expression of the different TDP genes identified in plants (TDP1α, TDP1β, and TDP2) is responsive to different stress conditions in different experimental systems, including cell suspensions, roots, aerial parts, and seeds (Arau´jo et al., 2016b; Balestrazzi et al., 2011a,b; Confalonieri et al., 2013; Dona` et al., 2013; Fae` et al., 2014; Macovei et al., 2018), suggesting their recurrent involvement in plant responses to genotoxic stress. Nucleotide excision repair, linked to the seed stress response (Macovei et al., 2011b, 2014), processes major DNA damage that implies covalent adducts or UV-photoproducts. It is specifically elicited during transcription (NER-TCR, NER-transcription coupled repair) and in nontranscribed regions (NER-GGR, NER-global genome repair) (Kunz et al., 2005; Conconi et al., 2002). Several factors are required to recruit and activate the NER machinery, among which the transcription elongation factor II-S (TFIIS) (Kuraoka et al., 2007) is involved in the abiotic stress response in M. truncatula (Macovei et al., 2011b) and dormancy regulation in Arabidopsis seeds (Grasser et al., 2009). Because of their crucial effects on genome stability, DNA damage dynamics and DNA repair pathways represent a promising field of applied research to assess and improve seed quality, concerning seed priming, long-term storability, and harvest yields. This intricate network of molecular events has been envisaged as a source of novel hallmarks of seed vigor (Fig. 1) (Balestrazzi et al., 2011a,b; Paparella et al., 2015; Pagano et al., 2017, 2018).

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5.1 Multilevel approaches to understand seed biology and assess seed quality The possibility to associate genotyped markers to specific phenotypes is at the base of genome-wide association studies (GWAS). In the case of seed quality, this approach has led to the identification of QTLs related to seed quality (Wang et al., 2018a,b). Extensive transcriptomic studies have been carried out in many model systems focusing on seed metabolism and have led to the identification of the most represented families of transcripts during the various stages of seed metabolism. In Arabidopsis seeds, genes related to protein turnover and cell wall plasticity are the most expressed during the early imbibition stage (Nakabayashi et al., 2005) while overall, the increased expression of auxin-related genes was required for cell division and elongation in the subsequent phases (Holdsworth et al., 2008b). However, substantial differences have been found between the embryo and endosperm in pathways related to reserve mobilization and energy utilization (Penfield et al., 2006). The role of posttranscriptional regulation and silencing mediated by miRNA has been highlighted in seed germination and seedling development in many model species, including Glycine max and Brassica napus (Fu et al., 2019; Wei et al., 2018).

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Through proteomic approaches, a global understanding of seed metabolism associated with improved seed vigor has been achieved for model plants such as Arabidopsis (Gallardo et al., 2001; Rajjou et al., 2006) and crop plants such as Medicago sativa (Yacoubi et al., 2013) and Triticum aestivum (Fercha et al., 2013, 2014). Furthermore, the combination of transcriptomic and proteomic data obtained from primed Brassica napus and Hordeum vulgare seeds has highlighted the overall upregulation of genes involved in water uptake (e.g., genes encoding aquaporins), cell cycle and division, the cytoskeleton, and response to oxidative stress in response to priming (Kubala et al., 2015; Mostek et al., 2016). Metabolomic profiling of germinating seeds has been successfully used to investigate the metabolic differences associated with different cultivars of T. aestivum (Das et al., 2017), Zea mays (Feenstra et al., 2017), and H. vulgare (Gorzolka et al., 2016), highlighting the differential accumulation and distribution of specific classes of amino acids, lipids, and carbohydrates. Metabolomic approaches have also been used to unveil the metabolic footprint of stress conditions in A. thaliana (Cohen and Amir, 2017) and M. truncatula (Pagano et al., 2018) seeds, identifying various putative hallmarks of seed germination and stress response. Metabolomic data can be deepened and integrated through specific analyses focused on particular classes of molecules, such as lipids or ions. Advancements in seed lipidomics are particularly promising, given the importance of lipids as structural components of membranes, carbon and energy reservoirs, and signaling molecules, especially in oily seeds (Horn and Chapman, 2014). Other high-throughput techniques are aimed at obtaining a dynamic picture of the metabolic fluxes at the cell, organ, and plant level. Through specific labeling and imaging techniques in more or less extended time lapses, “fluxomics” applied to seeds and embryos allows tracing the accumulation, compartmentalization, and mobilization of starch, lipids, and carbon, improving the current knowledge of seed metabolism and opening promising possibilities for the enhancement of seed nutritional properties (Salon et al., 2017).

6 Conclusion and future perspectives Despite the huge amount of data that can be obtained through “omics” techniques and the possibilities of data integration offered by system biology, the notable variability of biological systems in their stress response strategies leads to unavoidable difficulties in finding common principles and conserved patterns able to explain complex phenomena. With these premises, the individuation of specific gene expression patterns, DNA or RNA modifications, or metabolite accumulation that are recurrently associated with seed quality and vigor could have interesting output for plant biotechnology and the seed industry. The identification of such “molecular markers of seed quality” will allow biotechnologists to complement the empirical approaches currently used for seed priming and optimize invigoration protocols of agronomical relevance. Moreover, the availability of experimental systems for the study of seed deterioration will help understanding the impact of priming in preserving longevity whereas the so-called “priming memory” deserves more attention. The advanced avenues of genome editing are now open to explore the multifaceted aspects of seed vigor. CRISPR (clustered regularly interspaced short palindromic repeat)-Cas9 technology appears to be a promising tool to improve this complex trait.

Acknowledgments This work was supported by the CARIPLO Foundation in the frame of the WAKE-APT project (Code 2016-0723) (“Seed Wake-up with Aptamers: a New Technology for Dormancy Release and Improved Seed Priming”) and by the Italian Ministry of Education, University, and Research (MIUR): Dipartimenti di Eccellenza Program (2018–2022) -Dept. of Biology and Biotechnology “L. Spallanzani”, University of Pavia (to M.G., C.F., A.P., A.M., A.B.). C.F. and A.P. have been awarded research fellowships from the CARIPLO Foundation in the frame of the WAKE-APT project (Code 2016-0723). S.S.A. acknowledges the financial support from Fundac¸a˜o para a Ci^encia e a Tecnologia (Lisbon, Portugal) through the research unit “GREEN-IT -Bioresources for Sustainability” (UID/Multi/04551/2019) and her Ph.D. holder contract (DL57).

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Feenstra, A.D., Alexander, L.E., Song, Z., Korte, A.R., Yandeau-Nelson, M.D., Nikolau, B.J., Lee, Y.J., 2017. Spatial mapping and profiling of metabolite distributions during germination. Plant Physiol. 174, 2532–2548. Fercha, A., Capriotti, A.L., Caruso, G., Cavaliere, C., Gherroucha, H., Samperi, R., Stampachiacchiere, S., Lagana, A., 2013. Gel-free proteomics reveal potential biomarkers of priming-induced salt tolerance in durum wheat. J. Proteome 91, 486–499. Fercha, A., Capriotti, A.L., Caruso, G., Cavaliere, C., Samperi, R., 2014. Comparative analysis of metabolic proteome variation in ascorbate-primed and unprimed wheat seeds during germination under salt stress. J. Proteome 108, 238–257. Finch-Savage, W.E., Bassel, G.W., 2016. Seed vigour and crop establishment: extending performance beyond adaptation. J. Exp. Bot. 67, 567–591. Fu, Y., Mason, A.S., Zhang, Y., Lin, B., Xiao, M., Fu, D., Yu, H., 2019. 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Kubala, S., Wojtyla, L., Quinet, M., Lechowska, K., Lutts, S., Garnczarska, M., 2015. Enhanced expression of the proline synthesis gene P5CSA in relation to seed osmopriming improvement of Brassica napus germination under salinity stress. J. Plant Physiol. 183, 1–12. Kunz, B.A., Anderson, H.J., Osmond, M.J., Vonarx, E.J., 2005. Components of nucleotide excision repair and DNA damage tolerance in Arabidopsis thaliana. Environ. Mol. Mut. 45, 115–127. Kuraoka, I., Suzuki, K., Ito, S., Hayashida, M., Kwei, J.S., Ikegami, T., Handa, H., Nakabeppu, Y., Tanaka, K., 2007. RNA polymerase II bypasses 8-oxoguanine in the presence of transcription elongation factor TFIIS. DNA Repair (Amst) 6, 841–851. Li, D.-Z., Pritchard, H., 2009. The science and economics of ex situ plant conservation. Trends Plant Sci. 14, 614–621. Macovei, A., Balestrazzi, A., Confalonieri, M., Carbonera, D., 2010. 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Biomed. Res. Int. 2014, 1–15. Macovei, A., Fae`, M., Biggiogera, M., de Sousa, A.S., Carbonera, D., Balestrazzi, A., 2018. Ultrastructural and molecular analyses reveal enhanced nucleolar activity in Medicago truncatula cells overexpressing the MtTdp2α gene. Front. Plant Sci. 9, 596. Mahakham, W., Sarmah, A.K., Maensiri, S., Theerakulpisut, P., 2017. Nanopriming technology for enhancing germination and starch metabolism of aged seeds using phytosynthesized silver nanoparticles. Sci. Rep. 7, 8263. Marcos-Filho, J., 2015. Seed vigor testing: an overview of the past, present and future perspective. Sci. Agric. 72, 363–374. Matthews, S., 1985. Physiology of seed aging. Outlook Agric. 14, 89–94. Michel, B.E., Kauffmann, M.R., 1973. The osmotic potential of polyethylene glycol 6000. Plant Physiol. 51, 914–916. Momin, K.C., 2013. Challenges of the flower seed industry. Indian J. Appl. Res. 3, 244–245. Morohashi, Y., 2002. 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Res. 19, 213–224. Niranjan Raj, S., Shetty, N.P., Shetty, H.S., 2004. Seed bio-priming with Pseudomonas fluorescens isolates enhances growth of pearl millet plants and induces resistance against downy mildew. Int. J. Pest Manag. 50, 41–48. Oracz, K., El-Maarouf Bouteau, H., Farrant, J.M., Cooper, K., Belghazi, M., Job, C., Job, D., Corbineau, F., Bailly, C., 2007. ROS production and protein oxidation as a novel mechanism for seed dormancy alleviation. Plant J. 50, 452–465. Osborne, D.J., 1994. DNA and desiccation tolerance. Seed Sci. Res. 4, 175–185. Osborne, D.J., Dell’Aquila, A., Elder, R.H., 1984. DNA repair in plant cells. An essential event of early embryo germination in seeds. Folia Biol. (Praha). 30, 155–169. Osburn, R.M., Schroth, M.N., 1989. Effect of osmopriming sugar beet deed on exudation and subsequent damping-off caused by Pythium ultimum. Phytopathology 78, 1246–1250. Pagano, A., Susana Arau´jo, S., Macovei, A., Leonetti, P., Balestrazzi, A., 2017. The seed repair response during germination: disclosing correlations between DNA repair, antioxidant response, and chromatin remodeling in Medicago truncatula. Front. Plant Sci. 8, 1972. Pagano, A., De Sousa, A.S., Macovei, A., Dondi, D., Lazzaroni, S., Balestrazzi, A., 2018. Metabolic and gene expression hallmarks of seed germination uncovered by sodium butyrate in Medicago truncatula. Plant Cell Environ. 42, 259–269. https://doi.org/10.1111/pce.13342. Pandey, P., Bhanuprakash, K., Umesha, 2017. Effect of seed priming on biochemical changes in fresh and aged seeds of cucumber. I.J.E.A.B. 2, 2261–2264.

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Paparella, S., Arau´jo, S.S., Rossi, G., Wijayasinghe, M., Carbonera, D., Balestrazzi, A., 2015. Seed priming: state of the art and new perspectives. Plant Cell Rep. 34, 1281–1293. Parera, C.A., Cantliffe, D.J., 1994. Pre-sowing seed priming. Hort. Rev. 16, 109–141. Parmoon, G., Ebadi, A., Jahanbakhsh, S., Davari, M., 2013. The effect of seed priming and accelerated aging on germination and physiochemical changes in milk thistle (Silybum marianum). Not. Sci. Biol. 5, 1–8. Penfield, S., Li, Y., Gilday, A.D., Graham, S., Graham, I.A., 2006. Arabidopsis ABA INSENSITIVE4 regulates lipid mobilization in the embryo and reveals repression of seed germination by the endosperm. Plant Cell 18, 1887–1899. Pommier, Y., Huang S-Y, N., Gao, R., Das, B.B., Murai, J., Marchand, C., 2014. Tyrosyl-DNA-phosphodiesterases (TDP1 and TDP2). DNA Repair 19, 114–129. Powell, A.A., 1986. Cell membranes and seed leachate coductivity in relation to the quality of seed for sowing. J. Seed Tech. 10, 81–100. Powell, A.A., Matthews, S., 1981. Evaluation of controlled deterioration, a new vigour test for small seeded vegetables. Seed Sci. Technol. 9, 633–640. Pritchard, H.W., 2004. Classification of seed storage ‘types’ for ex situ conservation in relation to temperature and moisture. In: Guerrant, E.O., Havens, K., Maunder, M. (Eds.), Ex situ Plant Conservation: Supporting Species Survival in the Wild. Island Press, Washington, DC, USA, pp. 139–161. Probert, R.J., Bogh, S.V., Smith, A.J., Wechsberg, G.E., 1991. The effects of priming on seed longevity in Ranunculus sceleratus L. Seed Sci. Res. 1, 243–249. Probert, R.J., Daws, M.I., Hay, F.R., 2009. Ecological correlates of ex situ seed longevity: a comparative study on 195 species. Ann. Bot. 104, 57–69. Radhakrishnan, R., Khan, A.L., Lee, I.-J., 2013. Endophytic fungal pre-treatments of seeds alleviates salinity stress effects in soybean plants. J. Microbiol. 51, 850–857. Rajjou, L., Debeaujon, I., 2008. Seed longevity: survival and maintenance of high germination ability of dry seeds. C R Biol. 331, 796–805. Rajjou, L., Belghazi, M., Huguet, R., Robin, C., Moreau, A., Job, C., Job, D., 2006. Proteomic investigation of the effect of salicylic acid on Arabidopsis seed germination and establishment of early defense mechanisms. Plant Physiol. 141, 910–923. Rajjou, L., Lovigny, Y., Groot, S.P., Belghazi, M., Job, C., Job, D., 2008. Proteome-wide characterization of seed aging in Arabidopsis: a comparison between artificial and natural aging protocols. Plant Physiol. 148, 620–641. Rajjou, L., Duval, M., Gallardo, K., Catusse, J., Bally, J., Job, C., Job, D., 2012. Seed germination and vigor. Annu. Rev. Plant Biol. 63, 507–533. Rao, N.K., Roberts, E.H., Ellis, R.H., 1987. The influence of pre and post-storage hydration treatments on chromosomal aberrations, seedling abnormalities, and viability of lettuce seeds. Ann. Bot. 60, 97–108. Roberts, E.H., 1973. Predicting the storage life of seeds. Seed Sci. Technol. 1, 499–514. Rosbakh, S., Pacini, E., Nepi, M., Poschlod, P., 2018. An unexplored side of regeneration niche: seed quantity and quality are determined by the effect of temperature on pollen performance. Front. Plant Sci. 9, 1036. Salon, C., Avice, J.C., Colombie, S., Dieuaide-Noubhani, M., Gallardo, K., Jeudy, C., Ourry, A., Prudent, M., Voisin, A.S., Rolin, D., 2017. Fluxomics links cellular functional analyses to whole-plant phenotyping. J. Exp. Bot. 68, 2083–2098. Sarath, G., Hou, G., Baird, L.M., Mitchell, R., 2007. Reactive oxygen species, ABA and nitric oxide interactions on the germination of warm-season C4grasses. Planta 226, 697–708. Sattler, S.E., Gilliland, L.U., Magallanes-Lundback, M., Pollard, M., DellaPenna, D., 2004. Vitamin E is essential for seed longevity and for preventing lipid peroxidation during germination. Plant Cell 16, 1419–1432. Siavash Moghaddam, S., Rahimi, A., Noorhosseini, S.A., Heydarzadeh, S., Mirzapour, M., 2018. Effect of seed priming with salycilic acid on germina€ bility and seedling vigor of fenugreek (Trigonella Foenum-Graecum). Y€uz€unc€u Yıl Universitesi Tarım Bilimleri Dergisi 28, 192–199. Sun, W.Q., Leopold, A.C., 1995. The Maillard reaction and oxidative stress during aging of soybean seeds. Physiol. Plant. 94, 94–104. Taylor, A.G., Allen, P.S., Bennet, M.A., Bradford, K.J., Burris, J.S., Misra, M.K., 1998. Seed enhancements. Seed Sci. Res. 8, 245–256. Tsai, Y.C., Wang, Y.H., Liu, Y.C., 2017. Overexpression of PCNA attenuates oxidative stress-caused delay of gap-filling during repair of UV-induced DNA damage. J. Nucleic Acids 2017, 8154646. van Zanten, M., Koini, M.A., Geyer, R., Liu, Y., Brambilla, V., Bartels, D., Koornneef, M., Fransz, P., Soppe, W.J., 2011. Seed maturation in Arabidopsis thaliana is characterized by nuclear size reduction and increased chromatin condensation. Proc. Natl. Acad. Sci. U. S. A. 108, 20219–20224. Waller, F., Achatz, B., Baltruschat, H., Fodor, J., Becker, K., Fischer, M., Heier, T., Huckelhoven, R., Neumann, C., Von-Wettstein, D., 2005. The endophytic fungus Piriformis indica reprograms barley to salt-stress tolerance, disease resistance, and higher yield. Proc. Natl. Acad. Sci. U. S. A. 102, 13386–13391. Walters, C., 1998. Understanding the mechanisms and kinetics of seed aging. Seed Sci. Res. 8, 223–244. Walters, C., Wheeler, L., Stanwood, P.C., 2004. Longevity of cryogenically stored seeds. Cryobiology 48, 229–244. Walters, C., Wheeler, L.M., Grotenhuis, J., 2005. Longevity of seeds stored in a genebank: species characteristics. Seed Sci. Res. 15, 1–20. Walters, C., Berjak, P., Pammenter, N.W., 2013. Preservation of recalcitrat seeds. Science 339, 915–916. Wang, B., Zhang, Z., Fu, Z., Liu, Z., Hu, Y., Tang, J., 2016. Comparative QTL analysis of maize seed artificial aging between an immortalized F2 population and its corresponding RILs. Crop J. 4, 30–39. Wang, W., He, A., Peng, S., Huang, J., Cui, K., Nie, L., 2018a. The effect of storage condition and duration on the deterioration of primed rice seeds. Front. Plant Sci. 9, 172. Wang, T., Hou, L., Jian, H., Di, F., Li, J., Liu, L., 2018b. Combined QTL mapping, physiological and transcriptomic analyses to identify candidate genes involved in Brassica napus seed aging. Mol. Gen. Genomics. 29, 1421–1435.

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Waterworth, W.M., Masnavi, G., Bhardwaj, R.M., Jiang, Q., Bray, C.M., West, C.E., 2010. A plant DNA ligase is an important determinant of seed ‘longevity. Plant J. 63, 848–860. Waterworth, W.M., Bray, C.M., West, C.E., 2015. The importance of safeguarding genome integrity in germination and seed longevity. J. Exp. Bot. 66, 3549–3558. Wei, W., Li, G., Jiang, X., Wang, Y., Ma, Z., Niu, Z., Wang, Z., Geng, X., 2018. Small RNA and degradome profiling involved in seed development and oil synthesis of Brassica napus. PLoS One 13, e0204998. Weitbrecht, K., M€ uller, K., Leubner-Metzger, G., 2011. First off the mark: early seed germination. J. Exp. Bot. 62, 3289–3309. Wu, X., Li, J., Li, X., Hsieh, C.L., Burgers, P.M., Lieber, M.R., 1996. Processing of branched DNA intermediates by a complex of human FEN-1 and PCNA. Nucleic Acids Res. 24, 2036–2043. Zhang, F., Yu, J., Johnston, C.R., Wang, Y., Zhu, K., Lu, F., Zhang, Z., Zhou, J., 2015. Seed priming with polyethylene glycol induces physiological changes in sorghum (Sorghum bicolor L. Moench) seedlings under suboptimal soil moisture environments. PLoS One 10, e0140620.

Further Reading Bailly, C., Benamar, A., Corbineau, F., Come, D., 1998. Free radical scavenging as affected by accelerated aging and subsequent priming in sunflower seeds. Physiol. Plant. 104, 646–652. Diaz-Vivancos, P., Barba-Espı´n, G., Herna´ndez, J.A., 2013. Elucidating hormonal/ROS networks during seed germination: insights and perspectives. Plant Cell Rep. 32, 1491–1502. Macovei, A., Pagano, A., Leonetti, P., Carbonera, D., Balestrazzi, A., Arau´jo, S.S., 2017. Systems biology and genome-wide approaches to unveil the molecular players involved in the pre-germinative metabolism: implications on seed technology traits. Plant Cell Rep. 36, 669–688. Ventura, L., Dona`, M., Macovei, A., Carbonera, D., Buttafava, A., Mondoni, A., Rossi, G., Balestrazzi, A., 2012. Understanding the molecular pathways associated with seed vigor. Plant Physiol. Biochem. 60, 196–206.

Chapter 7

Plant histidine kinases: Targets for crop improvement Priyanka Guptaa, Ramsong C. Nongpiura, Sneh Lata Singla-Pareekb and Ashwani Pareeka a

Stress Physiology and Molecular Biology Laboratory, School of Life Sciences, Jawaharlal Nehru University, New Delhi, India, b Plant Stress Biology,

International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India

1 Introduction The rapid increase in the worldwide population is a major concern for food security across the globe. The fulfillment of the ever-increasing food demand and improvement of crop quality are major challenges in the coming years. Rapid urbanization and industrialization have also resulted in a significant decrease in the land area available for agriculture. Furthermore, adverse environmental conditions (environmental stresses) as a result of climate change could severely affect crop productivity. In this regard, efforts are being made to improve agricultural productivity as well as the nutritional quality of crops through various means. Plant breeding is at the forefront with breeders trying to combine high-yield traits along with stress-tolerant traits. QTL mapping and pyramiding have been widely used to improve the agronomic traits of various crops ( Jenks et al., 2007; Mumm, 2007; Hu et al., 2012; Kumar et al., 2015). However, current agricultural productivity is still significantly affected by environmental stresses and alternative methods for crop improvement such as transgenic technology have also been explored (Pareek et al., 1995, 2009; Singla-Pareek et al., 2006; Kumar et al., 2009, 2012; Kumari et al., 2009; Singh et al., 2012; Mustafiz et al., 2014; Joshi et al., 2016). Stress tolerance, especially abiotic stress tolerance, is multigenic in nature and the identification of all the associated markers with the mentioned traits remains a herculean task. The basic machinery involved in the stress response in plants includes stress perception, presumably by membrane-bound receptors, leading to the generation of secondary signaling molecules (Kanesaki et al., 2007; Osakabe et al., 2013). Calcium ions, reactive oxygen species, etc., are some key regulatory secondary messengers that get activated under any kind of stress (Takahashi et al., 2011). The signaling drives the necessary switching in the expression pattern of stress-signaling genes (Vierling and Kimpel, 1992) such as genes for the production of osmolytes, chaperones, etc. (Wang et al., 2004; Lee et al., 2008). Finally, the coordinated action of many genes results in tolerance to stress (Fig. 1). Phytohormones such as abscicic acid (ABA), auxins, cytokinins, ethylene, gibberellic acid, jasmonic acid, and salicylic acid are integral to the normal growth and development of plants as well as their response to environmental stresses. A recent review by Verma et al. (2016) has provided a detailed understanding of the role of different phytohormones in response to various environmental stresses. They also describe the crosstalk among the signaling components of different phytohormones, indicating that the environmental stress responses in plants constitute an intricately coordinated and regulated network of stress-responsive and phytohormone-responsive genes. In a similar study, phytohormone application could provide tolerance to wheat plants against abiotic stresses (Asif et al., 2019). Additionally, several important agronomic traits of crop species have been shown to be regulated by various phytohormones (Wen et al., 2018). Genes involved in both phytohormone and stress signaling constitute potential targets for crop improvement. Moreover, many of the protein kinases are known to impart positive roles in crop improvement (Chakradhar et al., 2019). In this regard, we have summarized the potential of utilizing the plant sensory histidine kinases for crop improvement, as histidine kinases (HKs) are important regulators of phytohormone and stress signaling.

2 Plant histidine kinases (HKs) and the multistep phosphorelay (MSP) HKs are the sensory components of a signal transduction superfamily of genes in plants known as the two-component system (TCS). The two-component system is one of the most versatile and robust signaling networks observed in Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00007-3 © 2020 Elsevier Inc. All rights reserved.

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FIG. 1 Schematic diagram to show the abiotic stress signaling and responses in plants. Perception of stress signal via receptors triggers downstream signaling, which involves the activation of distinct shuttling molecules that finally converge at the molecular level to turn on the stress response.

1. Signal perception

E.g., Sensor kinases, channels, histidine kinases

2. Generation of signal carrier

E.g., Calcium ions, ROS

3. Signal transduction

4. Signal transmission by transcription factors

5. Generation of effector molecules

E.g., MAPK, CIPK, SOS3, CDPK

E.g., RR, NAC, bZIP, GATA, WRKY, AP2/ERF

E.g., Osmoprotectants, chaperons, antioxidants, stress proteins

Stress adaptation and tolerance

FIG. 2 Components of TCS signaling machinery. (A) Bacterial TCS signaling components having a simple histidine kinase (HK) and response regulator (RR). (B) Hybrid histidine kinase (HHK) of eukaryotes where His-Asp-His-Asp phosphorelay operates for signaling. Histidine phosphor transfer (HPT) proteins shuttle between HHK and RR.

prokaryotes and plants, but it is absent in animals. The simplest form of TCS signaling found in prokaryotes, also called prototypical TCS, is composed of two types of proteins, the HKs and the response regulators (RRs). Signaling mediated by the prototypical TCS involves the sensing of stimuli by the HK, followed by its autophosphorylation on a conserved histidine residue (Fig. 2). This phosphoryl group is then transferred to a conserved aspartate (Asp) residue on the RR, which then mediates an output involving either transcriptional regulation or posttranslational modifications of other proteins (Stock et al., 2000; Nongpiur et al., 2012). The second type of TCS is found in both prokaryotes and eukaryotes, designated as the His-Asp-His phosphorelay or multistep phosphorelay (MSP). Here, the HK possesses a receiver domain similar to that of the RR and is called a hybrid-HK (HHK). Signaling in MSP proceeds once the signal is perceived by the HHK. This is followed by autophosphorylation of the HHK at the conserved Asp residue of the transmitter domain. The phosphoryl group is then transferred to a conserved Asp residue on the receiver domain of the HHK. This phosphoryl group is then transferred to a conserved his-residue of another protein called the histidine phosphotransfer protein (HPT), which then

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transfers the phosphoryl group to the conserved asp-residue of the cognate RR and generates an output (Stock et al., 2000; Nongpiur et al., 2012). In plants, only hybrid-HKs have been identified and signaling is proposed to proceed via an MSP involving HPTs and RRs. Plant HKs have been shown to regulate diverse physiological processes such as stress signaling (Urao et al., 1999; Tran et al., 2007; Karan et al., 2009; Mersmann et al., 2010; Pham and Desikan, 2012) and hormone signaling such as cytokinin, ethylene, and ABA (Chang et al., 1993; Bleecker et al., 1998; Hwang and Sheen, 2001; Inoue et al., 2001; Liu et al., 2014). The following sections describe how we can utilize the various plant HKs for improving crops with regard to environmental stress tolerance and increasing yield.

3 Histidine kinases for crop improvement in dicots Arabidopsis HKs are the most characterized among plant HK members (Heja´tko et al., 2009; Deng et al., 2010; Kumar and Verslues, 2015; Dautel et al., 2016). Therefore, knowledge from the Arabidopsis HKs can be employed for the development of improved dicot crop varieties. Based on the sequence similarity and conservation of domain, Arabidopsis HKs were classified into three distinct subfamilies: the ethylene receptor family, the phytochrome family, and the receptor family of cytokinin (Hwang et al., 2002). Phytochromes show sequence similarity with the typical histidine kinases, but are functionally reported as the Ser/Thr kinases and do not possess histidine kinase activity (Yeh and Lagarias, 1998). Therefore, they are no longer considered under histidine kinases.

3.1 Ethylene receptors Chang et al. (1993) identified the first functional histidine kinase, ETR1 from Arabidopsis. Five ethylene receptors have now been identified in Arabidopsis: ETR1, ETR2, ERS1, ERS2, and EIN4 (Hwang et al., 2002). However, ETR2, ERS2, and EIN4 do not function as histidine kinases, but rather show similarity to phytochromes and function as Ser/Thr kinases while ERS1 and ETR1 are functional histidine kinases (Moussatche and Klee, 2004). Ethylene regulates multiple facets of growth and development and is also a positive regulator of tolerance to various abiotic and biotic stresses and the activity of the ethylene receptors, especially ETR1, plays a crucial role in ethylene signaling (Khan et al., 2017). It should be mentioned that although some ethylene receptors possess histidine kinase activity, the primary mode of signaling is not through MSP. Ethylene receptors are negative regulators of ethylene signaling, and the binding of ethylene results in the inactivation of the receptors, which leads to downstream ethylene response (Hua and Meyerowitz, 1998). Regulating ethylene signaling through the modulation of ETR1 appears to be a potential strategy to generate crops with improved yield and tolerance to environmental stresses. However, studies have shown that a constitutive ethylene response resulting from mutations in ETR1 results in ethylene hypersensitivity and significant development defects (Cancel and Larsen, 2002). Thus, the modulation of ETR1 for desired phenotypes would require intricate genetic engineering or editing strategies. Ethylene plays a significant role in the ripening of climacteric fruits (Barry and Giovannoni, 2007). The modulation of either ethylene biosynthesis or perception has been shown to affect fruit ripening in tomatoes (Oeller et al., 1991; Nakatsuka et al., 1998; Kevany et al., 2008). Thus, desired traits such as a longer shelf life of fruit crops could be obtained through the silencing of fruit-specific ethylene receptors. Recent studies have also shown that the use of specific ETR1 mutants in tomatoes results in an increase in shelf life by up to 4–5 days (Mubarok et al., 2015).

3.2 Nonethylene receptors and cytokinin receptors Among the histidine kinases that are not ethylene receptors, the Arabidopsis HK, AtHK1/AHK1, was the first to be identified. AtHK1/AHK1 was found to function as a putative osmosensor in Arabidopsis and can functionally complement the osmo-sensitive double mutant Δsln1Δsho1 yeast strain (Urao et al., 1999). Apart from the AtHK1/AHK1, the Arabidopsis genome encodes for five more histidine kinases: CKI1, CKI2/AHK5, AHK2, AHK3, and AHK4/CRE1 (Hwang et al., 2002). Four of these HKs—CKI1, AHK2, AHK3, and AHK4/CRE1—are identified to function as cytokinin receptors (Kakimoto, 1996; Inoue et al., 2001; Yamada et al., 2001; Nishimura et al., 2004; Spı´chal et al., 2004; Riefler et al., 2006). Most of these AHKs are cytokinin as well as abiotic stress responsive (Suzuki et al., 2001; Ueguchi et al., 2001; Jeon et al., 2010; Kumar et al., 2015). However, they differ in their responses to environmental stresses. Arabidopsis AtHK1/AHK1 is the first identified plant osmosensor and positively regulates osmotic as well as water stress signaling in planta (Urao et al., 1999; Tran et al., 2007; Wohlbach et al., 2008). The transcript-abundant analysis of AtHK1/AHK1 suggests that its expression is higher in roots that get induced further under osmotic stress (Wohlbach et al., 2008). Tran et al. (2007) have shown that the AtHK1 contributes to the reduction of the lethal effect of water stress during the vegetative growth of Arabidopsis. In addition, it also alleviates the effect of dehydration stress

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during seed germination. Mutants defective in AtHK1 expression are sensitive to water stress (Wohlbach et al., 2008). Orthologues of AtHK1 in the crop plants such as chickpeas, soybeans, tomatoes, and peas can be identified and utilized to raise abiotic stress-tolerant crops. Interestingly, three of the soybean HKs—GmHK07-09, which are orthologues of AtHK1—show similar expressions as that of AtHK1 (Le et al., 2011). Apart from having a role in abiotic stresses, AtHK1 also has a role in normal plant growth. Tran et al. (2007) have reported that Arabidopsis ahk1/ahk2/ahk3 triple mutants show a stunted phenotype as compared to the wild-type. Thus, AHK1/AtHK1 and orthologues form interesting candidates for use in crop improvement toward osmotic stress tolerance. Extensive work has been carried out to decipher the role of AHKs in abiotic stresses (Tran et al., 2007; Jeon et al., 2010; Jeon and Kim, 2012). Multiple abiotic stresses are known to modulate the expression of these AHKs. However, the response of the Arabidopsis AHKs varies from one stress to others; some of them positively regulate stress signaling while others work in a negative manner (Tran et al., 2007). Early dehydration leads to the induction of the transcript levels of all the AHKs. Apart from this, salinity also results in the accumulation of a higher transcript level of AHK2 and AHK3 (Tran et al., 2007). However, AHK2/3/4 functions as a negative regulator of not only osmotic stress but cold stress as well (Tran et al., 2007; Jeon et al., 2010). Double mutants for ahk2/3 and ahk3/4 are more tolerant to cold stress as well as show sensitivity toward ABA at the time of seed germination ( Jeon et al., 2010). Additionally, ahk2/ahk3 mutation results in poor vegetative growth in Arabidopsis and shows a reduced level of chlorophyll in the mutant leaves, suggesting an important role of AHK2 and AHK3 in leaf development (Riefler et al., 2006). Both AHK2 and AHK3 are cytokinin receptors and defects in cytokinin signaling could have led to defects in plant growth. Bartrina et al. (2017) demonstrated that gain-of-function mutants of AHK2 and AHK3 have higher plant yields as compared to wild-type plants. Functional characterization of the AHK4 in planta has also been carried out (Ueguchi et al., 2001). Arabidopsis AHK4 loss-of-function mutants show resistance in cytokinin-induced greening of calli and also inhibition in shooting as well as root development, clearly indicating that AHK4 functions as a cytokinin receptor (Ueguchi et al., 2001). Various reports show the role of these AHKs in cytokinin signaling and organ development also (Suzuki et al., 2001; Ueguchi et al., 2001; Riefler et al., 2006; Heja´tko et al., 2009). This positive correlation of Arabidopsis HKs with plant growth gives a clear indication that HKs could be potential targets for crop improvement.

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Targeting histidine kinases to improve cereal productivity

Rice, being a model crop species, is the most widely studied cereal. Thus, a majority of the information about histidine kinases in monocots, in general, is obtained from studies in rice. Members of the TCS gene family in rice are diverse. Whole genome analysis to identify putative TCS genes revealed that the rice genome encodes for 51 genes for TCS members. Out of these 51 genes, 14 genes encode for putative HKs, five Hpts, and 32 RRs (Pareek et al., 2006). However, further studies have identified that the phytochromes are not functional histidine kinases. Rather, they function as Ser/Thr kinases and just show sequence similarity with the HKs and hence are removed from the HK family (Schaller et al., 2007). In contrast to Arabidopsis, only a few of the rice HKs have been functionally characterized. In an interesting study, it was revealed that rice HKs are differentially regulated in contrasting rice genotypes under salinity stress (Karan et al., 2009). Additionally, expression data available at various public platforms such as MPSS and the rice microarray database reveal that various abiotic stresses modulate the expression of these HK members (Singh et al., 2015). Moreover, various studies confirm that some of the rice HKs do function as cytokinin receptors (Du et al., 2007; Choi et al., 2012). Complementation assays revealed that some of the rice HKs such as OsHK4, OsHK5, and OsHK6 show cytokinin dependency, indicating that these genes might be coding for cytokinin receptors (Du et al., 2007). The first experimental evidence of rice HK functioning as a cytokinin receptor came in 2012 when Choi and colleagues showed that OsHK6 is actually able to reactivate the AHK2/ AHK3-mediated cytokinin signaling in the ahk2/ahk3 mutant background. Their analysis showed that OsHK6 demonstrates sensitivity toward isopentenyladenine (iP). Additionally, OsHK4 also responds to cytokinins such as trans-zeatin (tZ) and iP (Choi et al., 2012). Both OsHK4 and OsHK6 are able to complement the ahk2-ahk3 mutant phenotype and were able to establish activation of cytokinin-responsive ARR2 and ARR6, respectively. Evidently, rice calli overexpressing OsHK6 show green pigmentation and early shoot induction (Choi et al., 2012). Moreover, similar findings were observed in a study carried out by Ding et al. (2017), where they did mutation-based studies and found that one of the rice mutant Osckt1 demonstrated responses toward cytokinin treatment. Further analysis confirms that the mutation was in the OsHK6 gene (Ding et al., 2017). In addition, the Osckt1 mutant responded to isoprenoid, reconfirming the findings by Choi et al. (2012) and giving a strong indication that OsHK6 is a cytokinin receptor. Recently, the TCS interactome was proposed, which shed light on the important physical interactions of rice TCS proteins and hence signal transfer from HK to RR via HPTs (Sharan et al., 2017). The signaling network clearly depicts and identifies crosstalk mediated by the rice TCS members (Sharan et al., 2017). In another study, it was found that one of the

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rice HKs, OsHK3, plays an important role in ROS homeostasis (Wen et al., 2015). Moreover, the transcript level of OsHK3 rises in response to various abiotic stresses such as ABA, hydrogen peroxide, and drought (Wen et al., 2015). This membrane-localized receptor kinase functions in an ABA-dependent manner to modulate the antioxidant enzyme machinery and hence confers tolerance against the mentioned abiotic stresses via antioxidant machinery (Wen et al., 2015). The available information on rice HKs clearly indicates their role in the regulation of abiotic stress signaling and cytokinin signaling. In that regard, using histidine kinase-based transgenic technology could aid in crop improvement. Moreover, cytokinin homeostasis does affect plant growth in a positive manner. Transgenic rice plants expressing the IPT gene (one of the key enzymes in cytokinin biosynthesis) under water stress had a higher yield as well as total dry mass compared to the wild-type (Peleg et al., 2011). This positive correlation between stress and cytokinin signaling can be utilized for the betterment of crop plants under extremes of environmental conditions. Because cytokinins play a significant role in regulating various yield-associated traits in cereals such as tiller number, panicle number, and panicle branching, it would be interesting to investigate the effects on yield through the modulation of the cytokinin receptor HKs.

5 Genome-wide analysis: Histidine kinases from other plant species Arabidopsis and rice are the most explored plant systems for the functional analysis of HKs. However, over the last decade, various genome-wide studies have identified putative HK members in various plant species (Liu et al., 2014; He et al., 2016a,b). In addition, transcriptome analysis also suggests the role of these members in response to distinct environmental signals (Merchan et al., 2007; Coba de la Pen˜a et al., 2008; Liu et al., 2014; He et al., 2016b). A study carried out on Chinese cabbage identified 20 putative HK members (Liu et al., 2014). Most of these HKs show differential expression in response to salinity, ABA, and drought (Liu et al., 2014). He et al. (2016a) have also identified 20 putative HKs encoded by the tomato genome. Evidence for the participation of these HK members in abiotic stress and hormone signaling is also put forth (He et al., 2016a). A similar analysis carried out in cucumber and watermelon suggests the role of their TCS members in abiotic stresses (He et al., 2016b). H
ericourt et al. (2013) characterized one of the osmosensors from Populus tricocarpa, PtHK1, which can complement yeast osmosensor-deficient mutants and hence function as an osmosensor. HKs of Medicago sativa, MsHK1, and Medicago truncatula, MsHK2, are found to be salinity-responsive as their transcript level rises during salinity stress (Merchan et al., 2007; Coba de la Pen˜a et al., 2008). Though most of the available information on HKs from other plants gives structural information, transcriptome data direct toward their involvement in stress signaling, likewise in rice and Arabidopsis. Provided with the positive response under stress, the detailed functional analysis could indicate the utility of these HKs for the betterment of crops. Fig. 3 summarizes some of the key roles of HKs in plants.

FIG. 3 Representative functional diversity of plant histidine kinases and their role in crop improvement.

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Technology advancement

Crop plants are the primary source of all kinds of food variants. To address challenges such as crop sustainability, food security, food demand, etc., essentially the future is dependent on agriculture and crop research. Nevertheless, advancement in plant biology research has led to a better understanding of crop plants and opened a path for technology advancement. Genome editing for crop modification is the most booming technology in the current scenario. Basically, genome editing is a group of techniques devoted to targeted modification or deletion or the addition of a gene in the genome. Three major techniques of genome editing are zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspersed short palindromic repeats (CRISPR-Cas9). All these tools are widely used to raise crop plants tolerant to biotic stresses and to enrich them with nutrient content (Shukla et al. 2009; Shan et al. 2015). The CRISPR-Cas9 system is grabbing more attention because of the more efficient mode of gene regulation. Recently, CRISPR-Cas9 was used against an osmosensor hos1 gene of Leptosphaeria maculans, a fungal pathogen for canola plants (Idnurm et al., 2017). CRISPR-based hos1 disruption in the pathogen resulted in a lethal effect on pathogenicity and the canola plants were rescued from the fungal infection (Idnurm et al., 2017). Advancements in this area are being made such that even InDels created due to CRISPR-Cas9 can be easily predicted and identified (Hodgens et al., 2017). Using this technique, novel AHK3 null mutants have been identified (Hodgens et al., 2017). Overall, the genome editing techniques are very promising in the current scenario, which helps not just in regulation of gene expression but also in epigenetic modification.

7

Conclusion and future perspectives

The structural and domain diversity within HHKs is responsible for their involvement in distinct signaling pathways. In short, plant HHKs are mainly known to participate in cytokinin, ethylene, and abiotic stress signaling. The identification of Cre1/AHK4/WOL as the first Arabidopsis cytokinin receptor has fueled many studies, which revealed the functional complexities as well as redundancy of the plant HKs (Inoue et al., 2001; Schm€ulling, 2001; Nishimura et al., 2004; Bartrina et al., 2017). In recent years, the regulation of abiotic stress signaling by the plant histidine kinase has also been a topic of active research. Transcriptome data collected from various plant species under key abiotic stresses have also shed light on the variable expression pattern of these plant HKs, and hence their role in stress signaling. However, the findings are mainly restricted only to the model plants, Arabidopsis and rice. Extensive work needs to be done to comprehensively understand the evolution and role of these HKs in crop plants. Comprehensive knowledge of the sensor histidine kinases could aid the current knowledge about stress signaling, which could prove a useful resource in our quest to generate stresstolerant, high-yielding crop varieties. Perhaps this could be solved with recent advancements in plant biology research, which have led to the development of amazing tools for studying and potentially improving crops. These studies clearly indicate a possible path for obtaining the next generation of crops, which can be tailor-made for the geographical region in which they are cultivated.

Acknowledgments The senior research fellowship from IUSSTF to PG is duly acknowledged. The research grants received from the Department of Biotechnology, Government of India, International Atomic Energy Agency (Vienna), Indo-US Science and Technology Forum (IUSSTF), and Department of Science and Technology (DST-PURSE) through Jawaharlal Nehru University are duly acknowledged.

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Whole-genome analysis of Oryza sativa reveals similar architecture of two-component signaling machinery with Arabidopsis. Plant Physiol. 142 (2), 380–397. Pareek, A., Sopory, S.K., Bohnert, H.J., 2009. Abiotic Stress Adaptation in Plants. Springer. Peleg, Z., Reguera, M., Tumimbang, E., Walia, H., Blumwald, E., 2011. Cytokinin-mediated source/sink modifications improve drought tolerance and increase grain yield in rice under water-stress. Plant Biotechnol. J. 9 (7), 747–758. Pham, J., Desikan, R., 2012. Modulation of ROS production and hormone levels by AHK5 during abiotic and biotic stress signaling. Plant Signal. Behav. 7 (8), 893–897. Riefler, M., Novak, O., Strnad, M., Schm€ulling, T., 2006. Arabidopsis cytokinin receptor mutants reveal functions in shoot growth, leaf senescence, seed size, germination, root development, and cytokinin metabolism. Plant Cell 18 (1), 40–54. Schaller, G.E., Doi, K., Hwang, I., Kieber, J.J., Khurana, J.P., Kurata, N., Mizuno, T., Pareek, A., Shiu, S.H., Wu, P., Yip, W.K., 2007. Nomenclature for two-component signaling elements of rice. Plant Physiol. 143 (2), 555–557. Schm€ ulling, T., 2001. CREam of cytokinin signalling: receptor identified. Trends Plant Sci. 6 (7), 281–284. Shan, Q., Zhang, Y., Chen, K., Zhang, K., Gao, C., 2015. Creation of fragrant rice by targeted knockout of the Os BADH 2 gene using TALEN technology. Plant Biotechnol. J. 13 (6), 791–800. Sharan, A., Soni, P., Nongpiur, R.C., Singla-Pareek, S.L., Pareek, A., 2017. Mapping the ‘two-component system’ network in rice. Sci. Rep. 7 (1), 9287. Shukla, V.K., Doyon, Y., Miller, J.C., DeKelver, R.C., Moehle, E.A., Worden, S.E., Mitchell, J.C., Arnold, N.L., Gopalan, S., Meng, X., Choi, V.M., 2009. Precise genome modification in the crop species Zea mays using zinc-finger nucleases. Nature 459 (7245), 437. Singh, A.K., Kumar, R., Pareek, A., Sopory, S.K., Singla-Pareek, S.L., 2012. Overexpression of rice CBS domain containing protein improves salinity, oxidative, and heavy metal tolerance in transgenic tobacco. Mol. Biotechnol. 52 (3), 205–216. Singh, A., Kushwaha, H.R., Soni, P., Gupta, H., Singla-Pareek, S.L., Pareek, A., 2015. Tissue specific and abiotic stress regulated transcription of histidine kinases in plants is also influenced by diurnal rhythm. Front. Plant Sci. 6, 711. Singla-Pareek, S.L., Yadav, S.K., Pareek, A., Reddy, M.K., Sopory, S.K., 2006. Transgenic tobacco overexpressing glyoxalase pathway enzymes grow and set viable seeds in zinc-spiked soils. Plant Physiol. 140 (2), 613–623. Spı´chal, L., Rakova, N.Y., Riefler, M., Mizuno, T., Romanov, G.A., Strnad, M., Schm€ulling, T., 2004. Two cytokinin receptors of Arabidopsis thaliana, CRE1/AHK4 and AHK3, differ in their ligand specificity in a bacterial assay. Plant Cell Physiol. 45 (9), 1299–1305. Stock, A.M., Robinson, V.L., Goudreau, P.N., 2000. Two-component signal transduction. Annu. Rev. Biochem. 69, 183–215.

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Suzuki, T., Miwa, K., Ishikawa, K., Yamada, H., Aiba, H., Mizuno, T., 2001. The Arabidopsis sensor His-kinase, AHK4, can respond to cytokinins. Plant Cell Physiol. 42 (2), 107–113. Takahashi, F., Mizoguchi, T., Yoshida, R., Ichimura, K., Shinozaki, K., 2011. Calmodulin-dependent activation of MAP kinase for ROS homeostasis in Arabidopsis. Mol. Cell 41 (6), 649–660. Tran, L.S.P., Urao, T., Qin, F., Maruyama, K., Kakimoto, T., Shinozaki, K., Yamaguchi-Shinozaki, K., 2007. Functional analysis of AHK1/ATHK1 and cytokinin receptor histidine kinases in response to abscisic acid, drought, and salt stress in Arabidopsis. Proc. Natl. Acad. Sci. 104 (51), 20623–20628. Ueguchi, C., Sato, S., Kato, T., Tabata, S., 2001. The AHK4 gene involved in the cytokinin-signaling pathway as a direct receptor molecule in Arabidopsis thaliana. Plant Cell Physiol. 42 (7), 751–755. Urao, T., Yakubov, B., Satoh, R., Yamaguchi-Shinozaki, K., Seki, M., Hirayama, T., Shinozaki, K., 1999. A transmembrane hybrid-type histidine kinase in Arabidopsis functions as an osmosensor. Plant Cell 11 (9), 1743–1754. Verma, V., Ravindran, P., Kumar, P., 2016. Plant hormone-mediated regulation of stress responses. BMC Plant Biol. 16, 86. https://doi.org/10.1186/ s12870-016-0771-y. Vierling, E., Kimpel, J.A., 1992. Plant responses to environmental stress. Curr. Opin. Biotechnol. 3 (2), 164–170. Wang, W., Vinocur, B., Shoseyov, O., Altman, A., 2004. Role of plant heat-shock proteins and molecular chaperones in the abiotic stress response. Trends Plant Sci. 9 (5), 244–252. Wen, F., Qin, T., Wang, Y., Dong, W., Zhang, A., Tan, M., Jiang, M., 2015. OsHK3 is a crucial regulator of abscisic acid signaling involved in antioxidant defense in rice. J. Integr. Plant Biol. 57 (2), 213–228. Wen, C.-K., Zhao, Y., Yong, L.R., 2018. Hormonal control of important agronomic traits. Front. Plant Sci. 9, 1504. https://doi.org/10.3389/ fpls.2018.01504. Wohlbach, D.J., Quirino, B.F., Sussman, M.R., 2008. Analysis of the Arabidopsis histidine kinase ATHK1 reveals a connection between vegetative osmotic stress sensing and seed maturation. Plant Cell 20 (4), 1101–1117. Yamada, H., Suzuki, T., Terada, K., Takei, K., Ishikawa, K., Miwa, K., Yamashino, T., Mizuno, T., 2001. The Arabidopsis AHK4 histidine kinase is a cytokinin-binding receptor that transduces cytokinin signals across the membrane. Plant Cell Physiol. 42 (9), 1017–1023. Yeh, K.C., Lagarias, J.C., 1998. Eukaryotic phytochromes: light-regulated serine/threonine protein kinases with histidine kinase ancestry. Proc. Natl. Acad. Sci. 95 (23), 13976–13981.

Chapter 8

Recent efforts in developing high-yield, drought-tolerant rice varieties Nitika Sandhua,b, Shailesh Yadava and Arvind Kumara,c a

Rice Breeding Platform, International Rice Research Institute, Metro Manila, Philippines, b Punjab Agricultural University, Ludhiana, Punjab, India,

c

IRRI South Asia Regional Centre (ISARC), Varanasi, Uttar Pradesh, India

1 Introduction 1.1 Historical famines and food shortages in the world The world population is increasing at an alarming rate and is projected to reach 9.8 billion in 2050, up from the existing 7.6 billion people in 2017 (UN, 2017). The increase in population poses a challenge to the sustainability of food security, not only in underdeveloped nations but also in developing and developed nations. World food production will require an increase of 70% by 2050 and many of the developing countries will have to double their food production (FAO, 2017) to sustain achieved food security. Rising fuel prices, depletion of underground water, urbanization, habitat loss, and frequent floods and droughts due to climate change are the major obstacles to achieve the projected increase of food production. The SDG 2 (sustainable development goal) aims at ending hunger, achieving better nutrition and food security, and promoting sustainable agriculture by 2030 (FAO, 2017). Among more than 30 definitions (Maxwell and Frankenberger, 1992) of food security, “access by all (the) world’s people at all times to safe, sufficient, and nutritious foods to meet their dietary needs and food preferences for an active healthy life” (Collier and Dollar, 2002) is the most acceptable one. The main pillars of food security are access, availability, and utilization of nutritious food. Many countries are self-sufficient in food production, but still people suffer from hunger as well as nutritional deficiency. Therefore, access to not only food but also to more nutritious food is equally as important as producing surplus food. The third pillar of food security is proper utilization of accessed food by the people. Africa and Asia are the most prevailing regions compared to developed regions (FAO, 2017) facing famine and food insecurity. Food insecurity, malnutrition, and poverty are very interconnected phenomena. The lack of easy access to sufficient and nutritious food for the proper growth and development of people leads to food insecurity. Food insecurity has been classified as transitory and chronic food insecurity is based on its consistency and severity. In a situation of chronic food insecurity, households are unable to access the needed food, which is the primary cause of poverty in the world. Chronic food insecurity exists over prolonged periods of time. Transitory food insecurity is intermittent and can be further divided into seasonal and temporary food insecurities. The sudden and unpredictable outbreaks of abiotic or biotic stresses such as drought, flood, or disease epidemics are the root cause of temporary food insecurity. Seasonal food insecurity persists when food is continuously unavailable in a region due to insufficient food stocks or government policies. In the worst conditions, transitory food insecurity may be converted into famine (Thomson and Metz, 1996). Crop failure, population imbalance, natural disasters, poor government policies, conflicts, and political actions trigger mass mortality. Some of the famous famines of the world are listed in Table 1.

1.2 Food security and malnutrition Nutritional security, a sufficient nutritional supply in terms of energy, protein, minerals, and vitamins, is needed for all the world’s people at all times. Nearly two billion women and children, particularly from Asia and Africa, are suffering from “hidden hunger” as a result of micronutrient (iron, zinc, and vitamin A) deficiency. About 795 million people worldwide were reported as malnourished in 2014–16 (FAO, 2015). A significant development in fighting food starvation over the past years has been reported under ongoing climate change, volatile high prices, higher food and fuel prices, rising unemployment and underemployment rates (FAO, 2015). The percentage of undernourished people of the total world population Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00008-5 © 2020 Elsevier Inc. All rights reserved.

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112 Advancement in crop improvement techniques

TABLE 1 Chronological history of famous famines around the world. Famine

Year

Region

Caused by

Mortality

Irish Potato

1846–1847

Ireland

Late blight disease of potato

1,000,000

Soviet

1921–22

Soviet Union

Drought

9,000,000

Hunan

1929

China

Drought and conflict

2,000,000

Ukraine

1932–34

Soviet Union

Government policy

7,000,000–8,000,000

Great Bengal

1943–44

Bengal

Cyclone, Helminthosporium oryzae fungus and sociopolitics

2,100,000–3,000,000

Great Chinese

1958–62

China

Floods, drought, government policy

33,000,000

Biafra

1967–1970

Nigeria

Conflict

1,000,000

India

1972–1973

Maharashtra

Drought

13,000

Bangladesh

1974

Bangladesh

Floods

1,500,000

Cambodia

1975–1979

Cambodia

Conflict

2,000,000

Uganda

1980–1981

Karamoja

Drought and conflict

30,000

Ethiopia

1983–1985

–

Drought

590,000–1,000,000

Sudan

1984–1985

Darfur

Drought

250,000

Somalia

1991–1993

–

Drought and government policies

300,000–500,000

North Korea

1995–1999

North Korea

Floods

28,000,000

Global Food Security Crisis

2007–2008

Various regions of the world

Sudden food price increase due to increase in price of raw oil

–

has declined from 18.6% in 1990–92 to 10.9% in 2014–16. A large number of undernourished people live in the developing world, but tremendous success has been achieved by the most populous countries such as China and India in overall hunger reduction in recent years (Sharma et al., 2016). The World Food Summit in 2015 declared rapid and positive progress in reducing hunger in Latin America as well as the eastern and southeastern regions of Asia, but in Central Africa and Western Asia, the incidence of undernourished people increased compared to earlier estimates. Positive efforts should be undertaken globally as well regionally to improve the current status of food and nutritional security of these highly effected countries. Improving the nutritional status of children will increase their ability to fight infectious diseases as well as attain proper physical growth and intellectual development. Natural disasters such as floods and drought have claimed millions of lives and caused global food and nutritional security (FAO, 2015).

2

Climate change and its effect on food production

The Green Revolution (GR) from 1960 to 1980 transformed many of the developing countries, particularly Asian regions, from suffering a severe food crisis to being food self-sufficient and further extended the surplus food grain production (Pingali, 2012). No doubt, the GR had a lot of positive impacts by increasing crop productivity exponentially and saving the lives of millions of people. The use of semidwarf varieties, irrigation, mechanization, and chemical fertilizers increased the yields to 208% for wheat, 109% for rice, and 157% for maize for all developing countries between 1960 and 2000 (FAO, 2004). At the same time, the extensive utilization of the dwarfing allele sd1 in the development of dwarf, high-yielding, lodging-resistant, fertilizer-responsive rice varieties, and the advancement of breeding procedures under the most favorable conditions of water-nutrient availability caused the loss of many abiotic stress-tolerant alleles during the Green Revolution,

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resulting in the decreased tolerance of crops to abiotic stresses. The positive alleles of abiotic stress tolerance, namely drought, have been reported to have tight linkages with many undesirable traits such as tall height, low yield potential, and early maturity duration; they were eliminated from GR varieties during the selection process (Vikram et al., 2015). The effect of climatic change has posed a serious threat to world food security. Global climate change includes the occurrence and effect of droughts, floods, extreme temperature events, enhanced atmospheric carbon dioxide, ground-level ozone concentrations, and rises in sea levels. The IPCC (2007) reports highlighted the global impact of climate change and its variability on world agriculture and food security. Although a positive impact of climate change on crop production is predicted in some parts of world located within the northern widths, severe negative effects of these changes have been predicted in hot and dry parts of the world (Gregory et al., 2005). In the developing countries of Asia and Africa, the heat waves and drought are more intensified (Sivakumar et al., 2005). This has urged crop scientists to develop climate-resilient varieties with stable yields under variable climatic conditions and the increasing threats of droughts, floods, and high temperatures. Understanding the potential impact of changing climatic conditions on rice-based production systems is essential for the development of appropriate varieties and strategies to achieve long-term agriculture sustainability. The development and cultivation of crop varieties with multiple tolerances to abiotic stresses such as flood and drought are the most desirable breeding activities to minimize yield losses. The complexity of the genetic architecture and unpredictable climatic conditions poses a challenging task to breed varieties against these abiotic stresses.

3 Drought The major abiotic factors such as drought, flood, high temperature, and salinity are serious threats to world food security and have been reported to cause as high as a 70% yield reduction in crop production (Thakur et al., 2010). Among the abiotic factors, drought is the most disruptive, and extreme events of ongoing climate change affect millions of people worldwide every year by this single event. Drought is a recurring climatic event due to less precipitation over a time span over land, including the wet and humid regions of the world (Dai, 2011). Wilhite (2000) classified drought as: (i) meteorological drought, which is below normal precipitation, prevails over a period of months to years and is accompanied by above normal temperatures. The main causes of meteorological drought are high pressure in atmospheric gaseous circulation in a large-scale area or an increase in sea surface temperature (Hoerling et al., 2006). (ii) Agricultural drought, which is below average precipitation with dry soil, less-frequent rain events, and evaporation losses above normal. Crop production and productivity will be drastically affected due to the agricultural drought. (iii) Hydrological drought, which is when the water levels of reservoirs such as lakes, aquifers, and rivers fall below the mean level due to the continuous depletion of stored water. Apart from less precipitation, other factors such as poor uneven rainfall distribution over the crop growth period, water management, human interference, and land erosion are also responsible for enhanced droughts. Drought severity can be estimated based on the intensity of the rainfall absence, the duration of the rainfall absence, the coverage of the area for rainfall absence over land, and finally the reduction in yield. Drought can prevail from a few days to months or even years based on rainfall events, soil moisture, and water storage deficits (Stahle et al., 2007). The development of drought-tolerant varieties is the ultimate goal of crop breeders to reduce crop yield loss and to ensure the estimated world food production. However, breeding drought-tolerant varieties is extremely difficult due to the complexity of the trait (Reynolds and Tuberosa, 2008; Anami et al., 2009), the polygenic inheritance, and the difficulty in the selection of lines under drought. High G  E interactions and low heritability also make the task difficult (Fleury et al., 2010). Undesirable linkages of drought tolerance with tall plant height, low yield potential, and earliness further add to the complexity in breeding high-quality, high-yield, drought-tolerant varieties. Accordingly, traditional plant breeding approaches have met limited success in improving drought tolerances due to these reasons.

4 Biology of drought tolerance Drought has been reported to have intensive effects on the vegetative and reproductive growth stages of cereal crops (Kumar et al., 2008; Sabetfar et al., 2013; Farooq et al., 2017). The elucidation of the responses, tolerance, and adaptation of the crop plant to improve the resistance ability and to ensure high crop productivity under unfavorable environmental conditions has now become imperative. Drought tolerance is a complex trait controlled by polygenes, whose expressions are under the control of various genetic and environmental factors and interactions. Plants exhibit a range of biochemical, physiological, morphological, and molecular responses to combat the effect of drought stress. Adaptation and tolerance to drought stress are crucial concerns to study and to develop improved methods and varieties for drought-prone areas. Holistic breeding for drought tolerance requires the proper knowledge of suitable traits, well-defined breeding and

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transgenic approaches, novel and high-throughput phenotypic/genotyping strategies, and understanding the behavior of genes/genetic loci and their expression/interaction patterns (Kumar et al., 2014). There is an urgent need to maintain the economic yield of rice plants through the involvement of diverse stress-responsive mechanisms.

5

Trait characterization and phenotyping as selection criteria

To understand the drought-tolerance mechanism, the characterization of drought-responsive traits and the standardization of screening protocols are necessary to develop drought-tolerant rice varieties. The appropriate estimation of the type, intensity, and degree of drought with a suitable screening strategy for drought tolerance is a very key step. Screening of drought-tolerant material based on physiological/morphological and biochemical measures (Turner et al., 2007); direct selection for the grain yield under both drought stress and nonstress conditions simultaneously with biotic stress screening (Kumar et al., 2014; Vikram et al., 2011; Dixit et al., 2014a; Sandhu et al., 2014); and the use of appropriate statistical methods to clearly distinguish drought-tolerant and susceptible lines (Rizza et al., 2004) may be considered appropriate strategies for drought phenotyping. The comparative phenotypic evaluation of breeding lines for grain yield under reproductive stage drought stress under a controlled environment has shown the moderate heritability of grain yield under reproductive stage drought stress (Venuprasad et al., 2007, 2008; Kumar et al., 2014; Vikram et al., 2011; Dixit et al., 2014b). The heritability for grain yield under drought has been similar to the heritability of the secondary traits, indicating the selection for grain yield under drought as being as effective as the selection for secondary traits related to drought. In addition, high-throughput phenotypic screening involving CID (isotope discrimination; Richards et al., 2010), canopy spectral reflectance infrared thermography (Sirault et al., 2009), pulse amplitude-modulated fluorometry (Baker, 2008), NDVI (normalized difference vegetation index; Jones and Vaughan, 2010), PRI (photosynthetic reflective index; Gamon et al., 1992), PET (positron emission tomography), MRI (magnetic resonance imaging), and NMR (nuclear magnetic resonance) (Melkus et al., 2011) also provides a better understanding of different physiomorphological traits contributing to grain yield. Phenomic tools, airborne instruments, planes, and multispectral sensors can estimate the soil characteristics, water-nutrient availability and movement, and land productivity. The combination of all these analytical tools and high-throughput techniques is essential for standardized phenotyping to enable a trait and varietal development program to develop better drought-tolerant varieties.

6 Physiological, morphological, and biochemical response and derivations to tolerance The grain yield component of a crop plant integrates many processes in a complex manner. Therefore, it is hard to infer how plants accumulate, unite, and exhibit the unclear, complex, unknown internal growth and developmental processes over the entire life cycle of the crop. Grain yield is the result of the association and expression of several plant physiological, morphological, and biochemical factors. Various physiological responses comprising stomatal conductance, osmoregulation (Lanceras et al., 2004; Campos et al., 2004), leaf water potential ( Jongdee et al., 2006; Kumar et al., 2008), photosynthesis (Long et al., 2006), wateruse efficiency (Condon et al., 2004), source to sink reserves mobilization (Yamada et al., 2005), change in internal CO2 concentration, membrane integrity (Deshmukh et al., 1991), and transpiration efficiency (Cosentino et al., 2007) are reported to have important contributions to drought tolerance in plants. The realistic understanding, screening, and role of morphological traits such as root length, depth, thickness, penetration ability, root volume, fresh and dry root weight (Asch et al., 2005; Sandhu et al., 2011), lateral root, branching, nodal root, leaf area, size, senescence, shape (Lanceras et al., 2004), leaf cuticle, leaf extension (Passioura, 1996), waxiness, flag leaf length, width and angle (Lonbani and Arzani, 2011), number of xylem thickness, early flowering, harvest index (Kumar et al., 2014), and the differential growth response of roots and shoots could result in a significant yield advantage under drought stress. Drought tolerance involving biochemical responses, including the activation of stress metabolites; antioxidative enzymes such as catalase, superoxide dismutase, peroxidases, monodehydroascorbate reductase, glutathione reductase, and reactive oxygen species; and polyamines and osmotic regulators (Robin et al., 2003; Chaves et al., 2003) correlates with the positive response of plant defense systems to drought tolerance. These factors play an important role in the regulation of signal transduction and gene expression.

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7 Breeding strategies 7.1 Population development and improvement Drought-tolerant rice varieties should have a better yield over the presently available cultivars under drought stress, together with higher yield under irrigated conditions or at least no yield penalty under irrigated conditions across locations, environments, seasons, and conditions (Rizza et al., 2004; Ober et al., 2004; Pidgeon et al., 2006), in addition to being less sensitive toward biotic stresses, and possessing good grain, cooking, and nutritional quality. The development of an improved breeding population entails the exploitation of genetic diversity to identify specific donors and recipients with special characteristics adaptable for a specific or diverse environment. In addition to the desirable drought-tolerance trait, the traditional landraces/donors have various undesirable characteristics such as tall plant height, poor grain cooking and eating quality, low yield productivity; and little ground cover. Modern cultivars possess, along with the desirable traits, medium plant height, lodging resistance, biotic stress tolerance, and a medium to slender grain type, but are highly susceptible to drought. An improved population involving multiple tolerance donor parents in the background of high-yielding modern improved cultivars is necessary to get new combinations of genes and traits with high heritability and at par performance of genotypes across variable growing environmental conditions (Kumar et al., 2014). Suitable drought-tolerant donors such as PSBRc80, PSBRc68, PSBRc82, Dagaddeshi, Aday Sel, Aus 276, Kali Aus, Kalia, Apo, N22, and Dular IR77298-14-1-2 have been identified at the International Rice Research Institute (IRRI) and used in various complex modified conventional and markerassisted breeding programs to improve grain yield under drought stress. Several marker-assisted breedings of drought-tolerant lines without undesirable linkages have been developed through MAB (marker-assisted breeding) approaches. A number of recombinant inbred lines (RILs) involving crosses of two, three, four, five, and six parents contrasting for the traits of interest, subsequently followed by selfing and advancement through the single-seed descent (SSD) method were developed. In addition, nearly homozygous lines and backcross inbred lines (BILs) involving crossing of two parents contrasting for the target trait, backcrossed (n times) to recurrent parents to develop a BCnF1 population and then selfed through the SSD method were also developed (Vikram et al., 2011; Yadaw et al., 2013; Kumar et al., 2014; Mishra et al., 2013; Sandhu et al., 2014; Swamy et al., 2013). BIL populations are particularly appropriate for the introgression of desirable regions for traits of interest (0.1%) from exotic wild germplasm species to domestic varieties (Peterson, 2002) with the retrieval of 99.9% of the recurrent parent genome. Advanced backcross populations suitable for finemapping purposes (Dixit et al., 2012a) when large near-isogenic line (NIL) populations are needed with different segments of the targeted regions and similar genetic backgrounds were developed at IRRI. Double haploid (DH) populations, combining the advantages of attaining homozygosity at an early generation, have been developed for seedling and reproductive stage drought-tolerance studies in rice (Xu et al., 2011; Lanceras et al., 2004).

7.2 Conventional breeding The traditional conventional breeding approach is time-consuming as well as cost- and labor-intensive with the high probability of the transfer of undesirable genes. A modified conventional breeding approach involving the sequential selection and screening of a large population under both a normal irrigated situation as well as drought conditions together with screening for biotic stresses and grain quality has helped combine high yield under normal situations and good yield under drought stress. It involves the phenotypic and biotic stress (bacterial late blight and blast) screening of a large F2 segregating population under nonstress (control; NS) conditions, followed by screening of F3 plants under reproductive stage drought stress (RS), then phenotypic (plant type, plant height, grain type) screening of F4 and F5 generations under NS, followed by F6 generation screening under both NS and RS conditions. The best promising lines that have outperformed under both NS and RS conditions with acceptable plant type and grain quality traits will be evaluated under observational and advanced yield trials before the nominations of lines for multilocation trials. This defined, efficient, precise, cost- and labor-effective conventional breeding approach may speed up the development of high-yielding, drought-tolerant rice varieties with desirable characteristics and a high frequency of favorable genes. A number of conventional breeding programs worldwide have developed and applied systematic breeding programs that led to the development of several abiotic and biotic stress-tolerant varieties of cereal food cross such as rice (Kumar et al., 2014; Sandhu et al., 2018), soybeans, the common bean (Brick et al., 2008), wheat (Haley et al., 2007; Baenziger et al., 2008), chickpeas (Singh et al., 1996), and barley (Obert et al., 2008), and many of these varieties are presently under cultivation by farmers (Table 2). The modified conventional drought breeding program at the IRRI based

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TABLE 2 Drought-tolerant crop varieties released in different countries. S.N.

Crop

Variety name

Country

1

Rice

Sahod Ulan 1

Philippines 2009, Rainfed Lowland

2

Rice

Sahbhagi dhan

India 2010, Rainfed Lowland

3

Rice

BRRI dhan 56

Bangladesh 2011, Rainfed Lowland

4

Rice

Sookha dhan 1

Nepal 2011, Rainfed Lowland

5

Rice

Sookha dhan 2

Nepal 2011, Rainfed Lowland

6

Rice

Sookha dhan 3

Nepal 2011, Rainfed Lowland

7

Rice

Katihan 1

Philippines 2011, Upland

8

Rice

Tarharra 1

Nepal, 2009, Rainfed lowland

9

Rice

Sahod Ulan 3

Philippines 2011, Rainfed Lowland

10

Rice

Sahod Ulan 5

Philippines 2011, Rainfed Lowland

11

Rice

Sahod Ulan 6

Philippines 2011, Rainfed Lowland

12

Rice

Inpago Lipi GO1

Indonesia 2011, Upland

13

Rice

Inpago Lipi GO2

Indonesia 2011, Upland

14

Rice

CR Dhan 40

India 2012, Aerobic

15

Rice

CR Dhan 201 (IET 21924)

India 2013, Aerobic

16

Rice

CR Dhan 202 (IET 21917)

India 2013, Aerobic

17

Rice

CR Dhan 203 (IET 21920)

India 2013, Aerobic

18

Rice

CR Dhan 204 (IET 21922)

India 2013, Aerobic

19

Rice

DRR dhan 43 (IET 22080)

India 2013, Irrigated

20

Rice

DRR dhan 44 (IET 22081)

India 2013, Irrigated

21

Rice

M’ZIVA

Mozaobique 2013, Rainfed lowland

22

Rice

Sahod Ulan 12 (NSICRc348)

Philippines 2013, Rainfed lowland

23

Rice

UPIA 3

Nigeria 2013,Rainfed Lowland

24

Rice

Sukha dhan 4

Nepal, 2014, Rainfed Lowland

25

Rice

Sukha dhan 5

Nepal 2014, Rainfed Lowland

26

Rice

Sukha dhan 6

Nepal 2014, Rainfed Lowland

27

Rice

CR dhan 205

India 2014, Aerobic

28

Rice

DRR dhan 42

India 2014, Rainfed Lowland

29

Rice

Kaithan 2 (NSIC2014Rc25)

Philippines 2014,Upland

30

Rice

Kaithan 3 (NSIC2014Rc27)

Philippines 2014,Upland

31

Rice

Tripura Khara dhan 1

Tripura, India, 2014, Rainfed lowland

32

Rice

Tripura Khara dhan 2

India, Tripura, 2014, Rainfed lowland

33

Rice

Tripura Hak chuk1

India, Tripura, 2014, Rainfed Upland

34

Rice

Tripura Hak chuk2

India, Tripura, 2014, Rainfed Upland

35

Rice

Tripura Aus dhan 1

India, Tripura, 2014, Rainfed lowland

36

Rice

Inpago Lipi G04

Indonesia, 2014, Upland

37

Rice

BRRI dhan 66

Bangladesh, Rainfed Lowland, 2014

38

Rice

Yaenelo 4

Myanmar, 2015, Rainfed Lowland

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TABLE 2 Drought-tolerant crop varieties released in different countries—cont’d S.N.

Crop

Variety name

Country

39

Rice

BRRI dhan 71

Bangladesh, 2015, Rainfed Lowland

40

Rice

Swarna Shreya

India, 2016, Rainfed Lowland

41

Rice

Ardhjal (Identified for release)

India, 2016, Aerobic

42

Rice

Sahod Ulan 15 (NSIC Rc422)

Philippines, 2015, Rainfed Lowland

43

Rice

Sahod Ulan 20 (NSIC Rc432)

Philippines, 2015, Rainfed Lowland

44

Rice

MPATSA

Malawai, Irrigated ecology

45

Rice

KATETE

Malawai, Irrigated ecology

46

Rice

CAR 14

Cambodia, Rainfed direct seeded

47

Rice

CAR 15

Cambodia, Rainfed

48

Rice

Impari 40

Indonesia, Rainfed Lowland

49

Rice

Yaenelo 5

2016, RL, Myanmar

50

Rice

Yaenelo 6

2016, RL, Myanmar

51

Rice

Yaenelo 7

2016, RL, Myanmar

52

Rice

Sahod Ulan 26

Philippines, 2016, Rainfed Lowland

53

Rice

Sahod Ulan 24

Philippines, 2016, Rainfed Lowland

54

Rice

CR dhan 801

India, 2017, Rainfed Lowland

55

Rice

Baghugunidhan1

Nepal, 2017, Rainfed Lowland

56

Rice

Baghugunidhan 2

Nepal, 2017, Rainfed Lowland

57

Rice

Rajendra Neelam

India, Bihar, 2017

58

Maize

BH661

Ethiopia

59

Maize

HB513

Tanzania

60

Maize

Longe 10H

Uganda

61

Maize

SC719

Malawi

62

Maize

Pan53

Zimbabwe

63

Maize

Sammaz15

Nigeria

64

Maize

ZM523

Angola

65

Wheat

Ripper

United States

66

Wheat

Willow creek

Australia

67

Wheat

Prairie red

United States

68

Barley

Giza 2000

Egypt

69

Barley

Giza 132

Syria

70

Barley

Lignee 686

Egypt

71

Barley

Bentley

Canada

118 Advancement in crop improvement techniques

on the direct selection for grain yield under irrigated nonstress as well as reproductive stage drought stress has led to the development and release of 30 high-yielding, drought-tolerant rice varieties across Africa as well as South and Southeast Asia since 2009.

7.3 Marker-assisted breeding Several studies have been conducted on mapping populations involving one drought-tolerant donor and one droughtsusceptible line. They have reported the identification of genetic regions associated with drought-tolerance secondary traits (Tripathy et al., 2000; Price and Tomos, 1997) and grain yield under drought (Bernier et al., 2007; Kumar et al., 2008; Vikram et al., 2011). The careful consideration of the mapping population structure, size, and precise genotypic approach is an important preliminary step in a genetic study to identify genetic loci linked with complex traits such as drought. Various genotyping strategies such as whole-genome genotyping (WGG), selective genotyping (SG), bulk segregant analysis (BSA) (Vikram et al., 2011; Ghimire et al., 2012; Mishra et al., 2013; Yadaw et al., 2013), genotyping by sequencing, genome-wide association studies (GWAS) (Begum et al., 2015), and introgression in different genetic backgrounds involving MARS (marker-assisted recurrent selection; Xu and Crouch, 2008; Ribaut and Ragot, 2006) and MAB (marker-assisted backcrossing; Venuprasad et al., 2009; Mishra et al., 2013; Yadaw et al., 2013; Sandhu et al., 2015) have been reported to be efficient in marker-assisted breeding programs. Systematic, precise, cyclic (control and reproductive stage drought stress), multilocation, multienvironment and multiseason phenotyping of mapping populations in repeated years and the identification of specific polymorphic molecular markers for specific backgrounds have led to the identification of major, stable, large, and consistent effect quantitative trait loci (QTL) (Vikram et al., 2011; Ghimire et al., 2012; Yadaw et al., 2013; Mishra et al., 2013; Sandhu et al., 2014) for grain yield under drought stress. Several mapping populations involving drought-tolerant donors and modern high-yielding widely cultivated megavarieties as recipients were developed at IRRI (Vikram et al., 2011; Yadaw et al., 2013; Mishra et al., 2013; Sandhu et al., 2014). Cost-effective phenotyping and genotyping approaches involving large segregating populations (to cover huge genetic variation) have led to the identification of 12 large major effect QTLs (qDTY1.1, qDTY2.1, qDTY2.2, qDTY2.3, qDTY3.1, qDTY3.2, qDTY4.1, qDTY6.1, qDTY6.2, qDTY9.1, qDTY10.1, and qDTY12.1) with consistent effects in the background of IR64, MTU1010, Swarna, Sabitri, TDK1, and Vandana (the high-yielding, drought-susceptible, widely cultivated and acceptable popular rice varieties, except for Vandana, which is tolerant to drought) (Bernier et al., 2007; Vikram et al., 2011; Venuprasad et al., 2012; Ghimire et al., 2012; Mishra et al., 2013; Yadaw et al., 2013; Swamy et al., 2013; Sandhu et al., 2014; Dixit et al., 2014b). The genomic locations of these identified stable grain yield QTLs under reproductive stage drought are presented in Fig. 1. The stability of the genetic loci across seasons, locations, backgrounds, environments, and years has been reported in many studies, including Bernier et al., 2007 (qDTY12.1; 21 experiments conducted at IRRI and in eastern India; at IRRI, Philippines, and Nepal (Mishra et al., 2013) and Yadaw et al., 2013 (qDTY3.2; IRRI and Nepal). The seven genetic loci, qDTY1.1 (Ghimire et al., 2012; Vikram et al., 2011; Venuprasad et al., 2012), qDTY2.2 (Sandhu et al., 2014; Swamy et al., 2013), qDTY3.1 (Vikram et al., 2011; Venuprasad et al., 2009), qDTY3.2 (Yadaw et al., 2013; Ghimire et al., 2012), qDTY4.1 (Swamy et al., 2013), qDTY6.1 (Vikram et al., 2011), and qDTY12.1 (Yadaw et al., 2013; Bernier et al., 2007) have shown consistent effects across two or more ecosystems and genetic backgrounds. Furthermore, the reported QTLs qDTY1.1, qDTY2.2, qDTY6.1, and qDTY12.1, in addition to their effect under drought conditions, have shown effect under direct-seeded (DSR) and aerobic environments, representing the role of some of the common plant traits toward grain yield improvement across different cultivable conditions (Bernier et al., 2007; Sandhu et al., 2013). In addition to rice, QTLs for drought and drought-related traits have been reported in other crops (Table 3).

7.4 Fine mapping of identified genetic regions Molecular and physiological characterizations and fine mapping of identified QTL regions to identify the underlying candidate genes within the locus as well as the identification of tightly linked markers and interacting loci to capture all the positively interacted desirable gene combinations are essential steps before initiating a QTL introgression program. The detection and knowledge on the useful candidate genes underlying within the loci and the effective use of the identified loci in a wide background/environment prior to the introgression program may further strengthen the drought marker-assisted breeding program by avoiding the undesirable linkages associated with the identified QTLs. Fine mapping of large consistent effect QTL qDTY12.1 highlights the concept of “multigene directs the functionality of one genetic locus” and further supports the complex mature of grain yield under drought stress (Dixit et al., 2015). The partitioning of qDTY12.1 into subQTLs and multiple intra-QTL genes (OsNAM12.1 transcription factor and colocalized target genes) has shown the role of polygenes in drought tolerance. Insertion mutagenesis in the colocalized target gene in the qDTY12.1 region boosts the

Recent efforts in developing high-yield, drought-tolerant rice varieties Chapter

1

2

0

3

10M

qDTY2.1

15M

(Venuprasad et al., 2009)

20M

qDTY2.3

25M

qDTY6.1

(Swamy et al., 2013)

(Vikram et al., 2011)

119

6 (Venuprasad et al., 2012)

qDTY6.2

(Sandhu et al., 2014)

qDTY1.3 (Sandhu et al., 2014)

30M

5 qDTY4.1

qDTY3.2

qDTY2.2 (Swamy et al., 2013)

5M

4

8

(Dixit et al., 2014)

qDTY3.1 qDTY1.2 (Sandhu et al., 2014)

35M

(Venuprasad et al., 2009)

qDTY1.1 40M

(Vikram et al., 2011)

45M

0

7

8

9

10

11

5M

qDTY18.1

10M

(Vikram et al., 2011)

15M 20M

qDTY9.1

(Swamy et al., 2013)

qDTY18.2 (Swamy et al., 2013)

12

qDTY11.1

(Dixit et al., 2014)

qDTY12.1

(Bernier et al., 2007)

25M 30M

FIG. 1 Major effect QTLs identified at IRRI for grain yield under drought in rice.

development of lateral roots only under drought (not under nonstress conditions) in contrast to the wild-type (Dixit et al., 2015). Besides the contribution of a single QTL, the genetic linkage, the multiple effect of a gene (pleiotropy), and the epistasis interactions also play important roles in MAB programs (Lebreton et al., 1995; Li et al., 2003). Vikram et al. (2015) elucidated the linkage of qDTY1.1 with “sd1” (the Green Revolution gene) by the fine-mapping of qDTY1.1, confirming the loss of drought-tolerant alleles during the development of semidwarf rice varieties for the irrigated ecosystem in the era of the Green Revolution. The selection of the sd1 recessive allele for dwarf height led to the loss of the qDTY1.1 region tightly linked to the sd1 dominant allele governing tall plant height. The linkage between the qDTY1.1 and sd1 loci was broken and new drought-tolerant dwarf lines were developed, signifying the linkages of the sd1 gene with the qDTY1.1 region, in addition to nullifying the dispute of the pleotrophic effect of the sd1 gene. Under reproductive stage drought stress, the identified grain yield QTLs (qDTY1.1, qDTY2.3, qDTY3.1, qDTY3.2, and qDTY12.1) had shown collocation with genetic regions associated with DTF (days to flowering) or PHT (plant height) (Bernier et al., 2007; Venuprasad et al., 2009, 2012; Vikram et al., 2011). After the Green Revolution era, this kind of undesirable linkage proved to be the basis for the loss of the drought-tolerant allele as medium maturity, dwarf plant height, and higher yield potential were the main preferences of breeders. These linkages between desirable drought-tolerance traits and undesirable traits were also successfully broken and medium-duration, high-yielding, drought-tolerant lines in the Vandana, Swarna, and IR64 background were developed (Vikram et al., 2016).

120 Advancement in crop improvement techniques

TABLE 3 QTLs associated with drought tolerance related traits in cereal crops. Crop

QTLs/gene

Trait

Reference

Rice

qDTY1.1, qDTY2.1, qDTY2.2, qDTY2.3, qDTY3.1, qDTY3.2, qDTY4.1, qDTY6.1, qDTY6.2, qDTY9.1, qDTY10.1, qDTY12.1

Grain yield under reproductive stage drought stress

Bernier et al. (2007), Vikram et al. (2011), Venuprasad et al. (2012), Ghimire et al. (2012), Mishra et al. (2013), Yadaw et al. (2013), Swamy et al. (2013), Sandhu et al. (2014), Dixit et al. (2014b)

Rice

qRT, qRL

Root traits

Qu et al. (2008), Li et al. (2015)

Wheat

q7A-a, q4A-a, q4A-b

Grain yield and physiological traits

McIntyre et al. (2010), Suzuky et al. (2010)

Wheat

QTgw-7D-b

1000 Grain weight

Lopes et al. (2013)

Wheat

qGYWD.3B.1, qGYWD.3B.2

Grain yield

Shukla et al. (2015)

Wheat

qYld.idw-2B, qYld.idw-3B

Grain yield

Maccaferri et al. (2008)

Wheat

QWsc-c.aww-3A, Qchl.ksu-3B

Water soluble carbohydrate, Chlorophyll content

Bennett et al. (2012), Kumar et al. (2012)

Maize

sg1.1.1,sg1.6.1

Stay green

Zheng et al. (2009)

Maize

root-yield-1.06

Root traits and yield

Landi et al. (2010)

Maize

qLTD, qRSFW, qRSDW

Physiological traits associated with seedling water stress

Liu et al. (2011)

Maize

68 meta QTL (mQTL)

Grain yield and Anthesis-silking interval

Semagn et al. (2013)

Barley

q1H-3, q 2H-1, q 4H-3

Grain yield

Baum et al. (2003), Talame et al. (2004), Tuberosa and Salvi (2006)

Barley

QYld.CF-6H, QYld.CW-2H.1, QYld.FW6H.2

Grain yield

Obsa et al. (2017)

Sorghum

qStg1, qStg2, qStg3

Grain Yield

Harris et al. (2007)

Sorghum

Stg1-4

Water extraction, Green leaf area retention and Grain yield

Vadez et al. (2011)

7.5 Deployment of genetic loci: QTL pyramiding To improve the efficacy of MAB, combine biotic/abiotic stress tolerance, and study the positive/negative interactions among the loci, QTL pyramiding (Nagai et al., 2012) is an appropriate approach. The identification of large major effect abiotic and biotic stress associated genetic loci and their deployment into modern improved popular megavarieties through a marker-assisted introgression/QTL pyramiding program are the main aims of MAB (Kumar et al., 2014; Singh et al., 2016). Marker-assisted pyramiding can be a creative and practical approach to increase crop productivity under reproductive stage drought stress. The drought MAB programs at IRRI have shown a potential grain yield advantage of 0.8– 1.2 t ha 1 under severe reproductive stage drought with no yield reduction under a controlled environment, early maturing (105–110 days), better regulation of shoot growth (Wade et al., 2015; Vikram et al., 2015) activities, and better root traits (root plasticity traits, greater root length density) with better water nutrient use efficiency. The QTL introgression program involving high-yielding popular varieties, IR64 and Swarna (Venuprasad et al., 2009; Swamy et al., 2013; Sandhu et al., 2019), with a grain yield improvement of 0.8–1.0 t ha 1 was reported. The marker-assisted QTL pyramiding program in the background of megapopular rice varieties from Malaysia (MRQ74, MR219, qDTY2.2, qDTY3.1, qDTY12.1; Shamsudin et al., 2016), Nepal (Sabitri, qDTY3.2, qDTY12.1; Yadaw et al., 2013), Lao PDR (TDK1, qDTY3.1, qDTY6.1, qDTY6.2; Dixit et al.,

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2017), India (Anjali, qDTY3.1, qDTY12.1; Vandana, qDTY12.1; Sambha Mahsuri, qDTY2.2, qDTY4.1; Sandhu et al., 2018), and Korea (Gayabyeo, Jinmibyeo, Sangnambatbyeo and Hanarumbyeo, qDTY1.1, qDTY2.2) have also demonstrated grain yield improvement under reproductive stage drought. The grain yield advantage of the identified drought breeding lines/varieties over the presently grown popular cultivar shall encourages farmers to cultivate and adopt new drought-tolerant rice varieties. The large-scale dissemination of improved drought-tolerant varieties is needed to achieve sustainable productivity in the rainfed ecosystem. The challenge for modern plant breeding is not only to integrate multiple traits to combat abiotic/biotic stresses, but also to accelerate the genetic gain of the rice breeding programs at the same time. The introgression and pyramiding of desirable traits such as improved yield, resistance to pests/diseases, and adaptation to environments/growing conditions are needed as multiple stresses are coming with changing climatic conditions.

7.6 Interaction among QTLs, and with background and environment The proper selections of the donor and recipient (Xu and Crouch, 2008; Bovill et al., 2010) are a must in MAB programs as the background, environment (Ghimire et al., 2012), and interaction of QTL x QTL, QTL x background, and QTL x environment limit the use of genetic loci in the molecular breeding program (Courtois et al., 2003; Lafitte et al., 2004; Price et al., 2002; Bernier et al., 2008). The positive and negative interactions among the loci and with the background and environment could provide the explanation for the increase/decrease in the effect of genetic loci on the trait of interest. Harnessing these kinds of existing interactions among loci, with environments and genetic backgrounds, with the change in the degree/intensity of drought stress is a must for the success of MAB (Bernier et al., 2007; Vikram et al., 2011). Identification and introgression of these complementary interacted loci may lead to the wide adaptability of QTLs across different environments and backgrounds. The positive interactions of qDTY2.3 and qDTY3.2 loci with qDTY12.1 (Dixit et al., 2012b) and qDTY2.2 and qDTY3.1 with qDTY12.1 (Shamsudin et al., 2016) was observed as characterized by the grain yield enhancement of lines having qDTY12.1 in combination with qDTY2.3, qDTY3.2, qDTY2.2, and qDTY3.1. The QTLs qDTY4.1 and qDTY9.1 showed positive epistatic interaction with qDTY7.1 in the Samba Mahsuri pyramided line, enhancing the grain yield under drought (Sandhu et al., 2018). In addition to these known QTL x QTL interactions, many hidden unknown positive and negative genomic interactions with the background loci exist, which should be identified before the effective deployment of drought QTLs in MAS breeding programs. A total of 16, five, and six digenic interactions were detected in low-yielding NILs in the background of IR64, TDK1-Sub1, and Savitri under moderate and severe drought stress conditions whereas these interactions were not observed in high-yielding NILs and under nonstress conditions in all three backgrounds (Yadav et al., 2019).

7.7 Transgenic approaches Agriculture practices using GM crops (genetically modified) emerged as a modern effective technique to combat the drought stress of major food crops such as rice, wheat, pulses, soybeans, and maize. The transfer of novel combinations of genes and the enhancement of novel biotechnological techniques make it possible to reveal the unexplored multitudinous mechanisms behind tolerance. The expression of transcription factors and stress responsive genes has emerged as powerful tool for the manipulation of metabolic and biochemical changes under drought stress. Transgenic approaches to improve biotic and abiotic stress tolerance involve the incorporation of targeted cloned genes by restrictive transfer of unwanted genes from the donor organism. Rapid progress in rDNA (recombinant-DNA) technology as well as efficient and precise genetic engineering protocols have resulted in successful gene transfer encoding compatible organic solutes, biosynthesis of glycine betaine (GB) in maize and tobacco (Ashraf and Foolad, 2007; Quan et al., 2004); trehalose-6-phosphate synthase or phosphatase (TPSP) in rice (Wu and Garg, 2003) and tobacco (Karim et al., 2007); choline dehydrogenase (CHDH) in maize (Quan et al., 2004); and pyrroline-5-carboxylate synthetase (P5CS) in wheat, tobacco, soybeans, and petunias (Gubis et al., 2007; Yamada et al., 2005). Gene silencing, overexpression, underexpression, undesirable insertion/deletion, genetic alterations, tedious transformation processes, public acceptability, ethical issues, environmental susceptibility, growth and development stages, the guarantee time in biosafety regulations and release, and stable performance across laboratory, glasshouse, or field are important constraints to the success of transgenic crop development.

7.8 High-throughput novel genotypic strategies and techniques The exploitation of the full potential of novel genomics-assisted breeding using novel tools and techniques is on the way and will require advanced knowledge and understanding of high-throughput phenotyping as well as molecular, physiological, and developmental processes to improve drought tolerance (Swamy et al., 2013). Genomic selection, genomic

122 Advancement in crop improvement techniques

estimated breeding value by shortening the breeding cycle, and easy selection allow breeding programs to run larger numbers of crosses at the same time by planting only a few good progenies within a limited budget. The adequate supplementation of old and modern breeding genomics techniques and innovative technologies could contribute toward increasing crop productivity under drought stress. With the rapid progress in structural-functional genomics and proteomics as well as the development of genome-wide analytical tools and genome-wide association studies (GWAS) (Huang et al., 2010; Begum et al., 2015), candidate-gene sequencing will certainly be valuable to refine the existing approaches to accomplish significant progress in future crop improvement programs. The existing information on genes, their function, and expression, their involvement in different biochemical and molecular pathways in addition to the available information on their metabolite profiles will be a useful source in developing climate resilient rice varieties. Orthologous genes from the related cereal crops provide the opportunities to extrapolate the genetic information and functional links to complex genome crops such as rice and wheat genome. The availability of diverse rice germplasm such as introgression lines (ILs), mapping populations (MPs), wild species, mutants, near-isogenic lines (NILs), recombinant inbred lines (RILs), double haploids, and wild species will be a boon for the entire scientific community to develop new high yielding, nutrient efficient, and biotic/abiotic stress tolerant rice varieties. The immense pool of available genomic, transcriptomic, proteomic, and metabolomic information in rice can serve as the basis of structural and functional genomics studies involving designing novel rice varieties for a particular ecosystem. High-throughput approaches such as SNP chips, DNA sequencing, microarrays, SAGE (serial analysis of gene expression), site-directed mutagenesis (transposon tagging, T-DNA insertion, and homologous recombination), RNAi (RNA-mediated interference), and yeast two-hybrid screening will help in gene expression and mechanistic pathway studies of normal, altered, and knockout genes. Bioinformatic tools will be helpful to interlink the gathered multilocation phenotypic data with the candidate gene sequence and gene expression data under different conditions, which will eventually provide information on the candidate gene, gene function, and their phenotypic and genotypic expression, thereby helping breeders in the development of elite cultivars (Delseny et al., 2001). Crop models involving trait combinations, their interactions, genomics, physiology, and system and functional biology will enable us to fill the gap between the complex phenotype, genotype, and their differential behaviors (Yin et al., 2004). This will certainly be helpful to fine-tune the breeding as well as the molecular, physiological, biochemical, transgenic, and novel genomic approaches to achieve significant progress in crop improvement in the future (Fig. 2).

Rice germplasm characteriza on for drought tolerance (landraces, wild, cul vated, core collec on)

High throughput phenotyping (precise, reproducible, and cost effec ve)

Genomics

QTLs

Func onal genomics

Genome-wide associa on studies

Linked markers /genes/SNPs/func onal markers

Traits (grain yield, root architecture, biomass, and other morphological traits

Trait selec on, heritability, mapping popula on

Crop modelling, crop ideotype Near isogenic lines (NILs)

MAS introgression lines, MARS

QTL pyramided lines Intra/inter allelic interac ons, epista c interac ons

Drought tolerant variety

Strategic breeding

FIG. 2 Integrated strategy utilizing genomics, physiology, and breeding approaches for developing drought-tolerant varieties.

Physiology

High throughput genotyping/sequencing

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Advancements in genome editing technologies such as zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and CRISPR (clustered regularly interspaced short palindromic repeats)/Cas (associated protein) have made it possible for molecular biologists to more precisely target any trait or gene of interest. The achievements of the Industrial Revolution, CRISPR/Cas has attracted a great deal of rice researcher’s attention due to its power, effectiveness, and ease of use. So far, it has been adopted in nearly 20 crop species (Ricroch et al., 2017) for various traits including biotic and abiotic stress management and yield improvement. The CRISPR/Cas9 technique has been proved to capably edit drought-tolerance genes such as OsDERF1, OsPMS3, OsEPSPS, OsMSH1, and OsMYB5 in rice; SlMAPK3 in tomatoes (Wang et al., 2017); AGROS8 in maize (Shi et al., 2017); and MIR169a in Arabidopsis thaliana.

8 Computational analysis Computational methods and bioinformatic studies such as gene ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis have been used to identify the putative candidate genes to decode the biological processes and pathways involved in coping with drought stress. The computational studies of the sequenced rice genome revealed 75 MAPKKK (mitogen-activated protein kinase) families (Rao et al., 2010). In silico studies led to the identification of various miRNAs and differential accumulation trends of miRNAs under drought stress in different crop species (Wan et al., 2011; Pagliarani et al., 2017; Muthusamy et al., 2014; Ordo´n˜ez-Baquera et al., 2017; Sircar and Parekh, 2018).

9 Drought policies Progress on drought preparedness and drought policy development has been slow. With the increasing incidences of droughts, the combined efforts of science and policies on drought management are needed. The major constraints include the lack of a regional and national drought policy framework; limited coordination; inadequate social impact indicators; infrastructure, institutional, and legal issues; and government and nongovernment interventions and priorities (Pulwarty and Verdin, 2013). The involvement of government in terms of providing emergency assistance to drought victims is far away from the viewpoint of vulnerability reduction. The severity, intensity, and period of drought stress as well as the short periods (weeks/months) and long periods (seasons, years, or even decades) are also difficult to characterize because they are being evaluated on the basis of multiple severity indices and indicators (Luetkemeier et al., 2017). The presently existing drought monitoring and forecast mechanisms, which require high-quality forecast data and basic local understanding (Wang et al., 2016) to see the impact of dry conditions on local food and water supplies, are really unreliable and not sufficient to prevent natural calamities in countries at the highest risk. The understanding of the scientific community on the constraints of existing policies and the understanding of policy makers on the scientific and technical drought issues (Donald et al., 2014) will provide a useful framework in dealing with the problems associated with drought management. A sound communication between these two groups may be helpful in distinguishing the probability, possibility, and achievability of a broad range of science and policy issues. A coordinated drought policy for each country, including early warning and information systems, comprehensive monitoring, risk management measures, impact assessment, emergency response programs, and early drought plans, strategies, and action plans, may provide the key to cope with drought (Wilhite et al., 2005). Information on the historic impact and response of drought, current trends, and the involvement of a government drought task force including representatives of state and central government agencies, extensions, policy specialists, climatologists, planners, and sector-specific working groups of risk management and the private sector would be helpful in conducting the risk analysis and reshaping the drought mitigation program (Wilhite et al., 2005). The creation of awareness, the development of proper guidelines for drought-prone areas, capacity development, direct support from government and developed countries, partnerships with leading research institutes, and specialized organization should be at the heart of any national and international strategic development program. The policies provoking cooperation and coordination at each and every level of administration may increase the capacity to cope with the problem of water scarcity resulting from drought. This will lead to more drought-resilient societies, ensuring food security and environmental sustainability. Providing a safety net to the people or sectors at the most risk of drought vulnerability is a high priority issue and the challenge is to do it in a way that supports the principles of a drought risk reduction strategy.

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10

Conclusion and future perspectives

Drought stress and water deficiency are predicted to have significant effects on crop production. Many QTLs, genes, and pathways have already been identified and their successful introgression in different backgrounds has been reported to improve yield stability and drought tolerance. Conventional breeding, molecular genetics, genomics, bioinformatics, and databases linking the genomic, transcriptomic, proteomic, and metabolomic information are now providing the full scope of developing drought-tolerant, high-yielding rice varieties. The integration of all these innovations may provide strong solutions to meet the future needs of farmers for drought-prone areas.

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Venuprasad, R., Lafitte, H.R., Atlin, G.N., 2007. Response to direct selection for grain yield under drought stress in rice. Crop Sci. 47, 285–293. Venuprasad, R., Sta-Cruz, M.T., Amante, M., Magbanua, R., Kumar, A., Atlin, G.N., 2008. Response to two cycles of divergent selection for grain yield under drought stress in four rice breeding populations. Field Crops Res. 107, 232–244. Venuprasad, R., Dalid, C.O., Del Valle, M., Zhao, D., Espiritu, M., Sta Cruz, M.T., Amante, M., Kumar, A., Atlin, G.N., 2009. Identification and characterization of large-effect quantitative trait loci for grain yield under lowland drought stress in rice using bulk-segregant analysis. Theor. Appl. Genet. 120, 177–190. Venuprasad, R., Bool, M.E., Quiatchon, L., Sta Cruz, M.T., Amante, M., Atlin, G.N., 2012. A large effect QTL for rice grain yield under upland drought stress on chromosome 1. Mol. Breed. 30, 535–547. Vikram, P., Swamy, B., Dixit, S., Ahmed, H., Cruz, M.T.S., Singh, A., Kumar, A., 2011. qDTY1.1, a major QTL for rice grain yield under reproductivestage drought stress with a consistent effect in multiple elite genetic backgrounds. BMC Genet. 12, 89.

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Vikram, P., Swamy, M., Dixit, S., Singh, R., Singh, B.P., Miro, B., Kohli, A., Henry, A., Singh, N.K., Kumar, A., 2015. Drought susceptibility of modern rice varieties: an effect of linkage of drought tolerance with undesirable traits. Sci. Rep. 5, 14799. Vikram, P., Swamy, B.P.M., Dixit, S., Trinidad, J., Sta Cruz, M.T., Maturan, P.C., Amante, M., Kumar, A., 2016. Linkages and interactions analysis of major effect drought grain yield QTLs in rice. PLoS ONE 11, e0151532. Wade, L., Bartolome, V., Mauleon, R., 2015. Environmental response and genomic regions correlated with rice root growth and yield under drought in the OryzaSNP panel across multiple study systems. PLoS One 10, e0124127. Wan, P., Wu, J., Zhou, Y., Xiao, J., Feng, J., Zhao, W., Xiang, S., Jiang, G., Chen, J.Y., 2011. Computational analysis of drought stress-associated miRNAs and miRNA co-regulation network in Physcomitrella patens. Genom. Proteom. Bioinform. 9 (1–2), 37–44. Wang, W., Maurits, W.E., Svoboda, M.D., Hafeez, M., 2016. Propagation of drought: from meteorological drought to agricultural and hydrological drought. Adv. Meteor. 2016. https://doi.org/10.1155/2016/6547209. Wang, L., Chen, L., Li, R., Zhao, R., Yang, M., Sheng, J., Shen, L., 2017. Reduced drought tolerance by CRISPR/Cas9-mediated SlMAPK3 mutagenesis in tomato plants. J. Agric. Food Chem. 65 (39), 8674–8682. Wilhite, D.A., 2000. Chapter 1: Drought as a natural hazard: concepts and definitions. In: Wilhite, D.A. (Ed.), Drought: A Global Assessment. In: Vol. 1. Routledge Publishers, London, UK, pp. 3–18. Wilhite, D.A., Hayes, M.J., Knutson, C.L., 2005. Drought preparedness planning: building institutional capacity. In: Wilhite, D.A. (Ed.), Drought and Water Crises: Science, Technology, and Management Issues. CRC Press, Boca Raton, FL. Wu, R., Garg, A., 2003. Engineering Rice Plants with Trehalose-Producing Genes Improves Tolerance to Drought Salt and Low Temperature ISB News Report., pp. 3–7. Xu, Y., Crouch, J.H., 2008. Marker-assisted selection in plant breeding: from publications to practice. Crop Sci. 48, 391–407. Xu, Q., Yuan, X.P., Yu, H.Y., Wang, Y.P., Tang, S.X., Wei, X.H., 2011. Mapping QTLs for drought tolerance at seedling stage in rice using doubled haploid population. Rice Sci. 18, 23–28. Yadav, S., Sandhu, N., Majumder, R.R., Dixit, S., Kumar, S., Singh, S.P., Mandal, N.P., Das, S.P., Yadaw, R.B., Singh, V.K., Sinha, P., 2019. Epistatic interactions of major effect drought QTLs with genetic background loci determine grain yield of rice under drought stress. Sci. Rep. 9 (1), 2616. Yadaw, R.B., Dixit, S., Raman, A., Mishra, K.K., Vikram, P., Swamy, B.P.M., Sta Cruz, M.T., Maturan, P.T., Pandey, M., Kumar, A., 2013. A QTL for high grain yield under lowland drought in the background of popular rice variety Sabitri from Nepal. Field Crops Res. 144, 281–287. Yamada, M., Morishita, H., Urano, K., Shiozaki, N., Yamaguchi-Shinozaki, K., Shinozaki, K., 2005. Effects of free proline accumulation in petunias under drought stress. J. Exp. Bot. 56, 1975–1981. Yin, X., Struik, P.C., Kropff, M.J., 2004. Role of crop physiology in predicting gene-to-phenotype relationships. Trends Plant Sci. 9, 426–432. Zheng, J., Wu, A.Z., Zheng, C.C., Wang, Y.F., Cai, R., Shen, X.F., Xu, R.R., Liu, P., Kong, L.J., Dong, S.T., 2009. QTL mapping of maize (Zea mays) staygreen traits and their relationship to yield. Plant Breed. 128, 54–62.

Further reading Swamy, B.M., Kumar, A., 2013. Genomics-based precision breeding approaches to improve drought tolerance in rice. Biotechnol. Adv. 31 (8), 1308–1318. Zhang, H., Zhang, J., Wei, P., Zhang, B., Gou, F., Feng, Z., 2014. The CRISPR/Cas9 system produces specific and homozygous targeted gene editing in rice in one generation. Plant Biotechnol. J. 12, 797–807. Zhao, Y., Zhang, C., Liu, W., Gao, W., Liu, C., Song, G., Li, W.X., Mao, L., Chen, B., Xu, Y., Li, X., 2016. An alternative strategy for targeted gene replacement in plants using a dual-sgRNA/Cas9 design. Sci. Rep. 6, 23890.

Chapter 9

Advances in genomics and molecular breeding for legume improvement Abhishek Bohraa, Reyazul Rouf Mirb, Rintu Jhaa, Alok Kumar Mauryaa and Rajeev K. Varshneyc a

Crop Improvement Division, ICAR-Indian Institute of Pulses Research (IIPR), Kanpur, India, b Division of Genetics and Plant Breeding, Sher-e-Kashmir

University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Jammu and Kashmir, India, c International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana, India

1 Introduction Grain legumes such as chickpeas, pigeonpeas, and groundnuts are important crops with respect to human diet and animal feed worldwide. Owing to their higher protein and nutrient content, these crops are gaining increasing attention in view of the growing proportion of malnourished people, particularly in the developing world (Bohra et al., 2015a, b). The inherent abilities of grain legumes such as biological nitrogen fixation, soil fertility amelioration, and mitigation of greenhouse gas (GHG) emissions establish their suitability for sustainable and environmentally friendly production systems (Stagnari et al., 2017; Varshney et al., 2018). Properties such as phosphorus mobilization from unavailable forms and enhanced carbon sequestration in soil render them excellent crops for intercropping or rotation systems. Also, the role of these crops in low-input farming systems and conservation agriculture is well documented (Stagnari et al., 2017). The genetic improvement of these crops with conventional breeding methods has met with modest success. The increasing challenge to feed the burgeoning worldwide human population puts tremendous pressure on the current food production systems. Breeding programs of legume crops need to be more efficient to sustain the grain yields of these crops amid frequent occurrences of biotic and abiotic stress. Modern genomic tools and technologies could make great contributions to this end. The comprehensive genomic resources made available in these crops include genome assemblies, genome-wide molecular markers, and a variety of genes/QTLs controlling agriculturally important traits (Bohra et al., 2014, 2019, 2020; Varshney et al., 2013a, 2018, 2019a). The evolution of sequencing technologies has driven paradigm shifts in gene discovery and breeding methods. Here, we review the latest genomic advances in the three grain legume crops. We then highlight recent examples of genomics-assisted breeding in these crops, which is followed by a brief discussion on the role of modern breeding techniques such as genomic selection (GS), hybrid breeding, and rapid generation turnover for accelerating breeding and research.

2 Evolution of molecular marker technologies and genotyping assays DNA-based markers, also known as molecular markers, refer to assays used for the detection of specific genome sequence differences at a particular locus between two or more than two individuals of an organism (Langridge and Chalmers, 2005). Molecular markers have revolutionized agriculture by providing highly sophisticated crop improvement tools and techniques. The development and use of molecular marker technology has seen continuous evolution for the last three decades, from low-throughput restriction fragment length polymorphisms (RFLPs) in the 1980s to high-throughput array-based markers in the 2000s, and ultrahigh-throughput next-generation sequencing-based marker systems in the 2010s (Mir and Varshney, 2012; Mir et al., 2013; Varshney, 2016). Therefore, low-throughput marker systems such as RFLP, random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), simple sequence repeat (SSR), etc., are now considered past molecular markers. High/ultrahigh-throughput marker systems based on low-cost and highthroughput sequencing technologies, commonly called next-generation sequencing (NGS) technologies, such as RAD-tag sequencing and genotyping-by-sequencing (GBS) are considered current marker systems. Important grain legume crops for semiarid tropics (SATs) such as chickpeas, pigeonpeas, and groundnuts were considered orphan crops in the last decade due to meager sufficient genomics resources or their complete unavailability. Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00009-7 © 2020 Elsevier Inc. All rights reserved.

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However, due to tremendous efforts made by scientists at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) in collaboration with national/international partners in the last decade (2005–15), we have witnessed the development of large-scale genomic resources in chickpeas, pigeonpeas, and groundnuts that have changed these crops from orphan to genomic-rich crops (Varshney, 2016; Bohra et al., 2019). Now in chickpeas, pigeonpeas, and groundnuts, thousands of all important types of molecular markers, including SSR, diversity array technology (DArT), single nucleotide polymorphism (SNP), different SNP platforms, microarray-based markers, GBS, InDel markers, etc., are available. For instance, using different strategies/approaches, >2000 SSRs in chickpeas, >3000 in pigeonpeas, and >2500 in groundnuts have become available over the years. DArT markers with >15,360 features each for chickpeas, pigeonpeas, and groundnuts have been developed in collaboration with DArT Pty. Ltd., Australia. Similarly, tens of thousands of SNP markers have been developed using a variety of approaches. Several genotypic platforms based on SNP markers have also been developed for these three legume crops, including Kompetitive Allele Specific PCR (KASP) assays, GoldenGate assays, Vera-code assays, and 60 K SNP chips using the Affymetrix SNP platform (see Varshney, 2016 for more details). More recently, an Axiom SNP array with 56 K SNPs uniformly distributed across the genome was also developed and used in a study of genetic diversity and trait mapping for high-selfing flower and seed quality traits in the pigeonpea (Saxena et al., 2018a, b; Yadav et al., 2019). Similarly, an Axiom SNP array with 50,590 SNPs was developed for use in highresolution genetic mapping and breeding applications in the chickpea (Roorkiwal et al., 2018). Genome-wide InDel markers were developed as an extended marker resource for chickpea breeding programs ( Jain et al., 2019). In summary, a variety of molecular markers are now available in a large scale for all the SAT legume crops, including chickpeas, pigeonpeas, and groundnuts. These marker resources have been used extensively for the construction of highdensity maps (Varshney et al., 2009; Ravi et al., 2011; Sujay et al., 2012a, b; Thudi et al., 2011; Yang et al., 2011; Bohra et al., 2011; Hiremath et al., 2012; Kujur et al., 2015; Jaganathan et al., 2015; for more details see Varshney, 2016 and references therein) to facilitate trait mapping in these important grain legume crops.

3

Genetic resources and molecular mapping of agriculturally important traits

A variety of plant genetic resources have been developed and are available to improve SAT legume crops. These genetic resources include germplasm collections, landraces, core collections, donor genotypes, biparental mapping populations, multiparental MAGIC and NAM populations, wild relatives, and wild  cultivated introgression populations. These genetic resources are very important for gene mapping/tagging/high-resolution genetic mapping/gene cloning. In addition, genetic resources would also be an excellent breeding material to develop next-generation superior varieties based on trait performance. They could also be utilized for different crossing programs to enhance the genetic base of cultivated gene pools in the chickpea, pigeonpea, and groundnut. Wild relatives of these crops have been found to possess enormous potential to render desirable traits such as tolerance to abiotic stresses, resistance to pests and diseases, nutritional traits, photoinsensitivity, cleistogamy, and cytoplasmic male sterility (CMS) (Pazhamala et al., 2015; Varshney, 2016; Pandey et al., 2017). One of the most important aims in the development of genetic and genomic resources in SAT legume crops is to facilitate trait mapping for molecular breeding programs. For instance, in the chickpea, a genetic dissection was done for complex quantitative traits such as drought/droughtrelated traits and yield under drought (Varshney et al., 2014a, b). The efforts also led to the identification of a QTL hotspot region on likage group-4 harboring 12 major QTLs for drought tolerance-related traits, explaining up to a 58.20% phenotypic variation. The region was later fine-mapped using a GBS approach ( Jaganathan et al., 2015). Further fine mapping of this region was achieved through two complementary approaches, including a sliding window-based bin mapping approach and a genome-wide association study-based gene enrichment analysis of the skim sequenced data of the RIL population (Kale et al., 2015). Whole genome scanning and candidate gene sequencing approaches were also followed in the chickpea to identify QTLs/genes for drought- and heat-responsive traits in the chickpea (Thudi et al., 2014). Gene mapping was also undertaken for the two most important diseases in the chickpea, Fusarium wilt (FW) and Ascochyta blight (AB), using biparental mapping populations (Sabbavarapu et al., 2013; Varshney, 2016 and references therein). Similarly, QTLs have also been identified for botrytis gray mold (Anuradha et al., 2011). In the pigeonpea, FW and sterility mosaic disease (SMD) are considered the two major biotic stresses limiting production and productivity. Therefore, efforts have been made to map genes/QTLs for these two important diseases using different approaches and different genetic resources (see Pazhamala et al., 2015; Varshney, 2016). Transcriptomics approaches through the differential expression of genes have also identified the gene for FW and SMD in the pigeonpea (Raju et al., 2010; Dubey et al., 2011). Genes for determinacy through candidate gene sequencing and whole genome scanning have also been identified (Mir et al., 2013, 2014; Saxena et al., 2017). Stress-responsive genes conferring

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tolerance to drought, salinity, cold, and extreme temperatures have also been identified (Deeplanaik et al., 2013; Priyanka et al., 2010). Efforts have also been made toward mapping QTLs for some agronomic traits such as fertility restoration (Bohra et al., 2012), flowering, earliness, and plant height (Kumawat et al., 2012). Advance back-cross QTL mapping is also being used to map genes for agronomically important traits introgressed from wild relatives such as Cajanus cajanifolius and Cajanus acutifolius (R.K. Varshney et al., under preparation). NGS-based approaches such as MutMap and QTL-seq for the identification of candidate genes/genomics region(s) underlying the trait of interest are also being used now in the pigeonpea. The QTLs/genes/associated markers that are being identified will prove useful in pigeonpea molecular breeding programs (Pazhamala et al., 2015). In the groundnut, molecular mapping of genes/QTLs has been successfully completed for a variety of traits. Using different segregating biparental mapping populations/diverse germplasms, QTLs/genes have been identified for different biotic and abiotic stresses and quality traits (see Varshney et al., 2013a). Among the abiotic stresses, several QTLs (both main-effect and epistatic) were identified for drought tolerance and related traits (Varshney et al., 2009; Ravi et al., 2011; Gautami et al., 2011). Similarly, among biotic stresses, QTLs have been identified for late leaf spot (LLS), leaf rust, early leaf spot, and the tomato spotted wilt virus using biparental mapping populations (Khedikar et al., 2010; Sujay et al., 2012a, 2012b; Wang et al., 2013). QTLs have also been identified for oil quality traits, oil content (Sarvamangala et al., 2011; Pandey et al., 2014a, b), and a variety of important morphological/yield contributing traits such as seed weight, pod weight, number of branches, plant height, and plant biomass (Liang et al., 2009; Shirasawa et al., 2012). In addition, genome-wide association mapping was also conducted to study marker-trait associations using a groundnut reference set for important agronomic, disease, and quality traits (Pandey et al., 2014a, b). Due to some limitations such as the time-consuming and costly nature of traditional approaches to trait mapping, NGSbased approaches are preferred nowadays for trait mapping. Recent advances in NGS tools and technologies and a steeper drop in the sequencing cost provide an opportunity for trait mapping at the sequence level and the selection of plants at nucleotide levels. Recently, a large number of sequencing-based approaches, including trait mapping through sequencing an entire population and trait mapping through sequencing pooled samples, have been proposed and used for trait mapping (Pandey et al., 2017). Sequenced-based trait mapping approaches have also been initiated for the identification of candidate genes/genomic regions for rust and LLS resistance in the groundnut (see Pandey et al., 2017; Varshney, 2016). An exome sequencing approach has also been utilized to sequence 250 lines of the groundnut to understand the role of candidate genes for targeted traits (Pandey et al., 2017).

4 Whole genome sequencing of the reference genotypes Advances in NGS technologies have facilitated the establishment of a reference genome sequence in legumes (Bohra and Singh, 2015; Bohra et al., 2019). The pigeonpea is the first orphan crop and second food legume crop (after the soybean) for which the whole genome sequence has become available. Varshney et al. (2012) assembled a 605.78 Mb genome of the popular pigeonpea variety Asha (ICPL 87119), and the de nono genome assembly contains a total of 48,680 genes. A set of 111 genes was predicted to be responsible for the drought-tolerance trait of the pigeonpea. Similarly, NGS platforms were used to generate 738 and 520 Mb draft genome assemblies of the chickpea genotypes CDC Frontier (Varshney et al., 2013b) and ICC 4958 ( Jain et al., 2013), which contain a total of 28,269 and 27,571 protein-coding genes, respectively. In the groundnut, Bertioli et al. (2016) reported the genome sequences of Arachis duranensis and Arachis ipaensis with 1211 and 1512 Mb size, respectively. The two genotypes represent the diploid ancestors A. duranensis and A. ipaensis, donors of A and B subgenomes, respectively, in the cultivated groundnut. A. duranensis and A. ipaensis genome assemblies harbored 36,734 and 41,840 genes, respectively, of which 345 and 397 nucleotide-binding site leucine-rich repeat (NB-LRR) genes were predicted to confer resistance against pests and diseases. Another draft genome assembly of 1.05 Gb size was reported for A. duranensis harboring a total of 50,324 genes (Chen et al., 2016). Further analysis of the genome suggested the occurrence of three polyploidization events in the groundnut lineage, and shed new light on the genes and pathways related to important traits such as geocarpy, oil biosynthesis, and allergens. More recently, 2.54 Gb of A. hypogaea var. Shitouqi was assembled by Zhuang et al. (2019) using modern sequencing platforms such as PacBio chromosome conformation capture (Hi-C) sequencing. The genome assembly of the tetraploid groundnut contains a total of 83,709 proteincoding genes. The GC content reported in all these draft genome assemblies is comparable to the pigeonpea (32.8%: Varshney et al., 2012), chickpea (30.7%: Varshney et al., 2013b), and groundnut (31.7%: Chen et al., 2016). Approximately half these genomes are composed of repeat elements (REs), including 49.41% in the chickpea, 51.6% in the pigeonpea, and 59.77% in the groundnut, with the majority of the REs in the genome belonging to long terminal repeat (LTR) retro-transposons.

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TABLE 1 Reference genome assemblies in SAT legume crops. Chickpea

Pigeonpea

Groundnut

Cicer arietinum (2n 5 2 × 5 16)

Cajanus cajan (2n 5 2 × 5 22)

Arachis duranensis (2n 5 2× 5 20)

Arachis duranensis

A. ipaensis (2n 5 2 × 5 20)

A. hypogaea (2n 5 4 × 5 40)

Name of the reference genotype

CDC Frontier

ICPL 87119

V14167

PI475845

K30076

Shitouqi

Genome size

738.09

833.07 Mb

1.25 Gb

–

1.56 Gb

2.7 Gb

Assembly size

532.29 Mb

605.78 Mb

1211 Mb

1.05 Gb

1512 Mb

2.54 Gb

NGS system used for sequencing

Illumina HiSeq 2000

Illumina GA and HiSeq 2000

Illumina HiSeq 2000

Illumina Hiseq2500

Illumina HiSeq 2000

Illumina HiSeq 2000, PacBio RS II and Sequel, and Hi-C

Coverage

207

163.4

154

–

163

100

Number of genes

28,269

48,680

36,734

50,324

41,840

83,709

Percent share of TE elements

49

52

62

60

69

–

GC content

31

32

–

32

–

–

N50 (scaffolds)

39.99 Mb

516.06 kb

–

649 Kb

–

135 Mb

Reference

Varshney et al., 2013b

Varshney et al., 2012

Bertioli et al., 2016

Chen et al., 2016

Bertioli et al., 2016

Zhuang et al., 2019

The whole genome sequence analysis offers valuable information about the important genes and associated pathways, thus revealing breeding targets in these legume crops such as flowering time genes in the chickpea, and geocarpy, oil biosynthesis, and allergens in the groundnut. Key features of these genome assemblies are outlined in Table 1.

5

Resequencing multiple genomes to better understand genetic variation

A deeper understanding of the adaptive genetic variation is essential to breed climate-resilient cultivars in the face of rising temperatures and climatic fluctuations (Varshney et al., 2019b). The narrow genetic base of cultivated pools of the grain legume crops has greatly hampered the progress of breeding genotypes against biotic and abiotic stresses. Efforts made to exploit crop genetic resources in breeding programs of grain legume crops have seen modest success. Wild germplasms represent a vast resource of alleles associated with the key adaptive phenotypes that have been impacted during the course of domestication and subsequent breeding. With the dramatically declining cost of NGS technologies, whole genome resequencing (WGRS) has emerged as a promising approach to offer novel insights into genetic variation, population structure, and domestication history. The latest examples of the whole genome level characterization of the comprehensive germplasm collection include WGRS of 429 diverse chickpea genotypes at an average 10.22  coverage (Varshney et al., 2019b) and 292 pigeonpea accessions at depths ranging between 5 and 12 (Varshney et al., 2017). In the chickpea, high allelic variation was observed in wild genotypes as compared to landraces and the cultivated chickpea based on the analysis of nucleotide diversity per kb, implying a nearly 80% reduction in diversity during domestication. The study has revealed genomic regions that underwent selection during crop breeding and postdomestication diversification, thus delineating 122 genomic regions harboring 204 candidate genes. Earlier, Varshney et al. (2013b),

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based on the WGRS of 29 chickpea varieties, identified genomic regions on the pseudomolecule Ca4 that might have played a key role in the divergence of the desi and kabuli types. Combined analysis of the WGRS data of 29 varieties and RADSeq data of 61 varieties/landraces/wild relatives (Cicer reticulatum and Cicer echinospermum) uncovered a total of 122 genes, including 54 genes on Ca3. The presence of the CONSTANS gene homolog within this 54-gene candidate genomic region suggested its contribution to impart adaptability to the chickpea to a range of agro-climatic zones. An analysis of the resequencing data of 129 chickpea varieties released between 1948 and 2012 led authors to propose an increase in genetic diversity in chickpea varieties as a result of recent chickpea breeding efforts (Thudi et al., 2016). In the following analysis of WGRS data in the pigeonpea, genomic regions with the highest reduction of diversity (ROD) values were found vis-a-vis domestication (1722) and breeding (671) in the pigeonpea. The study underscores the role of SVs as targets of selection with the presence of 69 SVs [68 copy number variations (CNVs) and one presence absence variation (PAV)] in the ROD regions (Varshney et al., 2017). Mapping of the WGRS data with the reference genome sequences has allowed the construction of high-density HapMaps comprising genome-wide genetic markers, including SNPs and InDels as well as large structural variations such as CNV and PAV. A plethora of genetic markers unleashed by WGRS data includes 4,972,803 SNPs, 596,100 InDels, 4931 CNVs, and 60,742 PAVs in the chickpea. The availability of such genome-wide marker data in combination with phenotypic data paves the way for enhanced understanding of the genetic architecture of resilient traits. For example, a GWAS of 20 drought- and heat-tolerance related traits with 3.65 million SNPs in the chickpea suggested a total of 262 MTAs with 203 unique SNPs. Of these MTAs, 173, 51, and five MTAs could be categorized as robust, consistent, and stable, respectively. Similarly, 241 MTAs were identified in the pigeonpea after a GWAS involving WGRS data of 286 accessions and phenotypic data on eight agronomic traits. The majority of these MTAs, particularly for days to 50% flowering, were detected on CcLG09. Importantly, the functional impact of SVs was demonstrated with the presence of 63 SVs in 183 MTAs in breeding lines.

5.1 Genomics-assisted breeding in legume crops: From MAS to GS and sequence-based breeding Concerning the improvement of biotic stress tolerance in legume crops, QTLs associated with AB and FW have been deployed extensively in chickpea breeding programs. For instance, Varshney et al. (2014a) performed MABC for transferring QTLs for FW (foc1) and AB (ABQTL-I and ABQTL-II), respectively, into the background of the cultivar C 214. The resultant lines showed an improved level of resistance with the recurrent parent genome (RPG) of up to 92% and 85% for FW and AB, respectively, among various introgression lines (ILs). Introgression of the QTL controlling resistance to other FW races was also performed into the background of the popular chickpea cultivars Annigeri and JG 74 (for foc 4: Mannur et al., 2018) and Pusa 256 (for foc 2: Pratap et al., 2017). Similar successful stories of developing resistant lines using MABC techniques were reported recently in the groundnut, targeting major biotic stresses of economic importance such as foliar diseases (rust and LLS). Varshney et al. (2014b) demonstrated the immense utility of MABC for transferring QTLs, explaining up to an 83% phenotypic variation for rust resistance into the background of three groundnut cultivars; the authors obtained a set of 11 ILs carrying a target QTL region from the resistant parent. Apart from biotic stress, MABC was successful in enhancing the drought tolerance of the chickpea (Varshney et al., 2013c) and the oil quality of the groundnut ( Janila et al., 2016) (Table 2). The need to improve quantitative trait variation has caused a shift toward new molecular breeding techniques such as GS that do not rely on finding a set of significant markers. GS instead exploits genome-wide genetic marker information to harness quantitative variations controlled by a number of small-effect QTLs scattered throughout the genome. The GS concept was originally proposed by Meuwissen et al. (2001) in animal breeding. In GS, prediction models are developed using genotypic and phenotypic data on individuals of the training population. Genomic estimated breeding values (GEBVs) are then calculated to select candidates of the breeding population. Thus, GS avoids the need for repeated phenotypic evaluation of selection candidates of the breeding populations. In the chickpea, promising results have been reported on GS application. Different models such as ridge regression best linear unbiased predictor (RR-BLUP), kinship GAUSS, Bayes Cp, BayesB, Bayesian least absolute shrinkage and selection operator (Bayesian LASSO), and random forest were used recently in the chickpea (Roorkiwal et al., 2016). The authors have reported high prediction accuracies for traits that are less affected by environments such as 100-seed weight, highlighting a need to factor genotype  environment (G  E) interactions into GS models. The authors found no major difference in the performance of different GS models for estimating prediction accuracies in the chickpea. Later, the authors used a multivariate reaction norm (MRNM) model to tackle GXE interactions using three different genotyping datasets (GBS or DArTseq or both).

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TABLE 2 Successful examples of molecular breeding in SAT legume crops. Crop

Trait

Recurrent parent

Donor

Recurrent parent genome recovery

Chickpea

FW (foc1)

C 214

WR 315

92

Varshney et al., 2014a

FW (foc4)

Annigeri 1

WR 315

90–95

Mannur et al., 2018

JG 74

WR 315

90–97

FW (foc2)

Pusa 256

Vijay

>95

Pratap et al., 2017

Drought

JG 11

ICC 4958

72–99

Varshney et al., 2013c

AB (ABQTL-I and ABQTL-II)

C 214

ILC 3279

85

Varshney et al., 2014a

Rust

ICGV 91114, JL 24, TAG 24

GBPD 4

–

Varshney et al., 2014b

TMV 2

GBPD 4

–

Kolekar et al., 2017

ICGV 05141

SunOleic 95R

–

Bera et al., 2018

ICGV 06110, ICGV 06142, ICGV 06420

SunOleic 95R

–

Janila et al., 2016

Groundnut

High oleic acid content

References

Performance was found to be better with DArTseq and the combined genotyping set (DArTseq and GBS) than the GBS alone (Roorkiwal et al., 2018). Because the genetic relationship between the training population and selection candidates is crucial in GS, Neyhart et al. (2017) highlighted the practical importance of updating the training population and explored various methods to achieve this objective in both the short and long term. Further improvements in the prediction accuracies are likely to be achieved with an increasing scope for integration of the high-density genotyping data along with accurate and precise phenotypic records. Besides improving megavarieties for key traits, emphasis should also be given on the continuous improvement of breeding populations. In that context, Varshney et al. (2019a, b) recently proposed a sequence-based breeding approach that involves identification and hybridization among the germplasm/breeding lines that harbor the maximum number of superior alleles. New genome-scale techniques such as GWAS would allow the identification of superior alleles by harnessing data on sequencing (high coverage if possible) and multilocation phenotyping. Early screening of segregants may be performed with the help of existing SNP panels. Advanced fixed lines should be used to train GS models and superior candidates may then be selected based on GEBVs. The high-performing genotypes thus obtained could either enter into variety identification/release systems or could serve as parents for imitating the next breeding cycle.

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Speed breeding in legume crops for accelerating genetic gains

Reducing the length of crop breeding cycles and the time required to develop a new variety can substantially contribute to improving the rate of genetic gains (Ghosh et al., 2018; Li et al., 2018; Chiurugwi et al., 2019). In that context, speed breeding (SB) protocols have been recently optimized in these crops to enable rapid generation advancement (RGA). For instance, Watson et al. (2018) could obtain 4–6 generations per year in chickpeas grown in controlled conditions with a photoperiod of 22 and 2 h of darkness and a temperature regime of 22°C/17°C. The controlled conditions mentioned above caused the flowering time to be reduced by 35 days in comparison to plants grown in normal conditions. Harvesting immature seeds for advancement could further enhance the number of generations in 1 year without exerting any adverse

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impact on the next generation. Continuous light is also suitable to accelerate plant growth; however, a short period of darkness helps to maintain the circadian clock, apart from relieving stress. Earlier, chickpea researchers obtained 2–3 generations using various RGA technologies (Gaur et al., 2007; Sethi et al., 1981). According to Gaur et al. (2007), one crop was taken under normal field conditions and two crops were grown with extended photoperiods in a greenhouse. A continuous light of 24 h was provided to induce flowering in 25–35 days, thus allowing the crop to mature within 3 months. In an alterative method, advancement was made in different seasons, that is, winter (main crop), spring, and rainy. Crops were sown and harvested in the following manner: September to mid-January in winter and mid-January/February to the end of April in spring. Growing the crop in spring offered an additional opportunity to screen genotypes for high-temperature tolerance, and the authors reported the higher tolerance of kabuli types as compared to desi types. A third crop was taken in the rainy season (June to September) using the facility of a rainout shelter. RGA technology in the groundnut reduced the maturity time of the cultivars from 145 to 89 days (O’Connor et al., 2013). O’Connor et al. (2013) demonstrated the development of F2–F4 generations in less than 12 months, with the F2 generation grown in controlled conditions and the two generations advanced in field environments. Further, the authors compared the three different strategies in terms of F2–F4 progression: (i) conventional pedigree, (ii) two seasons, spring cycle and winter nursery, and (iii) controlled conditions with 24 h light exposure. They reported 17, 23, and 42 months, respectively, for generation advancement from F2 to F4, thus demonstrating a significant advantage of SB over the other two strategies.

7 Genomic technologies to accelerate hybrid breeding The discovery of CMS technology in the pigeonpea has enabled the harnessing of hybrid vigor for yield improvement. CMS technology relies on three lines: the male sterile line (A) line, the cognate maintainer line (B) line, and the restorer line (R) line. Owing to its inability to produce functional pollen, the CMS system accelerates hybridization by circumventing the need for manual emasculation. So far, eight CMS sources have been reported in the pigeonpea, of which two, A2 and A4, are being deployed for hybrid development (Bohra et al., 2016, 2010). The A2 and A4 CMS sources were derived from Cajanus scarabaeoides and C. cajanifolius, respectively (Bohra et al., 2017a). A variety of genomic tools have been developed in recent years to support hybrid pigeonpea breeding. Also, these genomic advances have contributed to improving our understanding of the CMS-Rf system in the pigeonpea (Bohra et al., 2016). Mapping the gene(s)/QTLs that restore fertility in the hybrid has been performed (Bohra et al., 2012; Saxena et al., 2018a, b). Bohra et al. (2012) analyzed pollen fertility data and genotypic data in three mapping F2 populations and reported four major QTLs (QTL-RF-1 to QTL-RF-4), explaining the phenotypic variation (PV) up to 24%. A more recent QTL study of an F2 population (ICPA 2039 X ICPL 87119) revealed the presence of a major QTL (S8_6388803 to S8_6474381) on CcLG08, which controls 21% PV for the pollen fertility trait (Saxena et al., 2018a, b). The identification of the genomic regions associated with the male fertility trait will facilitate the accelerated transfer of the Rf-associated regions to other genetic backgrounds and the rapid screening of large germplasm collections for the presence of Rf loci. The role of mitochondria in CMS induction in crop plants has been established in various studies. In the pigeonpea, 545.7 kb of the mitochondrial genome was assembled for the CMS lines (ICPA 2039). Further comparison of the mitochondrial sequences between the CMS and maintainer (ICPB 2039) led the authors to discover a set of 13 chimeric ORFs that could play an important role in the manifestation of the CMS trait in the pigeonpea (Tuteja et al., 2013). Further, expression profiling followed by structural variation analysis of the mitochondrial genes between ICPA 2039 and ICPB 2039 uncovered the association of a 10-bp deletion in the nad7a gene with the CMS trait in the pigeonpea (Sinha et al., 2015). These new insights will help greatly in understanding the nuclear-cytoplasmic crosstalk leading to male sterility in the pigeonpea. The assessment of the genetic purity of hybrid seeds is crucial to the successful exploitation of hybrid technology for crop improvement. The genetic purity of hybrid seeds was assessed conventionally through the grow out test (GoT), which relies on evaluating a set of morphological descriptors on a representative sample. In recent years, the use of DNA marker technologies has emerged as a promising approach to ensure the genetic purity of the hybrid and parental lines. In the pigeonpea, the utility of SSR-based molecular marker assays has been demonstrated in genetic purity assessment by various researchers (Bohra et al., 2011, 2015a, b, 2017b; Saxena et al., 2010).

8 Conclusion and perspectives Recent advances in genomics of the three legume crops have offered a variety of modern tools and technologies that can dramatically improve the genetic gains in the crop breeding programs. The availability of a reference genome sequence in

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combination with high-density genotyping and sequencing assays provide new ways to harness genetic variations for climate-resilience traits from underutilized germplasm resources. Modern breeding tools such as SB offer a tremendous opportunity to expedite crop breeding progress, particularly when combined with MAS or GS. The utility of SB protocols for improving generation turnover has already been demonstrated in the chickpea, pigeonpea, and groundnut. Embracing modern genomic tools and technologies in breeding programs will contribute to improving the performance of the legume crops in the face of increasing stress and climate fluctuations.

Acknowledgments AB, RJ, and AKM acknowledge support from the Indian Council of Agricultural Research (ICAR), New Delhi, India.

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Mapping of QTLs for resistance to fusarium wilt (race 1) and ascochyta blight in chickpea (Cicer arietinum L.). Euphytica 93, 121–133. Sarvamangala, C., Gowda, C.L.L., Varshney, R.K., 2011. Identification of quantitative trait loci for protein content, oil content and oil quality for groundnut (Arachis hypogaea L.). Field Crop Res. 122, 49–59. Saxena, R.K., Patel, K., Sameer Kumar, C.V., Tyagi, K., Saxena, K.B., Varshney, R.K., 2018a. Molecular mapping and inheritance of restoration of fertility (Rf) in A4 hybrid system in pigeonpea (Cajanus cajan (L.) Millsp.). Theor. Appl. Genet. https://doi.org/10.1007/s00122-018-3101-y. Saxena, R.K., Rathore, A., Bohra, A., Yadav, P., Das, R.R., Khan, A.W., Singh, V.K., Chitikineni, A., Singh, I.P., Sameer Kumar, C.V., Saxena, K.B., Varshney, R.K., 2018b. Development and application of high density axiom Cajanus SNP Array with 56 K SNPs to understand the genome architecture of released cultivars and founder genotypes for redefining future pigeonpea breeding programs. Plant Genome 11, 180005. Saxena, R.K., Saxena, K.B., Varshney, R.K., 2010. Application of SSR markers for molecular characterization of hybrid parents and purity assessment of ICPH 2438 hybrid of pigeonpea [Cajanus cajan (L.) Millspaugh]. Mol. Breed. 26, 371–380. Saxena, R.K., Obala, J., Sinjushin, A., Sameer-Kumar, C.V., Saxena, K.B., Varshney, R.K., 2017. Characterization and mapping of Dt1 locus which cosegregates with CcTFL1 for growth habit in pigeonpea. Theor. Appl. Genet. 130, 1773–1784. Sethi, S.C., Byth, D.E., Gowda, C.L.L., Green, J.M., 1981. Photoperiodic response and accelerated generation turnover in chickpea. Field Crop Res. 4, 215–225. Shirasawa, K., Koilkonda, P., Aoki, K., Hirakawa, H., Tabata, S., Watanabe, M., Hasegawa, M., Kiyoshima, H., Suzuki, S., Kuwata, C., Naito, Y., Kuboyama, T., Nakaya, A., Sasamoto, S., Watanabe, A., Kato, M., Kawashima, K., Kishida, Y., Kohara, M., Kurabayashi, A., Takahashi, C., Tsuruoka, H., Wada, T., Isobe, S., 2012. In silico polymorphism analysis for the development of simple sequence repeat and transposon markers and construction of linkage map in cultivated peanut. BMC Plant Biol. 12, 80. Sinha, P., Saxena, K.B., Saxena, R.K., Singh, V.K., Suryanarayana, V., Sameer Kumar, V., et al., 2015. Association of nad7a gene with cytoplasmic male sterility in pigeonpea. Plant Genome 8, 1–12. Stagnari, F., Maggio, A., Galieni, A., Pisante, M., 2017. Multiple benefits of legumes for agriculture sustainability: an overview. Chem. Biol. Technol. Agric. 4, 2. Sujay, V., Gowda, M.V.C., Pandey, M.K., Bhat, R.S., Khedikar, Y.P., Nadaf, H.L., Gautami, B., Sarvamangala, C., Lingaraju, S., Radhakrishan, T., Knapp, S.J., Varshney, R.K., 2012a. QTL analysis and construction of consensus genetic map for foliar diseases resistance based on two RIL populations in cultivated groundnut (Arachis hypogaea L.). Mol. Breed. 32, 773–788. Sujay, V., Gowda, M.V.C., Pandey, M.K., Bhat, R.S., Khedikar, Y.P., Nadaf, H.L., Gautami, B., Sarvamangala, C., Lingaraju, S., Radhakrishan, T., Knapp, S.J., Varshney, R.K., 2012b. QTL analysis and construction of consensus genetic map for foliar diseases resistance based on two RIL populations in cultivated groundnut (Arachis hypogaea L.). Mol. Breed. 32, 773–788. Thudi, M., Bohra, A., Nayak, S.N., et al., 2011. Novel SSR markers from BAC-end sequences, DArT arrays and a comprehensive genetic map with 1,291 marker loci for chickpea (Cicer arietinum L.). PLoS One 6 (11), e27275. Thudi, M., Chitikineni, A., Liu, X., He, W., Roorkiwal, M., Yang, W., Jian, J., Doddamani, D., Gaur, P.M., Rathore, A., Samineni, S., Saxena, R.K., Xu, D., Singh, N.P., Chaturvedi, S.K., Zhang, G., Wang, J., Datta, S.K., Xu, X., Varshney, R.K., 2016. Recent breeding programs enhanced genetic diversity in both desi and kabuli varieties of chickpea (Cicer arietinum L.). Sci. Rep. 6, 38636. Thudi, M., Upadhyaya, H.D., Rathore, A., Gaur, P.M., Krishnamurthy, L., Roorkiwal, M., Nayak, S.N., Chaturvedi, S.K., Basu, P.S., Gangarao, N.V.P.R., Fikre, A., Kimurto, P., Sharma, P.C., Sheshashayee, M.S., Tobita, S., Kashiwagi, J., Ito, O., Killian, A., Varshney, R.K., 2014. Genetic dissection of drought and heat tolerance in chickpea through genome-wide and candidate gene-based association mapping approaches. PLoS One 9, e96758.

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Tuteja, R., Saxena, R.K., Davila, J., Shah, T., Chen, W., Xiao, Y., et al., 2013. Cytoplasmic male sterility associated chimeric open reading frames identified by mitochondrial genome sequencing of four Cajanus genotypes. DNA Res. 20, 485–495. Varshney, R.K., 2016. Exciting journey of 10 years from genomes to fields and markets: some success stories of genomics-assisted breeding in chickpea, pigeonpea and groundnut. Plant Sci. 242, 98–107. Varshney, R.K., Bertioli, D.J., Moretzsohn, M.C., Vadez, V., Krishnamurthy, L., Aruna, R., Nigam, S.N., Moss, B.J., Seetha, K., Ravi, K., He, G., Knapp, S.J., Hoisington, D.A., 2009. The first SSR-based genetic linkage map for cultivated ground nut (Arachis hypogaea L.). Theor. Appl. Genet. 118, 729–739. Varshney, R.K., Chen, W., Li, Y., Bharti, A.K., Saxena, R.K., Schlueter, J.A., Donoghue, M.T.A., Azam, S., Fan, G., Whaley, A.M., Farmer, A.D., Sheridan, J., Iwata, A., Tuteja, R., Penmetsa, R.V., Wu, W., Upadhyaya, H.D., Yang, S.P., Shah, T., Saxena, K.B., Michael, T., McCombie, W.R., Yang, B., Zhang, G., Yang, H., Wang, J., Spillane, C., Cook, D.R., May, G.D., Xu, X., Jackson, S.A., 2012. Draft genome sequence of pigeonpea (Cajanus cajan), an orphan legume crop of resource-poor farmers. Nat. Biotechnol. 30, 83–89. Varshney, R.K., Gaur, P.M., Chamarthi, S.K., Krishnamurthy, L., Tripathi, S., Kashiwagi, J., Samineni, S., Singh, V.K., Thudi, M., Jaganathan, D., 2013c. Fast-track introgression of ‘QTL-hotspot’ for root traits and other drought tolerance traits in JG 11, an elite and leading variety of chickpea. Plant Genome 6, 1–9. Varshney, R.K., Mohan, S.M., Gaur, P.M., Chamarthi, S.K., Singh, V.K., Samineni, S., Swapna, N., Sharma, M., Singh, S., Kaur, L., Pande, S., 2014a. Marker assisted backcrossing to introgress resistance to fusarium wilt race 1 and ascochyta blight in C 214, an elite cultivar of chickpea. Plant Genome 7, 1–11. Varshney, R.K., Murali Mohan, S., Gaur, P.M., Gangarao, N.V.P.R., Pandey, M.K., Bohra, A., Sawargaonkar, S.L., Kimurto, P.K., Janila, P., Saxena, K.B., Fikre, A., Sharma, M., Pratap, A., Tripathi, S., Datta, S., Chaturvedi, S.K., Mallikarjuna, N., Anuradha, G., Babbar, A., Choudhary, A.K., Mhase, M.B., Bharadwaj, C.H., Mannur, D.M., Harer, P.N., Guo, B., Liang, X., Nadarajan, N., Gowda, C.L.L., 2013a. Achievements and prospects of genomicsassisted breeding in three legume crops of the semi-arid tropics. Biotechnol. Adv. 31, 1120–1134. Varshney, R.K., Pandey, M.K., Bohra, A., Singh, V.K., Thudi, M., Saxena, R.K., 2019a. Towards sequence-based breeding in legumes in the post-genome sequencing era. Theor. Appl. Genet. 132, 797–816. Varshney, R.K., Pandey, M.K., Pasupuleti, J., Nigam, S.N., Sudini, H., Gowda, M.V.C., Sriswathi, M., Radhakrishnan, T., Manohar, S.S., Nagesh, P., 2014b. Marker-assisted introgression of a QTL region to improve rust resistance in three elite and popular varieties of peanut (Arachis hypogaea L.). Theor. Appl. Genet. 127, 1771–1781. Varshney, R.K., Saxena, R.K., Upadhyaya, H.D., Khan, A.W., Yu, Y., Kim, C., Rathore, A., Kim, D., Kim, J., An, S., Kumar, V., Anuradha, G., Yamini, K.N., Zhang, W., Muniswamy, S., Kim, J.S., Penmetsa, R.V., Von Wettberg, E., Datta, S.K., 2017. Whole-genome resequencing of 292 pigeonpea accessions identifies genomic regions associated with domestication and agronomic traits. Nat. Genet. 49, 1082–1088. Varshney, R.K., Song, C., Saxena, R.K., Azam, S., Yu, S., Sharpe, A.G., Cannon, S., Rosen, B., Tar’an, B., Millan, T., Zhang, X., Baek, J., Ramsay, L.D., Iwata, A., Wang, Y., Nelson, W., Farmer, A.D., Gaur, P.M., Soderlund, C., Penmetsa, R.V., Xu, C., Bharti, A.K., He, W., Winter, P., Zhao, S., Hane, J.K., Carrasquilla-Garcia, N., Condie, J.A., Upadhyaya, H.D., Luo, M.C., Thudi, M., Gowda, C.L.L., Singh, N.P., Lichtenzveig, J., Gali, K.K., Rubio, J., Nadarajan, N., Dolezel, J., Bansal, K.C., Xu, X., Edwards, D., Zhang, G., Kahl, G., Gil, J., Singh, K.B., Datta, S.K., Jackson, S.A., Wang, J., Cook, D.R., 2013b. Draft genome sequence of chickpea (Cicer arietinum) provides a resource for trait improvement. Nat. Biotechnol. 31, 240–246. Varshney, R.K., Thudi, M., Pandey, M.K., Tardieu, F., Ojiewo, C., Vadez, V., Whitbread, A.M., Siddique, K.H.M., Nguyen, H.T., Carberry, P.S., Bergvinson, D., 2018. Accelerating genetic gains in legumes for the development of prosperous smallholder agriculture: integrating genomics, phenotyping, systems modeling and agronomy. J. Exp. Bot. 69, 3293–3312. Varshney, R.K., Thudi, M., Roorkiwal, M., He, W., Upadhyaya, H.D., Yang, W., Bajaj, P., Cubry, P., Rathore, A., Jian, J., Doddamani, D., Khan, A.W., Garg, V., Chitikineni, A., Xu, D., Gaur, P.M., Singh, N.P., Chaturvedi, S.K., Nadigatla, G.V.P.R., Krishnamurthy, L., Dixit, G.P., Fikre, A., Kimurto, P.K., Sreeman, S.M., Bharadwaj, C., Tripathi, S., Wang, J., Lee, S.H., Edwards, D., Polavarapu, K.K.B., Penmetsa, R.V., Crossa, J., Nguyen, H.T., Siddique, K.H.M., Colmer, T.D., Sutton, T., Von Wettberg, E., Vigouroux, Y., Xu, X., Liu, X., 2019b. Resequencing of 429 chickpea accessions from 45 countries provides insights into genome diversity, domestication and agronomic traits. Nat. Genet. 51, 857–864. Wang, H., Pandey, M.K., Qiao, L., Qin, H., Culbreath, A.K., He, G., Varshney, R.K., Guo, B., 2013. Genetic mapping and QTL analysis for disease resistance using F2 and F5 generation-based genetic maps derived from Tifrunner  GT-C20 in peanut (Arachis hypogaea L.). Plant Genome 6, 3. Watson, A., Ghosh, S., Williams, M.J., Cuddy, W.S., Simmonds, J., Rey, M.-D., Hatta, M.A.M., Hinchliffe, A., Steed, A., Reynolds, D., Adamski, N.M., Breakspear, A., Dixon, L.E., Riaz, A., Martin, W., Ryan, M., Edwards, D., Batley, J., Raman, H., Carter, J., Rogers, C., Moore, G., Harwood, W., Nicholson, P., Dieters, M.J., DeLacy, I.H., Zhou, J., Uauy, C., Boden, S.A., Park, R.F., Wulff, B.B.H., Hickey, L.T., 2018. Speed breeding is a powerful tool to accelerate crop research and breeding. Nat. Plants 4, 23–29. Yadav, P., Saxena, K.B., Hingane, A., Kumar, C., Kandalkar, V.S., Varshney, R.K., Saxena, R.K., 2019. An “axiom Cajanus SNP Array” based high density genetic map and QTL mapping for high-selfing flower and seed quality traits in pigeonpea. BMC Genomics 20, 235. Yang, S., Saxena, R.K., Kulwal, P.L., Ash, G.J., Dubey, A., Harper, J.D., Upadhyaya, H.D., Gothalwal, R., Kilian, A., Varshney, R.K., 2011. First genetic map of pigeonpea based on diversity array technology (DArT) markers. J. Genet. 90, 103–109. Zhuang, W., Chen, H., Yang, M., Wang, J., Pandey, M.K., Zhang, C., Chang, W.C., Zhang, L., Zhang, X., Tang, R., Garg, V., Wang, X., Tang, H., Chow, C.N., Wang, J., Deng, Y., Wang, D., Khan, A.W., Yang, Q., Cai, T., Bajaj, P., Wu, K., Guo, B., Zhang, X., Li, J., Liang, F., Hu, J., Liao, B., Liu, S., Chitikineni, A., Yan, H., Zheng, Y., Shan, S., Liu, Q., Xie, D., Wang, Z., Khan, S.A., Ali, N., Zhao, C., Li, X., Luo, Z., Zhang, S., Zhuang, R., Peng, Z., Wang, S., Mamadou, G., Zhuang, Y., Zhao, Z., Yu, W., Xiong, F., Quan, W., Yuan, M., Li, Y., Zou, H., Xia, H., Zha, L., Fan, J., Yu, J., Xie, W., Yuan, J., Chen, K., Zhao, S., Chu, W., Chen, Y., Sun, P., Meng, F., Zhuo, T., Zhao, Y., Li, C., He, G., Zhao, Y., Wang, C., Kavikishor, P.B., Pan, R.L., Paterson, A.H., Wang, X., Ming, R., Varshney, R.K., 2019. The genome of cultivated peanut provides insight into legume karyotypes, polyploid evolution and crop domestication. Nat. Genet. 51, 865–876.

Chapter 10

Advancements in plant disease control strategies Mamta Rani, Kriti Tyagi and Gopaljee Jha Plant Microbe Interactions Laboratory, National Institute of Plant Genome Research, New Delhi, India

1 Introduction Plants often encounter a wide range of pathogens, which include various microbes (such as viruses, bacteria, and fungi), nematodes, insects, etc. The pathogen attack can result in an average 26% annual loss in worldwide crop production (Oerke, 2006). Along with pathogen attacks, there are many other factors such as the increasing human population, climate change, environmental pollution, scarcity of water, etc., that adversely affect cultivation. Therefore, for sustainable food production, losses due to plant diseases should be minimized (Bebber et al., 2013; Raza et al., 2019). Rice, wheat, maize, and banana are major staple foods and their production is threatened by many deadly diseases worldwide (Fisher et al., 2012). The major rice diseases are blast disease caused by Magnoporthe grisea, sheath blight disease caused by Rhizoctonia solani, leaf blight caused by the bacterial pathogen Xanthomonas orzyae, etc. Wheat is also a major food crop, and its production is largely affected by fungal diseases such as take all disease (Gaeumannomyces graminis var. tritici), powdery mildew (Blumeria graminis), rust diseases (Puccinia species), Fusarium head blight (FHB), or scab disease (Fusarium graminearum), tan spot of wheat (Pyrenophora tritici-repentis) and septoria leaf blotch (Zymoseptoria tritici), etc. Similarly, maize production is severely affected by bacterial stalked rot (Erwinia crotovora), black bundle disease (Cephalosporium myadis), and common rust (Puccinia sorghi). The banana is majorly affected by black sigatoka and panama disease caused by Mycosphaerella fijiensis and Fusarium oxysporum f. sp. cuben-sis, respectively (Butler, 2013). With climate change, the resurgence of older foes (diseases) and the emergence of newer diseases are becoming important (Cox et al., 2019). Because of limited knowledge about resistance in plants, modern agriculture practices rely mainly on chemical pesticides for pathogen control, which may lead to the development of pesticide resistant or tolerant strains of pathogens (Marco, 2008; Childers et al., 2014; Hahn, 2014). Therefore, new alternative strategies of chemical control should be developed for broad-spectrum and durable resistance against pathogens. Currently, farming practices, biological control and disease-resistant cultivars are used as alternative strategies. Improved plant disease management strategies involving regular surveillance and the removal of infected plants are also being exploited to control the epidemic spread of the disease (Rimbaud et al., 2019). The development and advancement in plant genomic resources such as the availability of the genome sequence with detailed genetic and physical mapping as well as SSR and SNP markers make the breeding programs much faster. Moreover, advancement in research related to plant resistance and defense-related genes is being used to develop disease-resistant plants by transgenic approaches (Dangl et al., 2013; Nejat et al., 2017; Ali et al., 2018; Sa´nchez-Martı´n and Keller, 2019). RNA silencing technologies such as host-induced gene silencing (HIGS) and genome editing tools such as clustered regulatory interspaced short palindromic repeat (CRISPR) are also being used for developing disease-resistant varieties (Shah et al., 2018; Zaidi et al., 2018; Qi et al., 2019). CRISPR/Cas9 is used to target endogenous host susceptibility genes to develop transgene-free disease-resistant plants. This review mainly discusses various methods used for the control of phytopathogens and the development of disease resistance in plants, such as breeding methods, transgenic approaches, and biological control agents (BCAs).

2 Plant immune system Plants are constantly exposed to a wide array of microbial pathogens such as viruses, bacteria, fungi, oomycetes, etc., in their rhizosphere and aerial parts. The plant immune system works as a surveillance mechanism to recognize these pathogens and mount a defense against them. Plant immune system works in two layers of defense response which are known as Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00010-3 © 2020 Elsevier Inc. All rights reserved.

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pathogen-triggered immunity (PTI) and effector-triggered immunity (ETI). The PTI perceives and recognizes certain conserved molecular patterns, PAMPs (pathogen-associated molecular patterns) or DAMPs (damage-associated molecular patterns) (Kaku et al., 2006; Couto and Zipfel, 2016; Schreiber et al., 2016). These conserved patterns are recognized by plant cell-surface receptors. The receptors involved in PTI are termed as pattern recognition receptors (PRR) and they are structurally classified into two categories: receptor RLKs (receptor-like kinases) and RLPs (receptor-like proteins). Although plants use the PTI response against all pathogens, some pathogenic microbes can evade the primary immune response by secreting specialized molecules called effectors. These secreted effectors are recognized by intracellular receptors (Monaghan and Zipfel, 2012) and result in the induction of more specific second layer of defense response termed as ETI. There are two classes of ETI receptors: nucleotide-binding site leucine-rich repeat (NBS-LRR) proteins and Tolllike receptor (TLR) proteins. ETI involves the recognition of secreted pathogen effector proteins called “Avr” (avirulence) and cognate host “R” (resistance) proteins. This results in a cascade of signaling events for the induction of the immune response. Although both PTI and ETI work in collaboration to restrict pathogen growth, ETI provides a more specific, strong, and profound immune response against invading pathogens. The cell signaling events in both kinds of immune responses result in the production of reactive oxygen species, cell-wall modifications, the production of various antimicrobial molecules such as phytoalexins and various other secondary metabolites, antimicrobial peptides (AMPs) such as defensins, ribosome-inhibiting proteins (RIPs), CWDEs, etc. (Silva et al., 2018; Sher Khan et al., 2019). In addition to this, plants also use RNAi-mediated mechanisms for resistance against pathogens (Seo et al., 2013; Hua et al., 2018; Rosa et al., 2018). These defense-related biomolecules and RNAi mechanisms have been used to develop disease-resistant plants. Apart from genetic engineering-based approaches, molecular breeding is also used to develop improved varieties of disease-resistant plants. In the following sections, the molecular breeding and advanced biotechnological approaches are described for the development of disease-resistant crops.

3

Marker-assisted breeding for crop improvement

Breeding plants for desired traits has been a focus since ancient times. Modern food crops such as rice, wheat, maize, etc., are derived from the domestication of their wild relative varieties. The “green revolution” in India was achieved by using breeding methods to improve agriculturally important crops. Breeding for plant disease resistance traditionally involves different kinds of selection methods such as pure-line selection for self-pollinated crops, pedigree selection, backcross selection, recurrent selection, etc. (Acquaah, 2016). Modern molecular methods such as gene pyramiding and gene deployment involve the identification and use of one or more resistance genes to improve plant disease resistance (Miah et al., 2013). Further interspecies hybrids, and somaclonal variations are also used for improving plant disease resistance. These methods either use traditional breeding methods for the introgression of the desired genes in selected cultivars or employ plant transformation techniques. The recent advances in genomics as well as next-generation sequencing tools have led to the rapid discovery and identification of genomic markers associated with desired plant traits (Xu et al., 2017). These markers are being used for marker-assisted breeding and improvement programs. Marker-assisted breeding involves the identification of genetic variabilities among contrasting germplasms and the identification of various chromosomal regions, also called quantitative trait loci (QTL), linked to trait of interests. These QTLs are further explored for the identification of linked DNA markers, which are used in the selection of plants in breeding programs. In marker-assisted breeding selection of desired genotypic combinations and the elimination of undesired plants at early stages of selection are achieved. Marker-assisted breeding can be further divided into different breeding strategies such as genome-wide selection (GWS), marker-assisted selection (MAS), marker-assisted recurrent selection (MARS), and marker-assisted backcrossing (MABC) (Ribaut et al., 2010; Jiang, 2013). MAS has been successfully exploited for the identification of SSR marker Satt309 that is linked with rhg1 disease resistance gene (Cregan et al., 1999). Similarly in wheat, a major QTL Fhb1 linked with resistance against FHB (Fusarium head blight) disease has been identified ( Jiang et al., 2007b; Jiang et al., 2007a; Buerstmayr et al., 2009). MABC is the most successful molecular breeding method for the improvement of different plant species such as rice, wheat, maize, barley, pear millet, soybean, tomato, etc. (Dwivedi et al., 2007; Collard and Mackill, 2008; Xu and Crouch, 2008). MABC has been successfully employed for development of various Bt (Bacillus thuringiensis) maize varieties (Ragot et al., 1995). MABC has also been used to develop partial resistance against barley yellow dwarf by selecting a marker linked to the Yd2 gene ( Jefferies et al., 2003). Similarly, a major QTL loci qHSR1 was also identified in maize for resistance against head smut. MABC was successfully employed for the integration of this locus in head smut-susceptible inbred genotypes with high yield. Another approach in molecular breeding is marker-assisted gene pyramiding which is widely used for stacking multiple disease-resistant genes in one genotype. The advantage of combining multiple genes or QTL is to promote stable and broad-spectrum resistance against single or multiple races of the pathogen. In barley, two stripe rust resistance genes

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and three QTLs from two different parents are combined using marker-assisted gene pyramiding for quantitative resistance against stripe rust disease (Castro et al., 2003). Similarly, this approach is being used for developing broad spectrum disease resistance in rice and wheat (Collard and Mackill, 2008). Some examples of disease-resistant cereal crops developed using marker-assisted breeding are listed in Table 1.

4 Genome editing approaches for disease-resistant plants Genome editing tools have evolved recently that help in precise, efficient, and targeted genome modifications. Various genome editing techniques such as zinc-finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs) have been used frequently to improve crop traits. Recently a simpler and easier approach known as clustered regularly interspaced short palindromic repeats (CRISPR/Cas) has been developed for genome editing (Shah et al., 2018).

4.1 Emergence of CRISPR technology The CRISPR arrays were first identified in the genome of Escherichia coli, way back in 1987 (Makino et al., 2016), However, in 2005, research by various groups hypothesized that the spacer elements of the CRISPR array are of phage origin (Bolotin et al., 2004; Pourcel et al., 2004; Mojica et al., 2005). These spacers were found to consist of a common end sequence, known as protospacer adjacent motif (PAM). This was further validated experimentally by Barrangou et al. (2007), who proved that CRISPR arrays were involved in providing resistance against viruses in association with Cas genes. Later, the mechanisms underlying this phenomenon were deciphered. CRISPR is a complex system and is classified into six different types: Types I, II, III, IV, V, and VI. These different types of CAS proteins target different nucleic acids, as described in Table 2 (Koonin et al., 2017). TABLE 1 Molecular breeding in cereals for disease resistance using marker-assisted backcrossing and marker-assisted gene pyramiding strategies. Plant species

Disease

Gene/QTLs

References

Wheat

Powdery mildew

22 Pm genes

(Zhou et al., 2005)

Wheat

Powdery mildew

Pm2 and Pm4a

(Liu et al., 2000)

Rice

Bacterial blight

Xa21

(Chen et al., 2001)

Rice

Bacterial blight

Xa5, xa13, and xa21

(Sundaram et al., 2009)

Rice

Blast

Pil

(Shi-ping et al., 2003)

Rice

Bacterial blight

xa5, xa13 and xa4, xa21

(Huang et al., 1997)

Rice

Bacterial blight, yellow stem borer, sheath blight

Xa21, Bt, and RC7 chitinase gene, Bt

(Datta et al., 2002)

Rice

Blast disease

Pil, Piz-5 and Pil, Pita

(Hittalmani et al., 2000)

Rice

Brown plant hopper

Bph1 and Bph2

(Sharma et al., 2004)

Rice

Insect resistance and bacterial blight

xa21 and Bt

( Jiang et al., 2004)

Barley

Barley yellow dwarf virus

Yd2

( Jefferies et al., 2003)

Barley

Leaf rust

Rphq6

(Van Berloo et al., 2001)

Barley

Stripe rust

QTLs on 4H and 5H

(Toojinda et al., 1998)

Barley

Barley yellow mosaic virus

rym1 and rym5

(Okada et al., 2004)

Barley

Barley yellow mosaic virus

rym4, rym9, and rym11

(Werner et al., 2005)

Barley

Stripe rust

Rspx and QTLs 4, 7, QTL5

(Castro et al., 2003)

Maize

Corn borer

QTL on chromosomes 7, 9, and 10

(Gonza, 1999)

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TABLE 2 Classification of the CRISPR/Cas system. Class

Type

CAS proteins

Target

1

Type I

CAS1, CAS2, CAS 3, CAS4, CAS5, CAS6, CAS7, and CAS8

DNA

2

Type II

CAS1, CAS2, CAS3, and CAS9

DNA

1

Type III

CAS1, CAS2, CAS5, CAS6, CAS7, CAS10, Csm, and Cmr

RNA/DNA

1

Type IV

CAS1, CAS2, CAS7, and CAS5

RNA/DNA

2

Type V

CAS1, CAS2, CAS4, and CAS12

DNA

2

Type VI

CAS1, CAS2, and CAS13

ssRNA

Lately, Shmakov et al. (2017) predicted three novel Class 2 Cas proteins known as Class 2 candidate 1 (C2c1), 2 (C2c2), and 3 (C2c3). Among these, C2c1 and C2c3 show similarity to Cas12, which belongs to the Type V category. C2c2 is different as it cleaves single-stranded RNA and due to the unique features of C2c2, this system is now known as CRISPR/Cas13a (Table 2).

4.1.1 CRISPR-Cas system: A brief overview The CRISPR/Cas9 system mainly includes two components: a guide RNA and an associated endonuclease known as Cas9. Both these components form a complex where the guide RNA directs the Cas9 endonuclease to the target cleavage site, which is present upstream of a PAM. This leads to the cleavage of target sequence and subsequently the DNA repair occurs through nonhomologous end joining (NHEJ), resulting in insertion/deletion within the genome (Fig. 1). Remarkably, CRISPR/Cas9 has been used to develop homozygous knockout mutant plants in a single generation.

4.1.2 Application of CRISPR/Cas9 for plant defense Over several decades, biotic stresses have adversely affected the major plant species across the world. The need to develop disease-resistant cultivars has increased with the increasing population and demand. For this, newer techniques for crop improvement are needed. The era of traditional breeding practices used for crop improvement and disease resistance has become outdated as these techniques are time consuming and less efficient. The application of the CRISPR/Cas9-based genome editing system for crop improvement has recently gained popularity as this has been successfully used to develop resistant plants against various pathogens, including viruses, fungi, and bacteria. 4.1.2.1 Resistance against viruses Geminiviruses are single-stranded circular DNA viruses that cause destruction of many plants worldwide, leading to reduced crop yields (Moffat, 1999). Gemini virus-resistant plants have been generated by initiating double-stranded breaks (DSBs) within the viral DNA sequence (Arago and Faria, 2009). Recently, gemini virus-resistant tobacco plants (Nicotiana benthamiana) have been developed using this system wherein the intergenic region (IR) of the viral genome has been targeted (Ali et al., 2015; Baltes et al., 2015; Ji et al., 2015). CRISPR system has also been used for intervention against RNA viruses (Zen and Zhang, 2019). Two types of CRISPR/Cas effectors, Cas9 and Cas13a, isolated from Francisella novicida (FnCas9) and Leptotrichia shahii (LshCas13a) or L. wadei (LwaCas13a), are used to target RNA viruses (Sampson et al., 2013; Shmakov et al., 2017). 4.1.2.2 Resistance against fungi Modifications in various plant susceptibility (S) genes have been found to promote broad-spectrum disease resistance in several crop plant species. Wang et al. (2016) have successfully imparted enhanced resistance in rice against blast by mutating the ERF transcription factor gene OsERF922 through CRISPR/Cas9. A CRISPR/Cas9 edited tomato variety resistant to the powdery mildew fungal pathogen Oidium neolycopersici has been developed by mutating the MILDEW RESISTANT LOCUS O (Mlo) (Nekrasov et al., 2017). Mutation in Mlo locus has also led to resistance in wheat against powdery mildew (Shan et al., 2013). Apart from this, CRISPR/Cas-mediated targeting of the locus enhanced disease resistance 1 (EDR1), that encodes a Raf-like mitogen-activated protein has led to a severe reduction in powdery mildew disease in wheat (Zhang et al., 2017).

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SgRNA

Cas SgRNA

as C

DNA

NHEJ

Resistant plant

FIG. 1 CRISPR-Cas9-mediated genome editing in plants.

CRISPR/Cas is also employed for enhancing the biocontrol activity of fungal agents by targeting cellular pathways involved in biosynthesis and production of secondary metabolites as well as secretory enzymes. For example, Δtvk1 mutants of Trichoderma virens, which can produce more lytic enzymes, have enhanced biocontrol activity against R. solani (Mendoza-Mendoza et al., 2003). 4.1.2.3

Resistance against bacteria

Previously it has been reported that a mutation in arabidopsis AtJAZ2 gene confers resistance to biotrophic pathogen Pseudomonas syringaepv. tomato strain DC3000 (Pto DC3000). The Pto DC3000 is also known to cause bacterial speck disease of tomato. Using the tomato ortholog of AtJAZ2 (SlJAZ2), a bacterial speck-resistant tomato variety was generated through CRISPR/Cas9-mediated gene editing (Gimenez-Ibanez et al., 2017). Similarly targeting of OsSWEET through CRISPR has led to resistance against bacterial leaf blight disease in rice ( Jiang et al., 2013). Table 3 summarizes an overview of diseaseresistant plants generated through genome editing tools.

4.1.3 Limitations of CRISPR/cas9 system The sgRNA is a 20-nucleotide sequence that is complementary to target DNA. The PAM sequence adjacent to this target DNA consists of NGG where N could be any of the nucleotides (adenine, guanine, cytosine, or thymine). However, studies suggest that the PAM sequence could also be NRG where R is either adenine or guanine. Although the DNA complementarity is very specific, there are still chances of off target with 3–5 mismatches within the distal part of PAM. This leads to the hybridization of sgRNA to a wrong sequence, which is a major drawback for the application of CRISPR technology. Therefore to overcome this, a specific dCas9 is engineered which lacks nuclease activity and is fused with the nuclease domain of restriction enzyme FokI. The FokI nuclease is activated only when the two subunits interact.

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TABLE 3 Summary of genome-edited plants having resistance against pathogens. Plant S-gene or pathogen gene targeted

Targeted pathogen/ disease

Plant

System

Target modification

Tomato

Transgene free

Gene disruption

SlMLO1

Powdery mildew

(Nekrasov et al., 2017)

Arabidopsis

Transgene free

Gene disruption

eIF4E

Turnip yellow mosaic virus (TuMV)

(Pyott et al., 2016)

Cucumber

Transgene free

Gene disruption

eIF4E

CVYV (ipomovirus), ZYMV, and PRSMV (potyvirus)

(Chandrasekaran et al., 2016)

Apple

Transgene free

Gene disruption

DIPM-1, DIPM-2, and DIPM-4

Fire blight disease (caused by Erwinia amylovora)

(Malnoy et al., 2016)

Wheat

Transgenic

Gene disruption

TaMLO-A1, TaMLO-B1, and TaMLO-D1

Powdery mildew

(Shan et al., 2013)

Wheat

Transgenic

Gene disruption

TaEDR1 (three homologs)

Powdery mildew

(Zhang et al., 2017)

Rice

Transgenic

Promoter disruption

OsSWEET14

Bacterial blight

(Li et al., 2012)

Rice

Transgenic

Promoter disruption

OsSWEET11, OsSWEET14

Bacterial blight

( Jiang et al., 2013)

Rice

Transgenic

Gene disruption

OsMPK5

Fungal (Magnaporthe grisea) and bacterial (Burkholderia glumae) pathogens

(Xie and Yang, 2013)

Tomato

Transgenic

Promoter disruption

DMR6

Pseudomonas syringae, Phytophthora capsici, and Xanthomonas spp.

(De Toledo Thomazella et al., 2016)

Citrus

Transgenic

Promoter disruption

CsLOB1

Citrus canker

(Peng et al., 2017)

Apple

Transgene free

Gene disruption

DIPM-1 DIPM-2 DIPM-4

Erwinia amylovora

(Malnoy et al., 2016)

Grapes

Transgenic

TRF disruption

WRKY52

Botrytis cinerea

(Wang et al., 2018)

Tobacco

Transgenic

ORF and IR disruption

TYLCV-IR

Tomato yellow leaf curl virus (TYLCV)

(Ali et al., 2015)

Wheat/ Barley

Transient

Effectors

BEC1011, BEC1054, BEC1038, BEC1016, BEC1005, BEC1019, BEC1040, and BEC1018

Blumeria graminis

(Pliego et al., 2013)

Wheat

Transgenic

PKA catalytic subunit stable resistance

PsCPK1

Puccinia striiformis f. sp. Tritici

(Qi et al., 2019)

Wheat

Transgenic

Chitin synthase 3b

Chs3b

Fusarium graminearum

(Cheng et al., 2015)

Wheat

Transgenic

1,3-Glucan synthase

FcGls1

Fusarium culmorum

(Chen et al., 2016)

Wheat

Transgenic

MAP kinase, cyclophilin

PtMAPK1 and PtCYC1

Puccinia triticina

(Aranda et al., 2008)

References

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4.1.4 Current status of CRISPR-Cas technology CRISPR-Cas9 represents an improved breeding technology that has been used for generating or improving a variety of disease-resistant crops, apart from improving various other traits like yield, nutritional value, abiotic stress tolerance, and resistance to herbicides, etc. Further, recent progress has been made by using nanoparticles for the delivery of Cas9 and gRNA directly mediated through agrobacterium and viral replicons (Hiei et al., 2014; Nonaka and Ezura, 2014; Khatodia et al., 2016). Genome editing is a low-cost technique with higher precision and rapidness that can be applied to a wide range of plant species. It is very probable that more plants bred with CRISPR technology will be commercially available in the near future.

4.2 RNA interference as a tool for plant defense RNA interference (RNAi) is a gene silencing approach where complementary small RNA binds to its target before transcription (at the promoter) or posttranscriptionally, resulting in the downregulation of target gene expression. RNAi can be used to silence any target gene in plants or their pathogens by expressing an externally introduced RNAi construct with double-stranded hairpin RNA structures, complementary to the desired gene (Eamens et al., 2010; Rosa et al., 2018). In 1998, researchers first demonstrated that RNAi plants that express a longer self-complementary hairpin RNA (hpRNA) are more effective. Since then, hpRNA transgenes have been extensively used to silence plant-viral RNAs. The host gene silencing-hairpin RNAi (HGS-hpRNAi) method can be used to downregulate the expression of various plant susceptibility genes for development of fungal and bacterial disease-resistant plants.

4.2.1 Mechanism of RNA silencing A typical hairpin RNA (hpRNA) construct is comprised of inverted repeats of a sense and an antisense sequence of a region of the target gene and these repeats are joined by a spacer region that is noncomplementary. The sense and antisense sequences in the transcribed RNA are complementary to each other and form a dsRNA structure. This dsRNA structure isrecognized by Dicer enzyme, a member of the RNase III family, which cleaves it into small dsRNA molecules, commonly referred as small interfering RNA (siRNA) (Hamilton and Baulcombe, 1999). These siRNAs are incorporated into a multisubunit nuclease complex termed as RISC (RNA-induced silencing complex). Further, the RISC recognizes the target single-stranded RNA molecules based upon complementarity to siRNAs (Fig. 2). Host-induced gene silencing (HIGS) is also based on the same principle and it is being used for silencing of pathogen genes using host plant RNAi machinery (Hua et al., 2018; Rosa et al., 2018; Qi et al., 2019).

4.2.2 RNAi for plant resistance RNA silencing has been widely used to characterize various fungal pathogenicity genes. For example, the RNAi-mediated silencing of two ACT toxin genes compromised the pathogenesis of Alternaria alternate (Ajiro et al., 2010). In M. oryzae, silencing of genes involved in the calcium signaling revealed some of their importance in hyphal growth, sporulation, and pathogenicity (Nguyen et al., 2008). Similarly, RNAi-mediated silencing of mycotoxin-specific genes in Fusarium graminearum resulted in reduced virulence on wheat (McDonald et al., 2007). Tinoco et al. (2010) reported that RNAi-based HIGS can be used to specifically silence GUS expression in Fusarium verticillioides during infection in tobacco plants. HIGS has also been used for downregulation of several potential pathogenicity genes which were differentially expressed during B. graminis infection in barley. Barley stripe mosaic virus (BSMV)-mediated HIGS was used for disease resistance in wheat against leaf rust fungus Puccinia triticina (Pt) by silencing three pathogenicity genes, a MAPK, a cyclophilin, and a calcineurin regulatory subunit (Panwar et al., 2013). Resistance against bacterial pathogens has also been induced using an RNAi-mediated silencing approach, including crown gall disease caused by Agrobacterium tumefaciens (Escobar and Dandekar, 2003). RNA silencing has also been used to target nematode parasitism genes as well (Urwin et al., 2007). A dsRNA expressed in Arabidopsis thaliana targeting the parasitism-related gene (16D10) provided resistance against root-knot nematode Meloidogyne spp. (Huang et al., 2006).

4.3 Exosome-like vesicle-mediated RNAi silencing: an emerging approach There have been reports that plants transfer sRNA to pathogens and pests to inhibit their virulence. Recently, researchers have found new delivery tools for trafficking these RNA molecules from plants to pathogen. These tools are exosome-like extracellular vesicles, which move across the kingdom from organism to organism and cause silencing. In Arabidopsis and Botrytis cineria interaction, the host cell delivers sRNAs into fungal cells using extracellular vesicles (Cai et al., 2018). The

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FIG. 2 Model for small RNA guided gene silencing.

fungal uptake of these sRNAs induces silencing of the target fungal genes involved in pathogenesis (Fig. 3). These interesting findings may facilitate the use of these extracellular vesicles for the effective delivery of all kinds of sRNAs to silence pathogen virulence genes and provide resistance.

5

Biological control agents for efficient disease management

The wide use of chemical pesticides in agriculture has direct and indirect side effects on environment and organisms (Cook, 2003; Heydari et al., 2007; Kang, 2014). In addition, pathogens gradually develop resistance against many of the commonly used pesticides (Cook, 2003). Biocontrol agents are living organisms which can be used to control or prevent plant disease by inhibiting the growth of the pathogen (Baker, 2003; Cook, 2003). The BCAs can be used in many ways to control plant diseases. Antagonistic species or any other naturally available way to control the pathogen can be employed. In addition, the activation of plant defense response by the use of nonvirulent or incompatible microorganisms can be helpful for controlling the disease (Cook, 2003; Schouten et al., 2007). BCAs have been used to control powdery mildew, Botrytis and other soil-fungal pathogen infections, etc. (Baker, 2003; Cook, 2003; Heydari and Misaghi, 2003; Heydari et al., 2007; Kang, 2014). Some of the examples of biological control methods and their mode of actions have been elaborated below. However, a better understanding of the interaction between plant microbes and their environment is required to develop new and efficient strategies.

5.1 Mechanisms of pathogen antagonism by BCA Biological control requires the interaction of BCAs with plants or pathogens. Generally, a microbe may be considered a BCA when the interaction between the plant and the microbe is beneficial for the plant or the microbe is antagonistic to the pathogen (Cook, 2003; Pieterse et al., 2014). Biocontrol agents suppress plant disease and the causative pathogen in many ways. The following are some of the important ways of pathogen control by BCAs.

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Exosomal protein SiRNA Exosome containing SiRNA and proteins

Delivery of SiRNA and protein to target cells

Receptor protein

Target cell

FIG. 3 Illustration of exosome-mediated delivery of SiRNA into target pathogen cell.

5.1.1 Hyperparasitism In hyperparasitism, BCAs absorb nutrients from the pathogen and harm it. Hyperparasitism can be further divided into four categories based on the mechanism and mode of parasitism: obligate parasites, facultative parasites, predators, and hypoviruses. For example, a viral pathogen of Cryphonectria parasitica fungus has been used as a BCA to manage chestnut blight disease (Milgroom and Cortesi, 2004). There are many fungi that can attack phytopathogenic fungi, including the Coniothyrium minitans, which attacks Sclerotinia sclerotiorum in sunflowers and lettuce (McQuilken et al., 2003). Pythium oligandrum is an oomycete, which is known as a parasite against almost 50 fungal and oomycete species. This fungus spreads in plant roots and protects the plant from other pathogenic fungal and oomycete organisms by potentially degrading the invading pathogen and inducing a plant-defense response (Benhamou and Chet, 1997). In addition, there can be more than one hyperparasite for a pathogen; for example, Acrodontium crateriforme, Cladosporium oxysporum, and Ampelomyces quisqualis are a few fungi that are hyperparasites of the powdery mildew fungus (Milgroom and Cortesi, 2004).

5.1.2 Predation Predation is a generalized and nonspecific interaction between BCAs and pathogens, where the BCA kills the pathogen. Trichoderma spp. fungi are known for their predatory behavior against many pathogenic fungi (Harman, 2007). They also affect the pathogen by multiple mechanisms such as predation, competition, antibiotic secretion, increasing plant fitness by nutrient accumulation and inducing plant defense response. They are also known to change the rhizosphere of a plant, resulting in the inhibition of pathogen growth (Anees et al., 2010). The micropredation of Rhizoctonia solani by Trichoderma spp. involves the secretion of cellulases and other cell wall-degrading enzymes, leading to the direct killing of the pathogen (Benhamou and Chet, 1997).

5.1.3 Competition Competition between antagonistic microbes and pathogens for available nutrients in plants and rhizospheric soil is also effective in pathogen suppression (Keel, 2007; Press et al., 2007; Elad, 2008). Competition for iron in soil is important in disease control by BCAs. Because of the low availability of a soluble form of iron in soil, organisms produce iron-binding molecules called siderophores. It is evident by various studies that siderophore production is important for pathogen suppression by different antagonistic organisms (Keel, 2007). Pseudomonas putida strain which is defective in siderophore production has reduced antagonistic activity against F. oxysporum (Elad, 2008). Similarly, Pseudomonas aeruginosa FP6 produces siderophores for iron acquisition, which is important for its antifungal activities against Rhizoctonia solani and Colletotrichum (Sasirekha and Srividya, 2016). Therefore, iron uptake and utilization are critical for the biocontrol activity of microorganisms.

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5.1.4 Metabolite production Antagonistic microorganisms produce various lytic enzymes against various biomolecules such as chitin, cellulose and other cell wall polymers, proteins, and DNA (Anderson et al., 1988; Press et al., 2007;). Some of the examples of lytic enzyme-producing BCA are Serratia marcescens, Lysobacter, and Myxobacteria (Bull et al., 2007; Ordentlich, 2007). Serratia marcescens secrets chitinase to inhibit the growth of Sclerotium rolfsii. It also produces other metabolites such as hydrogen cyanide (HCN), ammonia, and iron-chelating molecules siderophores for pathogen inhibition. Pseudomonas fluorescens CHA0 produces HCN and siderophores, which are toxic to certain pathogens (Elad, 2008). Thielaviopsis basicola produces HCN to suppress the black rot pathogen of tobacco. Enterobacter cloacae produces ammonia to suppress the Pythium ultimum-caused symptoms in cotton (Howell, 2007). Antagonistic microbes also use specific plant molecules to colonize the plant and to suppress the infection and growth of pathogens. Pseudomonas putida is one such antagonists that uses plant agglutinin to colonize the root. Agglutinin utilization-deficient mutants of P. putida showed reduced rhizosphere colonization and reduced suppression effects against Fusarium wilt in cucumbers (Anderson et al., 1988; Tari and Anderson, 1988; de Boer et al., 2007)

5.1.5 Induction of resistance The nonpathogenic and growth-promoting BCAs can induce the plant defense signaling pathways, thereby making the host plant more resistant to further infection by pathogenic microbes. The plant defense thus induced can be local or systemic (Leeman et al., 1995; Vallad and Goodman, 2004; Audenaert et al., 2007; Cameron et al., 2013) BCAs such as symbiotic rhizobacteria, Pseudomonas sp., Trichoderma sp., and Piriformospora indica induce systemic resistance (ISR) via Jasmonic acid (JA)/ethylene hormonal signaling pathways (Vallad and Goodman, 2004; Haas and Defago, 2005; Harman, 2007; Alkooranee et al., 2017). The inoculation of plants with plant growth-promoting rhizobacteria (PGPRs) may lead to the production of various SAR and ISR elicitor molecules such as siderophores, 2, 3-butanediol, SA, etc. PGPRs are effective in providing resistance against several plant fungal diseases such as anthracnose disease caused by Colletotrichum lagenarium (Ryu, 2004; Pieterse et al., 2014). In addition, several other microbial molecules work as elicitors, which are recognized by plants for the induction of defense responses. These elicitors include cold shock proteins from several bacteria, flagellin and lipopolysaccharides present on Gram-negative bacterial cells, and chitin, ergosterol and xylanases, etc. present in fungi (Ryu, 2004).

5.2 Biological control of fungal pathogens Fungal diseases result in huge crop losses in agriculture. Biological control has mainly been used for postharvest disease control. Microbial populations with biocontrol activity are applied to seeds or soil to control soil-borne pathogens and as a granular spray for pathogens spread by the aerial parts of plants (Cook, 2003). Trihoderma harzianum 1295-22 has been used as a granular formulation to control soilborne pathogens. Its soil application can reduce pathogen growth in soil eventually reducing the disease progression (Lo, 2010). The effectiveness of these formulations is increased by some of the additives. For example, the addition of Triton-X-100 to Trichoderma strain formulations increased the effectiveness against multiple fungal pathogens (Lo, 2010). Triton-X-100 also increases the adhesion of spores to infection areas, thereby enhancing the efficacy of biocontrol formulations. The application of Trichoderma strain 1295-22 initially in soil as granules and later as spray inoculations at frequent time intervals in foliar parts significantly suppressed disease caused by Phythium spp. (Lo, 2010). Many bacterial species have also been reported as having biocontrol activities against Rhizoctonia solani, Fusarium moxysporium, Verticillium dahlia, etc. These bacteria include Pseudomonas spp., Burkholderia cepacian, Burkholderia ambifaria, Burkholderia gladioli, Bacillus subtillis, Bacillus polymyxa, Bacillus cerrues, etc. (Heydari et al., 1997; Heydari and Misaghi, 2003; Press et al., 2007; Leeman et al., 1995; Swain et al., 2017; Parikh et al., 2018). Apart from soilborne pathogens, some antagonist microorganisms are also effective against foliar pathogens, powdery mildew and gray mold diseases have been controlled using antagonistic fungi against these pathogens (Kovach et al., 2000; Kang, 2014). Cotton leak disease of the cucumber was effectively controlled by the bacterial antagonist Bacillus cerrues (Smith, 1993). Viruses also work as biocontrol agents. One such example is hypovirulence against the fungal pathogen Cryphonectria parasitica, the causative agent of chestnut blight (Milgroom and Cortesi, 2004). Biocontrol methods are ecofriendly and safer from a human-health perspective. As discussed earlier, biocontrol using bacterial and fungal antagonistic microbes has shown promising results in the control of various fungal diseases. The effectiveness of BCAs depends on many factors such as the method and timing of application and the amount of biomass used in the application. These strategies are successful in the greenhouse industry and are gaining popularity and acceptance for

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organic and conventional farming, indicating a bright future for their market ( Jacobsen et al., 2007; Joshi and McSpadden Gardener, 2007). In this direction, a biopesticide industry alliance has been formed to promote biocontrol strategies for pest and fungal diseases (Timms-Wilson et al., 2005; Joshi and McSpadden Gardener, 2007). Although the field and market of biocontrol strategies is growing, still new approaches for mass production and effective formulation of biocontrol methods need to be developed. The knowledge of the plant rhizosphere, its microbial members, and the molecular mechanism of disease control by antagonists is also limited. Therefore, this area of research needs to be expanded for the cost-effective and large-scale control of plant diseases. The success of biocontrol agents in disease control, plant growth promotion in greenhouses, and farm applications has proven that they are promising future alternatives in minimizing the use of chemical pesticides and fertilizers.

6 Computational tools The identification of important pathogenicity determinants of the pathogen and host disease resistance as well as susceptibility genes will be helpful to strategize the development of disease-resistant plants. The availability of high-throughput genomic information and advances in computational tools have been useful in mechanistic understanding of host-pathogen interactions. RNAseq is widely used to identify the differentially expressed host and pathogen genes during plant-pathogen interactions (Soderlund, 2009). BLASTx and BLASTp are helpful to functionally annotate the genes. Gene ontology (GO) analysis is used to functionally categorize the differentially expressed genes in various “terms” such as biological process, molecular function, and cellular component. The plant-host interaction-base (PHI-base) is another database that is manually curated and used to curate biological and molecular information for the prediction of virulence-related genes, loss of pathogenicity, etc. (Winnenburg, 2005; Baldwin et al., 2007). For example, PHI-base-based classification has been widely used to predict pathogenicity determinants in various pathosystems (Thakur et al., 2013; Ghosh et al., 2014; Zeng et al., 2018). Further information about pathogenicity-related genes can be obtained by identifying potentially secreted proteins and comparing them with already characterized pathogenic genes from other organisms. Signal IP is used to identify the secretion signal in protein sequences, whereas WoLF-PSORT can be used to identify the localization of proteins, especially extracellular pathogenic proteins (Bendtsen et al., 2004). Pathogen effector proteins are also predicted using EffectorP software based on protein size, net charge, and the presence of cysteine and serine amino acids (Sperschneider et al., 2016). For example, Signal IP and EffectorP are used to identify candidate pathogenicity genes in R. solani AG1A (Ghosh et al., 2018). Many databases such as PathoPlant provide information about molecular signaling cascades specific to organism-level plant-pathogen interactions (Bolı´var et al., 2014). Genomics tools have been helpful in screening the available germplasm to identify the genes associated with disease resistance. The resequencing of the genome is being widely used to identify natural variations in the available germplasm and to develop molecular markers (SNPs, SSRs) to assist in breeding disease-resistant plants ( Jiang, 2013). Further, computational methods have been developed to identify plant genes that may play important roles in disease resistance. For example, the plant R-gene identification has been made easier using software such as the plant resistance genes database (PRGdb). It is the first R-gene database that has information of around 16,000 R-genes belonging to several host-pathogen interactions (192 host plant species and 115 pathogens from diverse groups) (Sanseverino et al., 2009). Apart from this, genome-wide association studies (GWAS) can be used to directly identify candidate genes within the QTLs that are involved in resistance. For example, the R-gene Xa43(t) for bacterial blight was identified in rice using GWAS and confirmed through QTL mapping (Bazakos et al., 2017; Kim and Reinke, 2019).

7 Conclusion and future perspectives The ultimate goal of agricultural biotechnologists is to provide durable resistance and ensure crop protection. The molecular breeding approach has been widely successful. But its success is dependent upon the availability of disease resistance in the available germplasm. The plant transgenic approach does not have such limitations and has been successful in providing disease resistance. However, due to strict biosafety regulations, efforts are being made to use cisgenic and marker-free plants for better adaptability. Finding newer sources of disease resistance “R” defense genes, or manipulating the host susceptibility “S” factors will be helpful in this regard. With the increasing rate of global climate change, virulent strains of phytopathogens have emerged and controlling them will be challenging for sustainable agriculture. The advanced genomic, proteomic, metabolomic, and phenomic approaches can play major roles in identifying newer genes for disease resistance. Apart from these, exploring microorganisms that could serve as biocontrol agents could be an efficient strategy for managing plant diseases.

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Acknowledgments We acknowledge the authors whose work has not been cited in this book chapter due to space limitations. MR is supported by the National PostDoctoral Fellowship from the Science and Engineering Research Board, Government of India. KT is supported by the Senior Research Fellowship from the Department of Biotechnology (Govt. of India). GJ is supported by a core research grant from the National Institute of Plant Genome Research, India, and research funding from the Department of Biotechnology, Government of India.

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Introduction of bacterial blight resistance into Triguna, a high yielding, mid-early duration rice variety. Biotechnol. J. 4 (3), 400–407. https://doi.org/10.1002/biot.200800310. Swain, D.M., et al., 2017. A prophage tail-like protein is deployed by Burkholderia bacteria to feed on fungi. Nat. Commun. 8(1). https://doi.org/10.1038/ s41467-017-00529-0. Tari, P.H., Anderson, A.J., 1988. Fusarium wilt suppression and agglutinability of Pseudomonas putida. Appl. Environ. Microbiol. 54 (8), 2037–2041. Thakur, K., et al., 2013. De novo Transcriptome sequencing and analysis for venturia inaequalis, the devastating apple scab pathogen. PLoS One. 8(1) https://doi.org/10.1371/journal.pone.0053937. Timms-Wilson, T.M., Kilshaw, K., Bailey, M.J., 2005. Risk assessment for engineered bacteria used in biocontrol of fungal disease in agricultural crops. Plant Soil 266 (1–2), 57–67. https://doi.org/10.1007/s11104-005-2567-y. Tinoco, M.L.P., et al., 2010. 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In: Crop Science. pp. 1920–1934. https://doi.org/10.2135/cropsci2004.1920. Wang, F., et al., 2016. Enhanced rice blast resistance by CRISPR/Cas9-targeted mutagenesis of the ERF transcription factor gene OsERF922. PLoS One 11 (4), 1–18. https://doi.org/10.1371/journal.pone.0154027. Wang, W., et al., 2018. Transgenerational CRISPR-Cas9 activity facilitates multiplex gene editing in allopolyploid wheat. CRISPR J. 1 (1), 65–74. https:// doi.org/10.1089/crispr.2017.0010. Werner, K., Friedt, W., Ordon, F., 2005. Strategies for pyramiding resistance genes against the barley yellow mosaic virus complex (BaMMV, BaYMV, BaYMV-2). Mol. Breed. 16 (1), 45–55. https://doi.org/10.1007/s11032-005-3445-2. Winnenburg, R., 2005. PHI-base: a new database for pathogen host interactions. Nucleic Acids Res. 34 (90001), D459–D464. https://doi.org/10.1093/nar/ gkj047. Xie, K., Yang, Y., 2013. RNA-guided genome editing in plants using a CRISPR-Cas system. Mol. 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Chapter 11

How Crisp is CRISPR? CRISPR-Casmediated crop improvement with special focus on nutritional traits Tanushri Kaul, Sonia Khan Sony, Nitya Meenakshi Raman, Murugesh Eswaran, Rachana Verma, Arul T. Prakash, Jyotsna Bharti, Khaled Fathy Abdel Motelb, and Rashmi Kaul Nutritional Improvement of Crops Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India

1 Overview of CRISPR-Cas technology Clustered regularly interspaced short palindromic repeat (CRISPR) or CRISPR-associated (Cas) proteins function as molecular scissors in consonance with the cell’s endogenous repair machinery to form a nano-sized sewing kit, designed to cut and alter DNA at a specific point in the genome. Discovered as a mechanism involved in empowering, facilitating, and assisting bacteria in protecting itself against foreign DNA, the CRISPR-Cas system is comprised of a CRISPR array harboring several Cas genes, and a series of spacers that are short strands of DNA (which originate from and match the corresponding parts of viral DNA termed protospacers) derived from invading elements interspaced with tandem direct repeat sequences (Kim and Kim, 2014). Besides a combination of Cas genes, the complexed CRISPR locus contains small trans-encoded CRISPR RNA, that is, trans-activating crRNA (tracrRNA) sequences and sequences for noncoding RNA elements called CRISPR RNA (crRNA). The transcribed tracrRNA and crRNA together form a guide RNA complex that determines the site-specific cleavage of the target sequence in the DNA/RNA in concert with the protospacer adjacent motif (PAM) region ( Jinek et al., 2014). The endonuclease effect brought about by CRISPR loci is associated with Cas proteins, which are responsible for double-stranded breaks (Cong et al., 2013; Mali et al., 2013). This molecular mechanism of the CRISPR-Cas system was adapted for sequence-specific nuclease activity by using RNA-guided engineered nucleases composed of two components: (a) Cas9-site-directed/specific nuclease (SDN/SSN) and a short guide RNA (gRNA). The short guide RNA (18–20 bp in length) directs the Cas9 protein to its complementary target site to create double-strand breaks (DSBs) in any DNA sequence of the form N20-NGG, wherein NGG is the PAM quintessential for recognition by Cas9 (Sander and Joung, 2014). After DSB induction, the host’s homologous recombination mechanism can repair the DBS via nonhomologous end joining (NHEJ) or homology donor repair (HDR) pathways to ensure the desired modifications in a wide range of organisms and cell types (Fig. 1). As said earlier, targeted genome editing has been employed for gene disruptions, gene additions or replacements, and gene overexpression employing customized engineered nucleases (Xie and Yang, 2013; Kim and Kim, 2014; Hua et al., 2019; Chen et al., 2019; Sedeek et al., 2019). Numerous Cas9 and gRNA variants are available that may be utilized for novel applications, particularly in crop trait improvement, for instance increasing stress tolerance and yield and especially enhancing the nutritional value of crops. According to the updated phylogenetic classification, the CRISPR-Cas systems are divided into two classes, which can be further subdivided into 6 types and 33 subtypes, including their variants (Koonin et al., 2017). Class 1 systems (Types I, III, and IV) form multisubunit effector complexes while Class 2 systems (Types II, V, and VI) employ a single protein to target invading genetic elements (Makarova and Koonin, 2015). The Type II protein, Cas9, has been widely adopted as a molecular tool for genome editing purposes.

2 An array of CRISPR-Cas-mediated genome editing systems CRISPRs have ushered in a new era in genome modification. As previously mentioned, the CRISPR-Cas system is a prokaryotic nucleic acid-based natural adaptive immune response to resist and eliminate foreign genetic elements entering via Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00011-5 © 2020 Elsevier Inc. All rights reserved.

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FIG. 1 Editing plant genomes with CRISPR-Cas is an approach in modern plant biotechnology for integrated breeding and the generation of an innovative toolbox for emerging targeted genome/gene editing.

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plasmids and phage. However, the constant rivalry between microbes such as bacteria and archaebacteria as well as viruses has triggered the evolvement and progression of this CRISPR-based adaptive immunity in bacterial families, thereby empowering them to survive via viral evasion. As a result of this process, diverse CRISPR-Cas systems are currently available as a toolkit to facilitate efficient genetic modifications in crops for trait improvement.

2.1 Cas9 A new robust and efficient CRISPR technique based on the CRISPR-associated protein-9 nuclease (Cas9) from bacteria (Streptococcus pyogenes) is a powerful tool for genome editing (Barrangou et al., 2007). Among different nucleases, Cas9 is the most well studied and commonly used SDN nuclease in genome editing. It comprises two catalytic NHN and RuvC nuclease domains that are responsible for the cleavage of the complementary and noncomplementary strands of the gRNA spacer region, respectively (Nishimasu et al., 2014). The Cas9 protein guided by gRNA cleaves the target sequence at three nucleotides (nt) upstream of the protospacer-adjacent motif (PAM, the most efficient site for SpCas9 is 50-NGG-30), resulting in DSBs at the target site within DNA both in vivo or in vitro. The mutations are incorporated into the DNA when these DSBs are repaired by the host either by NHEJ (leads to knockout via insertions or deletions, that is, InDels) or HDR (leads to knock-in or gene replacement). Genome editing in crops has emerged as a propitious approach to cope with agricultural and food security challenges. Crops targeted for genome editing include Arabidopsis, tobacco, wheat, rice, maize, soybeans, tomatoes, potatoes, cucumbers, Populus, watermelons, and oranges, The results have revealed the precision and effectiveness of the CRISPR-Cas9 system for the genetic improvement of crops (Shan et al., 2013; Nekrasov et al., 2013; Liu et al., 2015a; Jacobs et al., 2015; Wang et al., 2015; Svitashev et al., 2016; Chandrasekaran et al., 2016; Ueta et al., 2017; Shi et al., 2017; Tian et al., 2017; Fred et al., 2018; Chenlong et al., 2019).

2.2 Cpf1 In addition to the CRISPR-Cas9 system that employs the Cas9 endonuclease, an increasing number of CRISPR-Cas systems have emerged that hold immense promise in crop genome editing for crop enhancement. CRISPR/Cpf1 (from the bacteria Prevotella and Francisella) has emerged as a remarkably versatile editing tool for genome editing in plants that is analogous to the CRISPR-Cas9 system (Zetsche et al., 2017). Cpf1 or Cas12a is a simpler and smaller endonuclease than Cas9, normally expressed using an RNA polymerase III (Pol III) promoter, which overcomes the limitations of the CRISPR-Cas9 system. Cpf1 genes are associated with the CRISPR locus, and the guide RNAs are noncoding small RNAs with g the guide sequence at their 30 end. The Cpf1 protein family consists of at least 16 reported members (Zetsche et al., 2015). Three Cpf1 orthologous proteins—LbCpf1 (Lachnospiraceae bacterium ND2006), FnCpf1 (Francisella novicida U112), and AsCpf1 (Acidaminococcus sp. BV3L6)—are the main Cpf1 proteins being identified. Among them, FnCpf1 is the most interesting Cpf1, as the PAM sequence “TTN” results in broader targeting opportunities as compared to the TTTV of AsCpf1 and LbCpf1. Certain characteristic features set Cpf1 apart from Cas9. First, the required PAM sequence to allow DSBs by Cpf1 is (T) TTV, directly upstream of the target. This T-rich PAM highlights the importance of Cpf1 as a genome editing tool, as AT-rich sequences are mostly found in intergenic regions while intragenic regions are GC-favored (Pozzoli et al., 2008). Second, Cpf1 does not require transRNA and has both DNase and RNase activities that empower it to process transcribed CRISPRs independently (Fonfara et al., 2016). As only one transcript would be required for multiple targets, this facilitated multiplex editing instead of employing distinct Pol III promoters for gRNA expression or gRNAs flanked by ribozyme sequences, as used for Cas9 (Tang et al., 2016). Finally, Cpf1 induced staggered DSBs, with 50 overhangs of 4–8 bases (Lei et al., 2017) that promoted HDR as against the DSBs with blunt ends created by Cas9. The first reports of FnCpf1 revealed the induction of differential average mutation frequencies, for instance in rice (28.2%) and tobacco (47.2%), where the crRNA was expressed employing the U6 promoter (Endo et al., 2016). Also, LbCpf1 showed a 41.2% efficiency in rice where a U3 promoter drove crRNA expression (Xu et al., 2017). Further, LbCpf1 in rice revealed a biallelic mutation frequency of 100% by employing the Pol III-expressed and ribozyme-processed crRNA system (Tang et al., 2017a).

2.3 Cas13a A Class 2 Type VI system (earlier known as C2c2), CRISPR-Cas13 offers an innovative RNA-targeted editing system based on the bacterial immune system that protects them from viruses. Cas13 can identify the target and efficiently cleave ssRNA (Aman et al., 2018), with a preference for targets with protospacer flanking sites (PFSs) (Cox et al., 2017). CRISPRCas13 is divided into four subtypes: Cas13a, Cas13b, Cas13c, and Cas13d (VI-D). The Cas13 protein family has two higher

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eukaryotic and prokaryotic nucleotide-binding (HEPN) domains in place of a DNAse domain that differentiate it from both Cas12 and Cas9. The target specificity of Cas13 has been regulated by a 28–30 nt spacer and a guide RNA (64 nt). Due to the presence of two HEPN domains, Cas13 has been exclusively associated with RNase activity and can be heterologously expressed in both mammalian and plant cells (Anantharaman et al., 2013). LwaCas13a from the bacteria Leptotrichia wadei showed RNA cleavage activity (comparable to RNAi knockdown), and effectively targeted either reporter or endogenous transcripts (Abudayyeh et al., 2017). The catalytic activity of the CRISPR-Cas13a system enabled RNA interference efficacy against RNA viruses in the plant system and also processed long pre-crRNA transcripts into functional crRNAs. It was reported that the CRISPR-Cas13a system resulted in RNA interference against TuMV-GFP in Nicotiana benthamiana (Aman et al., 2018). The CRISPR-Cas13a genome editing system may augment research possibilities for plants and other eukaryotic species via viral RNA interference.

2.4 Cas14a Constant rivalry between microbes, for instance bacteria and archaebacteria as well as viruses, has triggered the evolvement and progression of CRISPR-based adaptive immunity in bacterial families, thereby empowering them to survive via evading viruses. Previously, a Cas-II CRISPR-Cas protein family was identified that comprised a standalone 100–200 kDa Cas protein with multiple functional domains, and performed sgRNA-directed binding and incision of substrates of either DNA or RNA. On the basis of the phylogenetic analysis, DNA-binding Class 2 Cas proteins evolved from an ancestral gene that shared an RuvC-like endonuclease domain (Shmakov et al., 2017). In the recent past, Jennifer Doudna’s group discovered a simple, small, and efficacious CRISPR-Cas14a protein from an extremophile archaebacterium that belonged to the superphylum DPANN (Aquino-Jarquin, 2019). Cas14a represented a snapshot of the evolutionary process of the Class 2 CRISPR-Cas system (Harrington et al., 2018), which bound as well as cleaved single-stranded (ss) DNA rather than double-stranded (ds) DNA in a PAM-independent manner. It conferred immunity to natural hosts that propagated through ssDNA intermediates, for instance, viruses with ssDNA genomes, mobile genetic elements (MGEs) such as (retro)transposons, and integrative plasmids (Krupovic, 2013). The CRISPR-Cas14 system offers promising features for the precision introduction of desired mutations (via insertions and/or deletions) than earlier reported Cas proteins (Savage, 2019; Yan et al., 2019). The mass of the tracrRNA-crRNA-Cas14a assembled complex is 48% RNA by weight. Cas14a recognized and targeted sequences in the DNA substrate without a specific PAM sequence and represented the smallest RNA-guided nuclease molecular scissor of (400–700 amino acids). Cas14 exhibited high fidelity in the recognition of ssDNA substrates, which was mediated by seed sequence interactions near the middle of the ssDNA target. Cas14 elicited nonspecific (noncomplementary) ssDNA trans-cleavage activity, similar to the Cas12a nuclease. As an RNA-guided platform, CRISPR-Cas14 may screen mutation frequencies that differentiate genotypes in the single-nucleotide range (AquinoJarquin, 2019). Trans-acting nonspecific ssDNA degradation occurred by collateral nuclease cleavage and target binding by Cas14 (Harrington et al., 2018). However, Cas14, like most Type V proteins, cleaved dsDNA targets in the vicinity of a T-rich PAM (50 -TTTR-30 ) (Karvelis et al., 2019). It was reported that CRISPR-Cas14a acted as a powerful “dual-hit” system that enabled resistance against both plant ssDNA and dsDNA containing virus families, including nanoviridae and geminiviridae (Ali et al., 2015; Watters et al., 2018). In a nutshell, the usage, efficiency, and constantly evolving nature of these bacterial endonucleases pose crucial implications on the precise editing of crop genomes and thereby create innovating avenues for crop enhancement.

3

Advancements in genome editing for crop improvement: stress and nutritional traits

The design and application of zinc finger nucleases made its impact in 1996 and has since been employed for validation of the targeted inactivation of endogenous genes in plants, the high-frequency modification of genes, the precisely targeted mutation of the herbicide-tolerance gene, and the insertional disarray of a target locus in crops. ZFNs also have been used in maize for trait stacking. ZFNs provided high specificity and efficiency with minimal nontarget effects over other editing tools. Presently, efforts are focused on further improving the design and delivery as well as expansion of applications for diverse crops of interest. For example, the use of ZFNs in maize and Arabidopsis has led to the development of herbicide-tolerant genotypes through the mutation of herbicide-resistance genes, such as resistance to bialaphos (BAR) and acetolactate synthase or ALS, into targeted sites in the genome. Based on the specificity and mode of action of TALENs, it should be possible to introduce double-strand breaks in any location of the genome. That location harbors the recognition sequence corresponding to the DNA-binding domains of TALENs. There is another condition that also needs to be met, that is, the need for thymidine before the 50 end of the intended target sequence because it has been demonstrated that

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the W232 residue in the N-terminal portion of the DNA-binding domain interacts with the thymidine, influencing the binding efficiency. Unlike the chimeric TALEN proteins, target site recognition by the CRISPR-Cas9 system is proficient by the complementary sequence-based interaction between the gRNA (noncoding) and DNA of the target site. Also, the gRNA-Cas9 protein complex has the nuclease activity for the exact cleavage of the double-stranded DNA using Cas9 endonuclease. The CRISPR-Cas9 system has been employed in various fields of fundamental and applied biology, biotechnology, and genetic engineering due to the simplicity and robust efficiency of genome alterations to understand the regulation of gene activity and activation as well as the repression of proteins and promoter activity that control the gene function. In one example, the inhibition and stimulation of the function of the target gene can be achieved by complex binding to the target DNA. Another welcome feature of incorporating several gene constructs at different genome sites in multiple cells helps in investigating intergenic interaction. In essence, CRISPR-Cas9 genome editing techniques preserve the native genomic structure by minimal modification, unlike the transgenic approach. Therefore, it is considered a safe technology for crop improvement. Despite this, there are some concerns related to the biosafety issue of crops developed using these methods. One main concern, in terms of biosafety, is the possibility of off-target effects during genome editing. The ability to establish targeted genomic modifications makes genome editing tools very promising for engineering important crop traits. The advent of CRISPR-Cas9 has significantly augmented the application of genome editing for crop breeding (Xu et al., 2015a; Chen et al., 2019). Enormous progress has been achieved in the area of CRISPR-Cas breeding technology in the past 5–6 years. Here, we highlight the different tools available and their potential implications in crop improvement.

3.1 Gene knockout Gene knockout (KO) may be generated by DSBs via the removal of a few base pairs or fragments of a gene from the genome, thereby introducing a mutation that immobilizes the expression of the particular gene of interest. Gene KO by CRISPR-Cas mediated technology is widely used to study the functional importance of specific genes. To date, this system has been successfully established in a diverse range of crop species, for instance, two elite glutinous sticky japonica rice varieties that have been developed by the KO of the waxy (Wx) gene (Yunyan et al., 2019). Similarly, the maize waxy gene (Wx1) was knocked out by CRISPR-Cas9-mediated gene editing for generating high-amylopectin (waxy) maize by Corteva Agriscience (DuPont Pioneer, 2016). Wx1 encodes for the granule-bound starch synthase (GBSS), which is responsible for making amylose. Due to the KO of the GBSS gene, amylose was not synthesized, which led to the development of amylopectin-rich (waxy) maize. Another report revealed that the targeted mutagenesis of the starch branching enzyme SBEIIb using the CRISPR-Cas9-based system led to the generation of rice containing high amylose (Sun et al., 2017). Ethylene-responsive factors (ERF), a subfamily of the APETALA2/ethylene responsive factor (AP2/ERF) transcription factor superfamily in plants, are responsible for the modulation of multiple stress tolerances and are concerned with multiple stress responses (abiotic and biotic). The CRISPR-Cas9-mediated knockout of the OsERF922 gene produced blast-resistant rice lines (Wang et al., 2016). The CRISPR-mediated knockout of floral development genes (AP1, SVP, and TFL) led to an improvement of floral traits in Arabidopsis (Liu et al., 2019). The targeted knockout of the BADH2 (betaine aldehyde dehydrogenase) gene resulted in aroma enhancement in rice grains (Gaoneng et al., 2017). Thus, the employment of CRISPR-Cas-based tools or systems for the introduction of specific genetic mutations has led to the modification of complex metabolic processes. This which offers immense opportunities for the development of novel germplasms harboring crucial agronomic traits that may be utilized for CRISPR-Cas-mediated crop breeding in popular crop varieties.

3.2 Precise editing via gene targeting Based on homologous recombination (HR), the replacement of an endogenous gene fragment may be achieved by employing gene targeting (Capecchi, 2005). To enhance the frequency of homologous recombination in plants, DSBs in DNA have been introduced at the target site (Steinert et al., 2016). Moreover, the codelivery of the SSN editing system and a homology donor template as a repair template into the plant cell facilitated gene targeting in a precise manner (Li et al., 2013). Enhanced editing efficiency may be achieved via Gemini viral replicon, as they provide a high concentration of donor DNA (Baltes et al., 2015; Wang et al., 2017a). Gene targeting may also be influenced by balancing the ratio of donor DNA and CRISPR construct via a biolistic approach (Sun et al., 2016; Li et al., 2018a). Somatic cells have a low HR rate. To overcome this, riveting Cas9 expression in the early embryo and egg cells has been explored, thereby conferring improved gene targeting efficiency in Arabidopsis (Miki et al., 2018; Wolter et al., 2018). The customization of synthetic alleles has emerged as a tremendous attribute of genome-editing technologies that may not have been achieved with the available natural genetic variation in plants. For instance, switching the maize ARGOS8

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promoter with the GOS2 promoter increased the yield under limited water conditions (Shi et al., 2017). Romer et al. (2009) reported that shuffling several TAL effector-binding sites in the promoters of R genes conferred resistance across numerous strains of Xanthomonas. Even though genome editing offers differential beneficial aspects, complicated alleles required high precision. The CRISPR-Cas system enabled HDR-mediated gene targeting to tide over such constraints. However, to date the HDR pathway efficiency reported in plant cells has been low, which may be attributed to the lack of efficient delivery methods for DNA repair templates (Steinert et al., 2016; Yin et al., 2017; Chen et al., 2019; Sedeek et al., 2019). In line with this, several improvements in DNA delivery methods were developed, for instance, an increased amount of donor DNA (Baltes et al., 2014) as well as the use of KU70/80 and LIG4 that suppressed the nonhomologous end joining (NHEJ) repair pathway (Endo et al., 2016). According to Li et al. (2019), the production of RNA transcripts in vivo localized in the nucleus can serve as repair templates for transcript-template HDR (TT-HDR)-mediated precise gene editing; this showed a promising mutation frequency in rice (Li et al., 2019). Another report demonstrated that the sequential transformation of Arabidopsis thaliana for sequence replacement by homologous recombination improved the frequency of HDR-mediated gene editing (Miki et al., 2018). Hence, efficient gene replacement may be achieved in plant cells by harnessing the potential of the HDR pathway.

3.3 Base editing Base editing has been recently reported as a novel genome editing method that enables the irreversible conversion of one DNA base to another at a target site without the involvement of DSBs as HDR. This form of targeted base editing has been evolved by utilizing the merged complex of the Cas9-Nickase (Cas9n) and nucleoside deaminases. There are two classes of DNA base editors: adenine base editors (ABEs) that aid the conversion of an AT into a GC base pair, and cytosine base editors (CBEs) that convert a CG into a TA base pair. In this approach, nucleoside deaminases (cytidine, adenine) in combination with the Cas9/sgRNA loaded complex installed point mutation at a target site, resulting in the conversion of cytosine or adenine into uracil or inosine via the hydrolysis reaction. Subsequently, after repair or DNA replication, the edited strand had thymine or guanine instead of cytosine or adenine (i.e., a single nucleotide bubble created by Cas9n) (Li et al., 2017a; Hua et al., 2018; Ren et al., 2018; Kang et al., 2018). A uracil glycosylase inhibitor is also employed in Cas9n in cytosine base editors for increased specificity and efficiency of base editing (Komor et al., 2016; Ren et al., 2018). Both cytosine and adenine base editors (CBEs and ABEs) have been employed previously in several plant species. The rice genes OsNRT1.1B, OsSLR1, OsPDS, and OsSBEIIb edited with the BE3 system revealed an editing efficiency of up to 20% (Komor et al., 2016; Nishida et al., 2016; Ren et al., 2018; Zhu et al., 2019). Gao et al. (2017) demonstrated the efficacy of base editing system (BE3) in different crops for instance rice, wheat, and maize wherein it revealed editing efficiencies up to 43% with an indel frequencies between 0.01% and 0.22%. Taken together, single base editing has a promising role in introducing mutations at target genomic loci, as it enhanced the efficacy of CRISPR-Cas9-mediated genome editing by reducing off-target effects. The earliest described CBEs that facilitated the C-to-T conversion were created via the coalition of Cas9n with rat cytidine deaminase (rAPOVEC1) or activation-induced cytidine deaminase orthologs PmCDA1 (Li et al., 2017a; Lu and Zhu, 2017; Ren et al., 2018; Shimatani et al., 2017; Zong et al., 2017; Zhong et al., 2018; Zuo et al., 2019). Nevertheless, the increasingly efficacious and valuable CBEs were limited to edit sites, which comprise NGG-PAM sequences due to the routinely used SpCas9n (Anders et al., 2014; Nishimasu et al., 2014). This property restrained base editing to an exiguous window of a few base pairs from the upstream of the PAM. To circumnavigate this restriction, numerous studies reported novel CBEs that use SpCas9 variants or Cas9 homologs that identified the altered PAMs requisite for base editing instead of the canonical NGG protospacer adjacent motif (PAM) sequence. For instance, Wu et al. (2019) fused the Cas9 D10A Nickase of several SpCas9 variants with cytidine deaminase 1 from Petromyzon marinus (PmCDA1) as well as a uracil DNA glycosylase inhibitor (UGI). This created two novel efficacious PmCDA1-based cytosine base editors (pBEs), first SpCas9 Nickase (SpCas9n)-pBEs and second VQR Nickase (VQRn)-pBEs, which widened the scope of genome targeting for C-to-T in rice. Employing this approach, they achieved enhanced base editing efficiencies between 4% and 90% in T0 rice lines that were tantamount to increasing the base editing efficiencies by 1.3- to 7.6-fold (Wu et al., 2019; Wang et al., 2019). Numerous engineered Cas9 variants that accepted altered PAM sequences have been utilized with rAPOVEC1 or an activation-induced cytidine deaminase that generated novel CBEs employed in rice (Negishi et al., 2019; Jin et al., 2019), human cells (Zong et al., 2018; Kim et al., 2017; Hu et al., 2018; Nishimasu et al., 2019), and animals (Xie et al., 2019). Among the novel CBEs employed in plants, SpCas9n-NG, SaCas9n, and both rAPOVEC1 based and activation-induced cytidine deaminase based (PmCDA1-based) were efficiently utilized in rice (Qin et al., 2018; Endo et al., 2019). The evaluation of any potential RNA mutations rendered by DNA-based editors was elusive. Moreover, recently Zhou et al. (2019) quantitatively evaluated RNA single nucleotide variations (SNVs) that were incorporated by

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CBEs or ABEs and revealed that both CBEs and ABEs created thousands of off-target RNA SNVs. Eventually, by employing engineered deaminases, for instance, three CBE variants and one ABE variant, they demonstrated a reduction in off-target RNA SNVs to the baseline while sustaining high DNA on-target activity. A previously overlooked aspect of off-target effects in DNA editing may be eliminated via such proficient engineering of deaminases.

3.4 Prime editing The competence to create essentially any targeted change in the genome of any living cell or organism is a longstanding aspiration of scientists. Despite the rapid advancements in genome editing technologies, the majority of the > 75,000 known human genetic variants associated with diseases pose huge problems. Programmable nucleases such as CRISPR-Cas9 make double-strand DNA breaks (DSBs) that can inactivate genes by inducing mixtures of insertions and deletions (InDels) at target sites. DSBs, however, are associated with undesired outcomes, including complex mixtures of products, translocations, and p53 activation. Moreover, the vast majority of pathogenic alleles that arise from specific insertions, deletions, or base substitutions require more precise editing technologies to correct. While increasing the efficiency and precision of DSB-mediated editing remains the focus of promising attempts, these challenges inspire the exploration of alternative precision genome editing strategies. As presently reported, base editing efficiently incorporated four transition mutations (C→ T, G → A, A → G, and T → C) without requiring DSBs in many cell types and organisms, including mammals (Komor et al., 2016; Gaudelli et al., 2017; Rees and Liu, 2018; Gao et al., 2018), but cannot currently perform the eight transversion mutations (C→ A, C → G, G → C, G → T, A ! C, A → T, T→ A, and T→ G) such as the TA-to-AT mutation needed to correct the significant cause of sickle cell disease (HBB E6V). Moreover, a DSB-free method for the creation of targeted deletions, such as the deletion of the 4-base duplication that causes Tay-Sachs disease (HEXA 1278 +TATC), or targeted insertions, such as the 3-base insertion required to rectify cystic fibrosis (CFTR ΔF508), was elusive. Targeted transversions, insertions, and deletions are difficult to be rectified without byproducts in most cell types, even though they collectively account for most known pathogenic alleles. However, the latest report on the evolution of prime editing, a “search-and-replace” genome editing technology, enabled targeted insertions and deletions of all 12 possible base-to-base conversions and combinations thereof in human cells without the requirement of DSBs or donor DNA templates (Anzalone et al., 2019). Prime editors (PEs), initially represented by PE1, employed a reverse transcriptase (RT) fused to an RNA-programmable nickase (Cas9n) and a prime editing guide RNA (pegRNA) to directly copy genetic information from the extension on the pegRNA into the target genomic locus. PE2 utilized an assembled RT to modify editing efficiencies while PE3 nicks the nonedited strand to induce its substitution and led to accelerated editing efficiency, typically from 20% to 50% with 1%–10% InDel formation in human HEK293T cells (Anzalone et al., 2019). Prime editing generated less off-target activity than Cas9 at known Cas9 off-target loci, offered fewer byproducts and significantly similar efficiency compared to Cas9-initiated HDR, and had complementary strengths and weaknesses compared to base editors. By enabling precisely targeted insertions, deletions, and all 12 possible classes of point mutations without requiring DSBs or donor DNA templates, prime editing has the potential to advance the study and correction of the vast majority of pathogenic alleles.

3.5 Molecular farming Producing heterologous recombinant proteins and other secondary metabolites in the plant using genome editing tools offers a potent avenue to meet an almost unlimited demand. Molecular farming has emerged as a crucial approach to enhance crop quality and an improved strategy to produce biopharmaceuticals by modifying the characteristics of recombinant proteins. Human therapeutic proteins produced in plants often carry plant-like glycan rather than human-like. Plant glycan, sometimes considered undesirable, can affect protein stability, biological function, and immunogenicity. The modification of the plant metabolism to avoid glycan synthesis is an important application of multiplex genome editing (MGE) in molecular farming (Ma et al., 2003). Knocking out the targeted gene that encoded the enzymes, that is, β(1,2)-xylosyltransferase (XylT) and a (1,3)-fucosyltransferase (FucT), may produce a desirable recombinant protein without synthesis of the plant glycan. These two enzymes are liable for the production of key glycan signatures in plant proteins, which differ from those produced in mammals. It was demonstrated that the mutant of N. benthamiana also manufactured a recombinant antibody without the synthesis of plant glycans by knockout of the 2 XylT and 4 FucT enzyme encoding genes ( Jansing et al., 2019). Similarly, CRISPR-Cas9-based knock-outs of the XylT and FucT genes in tobacco L.cv Bright Yellow 2 (BY2) cell suspensions resulted in removal of plant glycans. It is irrefutable that the MGE technique offers a promising platform for manufacturing potent bio-pharmaceutical products (Mercx et al., 2017; Hanania et al., 2017). This may offer an adequate chance to extend potential targets for genome editing.

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3.6 Molecular domestication via CRISPR-Cas9-based breeding The limited genetic range of domesticated crops has played a major role in the global yield experienced in breeding programs. Genome-editing tools can be employed to remodel genetic diversity in individual genes; however, finding significant alleles could need more attention as most of the agronomic traits are regulated by multiple alleles. When combined with conventional breeding, genome editing technology can speed up the introduction of desired traits and significantly reduce costs. Besides, the genetic elements introduced can be moved from the genome through breeding or generating segregation lines, which make plants null segregate (Mao et al., 2019). The efficacy of targeting single gene-regulated qualitative traits using genome editing has been demonstrated, for instance, the grain amylose content and the oil quality of soybeans (Haun et al., 2014; Zhang et al., 2017). However, quantitative agronomic traits may be regulated by several QTLs (Zuo and Li, 2014; Xing and Zhang, 2010), for instance stress and yield should be targeted with caution as more than one gene may be implicated. Plant domestication involved the evolution of crop plants from their wild relatives by employing artificial selection. During the long domestication process, farmers selected useful genomic traits such as high plant yield, easy harvest, stress tolerance, etc. The domestication of wild plant species using the CRISPR-Cas system creates a novel platform for crop evolution. With the aid of quantitative genetic, bioinformatic, and genomic studies, several genes have been identified that control the domestication of traits in different crop species (Meyer and Purugganan, 2013). Numerous wild tomato species were identified associated with many agronomically desirable traits. Scientists reported the de novo domestication of the orphan Solanaceae crop and the groundcherry (distant tomato relative) by the CRISPR/Cas9based editing of orthologs of the tomato domestication genes (Lemmon et al., 2018). The improvement of the autotetraploid tuber crop potato through the conventional breeding process has posed huge difficulties. Recently, the potato has been redomesticated into the self-compatible diploid potato by disruption of the self-incompatibility gene S-RNase by using the CRISPR-Cas9 system (Ye et al., 2018).

3.7 Editing for simple and complex traits The potentialities to introduce precise and targeted genome editing in different agronomical important traits make genome editing technology very useful. As a genome editing tool, CRISPR-Cas9 has significantly stimulated the application of genome editing for crop breeding (Chen et al., 2019). Desirable agronomically important traits are controlled by a single gene called the single-gene trait. In the case of a single-gene controlling trait, the effect of the mutation on that gene generally affects the specific trait without compromising other important agronomic characteristics. The prolonged accumulation of heavy metal Cd in rice has harmful effects for consumer health, and it is very difficult to reduce this by conventional breeding approaches. Employing the CRISPR-Cas9 tool, the metal transporter gene OsNramp5 was knocked out, resulting in low Cd accumulation in rice grains without affecting other important agronomic characteristics (Tang et al., 2017b). Numerous single-gene controlling traits have been improved by targeted mutagenesis using the CRISPR-Cas9 system, including rice amylose content (Sun et al., 2017), rice aroma (Zhang et al., 2017), the photoperiod in soybeans (Cai et al., 2018), low phytic acid in maize (Liang et al., 2014), maize with high amylopectin by Corteva Agriscience (DuPont Pioneer, 2016), and maize higher density (Li et al., 2017b; Tian et al., 2019). The CRISPR-Cas9-based editing system has been employed to generate bacterial blight-resistant indica rice (IR24) by targeting the promoter regions of OsSWEET13 (Zhou et al., 2015). Similarly, blast disease-resistant rice lines also have been developed by targeted mutations in the ethylene-responsive factor, OsERF922 (Liu et al., 2012). CRISPR-Cas9-mediated KO rice lines for the Annexin gene (OsAnn3) revealed cold stress tolerance (Shen et al., 2017). In contrast, many economically important agronomic traits are regulated by complex genetic networks. Rice grain yield is an example of a well-characterized complex trait that is controlled by many quantitative trait loci (QTL) (Xing and Zhang, 2010). Rice yield may be improved by individual or multiplex genome editing of these QTLs, after careful analyses, such that other growth and development-related parameters remain unaffected. Numerous important traits such as yield and abiotic stress tolerance are regulated by more than one gene or QTL. Numerous attempts have been made via different crop improvement programs to map these quantitative stretches of QTL modulating agronomically crucial traits. The introgression of these characterized QTL regions into elite lines has led to the generation of varieties with improved performance. Invariably, the introgression of QTLs is difficult when they are closely linked and the incorporation of nontarget genomic regions into elite lines may be hazardous. Thus, CRISPRCas9-based breeding may have emerged as a potential tool to introgress or incorporate and analyze such rare mutations in crops. Shen et al. (2018) reported the role of QTLs that code for grain size (GS3) and number (Gn1a) in rice varieties employing the CRISPR-based QTL editing approach. Their study revealed that the same QTL interestingly showed increasingly varied and contrasting effects when introduced in differential backgrounds.

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3.8 Multiplex genome editing and applications The establishment of CRISPR-Cas tools offers powerful nuclease-mediated multiplex genome engineering (MGE) capabilities, thereby considerably saving resources and time for developing crop lines with multiple traits. The CRISPR-Cas system has been widely exploited because of its multiplexing capabilities for genome editing (Adiego-P
erez et al., 2019). For the concurrent introduction of multiple transgenes into plants, several approaches have been established (Naqvi et al., 2010). Recently, MGE in plants has been widely used to mutate homeoalleles/multiple alleles or simultaneously introduce up to 107 genes of the same gene family, target multiple genes and multiple sites in the same gene as well as in multiple gene variants or members of gene families (Kannan et al., 2018). To regulate gene expression at the genetic and epigenetic levels or to attain the concurrent alteration of multiple traits, MGE can target different genes with a similar function (e.g., developmental or metabolic pathway) (Minkenberg et al., 2017). Despite many advantages of ZFNs and TALENs in genome editing, the CRISPR-Cas9 system provides much more flexibility to edit dissimilar targets due to its simplistic and comparatively less expensive requirements of multiple guide RNAs (gRNAs) (Xing et al., 2014; Ma et al., 2015). The earliest report of using MGE involved two gRNAs that were used to simultaneously modify two targets within the acetolactate synthase gene (ALS1) in rice, resulting in the successful amino acid substitutions W548L and S627I (Sun et al., 2016). The multiplex genome editing system has offered several platforms that have different practical applications. Much progress has been made during the past few years. Here, we summarize the applications of multiplex genome editing for crop improvement. First, targeting noncoding regions that do not encode any protein sequence but have an impactful effect on the multiplex genome editing system. MGE introduced large fragment deletions or insertions in the noncoding region randomly by the RNA-guided Cas9 system, thereby providing a wide range of genetic variation in expression levels (Najera et al., 2019). Recently, the MGE system optimized in A. thaliana achieved the simultaneous mutation of the flowering control genes (ELF6, REF6, and At5g46910) by deleting 450 bp regulatory regions within intron 2 of the AGAMOUS gene (Yan et al., 2016). The MGE technique exploited the heterozygous loss of function in the tomato, targeting different regions of a 2 kb segment upstream of the tomato CLAVATA3 gene to create a wide range of variations in fruit size and inflorescence branching (Rodriguez-Leal et al., 2017). Second, metabolic engineering through MGE has been an evolutionary approach to modulate the metabolism of the organisms to produce the required amounts of the desired metabolite (Lau et al., 2014). Multiplex CRISPR-Cas9 editing has been targeted at three sites in the rice waxy gene, resulting in mutant plants with reduced amylose content (Ma et al., 2015). MGE was employed to modify the carotenoid biosynthetic pathway in tomato using six gRNAs for two targets sites in the SGR1 gene and one each in the genes LCY-E, LCY-B1, and LCY-B2 that led to an increased lycopene content (Li et al., 2018c). Moreover, the tomato genes for instance SSADH, GABA-TP1, GABA-TP2, GABA-TP3, and CAT9 involved in the GABA shunt metabolic pathway were edited using six gRNAs exhibited increased GABA levels (19-fold) in comparison to the wild-type (Li et al., 2018d). Third, the alteration of the hormone biosynthetic pathways in numerous crops has been accomplished utilizing MGE, such as two simultaneous paralogs (using two distinct gRNAs) of the HvPM19 gene in barley inhibited the gibberellin biosynthesis pathway (Lawrenson et al., 2015). Four paralogs of the rapeseed RGA family were simultaneously knocked out using two gRNAs that resulted in mutants with high levels of gibberellic acid (Yang et al., 2017). Further, the modulation of plant developmental characteristics has been undertaken in several crop plants, for instance, editing the MGE of paralogous genes has been successfully used for the modulation of different seed storage proteins. In sorghum, multiple genes of the KIC family were edited using a single gRNA, resulting in mutant plants with multiple mutations (Li et al., 2018e). The simultaneously edited MAP kinase signaling pathway of rice also been targeted using CRISPR-Cas9 to resolve the functions of the partially redundant genes MPK1, MPK2, MPK5, and MPK6 (two gRNAs for each gene), that led to the generation of double (45%) and quadruple (86%) mutants in the T0 generation (Minkenberg et al., 2017a). An initial report on editing of plant development-related members of the rice FT-like family that were involved in floral regulation via MGE revealed mutations in 10 genes that led to early senescence phenotype (Ma et al., 2015). The CRISPR-Cas-mediated system has been widely utilized for technological interventions in other crops as well. Genome editing is now routinely used to improve crop traits that have an immense impact on the current societal needs and progress, for instance, higher yields, improved nutritional traits, and resistance to biotic/abiotic factors.

4 Approaches in genome editing for crop improvement Introducing targeted genomic modifications has rendered the CRISPR-Cas9 system ingenuously useful for trait improvement in crops. In general, three different genome editing approaches may be employed for incorporating targeted mutations in the genomes of crops: (i) gain- or loss-of-function mutations, (ii) regulation of gene transcription, and (iii) modulation of gene expression at the posttranscriptional/translational level.

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(i) Gain- or loss-of-function mutations: Genome editing by the CRISPR-Cas-mediated system has been employed to unravel gene functions via the generation of gain- or loss-of-function mutations to significantly improve agronomical traits. This approach circumnavigates those genes that negatively influence the desired agronomical traits (Li et al., 2016). Modifications in the genome may be achieved either via frame-shift mutations, amino acid substitutions, and/or screening functional sites in a protein domain. In frameshift mutations, InDels are generated by ZFNs/TALENs/Cas9 due to the loss of functional alleles. Due to this approach’s simple and robust nature, InDels generated by it have emerged as a unique tool to study the functions of uncharacterized genes in crops (Chen et al., 2018). Amino acid substitutions can create partial gainor loss-of-function alleles via a base-editing approach. Functional sites within well-characterized proteins may be targeted by base editors (ABE, CBE) to introduce specific amino acid changes for the generation of gain- or loss-of-function alleles (Nishida et al., 2016; Shimatani et al., 2017; Zhong et al., 2018; Li et al., 2018a). In order to characterize unknown proteins, key functional residues were identified by functional screening through the transformation of pooled libraries comprising of a tiling array of sgRNAs, via either base editors or Cas9-based editing. The complete coding region of any targeted gene of interest may be covered by designing overlapping sgRNA tilling arrays, then further pooled for vector construction and plant transformation for screening of beneficial alleles (Wang et al., 2018a; Hua et al., 2019). (ii) Regulation at the gene transcriptional level: Genome editing tools can facilitate the regulation of gene expression via gene disruption or gene modification genome editing tools that can aid in regulating the expression of genes. Population genetics and genome analysis fostered the identification and validation of genes linked to beneficial agronomic traits and provided insights into the extent of natural variations in their promoter regions. The gene expression levels or patterns were strongly regulated by the variations in their promoter regions. Hence, the promoter regions of genes of interest may be earmarked as prospective target sites for CRISPR-Cas-mediated genome modification. Random disruptions introduced in the cis-regulatory elements regulated the expression of the gene of interest in a dose-dependent manner (Birchler, 2017). In addition to random mutations, the targeted disruption of the cis-elements within promoter regions that enact as transcription factor binding sites has emerged as an innovative strategy for the regulation of gene expression at the transcriptional level (Lescot et al., 2002). This may be implemented via a targeted approach employing base-editing tools to specifically substitute key nucleotides, which ultimately increased or decreased the binding efficiency of the transcription factors (Chen et al., 2018; Hua et al., 2019). Random insertions that were introduced during the NHEJ pathway and targeted insertions facilitated via the HDR repair pathway may influence or alter the promoter activity that in turn regulates expression levels (Li et al., 2019). The insertion of a transposon element within promoters or upstream of the promoter regions may impact the epigenetic status of the gene. dCas9-based epigenome editing tools may regulate gene expressions via epigenome modulation. The promoter region can be targeted for methylation and demethylation, and thereby the chromatin status directed the expression in the system. The concept of regulating the epigenetic state of the promoters for the regulation of gene expression is still elusive in crop breeding systems, as it has to deal with constraints such as the stability and heritability of the epigenetic markers in the consecutive generations (Hilton, 2015; Liu, 2016; Dominguezet et al., 2016; Hua et al., 2019). However, recently epigenetic modifications have been employed using a dCas9-Suntag fusion protein that is suitable for human DNA demethylase Tet1 and the Nicotiana tabacum DNA methylase DRM2 to demethylate and methylate, respectively, the targeted DNA (Gallego-Bartolome et al., 2018; Papikian et al., 2019). Apart from targeting the promoter region, the gene expression can be regulated via spatiotemporal targeting. In this strategy, the dCas9 gene can be fused with a repressor such as the Kruppel-associated box (KRAB) (Lawhorn et al., 2014; Tang et al., 2017a; Li et al., 2017a) or an activator such as VP16 or VP64 (Gilbert et al., 2013), thereby ensuing inhibition (CRISPRi) or activation (CRISPRa) of gene expression, respectively. (iii) Modulation of gene expression at the posttranscriptional/translational level: The agronomically important traits can be regulated at the posttranscriptional level. By far, microRNAs (miRNAs) are the short noncoding RNAs that regulate gene expression at the posttranscriptional level via cleavage or translational inhibition of the coding mRNA. The expression of the gene can be fine-tuned by disrupting the miRNA-mRNA binding. For that, a point mutation can be introduced in the miRNA binding site of the target gene without disruption of the protein amino acid sequence. In plants, the number and position of the mismatches in the miRNA-mRNA pair, influence the efficiency of miRNA-targeted degradation of the mRNA employing both CBEs and ABEs; thereby facilitating posttranscriptional gene expression (Hua et al., 2019). Alternatively, spliced mRNA forms known to regulate some important agronomical traits may lead to the induction of alternatively spliced forms of the mRNA effectuated through base editing tools. These tools can alter the intron donor (GT) or acceptor (AG) sites and by doing so, they can affect mRNA splicing (Li et al., 2018b). Conjointly, the genome editing tools play a crucial role in the regulation of gene expression at the translational level. Many plant transcripts harbor upstream open reading frames (uORFs) in combination with the standard open reading frame. CRISPR-Cas9-mediated disruption of the uORF translation via the introduction of mutations in the initiation codon of the uORF, subsequently, led to increased translation of the protein downstream of the standard open reading frame (Zhang et al., 2018). Additionally, the

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introduction of an NHEJ- or HDR-mediated translational enhancer in the 50 UTR may enhance the target gene expression (Hua et al., 2019), though this is not employed in crop plants yet. Promising novel applications of the CRISPR-Casmediated genome modification tools have led to the expansion of avenues for designing numerous strategies to develop the desired agronomically important traits in crops of interest.

5 Strategies for reducing off-target effects of the CRISPR-Cas system Despite the many advantages of the CRISPR-Cas-based genome modification system, there are some challenges as well. One of the potential factors that researchers need to address is the off-target effects in the postgenome. Off-targeting is an important issue in the case of the CRISPR-Cas system in plants. Off-target phenomena generate undesired mutations at random sites, thus impacting precise gene modification. Sometimes, these off-target effects might be beneficial to bacteria and archaea. Cas9 itself does not cause off-target effects; they exist solely due to the choice of sgRNA (Cho et al., 2014). There are numerous strategies that could minimize off-targeting, including the use of natural (Cas12a) or engineered Cas9 variants (e.g., eSpCas9, SpCas9-HF). Engineered CRISPR-Cas endonucleases exhibited higher editing efficiencies in comparison to wild-type SpCas9. CRISPR-Cas endonucleases that recognized longer PAMs (SaCas9) and specific DNA sites are expected to be more precise in cleaving and editing plant genomes, thereby reducing off-target effects. It was reported that these CRISPR-Cas versions worked with differential efficiencies in various crops, for instance, rice, Arabidopsis and maize (Tang et al., 2017b; Wolter et al., 2018; Lee et al., 2019). The specificity and efficiency of any CRISPR-Cas system may be affected by diverse aspects, for instance, target site selection and sgRNA design, the incidence or rate of homologydirected repair (HDR), the delivery methods, Cas9 inactivity due to anti-CRISPR proteins, and so on. These have been briefly described in the following sections.

5.1 Modulating Cas9 activity Several Cas9 proteins identified from different species, including Staphylococcus aureus (SaCas9) (Ran et al., 2013), Neisseria meningitidis (NmCas9) (Hou et al., 2013), and Streptococcus thermophilus (St1Cas9) (Kleinstiver et al., 2015), have been utilized for genome editing. Each of these Cas9 variants recognized different PAM sequences and possessed variable activities. Therefore, the optimal choice of a specific Cas9 ortholog may lead to improved gene editing efficiency for a given target sequence. However, other factors also influence the efficacy of Cas9 activity. In the eukaryotic system, Cas9 must be translocated in the nucleus. The insertion of a 32 amino acid spacer sequence between the Cas9 and NLS led to DNA cleavage activity (Shen et al., 2013). Additionally, incrementing the relative concentration of sgRNA to the Cas9 protein also led to increased on-target cutting activity. Further, reports revealed that the use of excessive sgRNA enhanced off-target effects (Fu et al., 2013).

5.2 Optimization of sgRNA design The selections of specific target sequences and target recognition sites (PAM) are the two most important factors for reducing CRISPR-Cas off-targeting (Doench et al., 2016). One of the crucial advantages of the CRISPR-Cas9 system is the ability to target any 23-bp sequence that contains a PAM motif on either strand of DNA. The PAM sequences reoccurred at every eight base pairs, approximately, in the case of SpCas9 (Ramakrishna et al., 2014). Numerous types of Cas proteins that recognized different PAM sequences have been identified. For instance, the PAM for N. meningitidis Cas9 has been reported to be 50 -NNNNGATT-30 (Ma et al., 2014). This newly identified Cas9 protein with a novel PAM sequence provided greater flexibility in target selection and cleavage. Additionally, Cas9 variants with altered PAM sequences resulted in higher genome editing efficiencies due to a directed progressive evolutionary process and structure-guided rational design (Doench et al., 2014; Anders et al., 2016; Hirano et al., 2016; Hu et al., 2018). The SpCas9 variants EQR, VGR, and VRER recognized different PAM sequences such as 50 -NGAG-30 ,50 -NGAN-30 , and 50 -NGCG-30 , respectively. However, target site selection and sgRNA design are not as simple as perhaps originally assumed (Anob et al., 2019; Cerma et al., 2017). It was reported that the CRISPR-Cas9 system showed lower genome editing efficiency than ZFNs or TALENs due to the presence of a relatively shorter targeting sequence (Cradick et al., 2013; Nishimasu et al., 2019). Concomitantly, the detectable off-target cleavage by CRISPR-Cas9 editing is only gRNA-dependent (Fu et al., 2013). In the case of polyploid species such as wheat, CRISPR-Cas off-targeting may be advantageous if targeting all three homoeologs with the same sgRNA (Liang et al., 2017). To date, a huge number of software and computational tools are available to facilitate rational sgRNA designing.

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5.3 Cas9 and Cpf1 variants Cas9 variants with the promising potentiality to broaden the target range and specificity are crucial for genome editing in organisms, including crop plants. Recently engineered, high-fidelity xCas9 and Cas9-NG that recognized (noncanonical PAM targeting) sites are two such important SpCas9 variants with improved on-target Cas9 activities. The xCas9 variant showed a similar editing efficiency as the wild-type Cas9 at most of the canonical PAM (NGG) sites, whereas it showed limited activity at noncanonical NGH (H ¼ A, C, T) PAM sites. The cytidine deaminase base editing system (C to T) in combination with xCas9 demonstrated improved editing efficiency at canonical PAM (NGG) sites. Contrastingly, Cas9-NG variants showed higher editing efficiency than xCas9 variants at most noncanonical AT-rich PAM sites such as GAT, GAA, and CAA. Nevertheless, Cas9-NG variants have significantly reduced activity at the canonical PAM sites (Ren et al., 2019; Hua et al., 2019; Zhong et al., 2019). On the other hand, noncanonical NGCG, NG, and NGA PAMs expanded the targetable range of adenosine base editing ( Jeong et al., 2019). Besides, mutations that employed both xCas9 and Cas9-NG resulted in engineered SpCas9 (XNG-Cas9), which significantly mutagenized endogenous target sites with GAA, NG, GAG, and GAT PAMs in the Arabidopsis or tomato genomes (Nishimasu et al., 2019). Previously identified AsCpf1 (BV3L6) and LbCpf1 (ND2006) exhibited limited availability of suitable target sites, which reduced the practical utility of Cpf1. Cpf1 has a specific requirement of a PAM (TTTV) in its DNA substrate, where V can be A, C, or G. Two engineered AsCpf1 variants that harbor the mutations S542R/K548V/N552R and S542R/K607R recognized the TATV and TYCV PAMs, respectively, which increased their target specificity by the alleviation of offtarget effects. Moreover, introducing an additional non-PAM-interacting mutation led to a further increase in efficiency. Similarly, the LbCpf1 variant also showed increased target specificity by altering its PAM (Gao et al., 2017). Efficient plant genome editing may be effectuated by empowered Cpf1 systems with altered, short, and more relaxed PAMs (TTV), as in the case of FnCpf1 (Zetsche et al., 2015). A recent report showed two FnCpf1 variants, FnCpf1-RVR and FnCpf1-RR, that recognized canonical PAM and revealed higher target specificity than their previous version (FnCpf1) in rice protoplast (Zhong et al., 2018).

5.4 DNA-free genome editing/Cas9 protein RNP complexes in vitro The direct delivery of CRISPR-Cas9 ribonucleoprotein complexes (RNPs) into plant cells also can reduce off-target mutations. Efficient single-cell regeneration is a major achievement in plant biotechnology (Svitashev et al., 2016; Liang et al., 2017; Anderson et al., 2017). The CRISPR-Cas9 RNP method involved the delivery of preassembled ribonucleoprotein complexes of Cas9 and in vitro transcribed sgRNA into host cells. It is a robust and efficient DNA-free genome editing technique. Recently, efforts have been made to deliver CRISPR-Cas9 in RNP form into the protoplasts of lettuce and tobacco, which revealed subsequent genome editing and regeneration from single protoplast cells (Woo et al., 2015; Lee et al., 2018a). A CRISPR/Cpf1 RNP editing method has been recently developed for soybeans and wild tobacco protoplasts (Kim et al., 2017a). Regeneration from protoplasts is tedious and quite inefficient in most plant species. Thus, the application of this technology and its potentiality to produce foreign-DNA-free edited plants may be limited to few crop plants. Recently, it was reported that RNPs could be delivered into wheat embryos and zygotes in rice rather than into protoplasts to obtain edited mutants (Toda et al., 2019; Liang et al., 2019).

5.5 Enhancing HDR pathway efficiency by reducing the NHEJ pathway The incidences of HDR-mediated DNA repair of DSBs are extremely low in comparison to the error-prone and inaccurate NHEJ DNA repair pathway. Incidentally, NHEJ is the more frequent repair mechanism observed after the creation of CRISPR-Cas-mediated DSBs, even in the presence of sufficient donor template DNA (Maruyama et al., 2015). However, several approaches have been experimented with to suppress the frequency of the NHEJ pathway and in turn enhance HDR efficiency, including the use of cell lines deficient in NHEJ components (Weinstock and Jasin, 2006), cell cycle synchronization (Lin et al., 2014), the use of small molecular inhibitors of the NHEJ pathway (Vartak and Raghavan, 2015; Yu et al., 2015), and gene silencing (Chu et al., 2015). The CRISPR-Cas-mediated DSB repair efficiency via the HDR pathway was enhanced 19-fold with the use of inhibitor Scr7 that targeted the NHEJ pathway enzyme DNA ligase IV (Srivastava et al., 2012; Chu et al., 2015; Vartak and Raghavan, 2015). However, these Sc7 inhibitors increased the gene-editing efficiency but produced toxic substances in the host cells. During synchronization of a cell in the late S and G2 phase, HDR activity is restricted and NHEJ is active. In this condition, direct nucleofection of the Cas9 ribonuclease complex along with HDR proved a feasible alternative to the chemical suppression of NHEJ (Lin et al., 2014). DN1S,

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a dominant-negative mutant of 53BP1, when fused to Cas9 resulted in a Cas9-DN1S fusion protein that tremendously improved the HDR frequency by blocking the NHEJ events, specifically at Cas9 cleavage sites ( Jayavaradhan et al., 2019).

5.6 High-throughput screening of plant mutant libraries CRISPR-Cas9 systems are potent tools for genome-wide screening (GWS), which offers an ingenious gene discovery platform due to the ease of designing the guide and the precise editing of the Cas9-sgRNA complex for the generation of KOs of the target gene expression of target genes (Sharma and Petsalaki, 2018). In CRISPR and GWS systems, it could be possible to design sgRNA for the whole genome, then subsequently clone the sgRNA into plant transformation vectors to form libraries. To identify desirable phenotypes such as biotic and abiotic stress tolerance, disease resistance, nutritional enhancement, and other traits, screening could be performed from the expressed progeny. Once edited plants are established, deep phenotyping and genotype screening are quintessential for the identification of novel traits and their genetic composition. Previously, the whole process was time-consuming, whereby consistent and persistent mapping efforts were a prerequisite that wasn’t a viable approach for many crops cultivated for food security. With the advent of CRISPR technology, the breeder’s toolbox would be upgraded toward yield enhancement as well as the improvement and introduction of desired agronomic traits in crops. Thus, applying CRISPR-Cas9 gene-editing technology in congruence with nextgeneration sequencing (NGS) offers an innovative approach for crop trait improvement.

5.7 Chimeric fusion of catalytic domains To overcome the major limitation of the CRISPR-Cas system, off-targeting, scientists have fused the catalytically inactive Cas9 (dCas9) to the dimerization-dependent nuclease domain (FokI) to develop a robust, efficient, and specific genome editing system. The fusion protein fCas9 cleaved the DNA more specifically and efficiently with similarity to the paired Cas9 nickases. The specificity toward the target was enhanced as cleavage required the association of two fCas9 monomers, which cleaved the DNA. The association of two monomers increased the sequence length required for the recognition of the target. This modification ultimately led to140-fold higher specificity in comparison to the wild-type Cas9 (Guilinger et al., 2014) and fourfold higher than the nickase. Although this system may increase the specificity, there is a restriction in overall targetable sequence space as the two targeted Cas9 compatible sequences are just 15–25 nt apart (Ribeiro et al., 2018). Further, to improve the binding precision and cleaving specificity of the Cas9, a DNA binding domain, either ZFP or a TALE, was fused with engineered Cas9 harboring a mutation in the key PAM interacting residues to reduce the DNA-binding affinity. A Cas9-ZFP end-to-end fusion protein decreased off-target cleavage and also reduced the size of the engineered protein so that any efficient delivery system can be utilized (Bolukbasi et al., 2015). Similarly, a Cas9-Cas9 (single- and dual-nuclease formats) fusion protein widened the target range for improved genome editing efficiency (Bolukbasi et al., 2018). Alternatively, to diminish the off-target activity, the SpCas9 was fused to the structurally unstable protein domain, dihydrofolate reductase (DHFR), or the estrogen receptor (ER50) (Maji et al., 2017), which targeted the fusion protein toward the rapid proteasomal degradation (Gautam et al., 2012). Switchable systems can be created by the fusion of DHFR or ER50 to both the N- and C-termini of SpCas9. These fusion proteins can only bind to the target DNA in the presence of trimethoprim (TMP) or 4-hydroxytamoxifen (4-HT), which is a small stabilizing molecule that stabilized DHFR and ER50, respectively, but the endonuclease activity is retained. In the absence of TMP or 4-HT, the fused proteins will be degraded by proteasome degradation (Maji et al., 2017). All these approaches demonstrated that restricting the Cas9 presence to a short and controlled period may limit the off-target activity. These approaches are not yet tried in the plant system but they are very potent in terms of reducing the off-target activity of the well-established CRISPR-Cas9 system.

5.8 Employing anti-CRISPR protein activities The inactivity of the CRISPR-Cas9 system by the anti-CRISPR (Acr) protein represents natural “off switches” that directly disarmed CRISPR-Cas systems. The first identified Acrs were active against Type I-E and I-F systems in phages that successfully infected Pseudomonas aeruginosa in the presence of the active type I CRISPR-Cas system and the matching CRISPR spacer (Bondy-Denomy et al., 2013). Subsequently, numerous Acr proteins were identified against Type II-C, Type II-A, Type I-D, Type I-C, and Type V CRISPR-Cas systems (Rauch et al., 2017; Lee et al., 2018b; Marino et al., 2018; Watters et al., 2018). As of now, three families of Type II-C Acrs (Pawluk et al., 2016a) and six families of Type II-A Acrs (Hynes et al., 2017, 2018) have been reported. The most commonly used SpCas9 inhibited by AcrIIA4Lmo (Type II-A)

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prevented Cas9-DNA binding by occupying the PAM-interacting domain (PID) and masking the RuvC nuclease domain, in part via DNA mimicry (Dong et al., 2017; Shin et al., 2017; Yang and Patel, 2017). Recently identified AcrIIC1, AcrIIC2, and AcrIIC3 proteins inhibited NmeCas9 (Neisseria meningitides) activity and another five Acr proteins (AcrIIA1–AcrIIA5) targeted different orthologs of Type IIA Cas9 (Zhu et al., 2019). Recently discovered Type V and Type II Acrs showed potential inhibition control over Cas9 and Cas12a-based applications. Anti-CRISPR protein sequences and their functional mechanisms vary widely and potentially interrupt CRISPR-Cas system functioning, for instance, crRNA processing, crRNA assembly, spacer acquisition, expression of Cas proteins, target DNA binding, and target DNA cleavage (Marino et al., 2018). On the other hand, 16 of the Type I Acr families are frequently encoded adjacent to putative transcriptional regulator genes but do not share common structural similarities or sequences known as anti-CRISPR-associated (aca) genes (Pawluk et al., 2018; Marino et al., 2018). Genes encoding Aca proteins are frequently associated with anti-CRISPR genes, and their conservation implies that they fulfill an important role in Acr function. To date, the potential function of Aca proteins is unclear. It was recently reported that Aca2 acts as an autoregulator that represses the anti-CRISPR-aca2 operon, which is encoded by the Pectobacterium carotovorum temperate phage (ZF40). Helix-turn helix domain protein Aca2 forms a homodimer, preventing DNA binding by interacting with two inverted repeats in the anti-CRISPR promoter. So it was demonstrated that the autoregulator Aca2 mediates antiCRISPR repression (Pawluk et al., 2016b; Birkholz et al., 2019).

5.9 CRISPR-Cas9 mediated antiviral breeding approaches Globally, plant viruses have led to an immense reduction in agricultural productivity. The CRISPR-Cas system provides a defense mechanism that cleaves both DNA and RNA viruses and thereby renders plants virus-resistant. Single-stranded DNA viruses such as geminivirus require a double-stranded intermediate, necessary for rolling-circle replication. Stable overexpression of Cas9-sgRNAs that specifically targets the geminivirus genome via inhibition of its replication offers viable antiviral crop breeding approaches. However, InDels developed by the NHEJ pathway that are created at DSB sites facilitated the generation of virus variants that can escape Cas9/gRNA cleavage. As the stem-loop intergenic sequence is a prerequisite for geminivirus replication, these emerged as ideal targets for the creation of geminivirus-resistant plants. FnCas9 also adequately suppressed the replication of the tobacco mosaic virus (TMV) and cucumber mosaic virus (CMV) in plants. Unlike most Cas proteins, Cas13a (C2c2) cleaved single-stranded RNA and interfered with turnip mosaic virus (TuMV) replication in plants. A limitation of the CRISPR-Cas system is the off-target mutation effect, but employing a viral promoter to drive Cas9 expression decreased off-target effects to an unnoticeable level (Chen et al., 2018).

5.10 Employing differential CRISPR-Cas delivery systems The most widely used systems for the delivery of CRISPR-Cas9 components can be broken down into two major categories: cargo and delivery vehicles. Regarding CRISPR-Cas9 cargoes, mainly three approaches have been reported: (i) mRNA for Cas9 translation alongside a separate guide RNA, (ii) plasmid DNA encoding both the Cas9 protein and the guide RNA, and (iii) the Cas9 protein with guide RNA (ribonucleoprotein complex). The delivery vehicle used for the CRISPR-Cas system will often depend on whether the system is usable in vitro or in vivo as well as which of these three cargos can be packaged, for instance, oligonucleotides and Cas9:sgRNA RNP are negatively charged but the Cas9 protein is positively charged. Additionally, the Cas9-sgRNA complex concentration can be modulated (Sun et al., 2015). The introduction of the Cas9 gene in place of the Cas9 protein makes it difficult to precisely ascertain the number of functional Cas9 units present in the system at any given time point. Vehicles used to deliver the gene-editing system cargo can be classified into three general groups: physical delivery, viral vectors, and nonviral vectors. The most commonly used physical delivery methods are microinjection and electroporation, a gene gun, or a biolistic delivery system (Chen et al., 2016). CRISPR-Cas systems have been profusely applied in both plant and animal systems as they have led to programmable modifications in the genome without any unintended incorporations other than the target site.

6

CRISPR achievements in plants that cater to nutrition

Strengthening nutritional security in addition to feeding the masses has been a single major goal for all plant science researchers. Gene editing approaches such as meganucleases, TALENs, and ZFNs were used only to a limited extent in plants (Table 1) as these technologies are much more labor-intensive. CRISPR-Cas provides the first user-friendly tool for plant biologists as an upgraded approach beyond RNAi and other similar techniques for gene inactivation in plants (Fig. 2). This technology has been implemented in many plant species to enable precise genome editing. The first report

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TABLE 1 Comparison of different plant genome editing tools. Features

Meganucleases

ZFN

TALEN

CRISPR-Cas9

Length of target sequence

14–40

18–24

24–59

20–22

Cleavage module

Nuclease domain

Fok1 nuclease domain

Fok1 nuclease domain

Cas9 protein

Specificity module

Target recognition domain

Zinc finger domain

TALE domain

crRNA

Cleavage efficiency

High

High

High

High with multiplexing capacity

Target recognition efficiency

Low

High

High

High

Off-target effects

Detected

Detected

Detected

Detected

Experimental ease

Complicated procedure; expertise required in protein engineering; redesigning for each new target site required

Complicated procedure; expertise required in protein engineering; redesigning for each new target site required

Relatively easy procedure; redesigning for each new target site required

Easy and quick procedure; redesigning for each new target site required

on the application of the CRISPR-Cas9 system in food crops appeared in 2013 for rice and wheat (Shan et al., 2013). Plant codon-optimized Cas9 containing nuclear localization signals was coexpressed along with sgRNAs to target the OsPDS (phytoene desaturase) gene in rice. This was facilitated by using two sgRNAs with a 15% mutagenesis rate in rice protoplasts. Further, three more rice genes and one wheat gene were mutated using protoplasts, which confirmed the ability of CRISPR-Cas9 to induce homology-directed repair in the OsPDS gene. The contribution by the same group in the following year involved the customization of sgRNAs to ensure the HDR mechanism in rice and wheat (Shan et al., 2014). Similar efforts guaranteed CRISPR-Cas9 to be successfully employed in model plants such as Arabidopsis, sorghum, and tobacco ( Jiang et al., 2013). Comparative gene editing efficiency studies were carried out by Johnson and coworkers in 2015 for editing the same target in Arabidopsis. CRISPR-Cas9, when compared to TALENs for targeted DNA cleavage, revealed a more convenient approach that enabled enhanced precision genome modification to improve food and feeder crops, thereby strengthening food security (Fig. 3). Although initial studies revealed successful genome editing analysis up to the first generation, stable transformation with targeted site analysis in several plant generations was revealed by Feng et al. (2014). Twelve different target sites in seven genes were studied for plants bearing chimeric, biallelic, homozygous, or heterozygous mutations in three generations. Such strong evidence validated the employment of the CRISPR-Cas9 system in crop plants for the production of agronomically improved varieties that can be readily used for field cultivation. Conventional transgenic approaches can now be replaced with the CRISPR-Cas9 approach. Studies have also been undertaken using distinct plant species in addition to popular models and cereal plants (Sugano et al., 2014). Several agriculturally important traits, for instance, resistance to biotic and abiotic stresses, yield, grain quality, male sterility, etc., have been targeted by genome editing (Borisjuk et al., 2019). The first successful experiment of genome editing using the CRISPR-Cas9 system in wheat was the editing of the powdery mildew-resistant gene TaMLO (Shan et al., 2013). Further powdery mildew-resistant wheat lines were developed by concurrent knock out of the three homologs of the wheat TaEDR gene that was enacted as a negative regulator of powdery mildew resistance (Upadhyay et al., 2013). The CRISPR-Cas9 system was also used to edit a wheat homolog of TaCe (ECERIFERUM) for the generation of drought-tolerant wheat lines (Liang et al., 2018). Later on, to enhance grain size and yield, several genes (TaGASR, TaGW, and TaDEP) were edited by the CRISPR-Cas9 system (Zhang et al., 2016). Plants such as Marchantia polymorpha used for land plant evolution studies were successfully targeted via CRISPR-Cas9 for rendering an auxin-resistant phenotype. Interestingly, stable mutant T1 lines were produced by asexual reproduction (Sugano et al., 2014). Recently, it was reported that CRISPR-Cas9 editing of three CRUCIFERIN C (CsCRUC) homoeologues of Camelina sativa changed the seed storage protein profile. The total oil

FIG. 2 Basic strategy to integrate in silico sgRNA design-based computational techniques with plant genome editing with the Cas/sgRNA system. Three main sgRNA design systems postselected of the desired gene for the distinct types of protospacer adjacent motif sequences that are identified for different Cas9 species or variants are depicted. The target sgRNA with the suitable Cas9 variant is to be cloned into a plant binary vector for transformation of the target plant. The putative transformed plants will then be analyzed for the presence of Cas9 and sgRNA and the desired mutation or editing can be screened by PCR/RE analysis and DNA sequencing.

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FIG. 3 Gene editing in primary crops such as rice and wheat that constitute more than 80% of the world’s nutritive index. This illustration shows different approaches that can be incorporated by plant breeders that target yield under normal and drought conditions and result in seeds with a high nutritive quotient.

content of seeds from the KO lines revealed and altered the fatty acid profile with a notably increased relative profusion of all saturated fatty acids (Lyzenga et al., 2019). Strict regulations over genetically modified organisms extended to agronomically important trait-generated plants have hampered their large-scale cultivation, especially in Asia and Europe. Gemini viral replicons have been suggested as delivery vehicles in plants using a replication initiation protein gene (REP) cotransformed with a Cas9/sgRNA construct (Baltes et al., 2014). A higher repair frequency and a nontransformational approach for seeds with desired modifications can be achieved by using virus-based DNA replicons for the delivery of reagents and constructs (Ali et al., 2015). Direct delivery of viruses was initiated in 2015 to demonstrate the efficiency of virus-mediated Cas9/sgRNA delivery (Yin et al., 2015). Recently, foxtail mosaic virus (FoMV)-based viral vectors were developed for virus-induced gene silencing (VIGS), virus-mediated overexpression (VOX), and virus-enabled gene editing (VEdGE) in monocots. These vectors were used for transient gene expression, employing single-guide RNA delivery for Cas9-mediated gene editing in Setaria viridis, maize, and N. benthamiana (Mei et al., 2019). Apart from agronomically important crop trait improvement, the fermentation processes of microorganisms belonging to Lactobacillus spp. also have benefited from genome editing that improved its different functional properties. Genome editing of microorganisms using a CRISPR-Cas system holds huge relevance in the food industry, primarily as probiotics and psychobiotics (Misra and Mohanty, 2017). Moreover, it remarkably enhanced their resistance against several stress conditions (Ismail et al., 2019). CRISPR interference demonstrated the RNA-guided, efficient, stable modulation of transcription via fusion of inactivated dCas9 to effector domains. dCas9 has functional genetic relevance for the regulation of gene expression and may be used as a fusion protein for gRNAs with its activation or repression domain coassisted by a transcription factor (Gilbert et al., 2013). Piatek et al. (2015) modulated the fusion of the dCas9 C-terminus to the EDLL domain while targeting the endogenous PDS gene in N. benthamiana for activation and the SRDX domain for repression. Two years later, Gilbert et al. (2014) determined that the target site for effective CRISPRi should lie between 50 to +300 bp from the transcription start site of a gene. In contrast, the CRISPR activator system modulated the gene expression of more than a 1000-fold range by the expression of a single sgRNA with one binding site (Gilbert et al., 2014). Genome-scale CRISPRi and CRISPRa libraries can be used to understand complex stress-related signaling pathways for functional genomics analysis (Liu et al., 2015b; Wang et al., 2018b). The adaptation of CRISPR has been simplified and made readily available by a wide array of online resources on CRISPR-Cas system tools (Tables 2 and 3) that rendered minimized off-target effects.

7 Foods developed employing CRISPR as a means to revolutionize agriculture New varieties developed from plant breeding focused on the identification of novel traits in one parental plant and later crossed with other plants. The offspring produced had the desired traits along with some undesirable characteristics, which were tracked by the screening of large populations. This form of breeding is time-consuming and labor-intensive. To speed

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TABLE 2 Description of CRISPR-based design tools and genome editing analysis tools. Off-target prevention

PAM

Platform

URL

References

CRISPR-Cas9 gRNA finder

No

NGG

Graphic/online/ web interface

http://spot.colorado. edu/slin/cas9.html

Mali et al. (2013)

Alignmentbased

Guide RNA/ Cas9

Yes

NGG

Perl script/ offline/ command line

http://www. biootools.com

Xie et al. (2014a)

Alignmentbased

CRISPRdirect

Yes

NGG, NRG

Web/online/ graphic interface

www.crispr. dbcls.jp

Naito et al. (2014)

Alignmentbased

CRISPRseek

Yes

NRG, NGG

Offline/ command line/ R package

www.bioconductor. org

Zhu et al. (2014)

Alignmentbased

CCTop

Yes

NGG

Graphic interface/ online/web

www.crispr.cos. uni-heidelberg.de

Stemmer et al. (2015)

Alignmentbased

CRISPR-P

Yes

NGG

Graphic interface/ online/web

www.cbe.hzau. edu.cn/crispr

Lei et al. (2014)

Alignmentbased

CRISPRfinder

No

NGG

Graphic interface/ online/web

www.crispr.u-psud. fr/server

Kurtz (2003)

Alignmentbased

WGE

Yes

NGG

Graphic interface/ online/web

www.sanger.ac.uk/ htgt/wge

Hodgkins et al. (2015)

Alignmentbased

Fly-CRISPR

Yes

NGG

Graphic interface/ online/web

www.tools. flycrispr.molbio. wisc.edu/ targetFinder

Gratz et al. (2014)

Hypothesisdriven

Protospacer Workbench

Yes

NGG

Offline/graphic interface/ MacOS X

www.protospacer. com

MacPherson and Scherf (2015)

Hypothesisdriven

E-CRISP

Yes

NGG

Web/online/ graphic interface

www.e-crisp.org/ E-CRISP/index. html

Hypothesisdriven

CRISPR

Yes

NGG

Web/online/ graphic interface

www.crispr.mit.edu

Hsu et al. (2014)

Hypothesisdriven

CHOPCHOP

Yes

NGG

Web/online/ graphic interface

www.chopchop.rc. fas.harvard.edu

Montague et al. (2014)

Hypothesisdriven

Cas9-design

No

NGG

Web/online/ graphic interface

www.vas9.cbi.pku. edu.cn

Ma et al. (2013)

Hypothesisdriven

CRISPR-ERA

Yes

NGG

Web/online/ graphic interface

www.CRISPR-ERA. stanford.edu

Liu et al. (2015a)

Hypothesisdriven

Cas-designer

Yes

NGG,NRG, NNAGAAW, NNNNGMTT

Web/online/ graphic interface

www.rgenome.net/ cas-designer

Park et al. (2015)

Model type

Tool

Alignmentbased

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TABLE 2 Description of CRISPR-based design tools and genome editing analysis tools.—cont’d Model type

Tool

Off-target prevention

PAM

Platform

URL

References

Learningbased

SSC

No

NGG

Web/online/ graphic interface

www.crispr.dfci. harvard.edu/SSC/

Xu et al. (2015b)

Learningbased

sgRNA scorer

Yes

NGG, NAG, NNAGAAW, NNNNGMTT

Web/online/ graphic interface

www.crispr.med. harvard.edu/ sgRNAScorer

Chari et al. (2015)

Learningbased

CRISPRScan

Yes

NGG

Web/online/ graphic interface

www.crisprscan.org

MorenoMateos et al. (2015)

Learningbased

WU-CRISPR

Yes

NGG

Web/online/ graphic interface

www.crispr.wustl. edu

Wong et al. (2015)

up the process, an alternative, precise, and efficient method was needed (Turcotte et al., 2017). Agriculture, the only source of the nutritive index for the sustenance of life, is largely impacted to an empirical scale with the advent of genome editing. Here, we have focused on the recent advancements that provided a remarkable impact on the fields of plant biotechnology, molecular biology, and breeding. The use of CRISPR-Cas technology in plant biotechnology has shown several examples of valuable products that maintained their availability in several generations and finally benefited consumers (Fig. 4). Some of the approaches undertaken by researchers around the world have been enlisted. (i) Antibrowning mushrooms: Researchers in the United States have engineered antibrowning mushrooms using CRISPR-Cas9 that disabled the browning of white truffles, increased their shelf life, and provided a commercial advantage. This was achieved by disabling a specific enzyme that achieved clearance by the US Department of Agriculture (USDA) for commercial cultivation as it did not contain any insertion of exogenous DNA such as other closely related plant species or prokaryotes (Waltz, 2016). The gene targeted to provide this advantage was achieved by a small deletion in the polyphenol oxidase gene that facilitated the oxidation of the polyphenols when exposed to air, resulting in the unappetizing appearance. (ii) Bananas resistant to streak virus: Breeders have found it significantly challenging to commercialize banana varieties due to the presence of endogenous banana streak virus in the genome of the banana, as it prevented the dissemination of hybrids. This virus self-activated in the presence of heat or drought as viral particles that can spoil plantations. Tripathi et al. (2019) successfully demonstrated the mutagenesis of viral DNA that resulted in switching off the endogenous virus. This approach not only validated a commercial advantage but also provided a promising model for deactivation of other endogenous viral genomes. (iii) Disease-resistant citrus species: The global reduction of citrus production may be largely attributed to the citrus greening disease that has affected the Americas, Africa, and Asia. This disease resulted in the yellowing of leaves, leaf veins, adjacent tissues of a leaf, and the death of twigs that ultimately led to the death of citrus trees, requiring huge monetary investments for survival and maintenance. Some of the gene-modifying strategies have replaced genes or large sections of DNA from other related or closely related plant genomes with failures. By using CRISPR, the genetic code of citrus was rewritten by initiating insertion, deletion, or substitution of its DNA, thereby creating robust varieties of citrus resistant to greening disease without compromising the desired traits that are favored by consumers and producers (Dong and Ronalda, 2019). (iv) Wheat with reduced gluten content: Gluten proteins in wheat are responsible for viscoelastic properties. In approximately 1%–2% of the global population that gets affected by celiac disease, the reactive immune system attacks gluten, resulting in intestinal damage. Such cases have been forced to adopt an expensive gluten-free diet that further reduces their nutritive quality in life. Gene editing has confirmed the removal of CD epitopes with modified α-gliadin features that lead to a depletion in immunogenicity with acceptable dough quality (Sanchez-Leon et al., 2018). These derived food products are expected to be sold to consumers at local grocery stores in America but would remain illegal in Europe due to the absence in conformity with GM regulations ( Jouanin et al., 2018). (v) Pathogen-free Theobroma cacao: The transient application of the CRISPR toolkit in cocoa resulted in increased resistance to Phytophthora tropicalis by targeting the nonexpressor of pathogenesis-related 3 (NPR3) gene that is a

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TABLE 3 Summary of select CRISPR-Cas activity models. Program name

Identifies/ scores targets

Training data used for model

gRNA transcription method

Model features and implementation

Comments

References Chari et al. (2015)

SSFinder

Identifies targets

NA

NA

NA

Does not score activity. Filters targets if the seed regions (12 bp preceding the PAM) are not unique within the input sequence

sgRNA Scorer

Identifies and scores targets

Mutation rates at target sites in HEK293t cells following treatment with CRISPR-Cas9 and gRNAs

In vitro transcription using a U6 promoter

SVM model using the nucleotide composition of the target site

Standalone program

sgRNAcas9

Identifies targets

NA

NA

NA

Does not score activity. Ranks targets based on potential off-targets (detected via alignment with SeqMap)

Xie et al. (2014b)

CRISPRseek (Zhu et al., 2014)

Identifies targets

NA

NA

NA

Does not score activity. Implemented as a bioconductor package for R

Zhu et al. (2014)

WU-CRISPR

Identifies and scores targets

Reanalysis of the data from Doench et al. (2014)

In vitro transcription using a U6 promoter

SVM model using the nucleotide composition of the target site and the sgRNA secondary structure

Employs strict filtering criteria, which results in a majority of potential targets being discarded prior to scoring. Implemented as a standalone program

Wong et al. (2015)

CRISPRscan (MorenoMateos et al., 2015)

Identifies and scores targets

Mutation rates at target sites in zebrafish embryos

In vitro transcription using a T7 promoter

Linear regression model using nucleotide composition of the target site

Implemented as a web app (www. crisprscan.org). Feature weights are also provided in the paper allowing for standalone implementations

MorenoMateos et al. (2015)

Rule Set 1 (Doench et al., 2016)

Scores targets

Enrichment rates of transfected gRNA following selection for changes in expression of cellsurface markers as determined by FACS in human and mouse cells

In vitro transcription using a U6 promoter

Logistic regression model using nucleotide composition of the target site

No implementation is available; however the feature weights are provided in the paper allowing for standalone implementation

Doench et al. (2016)

Azimuth

Identifies and scores targets

Enrichment rates of transfected sgRNAs targeting drug-resistance pathways

In vitro transcription using a U6 promoter

Combined SVM and logistic regression model using the nucleotide

Implemented as a stand-alone program and as a web app (https:// www.microsoft.

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TABLE 3 Summary of select CRISPR-Cas activity models.—cont’d

Program name

Identifies/ scores targets

Training data used for model

gRNA transcription method

following drug challenge in human cells. Also incorporates data from Doench et al. (2014)

TUSCAN (Wilson et al., 2018)

Identifies and scores targets

Reanalysis of the data from Chari et al. (2015)

In vitro transcription using a U6 promoter

Model features and implementation

Comments

composition of the target site and flanking region, the sgRNA secondary structure, and the position of the target site relative to transcription start

com/en-us/ research/project/ crispr/)

Random forest model using the nucleotide composition of the target site and flanking region

Provides both the activity score and general active/ inactive classification. Implemented as a stand-alone program and as a web app (https://www.gt-scan. net/tuscan)

References

Wilson et al. (2018)

suppressor of the defense response. Genome editing technology in cacao used Agrobacterium-mediated transient transformation to introduce CRISPR-Cas9 reagents into cacao leaves and cotyledon cells, which led to the development of pathogen-free cocoa. This approach resulted in a pathogen-free mutagenized phenotype (Fister et al., 2018). (vi) Sweeter strawberries: One of the major constraints for fruit producers is the insufficient shelf life of fruits until consumption. This can be achieved by targeting genes that offer a functional advantage at the ripening stage with any additive nutritional value. The strawberry breeding program at the University of Florida’s Institute of Food and Agricultural Sciences (UF/IFAS) provides direct significance to growers and cultivators in the region by discovering several key genes for disease resistance with a shift to a desirable genetic background that can be stabilized to several generations of the plant by conventional breeding. After the establishment of CRISPR in strawberries, DNA marker-assisted breeding tools can be utilized to track edited genes in subsequent generations (Seonghee et al., 2018). (vii) Rice with low and high amylose content: Rice is one of the most important cereal grains used globally. Glutinous (sticky) rice contains very little or no amylose that is commercially used in the brewing industry. The waxy gene (OsWaxy) encoded granule bound starch synthase enzyme is responsible for amylose synthesis. KO of the waxy gene using CRISPRCas9 technology generated sticky rice containing low amylose (Yunyan et al., 2019). Similarly, the targeted mutagenesis of the starch branching enzyme SBEIIb led to the generation of rice grains containing high amylose (Sun et al., 2017). (viii) Virus-resistant tomato: The most harmful and destructive virus for tomato production is the tomato yellow leaf curl virus (TYLCV), which is a member of the family Begomovirus. Targeting the TYLCV genome with the Cas9-sgRNA complex resulted in a significant reduction of TYLCV disease (Tashkandi et al., 2018). (ix) Lignin-enriched rice: Lignin is a natural polymer providing a potent source of valuable aromatic chemicals that is particularly important for plant cell-wall formation. Breeding approaches that enriched the lignin biomass offer beneficial properties that are required in biorefineries. However, limited information is available for molecular breeding for this trait. Site-directed mutagenesis of the transcriptional repressor OsMYB108 using CRISPR-Cas9-mediated genome editing enriched the p-coumaroylated and tricin lignin units in the cell walls of rice culm (Miyamoto et al., 2019). (x) Soybeans with high oleic acid: The soybean [Glycine max (L.)] is an important legume crop widely grown for its bean. It is a rich source of dietary proteins, vegetable oil, animal feed, and direct human consumption. The high concentration of monounsaturated fatty acids (α-linolenic and linoleic acids) causes oxidative instability in the quality of soybean oil and processed food. The soybean omega-6 desaturase gene GmFAD2 plays a crucial role in the conversion of oleic acid to linoleic acid. Therefore, the targeted mutagenesis of the GmFAD2 gene using the CRISPS/Cas9 technique reduced both linoleic and α-linolenic acids while increasing the accumulation of high oleic acids (Amin et al., 2019).

FIG. 4 The recent advancement in the use of the CRISPR toolkit for commercial varieties that fast-forwards crop breeder programs for domestication. All the crops mentioned in this illustration include commercially viable crops that have profit losses due to inherently present functional genes/proteins and can be exempt from GMO regulations in US soil with a consumer-friendly yield and a producerfriendly commercial advantage.

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(xi) Hairy root disease-resistant cowpea: Cowpea (Vigna unguiculata) is an important nutritious legume crop that is tolerant to low rainfall and low fertilization. Cowpea has an important role in the symbiotic nitrogen fixation process and its SYMRK gene is implicated in nodule formation. Agrobacterium rhizogenes are the main causal agent of hairy root disease present in the nodule of all leguminous crops. The cowpea SYMRK gene was successfully edited using the CRISPR-Cas9 genome editing system and nodule formation was completely inhibited in the mutant, resulting in reduced hairy root disease in the cowpea ( Ji et al., 2019). (xii) Drought-tolerant maize: Increased grain yield under water deficit conditions is much needed by maize farmers globally, especially in Africa and India. Maize ARGOS8 acts as a negative regulator of ethylene responses. The constitutive overexpression of maize ARGOS8 reduced ethylene sensitivity and improved grain yield under low water conditions. CRISPR-Cas9-mediated genome editing enabled the generation of novel ARGOS8 edited maize variants that showed higher grain yield under drought stress conditions (Shi et al., 2017). (xiii) Tetraploid potato: CRISPR-mediated genome editing has been recently employed to mutate the granule bound starch synthase gene (GBSS) in potatoes using U6 promoters ( Johansen et al., 2019). Editing efficiencies that were almost doubled were obtained by the replacement of the Arabidopsis U6 promoter with the use of endogenous U6 promoters. Researchers employed InDel detection amplicon analysis (IDAA) for the simple qualitative and quantitative detection of editing at the cell pool and ex-plant level in the complex potato genome. Such an approach that showed increased editing efficiency at the explant level has emerged as a robust tool for editing desirable traits in polyploid species. (xiv) Virus-resistant and isoflavone-rich soybean: Isoflavonoids have a significant role in plant environment interactions and are predominately distributed in pulses. Recently, the gene editing strategy has shown substantial achievement in the simultaneous targeting of three genes in the soybean isoflavone pathway. This multiplex gene editing system showed enhanced isoflavone content in soybean leaves and seeds, thereby favoring resistance to the soybean mosaic virus (Zhang et al., 2019). (xv) Blight-resistant rice: Bacterial blight (BB) is the most destructive tribulation of cultivated rice worldwide. The five concomitant members (OsSWEET11-15) of putative sucrose or fructose transporters that belonged to the OsSWEET family supported the virulence of Xanthomonas oryzae pv. oryzae (Xoo). This causative organism of bacterial blight of rice employed transcription activator-like effectors (TALEs) to promote the expression of the OsSWEET family of putative sugar transporter genes that in turn conferred disease susceptibility (S) in rice lines. The CRISPR-Cas9-mediated mutations of the TALE binding elements or “EBEs” in the promoters of three susceptible genes, OsSWEET11 (PthXo1), OsSWEET13, and OsSWEET14 (PthXo3/AvrXa7), in cv. Kitaake conferred these rice lines with vigorous and comprehensive resistance against bacterial blight (Oliva et al., 2019; Xu et al., 2019). (xvi) Glyphosate-resistant crops with improved amino acid profiles: Weeds are the most serious biological constraint to crop production. Manual weed control over large areas is not feasible from the point of labor supply and monetary costs. There is an urgent need to develop crop plants simultaneously resistant to more than one herbicide with a different mode of action to effectively control weed infestation by pre- as well as postemergent herbicide application. The CRISPR-Casbased engineering of herbicide-resistant crop plants allows the application of nonselective herbicides to virtually kill all kinds of weeds without injuring the crop plant. The Nutritional Improvement of Crops Group in ICGEB has accomplished the efficient genome modification of the PEP-binding target site of EPSPS [5-enolpyruvylshikimate-3-phosphate (EPSP) synthase] and ALS (acetolactate synthase) genes in maize, rice, and pigeonpea by CRISPR-Cas9 via knock-out and HDR-mediated knock-in to confer resistance to herbicides and develop subgenic crop plants tolerant to nonselective herbicides. These edited lines of maize and rice revealed a significantly enhanced aromatic amino acid profiles in comparison to the wild-type. The technology may be extrapolated to other crops, for instance, wheat, soybeans, onions, and other crops that face weed constraints. (xvii) Next-generation waxy maize hybrids: The waxy maize generated by Corteva Agrisciences (Agricultural Division of DowDupont), which is a flagship case of SDN-1/NHEJ developed via CRISPR-Cas9 genome editing, revealed a 30 bp deletion at the exon/intron boundary that produced a frameshift or null allele in the wx1 gene. The phenotypic characterization of the starch from these CRISPR waxy maize seeds was indistinguishable from the starch derived from the conventional waxy seeds. Moreover, these CRISPR waxy maize hybrids outyielded their conventional hybrids and revealed significantly higher content of amylopectin in their seeds.

8 Inclusion of GWAS into the CRISPR domain for additive nutrition Genomic information establishes the link between the multitude of phenotypes and marker information of plant populations. The genome-based markers provided an estimation of all the loci and predicted the genetic values of untested

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populations to achieve reliable and comprehensive information that accelerated the progress of plant breeding and other phenotypic observations. The purpose of genome-wide association studies (GWAS) is the establishment of marker alleles associated with a quantitative trait. Following this with statistical data that usually involved linear models may supplement the marker effect of the target phenotype and other effects, for instance, nutritional enhancement, effects related to biotic and abiotic stress tolerance, and so on. Significant criteria incorporated in numerous tests determined false positives and the associated markers identified may be employed for marker-assisted selection. As said earlier, genomic selection facilitated the prediction of the breeding value of a trait, based on the marker set that was characterized for a particular genotype and phenotype, thereby acting as the “training population.” The genomic selection model anticipated the phenotypic values of individuals, whereas GWAS panels helped to uncover the genetic diversity of a species that can lead to the most accurate predictions for breeding. The information gathered from GWAS analysis facilitated the identification of markers that could bring about a strong influence on the populations of individuals either unrelated or diverse. For complex traits that come under the banner of a stabilization selection, a large number of mutations may be accumulated at many loci. Domestication bottlenecks were not just reductions in population structure and size, but they were typically connected with phenotypic evolution. Domestication generally involved strong novel selection, which operated on suites of traits, varying selection coefficients in terms of magnitude and direction. For instance, rare alleles that resulted in softer seed coats could be deleterious in the wild but would be favored in domesticated crops. When rare alleles are vigorously selected, their fixation reduces variation at the selected locus and other proximally linked loci. On the other hand, for various crops, the impact of the domestication bottleneck had been the elimination of various unique or rare alleles that pushed average allele frequencies in the direction of intermediate values. Second, the human GWAS majorly endeavored to discover QTLs for complicated diseases, depended upon mutation-selection balance and resulted in genetic variance due to deleterious alleles segregating at low frequencies. Although there is a huge scope of genetic architectures (i.e., the number and effect size distribution of QTLs) for important agronomic traits, which have been under directional selection. Subsequently, in any event, when the QTL number was extremely huge and effective sizes were small, variation for these traits was not likely to be commanded by slightly deleterious alleles. This is pivotal because it suggested that QTLs in plants were more likely to be segregated at frequencies more similar to the frequencies of the marker alleles used to recognize them. For a targeted approach, this information can be documented by using CRISPR machinery to study the local adaptation that caused the genetic differentiation of traits such as diverse environmental adaptation or flowering time.

9

Value rendered by CRISPR toward the promotion of food security

Conservation and the sustainable utilization of biodiversity to develop food and agriculture play a critical role in the fight against hunger via ensuing environmental sustainability. At the same time, they potentially increase food and agriculture production. Although serious attention has been given to biodiversity, the declined sustenance of species that bore the weight of food security and economic growth has left rural incomes and nutrition at risk. Ensuring a healthy diet confirmed a necessity for the development of biofortified fruits, vegetables, and cereals with enriched nutrition by enhancing compounds such as essential amino acids, minerals, fatty acids, and antioxidants. Current strategies for the biofortification of crops include conventional breeding, mineral fertilization, and transgenic approaches. Recent research has been directed toward the great prospects of the CRISPR-Cas9 system for conferring plant immunity, as it can be utilized to target several sites of viral genomes and alternatively different viruses in the same plant simultaneously. Variations have been observed when it comes to the optimization of various Cas9 proteins put to action in CRISPR systems. Some research groups have utilized and displayed plant-codon optimized versions of Cas9 whereas a few described the use of the CRISPR-Cas9 system in plants using a human codon-optimized version as well. In plants, various promoters have been utilized to drive the expression of Cas9, among which ubiquitin and cauliflower mosaic virus 35S promoters have been the most commonly used CRISPR-Cas9 technology that has the potential to be utilized for breeding in crops by the formation of novel allelic variants. A similar CRISPR-based approach to enhance the content of indispensable micronutrients such as iron and zinc in the grains of rice and wheat is presently under way in our Nutritional Improvement of Crops laboratory. The ever-deteriorating ratio of species and varieties used in agriculture further hampers the farmer in adapting to opportunities, needs, new environments, and changes in the ecosystem. In the present day and age, 30 crops cater to 95% of the human energy needs, among which wheat, potato, maize, and rice are responsible for more than 60% of the energy. This dependency on a few crops for food security demands crucial efforts to balance high genetic diversity, agronomic profits, and environmental stresses related to the breeding of crops. A detailed pluralistic overview of the benefits rendered by CRISPR-Cas proteins such as Cas9, Cas12, and Cas13 has been compiled for fruit crops, wheat, rice, and maize (Kaul et al., 2019a,b).

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Several underutilized crops have been recognized for low input in agriculture that can be tapped for high mineral and vitamin content. Such species can provide huge benefits for the well-being of the poor. Whether the species are cultivated, managed, or wild should not be contentious as this directly impacts child, maternal, familial, and world nutrition. CRISPR tool may be employed to modify orphan or underutilized crop genomes to occupy important niches and adapt to the risky and fragile conditions in rural areas, thereby conserving their traditional landscapes and facilitating cost-effective survival and sustenance of rural communities. Classic examples of underutilized crops include sago palm and the Vigna species. The sago palm has been recognized as a typical underutilized indigenous food crop in Pacific and Asian countries that can be grown in peat swamps and wetlands. This plant provides an advantage over other food crops as 150–300 kg dry starch/plant was produced under environmental conditions where other food crops cannot be grown. Sago starch, if mixed with 60% wheat flour, can contribute to end products such as bread and noodles with no olfactory compromise and increased edible starch content. Such varieties have drastically decreased in the recent past due to the use of wetlands and swamps for the expansion of industrially and commercially important crops such as rubber and oil palm. A roadway to perform genetic engineering includes the identification of the target gene and its related pathway (by a combination of genome sequencing, bioinformatics tools, and analysis of the metabolome, proteome, and transcriptome); the development of vectors to prepare constructs (by the selection of a suitable vector, suitable promotor, and screening of selectable markers); the transformation and screening of the transgenic plant (delivery of the gene of interest, tissue culturebased confirmation of transgenic lines, and screening of transformed plants); and the phenotypic (morphological data), genotypic (transcriptome data), and biochemical evaluation of transgenic lines for improved quality. From the beginning of the 21st century, the role played by genetic engineering tools such as RNAi, ZFNs, TALENs, and CRISPR continues to be investigated as a means to reveal the understanding of mechanisms involved and different biochemical approaches for biogenesis. Crops or plant species grouped under the underutilized category are now fading due to the ignorance of their potential uses as fodder, fiber, food, oil, and/or medicine. Further, this group largely deals with food-related crops and plant species (Table 4, adapted from Raman et al., 2019). These food systems have also been largely associated with traditional food culture, food variety, and locally available food. A concerted effort by interlinking public policy, multisectoral support, flagship research programs, and community-based strategies that integrate urban consumers and rural producers is mandatory. Crop plants with great potential include pseudocereals (Amaranthus, buckwheat, and chenopods), millets (finger millet, proso millet, foxtail millet, and Kodo millet), grain legumes (rice bean, adzuki bean, faba bean, moth bean, and horse gram), tubers (taro, giant taro, greater yam elephant foot yam), vegetables (hyacinth bean, sweet gourd, Cho-Cho, horseradish tree, kang kong, and garden cress), and fruits (breadfruit, longan, durian, rambutan, mangosteen, carambola, sea buckthorn). Crops such as Vigna umbellata (rice bean) and Amaranthus sp. of grain amaranths possess exceptionally high food and nutritional value, including a higher amount of minerals and essential amino acids compared to many cultivated crops. Moreover, they are extremely useful in alleviating malnutrition, which is so widely prevalent. The Nutritional Improvement of Crops at ICGEB has pioneered whole genome sequencing and transcriptome analyses for the rice bean to facilitate the trait improvement of this underutilized crop (Kaul et al., 2019a,b). The manifold benefits of these species that can be tapped by CRISPR include: (i) environmental adaptation with contribution to stable agroecosystems, (ii) nutrient and micronutrient source for low-income groups, (iii) significant contributions to poverty alleviation and rendering a sustainable livelihood by generating income, (iv) catering to new market demands, and (v) acting as a source for secondary agriculture and the generation of value addition.

10 Technological influx and CRISPR-Cas technology The tools available for designing sgRNA for on-target efficacy may be categorized into three types (Table 2): (i) alignmentbased, where sgRNAs are aligned from the given genome upstream of PAM; (ii) hypothesis-driven, where the sgRNAs would be aligned and scored for the GC content and exon position for on-target efficacy, and (iii) learning-based, where the prediction and scoring of sgRNAs are carried out via trained models by considering different features that affect their efficacy. Hypothesis-driven and learning-based tools are expected to perform better as they have been based on different chromatin and sequence features, a prerequirement of the machine learning model. As detailed in Table 2, a different set of tools is suitable for different design scenarios, for instance, multiple PAM patterns other than a conventional NGG sequence, efficient sgRNA design with optimal prediction performance, and a logistic regression model with updated design on the original version. Although these tools have been validated under laboratory conditions using human and mouse cell lines or both, large-scale and multiple-species-based adaptations are yet to be validated. However, these tools can be preselected for preliminary analysis when genome-editing experimentation would be performed on corresponding species, as the on-target and sgRNA-predicting efficacy in different cell types is not clear. To facilitate this, an Excel-based

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TABLE 4 CRISPR-Cas9-mediated improvement in quality, yield, herbicide, pathogen, and stress traits in select plant species. Species

Gene of target

Trait/quality improved

References

Rice

OsIPA1

Number of tillers

Li et al. (2016)

OsGS3

Grain size and higher yield

OsDEP1

Dense and erect panicles

OsGn1a

Grain number

OsGW2

Grain weight and higher yield

Xu et al. (2016)

OsHD2

Early heading and maturity

Li et al. (2017c)

OsSWEET11

Grain filling and sugar transport

Ma et al. (2017)

OsSBEI, OsSBEIIb

Amylose-resistant starch

Sun et al. (2017)

OsERF922

Resistance to Magnaporthe oryzae

Wang et al. (2016)

OsEPSPS

Glyphosate tolerance

Jung et al. (2018)

OsSAPK2

Drought, osmotic, salinity tolerance; stomata and ABA signaling

Lou et al. (2017)

OsALS

Bispyribac sodium resistance

Butt et al. (2017)

OsMPK1, 2

Biotic/abiotic signaling

Khatodia et al. (2016)

SlSP5g

Early flowering and yield

Karkute et al. (2017)

SlJ2

Less fruit dropping and jointless fruit stem

Soyk et al. (2016)

SIEJ2

Higher yield with larger fruit

SlSP5G

Improves inflorescence architecture and fruit yield

SlMlo

Resistance to Podosphaera xanthii

Nekrasov et al. (2017)

SIAA9

Parthenocarpic fruits

Ueta et al. (2017)

ZmRPL and ZmPPR

Reduced protein level in kernels

Qi et al. (2016)

ZmARGOS8

High yield under drought stress

Shi et al. (2017)

ZmALS2

Chlorsulfuron resistance

Svitashev et al. (2016)

Phytoene synthase

White kernels and albino seedlings

Zhu et al. (2016)

FAD2-1A and 1B

Reduced linolenic acid levels

Kim et al. (2017)

GmFT2

Late flowering under long- and short-day conditions

Cai et al. (2018)

Watermelon

Phytoene desaturase (PDS)

Albino phenotype

Parmar et al. (2017)

Sweet orange

CsPDS

Increase in fruit size with albino phenotype

Jia and Wang (2014)

Citrus

PDS

Early stages of shoot generation; albino phenotype

Jia et al. (2017)

Grape

PDS

Albino leaves

Nakajima et al. (2017)

MLO7

Resistance to powdery mildew

Malnoy et al. (2016)

VvWRKY52

Increase disease resistance to Bitrytis cinerea

Wang et al. (2017b)

TaGW2

Increase in grain size and weight

Wang et al. (2018a)

Ms45

Rapid generation of male sterile bread wheat

Singh et al. (2018)

FAD2-1A and 1B

Reduced linolenic acid levels

Jiang et al. (2017)

Tomato

Maize

Soybean

Wheat

Flax

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program CRISPR Software Matchmaker was presented with detailed descriptions of various features concerning sgRNA designing tools to aid researchers in the selection of appropriate tools (MacPherson and Scherf, 2015). Sequencing and computation are majorly dependent on whole-genome sequencing and data analysis for the prediction of different sgRNA off-target profiles. Profiling of dCas9 binding sites, homology to the PAM-proximal half of sgRNA, and initiation of dCas9 binding may be facilitated by chromatin immune-precipitation sequencing (ChIP-seq) (Graham and Root, 2015). Further insights from the in-depth analysis of the off-target effects have been obtained by Digenome-seq (Kim et al., 2015) and various other DSB recognition techniques, for instance, Guideseq (Tsai et al., 2015). Disagreements have emerged while comparing the off-target data generated by two in silico off-target prediction modules. Possible disagreements may be due to differences in their capacities to tolerate mismatches, ensemble strategies for the generation of consensus results, and the structure of sgRNA and chromatin features. The volume of data generated for model training in relation to off-target related data was meager in comparison to that of on-target genome editing data. Thus, the pooling of data from sequencing and experimental techniques would serve as an important factor. In spite of the upsurge in tools for computational analysis, the computational models that deal with sgRNA efficacy prediction are elusive. More importantly, the data pooled from various sources globally remain privately controlled and are inaccessible to the scientific community, as this is not available in public domains. Facilitating the accessibility of this pooled data through public domains can bring in fresh perspectives to the data generated from experimental conditions, various platforms, cell types, or even organisms. Influencing parameters that could contribute to genomic features such as GC content, nucleotide preference, and the homology sequence pattern could also be investigated by integrating resources into the public domain. In-depth analytical studies of the CRISPR-Cas system have evolved this system as an impressive gene-editing platform, as it is considered an ideal tool for crop improvement possessing an innate potential to rapidly produce novel phenotypes or traits. Primarily, genome editing through CRISPR-Cas9 demands the delivery of sgRNA and the Cas9 protein into the target cells. Once this is attained, CRISPR-Cas9 tools can create significant opportunities for analyzing plant growth, productivity, and development. Other aspects include studying the metabolic pathways that may render plants resistant to stress, a better understanding of the cell cycle and its regulation, the study of water and nutrient uptake and utilization, and eminent alterations of the photosynthetic processes. A year-wise timeline documenting the frequency of publications for the past decade revealed a phenomenal augmentation in the interest of the research community to indulge in genome editing of plants via the CRISPR-Cas system. The infrequent data generated using the CRISPR system until the year 2012 could be due to the lack of standardized protocols for genome editing of organisms, including plants. More than a single-fold increase in publications related to CRISPR-Cas-based genome editing was observed between the years 2013 to 2017. In 2018, 315 publications were reported in food and fodder-related crops. Upon estimation of the CRISPR-Cas-based genome editing in 87 plants that was documented until 2017, it emerged that the global adaptation of this technique had led to the development of mutations across different plant species with minimum off-target effects by many research groups.

10.1 Machine learning and CRISPR-Cas9 genome editing Artificial intelligence (AI) offers novel strategies to employ the CRISPR-Cas9 framework for the analysis of edited crop lines with improved traits, for instance, higher nutritional value, stress tolerance, modified root and flower architectures, palatability, and so on. The modification of target genes and genomic regions significantly depends upon predetermination of the sgRNA target sites; however, the efficacy may not be defined as sgRNAs may be led to off-target effects. Machine learning (ML) methods may be employed for the prediction of off-target placement across crop genomes. ML can train and test the possible regression points that can either diverge or converge the plot of off-target or on-target specificities. The predictable sites from the trained set may emphasize the mechanisms of action in the CRISPR-Cas9 system in consonance with the guided specificity to PAM regions. The PAM-specific vertical of points is the significant component for complete prediction. Algorithms such as supervised, unsupervised, semisupervised, and reinforcement learning may be adopted to predict cleavage propensity. Accessible ML types may be employed to classify biological functionalities from mutations, and to screen on- and off-target mutations in a regression model using a random forest algorithm. It allows examining the significant features that lead to variations in cleavage efficiency. To compute the model, there are many widely accessed lab-scale data points to be incorporated as feature data such as GC content, CpG island, frame of coding regions, chromatic structures, expression profile, sgRNA secondary structure, alignment of sgRNA and target score distributions, complete descriptions of GenBank feature tables, and many other search accessibility data. Incidentally, the ML schema is not convoluted to a specific experimental system in the living cell where the system emphasized and predicted the response related to the consistency of the data. In the future, genome-wide engineering across crop species would integrate trained datasets, including variants and orthologs. Thus, ML-based learning methods may efficiently predict lethal interactions of sgRNAs and ensure the characterization of target regions in particular genetic combinations.

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FIG. 5 An overview of the CRISPR technique, the detection of its functional contribution to the plant, and the regulation policies established by various bodies strictly establishing guidelines that impact the human community by exposure to products released commercially using genome-based tools that mimic, alter, or contribute to the mutagenesis of natural processes.

11

Social acceptance of genome-edited (GE) plants using CRISPR technology

Genome editing tools may be efficiently employed for the introduction of desirable traits in crop plants through nucleotide substitutions, additions, deletions, and gene insertion or replacement in a random manner. The developed phenotype is not distinct from those that have evolved through random mutagenesis, natural genetic variations, and conventional breeding (Fig. 5). Like any other mutagenesis method (physical and chemical), genome editing is a method for biological mutagenesis that can be successfully applied in crop breeding. Genetically modified organisms (GMO) are regulated by the Cartagena Protocol, which comes under the international regulatory framework of living modified organisms (LMOs). According to this protocol, LMOs are living organisms that hold a novel combination of genetic resources modified through the use of modern biotechnology. This protocol has been a debatable issue over the years. On a global scale, the CRISPRCas technique has been discussed to be expunged from the current GMO regulations, but new technical challenges and government policies are still the biggest obstacles in the path of social acceptance of genome-edited crops (Araki and Ishii, 2015; Jones, 2015; Kanchiswamy et al., 2015). The current debates and discussions held nation-wise by GMO legislative regulatory and advisory authorities have suggested a reclassification of GE crop varieties as non-GMOs for social acceptance that would be regulated on the bases of either product-based and/or process-based GMO regulations (Araki and Ishii, 2015). One of the most remarkable features of genome-edited organisms is the absence of any foreign DNA, unlike GMOs. Genome edited crops can be more socially acceptable than plants that carry foreign DNA in their genomes. On these lines, the USDA and Food and Drug Administration (FDA) have approved food products developed through genome editing for human consumption (mushrooms and maize). These edited food products do not fall under the category of GMOs and would be exempted from traditional GMO policies and regulations (Waltz, 2016). In contrast, GE crops have been considered as equivalent to GMOs by the European Court of Justice (EU), and due to this decision the development of GE crops has been banned in the European Union (Callaway, 2018). The benefits of GE technology for world food security are withheld due to public perception and the current performance of crop breeding (Wolt et al., 2016).

12

Policy and government perspectives on the regulation of GE crops

GE crop plants developed by gene editing or site-directed nuclease (SDN) technology created genetic variations by introducing substantial changes to the genome of crop plants. SDN technology has recently emerged as a robust tool for obtaining desired characteristics through targeted adaptations. The main features of the SDN system encompass the

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introduction of small, specific changes at the DSB site by exploitation of the host’s natural repair system. Targeted edits resulted in the deletion and/or addition of nucleotides that in turn may generate novel or desired traits, for instance, increased nutrient quality or decreased production of allergens. In several countries, GE crops were regulated via biosafety frameworks that had been established by specific legislation. SDN technology is categorized into three classes. First is SDN-1 that may be created via double-stranded cleavage in the genome of a host cell without an interrogation of foreign particles, which are spontaneously repaired by a natural repair system, lead to a deletion or mutation, gene silencing, knockout of a gene. Second is SDN-2 that may be created via double-stranded cleavage being recognized and repaired by the cell’s repair machinery via a small DNA fragment harboring the desired mutation and complementary to the area of the break. The fragment of DNA is accompanied by minor changes in the genomic code, which the repair system copies into the genome resulting in a small variation of the target gene. Third is SDN-3 that may be created by a double-strand cleavage in the DNA, but it is accomplished by a fragment containing a gene or other template of genetic material. SDN-1 and SDN-2 do not harbor any exogenous DNA insertions or recombinant DNA, as they do not lead to the development of new plant varieties that come under the regulation of GMO legislation. However, SDN-3 would fall under the scope of GMO legislation, if the newly produced plant varieties contain more than 20 base pairs of foreign DNA insertions. In general, two categories of regulatory systems are known: process-based and product-based. Although regulation under the coordinated framework is frequently described as product-focused, the regulatory approach to GE organisms reflects a de facto process-based trigger in many representative cases (Wolt, 2017). Regulatory policies of the USDA are based on whether a plant pest, Agrobacterium tumefaciens, has been employed for the incorporation of DNA, and not based on product qualities or traits. We know that all the existing regulations have advantages and disadvantages; moreover, none of the systems has fully addressed the manner in which GE technology works, as it involves simple deletion, insertion, or base pair swapping. Small and medium enterprises (SMEs) exhibited a wide range of Europe’s innovative plant breeding sector, which could particularly benefit from the SDN (site-directed nuclease) system to meet market demands and produce better varieties that are highly sustainable and ecofriendly with improved yields. However, these uncertainties may be addressed if the EU clears their vision toward existing SDN technologies. In the future, if the administrative law could be reframed for these products in the same way, as conventional breeding or biological reproduction methods (e.g., asexual reproduction), the European plant breeding sector will then be able to focus its resources on research within their country rather than having to do so in non-EU countries. Only a few areas such as North and South America include a provision to welcome the approach taken for the development of GE crops by removing regulatory uncertainty. On the other hand, in European and Asian countries, only time would reveal the regulatory status of GE crops, as a significant level of inconsistency still exists (Wolt, 2017). Due to the inconsistency of regulatory policies at the global platform concerning the current regulatory approval of GE crops, most of the renowned biotech industries have moved their research and development sector to the United States. This may pose a serious issue for international trade between such countries, including India. To overcome this challenge, transparency in decision-making is crucial for GE applications.

13 Conclusion The unparalleled ability to create targeted, sequence-specific, genome-wide genetic diversity in plants via genome editing has resulted in unprecedented advancements in basic plant research and crop breeding. Genome editing technology, particularly the CRISPR-Cas systems, has transformed plant biology in a tremendous manner due to its simplicity, approachability, and the ability to simultaneously alter multiple traits in different organisms, including plants. The application of CRISPR technology in crop species to enhance yield, nutritional content, and disease resistance has proved to be beneficial in comparison to other technologies. This technology has been instrumental in synergizing basic and applied research for trait improvement across plant species via gene knock-outs, knock-ins, replacements, point mutations, fine-tuning of gene regulation, and other modulations at any given gene locus within crop genomes. Moreover, it has been successfully employed for the construction of high-throughput mutant libraries and antiviral breeding. Although impressive development has been made, the efficacy of any new genome editing process requires functional genomics, advanced genotype-independent delivery methods, and moderation of off-target effects. However, these concerns are being overcome with the rapid evolution of several homologs of Cas proteins and the incredible flexibility of the CRISPRCas systems. Prospects of a CRISPR-Cas-based genome-editing system would grow multifold in case of efficiently spreading genetic elements through the population, known as gene drive. This technique has immense potential for public health and humanitarian purposes, for instance alleviating the load of vector-borne diseases including malaria, even though it surely would have related ethical and social concerns. As of now, following Vietnam, Japan, and Australia, India is on the brink of accepting GE crops with the quintessential prerequisite regulatory framework being laid by the Department of Biotechnology under the Science and Technology Ministry. Eventually, this would create a roadmap for the approval

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of SDN-1, SDN-2, and SDN-3, for starters. CRISPR-Cas-based gene drive may be used to suppress or expunge invasive species such as weeds and pests and may be used as a potent tool to alter pathogens and incorporate agronomically desired novel traits into current populations. For instance, weeds such as congress grass (Parthenium sp.), pigweed (Amaranthus sp.), and others may be engineered via CRISPR-Cas-based gene drives, making them susceptible to widely used herbicides. However, genome editing is still at its infancy, so researchers should restrain from executing gene drives until regulatory and social frameworks are established for GE methodology. The systematized transfer of technologies from the lab to the field requires the swift discovery of genes and the genetic basis for crucial traits (utilizing the omics approach), robust efficiency of gene targeting, novel delivery routes for CRISPR-Cas reagents to plants. Additionally, developing efficient plant regeneration protocols with or without the employment of tissue culture, and the accessibility of prime editors and base editors with enhanced targeting capabilities would also foster this translation. Coupling the insights gained from advances in functional genomics combined with robust GE technologies and NGS along with synthetic- and systems biology may be employed to develop advanced crops harboring improved quantitative and qualitative traits that would pave the path toward a second Green Revolution.

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Yu, C., Liu, Y., Ma, T., Liu, K., Xu, S., Zhang, Y., Liu, H., La, R.M., Xie, M., Ding, S., Qi, L.S., 2015. Small molecules enhance CRISPR genome editing in pluripotent stem cells. Cell Stem Cell 16, 142–147. Yunyan, F., Jie, Y., Fangquan, W., Fangjun, F., Wenqi, L., Jun, W., Yang, X., Jinyan, Z., Weigong, Z., 2019. Production of two elite glutinous rice varieties by editing WxGene. Rice Sci. 26 (2), 118–124. Zetsche, B., Gootenberg, J.S., Abudayyeh, O.O., Slaymaker, I.M., Makarova, K.S., Essletzbichler, P., Volz, S.E., Joung, J., van der Oost, J., Regev, A., Koonin, E.V., Zhang, F., 2015. Cpf1 is a single RNA-guided endonuclease of a class 2 CRISPR-Cas system. Cell 163, 759–771. Zetsche, B., Heidenreich, M., Mohanraju, P., Fedorova, I., Kneppers, J., DeGennaro, E.M., Winblad, N., Choudhury, S.R., Abudayyeh, O.O., Gootenberg, J.S., Wu, W.Y., Scott, D.A., Severinov, K., van der Oost, J., Zhang, F., 2017. Multiplex gene editing by CRISPR-Cpf1 using a single crRNA array. Nat. Biotechnol. 35, 31–34. Zhang, Y., Liang, J., Zong, Y., Wang, Y., Liu, J., Chen, K., Qiu, J.L., Gao, C., 2016. Efficient and transgenefree genome editing in wheat through transient expression of CRISPR-Cas9 DNA or RNA. Nat. Commun. 7, 12617. Zhang, J., Zhang, H., Botella, J.R., Zhu, J.K., 2017. Generation of new glutinous rice by CRISPR-Cas9-targeted mutagenesis of the Waxy gene in elite rice varieties. Integr. Plant Biol. 60, 369–375. Zhang, H., Si, X., Ji, X., Fan, R., Liu, J., Chen, K., Wang, D., Gao, C., 2018. Genome editing of upstream open reading frames enables translational control in plants. Nat. Biotechnol. 36, 894–898. Zhang, P., Du, H., Wang, J., Pu, Y., Yang, C., Yan, R., Yang, H., Cheng, H., Yu, D., 2019. Multiplex CRISPR-Cas9-mediated metabolic engineering increases soybean isoflavone content and resistance to soybean mosaic virus. Plant Biotechnol. J. https://doi.org/10.1111/pbi.13302. Zhong, Z., Zhang, Y., You, Q., Tang, X., Ren, Q., Liu, S., Yang, L., Wang, Y., Liu, X., Liu, B., Zhang, T., Zheng, X., Le, Y., Zhang, Y., Qi, Y., 2018. Plant genome editing using FnCpf1 and LbCpf1 nucleases at redefined and altered PAM sites. Mol. Plant 11 (7), 999–1002. https://doi.org/10.1016/j. molp.2018.03.008. Zhong, Z., Sretenovic, S., Ren, Q., Yang, L., Bao, Y., Qi, C., Yuan, M., He, Y., Liu, S., Liu, X., Wang, J., Huang, L., Wang, Y., Baby, D., Wang, D., Zhang, T., Qi, Y., Zhang, Y., 2019. Improving plant genome editing with high-fidelity xCas9 and non-canonical PAM-targeting Cas9-NG. Mol. Plant 12, 1027–1036. Zhou, J., Peng, Z., Long, J., Sosso, D., Liu, B., Eom, J.S., Huang, S., Liu, S., Vera Cruz, C., Frommer, W.B., White, F.F., Yang, B., 2015. Gene targeting by the TAL effector PthXo2 reveals cryptic resistance gene for bacterial blight of rice. Plant J. 82 (4), 632–643. Zhou, C., Sun, Y., Yan, R., Liu, Y., Zuo, E., Gu, C., Han, L., Wei, Y., Hu, X., Zeng, R., Li, Y., Zhou, H., Guo, F., Yang, H., 2019. Off-target RNA mutation induced by DNA base editing and its elimination by mutagenesis. Nature 571, 275. https://doi.org/10.1038/s41586-019-1314-0. Zhu, L.J., Holmes, B.R., Aronin, N., Brodsky, M.H., 2014. CRISPRseek: a bio-conductor package to identify target-specific guide RNAs for CRISPRCas9 genome-editing systems. PLoS One. 9(9), e108424. Zhu, J., Song, N., Sun, S., Yang, W., Zhao, H., Song, W., Lai, J., 2016. Efficiency and inheritance of targeted mutagenesis in maize using CRISPR-Cas9. J. Genet. Genomics 43, 25–36. https://doi.org/10.1016/j.jgg.2015.10.006. Zhu, Y., Gao, A., Zhan, Q., Wang, Y., Feng, H., Liu, S., Gao, G., Serganov, A., Gao, P., 2019. Diverse mechanisms of CRISPR-Cas9 inhibition by type IIC anti-CRISPR proteins. Mol. Cell 74, 296–309. Zong, Y., Wang, Y., Li, C., Zhang, R., Chen, K., Ran, Y., Qiu, J.L., Wang, D., Gao, C., 2017. Precise base editing in rice, wheat and maize with a Cas9-cytidine deaminase fusion. Nat. Biotechnol. 35 (5), 438–440. https://doi.org/10.1038/nbt.3811. Zong, Y., Song, Q., Li, C., Jin, S., Zhang, D., Wang, Y., Qiu, J.L., Gao, C., 2018. Efficient C-to-T base editing in plants using a fusion of nCas9 and human APOBEC3A. Nat. Biotechnol. 36, 950–953. https://doi.org/10.1038/nbt.4261. Zuo, J., Li, J., 2014. Molecular genetic dissection of quantitative trait loci regulating rice grain size. Annu. Rev. Genet. 48, 99–118. Zuo, E., Sun, Y., Wei, W., Yuan, T., Ying, W., Sun, H., 2019. Cytosine base editor generates substantial off-target single-nucleotide variants in mouse embryos. Science. https://doi.org/10.1126/science.aav9973.

Chapter 12

Targeted genome editing using CRISPR-Cas9: Applications in fruit quality and stress resilience Diana Pimentel and Ana Margarida Fortes Universidade de Lisboa, Faculdade de Ci^ encias de Lisboa, BioISI, Campo Grande, Lisboa, Portugal

1 Introduction Plant domestication was essential in the transition from hunter-gatherer behavior to agriculture in the Neolithic period (Gepts, 2014; Purugganan and Fuller, 2009). Starting with trait selection then moving to conventional breeding, several plant crops were modified to increase productivity and nutritional value; improve quality traits such as flavor, color, and juiciness; and gain resistance to stress conditions. With the development of genetic engineering, new plant breeding techniques (NPBTs) were developed and are currently being applied. Genomic studies have shown that targeted DNA double-strand breaks (DSBs) by engineered nucleases has led to genome editing or transgene integration through homologous recombination (Gascuel et al., 2017). After nuclease cleavage, DSBs can be repaired by nonhomologous end joining (NHEJ) or homology-directed repair (HDR) pathways. In blunt-end DSB, NHEJ repair can lead to random insertions or deletions (InDels) that can cause the frameshift mutation of a coding sequence or the disruption of the cis-acting element in promoters or enhancers. When an exogenous DNA template homologous to the surrounding sequence of the DSB is supplied, HDR is used to introduce precise point mutation or specific nucleotide sequences. The most used technologies for targeted DSB were zinc finger nucleases (ZFN; Kim et al., 1996) and transcription activator-like effector nucleases (TALENs; Christian et al., 2010). Both are engineered fusion proteins with a DNA-binding domain fused with a nonspecific nuclease domain. Most recently, a new platform is gaining ground based on the archaea and bacterial adaptive immunity system: the type II clustered regulatory interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 nuclease (Cas9) (reviewed by Bortesi and Fischer, 2015; Sander and Joung, 2014). CRISPR was first identified in 1987 (Ishino et al., 1987) and applied to genome editing in 2013 (Cho et al., 2013; Cong et al., 2013; Mali et al., 2013; Hwang et al., 2013). CRISPR is a protective system against invading nucleic acids such as viruses and plasmids, acting by cleaving the foreign DNA in a sequence-dependent manner. Type II CRISPR systems incorporate fragments of the foreign DNA (known as spacers) between the CRISPR repeats as an array within the bacterial host genome. During infection, these arrays are transcribed and processed into small interfering CRISPR RNAs (crRNAs) combined with a transactivating CRISPR RNA (tracrRNA) in order to activate and guide the Cas9 nuclease to the homologous sequence in the foreign DNA (known as protospacers). The presence of a conserved three nucleotide protospacer-adjacent motif (PAM) is mandatory for cleavage; the most common is the 50 -NGG-30 motif. The 12 nucleotides upstream of the PAM are responsible for the specificity to target DNA. The transition from the CRISPR system of Streptococcus pyogenes to the targeted genome editing occurred when Jinek et al. (2012) found that the target DNA could be modified by changing the crRNA and that this could be fused with the tracrRNA into a single guide RNA (sgRNA). The CRISPR-Cas9 system became the simplest technology: (1) two components, Cas9 nuclease and a gRNA, must be expressed or introduced in the target cell of the organism, (2) the 20 bases at the 50 end of the sgRNA guide the Cas9 to the target DNA by RNA-DNA complementarity, and (3) the target site must be immediately upstream of a PAM sequence, normally a 50 -NGG motif. CRISPR-Cas9 technology has shown promising results in fruit crop improvement, which will be discussed in the following sections (Table 1). These studies were mainly applied in tomatoes, citrus, and cucumbers. Nevertheless, the applicability of CRISPR-Cas9 in gene editing was successful in several other fruit crops such as grapevines (Malnoy et al., 2016; Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00012-7 © 2020 Elsevier Inc. All rights reserved.

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TABLE 1 Application of the CRISPR-Cas9 genome editing system in fruit crop plants for biotic stress resistance, quality traits, and de novo domestication. Plant

Factor

Target gene

Trait

Reference

Citrus (Wanjincheng orange)

Biotic stress

CsLOB1

Citrus canker

(Peng et al., 2017)

Citrus (Duncan grapefruit)

Biotic stress

CsLOB1

Citrus canker

( Jia et al., 2017)

Cucumber

Biotic stress

eIF4E

Virus pathogen

(Chandrasekaran et al., 2016)

Grape

Biotic stress

VvWRKY52

Botrytis cinerea resistance

(Wang et al., 2016)

Tomato

Biotic stress

SlMlo1

Powdery mildew

(Nekrasov et al., 2017)

Tomato

Biotic stress

SlDMR6

Pseudomonas syringae, Phytophthora capsici, and Xanthomonas spp.

(Thomazella et al., 2016 [Preprint])

Tomato

Quality trait

PECTATE LYASE (PL)

Fruit firmness

(Uluisik et al., 2016)

Tomato

Quality trait

SELF-PRUNING 5G (SP5G) and SELFPRUNING (SP)

Photoperiodic response

(Soyk et al., 2017b)

Tomato

Quality trait

LONG-NON CODING RNA (lncRNA1459)

Fruit ripening

(Li et al., 2018a)

Tomato

Quality trait

ORGANELLE RECOGNITION MOTIF (SlORRM4)

Mitochondrial function

(Yang et al., 2017)

Tomato

Quality trait

SlAGAMOUS-LIKE 6 (SLAGL6)

Parthenocarpic fruits

(Klap et al., 2017)

Tomato

Quality trait

SlIAA9

Parthenocarpic fruits

(Ueta et al., 2017)

Tomato

Quality trait

ALC allele

Shelf life

(Yu et al., 2017)

Tomato

Quality trait

SlGAD2 and SlGAD3

GABA accumulation

(Nonaka et al., 2017)

Tomato

Quality trait

GABA-TP1, GABA-TP2, GABA-TP3, CAT9, and SSADH

GABA accumulation

(Li et al., 2018b)

Tomato

Quality trait

SGR1, LCY-E, Blc, LCY-B1, and LCY-B2

Lycopene accumulation

(Li et al., 2018c, d)

Tomato

Quality trait

cis-Regulatory elements

Fruit size, inflorescence branching, and plant architecture

(Rodrı´guez-Leal et al., 2017)

Tomato

Quality trait

Pectate lyase 56 (PL), polygalacturonase 2a (PG2a) and β-galactanase (TBG4)

Pectin degradation in ripening

(Wang et al., 2019)

Wild tomato

De novo domestication

SELF-PRUNING (SP), OVATE (O), FRUIT WEIGHT 2.2 (FW2.2), LYCOPENE BETA CYCLASE (CycB), FASCIATED (FAS), and MULTIFLORA (MULT)

Solanum pimpinellifolium domestication

(Zs€ og€ on et al., 2018)

Wild tomato

De novo domestication

SP, SP5G, SlCLV3, and SlWUS

Solanum pimpinellifolium domestication

(Li et al., 2018c, d)

Groundcherry

De novo domestication

SP, SP5G, and CLV1

Physalis pruinose domestication

(Lemmon et al., 2018)

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Osakabe et al., 2018; Ren et al., 2016), apples (Malnoy et al., 2016; Nishitani et al., 2016), watermelons (Tian et al., 2017), wild and cultivated strawberries (Martı´n-Pizarro et al., 2018; Zhou et al., 2018), kiwifruit (Wang et al., 2018), and bananas (Kaur et al., 2018). Legislation regarding plants edited with CRISPR-Cas9 system is still up for debate. In the United States, if there is no trace of any foreign genetic material, the US Department of Agriculture (USDA) does not consider the organisms generated by targeted mutagenesis with self-repair mechanisms as GMOs (genetically modified organisms) ( Jones, 2015; Ledford, 2013; Waltz, 2012). On the other hand, in the European Union, plants created with CRISPR or other gene editing tools are considered GMOs and are not derived from conventional mutagenesis; therefore, they must follow very stringent rules to be cultivated (Callaway, 2018; Kupferschmidt, 2018). The CRISPR-Cas9 system has been applied in integrating the Cas9 gene and the sgRNA into the genome of the edited organism at the initial stage. However, studies have demonstrated that by segregation, it is possible to obtain homozygous mutated plants without the transgenic part in the second or third generation. These final homozygous lines should not be considered transgenic plants because the final organism has no difference compared to classic mutagenesis such as that caused by irradiation. Still, using this strategy, the T0 generation integrates transgenic genes that can raise legal problems. To overcome this problem, some studies have been focused on exploring the direct delivery of purified sgRNA-Cas9 ribonucleoproteins (RNPs) into the target tissues/cells. Malnoy et al. (2016) successfully edited both grape and apple protoplasts using RNPs, avoiding the integration of plasmid DNA into the target genome. They targeted the MLO-7 gene in the grapevine and DIPM-1, DIPM-2, and DIPM-4 in the apple to increase resistance against powdery mildew and fire blight disease, respectively (Malnoy et al., 2016). The optimization of regeneration protocols from edited protoplasts is crucial to apply the RNP delivery to the development of edited but nontransgenic fruit crop plants. In this chapter, studies conducted so far using CRISPR technology applied to fruit crop quality enhancement and stress mitigation are reviewed.

2 Improvement of traits associated with fruit quality The improvement of fruit quality is one of the main purposes of NBTs. In the tomato, several studies were performed using the CRISPR-Cas9 system to obtain parthenocarpic tomato fruits (Klap et al., 2017; Ueta et al., 2017), and to increase shelf life (Yu et al., 2017) and fruit yield (Soyk et al., 2017b). Several tomato traits were also reviewed by Rothan et al. (2019), and suggested as future targets for tomato improvement. One of the most important traits for agriculture nowadays is the production of seedless fruits by parthenocarpy, that is, a fertilization-independent fruit set. Breeding for parthenocarpy brings several advantages such as stable and sustainable crop production in the context of climate change and a higher content of total soluble solids (Klap et al., 2017). Moreover, seedless fruits are more appreciated by the consumers and more useful in some industries (such as sauce production). Klap et al. (2017) used CRISPR-Cas9 technology to target the loss-of-function mutation of the SlAGAMOUS-LIKE 6 (SLAGL6) gene. The MADS-box gene SLAGL6 was suggested to be involved in the regulation of “ovary arrest” until fertilization and its mutation conferred facultative parthenocarpy. Under heat stress, mutants are capable of seedless fruit production with similar characteristics to the wild-type (WT). As pollen viability and sexual reproduction are maintained, this study suggests the use of SLAGL6 for facultative parthenocarpy (Klap et al., 2017). Furthermore, Ueta et al. (2017) also suggested a rapid breeding strategy to obtain seedless tomato fruits using CRISPR-Cas9. SlIAA9, a key regulator of auxin signaling involved in the repression of fruit initiation without fertilization, was mutated with very high efficiency rates in both Micro-Tom and Ailsa Craig cultivars. Biallelic and homozygous mutated T0 plants showed typical parthenocarpy phenotypes. In some cases, fertilized fruits were developed with few seeds that inherited the mutation and exhibited the seedless phenotype (Ueta et al., 2017). These studies proved the efficiency of the CRISPR-Cas9 system in improving tomato quality traits. Another critical trait of fleshy fruits for farmers is the shelf life. One of the main objectives of the breeding programs is to extend this time. In tomato plants, several natural mutations slow ripening and confer a longer shelf life, such as rin (ripening inhibitor), nor (nonripening), and alc (alcobaca syn. DFD, delayed fruit deterioration). The most used strategy so far to increase shelf life is hybridization with mutated varieties, which is time-consuming and may compromise other quality traits such as flavor and color. With CRISPR-Cas9, it will be possible to rapidly replace the target locus in order to extend the storage time. In fact, the HDR-mediated replacement of the ALC allele for the recessive alc in M82 tomato fruits resulted in a longer shelf life (Yu et al., 2017). In this work, a homozygous alc line without the T-DNA insertion was generated at the T1 generation, and it showed better performance during storage than WT (Yu et al., 2017). Preventing fruit softening is another strategy to increase shelf life. Most fruits undergo softening during ripening, which is important for fruit quality but a problem for storage and transportation. The pectin degradation on fruit cell walls is on the basis of fruit

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softening during ripening (Brummell, 2006). Pectate lyase (PL) was reported as critical in fruit softening and its targeted mutation affects firmness without disturbing ripening aspects such as ethylene biosynthesis, color, total soluble solids, yield, or weight (Uluisik et al., 2016). Additionally, Wang et al. (2019) used the targeted loss-of-function mutation of genes associated with pectin degradation in the tomato (PL; polygalacturonase 2a, PG2aI; and β-galactanase, TBG4). They found that only the PL mutation had a significant impact on fruit softening, although mutations in PG2a and TBG4 influenced fruit color and weight. RNA editing plays a key posttranscriptional role in gene expression, and its involvement in fruit ripening is being studied. ORRM4 is a mitochondrial RNA editing factor, and silencing the SlORRM4 gene was shown to delay tomato ripening by lowering the respiratory rate and ethylene production; it was localized to the mitochondria (Yang et al., 2017). The SlORRM4 mutation disrupted the RNA editing function for several mitochondrial genes. This study has shown the involvement of RNA editing factors in fruit ripening (Yang et al., 2017). With increased concern regarding human health and life quality, nutraceutical properties are desirable to prevent some health problems. The γ-aminobutyric acid (GABA) is a nonprotein amino acid found in bacteria, animals, and plants. Several studies have been shown to confer health benefits such as lowering the blood pressure of hypertensive patients; the consumption of GABA-enriched foods is being promoted (Takahashi et al., 1955, 1961; Yoshimura et al., 2010). An efficient increase of GABA content was obtained in tomato fruits (Nonaka et al., 2017). GABA is synthesized from glutamate by the glutamate decarboxylase (GAD), which generally has an autoinhibitory domain at the C-terminus. Nonaka et al. (2017) used targeted mutagenesis to knock out the autoinhibitory part of two tomato GAD genes (SlGAD2 and SlGAD3); the deletion of the C-terminus showed increased GABA accumulation in comparison with WT. In particular, SLGAD3 with a truncated C-terminal presented increased GABA content without significantly disturbing the plant size, flowering, and fruit yield, suggesting that SLGAD3 would be a more suitable target for future breeding using targeted mutation (Nonaka et al., 2017). Another study also increased the GABA content in tomato fruits using the multiplexed pYLCRISPR/Cas9 system (Li et al., 2018b). Five key genes of the GABA metabolism (GABA-TP1, GABA-TP2, GABA-TP3, CAT9, and SSADH) were targeted using a single vector. Despite the lack of efficiency of one sgRNA, it was possible to obtain a quadrupole mutant, proving the applicability of the multiplex CRISPR-Cas9 system in tomato genome editing (Li et al., 2018b). Further studies will be essential to improve sgRNA efficiency. Another bioactive compound associated with preventing health problems is lycopene, a C40 carotenoid synthetized during fruit ripening. In the ripe tomato, lycopene is the most abundant carotenoid and confers color and fruit quality. Recently, Li et al. (2018d) used a bidirectional strategy to promote lycopene biosynthesis and prevent its catabolism. Five target genes were selected (SGR1 to promote lycopene synthesis; and, LCY-E, Blc, LCY-B1, and LCY-B2 to prevent lycopene cyclization) and six sgRNA were assembled in the pYLCRISPR/Cas9 vector (Li et al., 2018c, d; Ma et al., 2015). Single to quadruple mutants were obtained and they showed higher lycopene and β-carotene content than WT plants. The single SlSGR1 mutant presented the higher lycopene content, about 5.1-fold in comparison to WT, and a more vivid color after the breaker stage (Li et al., 2018c, d). The mutation was transmitted to subsequent generations (Li et al., 2018c, d). Flowering and inflorescence architecture are also important for fruit production. Seasonal changes in day length trigger flowering and the photoperiod response can limit the geographical range of plant cultivation. Soyk et al. (2017b) showed that genome editing of the tomato flowering repressor, SELF-PRUNING 5G (SP5G), improves the inflorescence architecture and rapid flowering that lead to an early fruit yield. The same authors used the CRISPR-Cas9 system to study the inflorescence architecture and branched varieties (Soyk et al., 2017a). They identified two mutations in two closely related MADS-box transcription factor genes (j2 and ej2) and verified a dosage relationship among natural and gene-edited mutations that could lead to improved inflorescence architecture and yield (Soyk et al., 2017a). Alternatively, to target CDS regions, Rodrı´guez-Leal et al. (2017) targeted cis-regulatory elements (CREs) in promoters, which resulted in several novel cis-regulatory alleles for three tomato genes that regulate fruit size, inflorescence branching, and plant architecture. Naturally occurring CRE mutations lead to the modification of gene expression, which has contributed to domestication (Meyer and Purugganan, 2013). This study opens a new window in the genome-editing strategies: CREs are now a potential target to enhance variability for quality traits. More studies are needed to understand the involvement of the several functional motifs that are identified in the promoter regions.

3

Mitigation of climate change effects on agricultural productivity

Improvement of the crop yield and quality is the aim of many breeders. In the present scenario, the concerns about sustainable agriculture, climate change, and overpopulation are growing. Climate change is one of the main topics in international political debates and researchers are putting in efforts to mitigate its effect.

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Conventional breeding is being used for the introgression of stress-tolerance genes from wild species into cultivated crops; however, this strategy is time-consuming. In several crops, wild relatives are found to be adapted to challenging environments; therefore, the de novo domestication of wild species using targeted genome editing is being proposed (reviewed by Khan et al., 2019; Li et al., 2018c, d; Østerberg et al., 2017; Zs€og€on et al., 2017, 2018). Many of the domestication traits are monogenic and have Mendelian inheritance patterns (Doebley et al., 2006; Meyer and Purugganan, 2013). In a review presented by Zs€ og€ on et al. (2017), several genes affecting productivity, fruit quality, and stress resilience in the tomato are discussed and suggested as targets for de novo domestication. The same authors designed two separate CRISPRCas9 strategies to domesticate the wild species Solanum pimpinellifolium by targeting the coding region of genes important for key traits: general plant growth habit, fruit shape and size, fruit number, and nutritional quality (Zs€og€on et al., 2018). Studies indicate that a semideterminate growth habit combines the advantages of determinate and indeterminate growth, such as increased yield, Brix, and water-use efficiency (Vicente et al., 2015). Edited S. pimpinellifolium lines presented higher fruit size and number than WT and showed a higher fruit lycopene accumulation in comparison with S. lycopersicum cv. MicroTom. In a similar study, Li et al. (2018c) also intended to domesticate S. pimpinellifolium by targeting not only the coding regions but also the promoter region of genes related to day-length sensitivity (SELF-PRUNING 5G, SP5G), shoot architecture (SELF-PRUNING, SP), flower and fruit production (CLAVATA3, CLV3, and WUSCHEL, WUS), and nutrient content (GGP1, vitamin C-biosynthetic enzyme). These studies gave rise to a new level of domestication of wild species to overcome challenging environmental conditions without compromising quality traits that are normally affected in traditional breeding, such as flavor and nutritional properties. Additionally, Lemmon et al. (2018) used CRISPR-Cas9 to perform the de novo domestication of the orphan Solanaceae crop groundcherry (Physalis pruinosa), editing genes associated with productivity traits such as plant architecture, flower production, and fruit size. Besides adaptation to climate change, plants are expected to face increased susceptibility to several pathogens. Susceptibility (S) genes are important in plant-pathogen interactions and the mutation of those genes can lead to higher disease resistance. An example is the eukaryotic translation initiation factor 4E (eIF4E), a plant translation factor crucial for the cellular infection cycle of potyviruses. In the cucumber, Chandrasekaran et al. (2016) applied CRISPR-Cas9 technology to increase the virus recessive resistance through mutation of the eIF4E. The cucumber genome has one copy each of eIF4E and eIF(iso)4E. In this study, targeted mutagenesis with specific sgRNAs targeting nonhomologous regions of exons 1 and 3 of eIF4E generated small deletions in the targeted sites. Homozygous T3 cucumber plant lines showed higher resistance to three important viruses, cucumber vein yellowing virus (Ipomovirus) and the potyviruses zucchini yellow mosaic virus and papaya ring spot mosaic virus-W. Moreover, three backcrossings were sufficient to lose the Cas9 gene producing nontransgenic plants (Chandrasekaran et al., 2016). Higher resistance to potyviruses was also obtained in Arabidopsis by disrupting the same gene (Pyott et al., 2016). The CsLOB1 was shown to be a critical S gene for citrus canker, caused by Xanthomonas citri ssp. citri (Xcc). It promotes pathogen growth and erumpent pustule formation (Hu et al., 2014). The Duncan grapefruit (Citrus  paradisi) contains two alleles of the CsLOB1, and CRISPR-Cas9 was applied to mutate the coding region of the CsLOB1 in both alleles, leading to citrus canker-resistant plants ( Jia et al., 2017). Moreover, CsLOB1 contains an effector-binding element (EBEPthA4) that is recognized by the PthA4 effector of Xcc and activates CsLOB1 expression. Another strategy to increase citrus canker resistance was implemented by Peng et al. (2017); sgRNA was designed to target the EBEPthA4 effectorbinding element in the promoter of CsLOB1 in the Citrus sinensis var. Wanjincheng. Deletion of the entire EBEPthA4 sequence from both CsLOB1 alleles provided increased resistance to Xcc. Editing the CsLOB1 promoter region alone was sufficient to enhance citrus canker resistance in the Wanjincheng orange (Peng et al., 2017). In this context, the genome-wide analysis of the LOB domain gene family in the grapevine enabled the identification of potential targets for increasing stress resilience in this important fruit crop (Grimplet et al., 2017). Additionally, promoter analysis revealed several motifs associated with stress responses that could be targeted and studied (Grimplet et al., 2017). Another important S gene that shows a high impact in powdery mildew susceptibility is the MILDEW RESISTANT LOCUS O (Mlo), which encodes a membrane-associated protein conserved in monocots and dicots. In the tomato, the SlMlo coding sequence was targeted with two sgRNAs separated for 48 bp, leading to a deletion of that size and to full resistance to the powdery mildew fungus Oidium neolycopersici (Nekrasov et al., 2017). From this study, a nontransgenic plant was created and named the Tomelo variety; the authors suggest that the slmlo1 mutation could be easily introduced into elite or locally adapted varieties (Nekrasov et al., 2017). DOWNY MILDEW RESISTANCE 6 (DMR6) has also been studied to increase broad-spectrum resistance against multiple pathogens. Two AtDMR6 Arabidopsis orthologs were identified in the tomato (SlDMR6-1 and SlDMR6-2), and SlDMR6-1 is upregulated during infection with Pseudomonas syringae pv. tomato and Phytophthora capsici (Thomazella et al., 2016 [Preprint]). In this work, the disruption of exons 2 and 3 using CRISPR-Cas9 resulted in truncated versions of the DMR6. The homozygous T1 line showed resistance to several pathogens, namely the bacteria Xanthomonas

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gardneri Xg153, Xanthomonas perforans Xp4b, and P. syringae DC3000 and the oomycete P. capsici LT1534, without affecting plant development and morphology (Thomazella et al., 2016 [Preprint]). The authors state that they are evaluating the performance of these tomato varieties under conditions that are relevant to agricultural practices (Thomazella et al., 2016 [Preprint]). One fruit crop that is suffering from climate change is the grapevine. The grapevine is a very important crop with high impact in the global economy, in particular in Mediterranean countries. Grapevine is very susceptible to several pathogens and a lot of effort is being done to increase resistance by breeding with other resistant Vitis species. The main problem with these procedures is the decrease of the organoleptic properties of grapes and, consequently, of wine. Genome editing could be applied to induce resistance to several pathogens in the V. vinifera species. Preliminary studies have been performed on grapevine cell cultures to optimize CRISPR-Cas9 technology (Malnoy et al., 2016; Nakajima et al., 2017; Osakabe et al., 2018; Ren et al., 2016) and increase resistance (Wang et al., 2018). The first applications of CRISPR-Cas9 gene editing were performed in 2016, when Ren et al. (2016) efficiently mutated the L-idonate dehydrogenase (IdnDH) responsible for the accumulation of tartaric acid in Chardonnay suspension cells and to regenerate grape plantlets, and Malnoy et al. (2016) mutated the MLO-7 gene in grape protoplasts (referred to in the introduction section). In the same year, Wang et al. (2016) identified potential CRISPR-Cas9 target sites for grapevine genome editing. More recently, the targeted mutagenesis of the VvWRKY52 gene resulted in increased resistance to fungal infection with Botrytis cinerea (Wang et al., 2018). Interestingly, recent hormonome analysis of Trincadeira and Syrah cultivars upon infection with B. cinerea has shown that higher basal levels of salicylic acid, jasmonates, and IAA on the Syrah cultivar at an early stage of ripening could confer more tolerance to Botrytis infection (Coelho et al., 2019). Therefore, targeting the basal content of key hormones by editing genes associated with the hormonal metabolism could be another direction in the improvement of stress tolerance. The use of CRISPR-Cas9 technology in de novo plant domestication and stress mitigation has shown promising results and applications in other fruit crops are expected.

4

Computational analysis

Nowadays, the number of nonmodel plants with their genome sequenced is increasing, which gives a huge advantage for the application of targeted NBTs, in particular of CRISPR technology. With all genomes sequenced, the prediction of off-target effects in the rest of the genome is facilitated and several platforms are being developed to identify single guide RNA with more accurate quality scores (reviewed by Hahn and Nekrasov, 2018). One of the platforms available for off-target prediction is the Cas-OFFinder, which has more than 90 plant genomes in its database, including the tomato, grapevine, and apple. It also has the possibility of requesting the upload of more organisms, becoming a very useful tool in CRISPR-Cas9 application (Bae et al., 2014). It also allows the selection of the nuclease used in order to maximize the accuracy of the off-target prediction.

5

Technology advancement

CRISPR refers to tandem repeats flanked by nonrepetitive DNA and was first described in 1987 in Escherichia coli (Ishino et al., 1987). It was applied to genome editing in 2013, and since then, its application has grown fast. The most used application of CRISPR is the targeted loss of function. However, this technology can be applied in the regulation of gene expression using a catalytically inactive Cas9 (dCas9), that is, dCas9 can specifically bind to the target sequence guided by sgRNA but cannot break the genome. In fact, Piatek et al. (2015) successfully modified the CRISPR-Cas9 platform to modulate gene expression in plants by developing chimeric dCas9-based transcriptional activators and repressors. Moreover, CRISPR-dCas9 was reported to allow epigenetic modifications such as acetylation and methylation of the genome (Thakore et al., 2015). The modification of Cas9 improves the biotechnological application of CRISPR technology. Several additional CRISPR-modified systems are being created (reviewed by Khatodia et al., 2016; Schindele et al., 2018). The CRISPR-Cpf1 system has been developed as an alternative to the CRISPR-Cas9 system. Cpf1, also known as Cas12a, belongs to the Class II CRISPR system and is also an RNA guided nuclease that makes DSB with alternative noncanonical PAMs, increasing the number of possible DSB targets. Cpf1 recognizes T-rich PAMs that are located upstream of the guide RNA, and generates staggered DSBs distal from the PAM. Additionally, Cas13 (also known as C2c2) has recently been reported to target and cleave specific strands of RNA and has been applied to degrade mRNAs and combat viral RNA replication (reviewed by Schindele et al., 2018). CRISPR-Cas9 has shown high specificity to the target sequence; however, off-target mutation is always a possibility. Dimeric RNA-guided FokI nucleases (RFNs), where Cas9 is replaced by a FokI nuclease, were developed to prevent off-target mutations because RFN cleavage activity depends on two sgRNAs with specific spacing and orientation (Tsai et al., 2014). All these alternatives of the CRISPR

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system are creating a new range of possibilities for genome editing and future studies are required to improve their applicability.

6 Conclusions and future perspectives CRISPR technology is a NPBT that is showing tremendous advantages over the technologies available. This technology is rapidly becoming one of the most used in functional studies, clinical research, and crop improvement due to its ease, low cost, and efficiency. The studies presented in this chapter indicate the beginning of a new era in the genetic engineering of fruit crops. Nevertheless, CRISPR is still a very recent technology and further studies are needed to explore its full potential. The most advantageous feature of the CRISPR system over the NBTs used until now is the production of cisgenic plants without any trace of transgenic genes for biotechnological purposes. The classification of these organisms is still under debate. Cisgenic plants obtained with CRISPR-Cas9 technology could not be distinguished from a wild-type plant and the scientific community does not agree in considering these organisms transgenic plants. A consensus among the scientific community and political institutions should be achieved in a short term so this highly promising technology could be implemented in agriculture in the near future.

Acknowledgments Funding was provided by the Portuguese Foundation for Science and Technology (FCT) [UID/MULTI/04046/2019 Research Unit grant from FCT, to BioISI, project PTDC/ASP-HOR/28485/2017, grant PD/BD/114385/2016] and COST Action INTEGRAPE (CA17111).

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Chapter 13

Systems biology of crop improvement: Drought tolerance as a model to integrate molecular biology, physiology, and breeding Isaiah Catalino M. Pabuayona, Jennylyn L. Trinidadb, Rosalyn B. Angeles-Shima and Ajay Kohlib a

Department of Plant and Soil Science, Texas Tech University, Lubbock, TX, United States, b Strategic Innovation Platform, International Rice Research

Institute, Metro Manila, Philippines

1 Introduction Climate change-mediated negative effects on agriculture would be most pronounced in the highly populated areas of the world. Asia supports nearly half the world’s population. The staple crop of Asians is rice. Africa holds the second-largest proportion of the world’s population and rice consumption is increasing annually in Africa. The two continents are also the ones with the highest rate of population increase. Thus, the global demand for rice, which at present feeds an estimated 3.5 billion people worldwide, is progressively increasing. Rice is not only a source of food but also of livelihood (IRRI, 2018). The maximum percentage of poor and malnourished people also resides in Asia and Africa. Aspects of nutritional security are also most important on the two continents. This is because the consumption of rice as a staple, mostly as milled and polished rice, does not meet micronutrient requirements. However, it accounts for 35%–60% of the total caloric intake in Asia (Khush, 1997). Hence, such a scenario necessitates the continuous improvement of rice yield, quality, stress tolerance, and postharvest care. Present-day rice is extremely sensitive to drought (Lafitte et al., 2004) due to its mainstream cultivation practices in waterlogged paddy fields for thousands of years. Overall, drought threatens both rice yield and quality (Fitzgerald and Resurreccion, 2009; Kim et al., 2011a, 2011b). This is especially true when drought occurs at the reproductive stage (Matsui et al., 2001; Jagadish et al., 2008). Drought is characterized by sustained below-average precipitation in an area whereby plants do not have sufficient water. A reduction in water content interferes with life processes because water encased in the hydrophobic membrane largely makes up the living unit of the cell, where it solubilizes various biopolymers and metabolites and acts as a nucleophile in enzymatic reactions. Drought can occur even in wet and humid areas, as it is defined relative to the condition in the locality. Over the past decades, the drought frequency has increased due to global warming (Dai, 2011). Drought spells now are of longer duration and thus the agricultural, socioeconomic, and ecological consequences are worse (Zhang et al., 2016). Up to 60% of crop loss can occur due to drought. In the past 25 years, 21% of losses in wheat and 40% of losses in maize were attributed to drought (Yin et al., 2014; Daryanto et al., 2016). Predictions for the severity of drought events in the future make for bleak projections. Leakey et al. (2006) project that increased drought and flooding due to global climate change may decrease the food crop yield over the next 50 years. Two-thirds of the world is projected to experience water stress conditions by 2025 (Manavalan and Nguyen, 2017). In this chapter, we discuss the multiple mechanistic pathways, each a complex process in itself, associated with plant response to drought, mostly using rice as a model. What grows out of such an understanding is the need for combining the current knowledge from molecular, physiological, organismal, ecogeographical, and environmental levels to breed for drought tolerance. The knowledge base of each of the component disciplines rests on the trait phenotype comparison of a relatively tolerant genotype. Hence, the importance of standardized phenotyping protocols cannot be overemphasized. Yet, for drought tolerance phenotyping, such protocols depend on edaphic and ecogeographical factors, necessitating the understanding of agronomical aspects as well. In the current era of “big data,” there are avenues for integrating knowledge

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from molecular biology with population genomics going onto field-based physiological and agronomical responses of plants to inform and formulate breeding strategies. Gene discovery and functional analysis for relevant physiological traits for drought tolerance are increasingly predicated on sequencing-based technologies. Yet, moving the target genes for such traits from one genotype to another still depends on molecular marker technology. However, varietal improvement for quantitatively inherited traits such as abiotic stress tolerance through molecular marker technology has not been very successful. This is because such traits are regulated by multiple QTLs, often with small additive effects, and are influenced by genetic background, epistatic interactions, and the environment and its interaction with the QTL. At the very least, marker-based breeding for the improvement of complex traits requires the identification of the number of loci controlling the phenotype, the approximate location of the identified loci in the genome, the magnitude of QTL effects, and the stability of these effects in different environments and genetic backgrounds. When such requirements are met, as for the rice submergence tolerance gene (Sub1A; Xu and Mackill, 1996; Xu et al., 2006), substantial genetic gains for the trait can be achieved (Angeles-Shim and Ashikari, 2017). Most rice breeding programs strive to achieve a balance between speed, cost, quality, and acceptability. However, addressing the most critical bottleneck and satisfying the other three aspects can lead to a successful product delivery. Yet, a consolidated, interagency effort is important to generate, disseminate, and deploy a new variety to make a difference at the farmer and customer level. Hence, it is not just a multidisciplinary undertaking that integrates physiology and molecular biology to facilitate breeding, but a multistakeholder undertaking to ensure that the useful new variety is successful. We present details of the relevant physiological and molecular factors known to be important for abiotic stress tolerance. We then present examples of attempts at integrating the upstream experimental and downstream product development and deployment efforts to formulate pipelines that can deliver novel varieties for withstanding drought conditions and reducing yield penalties. We believe that it is only through such efforts that the complex traits of stress tolerance, yield improvement, and quality enhancement can be addressed to meet the food and nutritional security demands of an ever-increasing population.

2

The complex physiological response to drought

The complexity of drought response starts right from the osmoticum-mediated ionic differentials across cell membrane that signal the sequential cascading responses at the hormones, genes, proteins, and metabolites level. Identification and characterization of the players involved at these levels target the improvements needed at the cell, tissue, organ, and organism level. In turn, this feeds into the feasibility of deploying the improved variety in the target environment (Henry et al., 2015). To begin with, the manifestation of the apparent changes at the organismal level is the most basic way of screening for tolerance. One of the simplest parameters used in screening for drought tolerance is the difference in the degree of leaf rolling, a physiological means of reducing transpiration under water stress. Leaf rolling under drought can be affected more by leaf morphology (leaf width) than by stomatal conductance, leaf water status, or maintenance of shoot biomass (Cal et al., 2019), and that narrow leaves roll up earlier than wider leaves. The stomata have a crucial role to play by closing and limiting water loss via transpiration. However, that inhibits CO2 entry into the leaf cells and reduces the plant’s photosynthetic rate. Indeed, stomatal density and the extent of stomatal closure affect survival under water stress (Bertolino et al., 2019). Increased leaf cuticle, reduced leaf area, and leaf blade orientation parallel to direct sunlight can prevent water loss (Fang and Xiong, 2015). These crucial adaptations increase drought resistance and promote survival (Passioura, 1996; Taiz and Zeiger, 1998; Biswal and Kohli, 2013). Other aerial manifestations of drought notwithstanding, the importance of the “hidden half,” that is, the roots of the plants is now being increasingly considered. Drought tolerance was maximal in rice plants with increased root hydraulic conductance (Lpr). These plants also had greater root density and depth. These traits together contributed to improved leaf water status (Henry et al., 2015). The resultant enhanced water transport can improve grain yield under drought (Henry et al., 2016). Drought-tolerant plants also show a greater large vein to small vein intervenal distance and mesophyll area (Henry et al., 2019), and these plants show increased lateral roots, especially under drought. Near isogenic lines (NILs) for drought tolerance QTL qDTY3.2 exhibited reduced root growth distribution to the shallow soil layer but increased distribution to the deeper soil layer as well as an increased number of root tips. Such a root system architecture (RSA) through qDTY3.2 led to more water use efficiency, an early flowering phenotype, and increased grain yield under drought (Dixit et al., 2014; Grondin et al., 2018). A water deficit forces plant biomass allocation to the roots to improve water uptake, but that can compromise plant photosynthetic efficiency. Together with stomatal closure, which limits CO2 entry, such a carbon deficit negatively impacts the essential cellular processes (Lichtenthaler, 1996; Blum, 1996; Zlatev and Lidon, 2012). One adaptation for water stress is spongy tissues in roots as water reservoirs, which can limit biomass

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allocation to roots. Thus, phenotyping for particular morpho-anatomical differences in leaves and roots can support the selection and prediction for drought-tolerant genotypes. Drought stress response involves two major mechanisms: escape and resistance. Drought escape refers to developmental plasticity to shorten the plant’s life cycle, finishing before stress can do irreparable damage and eliminate the chance for reproduction (Yue et al., 2006). On the other hand, drought resistance can mean either avoidance or direct tolerance to the stress. Avoidance employs mechanisms to maintain high tissue water potential. This is achieved through several adaptations such as improved root traits, reduced radiation absorption, stomatal conductance, leaf area, or changes in leaf orientation (Price et al., 2002). Drought tolerance is the plant’s capacity to maintain its metabolic activity while enduring water deficit and low tissue water potential (Ingram and Bartels, 1996). Osmotic adjustment is one strategy to alleviate drought stress effects. The accumulation of compatible osmolytes and solutes can sustain cell structure and photosynthesis at low water potentials, delay leaf senescence, and even improve root growth as drought severity increases. The hydrophilic nature of these osmolytes increases water availability by trapping water molecules when water is scarce. Thus, osmolytes help maintain osmotic potential and cellular turgidity. Proline, glycine betaine, sugars, and sugar alcohols are some of the most common compatible solutes. Sugars help stabilize membranes, and together with other molecules such as late embryogenesis abundant (LEA) proteins, prevent membrane fusion. For example, the accumulation of trehalose aids in the regulation of the carbon metabolism and photosynthesis during drought (Itturiaga et al., 2009). These solutes can also have an additional role, that of managing oxidative stress by suppressing reactive oxygen species (ROS) production (Chen and Murata, 2002; Bartels and Sunkar, 2005; Turner et al., 2001).

2.1 ROS production and antioxidants as a means for drought tolerance Dehydration leads to increased ROS production, either as singlet oxygen, superoxide anion radicals, hydroxyl radicals, or hydrogen peroxide forms (Bartels, 2001). Because ROS production mainly occurs in the chloroplast, the plant’s photosynthetic activity is greatly affected (Kranner, 2002; Montero-Tavera et al., 2008). The main harm caused by ROS is due to its high reactivity and toxicity, which can damage biomolecules in the cell. This leads to an arrested cellular metabolism because of protein degradation and enzyme inactivation. Eventually, ROS damage will lead to cell death (Gill and Tuteja, 2010). During increased ROS formation, plants protect themselves by employing enzymatic antioxidant defense systems that include a variety of scavengers such as superoxide dismutase (SOD), ascorbate peroxidase (APX), glutathione peroxidase (GPX), glutathione S-transferase (GST), and catalase (CAT) as well as nonenzymatic low molecular metabolites such as ascorbic acid (ASH), glutathione (GSH), α-tocopherol, carotenoids, and flavonoids (Mittler et al., 2004). SOD is believed to be the most effective enzymatic antioxidant, providing the first line of defense against elevated ROS levels. Catalases (CAT) are tetrameric heme-containing enzymes that can directly dismutate H2O2 into H2O and O2. They remove H2O2 generated by oxidases during β-oxidation of fatty acids, photorespiration, and purine catabolism in the peroxisomes (Mallick and Mohn, 2000; Garg and Manchanda, 2009). Peroxidases are localized in the cytosol, vacuole, and extracellular space. These enzymes catalyze the scavenging of H2O2 by oxidation of substrates. Of these, the most commonly known are GPXs, which catalyze the reduction of H2O2, organic hyperoxides, and lipid peroxides in the presence of the hydrogen donor GSH (Ursini et al., 1995). APXs utilize ascorbate as the electron donor. Also, GSTs are a large group of multifunctional enzymes involved in processes such as hormone homeostasis, hydroxyperoxide detoxification, tyrosine metabolism, and herbicide detoxification as well as in response to biotic and abiotic stresses. GSTs catalyze the conjugation of electrophilic xenobiotic substrates with GSH (Dixon et al., 2010). GSTs are abundant proteins predominantly found in the cytoplasm. They can also reduce peroxides that can destroy DNA, RNA, and proteins (Noctor et al., 2002). Additionally, enzymes that regenerate the molecules used by peroxidases are also important components for ROS defense. Glutathione reductases (GR), monodehydroascorbate reductase (MDHAR), and dehydroascorbate reductase (DHAR) all work toward the regeneration of glutathione and ascorbate. The spatiotemporal expression pattern of these sets of enzymes is complex (Willekens et al., 1997). Under stress, some of these enzymes are observed to be upregulated (Sharma and Dubey, 2005; Eltayeb et al., 2007; Ushimaru et al., 1995; Chen and Gallie, 2005; Kwon et al., 2003). For example, plant GPX mRNA levels are known to increase during different environmental stresses, for example in the moss Tortula ruralis under drought stress (Dhindsa, 1991) and in citrus under salt treatment (Avsian-Kretchmer et al., 1999). Meanwhile, a decrease in the activities of GR, MDHAR, and DHAR enzymes leads to stress susceptibility (Ding et al., 2009). Higher chloroplast APX activity was observed in drought-stressed plants (Sharma and Dubey, 2005). Overexpression of APX in Nicotiana tabacum chloroplast enhanced salt-stress and waterdeficit tolerance (Badawi et al., 2004). The plant CAT isozyme expression under stress is regulated by the presence of antioxidant or hormone-responsive elements in their promoters to have a protective role in osmotic and oxidative stress (Polidoros and Scandalios, 1999; Guan and Scandalios, 2000). Phytohormones thus have a crucial role under stress.

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2.2 Phytohormones in drought stress response Plants depend on their ability for fast and highly adapted responses to environmental stresses. Such responses are facilitated by various chemical compounds that serve as signals for the plant to take remedial actions under stress. Hormones are the main class of such compounds (Chen and Murata, 2002; Browse, 2009). Hormones create a signal transduction network that leads to a cascade of processes that enables the physiological adaptation of the plant to stress (Bari and Jones, 2009; Pieterse et al., 2009). Abscisic acid (ABA) plays an important role in the perception of stress, alarming the plant’s defense mechanism to preserve water by stomatal closure and reduced leaf expansion (Davies et al., 2002; Wilkinson and Davies, 2002). ABA also modulates adaptive root traits such as deeper growth and architectural modifications (Spollen et al., 2000; Giuliani et al., 2005) as well as aquaporin-mediated root and shoot hydraulic conductivity for improved water uptake (Parent et al., 2009). ABA also regulates the synthesis of compatible solutes and antioxidants (Chaves et al., 2003). ROS also acts as a signaling molecule in conjunction with ABA, Ca2+, and sugars, which participate in both up- and downstream of ABA-dependent signal transduction pathways during drought (Kwak et al., 2006). At the molecular level, ABA is involved in the transcriptional regulation of several drought-responsive genes and transcription factors such as DREB1/ CBF (drought-responsive element binding protein 1/C-repeat binding factor), DREB2, AREB (ABA-responsive element binding protein), ABF (ABRE-binding factor), and ABI5 (ABA-insensitive 5; Zhang et al., 2006; Kohli et al., 2013). In rice, the ABA-regulated bZIP-TF ABI5-Like1 (ABL1) is induced by salinity and drought. ABL1 then activates several stress response genes such as WRKY (Kohli et al., 2013). The binding of AREB1, AREB2, and ABF3 to the promoter sequence of DREB2A activates the protein to facilitate drought response (Kim et al., 2011a, b). Jasmonic acid (JA) signaling in response to drought stress has been reported in different species. Endogenous JA concentrations increase under stress and elicit the expression of JA-induced proteins, as observed in barley (Lehmann, 1995; Kramell et al., 2000), corn (Xin et al., 1997), and strawberry (Wang, 1999). In rice, JA has a negative regulatory role in drought tolerance (Riemann et al., 2015; Dhakarey et al., 2017). SA is another phenolic compound widely used in plants as an important signaling molecule for stress response (Raskin et al., 1990). The SA concentration increases with water stress and this helps maintain cell membrane integrity and elicit the production of proline in barley (Bandurska et al., 2003). The exogenous application of SA also mitigates stress. Application of SA to tomato and bean enhanced drought tolerance, but this effect tapers off at higher concentrations (Senaratna et al., 2000). SA also has the effect of increasing dry matter accumulation, SOD activity, and total chlorophyll content, as observed in wheat (Hamada and Al-Hakimi, 2001; Singh and Usha, 2003). One of the main effects of SA application is the increased protection from oxidative stress, as it increases SOD and CAT activity, as observed in wheat and barley (Ananieva et al., 2002; Krantev et al., 2008). Strigolactones (SL) were first characterized as seed germination stimulants in the root parasitic plants Striga, Orobanche, and the Phelipanche species (Xie et al., 2010; Ruyter-Spira et al., 2013). Ha et al. (2014) demonstrated that SL also acts as a positive regulator of stress signaling networks, working in conjunction with ABA. It regulates the expression of many stress- and/or ABA-responsive genes involved in abiotic stress response, indicating crosstalk between SL and ABA. Similarly, brassinosteroids (BRs) function both in regulating plant growth and development and in biotic and abiotic stress response (Sasse, 2003; Krishna, 2003). In general, BR enhances the tolerance of plants to heat, cold, drought, and salinity stresses. Its induction is correlated to a higher expression of stress-inducible genes such as heat shock protein genes, RD29, and ERD10, indicating its importance in stress response (Dhaubhadel et al., 1999, 2002; Kagale et al., 2007; Koh et al., 2007). Drought-stressed rice seedlings treated with BR showed improved water economy and CO2 assimilation, improving survival under drought (Farooq et al., 2009). Similar results were observed in tomato, wherein BR treatment increased the relative water content and net photosynthetic rate under drought stress. BR also increased the ABA levels and activities of antioxidant enzymes (CAR, APX, and SOD) and decreased CO2 concentration and H2O2 (Yuan et al., 2010).

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Connecting physiological and molecular responses to drought

3.1 Drought-inducible proteins Plants respond to drought at the organismal level by altering growth and development and by changing water and nutrient accumulation/translocation. These changes manifest into altered physiological processes such as photosynthesis and water and nutrient use efficiency. Along with small molecule metabolites, the main molecular machinery underlying these changes is the differential content of the biomolecules of RNA and protein. Proteins can function to protect other proteins and membranes from damage or even directly form molecular conduits for water and nutrients. LEA and dehydrin proteins are examples of such protective proteins. LEAs are activated through

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ABA-responsive elements (ABREs) and low-temperature responsive elements (LTREs) in their promoters (Hundertmark and Hincha, 2008). HVA, an example of such LEA proteins, is inducible by different stresses such as salt, cold, and dehydration as well as through the action of ABA. The expression of HVA1 under stress helps stabilize proteins to increase water use efficiency and allow root growth and development (Chen et al., 2015). LEAs and dehydrins act as chaperones to protect the structural integrity of the proteins by replacing hydrogen bonds generally formed with water. The presence of functional structures of proteins helps in early recovery from stress because when water is available, these proteins become functional by water forming those hydrogen bonds again by replacing the dehydrins. The functional proteins do not have to be synthesized de novo, which saves resources, energy, and time, and the plant can initiate survival mechanisms immediately. On the other hand, aquaporins form water channel proteins that facilitate water transport through vacuolar and plasma membranes (Maurel, 1997). They are involved in the opening and closing of cellular gates, directly affecting cellular water balance and water use efficiency (Tyerman et al., 2002; Martre et al., 2002; Maurel, 2007). Aquaporins are classified into four major subfamilies: plasma membrane intrinsic proteins (PIPs), tonoplast intrinsic proteins (TIPs), Nod26-like intrinsic proteins (NIPs), and small and basic intrinsic proteins (SIPs). In rice, 33 aquaporin genes were identified through genome sequencing (Oryza sativa L cv. Nipponbare). These genes showed organ-specific expression throughout the plant’s life cycle. Specifically, OsPIP2;4 and OsPIP2;5 had significant water channel activity, especially in the roots (Sakurai et al., 2005). Members of the subgroup PIP1 have been shown to improve stress tolerance, such as in the example of OsPIP1;1 in rice, TdPIP1;1 in durum wheat, and TaAQP in tobacco (Liu et al., 2013; Ayadi et al., 2011; Hu et al., 2012). Other classes of proteins and RNA that come into play for drought tolerance affect gene expression, protein modification, or protein stability that feed into the structure–function modification of proteins under different conditions. The most popular examples of such protein classes are the transcription factors, kinases, and micro-RNAs.

3.2 Transcription factors The complexity of drought response is emphasized by changes in the expression of a multitude of genes in response to most abiotic stresses. These gene expression variables are controlled by transcription factors (TF; Chen et al., 2012). Examples of TF families well known to be involved in stress response include WRKY, zinc finger (ZF), basic leucine zippers (bZIP), AP2/EREBP (Apetala2/Ethylene-responsive element binding proteins), MYB (myeloblastosis), and NAC (NAM-ATAF1/ 2-CUC2) proteins. NAC is one of the largest families of plant-specific TFs. In rice, tissue-specific and stress-responsive NAC genes have been identified (Fang et al., 2008; Ooka et al., 2003). In Arabidopsis, AtNAC072, AtNAC019, AtNAC055, and AtNAC102 have been identified to respond to drought, salinity, cold, and submergence (Fujita et al., 2004; Tran et al., 2004; Christianson et al., 2009). Stress NACs (SNAC) such as SNAC1, SNAC2/OsNAC6, OsNAC5, and OsNAC10 have been identified as expressed in response to abiotic stresses (Hu et al., 2006; Nakashima et al., 2007; Sperotto et al., 2009; Zheng et al., 2009; Jeong et al., 2010). In rice, OsNAC5 was upregulated in the flag leaf during rice grain filling (Sperotto et al., 2009) while OsNAC6 greatly improved dehydration tolerance (Nakashima et al., 2007). The overexpression of SNAC1 resulted in enhanced drought tolerance at the reproductive stage. The SNAC overexpression transgenic line exhibited rapid stomatal closure and slow leaf water loss compared to the wild-type (Hu et al., 2006). SNAC1 also contributed to the maintenance of turgor pressure at a significantly lower level of relative water content. The overexpression of ONAC045 showed increased drought and salt tolerance (DST) (Zheng et al., 2009). Root-specific expression of OsNAC10 resulted in enlarged roots, leading to enhanced drought tolerance and a significant increase in grain yield under field drought conditions ( Jeong et al., 2010). OsNAM12.1 was found to be a regulatory hub for drought response affecting root and panicle traits (Dixit et al., 2015b). The basic leucine zipper (bZIP) subfamily of TFs makes up one of the largest TF families in plants. Members include ABA-responsive element-binding factors or ABA-responsive element binding proteins (ABF/AREB) with significant roles in the ABA-dependent regulation of drought, salinity, and cold tolerance in Arabidopsis (Nakashima et al., 2007). In rice, 89 bZIP transcription factors have been identified in the variety IR64, with several bZIPs shown to be responsive to abiotic stresses (Nijhawan et al., 2008). The expression of bZIPs is also induced by ABA, which means that it also serves to amplify the signals provided by ABA. Constitutive activation of the rice bZIP genes bZIP23 and bZIP46 augmented ABA sensitivity and stress-related gene expression (Xiang et al., 2008; Tang et al., 2012). OsB28, OsbZIP23, and OsbZIP72 are believed to be involved in an ABA-dependent drought signal transduction (Nakagawa et al., 1996; Xiang et al., 2008; Lu et al., 2009). The signal transduction facilitated by bZIP members has been reported to increase drought tolerance, as observed in the case of OsbZIP16 (Chen et al., 2012). MYB (myeloblastosis-related proteins) and MYC (myelocytomatosis-related proteins) family members have been shown to activate ABA-dependent regulatory systems (Valliyodan and Nguyen, 2006). The MYB family is a large family

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of transcription factors in plants. There are 198 MYB genes in Arabidopsis and 183 MYB genes in rice (Chen et al., 2006), most of which are observed to be responsive to abiotic stresses. MYB and MYC induction is observed after ABA accumulation. Transcriptome analysis shows that their target genes include ABA- or JA-inducible genes (Abe et al., 2003). For example, the overexpression of AtMYC2 and AtMYB2 in Arabidopsis resulted in hypersensitivity to ABA as well as improved osmotic stress tolerance (Shinozaki and Yamaguchi-Shinozaki, 2007; Gao et al., 2011). OsMYB48-1 regulates the expression of some ABA biosynthesis genes, early signaling genes, and late response genes (Xiong et al., 2014). Similarly, zinc finger proteins are one of the largest groups of transcription factors in eukaryotes (Kubo et al., 1998). The overexpression of the Cys2/His2-type (C2H2) zinc finger proteins activates some stress-related genes and leads to enhanced tolerance to salt, dehydration, and/or cold stress (Sakamoto et al., 2004). Other examples of zinc finger proteins induced by stress include ZFP245 and ZFP252, which are important in cold and drought response (Huang et al., 2005; Xu et al., 2008). Physiological processes, such as stomatal closure, are also controlled by zinc finger proteins. For example, a DST gene was found to negatively regulate stomatal closure under salt and drought stress in rice by regulating genes involved in ROS homeostasis (Huang et al., 2009). The overexpression of OsRZFP34 also increased relative stomatal opening (Hsu et al., 2014). Another RZFP, OsCOIN, is strongly induced by low temperature, ABA, salt, and drought. The overexpression of OsCOIN lines showed significantly increased tolerance to cold, salt, and drought as well as the upregulation of OsP5CS expression, leading to elevated cellular proline levels (Liu et al., 2007). The WRKY family of transcription factors is widely known to be involved in many processes, including plant development as well as plant responses to biotic and abiotic stresses ( Jang et al., 2010). These proteins are defined by the WRKY domain, which specifically binds to the W-box-type [(T)TGCA(C/T] DNA sequence elements (Du and Chen, 2000). WRKY members are transcriptional activators, repressors, or can act as both (Rushton et al., 2012). The function may depend on the protein a WRKY is interacting with, which may be MAP kinases, 14-3-3 proteins, calmodulins, histone deacetylases (HDACs), other resistance proteins, or other WRKYs (Rushton et al., 2010). Seventy-four WRKY genes were found in Arabidopsis through a genome-wide search (AtWRKY1 to AtWRKY74; Eulgem et al., 2000). Microarray data showed that WRKY expression is upregulated by drought, cold, and salinity stresses (Fowler and Thomashow, 2002; Seki et al., 2002). Twenty-four rice WRKY genes were reported to be induced seven-fold by osmotic stress, flooding, or drought (Berri et al., 2009; Wu et al., 2009). The AP2/ERF (Apetala2/ethylene response factor) superfamily of transcription factors is defined by the AP2/ERF domain, a DNA-binding domain consisting of 60–70 amino acids. This gene superfamily includes some of the most well-known stress-responsive transcription factors. The ERF gene subfamily is further divided into two major subfamilies: ERF and DREB. ERF proteins have major roles in transcriptional regulation of a variety of biological processes related to growth and development and in response to environmental stimuli (Nakano et al., 2006), specifically in hormonal signal transduction (Ohme-Takagi and Shinshi, 1995) in response to abiotic stresses (Stockinger et al., 1997; Liu et al., 1998; Dubouzet et al., 2003). Many experiments with transgenic plants for ERF genes have validated their roles in the response to drought and other stresses. For example, SlERF5 conferred high tolerance to drought and salt stress in the transgenic tomato plants (Pan et al., 2012). The same phenomenon was observed when other tomato ERF genes such as TERF1 and JERF1 were overexpressed in rice and tobacco. The overexpression of these genes resulted in the accumulation of osmolytes, the reduction of water loss, and the activation of oxidative stress-responsive genes (Gao et al., 2008; Wu et al., 2008). A dehydration-responsive element (DRE) was identified as a cis-acting promoter element in regulating gene expression in response to drought, high salt, and cold stresses in Arabidopsis. DRE is essential for the expression of rd29A, a droughtresponsive promoter gene under stress (Yamaguchi-Shinozaki and Shinozaki, 1994). DRE-binding proteins CBF1, DREB1A, and DREB2A bind specifically to the DRE/CRT (CRT: C-repeat) sequence and activate the transcription of genes driven by the DRE/CRT sequence in Arabidopsis (Dubouzet et al., 2003). Constitutive expression of CBF3/DREB1A in japonica rice (cv. Nakdong; Oh et al., 2005) and indica rice (cv. BR29; Datta et al., 2012) improved drought stress tolerance. The overexpression of CBF3/DREB1A has also improved the drought tolerance of rice megavarieties such as Samba Mahsuri. Physiological tests showed that AtDREB1A is associated with increased accumulation of proline, chlorophyll maintenance, increased relative water content and decreased ion leakage (Ravikumar et al., 2014).

3.3 Kinases Kinases affect one of the most important functional groups, especially in the context of drought stress response. Kinases such as the mitogen-activated protein kinases (MAPK), calcium-dependent protein kinases (CDPK), and receptor-like kinases (RLK) were reported to regulate drought stress tolerance (Fukao and Xiong, 2013). MAPK cascades are evolutionarily conserved in all eukaryotic organisms. The basic components of the cascade are comprised of a distinct combination of

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at least three protein kinases: MAPKKK (MAPK/MEKK/MKKK), a MAPKK (MKK/MEK), and a MAPK (MPK), which sequentially activate the succeeding kinase via phosphorylation (Colcombert and Hirt, 2008). The MAPK cascade is an important signaling pathway that transduces extracellular stimuli intracellularly, regulating cellular signaling for processes related to growth and development as well as stress response (Rohila and Yang, 2007). The action of the MAPK cascade results in the phosphorylation of specific protein targets and the modulation of the activities of different functional protein groups in response to stimuli (Taj et al., 2010). For example, the MKKK gene DSM1 was reported to confer drought stress tolerance in rice by regulating ROS scavenging (Ning et al., 2010). Plant MAPK cascades can also interact with transcription factors, such as WRKY, to regulate downstream gene expression in response to biotic and abiotic stresses (Andreasson et al., 2012; Shen et al., 2012). In plants, Ca2+ acts as a universal messenger in numerous signal transduction pathways, including abiotic stress responses (Frohnmeyer et al., 1999; Kim et al., 2003). Thus, kinases that act to sense Ca2+ are also involved in stress response. These include CDPKs (Sheen, 1996), sucrose nonfermentation-related kinases (SnRKs; Fujii and Zhu, 2012), and the calcineurin B-like protein-interacting protein kinase (CIPK) subfamily (Shi et al., 1999). SnRKs are composed of 38 members grouped into three subfamilies: SnRK1, SnRK2, and SnRK3. SnRK1 is involved in the regulation of carbon metabolism and energy status while SNRK2 and SnRK3 regulate ABA-mediated signaling pathways (Coello et al., 2011). This happens in part through their interaction with AREBPs (ABA-response element binding proteins), which are their targets for phosphorylation (Coello et al., 2012). The CIPK signaling pathway is implicated in various abiotic stress responses (Kim et al., 2003; Kolukisaoglu et al., 2004). Thirty putative OsCIPK genes in rice were analyzed for their transcriptional responses to various abiotic stresses including drought, and 20 were found to be differentially induced by stress treatment. Overexpression lines containing OsCIPK03, OsCIPK12, and OsCIPK15 all showed improved tolerance to cold, drought, and salt stress, respectively (Xiang et al., 2007). CDPKs are also induced by different stress treatments. For example, gene overexpression and knockdown analyses of OsCPK9 revealed its positive role in drought stress tolerance and spikelet fertility, which manifests through increased stomatal closure, osmotic adjustment ability, pollen viability, and enhanced ABA sensitivity in overexpression lines (Wei et al., 2014). Another kinase, OsCPK4, was induced by salinity, drought, and ABA. Overexpression of the gene showed stronger water-holding capacity, and reduced levels of membrane lipid peroxidation and electrolyte leakage under drought and salinity stresses, which increased the tolerance of the overexpression. These suggest that OsCPK4 upregulates genes involved in the lipid metabolism and protection against oxidative stress (Campo et al., 2014).

3.4 Micro-RNAs Plant response can also be regulated posttranscriptionally by micro-RNAs (miRNAs). MiRNAs are known to play various important roles at each major stage of development, targeting regulatory genes such as those encoding TFs ( Jones-Rhoades et al., 2006). MiRNAs are single-stranded RNAs usually 20–24 nucleotides in size. They serve as gene regulators in a wide range of organisms and play key roles in plant responses to biotic and abiotic stresses. Studies revealed that the expression of miRNAs is altered in plants during drought stress (Ferdous et al., 2015). miRNAs regulate their target genes via cleavage and translational repression of target mRNAs (Bartel, 2004; Du and Zamore, 2005). miRNAs whose expressions are modulated by drought have been identified through transcriptome analysis (Zhou et al., 2010). Though nonprotein coding, these miRNAs are indeed genes and thus are also controlled by transcriptional cascades. For example, miR-169 g was discovered to be part of the CBF/DREB network based on the presence of DREs in its promoter (Zhao et al., 2007). It can then be inferred that miRNAs are used as another layer of control for the signaling cascade. MiRNAs allow for optimal expression of the genes involved in the cascade, despite not being proteins participating in the cascade itself. Just like protein modification such as phosphorylation alters its stability, interaction, or function, the modification of DNA also plays into regulating gene expression. Such a control through DNA and protein modification with methylation or acetylation is called epigenetic control.

3.5 Role of epigenetic response to abiotic stress Apart from the information contained in an organism’s genome for gene expression, variations in chromosome configuration that occur through changes in histone protein and DNA methylation can affect gene expression. Enzymes such as histone acetyltransferase (HAT), HDAC, histone methyltransferase (HMT), and histone demethylase (HDM) all function to modify the N-terminal tails of the histones (Kim et al., 2010). Thus, it is not surprising that gene regulation for stress response is also associated with histone modifications. Modifications that serve to loosen histone binding to DNA such as acetylation, phosphorylation, or ubiquitination enhance transcription. Processes that close histone binding such as

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biotinylation and sumoylation repress gene expression (Shiio and Eisenman, 2003; Filenko et al., 2011). Methylation of histones controls transcription depending on the context. For example, trimethylation of histone H3K4 activates while demethylation of H3K9 and H3K27 represses transcription (Chinnusamy and Zhu, 2009). There are many cases wherein histone modification enzymes show roles in stress response. In Arabidopsis, HDA6 and HDA19 mediate histone deacetylation in response to biotic and abiotic stresses. HDA6 is induced by JA and ethylene (Zhou et al., 2005) while the HDA19 protein is involved in transcriptional gene silencing (Probst et al., 2004). AtHD2C is a histone deacetylase downregulated by ABA. The overexpression of AtHD2C showed enhanced expression of ABA-responsive genes and better tolerance to salt and drought, suggesting that histone deacetylation has an important role in ABA and stress response (Sridha and Wu, 2006). Drought-induced expression of stress-responsive genes also increased H3K4 trimethylation and H3K9 acetylation (Kim et al., 2008). Different members of HDAC in rice showed differential regulation in response to cold, salt, osmotic stress, and the hormones ABA, JA, and SA (Fu et al., 2007). DNA methylation in plants is regulated by various physiological, developmental, and stress stimuli. Methylation patterns that are retained through different cell cycles may be referred to as “epigenetic memory,” as it is possible to reinstate the DNA methylation state in daughter cells after replication. The level of DNA methylation differs from each plant species, and can also be controlled by hormonal fluxes, which in turn can be affected by various stresses (Steward et al., 2000; Zhang et al., 2012). This process can occur at both the promoter and the gene body (Finnegan et al., 1998). Methylation can be asymmetric or symmetric and is catalyzed by DNA methyltransferases and DNA demethylation enzymes: DRM1 (DOMAINS REARRANGED METHYLASE 1), DRM2, MET1, and the plant-specific chromomethylase 3 (CMT3; Henderson and Jacobsen, 2007). Stress can cause changes in gene expression through hypomethylation or hypermethylation of DNA. For instance, drought stress is known to induce hypermethylation in the pea (Labra et al., 2002). Plants growing under stress conditions can exhibit transgenerational inheritance of DNA-methylation patterns. This “stress memory” serves to create important epigenetic plasticity that allows response to stress both in the immediate short term and for long-term acclimatization (Mirouze and Paskowski, 2011). In rice, salt-tolerant genotypes showed hypermethylation while salt-sensitive ones showed demethylation, indicating that DNA methylation remodeling may play a role in conditioning for salt stress tolerance (Feng et al., 2012). DNA methylation-sensitive amplified polymorphism (MSAP) analysis revealed that drought induced 2.1% of total site-specific methylation differences that were genome-wide, across genotypes, tissues, and developmental stages (Wang et al., 2011). Small interfering RNAs (siRNA) have a role in epigenetic regulation in response to biotic and abiotic stresses via transcriptional gene silencing through RNA-directed DNA methylation (RdDM; Henderson and Jacobsen, 2007). These are distinct from miRNA and may arise from repeats, transposons, or noncoding regions of the genome as opposed to miRNAs, which are genuine genes. The ability of a genomic region to produce small RNAs and its propensity for DNA methylation is highly correlated. siRNAs are responsible for methylation of at least one-third of all methylated loci (Lister et al., 2008). Temperature and other abiotic stresses can regulate specific small RNAs. In Arabidopsis, endogenous siRNAs found to be regulated by abiotic stresses have been identified (Sunkar and Zhu, 2004).

3.6 Novel molecular targets and processes for drought tolerance Apart from the protein classes and their functions listed above, additional candidates of protein classes could be explored whose role is critical. For example, any natural system would react to stress for survival through resource utilization efficiency and economy. Protein posttranslational modifications (PTMs) that occur during stress are a good example for functional agility with resident proteins without the need to synthesize new ones. The genes involved in these PTMs may then be useful targets for manipulation (see Chapter 23). Such manipulation can now be done in a much improved and safe manner through the gene editing processes. The continuous improvement of gene editing tools (ZFNs, TALENs, CRISPR-Cas9) has been fascinating and truly advantageous. CRISPR-Cas9 has greatly increased the precision and efficiency of targeting and manipulating specific genes, revolutionizing genetic studies and crop breeding (Zaidi et al., 2019). Recently, cell-penetrating peptides (CPPs) were developed as a way to accurately deliver molecules to specific organelles in a cell. In plants, it was shown that CPPs were viable for uptake by tobacco protoplasts, Arabidopsis plants, and Arabidopsis pollen, indicating that CPP was not hindered by the cell wall. However, CPPs are targets for proteolytic degradation in vivo. To prevent degradation, an alternative peptide mimetic was produced by linking the cationic amino acid side chain to the amide N instead of the α-C of the peptide bond, rendering it resistant to proteolytic digestion. The resulting peptoid can then be used to carry molecules to the cell. In the study by Asfaw et al. (2019), the peptoid was linked with coenzyme Q10 (PeptoQ) and was taken up by the cell via endocytosis. PeptoQ, which is localized in the mitochondria, interacted with the electron transport chain in the mitochondrial membrane and acted as an antioxidant during salt stress-induced oxidative stress. It improved redox homeostasis under salinity stress and alleviated stress-induced

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programmed cell death. The technology presents a method for understanding the role of the plasma membrane and the mitochondria as key organelles during oxidative stress. Further understanding of these mechanisms to mitigate the damage incurred by the organelles during stress will hasten the identification of genes that can then be targeted in breeding programs.

4 Breeding for drought tolerance Breeding for tolerance entails the identification and then selection of traits in the introgression breeding program ( Jackson et al., 1996; Kaloki et al., 2019). Traits should be highly heritable, easy to measure, and correlated to yield (Monneveux and Ribaut, 2006). The trait must not have pleiotropic effects on other economically important qualities (Richards, 2006). Traits that can be measured accurately with nondestructive phenotyping methods are preferred. However, dealing with large plant populations and different traits can be quite labor-intensive and expensive. The development of high-throughput phenotyping (HTP) platforms aims to overcome such challenges. Examples of such phenotyping methods include near infrared (NIR) spectroscopy that can capture differences in crude proteins, starch, and dry matter; and multispectral reflectance used to measure canopy architecture, water status, and nitrogen content (Montes et al., 2007). Because breeding for improved drought resistance must be based on the stability of yield components and not just on survival, the most efficient method is to select for yield and its components under reproductive drought stress. The ideal phenotype should have high yield potential under well-watered (normal) conditions, and reduced yield penalty under drought. Therefore, it is important to identify essential mechanisms and genes that regulate yield under drought stress that will not affect yield through linkage drag under normal conditions (Basu et al., 2016). For example, improved rice varieties from the Green Revolution are selected for ideal environments and have minimal tolerance to abiotic stresses. In the case of drought, improvement of these high-yielding rice varieties was difficult due to the tight linkage of genes/QTLs for drought tolerance with those for shorter plant height (i.e., semidwarfing gene sd1; Vikram et al., 2015). It has been long recognized that drought tolerance is a multigenic trait that operates at different levels of regulation. The expression of the relevant genes is affected by the variety and the duration, timing, and severity of drought stress. In particular, drought stress at the reproductive stage is of high importance as yield is greatly reduced when this occurs (Lanceras et al., 2004; Bernier et al., 2008). There is thus a complex interaction between genes involved in drought tolerance with those involved in grain yield potential (Price et al., 2002). A simplistic view is that a number of QTLs may be involved that would need to be pyramided. Thus, varieties that showed drought tolerance and acceptable yield under drought were used as sources of genes and quantitative trait loci (QTL) for the improvement of high-quality yet susceptible genotypes. Several QTLs have been identified and mapped: qDTY1.1 (Vikram et al., 2011; Ghimire et al., 2012), qDTY2.1, qDTY3.1 (Venuprasad et al., 2009), qDTY2.2, qDTY4.1, qDTY9.1, qDTY10.1 (Swamy et al., 2013), qDTY3.2 (Vikram et al., 2011), qDTY6.1 (Dixit et al., 2014), and qDTY12.1 (Bernier et al., 2007). The consistent effects of these QTLs across different genetic backgrounds make them valuable for marker-assisted breeding. Most of these QTLs were shown to have large effects under drought stress at different stages and have also been successfully pyramided in popular rice megavarieties (Swamy and Kumar, 2013). An important understanding could arise from these QTLs whose physiological and molecular basis could be integrated to reveal the value in selecting the trait and associated genes for the breeding program.

4.1 The case of the QTL qDTY12.1 The QTL qDTY12.1 leads to increased yield under drought as compared to the negligible yield without this QTL. Interestingly, it showed a consistent effect across different environments, genotypes, growth stages, and ecogeographies (Mishra et al., 2013). It was identified under upland conditions in a cross between the drought-tolerant variety Vandana and the drought-susceptible variety Way Rarem (Bernier et al., 2007). Dixit et al. (2012) used backcross-derived populations to fine map qDTY12.1. The QTL was identified from the susceptible parent Way Rarem, and it reduced the yield penalty suffered by Vandana under drought. Epistatic interactions were hypothesized to explain this observation (Dixit et al., 2012). Molecular analysis of qDTY12.1 showed possible epistasis occurring in the genes within the QTL as well as between genes within qDTY12.1 and other chromosomes (Dixit et al., 2015a). Allelic analysis of qDTY12.1 showed its interaction with a drought-responsive major flowering locus qDTY3.2, resulting in a reduction in flowering duration during stress (Vikram et al., 2016). Several putative candidate genes were determined upon in silico analysis of qDTY12.1. Expression analysis of these candidate genes showed the upregulation of the transcription factor OsNAM12.1 (No Apical Meristem) in the flag leaf, leaf, panicle, and roots of drought-stressed plants at the reproductive stage. Further analyses showed the central role of OsNAM12.1 in controlling multiple colocalized genes within the QTL (Dixit et al., 2015b). These genes are annotated for various functions, highlighting the multigenic and multitrait nature of drought tolerance. In addition, OsNAM12.1 has been

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found to be posttranslationally modified. This implies that genes in the background genome are essential to make the protein function toward helping maintain yield under drought. Comparison of the parental and NILs for the transcriptomic, metabolomic, and proteomic responses further illustrated the role of various genes, proteins, and metabolites affected in a networked response by the introgression of the QTL in different tissues (Dixit et al., 2015b; Raorane et al., 2015a, b). Such a simultaneous multitissue comparison clearly illustrated that the role of the same molecular factor may not be the same in different tissues in response to drought. Importantly, physiological traits and genes related to root and panicle architecture, water use efficiency, flowering, and yield could be implicated from within the same QTL. Fortunately, the grain quality of the NILs was of an acceptable nature and this allowed for the QTL to be taken up in the breeding program to deliver drought-tolerant lines that were directly commercially useful. In rice breeding, varieties have been bred and released for higher yield potential and resistance to stresses, without a high priority on grain quality (Pang et al., 2016). Ideally, high yield must be coupled with consumer-accepted rice grain quality (Sreenivasulu et al., 2015). This entails having the two most important traits in consumer acceptance, namely uniformity in grain shape and translucent endosperm. In an assessment of consumer-preferred rice in two rural towns in the Philippines, the consumers preferred rice with long and slender grains (Cuevas et al., 2016). Zhao et al. (2015) identified markers that are associated with grain quality traits while Pang et al. (2016) identified rice cultivars that contain similar eating and cooking quality components to those of high-quality rice varieties. Breeding for a minimum of three complex traits of yield, stress tolerance, and grain quality simultaneously under the increasing pressures of time and resources is a Herculean task. However, the upcoming digital technologies can make such tasks somewhat amenable.

4.2 Big data analytics for efficient breeding The world’s population is projected to reach 10 billion by the year 2050, and plant breeders are faced with the enormous task of ensuring food and nutritional security for all. This task is made more difficult by the continuously decreasing land, labor, and resources and the looming threat of climate change. Thus, this endeavor needs to leverage all novel strategies and innovative technologies (Rao, 2018; Delgado et al., 2019). Developments in several areas such as crop genomics, phenomics, remote sensing, and other sensor technologies have been adopted for high-throughput precision agriculture (Shakoor et al., 2019). HTP is a valuable tool that aids in the rapid advancement of genetic gain in breeding programs (Zhao et al., 2019). The use of these technologies leads to the generation of extremely large datasets spread across disciplines and space that need to be efficiently curated, annotated, and analyzed (Ma et al., 2014). The challenge, however, is for the breeders, physiologists, molecular biologists, and bioinformatics community to effectively create, analyze, and use this big data for novel information (Ma et al., 2014). The 3K rice genomes project is a good example of how massive amounts of data can be used to streamline selection processes and candidate gene identification. This project undertook the resequencing of 3010 cultivated rice accessions from 89 countries with the aim of building a large-scale information database for the discovery of novel alleles for plant breeding (3K Genomes Project, 2014). Data revealed genetic variations among the accessions as shown by 29 million SNPs (single nucleotide polymorphisms), 2.4 million small InDels, and 90,000 structural variations (Wang et al., 2018; Fuentes et al., 2019). These variations are important sources of information for targeting traits or genes for subsequent marker-aided selection or genetic engineering as well as for elucidating molecular mechanisms that govern the trait or targeted responses (Fuentes et al., 2019). Additionally, nearly 1000 genotypes of wild and cultivated species have now been sequenced and analyzed for variations. This dataset is now being complemented with extensive phenotyping of the sequenced genotypes. The phenotyping effort will create datasets in the same magnitude as the 3K genomes, and the next task will be association analysis for identifying key genes to desired traits. For example, Campbell et al. (2017) performed a genome-wide association study on 383 different genotypes for low salt concentration in roots, which allowed them to identify desirable alleles of OsHKT1;1. Similarly, Wang et al. (2017) utilized the same approach for grain quality traits and found multiple novel QTLs and previously confirmed QTLs. Apart from the integration of phenotyping and genomics, big data analytics can also be applied toward the mechanistic dissection of different traits. Systems-level approaches are essential in identifying the best genetic configuration for a given environment, as each environment can present its own problems. It can also be used to determine gene networks that can be complementary to one another when combined into a genotype. For example, the unique BR gene network in Oryza officinalis presents a viable complementary network that can be integrated to O. sativa, which may improve its cold tolerance (Kitazumi et al., 2018). Another example is the discovery of improved source-sink dynamics in qDTY12.1 NILs that maintained yield under drought (Raorane et al., 2015a, b). The proteomics approach is also utilized in the study conducted by Dhakarey et al. (2017), which showed the negative regulatory effects of JA toward drought resistance. Such integrated

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networks underlying the TFs or phytohormones could only be discovered using systems-level analysis on large genome, transcriptome, proteome, metabolome, and phenome datasets. The possibilities of discoveries that can be made if different large datasets across divisions, institutes, or countries can be combined are staggering, to say the least. With continuous technological improvements, the limiting factor then becomes the analytical power and assigning the biological significance to the computational analysis. This necessitates an extensive capacity building undertaking in bioinformatics with researchers who have a biology background or can take to biology easily.

5 The WISH project: A case study Designing a strategy for improving a trait as complex as drought tolerance depends on gleaning lessons from successes and failures of breeding platforms that have targeted value-added traits. An example of a rice breeding strategy that produced tangible improvements in two quantitative traits, that is, yield and biotic stress resistance, under an international collaborative program is described to illustrate the potential use of a similar approach. Considerations that address the most common bottlenecks in breeding during the implementation of the project are also presented.

5.1 Wonder Rice Initiative for Food Security and Health Realizing the grave challenge of food insecurity, Japan’s Nagoya University and Kyushu University, in collaboration with the International Rice Research Institute (IRRI) in the Philippines, supported by the Japan International Cooperation Agency (JICA) launched the Wonder Rice Initiative for Food Security and Health (WISH) in 2012. This is a collaborative rice breeding effort with the specific goals of increasing the yield and disease resistance of select rice varieties. The major rice-growing regions of the world are targeted and marker-assisted backcrossing technology is being used. The project capitalizes on the results of several years of foundational research by the two universities to identify, fine map, clone, and functionally analyze the genes that regulate yield and disease-resistance traits. For yield traits such as plant height, grain number, and primary branches and spikelets per panicle as well as for disease resistance, diseases such as blast, bacterial blight, and rice yellow mottle virus are targeted. In collaboration with IRRI, WISH began its initial phase of 5-year varietal improvement in January 2013. Parallel breeding programs were conducted at Nagoya University in support of the breeding operations at IRRI. Within the duration of the first phase of the project, target genes for increased grain number (Grain number 1a; Gn1a; Ashikari et al., 2005) and number of primary branches per panicle (Wealthy Farmer’s Panicle; WFP; Miura et al., 2010) as well as for improved resistance against blast caused by Magnaporthe grisea (pi21; Fukuoka and Okuno, 2001; Fukuoka et al., 2009) were successfully transferred by marker-assisted backcrossing. The genes were fixed up to BC3F5-7 and BC4F5-6 into more than 300 WISH lines in the genetic background of rice cultivars that are preferentially grown by farmers across Asia and Africa. Different combinations of the aforementioned genes have also been pyramided in another 300 WISH lines in the same genetic backgrounds (http://motoashikari-lab.com/wp/wp-content/uploads/2018/11/ WISH_catalogue_lite4.pdf). The initial field evaluation of WISH lines bred for increased grain number and number of primary branches per panicle at IRRI showed significant increases in both primary branching per panicle and grain number compared to the recurrent parents used in the program (Fig. 1; Angeles-Shim et al., 2015; Makihara et al., 2017; Yamada et al., 2020). Similarly, results of preliminary field and nursery screening showed an improvement in the spectrum of resistance to blast for WISH lines bred to have pi21, with neither penalty to yield nor to grain quality (Angeles-Shim et al., 2020). By the completion of the initial phase of the project in 2018, around 300 improved WISH lines with individual or combined target genes were distributed to partner agencies, universities, and institutes in Cambodia, Vietnam, Sri Lanka, Myanmar, Nepal, Lao PDR, and Indonesia in Asia as well as in Kenya, Burundi, and Mozambique in Africa. Through these international partnerships, the second phase of WISH, which includes regional testing and further improvement or adoption of the WISH lines, was launched with the support of the Canon Foundation in Japan. Preliminary reports on the field evaluation in Kenya of NERICA rice carrying Gna1 and/or WFP also showed the better yield potential of the improved WISH lines compared to the recurrent parents.

5.2 Addressing common breeding bottlenecks under the WISH program 5.2.1 Speed and cost of varietal improvement In rice, the use of molecular markers to monitor the introgression of one or a few genes of interest in breeding materials has proven effective if marker-trait association was established and validated (Collard and Mackill, 2008). With the 5-year timeframe of WISH to develop advanced breeding lines, marker-assisted selection (MAS) was critical. Genes regulating

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FIG. 1 Plant and panicle morphology of NERICA 1 (A) and BC3F3 lines in the NERICA 1 background having WFP (B) and Gn1a (C). The effects of WFP and Gn1a on the yield and yield components of NERICA 1 are presented in D, E, and F, respectively. Values are means of 35 samples. Bar ¼ 10 cm.

the target traits were identified, cloned, and validated for their phenotypic effects and stability in different backgrounds. The basic genetic, molecular, and physiological research was conducted mostly in the participating universities. IRRI undertook the backcrossing and gene fixing activities through three or four backcrosses to the recurrent parent. The transfer of diseaseresistance genes has been reported to be commonly accompanied by linkage drags that result in cultivar fitness reduction. The quantitative pi21 in particular has been reported to be linked with other genes that are associated with poor eating quality (Fukuoka et al., 2009). Increasing the frequency of backcrossing not only allowed the recovery of a higher proportion of the recurrent genome, but also increased the chances of recombination that can dissociate pi21 with downstream genes causing poor grain quality. Selection of the desirable traits without necessarily recovering 99% of the genetic background of the recurrent parents was useful in reducing time and cost.

5.2.2 Quality of improved rice cultivars To deliver significant varietal improvements, yield components that will produce the maximum impact were selected as breeding targets. The grain number as regulated by Gn1a (Ashikari et al., 2005) and number of primary branches per panicle as controlled by WFP (Miura et al., 2010) were used. The development of near-isogenic lines for both traits confirmed the genetic and phenotype stability of the two genes in different genetic backgrounds under a given environment (Ashikari et al., 2005; Miura et al., 2010). Similarly, while qualitative blast resistance has been widely used in breeding, it is highly race-specific and imposes selection pressure that drives the evolution of new races of the pathogen (Kuo and Wang, 2012). This has caused the breakdown of blast resistance in many cultivars as well as the emergence of new races of the pathogen.

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In contrast, quantitative resistance genes have small effects that confer partial but durable resistance to most races of the same pathogen. Quantitative resistance slows the spread of the disease. The reduced selection pressure has been proposed to provide durability of resistance (Fukuoka and Okuno, 2001; Fukuoka et al., 2009, 2012). Under the WISH project, breeding for blast resistance was incorporated as a quantitative trait to ensure the durability of resistance. Thus, for both yield and blast resistance, the quality of the advanced lines was high.

5.2.3 Acceptability of improved varieties by farmers Consideration of the ecology of the regions where the improved rice cultivars will be grown and the needs of the end users are two primary criteria for the success of any rice breeding program. The experiences in the development and dissemination of submergence-tolerance rice having the Sub1A gene exemplify the importance of considering the needs and preferences of farmers. Sub1A was initially bred into six Asian rice megavarieties, namely Swarna, Sambha Mahsuri, IR64, BR11, Thadokkam1, and CR1009, by marker-assisted backcrossing at IRRI (Mackill et al., 2006; Septiningsih et al., 2009). All the improved varieties performed very well under controlled submergence tests in IRRI, showing significantly higher survival rates compared to the recurrent parents (Septiningsih et al., 2009). Despite this, the adoption of these varieties in the flood-prone target regions of Lao PDR, Indonesia, Philippines, and Vietnam was not as extensive as expected. In fact, in Indonesia where Swarna-Sub1 yielded higher than Ciherang after weeks of inundation, farmers still preferred to grow the latter due to its early maturity, grain shape, plant height, and resistance to disease and not least because of customer demand based on the eating and cooking qualities of Ciherang. This shows that varieties that are preferred by farmers are not necessarily those with the highest yield (Manzanilla et al., 2011). Hence, in the WISH project line for Africa, the New Rice for Africa or (NERICA) lines were selected as targets. For Asia, local cultivars with features preferred by farmers such as Kinandang patong (drought-tolerant), Azucena (drought-tolerant), and Basmati (aromatic) were targeted for improvement. The ongoing field testing of improved WISH cultivars toward their official release and dissemination by regional partners such as the Kenya Agricultural and Livestock Research Organization would have been impossible if the local preferences of farmers were not considered at the beginning of the program. Along with the breeding strategy, effective collaborations are an equally important deciding factor to the success of a breeding program. In the WISH project, Nagoya and Kyushu University are both very prestigious research-oriented universities. IRRI is the birth place of the Green Revolution with continued research expertise and extensive global relationships with research networks, governments, civil societies, and farmer communities. JICA is the Japan government’s official agency that coordinates development assistance in developing nations. It is the expertise and strength of each partner that fosters the successes of the WISH Project.

6 Conclusions Breeding for complex traits such as drought tolerance requires a synergistic approach. Plant breeders indirectly harness the correct physiological responses and molecular networks. Mechanistic understanding of such responses and networks can fast-track crop improvement by homing in on the underlying associative genetic markers. In this chapter, various tolerance mechanisms and successful cases for improving drought tolerance were presented. A combined approach using different aspects of the examples presented may show a way toward bridging the yield gap humanity faces. As technological advances continue, the knowledge bank for the different aspects of genomes and phenomes also advances. The issue is then combining the two to elucidate the complexities of a biological system, such that it is possible to model various scenarios of response depending on environmental conditions. This would allow breeding programs to be performed with maximum efficiency with the thought of making optimally adapted varieties for different conditions, similar to how genomics has enabled the creation of “personalized medicine” for people (Delos Reyes, 2019). This prospect is not a pipe dream, but rather a goal that can be achieved through continuous multidisciplinary collaboration to remove the limits of humans to analyze massive amounts of data. Bridging the information gap between breeders, biologists, stakeholders, farmers, and consumers must also be considered. All in all, just as drought tolerance is a multigenic trait, so should the effort be to solve it–by combining multiple layers of information through collaboration, solutions will arise to mitigate the problems it presents.

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Chapter 14

The microbial symbionts: Potential for crop improvement in changing environments Ram Prasada, Sagar Chhabrab, Sarvajeet Singh Gillc, Pramod Kumar Singhd and Narendra Tutejae a

Department of Botany, Mahatma Gandhi Central University, Motihari, Bihar, India, b Department of Biotechnology, Invertis University, Bareilly, India,

c

Centre for Biotechnology, MD University, Rohtak, Haryana, India, d Department of Botany, Udai Pratap College, Varanasi, India, e Plant Molecular

Biology Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India

1 Introduction Living beings tend to be sensitive to severe fluctuations in their environments. In drastic circumstances, abiotic (high and low temperature, UV exposure, pressure, drought, cold, salinity, and pH) and biotic (bacteria, viruses, fungi, parasites, beneficial and harmful insects, and weeds) stresses disturb the essential communications that possess biomolecules folded structure and functional, thereby swiftly disruption the metabolism of cellular integrity. For every environmental situation explored, a diversity of microorganisms has revealed that they not only can tolerate these conditions, but that they also survive under such conditions. These conditions may include physical extremes (e.g., thermal, radiation, energy, and pressure), chemical extremes (e.g., desiccation, salinity, pH, hypoxia, and redox state), etc. Microorganisms can thrive in a range of environments and are associated with plants. Microorganisms inhabit the surface or deep inside the Earth; under extreme acidic to basic conditions (pH 0–12.8); in high altitudes; and in frozen sea water to hydrothermal vents (at 20°C to 122°C).

2 Diversity of soil- and plant-associated microorganisms isolated from environments The diversity of microbes means they are adapted to a range of agriculture lands and are isolated from environments. Plant rhizospheres are hotspots for a range of microorganisms and help to provide nutrient availability and other potential mechanism for plant growth. The phyllosphere is a niche that helps microorganisms colonize plant interiors (endosphere). The root and stem interior or seeds are other compartments of the plant where microorganisms thrive without causing any harmful effects on the host plant. Microorganisms perform several functions and are important indicators to soil environments (Schloter et al., 2018). Some of the commonly associated microbiomes of the plant rhizosphere are symbiotic (Rhizobium, Bradyrhizobium, Mesorhizobium) and nonsymbiotic (Pseudomonas, Bacillus, Klebsiella, Azotobacter, Azoarcus, Azospirillum, Azomonas, Burkholderia) (Prasad et al., 2015). The microorganisms isolated from the rhizospheric environment perform functions for plant productivity (Singh et al., 2019a). The extreme habitats/niches also harbor known and novel microbial diversity or microbiomes with potential and activity in plants and soils as well as in land productivity (Singh et al. 2019).

3 The endophytic microbes associated with plant symbionts and their functions The four groups of symbiotic microbes of considerable interest are the diazotrophic bacteria Rhizobium (family Rhizobiaceae); the arbuscular mycorrhizal fungi (AMF) (plural mycorrhizas) in the phylum Glomeromycota; the Trichoderma strains of fungi (family Hypocreaceae, division Ascomycota); and Serendipita indica (phylum Basidiomycota). These microbes are phylogenetically distant and distinct. Each group has autonomously grown means to colonize inside plant roots, thus becoming inhabitant plant root endophytes (Table 1). These endophytic microbes are real phytosymbionts in that they have deliberate benefits to the plants whose roots they first colonize and at the same time, they derive nutrients (phosphorus, nitrogen) and other benefits from their plant hosts (Harman and Uphoff, 2019). Although their mechanistic approaches of colonization and style of living within plant roots Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00014-0 © 2020 Elsevier Inc. All rights reserved.

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TABLE 1 Endophytic symbiotic microbes and their ability to increase plant productivity and yield. Symbiotic microbes

Crop

Effects

References

Rhizobiaceae

Glycine max

Metaanalysis revealed that inoculants have higher efficacy for nodule number and grain yield compared to controls

Tilakarathna and Raizada (2017)

Commercial Rhizobium inoculants

G. max

At Purdue University, yield increases were 1%–2%

Conley and Chrisstmas (2018)

Rhizobium phaseoli

Vigna radiata L.

In the pot experiment, the presence of tryptophan and Rhizobium mitigated the adverse effects of salt stress and enhanced the plant height, number of nodules per plant, plant biomass, and grain yield

Zahir et al. (2010)

Rhizobium leguminosarum bv. trifolii

Phaseolus vulgaris

Increased seed yield of 2–3.5 t/ha under saline/drought stressed condition

Yanni et al. (2016a, 2016b)

Rhizobium strain MRP1

Pisum sativum

Pot experiment significantly observed increased growth, nodulation, N and P nutrients in the plant, seed yield, and grain protein. Inoculation increased growth under tebuconazole stress

Ahemad and Khan (2011)

AMF

Numerous crops

Enhances in yield after AMF inoculation. The combined effects of AMF and fungal endophytes on plant growth Elymus hystrix

Larimer et al. (2012)

AMF (Glomus versiforme)

Watermelon

Mycorrhizal colonization enhanced watermelon drought tolerance and increased shoot and root growth. Inactivation of ROS by gene expression changes

Mo et al. (2016)

Trichoderma harzianum, T. virens, T. viride, etc.

Several plant species

Increased growth and plant productivity with numerous vegetable and cereal crops and greenhouse ornamental plants. Also helps plants to tolerate abiotic stresses and improve nutrient uptake

Harman (2000) and Harman et al. (2004)

T. harzianum

Tomato, maize

Enhanced redox state of colonized plant roots by their higher activity of ascorbate and glutathione-recycling enzymes, higher activity of superoxide dismutase, catalase, and ascorbate peroxidase or ROS scavenging pathways in colonized plants, enhances tolerance to abiotic and biotic stress conditions

Mastouri et al. (2010, 2012)

T. harzianum

Vitis vinifera

To improve crop yield; increase antioxidant and polyphenols activity

Pascale et al. (2017)

Serendipita indica (Piriformaspora indica)

More than 150 plant species

Several documents have stated plant growth-promoting activities, better seed germination and early flowering, improved resistance of plantlets during micropropagation and stress resistance

Varma et al. (2012); Gill et al. (2016)

S. indica

Hordeum vulgare

S. indica reduced effects of pest and phytopathogens, inducing reprogramming plant gene expression, which observed plant growth promotion and resistance to abiotic stresses. These include upregulation of enzymes that deactivate toxic levels of ROS that are formed in plants under stressful conditions

Waller et al. (2005), Baltruschat et al. (2008), Vadassery et al. (2009), Sun et al. (2010), and Gill et al. (2016)

differ, overall they promote plant productivity. The microbes promote plant growth by helping plants to acquire nutrients (nitrogen and minerals), preventing pathogen infections (antimicrobial agents), siderophore production, or establishing the plant’s systemic resistance. Furthermore, these microbes can also produce antioxidant enzymes to defend plants from ecological stresses that lead to the generation of reactive oxygen species (ROS), which cause cell damage (Kapoor et al., 2019; Singh et al., 2019a, b).

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3.1 Rhizobium (Rhizobiaceae) Nitrogen-fixing microorganisms are capable of transforming atmospheric nitrogen into fixed nitrogen. Generally, they are classified as two kinds: symbiotic N2 fixing, containing rhizobia bacteria that form a symbiosis with the root nodules of the legume family plants Fabaceae (Ahemad and Kibret, 2014) and nonleguminous trees (e.g., Actinorhizal plants with Frankia); and nonsymbiotic (free living, associative, and endophytes) nitrogen-fixing forms such as cyanobacteria, Azospirillum, Azotobacter, Gluconoacetobacter diazotrophicus, and Azocarus (Bhattacharyya and Jha, 2012; Prasad et al., 2015). Associations of symbiotic N2 fixing rhizobia within the members of rhizobiaceae (α-proteobacteria; Gram-negative) infect and establish a mutual cooperation relationship with the roots of the legume family plants. The establishment of the symbiotic association includes a complex relationship between the host and symbiont, resulting in nodule formation wherein the rhizobia colonize intracellularly. Plant growth-promoting rhizobacteria (PGPR) that fix the atmospheric N2 in nonleguminous plants are also known as diazotrophs, which are capable of forming a facultative interaction with the host plants (Glick et al., 1999). The development of N2 fixation is involved by a nitrogenase enzyme complex. The structure of nitrogenase was revealed by Dean and Jacobson (1992) as a two-component metalloenzyme that involves dinitrogenase reductase (part of Fe-protein) and (ii) dinitrogenase (metal cofactor). Dinitrogenase reductase delivers electrons with high reducing power while dinitrogenase uses these electrons to reduce N2 to NH3. Typically, biological N2 fixation is recognized as the act of molybdenum nitrogenase, which is contained in all diazotrophs (Bishop and Jorerger, 1990). The rhizobia are diazotrophic bacteria capable of creating a mutualistic nitrogen-fixing endosymbiosis with precise legumes (Fabaceae) developing root nodules on the host plant. In general, they are Gram-negative, motile, nonsporulating rod-shaped bacteria. Legume-rhizobium symbiosis commences with a molecular interchange between the two associates. The legume plant secretes biomolecules (flavonoids and isoflavonoids) into the rhizospheric region. These signals are taken up by rhizobia, bind the transcriptional regulator NodD, and then activate bacterial nodulation genes. These nodulation genes are essential for the production of lipochitooligosaccharides (LCOs) called Nod factors. Nod factors are central symbiotic signals and essential in the specific host-Rhizobium interface as well as at later stages in the infection process and nodule organogenesis (Oldroyd and Downie, 2008). Infection occurs through plant root hairs in concurrence with multifarious plant-microbe interface through chemical signaling. The establishment and functioning of physical symbiosis is dependent on genetic determinants in both the plant and the bacteria. The entirely compatible symbiosis proceeds from recognition, penetration, and stimulation of host cell division as well as differentiation of the endosymbiont. In several cases, the plant produces “infection threads” that monitor the bacteria to plant root cells where the bacteria transform into nitrogen-fixing bacteroids. In other cases, the bacteria mostly infect the roots through surface cracks where secondary roots have developed. Members of the Fabaceae family produce complex nodules around the bacteroids’ nitrogen-fixing cells. These nodules are filled with the iron-containing protein (leghemoglobin) that removes oxygen and provides the hypoxic environment for the bacteroids to fix nitrogen, reducing N2 to NH3 (Ammonia), then assimilated into nucleotides, amino acids, vitamins, and flavones that are utilized by the plant. The plant root cells convert sugar into organic acids, which are then supplied to the rhizobia in exchange, hence a symbiotic relationship between the rhizobia and the legumes (Limpens and Bisseling, 2003; Ferguson et al., 2010). These interactions that lead to nodule formation are highly specific, with only certain rhizobial species or strains able to colonize a particular host legume. But, a few have reported that Rhizobiaceae are also able to colonize the roots of many nonleguminous plants, including wheat (Yanni et al., 2016a, b) and potatoes (Schmidt et al., 1994). This infection occurs when Nod factors (Nod gene) initiate plant cell division and meristem formation, and the rhizobia infect legume roots through crack entry, intercellular colonization of epidermal cells, or the well-studied formation of infection threads (Sprent and James, 2007). Rhizobia ultimately enter through root cortical cells via endocytosis. However they differentiate into nitrogen-fixing bacteroids within the plant organelle called the symbiosome, where they offer significant benefits for plant growth and development. Rhizobiaceae have both a highly specific plant-microbe interaction that primes nitrogen-fixing nodules in legumes and a much less host-specific mechanism that benefits many nonleguminous plants. Both approaches are highly valuable to the host plants (Mus et al., 2016). In the leguminous plant, nodulation takes around 4–6 weeks after crop planting. The nodule number and inside color express the form of nitrogen fixation in the plant. The nodule size and shape is dependent on the crop plants, that is, Glycine max or Arachis hypogaea will have larger nodules than fodder legumes Trifolium pratense or alfalfa because their nitrogen needs are higher. Nodulation is an essential process that is controlled by both external (temperature, acidic soils, drought, nitrate) and internal [autoregulation of nodulation (AON), ethylene] factors. AON controls the number of nodules per plant through a general process involving the leaf. Leaf tissue senses the early nodulation methods in the root through an unknown chemical signal, then confines further nodule development in newly developing root tissue. The AON factor depends on the leucine-rich repeat (LRR) receptor kinases (NARK in G. max, HAR1 in Lotus japonicus, SUNN in Medicago truncatula).

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3.2 Arbuscular mycorrhizal fungi AMF (division Glomeromycota) the first plants were colonizing; fossil evidence and DNA sequence analysis suggests that associations appeared 400–460 million years ago. The AMF are obligate symbionts that cannot be pure cultured and cannot grow without a living plant host. AMFs form mutualistic associations with the roots of 80%–90% of terrestrial plant species and may constitute up to 50% of the total soil microbial biomass (Prasad et al., 2017). Both partners benefit from the bidirectional nutrient transfer. Naturally, the host plants deliver a carbon source and the fungi return the uptake of macronutrients (N, P, and K) and micronutrients (Chhabra, 2019; Chhabra and Dowling, 2017). The first step is the infection and establishment of AMF within plant roots containing intricate chemical signaling molecules released by both partners. Plants exude several primary metabolites (i.e., sugar, hormones, enzymes) and bioactive secondary metabolites in the rhizosphere that affect the root microbiome. Nevertheless, the active “branching factors” that activate spore germination and hyphal branching of AMF have been recognized as strigolactones (Akiyama et al., 2005). AMF contributes to the molecular exchange with the plant by releasing a mixture of signaling biomolecules, including LCOs and short-chain chitooligosaccharides (chitotetraose and chitopentaose) (Maillet et al., 2011; Genre et al., 2013). Interestingly, similar microbe-associated molecular patterns (MAMPs) play a key role in innate immunity and are also required in the early steps of the rhizobia-legume symbiosis (Luo and Lu, 2014). LCOs from AMF are similar to those produced by rhizobia (Nod factors) (Maillet et al., 2011). The backbone of LCOs is synthesized by three Nod genes present in most rhizobia: a GlcNAc transferase (nodC), a chitin deacetylase (nodB), and an acyltransferase (nodA). Once the fungi penetrate the host roots, a prepenetration apparatus (PPA)—analogous to the infection threads used by Rhizobiaceae—monitors the fungi to the suitable cell determined by the host. Mycorrhizal spores existing in soil are germinated by volatile compounds released from the plant. Hyphae extend from the germinating spore and penetrate the epidermis of the plant root. Inside the root, the hyphae branch and penetrate cortical cells, where highly branched structures called arbuscules are found (Morgan and Connolly, 2013). Externally, hyphae extend into the soil beyond the area accessible to the root. This type of symbiosis assists plant nutrient uptake from the soil by enhancing the root’s absorptive surface area (Karandashov and Bucher, 2005).

3.3 Trichoderma Trichoderma are a genus of fungi (Hypocreales, Ascomycota) that is the most widespread and common filamentous fungi present in soil. They also display a remarkable range of lifestyles such as saprophytic growth in soils in which they degrade complex and natural materials (such as chitin, cellulose, lignin, polyphenols, minerals, plant growth hormones, etc.) and interactions with other fungi, animals, and plants. Trichoderma were documented long ago as biological agents to protect plants from disease and for their ability to improve nutrient uptake as well as to increase plant biomass and development, crop productivity, and abiotic stress tolerance. Nevertheless, the Trichoderma species has been applied in different biotechnological applications such as biopesicides, biofertilizers, industrial enzyme production, soil amendments, and bioremediation (Harman et al., 2004). Trichoderma are not restricted to soil environment conditions and they have the ability to colonize plant root ecosystems. Some strains of Trichoderma are able to colonize the roots of the plant host via direct penetration of the epidermal cell walls, and some strains become highly efficient endophytes that continue for the development of crop health. Presently, several Trichoderma bioinoculants are commercially available with strain mixes becoming increasingly common due to their greater stability of performance. Several mechanisms have been suggested to illuminate growth promotion and plant productivity, including protection from phytopathogens, improved nutrient uptake to the plant root, improved carbohydrate and protein metabolism, photosynthesis, and phytohormone (indole acetic acid) synthesis (Harman and Uphoff, 2019).

3.4 Serendipita indica The root endophytic fungus S. indica (formerly Piriformospora indica) belongs to the basidiomycete of the order Sebacinales (Verma et al., 1998; Siddhanta et al., 2017; Singhal et al., 2017). It is one of the most favorable candidates for plant-promoting fungus. It extends its mutualistic symbiotic relationship with bryophytes, pteridophytes, gymnosperms, and angiosperms, including monocots and dicots (Varma et al., 2012). Its complete genome (24.97 Mb) has been sequenced. Unlike AM fungi, which cannot be cultured axenically, S. indica can be easily grown on several substrates. This fungus has growth-stimulating properties on a wide range of important agricultural plants such as Hordeum vulgare, Oryza sativa, Zea mays, and Triticum aestivum; medicinal plants such as the wonder plant Aloe vera, the brain tonic plant Bacopa monniera, and the wormwood plant Artemisia annua (Bagde et al., 2010; Prasad et al., 2013); and model plants

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such as Arabidopsis thaliana and Nicotiana tabacum (Gill et al., 2016). S. indica was found to have a positive effect on host plant growth under biotic and abiotic stress conditions. Under osmotic stresses, this fungus enhances the cellular osmolarity of the plant and maintains turgor (Gill et al., 2016). The relationship with drought-responsive genes in S. indica also altered the expression of the proline synthesizing gene, P5CS. This gene is involved in proline biosynthesis and the proteogenic amino acid, which is critical for plant growth development and beneficial for the biotechnological improvement of plants. Proline is a compatible solute (highly soluble, zwitterionic), so its higher accumulations do not disrupt the cellular structure of plants. Proline acts as both an osmotic agent and induces drought tolerance by radical scavenger ROS (Kishor et al., 2014, 2015). S. indica improves the nutrient uptake of phosphorus (P) and zinc (Zn) and alterations in the root architecture. High P uptake is liable for protection of the optimum relative water contents of leaves, the quantum efficiency of the photosystem II, and the net photosynthetic rate. A high phosphorus level decreases the malondialdehyde content and enhances osmolytes and the antioxidant concentration (Tariq et al., 2017). Zinc is a redox-inert metal and catalytic action of antioxidant complexes (Cu/Zn-SOD) and is also important for scavenging ROS that ultimately stabilize the cellular membranes structure and minimizes their oxidative/peroxidative damage (Gill and Tuteja, 2010; Ngwene et al., 2016). In response to these features, the plant could afford up to 15%–20% of the produced photosynthates to this fungus and agricultural tool to improve crop yield underneath drought stress conditions (Saddique et al., 2018). Investigations have revealed that S. indica induces the resistance of colonized plants against phytopathogens. It has also been demonstrated that the H. vulgare- and S. indica-inoculated plants are tolerant to salinity stress and more resistant to root pathogens. The S. indica-colonized plant showed antioxidant activity compared to the control plant. The fungus also induces systemic disease resistance in plants. S. indica was observed to involve host cell death for proliferation during mutualistic symbiosis in H. vulgare (Deshmukh et al., 2006). Root colonization by S. indica showed an enhanced plant biomass, early flowering and fruiting, grain yield, alterations in the active ingredients, and alternation of diverse abiotic and biotic stresses. The root colonization is initiated with a biotrophic phase; this fungus directly penetrates cells and establishes colonies within them. Their growth within roots is follow by a programmed plant cell death phase, and the fungus proliferates within these killed cells. The established fungus is living within the cortical cells of roots, but does not colonize the root tip meristematic cells. In many environments, the performance of S. indica suggests its efficiency in crop improvement such as N, P, etc., availability, which supports the microbial potential and adaptability to conditions (Del Barrio-Duque et al., 2019). This fungus has great potential for biotechnological applications and future exploration for bioagricultural engineering in crop productivity.

3.5 Significance of microorganisms for agriculture and inoculants in the future The features of agricultural practices are to sustain and/or restore soil assets and improve plant productivity. The soil microorganisms (PGPRs, fungi, actinomycetes) have revealed sustained plant development and land remediation. The associations of land plants with AM fungi are vastly known and have been shown to produce a glycoprotein, glomalin, which is accountable for improved soil aggregate stability and decreased soil erosion (Sharma et al., 2017). Filamentous fungi have unique structures to be used in several applications of biomineralization-based technologies. Macroinvertebrates (mainly earthworms, ants, snails) promote soil aggregation and produce microbial communities at a larger scale by the ingestion, digestion, and assimilation of organic matter, producing secretions and transforming organic residues. In plant root systems, microbes multiplying throughout the upper layer of the soil profile, sustenance microbial communities, actively involved in soil accumulation by providing organic carbon through rhizodeposition and thus helping stabilize soil structure and decline the soil erosion (B€unemann et al., 2018). Soil microorganisms are exposed for the mineralizing and humification of organic matter, including organic contaminant molecules (pesticides). Half-lives of agrichemicals are established on the biodegradative capabilities of the soil microbial community, along with local environmental surroundings. During the mineralizing of organic matter, microbial communities release combined elements (e.g., nitrogen, phosphorus, sulfur) in their chemically reduced forms (redox transformations), regularly increasing their availability to plants (Lehman et al., 2015; Karlen and Rice, 2018). In brief, microorganisms moderate the abundance, speciation, and plant bioavailability of nutrients in the soil. Nitrogen-fixing bacteria occur in symbiotic and associative interactions with plants and as free-living microbial communities in the soil to deliver nitrogen to the plants and help in crop productivity.

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Technological advancement

Microorganisms have the ability to colonize plant roots and stimulate plant growth. The identification of microbial strains for targeted use in agriculture and soil remediation to improve soil quality (Hirth et al., 2016; Venneman et al., 2017; Ventorino et al., 2018). Molecular analyses allow studying the mechanistic approaches of plant-microbe interactions, the detection and growth activity assessment of inoculated strains, and the analysis of microbial plant-associated communities ( Jacoby et al., 2017; Hassani et al., 2018). This information permits using these microbial functions to promote plant productivity, combat pathogens, and remediate soils contaminated with heavy metals or organic pollutants (Prasad et al., 2018).

5

Conclusion and future perspectives

Several stresses such as thermal, cold, salinity, drought, heavy metals, and elevated CO2 are estimated to arise concurrently and will directly affect agriculture crops in the near future. Mostly agriculture practices, that is, biofertilizers, natural pesticides, crop rotations, inter- and relay cropping, plants with allelopathic effects. Agroforestry comprising fruits, nuts, and timber trees; sowing seeds directly in living cover crops or mulching; and the association of seminatural landscape elements at the field and farm scale or their management at the landscape scale are some of the agroecological practices that need to be properly integrated into our current agricultural systems. Through monetary rewards and other incentives, farmers should be encouraged to adapt the best agricultural practices for crop productivity that ensure a greater and sustainable yield and environmental stability.

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Sharma, S., Prasad, R., Varma, A., Sharma, A.K., 2017. Glycoprotein associated with Funneliformis coronatum. Gigaspora margarita and Acaulospora scrobiculata suppress the plant pathogens in vitro. Asian J. Plant Pathol. https://doi.org/10.3923/ajppaj.2017. Siddhanta, S., Paidi, S.K., Bushley, K., Prasad, R., Barman, I., 2017. Exploring morphological and biochemical linkages in fungal growth with label-free light sheet microscopy and Raman spectroscopy. ChemPhysChem 18 (1), 72–78. https://doi.org/10.1002/cphc.201601062. Singh, D., Raina, T.K., Kumar, A., Singh, J., Prasad, R., 2019a. Plant microbiome: a reservoir of novel genes and metabolites. Plant Gene. https://doi.org/ 10.1016/j.plgene.2019.100177. Singh, S., Kumar, V., Kapoor, D., Singh, S., Dhanjal, D.S., Datta, S., Kumar, S., Samuel, J., Dey, P., Wang, S., Prasad, R., Singh, J., 2019b. Revealing on hydrogen sulfide and nitric oxide signals co-ordination for plant growth under stress conditions. Physiol. Plant. https://doi.org/10.1111/ppl.13002. Singhal, U., Prasad, R., Varma, A., 2017. Piriformospora indica (Serendipita indica): the novel symbiont. In: Varma, A., Prasad, R., Tuteja, N. (Eds.), Mycorrhiza—Function, Diversity, State of the Art. Springer, Cham. Sprent, J.I., James, E.K., 2007. Legume evolution: where do nodules and mycorrhizas fit in? Plant Physiol. 144, 575–581. Sun, C., Johnson, J.M., Cai, D., Sherameti, I., Oelmuller, R., Lou, B., 2010. Piriformospora indica confers drought tolerance in Chinese cabbage leaves by stimulating antioxidant enzymes, the expression of drought-related genes and the plastid localized CAS protein. J. Plant Physiol. 167, 1009–1017. Tariq, A., Pan, K., Olatunji, O.A., Graciano, C., Li, Z., Sun, F., Sun, X., Song, D., Chen, W., Zhang, A., 2017. Phosphorous application improves drought tolerance of Phoebe zhennan. Front. Plant Sci. 8, 1561. Tilakarathna, M.S., Raizada, M.N., 2017. A meta-analysis of the effectiveness of diverse rhizobia inoculants on soybean traits under field conditions. Soil Biol. Biochem. 105, 177–196. Vadassery, J., Tripathi, S., Prasad, R., Varma, A., Oelmuller, R., 2009. Monodehydroascorbate reductase 2 and dehydroascorbate reductase 5 are crucial for a mutualistic interaction between Piriformosporaindica and Arabidopsis. J. Plant Physiol. 166, 1263–1274. Varma, A., Sherameti, I., Tripathi, S., Prasad, R., et al., 2012. The symbiotic fungus Piriformospora indica: review. In: Hock, B. (Ed.), Fungal Associations, The Mycota IX, second ed. Springer-Verlag, Berlin Heidelberg, pp. 231–254. Venneman, J., Audenaert, K., Verwaeren, J., Baert, G., Boeckx, P., Moango, A.M., Dhed’a, B.D., Vereecke, D., Haesaert, G., 2017. Congolese rhizospheric soils as a rich source of new plant growth-promoting endophytic Piriformospora isolates. Front. Microbiol. 8, 212. https://doi.org/ 10.3389/fmicb.2017.00212. Ventorino, V., Pascale, A., Adamo, P., Rocco, C., Fiorentino, N., Mori, M., Faraco, V., Pepe, O., Fagnano, M., 2018. Comparative assessment of autochthonous bacterial and fungal communities and microbial biomarkers of polluted agricultural soils of the Terra dei Fuochi. Sci. Rep. 8, 14281. Verma, S., Varma, A., Rexer, K., Hassel, A., Kost, G., Sarbhoy, A., et al., 1998. Piriformospora indica, gen. et sp. nov., a new root colonizing fungus. Mycologia 90 (5), 896–903. Waller, F., Achatz, B., Baltruschat, H., et al., 2005. The endophytic fungus Piriformospora indica reprograms barley to salt-stress tolerance, disease resistance, and higher yield. Proc. Natl. Acad. Sci. 102, 13386–13391. Yanni, Y., Zidan, M., Dazzo, F., et al., 2016b. Enhanced symbiotic performance and productivity of drought stressed common bean after inoculation with tolerant native rhizobia in extensive fields. Agric. Ecosyst. Environ. 232, 119–128. Yanni, Y.G., Dazzo, F.B., Squartini, A., Zanardo, M., Zidan, M.I., Elsadany, A.E.Y., 2016a. Assessment of the natural endophytic association between rhizobium and wheat and its ability to increase wheat production in the Nile delta. Plant Soil 407, 367–383. Zahir, Z.A., Shah, M.K., Naveed, M., Akhter, M.J., 2010. Substrate-dependent auxin production by Rhizobium phaseoli improves the growth and yield of Vigna radiata L. under salt stress conditions. J. Microbiol. Biotechnol. 20, 1288–1294.

Chapter 15

Reactive oxygen species (ROS) management in engineered plants for abiotic stress tolerance Punam Kundua, Ritu Gilla, Ashima Nehraa, Krishan Kant Sharmab, Mirza Hasanuzzamanc, Ram Prasadd, Narendra Tutejae and Sarvajeet Singh Gilla a

Centre for Biotechnology, MD University, Rohtak, Haryana, India, b Department of Microbiology, MD University, Rohtak, Haryana, India, c Department

of Agronomy, Faculty of Agriculture, Sher-e-Bangla Agricultural University, Dhaka, Bangladesh, d School of Environmental Science and Engineering, Sun Yat-sen University, Guangzhou, China, e Plant Molecular Biology Group, International Centre for genetic Engineering and Biotechnology (ICGEB), New Delhi, India

1 Introduction The global population is continuously increasing, and it is expected to be about 9 billion by 2050 (USDA, 2019). Accordingly, the agriculturally important land area is decreasing due to urbanization and other developmental activities. The growth estimation is strongest in developing countries, where the problem faced is not just to produce food but to ensure that it will bring food security (FAO, 2011). Every country wants to increase its agricultural productivity, but how to do that varies greatly with the area or region in question. In a 2019 report from the US Department of Agriculture (USDA), agriculture production has decreased in a large number of countries from 4% to 30%. In South Africa, the 2018/19 crop yield was calculated at about 11.5 million metric tons (mmt), which is 4% less from December and 15% from the year 2017. In Argentina, the USDA estimates the production of wheat in 2018/19 at 19.2 mmt, that is, less than 2% from December and 4% from last season. In Brazil, soybean production for 2018/19 was estimated at 117.0 (mmt), down 5 mmt or 4% from December and 3% from last year’s record. Crops have been lost because of several constraints such as drought, salinity, chilling stress, and high metal toxicity extended by climate change (Tilman et al., 2011). Salinity is responsible for crop productivity loss in the world and in particular dry and semidry areas where both saline water and soil salinity are major problems (Wani and Sah, 2014). Plants adapt various mechanisms to cope with salinity pressure and activate an array of stress-responsive genes to counteract the salinity-induced osmotic and ionic stresses (Evelin et al., 2019). In the past several decades, remarkable crop production has been obtained on a precise land area with the help of breeding methods and progressive management practices. In many countries, farmers have adopted genetically modified (GM) seeds to increase crop production and reduce the use of costly fertilizers and herbicides. The genetic engineering of plants, a most powerful approach, permits the introduction of a particular gene or a number of desirable genes in a single step, reducing the chance of introducing an undesirable gene. In 1984, Horsch et al. developed the first transgenic plant and opened the door to utilize this new technology for different purposes such as protection of crops from biotic and abiotic stresses and improvement in nutritional value. This technology is based on cellular and molecular biology. It refers to the alteration of the genetic material of a living being, either a plant or an animal, so that it obtains desired characteristics that are necessary to survive in that particular area. Advanced technologies have been developed in the last few decades that provide a greater understanding of genetic material such as DNA and RNA at the molecular level as well as their role in maintaining the biochemical and physiological status of living beings, including both animals and plants. In conventional breeding, there is a great probability of transferring genes with undesirable traits with that of the desirable one. In addition, there may be a loss or gain of function of other genes in crossing. Most crops produce allergens or toxins as a natural product to protect themselves from insects, which decreases the nutritional value of plants (Gill and Tuteja, 2010). In canola, the level of glucosinolates, an undesirable product, was observed to be very high by canola breeders. Potato breeders also monitor the glycoalkaloid content that decreases their product’s nutritional value. In short, if the breeding line generates too much undesirable product, its nutritional value automatically declines (Hahn et al., 2011; Kozukue et al., 1999). An undesirable Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00015-2 © 2020 Elsevier Inc. All rights reserved.

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product limits the scope of conventional breeding while genetic engineering allows even a single gene to be transferred to obtain the desired expression. A gene that is transferred can be isolated from closely or distantly related organisms (Baenziger, 2006). Genetic engineering tools are not just involved in the insertion of foreign genes. It also allows the modification of an organism’s genetic materials by removing or repeating genes that are already present in their chromosome so that it can repress or overexpress its genes. To develop GM plants, complex DNA machinery is required to achieve the most favorable effects (Cabrera-Bosquet et al., 2012).

2

Abiotic stresses

Adverse environmental perturbations, called abiotic stress, have become the major challenge due to their widespread nature that negatively affects plant growth, yield, and quality of produce. Drought, salinity, extreme temperature, and heavy metals are the most important forms of stress (Wani et al., 2016). In agriculture, the annual loss at the global level due to salinity is estimated to be $12 billion (FAO, 2011). As the revolution in agriculture has already reached its limit, the food supply for the exponentially increasing population will not be met because of shrinking agricultural land and industrialization in agriculturally suitable land. Along with this, unfavorable environmental conditions are also a critical factor (Walker et al., 2010; Gill and Tuteja, 2010). Abiotic stress salinity is a type of soil condition in which the concentration of soluble salts is very high, such that the ion concentration exerts osmotic pressure equivalent to that of 40 mM NaCl (Munns and Tester, 2008). Salinity problems are also added by irrigation and excessive water loss through transpiration, although more so in hot regions. In salinity conditions, osmotic stress is caused by the Na+ ions in plant roots by interfering with the extraction of water, reducing plant growth. An increase in ionic disequilibrium due to salinity results in the inactivation of enzymes, toxicity in the plant tissue, and nutrition depletion. These conditions further initiate secondary effects such as osmotic stress and reactive oxygen species (ROS) production. ROS damages plants by damaging genetic materials and inhibiting photosynthesis. Lipid oxidation in the plasma membrane can lead to plant death (Gill and Tuteja, 2010; Turan and Tripathy, 2013). In response to the high ROS concentration, plants counteract by producing osmolytes such as trehalose, proline, or glycine betaine, which protect them from denaturation and dehydration. In response to stress, the production of different enzymatic and nonenzymatic antioxidants takes place. Plants under abiotic stress activate a number of different mechanisms to resist stress such as excluding salt or raising and storing ions in different tissue compartments (Munns and Tester, 2008). To produce stress-tolerant and high-yield crops, breeders have long used conventional breeding methods, but this is inadequate due to the low genetic variation in major crops. Interspecies and intraspecies variability in the plant in response to stress are also not adequate (Turan and Tripathy, 2013). Wheat crop species (Triticum aestivum) are affected by more than one abiotic stress that can occur at a time, For example, an increase in temperature often goes along with low water supply, which additionally increases mineral toxicities in roots and retards plant development. Plants under a particular abiotic stress automatically become susceptible to another stress, for example, plants under water stress are susceptible to high radiation damage. It leads to a change in the necessary photosynthetic process in which the reduction and oxidation of NADPH is responsible for the production of ROS (Araus et al., 2002). Some economically important plants such as grapes (Vitis vinifera) are highly susceptible to high salt concentration, more so than other plants (Cunha et al., 2016). Due to the high salinity, the rate of photosynthesis also declines, which further influences the growth of organs, budburst timing, size, and carbohydrate level in fruits (Walker et al., 2010). Traditional approaches such as breeding can improve abiotic stress tolerances but so far have met limited success (Mun˜ozEspinoza et al., 2016a, b). The exploitation of the latest resources such as genetic transformation for many crops against abiotic stresses in plants needs to explore traditional methods. It is remarkable that in some plants, the actual production of plants with new traits is slower than estimated. To evaluate such plant species and release a new variety can take up to 12 years because of the need to meet at least three condition: genetically stable, genetically uniform, and distinct from other varieties at the genetic level (UPOV, 2019). Some techniques of genetic modification other than genetic engineering are also used such as simple selection, in which the plant with most desired traits is selected. This means a superior genotype, and the seed from the superior is further used for growing in the next generation. With selection, the population of the superior genotype increases so that the crop is dominated by the superior variety. Now, these oldest methods are replaced by modern technology (Abogadallah et al., 2011). Because of reproductive barriers as well as the transfer of undesirable traits, these methods are not very successful. Genetic modification is advanced molecular technique than conventional plan breeding approach as it involves gene transfer from an source to change its expression by using recombinant DNA technology. Transformation vectors for higher plants have been constructed with several features that make them efficient to use. Agrobacterium tumefaciens harbors large Ti plasmids that cause tumorous growths, or crown galls, on a wide range of plants. In agrobacterium-mediated transformation, the nuclear genome of a susceptible plant is modified

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by a large segment of the Ti plasmid called T-DNA. The T-DNA of the Ti-plasmid contains a wide range of genes responsible for opine synthesis. An efficient agrobacterium vector utilizes the trans-acting functions of the vir region on a Ti plasmid to transfer a modified T-DNA region to the plant cells. The modified T-DNA contains genes of interest and neomycin phospho-transferase for selection. By exploiting genetic transformation for many crops against abiotic stresses, we can modify signaling processes that negatively affect plant growth. Among them, calcium signaling is the most important signaling transduction chain or cascade in plants. Intracellular proteins have been adapted to bind Ca2+ ions to trigger a response through secondary messenger pathways (Steinhorst and Kudla, 2014). In a water-deficit condition, gradients are developed. In this condition, the plant’s ability to take water from the soil is compromised, which affects several physiological and molecular components as well as the membrane integrity of the cells. Physical changes in the cell include alterations in its turgor, protein structure, and volume. Other metabolic process such as cell wall synthesis, protein synthesis, and stomatal conductance are also affected (Bartels and Sunkar, 2005). In an unfavorable environment, the plant also triggers adaptation mechanisms by synthesizing the phytohormone abscisic acid (ABA) and starts the synthesis of the osmolyte to overcome these difficulties (Mahajan and Tuteja, 2005). These mechanisms start downstream signaling, leading to the activation of small secondary messengers such as proteins or ions present in the cytoplasm. In this way, a cascade of signals starts to overcome such undesirable conditions. Enzymes involved in signal transduction pathways such as protein kinase and phosphatases play very important roles in the regulation of a number of metabolic processes under stress. A number of genes are known to be tolerant for salinity and other stresses when transferred in plants. They have the ability to induce the formation of various osmolytes or osmoprotectants and upregulate antioxidant machineries. The upregulation of avariety of genes that are involved in stress tolerance such as the genes responsible for the activation of ion transporters,ion channels, transcriptional factors, and other signaling mechanisms is critical for agriculture (Hahn et al., 2011; Qi et al., 2011). For the insertion or transfer of these genes, genetic engineering strategies are more reliable than other approaches, as they can deal with a single gene only. Genetic engineering has been exploited by scientists to generate transgenic plants to respond against salinity, osmotic stress, etc., by transferring such responsive genes from tolerant to sensitive crop plants (Gill et al., 2015; Gupta and Tuteja, 2011). Modern molecular methods involve the identification of genes that participate in stress tolerance and use them to develop modified plants by overexpressing these genes so that plants remain viable in adverse conditions. These are the best options to improve plant immunity and a faster way to insert beneficial genes from other organisms (Allen, 1995). It is the only option when genes are taken from distant relatives.

3 Reactive oxygen species and its scavenging machinery ROS are formed as a natural byproduct in both plants and animals. These species play an important role in cell signaling and redox homeostasis. By definition, these are the partially reduced or activated form of atmospheric oxygen that are formed at various steps during the aerobic metabolism (Gill and Tuteja, 2010; Mittler et al., 2011). Different kinds of reactive oxidative species are produced during the metabolic process, including the peroxide H2O2, the superoxide O2 , the hydroxide OH , alpha oxygen, etc. When these species cross the level and are kept unchecked, they lead to the degradation of cellular machineries such as proteins and nucleic acid. In these circumstances, the plant is said to be under oxidative stress (Choudhury et al., 2017). Higher plants have evolved numerous pathways to protect themselves from ROS and maintain their level so that they are just involved in signaling, not destructive activities (Foyer and Noctor, 2013; Mignolet-Spruyt et al., 2016). Almost all subcellular compartments of a cell have ROS detoxifying proteins such as superoxide dismutases (SODs), ascorbate peroxidases (APXs), catalase (CAT), glutathione peroxidases (GPXs), and ferredoxin to mitigate ROS detoxification. ROS detoxification is also enhanced by different molecular adaptions by maintaining free transient metal ions to check ROS production, as shown in the Fenton reaction (Gill and Tuteja, 2010). In temperate areas, the sugar beet (Beta vulgaris L.) is an important economical crop used as a source for sugar and bioethanol production (Magan˜a et al., 2011; Hamouda et al., 2016). However, it requires careful agronomical practices to cope with both biotic and abiotic stresses. Again among abiotic stresses, drought and salinity are the most serious threats for its production (Hossain et al., 2017). By improving the salinity tolerance in sugar beet crops, more areas can be added for production. A high saline condition develops ionic and osmotic imbalances that lead to oxidative damage, which further influences plant growth inversely. Thus, the mechanism involved in salinity tolerance is an important area for research (Vastarelli et al., 2013). At an appropriate level, ROS perform their function as a signaling molecule to counteract with unfavorable environmental stimuli (Choudhury et al., 2017). Salinity stresses enhance the ROS level. To prevent the accumulation of ROS, various detoxifying signaling pathways play crucial roles. These pathways are involved in controlling the homeostasis of cellular ROS levels under various conditions (Gill and Tuteja, 2010). Physiological and biochemical changes lead to successful acclimation by selective ion uptake, exclusion, and compartmentalization of ions to maintain a proper balance of ions inside

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and outside the cells (Hamouda et al., 2016). Sugar beets have the ability to tolerate salinity up to 500 mM Na+ Cl+ for 7 days without losing viability, which makes them excellent models for studying signaling pathways involved in salinity stress tolerance (Yang et al., 2012). ROS producer systems such as the electron transport chain in photosynthesis produce hydrogen peroxide while in respiration. The electron transport chains and enzymes involved such as glucose oxidase, xanthine oxidase, and peroxidases are very important sources for cellular ROS production. Plasma membrane-bound NADPH oxidase RBOH is an important enzymatic machinery to control cellular redox homeostasis under salinity stress by generating ROS (Hossain and Dietz, 2016). In contrast to ROS producers, enzymatic and nonenzymatic antioxidants are ROS scavenging machineries that regulate redox homeostasis by scavenging ROS and preventing metabolic imbalances and biomolecule degradation while helping in stress adaptation (Foyer et al., 2009). SODs are produced in most cellular compartments as key regulators against superoxides (O2 ) while peroxidases such as GPXs and perreedoxins (Prxs), Type III heme peroxidases, APX, and catalase provide defense against H2O2 (Mittler and Poulos, 2005). Disturbed redox homeostasis enhances the production of ROS in plants. Various cell components take part in stabilizing redox homeostasis. As we discussed, salinity is a major critical factor for sugar beets, a variety of sugar beet cv. When compared with Beta maritime, Huzar shows large tolerance under salinity. Under long-term exposure of salt stress, some genes are not activated in B. maritime but are in sugar beet cv. In Huzar, these genes are activated (Dunajska-Ordak et al., 2014). An expression pattern of PIP aquaporins was different between cv. Huzar and B. maritima in response to salinity. At gene families and transcriptomic levels, these differences are observed (SkorupaKłaput et al., 2015; Skorupa et al., 2019). Thus, the sugar beet can be used as a model plant in research to observe and compare the molecular mechanisms between a species and its ancestors. In Arabidopsis, HsfA4a sensors sense the level of ROS; if their levels are more than the threshold, it regulates the expression of genes responsible for ROS production (Miller and Mittler, 2006). p46-MAPK is an example of a sensor in wheat that senses ROS homeostatis disturbance and initiates downstream signaling events. ACHT1 and glutathione peroxidase (ATGPX3) in Arabidopsis are associated with changes in the photosynthetic production of H2O2. AsNF-YC8 is an NF-Y family gene from garlic (Allium sativum) used to transform tobacco. The overexpressing AsNFYC8 transgenic tobacco plants showed higher germination rates, longer root length, and better plant growth under salt and drought stresses (Gill and Tuteja, 2010). There are a number of nuclear factor genes that are induced in response to salinity in plants and also by ABA, NaCl, and PEG. The ROS levels are observed much less in transgenic tobacco lines that exhibited higher antioxidative enzyme activities as compared to the wild-type (WT). The overexpression of AsNF-YC8 improves the detoxifying machineries by managing the activities of the enzymes that defend plants from abiotic stresses (Ha et al., 2012; Van Ha et al., 2014). In Pisum sativum, lectin receptor-like kinase (LecRLK) transcription is upregulated under salinity stress. The first site for interaction takes place on the plasma membrane where signals are perceived by receptors that are embedded in the plasma membrane (Tuteja and Sopory, 2008). LecRLKs are members of the RLK family that spans the plasma membrane and are described as transmembrane proteins. LecRLKs consist of three domains: the lectin-like extracellular recognition domain, the transmembrane domain, and the cytoplasmic kinase domain. These proteins are believed to be involved in signal transduction. PsLecRLK overexpression in transgenic tobacco plants confers salinity stress tolerance. A minimum risk of membrane injury and less harm to crop production occur under stress in transgenic tobacco plants due to the tissue compartmentalization of ions and ROS scavenging activities (Vaid et al., 2015). Transmembrane kinases with a receptor-like region initially were identified in Zea mays that possess an extracellular region similar to the glycoproteins involved in self-incompatibility in the Brassica species (Walker and Zhang, 1990). Several genes involved in cellular homeostasis are also activated by overexpressing receptor-like kinases that perceive signals and also have phosphorylation activities. Receptors such as GPCR, RLKs, or histidine kinases first perceive the stress signals, then activate the secondary signaling molecules. These secondary signals activate various genes that regulate the opening of ion-gated channels. Intracellular Ca2+ ion concentration activates the phosphoprotein cascade and leads to the activation of the stress-responsive gene (Xiong et al., 2002). When plants are exposed to stresses, it triggers local and systemic responses to generate an immune response to prevent subsequent threats. Sequential oxidative bursts in the plant apoplast are key features of systematic stress response. Confrontation of plants with unfavorable environments develops acquired resistance in plants. In Arabidopsis plants, high light intensity induces systematic adaptive response. ROS production by NADH oxidase and RBOH demonstrate the acquired acclimation of plants. A number of genes encoding RBOH have been reported in Arabidopsis, and the most important of them are AtRBOHD and AtRBOHF. To improve abiotic stress-sensitive crop plants, we must have an inclusive understanding of the mechanisms through which plants respond to stress so that by identifying the genes involved in stress response, we can exploit them against stresses. In plants, the stomata opening and closing are the most crucial steps involved in the water-saving approach by reducing transpiration as well as prohibiting the entry of CO2 means indirectly control the production of ROS (Gill and Tuteja, 2010; Wellburn et al., 1996). The limitations of CO2 fixation will reduce NADP+ regeneration in the electron

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e– O2

SOD

O2•−

Fe2+ Fenton reaction

O2

Fe3+

H2O2 CAT, GPX PRX

+

H

O2

H2O

OH• MDHAR

2 MDHA + NADH

2AA + NADH

DHAR

DHA + GSH

2 AA + GSSG

FIG. 1 Schematic view of the role of SOD, CAT, GPX, APX, MDHAR, and DHAR as ROS scavengers in plants under abiotic stresses.

transport system. During stress in the photosynthetic process, the leakage of electrons via the Mehler reaction was observed, and these leaked electrons transferred to oxygen. In wheat under stress, there was a 50% increment of the leaked photosynthetic electrons in contrast to plants under normal conditions. In addition, the photorespiratory pathways are also enhanced, and RuBP oxygenation reached the highest value due to the limitation of carbon dioxide fixation. Under stress, approximately 70% of H2O2 production is mainly due to photorespiration. Therefore in chloroplasts, a number of different kinds of scavenging machineries and metabolites are present to cope with the continuous production of ROS (Kangasjarvi et al., 2012). In plants, the detoxification system is situated in all organelles with a few exceptions, such as the catalase enzyme that is solely present in peroxisomes. SODs are the enzymes that function to efficiently catalyze the dismutation of superoxide anions. This front-line enzyme attacks and rapidly scavenges the superoxide, dismutating it to oxygen and H2O2 (Gill and Tuteja, 2010). Superoxide dismutase only converts one form of ROS (superoxide) to another (H2O2) so need to be scavenges another form of ROS because it attack on compounds which contain thiol groups (Shabala et al., 2014). For peroxides, the major enzymatic cellular scavengers are catalase and APX. In plant organelles, H2O2 is a more stable and freely diffusible molecule than other ROS species. The reduction of H2O2 by APX into water and oxygen is referred to as the Mehler peroxidase reaction or the water-water cycle (Abogadallah et al., 2011). CAT enzymes are found only in peroxisomes. They function as scavengers to detoxify the excess of ROS under stress. Another enzyme, glutathione reductase (GR), maintains the concentration of intracellular glutathione in a reduced form and functions as a reducing agent indirectly and as an antioxidant directly. The scavenging of singlet oxygen, superoxide, and hydroxyl groups are accomplished by catalase directly while recycling of ascorbic acid shows an indirect role in scavenging. In the recycling process, the oxidative form of catalase is transformed in a reduced state by enzyme dehydroascorbate reductase (Gill and Tuteja, 2010). Transgenic Arabidopsis plants are developed to overexpress the genes that take part in ROS detoxification (Shafi et al., 2015). When expressed simultaneously, SOD and APX lead to the downstream activation of transcription factors (TFs) and genes. Both play roles in detoxification, salinity tolerances and developing value-added cultivars (Kangasjarvi et al., 2012) (Fig. 1 and Table 1).

4 Role of ion transporters Plants have adapted a variety of mechanisms to oppose unfavorable conditions. Ion transporters are the most important, and they maintain the intracellular ion concentration in cells (Sunarpi et al., 2005). Structurally, these transporters are transmembrane proteins embedded in the membrane and provide passages for ion movement through the membrane (Huang et al., 2008). On the basis of energy consumption, these are divided into two main categories: ion channels and ion pumps. Ion channels allow the movement of ions from a high to a low concentration while ion pumps mediate their movement against the concentration gradient through active transport (Wang et al., 2003). In a passive flow, ions rush along the concentration gradient, which is mediated by the ion channel and the electric potential. In this case, no energy is needed for ion transportation. On the other hand, ion pumps require energy sources to transport ions against the gradient. ATP or proton motive forces provide energy for transport; therefore, this is called active transport. To prevent high toxic level of sodium, Na+/H+ transporters play a pivotal role as the antiporter in a saline environment (Berthomieu et al., 2003). HKT1-type transporters are also an important example of channels that regulate sodium homeostasis by maintaining equilibrium between the cellular and extracellular environment (Ali et al., 2016). In cells, the concentration of ions in the cytoplasm controls major phenomena such as signaling, maintaining pH, volume

TABLE 1 Genes of the antioxidant defense pathway responsible for imparting abiotic stress tolerance in plants when overexpressed in model or crop plants.

S. No.

Gene

Source

1.

AhCuZnSOD

Arachis hypogaea

2.

MnSOD1 and Mn-SOD II

3.

Target transgenic plants

Response in transgenic plants

References

Nicotiana tabacum (L.) cv. Xanthium

Detoxification of ROS and conversion of superoxide radicals to H2O2

Negi et al., 2015

Nelumbo nucifera

Helianthus annuus L.

Protects plants from oxidative damage

Ferna´ndezOcana et al., 2011

MeCu/ ZnSOD

Manihot esculenta Crantz

Cassava

Improves tolerance to oxidative and chilling stresses

Xu et al., 2014

4.

Cu/Zn SOD

Ipomoea batatas

OE in Ipomoea batatas

Enhances tolerance to SO2 in transgenic sweet potato plants

Yong et al., 2017

5.

CuZn SOD

Avicennia marima

Oryza sativa

Increases tolerance against MV-mediated oxidative and drought stress

Prashanth et al., 2008

6.

SOD

Cakile maritime

Arabidopsis thaliana

Improves tolerance against oxidative stress

Ellouzi et al., 2011

7.

FeSOD

Arabidopsis thaliana

Populus tremula

Conferred salt tolerance

Foyer et al., 1991

8.

IbCAT2

Ipomoea batatas

E. coli and Saccharomyces cerevisiae

Improves salt and drought stress tolerance

Yong et al., 2017

9.

SPCAT1

Sweet potato

OE in Ipomoea batatas

Plays role in coping with H2O2 homeostasis in leaves caused by developmental cues and environmental stimuli

Chen et al., 2012

10.

GhCAT1

Gossypium hirsutum

OE in Cotton

Exhibited higher tolerance to MV and salinity stress

Luo et al., 2013

11.

BjCAT3

Brassica juncea

Nicotiana tabacum

Enhances tolerance under Cd stress

Guan et al., 2009

12.

Zm Cat2

Zea mays

Nicotiana tabacum

Affects plant-pathogen interactions and resistance to oxidative stress

Polidoros et al., 2001

13.

CAT

Triticum aestivum L.

Oryza sativa L. cv Yuakara

Develops low-temperature stress tolerance and detoxification of ROS

Matsumura et al., 2002

14.

OsAPX1 and OsAPX2

Oryza sativa

Overexpressed in Oryza sativa

Exhibits significant changes in the redox and increased glutathione and ascorbate redox states

You and Chan, 2015

15.

IbAPX

Sweet potato

Fescue plant

Increases tolerance to a wide range of abiotic stresses

Lee et al., 2007

16.

APX

Arabidopsis thaliana

Nicotiana tabacumcv. Xanthi

Water-deficit tolerance with higher photosynthesis

Yan et al., 2003

17.

SbpAPX

Salicornia brachiata Roxb.

Nicotiana tabacum

Confers salt and drought stress tolerance in tobacco

Singh et al., 2014

18.

APX (PutAPX)

Puccinellia tenuiflora

Arabidopsis thaliana

Decreasing of H2O2 accumulation

Guan et al., 2015

19.

Cyt APX

Prunus spp.

Plum

Improves salt tolerance in transgenic plant

Diaz-Vivancos et al., 2013

20.

StAPX

Cyanidioschyzon merolae

Arabidopsis thaliana

Heat stress tolerance

Hirooka et al., 2009

21.

AtGR1

Arabidopsis thaliana

Arabidopsis thaliana

Detoxification of lipid peroxide, reactive carbonyl species in transgenic plants under aluminum stress

Yin et al., 2017

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TABLE 1 Genes of the antioxidant defense pathway responsible for imparting abiotic stress tolerance in plants when overexpressed in model or crop plants—cont’d

S. No.

Gene

Source

22.

Os GRX

Oryza sativa

23.

GR

24.

Target transgenic plants

Response in transgenic plants

References

Escherichia coli Saccharomyces cerevisiae

Modulates the expression and functions of aquaporin

Verma et al., 2016

Arabidopsis thaliana

Gossypium hirsutum

Chilling stress tolerance and photoprotection

Kornyeyev et al., 2003

GR3

Oryza sativa

Oryza sativa

Salt tolerance in transgenic rice

Wu et al., 2015

25.

Br DHAR

Brassica juncea

Synechococcus elongatus PCC 7942

Enhanced biomass and oxidative stress tolerance

Kim et al., 2017a, 2017b

26.

DHAR-OX

WT

Nicotiana tabacum

Confers tolerance to Al stress in transgenic plants

Yin et al., 2010

27.

BrDHAR

Brassica rapa

Arabidopsis thaliana

Confers tolerance to freezing-induced oxidative stress

Shin et al., 2013

28.

AtGR1/GR2

Arabidopsis thaliana

Overexpressing Arabidopsis thaliana

Contributes to detoxification of lipid peroxidederived reactive carbonyl species in transgenic plants

Yin et al., 2017

29.

GR

Fragaria vesca

Fragaria ananassa

Develops salinity tolerance in plants

Galli et al., 2019

30.

GR

E. coli

Triticum aestivum

Increases GSH content, SOD, and GR activity

Melchiorre et al., 2009

31.

EcMDAR

Eleusine coracana

Arabidopsis transgenic lines

Strengthens the detoxification ability of plants and maintains redox homeostatis

Negi et al., 2017

32.

OsMDHAR4

Oryza sativa

Nicotiana benthamiana

Resistance to heat stress in transgenic

Kim et al., 2017a, 2017b

33.

TaMDHAR4 and TaMDAR6

Triticum aestivum

Oryza sativa

Improves resistance against Puccinia striformis

Feng et al., 2014

34.

LeMDAR

Lycopersicon esculentum

Arabidopsis thaliana

Resistance to heat stress

Abou-Attia et al., 2016

35.

AtMDAR1

Arabidopsis thaliana

Nicotiana tabacum

Enhances tolerance to ozone, salt, and polyethylene glycol stresses

Eltayeb et al., 2007

36.

Plastidial GR

Haynaldia villosa

Triticum aestivum

Enhances powdery mildew resistance in wheat

Chen et al., 2007

37.

GR

S. oleracea

Nicotiana tabacum

Reduces sensitivity to chilling stress

Aono et al., 1995

38.

MDAR1

Arabidopsis thaliana ecotype Columbia

Nicotiana tabacum

Ozone, salt, and PEG stress tolerance due to higher MDAR activity and higher level of ascorbic acid

Eltayeb et al., 2007

39.

DHAR

Oryza sativa

Arabidopsis thaliana

Salt and paraquatstress tolerance due to GST, CAT, and SOD activity

Chen and Gallie, 2005

40.

GST

Suaeda salsa

Oryza sativa cv. Zhongahua 11

Salt and paraquat stress tolerance due to GST, CAT, and SOD activity

Zhao and Zhang, 2006

41.

PTOX

Thellungiella halophila

Arabidopsis

Improves salinity stress tolerance

Stepien and Johnson, 2009

42.

APX

Nicotiana tabacum

Arabidopsis

Develops salt-stress and water-deficit tolerance

Badawi et al., 2004

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regulation, and the cell cycle (Kaldenhoff et al., 2008; Smart et al., 2001). Ions flowing through channels generates a transmembrane electric current, exchange of Na + or K+ ions across membrane responsible for development of electric potential that further act as physical signals, whereas in case of Ca2+ ion it actively participate signal transduction directly, and act as chemical signals. Aquaporins are the water channels embedded in cell membranes as well as in the membranes of intracellular organelles. When a plant is exposed to water stress, these channels regulate its water potential, turgor pressure, and hydraulic conductivity by changing the permeability of the membranes (Heinen et al., 2009; Maurel and Chrispeels, 2001). Other channels such as K+ ion channels and the plasma membrane intrinsic protein (PIPs) in the root cells also play roles during water-deficit conditions. The expression of these channels is upregulated or downregulated according to water availability Aquaporin gene expression regulates the water balance under drought conditions to help the plants survive in unfavorable environments (Lian et al., 2004; Tyerman et al., 2002; Galmes et al., 2007). It was observed in rice that the genes encoding the PIPs and K+ channels could be downregulated by polyethylene glycol under water stress. Downregulation of these channels helps in cellular water conservation by reducing the water permeability of the membrane under water stress (Liu et al., 2006a, 2006b). Under stress, K+ ion transporters are downregulated so that the K+ ion concentration decreases in cells. It alters root conductance and signal transduce shift or changes aquaporin activity (Sahr et al., 2005; Tazawa et al., 2001). The Na+ ion, due to its high solubility, is easily accessible to plants in high saline conditions and it disturbs the osmotic potential and turgor pressure in glycophytes (Flowers and Colmer, 2008). Salicornia europaea helps to understand themechanisms used by halophytes to prevent high Na+ accumulation in the cell cytosol (Ruan et al., 2010; Shabala et al., 2014) open the door to develop transformed glycophytes species that can grow in high saline conditions. It can be exploited to improve salt-sensitive glycophytes (Assaha et al., 2017; Schulze et al., 2012; Maser et al., 2002; Ward et al., 2003). Ian influx of Na+ ions inside the cell against the electrochemical gradient is mediated by the sodium transporter HKT1 and by nonselective cation channels (Pardo and Quintero, 2002). No specialized sensors have been identified in halophytes, thus the information on how plants perceive salt stress signals remains limited (Zhu, 2003; Sun et al., 2012). It was found that calcium can diminish the loss of integrity of the membrane and minimize the potassium leakage in cytosol. Under stress, the initial responses in plant root cells are the replacement of Ca+ by Na+. However, some researchers have suggested that this replacement has negligible significance to salt stress. Shabala et al. in 2015 claimed that there are some stress sensors that perceive signals and are responsible for the intial response such as the activation of exchangers and transporters. The Na+-H+ antiporter and histidine kinases are involved in early signaling events under stresses. AHK1/ATHK1 is a potential salt sensor or osmosensor that triggers signaling cascades in salt stress. Transgenic plants that overexpress AtNHX1 had markedly improved salinity tolerance as well as growth in plants (Apse et al., 1999). NHX family members are located on the tonoplast, that is, the membrane of the vacuole in most cases while a few are on the plasma membrane of the endoplasmic reticulum (Gierth and Maser, 2007). The intracellular NHX transporters consist of a number of subclasses such as the CPA family. Cation-proton antiporters, or CPA family members are Na+/H+ antiporters except few that are K+/H+ antiporters. Antiporters that transport Na+ ions outside cells are rare. The SOS1Na+/H+ antiporter is the only reported one that exports sodium ions outside, and its activity is regulated by SOS2 and SOS3. SOS2 is a serine/threonine protein kinase (CIPK24) while SOS3 is a myristoylated calcium binding protein that interacts with the calcium ion directly and activates SOS2. SOS2 is recruited by SOS3 to the plasma membrane while the CBL-CIPK complex of SOS2 activates SOS1 by phosphorylation and increases Na+/H+ exchange activity (Demidchik and Tester, 2002). Activated SOS1, which are Na+/H+ antiporters present on the plasma membrane, extrude the Na+ outside the cell (Quintero et al., 2002; Guo et al., 2004). The vacoular transporter NHX1 enhances salt tolerance in rice (Fukuda et al., 2004) and also plays an important role in a variety of plant developmental processes and adjustments to environmental stress.

5

Role of osmolytes/osmoprotectants

Osmolytes are highly soluble organic compounds with a low molecular weight that do not hinder regular metabolic reactions, even at high cellular concentrations, because of their nontoxic nature such as proline, mannitol, fructan, trehalose, glycine betaine, or ononitol (Hasanuzzaman et al., 2019). These compounds play a role in the regulation of osmosis and maintain osmotic pressure by maintaining the cell volume and fluid balance in and outside cells (Batista-Silva et al., 2019). In an adverse condition, glycophytes accumulate osmolytes. Osmolytes play a role in osmotic adjustment and subcellular protection. They maintain the integrity of the membrane and prevent protein denaturation. Osmotically active solutes facilitate the influx of water into a cell and provide the turgor necessary for the expansion of a cell under stress while also contributing to fitness under stressful environments (Khan et al., 2018a, b). Chemically, osmolytes are of two types: inorganic and organic (Foyer and Noctor, 2005). The osmolyte concentration increases with the decrease in

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the water potential of the cell. Earlier, Rhodes and Hanson, 1993 showed that osmolytes act as safeguards against ROS species and help in scavenging oxide radicals without disturbing cell integrity. It has to be shown that the accumulation of mannitol in the chloroplast increases the tolerance against oxidative damage in tobacco. In photosynthesis, the absorption of incident energy used by the plant for the metabolism also has destructive consequences. Under stress, the photon range exceeds the normal, which further develops redox imbalances that enhance the use or consumption of O2 as an electron acceptor instead of NADP+. Synthesis and degradation of osmolytes regulate the cellular redox homeostasis in the cytoplasm and other organelles. In transgenic Arabidopsis, there is no net accumulation of proline when the expressions of both proline dehydrogenase and P5Csynthetase were induced (Feigl et al., 2015). The synthesis and degradation of proline play significant roles in maintaining redox homeostasis and help to adapt to a water-deficit environment when a plant experiences it on a daily basis. The synthesis of glycine betaine involves a two-step process. In the first step, choline is oxidized into an unstable intermediate betaine aldehyde, and in the next step, into glycine betaine in a light-dependent process. Therefore, the accumulation of osmolytes in plant cells maintains the turgor pressure under low water potentials ( Jogeswar et al., 2006). In the tomato, the accumulation of osmolytes functions as an osmoprotective substance by stabilizing proteins and cell membranes under dehydration. Osmolytes also protect cells from oxidative stress by preventing oxidative bursts by exerting an inducer (Gao et al., 2008; Szabados and Savoure, 2010). Primary metabolites such as proline, glycine, and soluble sugars are responsible for cellular osmotic adjustment while others such as malondialdehyde (MDA) and some nonenzymatic antioxidants such as carotenoids, phenolics, and flavonoids are synthesized in response to secondary oxidative stress. Carotenoid pigments do not play a role in photosynthesis, but their function is important in oxidative stress tolerance (Gill and Tuteja, 2010). Phenolic compounds perform numerous roles involved in the responses of plants to abiotic stress such as UV radiation, extreme temperatures, mineral nutrient imbalance, drought, salinity, heavy metals, and herbicides. These compounds play roles in growth and developmental processes and in the defense process against herbivores and pathogens (Cheynier et al., 2013). Oxygen in the electronic singlet state is a very powerful oxidant in the tomato, which interferes in a variety of biological processes. Proline quenching actions against singlet oxygen protect cells from damage (Alia and Matysik, 2001). However, the accumulation of two major osmolytes—glycine betaine and proline—has been observed in various plant species under stress, but their real significance in plants is not clear. Both compounds are thought to have a positive effect on enzymes and the membrane integrity of cells. These may have adaptive roles in maintaining osmotic adaptation in plants (Ashraf and Foolad, 2007).

6 Role of transcription factors TFs are adaptor molecules that recognize specific sequence in DNA and facilitate the protein assembly to bind and regulate in gene expression. TFs consist of two different types of domains: one binds with DNA and the other activates and regulates the transcription rate of genes. Therefore, they play important roles in regulating diverse cellular processes. In response to stresses, plants start to activate a wide range of mechanisms at the physiological, biochemical, and molecular levels to adapt to a changing environment and increase the stress tolerance, survival, and productivity (Bartels and Sunkar, 2005; Zhou et al., 2009; Nakashima et al., 2012). By using molecular techniques such as microarray analysis and transcriptome analysis, researchers have identified a wide array of genes that activate under stress (Fowler and Thomashow, 2002). These genes are responsible for the activation of useful enzymes and proteins that play a role in signal transduction under unfavorable conditions (Lata and Prasad, 2011). Proteins used in metabolic processes are called metabolic or functional proteins while the proteins that regulate function at the transcriptional and expressional levels are known as regulatory proteins. Transcriptional factors (TFs) are the most important regulatory proteins which play a crucial role in signal transduction by perceiving stress signals and transforming theminto stress-responsive gene expression by interacting with upstream sequences of promoter or cis acting element presentin promoter (Akhtar et al., 2012). Some important transcriptional factors that play important roles during stress are reported in Arabidopsis. These are heat stress factors or HSFs, MYB domain TFs, basic leucine zipper (bZIP) TFs, AREB/ABF TFs, NACTFs, etc. Heat stress factor proteins, having an N-terminal DNA binding domain that binds to a specific sequence, present inside or outside to the promoter and facilitate the transcription of stress-responsive genes. In a few model species such as Arabidopsis, tomato, rice, wheat, soybean, etc., the transcriptional factor of HSF family has been reported. There are 21 HSF encoding genes in Arabidopsis, 24 in tomato, 52 in soybean, and 56 in wheat (Scharf et al., 2012; Fragkostefanakis et al., 2015). In Arabidopsis, the expression of CDF3 is highly induced by drought, temperature, and ABA treatment. CDF3 is a type of DOF gene that activates in response to abiotic stress and also plays a crucial role in the developmental and flowering processes. Overexpression of CDF3 enhances the tolerance in transgenic plants under abiotic stresses and

250

Advancement in crop improvement techniques

Abiotic stresses

Drought Temperature

Salinity

Cereal plants

At cellular level Receptor Perception of signals

Sensors

cAMP AP2/ERFBP

Signal transduction Transcription factors Activation

CDPK MYB

Ca2+

MAPK Tfs

WRKY bZIP

Physiological response

Transporter

NAC

Stress responsive genes expression FIG. 2 Plants under abiotic stress activate various signaling pathways and regulate the expression of stress-responsive genes.

promotes late flowering. CDF3 also regulates a set of genes involved in cellular osmoprotection and oxidative stress, including the stress-tolerance TFs such as CBFs, DREB2A, ZAT12, γ-aminobutyric acid, proline, glutamine, and sucrose observed much higher in CDF3-overexpressing plants (Corrales et al., 2017). MYB TFs, another most important TF, play a central role in triggering light response. In the Arabidopsis genome, more than 1600 TF genes are identified that contribute up to approximately 6% of the total number of genes (Gong et al., 2004). These are characterized on the basis of the DNA binding domain and assigned into different families and super families. Genes for several TFs such as MYC, MYB, MAD, bZIP, BHLH, AP2/ERF, and WRKY play important roles in plants to develop abiotic stress tolerance. The MYB domain is a type of DNA binding TF that consists of a variable number of MYB repeats at the N-terminus. MYB repeats of TFs at the N-terminus bind with DNA and are also associated with proteinprotein interactions while variable domains at the C-terminus modulate the regulatory activity of protein (Zimmermann et al., 2004). MYB TFs are associated with the biosynthesis of secondary metabolites involved in the absorption of UVB radiation in plants. In Arabidopsis, MYB4, a member of the R2R3 group, represses the transcription of gene encoding cinnimate 4-hydroxylase, which is involved in hydroxycinnimate ester biosynthesis (Katiyar et al., 2012). It was observed that the expressions of various MYB TF genes such as AtMYB2, AtMYB74, and AtMYB102 are induced under drought stress in Arabidopsis. AtMYB2 functions as a transcription activator in ABA signaling and R2R2-MYB TF. MYB96 is also involved in the regulation of lateral root growth via the ABA-auxin signaling network under stress (Baldoni et al., 2015). Another important TF, bZIP, which consists of a basic leucine zipper and a DNA binding region, binds with DNA and has an important role in abiotic stress tolerance. The basic region for nuclear localization and DNA binding are present at the N-terminus and a leucine-rich motif for dimerization at the C-terminus in bZIP (Wei et al., 2012). bZIP plays a pivotal role in developmental processes and also responds to various abiotic stresses such as drought, high salinity, and cold. It has been reported in Arabidopsis, rice, and maize ( Jakoby et al., 2002; Nijhawan et al., 2008; Wei et al., 2012). Various kinds of TFs that have important roles in abiotic stress tolerance can be used as tools to improve the plant response to multiple abiotic stresses. Genetic manipulation of selected TF genes by overexpressing them in cereal crops is a powerful approach to improve plant tolerance to multiple stresses (Fig. 2).

7

Genetic engineering approaches to develop salinity tolerance

Genetic engineering means the modification of the genome of plants by the insertion of either a single gene or a few genes with the help of bacteria or by using other highly sophisticated methods. The resulting modified plants are described as transgenic plants. The insertion of genes that code for desirable traits is a key feature of genetic engineering. Sources

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for genes of interest can be plants or bacteria. A variety of restriction endonucleases are used to cut out the parental DNA at a specific site. Genetic engineering makes it possible to introduce genes of interest by using modern tools of rDNA techniques within the same or different species. As plants are sessile, they constantly encounter changing environmental conditions that are often unfavorable for their growth and development. Abiotic stresses are major environmental threats that affect the geographical distribution of plants in nature. These stresses limit plant productivity and threaten food security. Soil salinity is one of the major constraints to agriculture (Munns and Tester, 2008). Annual losses due to salinity are estimated at $12 billion. Salinity reduces the yield of agriculture crops because most of them are salt-sensitive glycophytes. However, the genetic approach paves the way for the development of transgenic crops with high yields under salinization. In the initial water-deficit stage, osmotic stresses are developed that are not very harmful to plants, primary signal of water stress are hypo-osmotic condition and cells can protect themselves from these but long term stress lead to drought stress condition means secondary stage of stress lead oxidative damage of biomolecules such as protein, lipid, membrane integrity and ion toxicity. Ion fluxes control ion concentrations and are essential for salinity tolerance. Soil salinity is inversely correlated with photosynthesis in both vegetative as well as reproductive phases (Senguttuvel et al., 2014). In rice, the seedling stage has been observed to be very tolerant compared to later stages; in the later stages, rice crops are very prone to injury (Cunha et al., 2016). Drought and salinity lead to the accumulation of phytohormone ABA that brings out the adaptive response in plants against stress (Zhu et al., 2016). Plant cells show these adaptive responses in order to survive in unfavorable environments. How do they sense whether that outer environment is favorable? There are some receptor molecules such as lipids, proteins, ions, or other macromolecules that can sense physical signals such as a change in ionic concentration, osmotic pressure, pH, and temperature. In rice OSCA1, putative hyperosmotic sensors have been identified (Yuan et al., 2014). Molecular control mechanisms of salinity stress tolerance are used to develop more tolerant plants that rely on the expression of specific stress-related genes that are involved in signaling transduction and transcriptional control such as MYC, MAP kinases, SOS kinase, and phospholipases (Gill et al., 2011; Hsu and Kao, 2007). TFs such as HSF, CBF/DREB (the dehydration responsive TFs), C-repeat binding factors (CBF), ABF/ABAE families, MYB, etc., can also be exploited to generate tolerant plants. These genes are categorized into three main groups on the basis of the functions of their products: l

l

l

Genes that act as safeguards for membranes and proteins such as HSF and chaprones (Bray et al., 2000), osmolytes, and free radical scavengers. Genes involved in signal cascades and controlling the transcription machineries such as MYC, MYB, MAP kinases, SOS kinases, etc. (Blumwald, 2000). Genes that take part in water uptake and ion transport such as aquaporins and ion transporters (Zhu, 2002).

When plants are exposed to various stress conditions, the level of various metabolites in response to stress also changes so that it modulates the ability of plants to tolerate unfavorable circumstances. Metabolites that contribute to enhanced saltstress tolerance include amino acids (glycine, proline etc), organic acids, osmolytes, and sugar derivatives. Other alternatives to enhance tolerance are ion transporters, antioxidant machinery, TFs, helicases, etc. Thus, genes responsible for the production of glycine betaine, proline, organic acids, osmolytes, sugar derivatives, ion transporters, antioxidant machineries, TFs, and helicases play the most crucial role in the survival of plants in a saline environment.

8 To increase crop production As we discussed, the present population is expected to rise to about 9 billion by 2050. About 1 billion people are undernourished and lack sufficient nutrients in their diet, which has a negative impact on global health. Nutrient-deficient diets lead to the impairment of various biological and physiological systems and make the human body susceptible to infections and diseases. As the population increases, the global demand for food is expected to increase by 40% by 2030 because an additional 2 billion people will be on the planet and barely 15% of the Earth’s surface can be exploited for agriculture. To meet the global demand for food production by simply increasing inorganic fertilizers and the water supply or applying organic farming systems to agriculture will be unsatisfactory. On limited land resources, increased food production will depend on innovative agronomic practices together with the genetic improvement of crops. Genetic approaches are frequently offered as hope for increasing crop yields in less-developed areas where crop production using wild varieties is very low. Photosynthesis is the best known process among all green plants and is similar across all crops because the steps involved in both the cycles C3 and C4 are similar in cereals. In tobacco, the sedoheptulose-1:7-bisphosphatase (SBPase) enzyme was upregulated to increase the carbon metabolism. It was predicted that the upregulation of the SBPase would contribute to a 60% increase in the crop yield of tobacco by increasing the efficiency of photosynthesis (Zhu et al., 2007). Various studies have now shown that using promoter-specific germ lines expressing Cas can significantly improve the frequency and heritability of mutations in Arabidopsis (Yan et al., 2015) (Table 2).

TABLE 2 Genes responsible for imparting salinity tolerance in plants when overexpressed in model or crop plants. S. No.

Genes

Source

Salt-responsive elements +

+

Function

Target plants +

1.

SOS1

Fungus and bacteria

Na /H antiporter

Excludes excess Na , accumulates these ions into cellular compartments such as vacuoles, maintains ionic homeostasis

Arabidopsis thaliana (Shi et al., 2003)

2.

SOD2

Schizosaccharomyces pombe

Na+/H+ antiporter

Maintains ionic homeostasis in stress

Arabidopsis thaliana (Gao et al., 2008)

3.

NhaA

E. coli

Antiporter

Stabilizes cations and binding and their transport

Arabidopsis thaliana (Wu et al., 2005)

4.

ScVP

Suaeda corniculata

H+-pyrophosphatase

V-H+-Pase, enhances their salt tolerance

Cotton (Pasapula et al., 2011)

5.

AtNHX1

Arabidopsis thaliana

Maintain electrochemical graidient of H+ ions generated by the vacuolar H+-ATPase

Improves salinity and drought tolerance

Tomato and Brassica (Zhang et al., 2001)

6.

AgNHX1

Atriplex gmelini

Na+/H+ antiporter

Excludes Na+ ions from cytoplasm

Rice (Ohta et al., 2002)

7.

HbNHX1 GhNHX1 BnNHX1

Barley Cotton Brassica napus

Sodium-hydrogen transporter

Improves salinity tolerance

Tobacco (Wang et al., 2004; Wu et al., 2004)

8.

P5CS gene

Vigna acontifolia

Pyrroline-5-carboxylate synthase

Synthesizes proline from its precursor glutamic acid that acts as an osmoprotectant

Nicotiana tabacum (Hayat et al., 2012; Delauney and Verma, 1993)

9.

MH1

Alfalfa

Mh1 helicase

Improves antioxidant defense system

ArabidopsisThaliana (Luo et al., 2009)

10.

GmERF3

Glycine max

AP2/ERF transcription factor

Enhances drought and salinity tolerance

Nicotiana tabacum (Carlos et al., 2016)

11.

OsGlyI, OsGlyII

Rice

Encode enzymes glyoxalase I and glyoxalase II

Detoxification of methylglyoxal in stress conditions

Nicotiana tabacum (Mustafiz et al., 2014; Ghosh et al., 2014)

12.

CcHARDY

Christolea crassifolia

Encoding transcription factor

Overexpression enhances salinity and drought tolerance

Lycopercicum esculentum (Guo et al., 2017)

13.

HARDY

Arabidopsis thaliana

AP2/ERF transcription factor

Enhances drought and salinity tolerance

Trifolium alexandrinum (Abogadallah et al., 2011)

14.

AvDH1

Apocynum venetum

Enhancement of helicase and ATPase activity

Enhances ROS scavenging capacity and osmotic adjustment

Arabidopsis thaliana (Vashisht and Tuteja, 2005)

15.

MCM6 DNA helicases

Pisum sativum

MCM6 Promoters have stress responsive elements

Overexpression of MCM6 was found to be salinity tolerant in transgenic plants

Nicotiana tabacum (Dang et al., 2011)

16.

ZmMKK4

Zea mays

Encode mitogenactivated protein kinases (MAPK)

Plays role in signal transduction

Arabidopsis thaliana (Shou et al., 2004)

17.

OsCDPK21

Oryza sativa

Activate calciumdependent protein kinases (CDPKs), cascade

Overexpression in transgenic rice improves salinity tolerance

Rice (Asano et al., 2011)

18.

OsHKT2

Oryza sativa

(Na+/K+ symporter)

Overexpression in transgenic rice improves salinity tolerance

Rice (Mishra et al., 2016)

19.

OsMPK4 OsMKK6 OsEDR1 OsMAPK5OsMAPK44OsMAPK33OsMKK1

Oryza sativa

Mitogen-activated protein

Enhances chilling stress tolerance in plants

Rice (Lee et al., 2011; Kumar et al., 2013; Wang et al., 2014)

20.

AtNHX1 and bar

Arabidopsis thaliana

Herbicide resistance

Improves the tolerance to salinity, oxidative stress

Mungbean (Kumar et al., 2017)

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To create accurate incision, substitution, and mutation, mainly two important types of genome editing systems are used in plants: l l l

TALENS: Transcription activator like effector nuclease CRISPR: Clustered regularly interspaced short palindromic repeats Cas System: CRISPR associated system

In the developing world, the production of biotech food crops with improved nutrition qualities such as increased ferritin (iron storage protein), folate, vitamin A, etc., can provide sufficient levels of micronutrients that are lacking in diets. In rice, barley, tobacco, maize, and Arabidopsis, genome editing methods have been performed and are currently in a beginning stage of development. Vitamin A deficiency causes night blindness and eye damage in millions of children. Future work could focus on identifying Cas variants that have maximal activity at temperatures used for plant growth. Random mutagenesis has been used to quickly generate new genotypes in most cereal varieties, but its potential is greatly limited by the nature of their genomes and the limited screenable population sizes, so that the approach has not yielded much (Parry et al., 2009). Wheat crop production is greatly influenced by high temperature. Each 1°C rise in temperature may decrease production by 6%. Temperatures above 35°C disrupt rubisco, the key enzyme of photosynthesis (Asseng et al., 2015).

9

To increase nutrition values

According to the World Health Organization’s Global Nutrition Report 2018, children under 5 years old face malnutrition problems. Approximately 150.8 million children below the age of five years are stunted, whereas, 20 billion kids born each year are underweight. Even the women are anemic in their reproductive stage and faces the problem of obesity. To overcome these malnutrition problems, the diet must be balanced, meaning proper proportions of nutrients in food are also important to avoid malnourishment. Due to poor absorption from cereals, iron deficiency is the most widespread micronutrient deficiency worldwide. The most important cereal crops in the world are rice, barley, maize, wheat, rye, sorghum, and millet. According to the WHO report, approximately 30% of the worldwide population suffers from iron deficiency. To enhance nutrition quality and crop yield, GM crops can act as powerful tools instead of the laborious and time-consuming conventional breeding methods (Kamthan et al., 2016). The demands of all essential nutrients required by humans are fulfilled by plant crops. Unfortunately, these are present in low concentrations in some plants. The process of enhancing mineral content and essential vitamins in staple food crops through plant breeding is called biofortification (Bouis et al., 2011). Biofortified rice with the transgenic approach could be cost-effective in alleviating folate deficiency rather than conventional supplementation programs. Phytic acid (PA) is a known inhibitor of zinc absorption and is prevalent in many cereals. It binds to zinc and other minerals such as iron to form an insoluble complex that prevents mineral absorption. Because the prevalence of PA in cereals such as wheat, maize, and rice can have serious nutritional consequences, efforts have been made to reduce its content. Iron is an essential nutrient present in blood and makes a compound with oxygen; it also plays a different role in the body. Approximately 65%–80% of the body’s iron is present in the form of hemoglobin while another complex myoglobin in muscle cells also requires iron to carry oxygen (Finkelstein et al., 2017). Rice, beans, and pearl millet are the only main iron-fortified staple foods to date, but the amount of iron increase is not enough. Transgenic approaches to introduce the ferritin gene from Phaseolus vulgaris into rice increases their iron content by up to twofold. By silencing the genes responsible for PA synthesis, we can enhance the absorption of iron because it interferes with the absorption of iron from cereals. To increase iron bioavailability, a thermo-tolerant phytase from Aspergillus fumigates is introduced into the rice endosperm. In rice, a high content of iron with a high level of phytase is expected to improve iron nutrition in rice-eating populations (Lucca et al., 2001). Animals cannot synthesize all amino acids in their bodies. Twenty amino acids are required for the formation of proteins. Amino acids that cannot be synthesized by animals themselves are called essential amino acids. There are nine of these and they are obtained from outside or external sources. The external sources are mainly plants, but the low levels of some essential amino acids limit the nutritional quality of plants. Phenylalanine and tryptophan are essential aromatic amino acids. The synthesis of aromatic amino acids begins via the shikimate pathway in which phosphoenolpyruvate and erythrose 4-phosphate are converted into chorismate. Chorismate is then transferred into phenylalanine and tryptophan by amino acid biosynthetic pathways (Basset et al., 2004; Galili et al., 2016).

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10 Genomewide perspective of ROS scavenging machinery in plants A genome-wide analysis of any gene family divulges many functional and important aspects such as the number of genes or proteins, domain composition, cellular localization, evolutionary relationship based on orthologous, expression pattern, consequences of mutations, and the prediction of protein structure and its particular attributes. It also reveals the characteristic features that can deeply modify the experimental biology. There are many studies that can give large amounts of information by bioinformatics tools and can be the basis of advanced research experiments. Genome-wide studies in different plants revealed a differential number of SOD genes in different plants, which showed large variations in SOD gene number. The maximum number of SOD genes that are reported is 41 SODs in Oropetium thomaeum (Gupta et al., 2019) as well as nine SODs in Arabidopsis thaliana, six SODs in Larix kaempferi, and 18 SODs in Gossypium raimondii and Gossypium arboreum (Gill et al., 2015; Han et al., 2019; Wang et al., 2016). These genomic studies have been informed about the presence of SODs in cytosol as well as in chloroplast. Han et al. reported that out of six LkSODs, three SODs (LkSOD21, 3 and 4) are localized in cytosol and three other proteins (LkSOD2, 5, and 6) in chloroplast. SOD genes show tissue-specific as well as stage-specific expression patterns. In the case of G. raimondii and G. arboreum, out of 18 SODs, 9, 10, 9, 8, and 18 genes were expressed in the root, stem, leaf, flower, and ovule, respectively. There are some genes that are found to be involved in stage-specific expression and peaked during the elongation stage, and expression is declined as the secondary cell wall synthesis starts (Wang et al., 2016). Genomic studies of the catalase gene family give the number of genes in different plants such as Cucumis sativus (four catalase), A. thaliana (three catalase), Oryza sativa (four catalsase), Xerophyta viscosa (16 catalase), Gossypium hirsutum (seven catalse), and Gossypium barbadense (seven catalase) (Hu et al., 2016; Alam and Ghosh, 2018; Gupta et al., 2019; Wang et al., 2019). By these studies, the minimum number of CATs is found in Arabidopsis. Arabidopsis and rice contain three and four catalases, respectively, but codes for seven proteins in each. They were able to find five conserved motifs in the main active site of the enzyme of each of 87 sequences. Similarly, 120 APX genes also examined in a similar manner revealed the conserved feature and expression pattern (Ozyigit et al., 2016). Some other studies of the peroxidase gene family identified a number of genes: Sorghum bicolor (nine APX and seven GPX) and Selaginella lepidophylla (28 GPX) (Akbudak et al., 2018; Gupta et al., 2019). G. hirsutum has 26 APX genes but 13 GPX genes, which is the half of its APX genes. The APX1 gene is reported to perform important functions during fiber elongation in the cotton plant (Tao et al., 2018; Chen et al., 2017). Trivedi et al., 2013 reported three GR genes in rice and two genes in Arabidospsis thaliana. An evolutionary study of these genes showed the conserved pyridine nucleotide-disulphide oxidoreductase class-I active site among the GR in Arabidopsis and rice. When the glutathione S-transferase (GST) gene family analysis was done in Capsella rubella, 49 GST genes were established and classified in eight classes; the two most diverse classes were tau and phi. In the present study, the expression of all 49 GSTs was examined in four tissues such as leaves, roots, seeds, and hypocotyl. Out of 25 tau GSts, 13 GSTs are expressed in all tissues but 12 showed tissue-specific expression. CrGSTU23 only expressed in root tissues and CrGSTU5 and 19 in seed tissues (He et al., 2016). In Solanum lycopersicum and Brassica rapa, 90 and 75 GST genes are reported, respectively, and the S. lycopersicum GST family found the largest (Islam et al., 2017; Khan et al., 2018a, b).

Acknowledgments SSG and RG acknowledge partial support from the Department of Science and Technology (DST), Council of Scientific and Industrial Research (CSIR), and University Grants Commission (UGC). NT also acknowledges partial support from the Department of Biotechnology (DBT) and DST, Govt. of India, New Delhi. PK is thankful to CSIR, Govt. of India, for the Junior Research Fellowship.

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Yin, L., Wang, S., Eltayeb, A.E., Uddin, M.I., Yamamoto, Y., Tsuji, W., Takeuchi, Y., Tanaka, K., 2010. Overexpression of dehydroascorbate reductase, but not monodehydroascorbate reductase, confers tolerance to aluminum stress in transgenic tobacco. Planta 231 (3), 609–621. Yin, L., Mano, J., Tanaka, K., Wang, S., Zhang, M., Deng, X., Zhang, S., 2017. High level of reduced glutathione contributes to detoxification of lipid peroxide-derived reactive carbonyl species in transgenic Arabidopsis overexpressing glutathione reductase under aluminum stress. Physiol. Plant. 161, 211–223. Yong, B., Wang, X., Xu, P., Zheng, H., Fei, X., Hong, Z., Ma, Q., Miao, Y., Yuan, X., Jiang, Y., Shou, H., 2017. Isolation and abiotic stress resistance analyses of a catalase gene from Ipomoea batatas (L.) Lam. Biomed. Res. Int. 6847532. You, J., Chan, Z., 2015. ROS regulation during abiotic stress responses in crop plants. Front. Plant Sci. 6, 1092. Yuan, Y.C., Shao, A.H., Liang, L.C., Bian, Y.F., 2014. A cross-lagged analysis of the relation between unsociability, peer rejection and peer victimization. Psychol. Dev. Educ. 30, 16–23. Zhang, H.X., Hodson, J.N., Williams, J.P., Blumwald, E., 2001. Engineering salt-tolerant Brassica plants: characterization of yield and seed oil quality in transgenic plants with increased vacuolar sodium accumulation. Proc. Natl. Acad. Sci. U. S. A. 98, 12832–12836. Zhao, F., Zhang, H., 2006. Salt and paraquat stress tolerance results from coexpression of the Suaeda salsa glutathione S-transferase and catalase in transgenic rice. Plant Cell Tissue Organ Cult. 86, 349–358. Zhou, R., Li, B., Liu, H., Sun, D., 2009. Progress in the participation of Ca2+-calmodulin in heat shock signal transduction. Prog. Nat. Sci. 19, 1201–1208. Zhu, J.K., 2002. Salt and drought stress signal transduction in plants. Annu. Rev. Plant Biol. 53, 247–273. Zhu, J.K., 2003. Regulation of ion homeostasis under salt stress. Curr. Opin. Plant Biol. 6, 441–445. Zhu, M., Shabala, L., Cuin, T.A., Huang, X., Zhou, M., Munns, R., Shabala, S., 2016. Nax loci affect SOS1-like Na+/H+ exchanger expression and activityin wheat. J. Exp. Bot. 67, 835–844. Zhu, X.-G., de Sturler, E., Long, S.P., 2007. Optimizing the distribution ofresources between enzymes of carbon metabolism can dramatically increase photosynthetic rate: a numerical simulation using an evolutionary algorithm. Plant Physiol. 145, 513–526. Zimmermann, P., Hirsch-Hoffmann, M., Hennig, L., Gruissem, W., 2004. Genevestigator. Arabidopsis microarray database and analysis toolbox. Plant Physiol. 136 (1), 2621–2632.

Further reading Kuiper, H.A., Kleter, G.A., Noteborn, H.P., Kok, E.J., 2001. Assessment of the food safety issues related to genetically modified foods. Plant J. 27, 503–528.

Chapter 16

Metabolomics-assisted crop improvement Ruchi Agarrwal and Suresh Nair Plant-Insect Interaction Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India

Agriculture is the mainstay of human survival and the backbone of most economies. As per a United Nations estimation (Anonymous, 2017), the global population may reach 9.8 billion by the year 2050. Under such a scenario, improved crop varieties with enhanced yield potential and nutritional quality as well as resistance to biotic and abiotic stresses would be needed to ensure an adequate food supply to the world. This can be achieved through the application of advanced molecular tools, including both nontransgenic (QTL-based) and transgenic methods. Association mapping and marker-assisted breeding (MAB) are potentially useful for mapping studies and subsequent allele mining (Takeda and Matsuoka, 2008). Traditional varieties, when bred with wild species of the respective crops, may reveal novel genetic variations that may be successfully introgressed into cultivated crops for imparting tolerance against multiple stresses that may challenge global crop production. This is likely to be very relevant in the coming years as global warming is expected to give rise to unpredictable environmental conditions. Thus, the conservation of traditional varieties and wild species of crop plants becomes imperative. This will not only prevent their loss by genetic erosion, but will pave the way for future crop improvement. Plants are sessile organisms, and therefore cannot escape from adverse environmental conditions. They can only trigger or modify certain metabolic pathways to overcome the difficulties imposed by the stress factors. Thus, an understanding of how such organisms deal with adverse environments gains practical significance in agriculture. Advanced genetics as well as conventional plant breeding-based methods have aided the progress toward increasing crop productivity in the last few decades. Efforts to develop stress-tolerant transgenic plants or those with improved agronomic traits are also under way. However, approvals and the large-scale commercialization of transgenic crop plants in many countries such as India are still years away. Consequently, utilizing the naturally occurring resistance mechanisms in plants against biotic or abiotic stress factors becomes a safe and acceptable option.

1 Plant metabolome and metabolic pathways Metabolites are said to be the end product of gene expression and protein activity. Plant metabolites have been classified in two ways: primary metabolites produced during the primary metabolism and involved in plant growth and development, or secondary metabolites produced during the secondary metabolism and involved in chemical defenses against pests and pathogens. These secondary metabolites may not be directly involved in plant growth and development (Bennett and Wallsgrove, 1994; Theis and Lerdau, 2003; Mao et al., 2007). Interestingly, the scientific literature provides plenty of examples where primary metabolites have been shown as equally active and important in host defense as the secondary metabolites (reviewed by Schaaf et al., 1995; Schwachtje and Baldwin, 2008). Primary metabolites such as sugars (Wingler and Roitsch, 2008), fatty acids (Upchurch, 2008), amino acids (Liu et al., 2010), and sterols (Sharfman et al., 2014) are involved in plant response to abiotic stress factors as well as defense against pathogens and herbivores. Furthermore, the plant stress response against biotic or abiotic factors is an interplay of various lines of defense. The primary metabolites may serve as central points for pathway crosstalk, resulting in signal integration for a coordinated defense response. For example, plant defense mechanisms against pests and microbial pathogens (Bostock et al., 2001) or abiotic stress (Tumlinson and Engelberth, 2008) are not mutually exclusive from each other. Therefore, to study the connection between different pathways (metabolic and defense), experimental approaches involving metabolomics and its subsequent integration with transcriptomics or proteomics can be used. Moreover, with advancements in highthroughput (HTP) techniques, the quantitative and/or qualitative analyses of spatial and temporal alterations in gene expression (transcriptomics), protein activity (proteomics), and metabolite abundance (metabolomics) will unveil the complex metabolic diversity of plants. Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00016-4 © 2020 Elsevier Inc. All rights reserved.

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Acquire mass spectral data

Design experiment, harvest tissue and extract metabolites

Peak deconvulation and curation

m/z 204 m/z 133

m/z 131 m/z 129

m/z 374

Metabolite identification

m/z 368

Hypothesis

6

Data

Metabolites 4

Univariate statistical analysis

2 0

Component 2 (75.1%) –3000 0 3000

Data normalization

+ Infested + Un-Infested

Samples

Relative abundance

Interpretation

Experiments

Generation of data matrix

Multivariate statistical analysis –5000 0 5000 Component 1 (20.3%)

FIG. 1 Steps involved in a typical metabolomics-based plant study that may be designed to answer a complex biological question or to generate a hypothesis pertaining to the biochemical mechanism of stress response.

Metabolites may be considered determinants of the biochemical phenotype of an organism. Thus, the study of the plant metabolome becomes a convenient tool to reveal the underlying biochemical principle of plant stress response (Fiehn, 2006; Fig. 1). Further, an analysis or comparison of the metabolome under different environmental conditions leads to information related to biochemical changes occurring during organ differentiation and development during plant growth or the compositional and nutritional quality of crops (Harrigan et al., 2007).

2

Metabolomics

Metabolomics includes the detection of metabolites with known chemical structures and functions, followed by their identification and quantification. It also accounts for the presence of novel metabolites with unknown structures and undefined biological functions. Moreover, it directly correlates the phenotypic plasticity of a cell with the biochemical fluctuations taking place inside it. However, it may not benefit directly from the results of whole genome sequencing projects because there is no linear relationship between the genome sequence and the metabolome of an organism (Saito and Matsuda, 2010). Multiple analytical platforms have been developed that can perform metabolomics and assess biochemical changes occurring in biological systems exposed to genetic perturbations or any (a)biotic stress (Balmer et al., 2013). However, none of the analytical platforms or extraction methods when used individually can cover the total biochemical diversity of a cell (Lei et al., 2011).

2.1 Practical approaches in metabolomics Studies focussing on the analysis of one or a few metabolites are not uncommon in the scientific literature. However, studying one metabolite or one pathway at a time is not only time-consuming, but also overlooks the global effect of the experimental treatment to which the system is subjected. This shortcoming in the earlier approach has led to advancements in HTP metabolomics that mainly involve two practical approaches-targeted and nontargeted metabolomics (Goodacre et al., 2004, reviewed by Patti et al., 2012), as discussed below.

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2.1.1 Targeted metabolomics This methodology involves profiling known metabolites with defined chemical structures and carrying out their quantifications by using authentic chemical standards (Albinsky et al., 2010; Dudley et al., 2010). Thus, this approach is limited to the analysis of only a narrow range of metabolites. The preferred analytical platforms for carrying out targeted metabolomics are gas chromatography (GC) or liquid chromatography (LC), coupled with triple quadrupole mass spectrometry (MS; Lisec et al., 2006, Lu et al., 2008). Targeted metabolomics may not be very effective in deducing the functions of an unknown gene (over- or underexpressed) in the system under study. This is because it may not offer a comprehensive picture of the entire metabolic perturbations with respect to altered gene expression, and analysis will be inclined toward those metabolites for which authentic standards are available (Kueger et al., 2012).

2.1.2 Nontargeted metabolomics Nontargeted metabolomics expands its analysis from known to novel or unknown metabolites by either metabolic fingerprinting or metabolic profiling (Last et al., 2007; Allwood and Goodacre, 2010). This results in raw data that can be analyzed by multivariate (MVA) statistical tools to obtain meaningful information regarding metabolic biomarkers whose concentrations are significantly different between samples under study. GC or LC coupled with time-of-flight (TOF) are commonly used analytical platforms for nontargeted metabolomics. Nuclear magnetic resonance (NMR) can also be used to deduce the chemical identity of the unknown compounds identified by nontargeted metabolomics (Kim et al., 2011a, b; Kueger et al., 2012). The advantages and disadvantages of these methods are discussed later in this chapter.

2.1.3 Metabolomics at the cellular and subcellular levels Researchers in metabolomics may also be interested in determining the spatial distribution of metabolites at the cellular or subcellular level. Several methods have been established to explore the distribution of metabolites at the tissue level. These include matrix-associated laser desorption ionization-mass spectrometry imaging (MALDI-MSI; Kaspar et al., 2011), desorption electrospray ionization (DESI)-MSI (M€uller et al., 2011), laser capture microdissection (LCM; Kerk et al., 2003; Nakazono et al., 2003), and cell sap sampling (CSS), combined with GC-MS or capillary electrophoresis (CE; Lochmann et al., 1998, 2001; Ebert et al., 2010). To determine the subcellular distribution of metabolites, the following approaches can be used: nanosensor based on fluorescence resonance energy transfer (FRET; Fehr et al., 2005; Looger et al., 2005), protoplast fractionation (PF) or nonaqueous fractionation (NAF; Robinson and Walker, 1980; Gerhardt and Heldt, 1984), or NMR spectroscopy (Aubert et al., 1999; Gout et al., 2011). Furthermore, a recently developed in vivo sampling mode of direct immersion-solid phase microextraction (DI-SPME) can capture the entire metabolome of entire living plant specimens (Risticevic et al., 2016).

2.2 Integration of metabolomics with other “omics” The complexity of living systems increases many-fold as we ascend life’s “complexity pyramid” (Oltvai and Baraba´si, 2002). To investigate this complexity at the molecular or cellular level, genomics, transcriptomics, proteomics, and metabolomics data can be used. Unlike transcriptomics and proteomics, the metabolomics results are difficult to interpret. This is because the enhanced relative abundance of transcripts or proteins can be expected to correlate to their enhanced biological activity. However, an increase in the abundance of metabolites may not directly correspond to its increased biological function due to several factors, as discussed by Fernie and Stitt (2012). Thus metabolomics, when integrated with genomics, transcriptomics, or proteomics, can reproduce a complete snapshot of the biological functioning of a system (Fiehn et al., 2001).

2.2.1 Integration of metabolomics with transcriptomics Microarrays and next-generation RNA sequencing (RNA-Seq) techniques are the most popular and hence widely used approaches for transcript profiling (Zhao et al., 2014). However, transcript profiling using standardized methods in isolation cannot represent a complete scenario of the biochemical regulation in a cell that may occur at different levels such as mRNA, proteomic or enzymatic, and metabolic (Stitt, 1990; ter Kuile and Westerhoff, 2001). Consequently, the integration of data obtained from transcript profiling with metabolite profiling may be a state-of-the-art approach to unveil the relationship between the genotype and phenotype of an organism (Hirai et al., 2004). Particularly, targeted metabolomics in conjunction with gene expression profiling can identify the genes that are responsible for alterations in the abundance of a specific metabolite in microbes (Askenazi et al., 2003) or plants (Goossens et al., 2003). On the contrary, nontargeted

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metabolomics in conjunction with transcript profiling would be useful to demonstrate the relationship between metabolism and gene functioning inside a whole cell (Hirai et al., 2004). For example, an integrated study of transcriptomics and nontargeted metabolomics led to deeper insights into the resistance mechanism exhibited by an indica rice variety against one of its major pests, the Asian rice gall midge (AGM; Agarrwal et al., 2016). Thus, the integration of data obtained from transcriptomics and metabolomics can provide a comprehensive snapshot of gene expression and the biochemical composition of a living system under a given environmental condition (Table 1).

2.2.2 Integration of metabolomics with proteomics An integration of metabolomics with proteomics may unveil the alterations in the metabolite and the protein composition of a cell required to manifest phenotypic plasticity by the organism, including plants (Chen et al., 2012; Zhang et al., 2013). For example, identification of resistance-related biochemical(s), obtained by the integration of data obtained from metabolomics and proteomics of plant-pathogen interaction (Kushalappa and Gunnaiah, 2013), may provide researchers vital clues leading up to the identification of resistance-related genes. Both metabolomics and proteomics rely heavily on the use of MS and several hyphenated techniques (such as GC-MS and HPLC-MS) that have been put to use to comprehensively study the metabolome and proteome of biological systems. For example, LC-MS/MS was used to study the metabolic and proteomic response of maize to drought stress (Alvarez et al., 2008) and LC-MS in conjugation with GC-MS was used to

TABLE 1 Summary of recent studies based on the integration of metabolomics with transcriptomics to study various aspects of plant biology. Plant

Aspect of plant biology studied

Metabolomics technique

Transcriptomics technique

Grape

Fungal pathogenesis

NMR

Microarray

Figueiredo et al. (2008)

Rice

Bacterial pathogenesis

GC-TOF-MS, LC-TOF-MS

Microarray

Sana et al. (2010)

Tobacco

Insect herbivory

LC-TOF-MS

Microarray

Kim et al. (2011a, 2011b)

Tomato

Fruit development

GC-MS, LC-MS

Microarray

Rohrmann et al. (2011)

Oak

Insect herbivory

FT-ICR-MS

RNA-Seq

Kersten et al. (2013)

Tomato

Hypersensitive response

GC-MS, LC-TOF-MS, GC-FID

Microarray

Etalo et al. (2013)

Grape

Fruit development

GC-MS, LC-MS

RNA-Seq

Degu et al. (2014)

Bermuda grass

Abiotic stress

GC-MS

RNA-Seq

Shi et al. (2015)

Grape

UV-C

LC-MS

Microarray

Suzuki et al. (2015)

Wheat

Fungal pathogenesis

LC-MS, GC-MS

RNA-Seq

Rudd et al. (2015)

Medicago

Root cell, border cell metabolism

GC-MS, LC-MS, UPLC

Microarray

Watson et al. (2015)

Eucalyptus

Insect herbivory

GC-MS

RNA-Seq

Oates et al. (2015)

Citrus

Fruit senescence

GC-MS, HPLC-TOF-MS

Microarray

Ding et al. (2015)

Medicago

Fungal pathogenesis

LC-TOF-MS

Microarray

Ishiga et al. (2015)

Rice

Insect herbivory

GC-MS

Microarray

Agarrwal et al. (2016)

Allium

Addition of chromosome

LC-MS

RNA-seq

Abdelrahman et al. (2019)

Note: Table is chronologically arranged.

Reference

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study changes in the maize metabolome and proteome during nitrogen assimilation (Amiour et al., 2012) or its deficiency (Amiour et al., 2014). The isolation and characterization of a single protein is routinely performed in biological research; however, with the advent of MS-based high-throughput proteomics (HTP) techniques, the identification and quantification of hundreds of proteins at once has become possible. Though fundamentally different, the two techniques have been widely employed for HTP: (i) two-dimensional gel electrophoresis-based separation of proteins followed by MS analysis, and (ii) shotgun proteomics (Koller et al., 2002; Schmidt et al., 2004; Weckwerth, 2008). Each possesses several advantages as well as shortcomings over the other.

3 Metabolomics-assisted crop improvement Of more than 50,000 edible plant species in the world, only a few hundred contribute significantly to food supplies. Just 15 crop plants provide 90% of the world’s food energy intake, with three—rice, maize, and wheat—accounting for 60% of the same (Loftas and Ross, 1995). To meet the ever-growing food demand of a rapidly growing world population, there is tremendous pressure on breeders and researchers to introduce crop species that will realize their full yield potential, resist pests and diseases, and tolerate changing climatic conditions. The nontargeted metabolic profiling (Section 2.1.2) provides an unbiased snapshot of metabolites present in the plant cell or tissue (spatial) at a given point in time (temporal) under normal or stress conditions (comparative metabolomics). The enormous data thus obtained can be channeled for an efficient metabolomics-assisted crop improvement program (Fernie and Schauer, 2009), as discussed below (Fig. 2). Traditionally, researchers and breeders focused upon a single metabolic trait or a group of metabolic traits (having industrial or nutritional value) such as the protein content of maize, the carotenoid content of tomatoes, and the starch content of potatoes and rice (Moose et al., 2004; Fernie et al., 2006). However, with the advent of modern techniques, the natural variations in the overall chemical compositions of several crop plants such as rice (Kusano et al., 2007), tomatoes (Schauer et al., 2005), potatoes (Roessner et al., 2001), maize (Harrigan et al., 2007), and barley (Huang et al., 2008) have been studied, and the results obtained from such studies may be crucial to design crop improvement methodologies for these crops. For instance, MALDI-TOF-MS has been successfully employed to screen tomato germplasms with high levels of carotenoids (Fraser et al., 2007) that can be used for breeding of plants with high antioxidant levels. The discovery of metabolic quantitative trait loci (mQTLs) by metabolic profiling and the corresponding metabolomebased genome-wide association studies (mGWAS) of plant genotypes have further strengthened the involvement of metabolomics in the selection of elite breeding lines or metabolic marker-assisted breeding programs. Although all the genes located in the QTL region are difficult to study and verify using modern biotechnological tools such as the transgene approach, the mQTLs can be used for marker-assisted breeding if the necessity to characterize the underlying gene can be overlooked (Kaur et al., 2015). Several studies have reported mQTLs in economically important crops such as maize (Harrigan et al., 2007), rice (Matsuda et al., 2012), wheat (Hill et al., 2015), mustard (Feng et al., 2012), and tomato (Causse et al., 2002; Schauer

FIG. 2 A flowchart of the processes or methodologies that could be followed to use metabolomics in crop improvement. (Adopted from Hong et al., 2016).

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et al., 2006; Tieman et al., 2006). Schauer et al. (2006) concluded that the mQTLs were mostly dominantly inherited. However, they observed less association between morphological and metabolic traits in the ILHs (introgression line hybrids) that were heterozygous for the introgression than in the ILs (introgression lines), which is suggested to have wide implications for breeding strategies. Several mGWAS have found association between the genomic region and the metabolic content of crop species, for example, pro-vitamin A content (Palaisa et al., 2003), kernel composition and starch content (Wilson et al., 2004), lignocellulosic biomass quality (Riedelsheimer et al., 2012) in maize, phytate content in mustard (Zhao et al., 2007), secondary metabolite composition in rice (Chen et al., 2014; Matsuda et al., 2015), and multitraits in sugar beets (Stich et al., 2008). Interestingly, in a study on sesame, it was found that the metabolic and genetic diversity lacked association between them. However, the data suggested that metabolomics can be used as a means of selection during breeding along with data obtained after screening sesame populations with neutral DNA markers (Laurentin et al., 2008). An integration of information obtained from genomics and metabolomics provides newer insights on gene annotation (Goossens et al., 2003) while that of transcriptomics and metabolomics leads to a better understanding of the gene regulation network (Urbanczyk-Wochniak et al., 2003) in complex biological systems such as plants. These integrated approaches have led to the identification of several candidate genes including those whose expression correlates strongly with the levels of metabolites with important nutritional or organoleptic properties (Causse et al., 2002; Fridman et al., 2005). Recently, the integrated transcriptomic and metabolomic analyses of Allium fistulosum, monosomic for a chromosome from A. cepa, identified a “hotspot” in a chromosome involved in inducing flavonoid accumulation in A. fistulosum (Abdelrahman et al., 2019). Moreover, if suitable information on the regulation of metabolic pathways is made available, genetic engineering techniques can be employed to modify the metabolism of an organism—a process known as metabolic engineering. It involves two aspects: the optimization of existing biochemical pathways or the introduction of pathway components. Interestingly, in a study (Schauer et al., 2006) based on a GC-MS analysis of 76 tomato Ils, it was suggested that in order to have a greater impact on plant morphology, the manipulation of “more central” metabolic pathways should be attempted rather than “less central” pathways. Metabolic engineering can thus be an instant way of employing metabolomics for crop improvement strategies. One of the most popular and significant examples of metabolically engineered plants is opium-free poppies (Allen et al., 2004; Millgate et al., 2004; Larkin et al., 2007). This involved the transgenic expression and RNAi silencing of genes encoding enzymes involved in the benzyl-isoquinoline pathway to modulate the production of morphine and other pharmaceutically important products such as thebaine (precursor for some analgesics). Metabolic engineering can also be employed to enhance the nutritional quality of food crops, for example quality protein maize (QPM, the winner of the World Food Prize in 2000), which is a mutated version of maize for the higher production of lysine (Vietmeyer, 2000; Prasanna et al., 2001). However, certain unintended changes also occurred in these plants such as alterations in the levels of other free amino acids (Wang and Larkins, 2001). Such unintended side effects while generating a genetically modified (GM) plant can also be analyzed at the metabolic level by performing nontargeted metabolic profiling, providing a metabolic snapshot of GM plants. A comparative metabolomics study is thus useful for establishing substantial equivalence of GM crops. For example, the LC-MS-based targeted metabolic profiling of transgenic rice (having a mutated anthranilate synthase gene for feedback inhibition-insensitive synthesis of tryptophan) found elevated levels of free tryptophan and only minor changes in levels of other free amino acids (Wakasa et al., 2006) and downstream metabolites (Dubouzet et al., 2007). Several other crops such as soy (Padgette et al., 1996), potatoes (Hellwege et al., 2000), wheat (Obert et al., 2004), and alfalfa (McCann et al., 2006) have also been analyzed at the metabolic level to establish substantial equivalence between their GM and non-GM counterparts. Furthermore, a thorough study of a metabolic mutant may lead to better insights into gene function characterization. Knock-out mutants of the PAL gene (phenylalanine ammonia lyase) involved in the phenylpropanoid pathway in Arabidopsis accumulated higher levels of phenylalanine and also showed perturbed metabolisms of other aromatic amino acids (Rohde et al., 2004). A thorough study of the metabolites involved in plant growth and development as well as the response to various stress conditions can lead to the identification of metabolic biomarkers for particular environmental conditions under study or the developmental stage of the plant. For example, tomato seeds and flesh exhibited differences between their metabolic composition at all developmental stages (Mounet et al., 2007), an observation that can guide successful breeding programs. This is critical for the introduction of desired biological features (Salekdeh and Komatsu, 2007) to a crop plant as a step toward crop improvement to enhance the yield or sustainability of production. However, the identification of metabolic biomarkers involves the intensive use of univariate and multivariate statistical analysis of metabolic data. GC-MS based nontargeted metabolic profiling of rice has been utilized to identify a set of biomarkers for the developmental stages of rice (Tarpley et al., 2005) or its interaction with an economically important pest, AGM (Agarrwal et al., 2014). Metabolites involved in the salt stress adaptive mechanism of wild and cultivated soybeans have also been recently revealed (Li et al., 2019).

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Comprised mainly of organic acids, sugars, fatty acids, and amino acids, these “biomarker sets” could pave the way for a targeted approach for subsequent studies.

4 Computational analysis High-throughput metabolomics studies generate a huge amount of data that is impossible to handle manually, therefore requiring the computational analysis of such data (Arita, 2004). Instruments such as GC-MS, LC-MS, or NMR can detect even tiny peaks with high resolution, after which these peaks need to be resolved by precise system software. This software is also capable of identifying (similarity search against a library as in the case of MS) or quantifying (against authentic standards) each metabolite. Therefore, computational analysis holds an important place in a complete metabolomics study. Several databases and software programs are available online that allow an easy flow of information in the field of metabolomics. For example, DrDmassPlus (http://kanaya.naist.jp/DrDMASSplus/) is software for processing FT-ICR-MSbased metabolome data and KNApSAcK (http://kanaya.naist.jp/KNApSAcK/) is one of the comprehensive metabolite databases containing information on thousands of metabolites. Metaboanalyst is an online tool for statistical analyses of metabolomics data (https://www.metaboanalyst.ca/). No metabolomic study is complete without subjecting its data to statistical analysis. Several univariate and multivariate statistical analyses can be performed on the data to obtain meaningful information from raw data. For example, univariate analysis such as ANOVA followed by a posthoc test of data obtained in a comparative metabolomic study of rice tissue during its interaction with AGM led to the identification of metabolic biomarkers for the interaction (Agarrwal et al., 2014). Multivariate analysis such as principal component analysis (PCA) or partial least squares-discriminant analysis (PLS-DA) can be useful to identify features responsible for maximum variation and separation between components (Worley and Powers, 2013). These statistical tools also allow researchers to identify outliers, if any, in their datasets (Breiman, 2001).

5 Technological advancements and limitations Modern metabolomics techniques have two dimensions: a high-resolution separation technique primarily based on chromatography such as GC or high performance liquid chromatography (HPLC), or CE and a highly sensitive detection technique such as NMR or MS. NMR has the advantage of linear quantitative response, that is, large signals of a given metabolite in NMR can be directly interpreted as high concentrations of that metabolite while MS performs better than NMR in the following aspects: (i) resolving complex mixtures of compounds, (ii) sensitivity, (iii) cost effectiveness, and (iv) ease of coupling with chromatographic techniques. These advantages of MS over NMR led to the advent of “hyphenated” techniques (term first used by Hirschfeld, 1980) such as GC-MS, HPLC-MS, and CE-MS that can be successfully used in metabolomics (reviewed by Fiehn, 2006). The advantages and disadvantages of most of the techniques (Kopka et al., 2004; Kopka, 2006; Leiss et al., 2011; Barding et al., 2012) popularly used for metabolomics are summarized in Table 2. It will be exciting to unveil the entire metabolome of a plant just like a whole genome project, but there are many hurdles in the way of achieving this goal. Recent years have seen dramatic advancements in the techniques being utilized for metabolomics studies. However, these analytical advances and enhanced computational capabilities still leave behind some concerns related to the acquisition, interpretation, and statistical treatments of omics data, particularly involving nontargeted approaches (Broadhurst and Kell, 2006; Lay Jr. et al., 2006). Metabolomics itself or its integration with other highthroughput techniques results in huge datasets that can be difficult to analyze and report. Moreover, a large repertoire of metabolites still remains unidentified and structurally uncharacterized, leaving bulk information nonextractable.

6 Conclusion and future prospects Breeding-based crop improvement usually depends on phenotypic performance and/or the presence of genetic markers. However, the use of the emerging field of metabolomics, mQTLs, and mGWAS will lead to a better choice and selection of elite lines for breeding. Moreover, its integration with data obtained from other omics studies will reveal the regulatory mechanism behind metabolic pathways that may be directly involved in the expressions of traits of agronomic value. This will allow breeders or researchers to produce metabolically engineered plants, either by conventional breeding or through the use of modern biotechnological techniques. Further, these engineered plants can be useful for gene function characterization. The identification of metabolic biomarkers during plant stress response indicates that metabolomics-assisted crop improvement is the key to future food security as well as raising plants that are capable of combating adverse environments. Metabolomic profiling in crop plants can be further exploited to develop future crop improvement strategies.

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TABLE 2 Summary of advantages and disadvantages of analytical techniques being routinely applied to the field of metabolomics. Technique or analytical platform

Advantages

Disadvantages

GC-MS

Low cost, high chromatographic resolution and reproducibility, high repeatability in mass spectral fragmentation, fewer matrix effects, faster scanning rates

Need for chemical derivatization of nonvolatile metabolites into volatile derivatives, stereoisomers, alpha-beta anomers not differentiated, need for chemical standards for absolute quantification

LC-MS

Separation of high molecular weight compounds, selectivity, unbiased identification

Lack of automated procedure for evaluation, stereo-isomers, alpha-beta anomers not differentiated

CE-MS

Higher sensitivity and flexibility

Stereo-isomers, alpha-beta anomers not differentiated

NMR

Noninvasive structural analysis of metabolites, identification of novel compounds, chemical standards not required, simultaneous identification and quantification of metabolites, reproducible

High cost, lower sensitivity and resolution, smaller dynamic range, and detects fewer metabolites

Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS)

Greater accuracy even at sub ppm levels

Lack of method validation, high cost, low scanning rates

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Chapter 17

Improving medicinal crops through phytochemical perspective: Withania somnifera (Ashwagandha) Yashdeep Srivastavaa and Neelam S. Sangwana,b a

CSIR-Central Institute of Medicinal and Aromatic Plants (CIMAP), Lucknow, UP, India, b Department of Biochemistry, Central University of Haryana,

Jant-Pali, Mahendergarh, Haryana, India

1 Introduction Crop improvement has always been a part of human development, as the population depends on crops to fulfill their need for food and medicines (Raskin et al., 2002). Crop improvement includes several prospects such as increased tolerance of the crops toward biotic and abiotic stresses, increased nutritional value, and increased yield. Crop improvement is also needed to fill the gap between the demand and supply of plant-based products, as the global population is continuously increasing along with decreases in total cultivable area due to urbanization (Smil, 2001). Because of this, plant biologists have been facing the challenges of boosting crop productivity within a restricted land area as well as limited water supply with limited use of chemicals for environmental protection. This current genomic era with advanced molecular biology tools provides prospects for plant scientists to produce crops with advanced traits (Easterling et al., 2007). The identification of molecular markers provides a backbone to plant breeders and is helpful in terms of marker-assisted breeding. Isolation, cloning, overexpression, silencing, and transgenesis of important genes are also promising approaches to produce plants with improved qualities. Metabolomics, proteomics, transcriptomics, and genomics along with markerfree transformation also act as supportive means for crop improvement (Gupta et al., 2012; Sangwan and Sangwan, 2013; Tripathi et al., 2017).

2 Diverse species of W. somnifera A total of 61 species of the genus Withania are known throughout the world, among which only five—Withania somnifera (L.) Dunal, Withania japonica (Franch and Sav) Hunz., Withania coagulans (Stocks) Dunal, Withania frutescens (L.) Pauquy, and Withania begonifolia (Roxb.) Hunz.—have an accepted name status (The Plant List, 2013). Among this diversity of genus Withania, India is represented basically by the two most eminent ones, that is, W. somnifera and W. coagulans. Recently, a new species of Withania was reported from the Indian germplasm and designated as Withania ashwagandha (Kumar et al., 2011).

3 Ethnobotany of W. somnifera Since antiquity, people have used plants as a source of medicine, food, dye, oil, gum, resin, wax, latex, soap, etc. The people of a native region even use plants in their ceremonies and spiritual rituals. According to the US Department of Agriculture (USDA), ethnobotany is mainly the study of how people of a particular culture or region make use of indigenous plants. W. somnifera has been used since time immemorial to treat different types of health issues in India and other parts of the world. In India, it was used as rasyana (a tonic) and regarded as Medharasayana due to its memory-enhancing activity or “Sattvic Kaph rasayana,” that is, a tonic that regulates the master fluid of a body. It is used in Ayurveda for the treatment of goiters, boils, pimples, flatulence, leucorrhoea, oligospermia, constipation, piles, and leucoderma (Singh et al., 2011). The plant is also used to clear the white spots of the cornea and also to treat hysteria, memory loss, and debility in old age. The herb is also used to treat emaciated children and the loss of muscular energy in the body (Chatterjee et al., 2010; Advancement in Crop Improvement Techniques. https://doi.org/10.1016/B978-0-12-818581-0.00017-6 © 2020 Elsevier Inc. All rights reserved.

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FIG. 1 Major approaches for improvement of W. somnifera.

Ahmad et al., 2014). In Unani and homeopathic medicine systems, drugs derived from W. somnifera are also used to treat various malfunctions of the body such as antiinflammatory, sedative, hypnotic, narcotic, general tonic, anticancer, aphrodisiac, bone strengthening, anti-Parkinsons, and neuroprotection (Ahmad et al., 2005, 2016a; Mondal et al., 2010, 2012; Uddin et al., 2012; Khedgikar et al., 2013, 2015). Major approaches for improvement and production potential of Ashwangandha may include metabolic engineering, in vitro-based methods, and in silico and marker-based approaches, besides conventional breeding approaches (Fig. 1).

4

Withanolides: The signature molecules of W. somnifera

Withanolides belong to a natural class of steroid-based molecules on an ergostane framework and are identified by the presence of a lactone-containing side chain (Fig. 2). The involvement of the steroid nucleus, the side chain, and an n-number of additional rings is the basis of the structural diversity between these compounds (Chaurasiya et al., 2009). These molecules are produced by the involvement of two pathways, MVA and DOXP (Fig. 3) (Chaurasiya et al., 2008, 2012).

5

Development of improved varieties of W. somnifera

The development of a superior variety is the major goal of any researcher in plant science. Both conventional and nonconventional approaches are being applied to improve or alter the characteristics or traits of a plant. Conventional approaches include breeding approaches such as germplasm evolution, mutagenesis, hybridization, interspecific hybridization, etc. Nonconventional approaches include approaches based on in vitro methods such as tissue culture (somaclonal variation) and biotechnological approaches (genetic engineering/metabolic engineering). While conventional approaches have served the world for a long time with promising developments, modern approaches that utilize the latest tools and techniques are considered precise and targeted. In this section, we will discuss them in detail.

5.1 Improvement in W. somnifera by conventional approaches Breeding programs at various research centers such as ICAR and the CSIR-Central Institute for Medicinal and Aromatic Plants (CIMAP), Lucknow, have resulted in the release of a few promising varieties for commercial cultivation. Some improved varieties were earlier made available such as JA-20 and JA-134 from Jawaharlal Nehru Krishi Vishwavidyalaya, Mandsaur. Recent efforts resulted in CIM-Pratap, CIM-Chetak (Naguri withania variety), NMITLI-118, NMITLI-101, Rakshita, and Poshita varieties from CIMAP. WS 20 was a selection variety developed for increased dry root yield (about 30%) and alkaloid content over local varieties such as Mansa and Kukedesher (Nigam, 1991). This variety is stable over a wide range of environments as compared to the wild varieties. Poshita was developed as a selection variety from breeding methods (Misra, 2001) Rakshita was developed by CSIR-CIMAP, and produces approximately 10 quintal of roots per hectare with 0.5% alkaloid content. Extensive phytochemical screening of W. somnifera plants from diverse habitats

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R2 R1

OH

O

O O

O O

O

O

O

OH

Withaferin A

Withanone

HO OH

R1

R2 R3

H

O

O

O

O

OH

O O

O OH

Withanolide E

Withanolide G

HO H H O

O

OH

O

O OH

O

O OH OH

OH

O

Withanolide R

Withanolide P

O

O

H O

H H OH

OH

H H

S

OH OH

H H

O

H O

O

HO

Ashwagandhanolide

FIG. 2 Structures of withanolides from W. somnifera.

by our research group resulted in the development of new and elite varieties of W. somnifera under the CSIR-NMITLI program. These varieties are known as NMITLI-118, NMITLI-101, whereas NMITLI 128, and NMITLI-135 are extensively characterized distinct chemotypes (Sangwan et al., 2008; Chaurasiya, 2007; Kushwaha et al., 2013). So far, these are the best varieties in terms of overall yield as well as phytochemical quality of roots (Chaurasiya et al., 2009). CIM-PRATAP was another variety of W. somnifera produced by selection breeding (Lal et al., 2012) for drought-prone areas of the country with better withanolide content as compared to the Poshita variety.

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MVA pathway

MEP pathway

Cytosol

Plastid Pyruvate

Acetyl Co-A

Acetyl Co-A

GA-3P

ACT DXS

AcetoacetylCo-A

DOXP

HMGS

DXR

HMG Co-A HMGR

MEP

Mevalonate MVAK

IPP

Mevalonate phosphate

DMAPP

MVAPK

IDI

Mevalonate diphosphate MVAPPD

DMAPP

IPP GPPS

Geranyl pyrophosphate FPPS

Farnesyl pyrophosphate SQS

Squalene SQE

2,3 -Oxidosqualene

Withaferin A, Withanolide A, Withanolide D

CAS

Cycloartenol SMT

24 -Methylenecycloartenol ODM

24 -Methylenecholesterol

CYP

Obtusifoliol

FIG. 3 Representative biosynthetic pathway of withanolide.

5.2 Improvement by nonconventional approaches 5.2.1 Technical advancement of W. somnifera In the modern era, researchers are developing advanced technologies to combat challenges in conventional agricultural systems throughout the world. In W. somnifera, the major advancements are achieved by applying various technologies such as breeding, metabolomics, computational biology, modern molecular biology, and tissue culture. These approaches have proven to be helpful in the development of W. somnifera plants with better survival efficiency with improved metabolite content, both qualitatively and quantitatively. Also, these approaches provide a better understanding of various physiological processes in W. somnifera. A number of genes involved in the biosynthesis of withanolides were successfully recognized and characterized for the identification and confirmation of their role in the metabolic pathway (Sharma et al., 2007; Madina et al., 2007a,b; Gupta et al., 2012; Grover et al., 2013; Razdan et al., 2013; Tripathi et al., 2017, 2019).

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Protocols were established for the stable as well as transient transformation of W. somnifera (Mishra et al., 2013). Successful heterologous gene transfers from plants such as Pelargonium and Ocimum were also achieved in W. somnifera to study the terpene biosynthesis pathway ( Jadaun et al., 2017a,b; Bansal et al., 2018). Tissue cultures and cell suspension cultures provided a platform for a better understanding of the role of elicitors and hormones on the physiological and metabolic processes of the plant (Sabir et al., 2008, 2010, 2012; Sivanandhan et al., 2012, 2013). Advancements in next-generation sequencing technologies increased the repertoire of information associated with gene expression in different tissues, specifically chemotypes and stress conditions (Dasgupta et al., 2014; Gupta et al., 2013, 2015; Tripathi et al., 2017, 2019). In the following sections, we focus on technical advancements in W. somnifera by the application of different approaches in detail.

5.2.2 Application of metabolic engineering Modern techniques, especially related to molecular biology, are being used to identify and reveal the biosynthesis and regulation of pharmacologically important molecules in W. somnifera (Nafis et al., 2011; Sangwan et al., 2017, 2018). To uncover the steps involved in the biosynthesis of a metabolite, overexpression and silencing of a gene are the two major approaches. These are involved in the alteration of the level of a metabolite accumulating as an end product of a pathway (Table 1). The identification and functional characterization of the genes related to the synthesis of key metabolites would allow manipulating the production by metabolic engineering. Earlier approaches in other medicinal plants have shown great promise (Hiei et al., 1994; Fischer et al., 2001; Nafis et al., 2011; Jadaun et al., 2017a,b; Bansal et al., 2018). In W. somnifera as well, such approaches will be highly useful to improve the yield of such molecules for drug development. 5.2.2.1

Functional characterization of enzymes involved in early biosynthetic steps

The pathway for withanolide biosynthesis involves the participation of both the classical MVA and the DOXP pathways. The MVA pathway has long been identified as a major pathway for the synthesis of isoprenoids to provide IPP. The enzyme that is involved in the catalysis of the initial steps of IPP biosynthesis, that is, 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR), was cloned and characterized from W. somnifera (Akhtar et al., 2013). The report showed that the gene was expressed differentially in tissues and its level increases by the treatment of elicitors such as SA and MeJA as well as mechanical injury. The researchers also compared the chemotype-associated expression level of HMGR and found its significant correlation between withanolide biosynthesis and gene expression. Furthermore, the exogenous HMGR in overexpression studies also confirmed the participation of HMGR in withanolide biosynthesis and other terpenoids (Bansal et al., 2018). WsDXR2 (1-deoxy-D-xylulose-5-phosphate reductoisomerase) and WsHMGR2 (hydroxymethylglutaryl-CoA reductase) were characterized by Singh et al. (2014) to study the functional role of MEP (2-C-methyl-D-erythritol-4-phosphate) and MVA (mevalonic acid) pathways on withanolide and the sterol biosynthetic pathway in W. somnifera. Transgenic tobacco overexpressing WsHMGR2 showed a higher accumulation of campesterol and stigmasterol as compared to the WsDXR2 transgene lines while the withanolide content was transiently suppressed in W. somnifera, in which the HMGR and DXR genes were inhibited. However, when these sterols (campesterol or stigmasterol) were fed, then again it was found that the withanolide content was increased. This indicated that the leading pathways for withanolide biosynthesis passed through the stigmasterol or campesterol. The multiple genes of the pathway such as WsDXS, WsDXR, WsHMGR, WsFPPS, and WsDWF5 were silenced and their effects were reported in earlier studies (Jadaun et al., 2017a,b; Bansal et al., 2018). The functionality of the genes was assessed in terms of morphological parameters, indicating that the genes were involved in primary metabolic and hormone biosynthetic pathways as well as in dedicated secondary metabolic pathways. A decrease in withanolide content after silencing the FPPS and DWF5 genes in W. somnifera suggested that these genes were involved in withanolide biogenesis (Gupta et al., 2015). Also, the little reduced levels of withanolides in the leaves of DXS and DXR silenced plants suggested that these genes were involved in the initial key steps and provided precursor moieties for the synthesis of various terpenes. A small reduction in withanolide levels in HMGR-silenced plants showed the emphasis on the hypothesis and proved the involvement of this gene in flux maintenance to end products of the MVA pathway. Earlier studies on the role of DXS, DXR, and HMGR complemented the role of these steps in providing isoprenoid precursors (Akhtar et al., 2013; Bansal et al., 2018). The results were functionally ascertained in heterologous plant systems as well ( Jadaun et al., 2017a,b; Bansal et al., 2018) for HMGR, DXS, and DXR genes from Pelargonium spp. The report was the first investigation of isoprenoid biosynthetic genes from Pelargonium spp. Results suggested that the DXS gene from plants appeared to be the key to the biosynthesis of secondary metabolites. Overexpression of the DXS gene from the geranium in W. somnifera resulted in increased withanolide content ( Jadaun et al., 2017a,b). Earlier reports on such heterologous expression from Ocimum have been reported (Bansal et al., 2018). Farnesyl diphosphate synthase (FPPS), a major enzyme in the terpene

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TABLE 1 Biological activities of W. somnifera. Activity Antiinflammatory properties

Anticancer properties

Immunomodulatory properties

Neuroprotective properties

Plant part/ phytochemical

Effect

References

Root extract

Modulation of cytokines, antioxidants, peripheral blood mononuclear cells, and apoptosis in leukemic THP-1 cells

Naidoo et al. (2018)

Root extract

Reduces inflammation caused by trinitro benzyl sulfonic acid (TNBS)

Pawar et al. (2011)

Root powder

Potent antiinflammatory activity against collagen-induced arthritic rats

Root powder

Regulates β-glucuronidase and lactate dehydrogenase level in monosodium urate crystal-induced rats

Leaf extract

Formation of nitrooxidative stress enzymes and suppression of inflammatory cytokines

Leaf extract

Inhibits TNFα in zebrafish

Withaferin A

Decrease in mammary tumor invasiveness

Whole plant extract

Effective agent for hepatocellular carcinoma inhibition by induction of autophagosomes-lysosomes fusion

Root

A protein fraction, WSPF, isolated from roots exhibits cytotoxic properties against cancerous cell lines due to its apoptotic activity

Withaferin A

Decreased proteasomal activity, increased Bax, increased IκB-α, p27, caspase-3 activity, and decreased CD31 activity in prostrate tumor cells

Withanolide D

Antileukemic action by the activation of c-Jun N-terminal kinase and p38 protein kinase

Withaferin A

Reduction of breast cancer by decreased PCNA and apoptosis in the MDA-MB-231 breast cell line

Withanolide D

Apoptosis in cancer cell lines by Bax/Bak dependent pathway in p53wild type cells

Leaf extract

TEG (triethylene glycol) in extract causes suppression of cancer cells by activation of p53 and pRB proteins

Leaf extract

Activity against breast, lung, and ovary cancer cell lines

Root extract

Inhibits cancer metastasis by inhibiting EMT and TGF-β proteins in human breast cancer cell line

Withaferin A

Induced apoptosis (Par-4-dependent) in prostate cancer cells

Whole plant extract

Enhanced antileishmanial activity was reported when W. somnifera was applied in combination with cisplatin in a mice model

Root

Promising impact on HIV disease due to its Th1 immunomodulatory effect

Root extract

Active against cyclophosphamide-induced toxicity in rats

Root extract

Enhanced neutrophil counts and humoral antibody response observed in mice after administration of extracts

Root powder

Enhances immune response against diseases in fish caused by A. hydrophila infection in O. niloticus

Root powder

Prevents the impairment of memory induced by PTSD (posttraumatic stress disorder)

Root extract

Root extracts significantly ameliorates the level of bisphenol-A intoxicated oxidative stress, thereby potentially treating cognitive dysfunction

Mondal et al. (2010)

Mondal et al. (2012)

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TABLE 1 Biological activities of W. somnifera—cont’d Activity

Cardioprotective activities

Antidiabetic properties

Antimicrobial properties

Antistress properties

Plant part/ phytochemical

Effect

References

Root extract

Extract was active against cerebral stroke in rats

Ahmad et al. (2016a)

Whole plat extract

Effective in the treatment of depression and anxiety symptoms in schizophrenia

Gannon et al. (2019)

Root extract

Increased serotonin levels in brain

Bhatnagar et al. (2009)

Root extract

Active against MB-PQ-induced nigrostriatal dopaminergic neurodegeneration in mice

Prakash et al. (2013)

Leaf extract

Activity observed against glutamate-induced toxicity in rat glioma and human neuroblastoma cells

Root extract

Extract protects PC12 cells against both hydrogen peroxide and Aβ(1–42)-induced cytotoxicity

Root extract

Neuroprotective role in induced stroke rat models

Ahmad et al. (2016b)

Whole plant

Cardioprotectant by activating Nrf2 nuclear factor

Reuland et al. (2013)

Whole plant

Low-dose Withaferin A is cardioprotective via upregulation of the antiapoptotic mitochondrial pathway in an AMP-activated protein kinase-dependent manner

Leaf extract

Increased antioxidant enzymes

Root and leaf extracts

Active against doxorubicin-induced toxicity in Wistar rats

Whole plant extract

Exhibited antioxidant and antiapoptotic activity in rats

Root and leaf extracts

Glucose uptake in myotubes and adipocytes was increased in model animals

Root extract

Enhanced insulin sensitivity index in rat models

Root and leaf extracts

Showed hypoglycemic and hypolipidemic effects in diabetes-induced experimental rats

Leaf extract

Antibacterial (B. subtilis, E. coli, P. fluorescens, S. aureus, and X. axonopodis) and antifungal (A. flavus, D. turcica, and F. verticillioides) activity

Leaf extract

Activity against S. aureus and Enterococcus spp.

Root extract

Active against S. aureus

Aerial part extract

Antifungal activity against C. albicans, C. neoformans, M. gypseum, T. mentagrophytes

Mwitari et al. (2013)

Root extract

Restored the ambulatory behavior of experimental rats

Singh et al. (2016)

Root powder

Improves fertility under stress conditions in males

Mahdi et al. (2011)

Root extract

Increases memory and prevents neurodegeneration in model rats

Gorelick et al. (2015)

Udayakumar et al. (2009)

Bisht and Rawat (2014)

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biosynthetic pathway, was characterized from W. somnifera (Gupta et al., 2011). FPPS is involved in the catalysis of two successive steps. In the first step, the IPP (isopentenyl diphosphate) and DMAPP (dimethylallyl diphosphate) form 10 C intermediate GPP and the second step involves the condensation of GPP (geranyl diphosphate) with another IPP to form a 15 C compound FPP. The expression analysis suggests that the flower and young leaf tissues have maximum FPPS gene expression as compared to other tissues and its expression was significantly increased in response to SA, MeJA, and mechanical injury, as deduced for other key pathway genes (Gupta et al., 2012). Squalene synthase (SQS) is a major enzyme in the production of phytosterols, brassinosteroids, and triterpenes in plants (Lee et al., 2004). SQS catalyzes the first enzymatic step imparting carbon away from the isoprenoid pathway and directs it toward sterols and triterpene synthesis (Devarenne et al., 2002). This enzyme dimerizes two molecules of farnesyl diphosphate (FPP) and forms one molecule of squalene. Bhat et al. (2012) performed cloning, expression, and promoter analysis of the SQS gene from W. somnifera. Another work on this enzyme from W. somnifera showed that the SQS enzyme was expressed more in young leaves than in mature leaves, stems, and roots (Gupta et al., 2012). An enzyme assay was also performed to study the regulatory and catalytic functions of this enzyme. This confirms that the recombinant SQS enzymes of W. somnifera were active and catalyzed the two-step cyclization reaction of FPP to squalene via presqualene diphosphate (PSPP) in the presence of NADPH and Mg2+. Overexpression of this enzyme in the W. somnifera plant via Agrobacterium-mediated transformation resulted in a 2.5-fold increase in the formation of withanolide A and withaferin A as compared to the nontransformed plant (Grover et al., 2013). Earlier studies on cultured tissues of the plant also showed that withanolides correlated with pathway gene expression (Sabir et al., 2013). Molecular characterization and promoter analysis of the squalene epoxidase (SQE) gene from W. somnifera was performed (Razdan et al., 2013). Squalene epoxidase catalyzes the stereospecific epoxidation of squalene to 2,3-oxidosqualene by utilizing NADPH-cytochrome P-450 reductase; it is also considered a rate-limiting step in the sterol and triterpene biosynthesis. Real-time PCR results revealed that gene transcripts were relatively abundant in leaf tissues, followed by the stalk; it was the least in root tissues. Cis-regulatory elements found during promoter analysis provide a way to deduce the function of SQE in the withanolide biosynthetic pathway. The characterization of NADPH-P450 reductases facilitates the elucidation of the biosynthesis of different withanolides in W. somnifera (Srivastava et al., 2015). 5.2.2.2 Enzymes involved in the modification of the terpene backbone in withanolide biosynthesis In higher plants, glycosylation catalyzed by UDP-glycosyltransferases (UGTs) is considered an important terminal modification in the secondary metabolic pathway, and it forms a variety of natural glycosides (Tiwari et al., 2014). The glycosylation process is integral to the formation of diversified skeletal and structural forms of sterols such as withanolides in W. somnifera. Sterol glucosyltransferases (SGTs) from this plant were initially characterized by Sharma et al. (2007) and named SGTL1. This sterol glucosyltransferase transfers glucose to the C-3 position of sterols and was ubiquitously expressed in the whole plant; it was also actively involved during biotic and abiotic stress signaling in the plant (Sharma et al., 2007). Another sterol glucosyltransferase specific to the 3β-hydroxy position has been isolated from the leaves of W. somnifera. This 27β-hydroxy glucosyltransferase was found to add glucose at the C-27 position in the lactone ring of withanolide and to higher positions in other sterols. The enzyme utilized UDP-glucose as a sugar donor but not UDPgalactose. The activity of this enzyme in the leaves was shown to increase after SA application and decrease on heat shock treatment, which suggested the involvement of this enzyme in biotic and abiotic stresses (Madina et al., 2007a,b). Molecular cloning and the characterization of three members of the oxidosqualene synthase (OSC) superfamily gene— β-amyrin synthase, lupeol synthase, and cycloartenol synthase (CAS)—were carried out (Dhar et al., 2014). All three enzymes were maximally expressed in leaf tissues. Elicitors (methyl jasmonate, gibberellic acid, and yeast extract) regulated three OSCs leading to the alterations of accumulation of major withanolides that is, withanolide A, withanone and withaferin A. MeJA elicitation significantly elevated the withaferin A level. However, the withanolide concentration in response to the yeast extract was significantly increased as compared to the MeJA treatment. The repression of β-amyrin synthase and lupeol synthase diverted the pathway toward CAS and increased withanolide production. This approach might be considered a useful predictive tool for future metabolic engineering efforts for enhanced withanolide production. Recently, Pandey et al. (2014) expressed and functionally characterized a sterol glycosyltransferase gene from W. somnifera in transgenic tobacco plants, and named it WsSGTL1. The overexpression of this enzyme in transformed plants showed increased accumulation of main sterols such as in the glycosylated form. Cytochrome P450 is a major gene family involved in hydroxylation reactions in plants in a position-specific manner ( Jun et al., 2015). Molecular cloning, characterization, and expression of two A-type P450s, CYP98A and CYP76A, from W. somnifera were performed (Rana et al., 2014). The A-type P450s are reported to be essential for the biosynthesis of a variety of natural products. This study also recorded the gene expression of these genes in different parts of the plant. CYP98A was highly expressed in stalks while

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CYP76A transcript levels were more detected in roots. MeJA elicitation significantly increased the withaferin A accumulation while in GA3-treated samples, a decrease in withaferin A and withanolide A accumulation was noticed. It was also shown that the transcript levels of both P450s were related to the higher production of withanolides (Rana et al., 2014). In plants, cytochrome P450s play an important role as they are involved in various oxygenation/hydroxylation reactions responsible for the metabolic diversity of plants. Srivastava et al. (2015) cloned four CYP genes—WSCYP93Id, WSCYP93Sm, WSCYP734B, and WSCYP734R—from W. somnifera. Their results suggested that the genes were regulated by light and auxin in developing seedlings. Also, WSCYP93Id and WSCYP93S were involved in the oxygenation reactions. The recombinant protein expressed in Escherichia coli. was found to be involved in the conversion of withaferin A to a hydroxylated product. Thus, the genes were involved in the modifications of end products of the isoprenoid pathway. Such reactions were also perceived from the cultures of W. somnifera catalyzing the oxygenation of artemisinin (Sabir et al., 2010). The silencing of the cycloartenol synthase (CAS) gene through RNAi was reported by Mishra et al. (2013). Cycloartenol synthase is a part of the 2,3 oxidosqualene cyclases (OCSs) gene family. This enzyme is regarded as an important enzyme of the downstream step of the withanolide biosynthetic pathway, as it is involved in the catalysis of 2,3oxidosqualene into cycloartenol. The CAS-silenced lines showed a decrease in the transcript levels of CAS, which suggested a decrease in the level of the CAS enzyme after silencing. A decrease in withanolide content was recorded in CAS-silenced lines, which clearly indicated the role of the enzyme in withanolide biogenesis. Sterol glucosyltransferases were involved in sterol modification in W. somnifera by the production of glycoconjugates after the transfer of a glycon moiety to the sterol structures. Singh et al. (2016) reported silencing different SGTs from W. somnifera. Increased sitosterol, withanolide A, and withaferin A content was recorded in SGT-silenced lines. Also, the increased expression of withanolide pathway genes was recorded in these lines. The study showed that silencing SGTs has a positive effect on withanolide biosynthesis. Also, enhanced pathogen susceptibility was recorded, which might be due to the induction of withanolide biogenesis. Singh et al. (2017a,b) suggested that these SGTs enzymes were associated with the adaptation during heat stress. Side chain modification is an important phenomenon associated with the biosynthesis of a metabolite. Knoch et al. (2018) reported the characterization of the DWF1 (DIMUNUTO/DWARF 1) gene for the deduction of side chain modification in the withanolide biosynthetic pathway. The gene is responsible for the biosynthesis of sterol Δ24-isomerase (24ISO). Δ24-isomerase is involved in the formation of 24-methylenecholesterol to 24methyldesmosterol. The basis for their selection of the gene was that both the Δ24-isomerase and withanolides existed exclusively in the medicinal plants of the Solanaceae family, not in crop plants. The WRKY transcription factor was isolated and cloned by Singh et al. (2017a,b) to study the involvement of WRKY TF in triterpene biosynthesis and defense functions in W. somnifera. The study revealed that WRKY TF was induced by methyl jasmonate and salicylic acid. Silencing WRKY TF resulted in changes in the morphology of the plant with reduced synthesis of sterols as well as withanolides in the W. somnifera plant. WRKY silenced lines also showed a decrease in the transcript levels of the phytosterol pathway genes. Further, the overexpression of the gene resulted in an increased level of phytosterols and withanolides in W. somnifera. Similar results were obtained when WRKY from W. somnifera was overexpressed in N. tabacum and S. lycopersicum (Singh et al., 2017a,b).

5.2.3 Application of computational and in silico studies Bioinformatics/computational biology approaches have played an important role in elucidating the pharmacological activity of some important withanolides, along with finding the structural and functional activities of the enzymes involved in the biosynthesis of key metabolites (Sangwan et al., 2014). These studies played a very useful role for researchers in elucidating the usefulness of this important medicinal plant. Some recent works related to the bioinformatics analysis in W. somnifera are reported here (Table 2).

5.2.4 Computational analysis in W. somnifera Bioinformatics/computational biology approaches have also played an important role in elucidating the pharmacological activity of some important withanolides, along with finding the structural and functional activities of enzymes involved in the biosynthesis of key metabolites (Sangwan et al., 2014, 2017). These studies played a very useful role for researchers in elucidating the usefulness of this important medicinal plant. Protein kinase G (PknG) is a major virulence factor that blocks the intracellular degradation of M. tuberculosis in lysosomes (Santhi and Aishwarya, 2011). Blocking PknG activity by certain inhibitors will promote the rapid translocation of mycobacteria into the host cell lysosomes and its degradation. Bioinformatics and docking results suggest that withanolide E, F, and D from W. somnifera have the ability to bind with the active site residues of PknG and block its activity (Santhi and Aishwarya, 2011). Withanolide A, a secondary metabolite from the ayurvedic plant W. somnifera, has neuroprotective

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TABLE 2 Targeted genes for metabolic engineering of W. somnifera. Gene focused

Approach

Main features

References

WsHMGR

Gene complementation

The functional WsHMGR protein played a catalytic role in isoprenoid biosynthesis.

Akhtar et al. (2013)

WsSGTL1

RNAi-mediated gene silencing

Decrease in withanolides (withaferin A and withanolide A) contents in silenced lines.

Singh et al. (2016)

WsSGTL1

Heterologous overexpression in E. coli

Sterol glucosyltransferase transfers glucose to C-3 position of sterols and was ubiquitously expressed in whole plant and also actively involved during biotic and abiotic stress signaling in the plant.

Sharma et al. (2007)

WsSGTL1

Heterologous overexpression in E. coli

The enzyme utilized UDP-glucose as sugar donor but not UDP-galactose. The activity of this enzyme in the leaves was recorded to increase after SA application and decrease on heat shock treatment, which suggested the involvement of this enzyme in biotic and abiotic stresses.

Madina et al. (2007b)

WsSGTL1

Recombinant protein overexpression

The encoded functional protein was involved in the glycosylation of stigmasterol.

Chaturvedi et al. (2012)

Ws-Sgtl4

Overexpression by hairy root culture

Overexpression of gene resulted in enhanced withanolide content (withanolide A) in hairy root culture in response to elicitors.

Pandey et al. (2016)

WsSGTL1

Overexpression in A. thaliana

Transgenic plants showed increased abiotic stress tolerance due to glycosylation of sterol glycosides. Also, the transgenics plants have improved tolerance toward the fungus A. brassicicola.

Mishra et al. (2017)

WsDXS

Heterologous overexpression from geranium

Overexpression resulted in enhanced withanolide production in W. somnifera.

Jadaun et al. (2017a,b)

WsDXR WsDXS

Gene expression by elicitation and stress

Differential expression of the genes after elicitation (salycylic acid and methyl jasmonate) and mechanical injury.

Gupta et al. (2013)

WsCYP98A WsCYP76A

Recombinant protein expression

A-type P450s are reported to be involved and essential for the biosynthesis of a variety of natural products. MeJA elicitation significantly increased the withaferin A accumulation while in GA3-treated samples, a decrease in withaferin A and withanolide A accumulation.

Rana et al. (2014)

WSCYP93Id, WSCYP93Sm, WSCYP734B, and WSCYP734R

Recombinant protein overexpression

WSCYP93Id and WSCYP93Sm genes were involved in the formation of hydroxylated product from withaferin A.

Srivastava et al. (2015)

WsCPR1 WsCPR2

Recombinant protein expression

Increase in the withanolide content (withanolide A and withaferin) was recorded in elicitor-treated samples of W. somnifera.

Rana et al. (2013)

WsSQS

Recombinant protein expression in E. coli

The recombinant SQS enzymes of W. somnifera were active and catalyzed two-step cyclization reaction of FPP to squalene via presqualene diphosphate (PSPP) in the presence of NADPH and Mg2+.

Gupta et al. (2012)

WsSQS

Recombinant protein expression and promoter analysis

Recombinant protein (C-terminus truncated) was successfully expressed. Promoter analysis revealed that the gene is actively present in the secondary metabolism of W. somnifera.

Bhat et al. (2012)

WsSQE

Recombinant protein expression and promoter analysis

Cis-regulatory elements found during promoter analysis provide a way to deduce the function of SQE in withanolide biosynthetic pathway.

Razdan et al. (2013)

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TABLE 2 Targeted genes for metabolic engineering of W. somnifera—cont’d Gene focused

Approach

Main features

References

WsOSCs/LS, BS, CS

Overexpressed in Yeast

Differential expression of genes under salicylic acid and yeast and methyl jasmonate treatments.

Dhar et al. (2014)

WsDWF1

Recombinant protein expression

Overexpressed under methyl jasmonate, 2,4-D, and gibberellic acid treatments.

Razdan et al. (2017)

WsDWF5

Virus-induced gene silencing

Reduced content of withaferin A in silenced plants suggested the role of WsDWF5 gene in W. somnifera.

Gupta et al. (2015)

WsFPPS

Gene cloning and expression analysis

The expression analysis suggests that flower and young leaf tissues have maximum FPPS gene expression as compared to other tissues and its expression was significantly increased in response to SA, MeJA, and mechanical injury, as deduced for other key pathway genes.

Gupta et al. (2011)

WsCAS

Silencing and homologous overexpression

Modulation in withanolide levels in silenced as well as over-expressed lines.

Mishra et al. (2013)

WsTR1

Protein overexpression

Functional protein was involved in the formation of tropine from tropinone, as revealed by enzyme assay.

Kushwaha et al. (2013)

WsLWD1

Transient overexpression in W. somnifera.

Overexpressing tissues have increased level of withaferin A.

Tripathi et al. (2017)

WsWUSCHEL

Transient overexpression in W. somnifera

Overexpressing tissues have increased level of withaferin A, thus the gene played an active role in regulation of secondary metabolites.

Tripathi et al. (2017)

WsDXS, WsDXR, WsHMGR, and WsFPPS

Virus-induced gene silencing

Decrease in withanolide content after silencing of FPPS and DWF5 gene in W. somnifera suggested that these genes were involved in withanolide biogenesis. Levels of withanolides in leaves of DXS and DXR silenced plants suggested that these genes were involved in the initial key steps and provided precursor moieties for the synthesis of various terpenes.

WsWRKY

Overexpression and virusinduced gene silencing

WRKY silenced lines showed a decrease in transcript level of phytosterol pathway genes and with reduced synthesis of withanolides. Overexpression of gene resulted in increased phytosterols and withanolides (triterpenoid) contents.

Singh et al. (2017a,b)

WsDWF1

Heterologous expression, VIGS, phylogenetic, metabolomic and gene expression analysis

24ISO enzyme was found to be involved in the conversion of 24-methylenecholesterol to 24methyldesmosterol. Based on this finding, they suggested that this catalytic step is a key step in withanolide biosynthesis.

Knoch et al. (2018)

WsELI

Transient overexpression

Increased withanolide content in transformed tissues suggested the role of gene in withanolide biosynthetic pathway in relation to the development.

Tripathi et al. (2019)

abilities and can inhibit the activity of the acetylcholinestearase enzyme, thereby increasing the level of acetylcholine in synapses, which can be a preventive measure in the treatment of Alzheimer’s disease. Docking and molecular dynamics studies shows that withanolide A is able to bind with the amino acid residues present in the active sites of the human acetylcholinestearase enzyme and inhibit the activity of that enzyme (Grover et al., 2012). 4 Beta-hydroxy withanolide-E and 7,8-dehydrocalotropin were used to develop the secondary QSAR model, that is, the ANN map model. These studies suggested that withanolides are androstenedione skeleton-containing compounds that have cytotoxic activity against the human breast cancer cell line MCF-7 and thus may lead to potential anticancer molecules by lead optimization

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(Prakash et al., 2013). The prediction of the protein structure of an enzyme is an important step to reveal its characteristics and activity. Further, these structures will be useful in understanding the molecular interactions of pathway proteins with their substrates (Srivastava et al., 2015). Some reports were available on the prediction of the secondary structure of some important pathway enzymes from W. somnifera. Structures of HMGR, DXS, DXR, FPPS, SQS, SQE, and CS enzymes were predicted by the homology modeling strategy (Sanchita et al., 2014). The motifs identified in these proteins were found to be involved in the formation of binding sites for the substrate to perform the chemical reaction. The structures of some CYP450 enzymes were predicted to assign the role of the genes in the withanolide biogenesis pathway (Srivastava et al., 2015). The predicted structures of DWF5 isoforms revealed the existence of a significant difference in the structures of the isoforms.

5.2.5 Transcriptome-wide analysis to identify genes involved in withanolide biosynthesis Transcriptome analysis/RNA sequencing provide better opportunities for the identification and characterization of differential gene expression of tissues subjected to stress or involved in the biosynthesis of a particular metabolite (Sangwan et al., 2013). The recognition of specific genes involved in a metabolic pathway or stress management enhances the possibility to develop a crop with improved qualities. Thus, they provide a platform for future research, specifically for those plants in which no genome was available (Sangwan et al., 2014, 2017). In W. somnifera, no genomic data is available, so transcriptome-based studies are the only sources to identify the genes involved in the tissue-specific regulatory processes. Table 3 summarizes the transcriptomic analysis studies in W. somnifera. After the advancement of the next-generation sequencing (NGS) approach, the transcriptomic analysis of leaf and root tissues was performed to increase our understanding related to withanolide (the major and important secondary metabolite in the Withania genus) biosynthesis (Sangwan et al., 2017). Many transcription factors were also identified that may regulate some important steps of withanolide biosynthesis. This information provides a path for differential metabolic engineering related strategies that would enhance specific withanolide production (Tripathi et al., 2016, 2017). Pyrosequencing of the leaf and root tissues of W. somnifera NMITLI-101 identified differentially expressed methyltransferases, cytochrome P450s, and glycosyltransferases from the transcriptomic data related to withanolide biosynthesis (Gupta et al., 2013). Transcriptome analysis identified the participating genes of the secondary metabolite synthetic pathway in W. somnifera. A comparative transcriptome of the leaf and root tissue was reported to study the difference in the withanolide content and properties between different chemotypes of W. somnifera (Gupta et al., 2015). Silencing of the enzyme WsDWF5a that catalyzes the biosynthesis of 24-methylene cholesterol results in a low yield of withaferin A. The study confirmed that 24-methylene cholesterol is a major precursor molecule for the synthesis of withanolide (Gupta et al., 2015). The study provided a large genomic resource to identify chemotype and tissue-specific withanolide syntheses. The comparative transcriptome analysis of in vitro cultured W. somnifera was carried out by researchers. The enzyme of the first major step in the isoprenoid pathway, that is, HMGR, was found to be expressed after initial month of in vitro root culture (Gupta et al., 2015). Transcription factors (TFs) are the master regulators of gene expression. Thus, they play an important role in the regulation of the synthesis of a metabolite. An in-depth analysis of the leaf and root transcriptome of W. somnifera was performed earlier by our group (Tripathi et al., 2017, 2019). The reports revealed the presence of 3532 annotated transcripts belonging to the transcription factors from 90 families in the leaf and root tissues of the plant. The WRKY and WD TFs were found in abundance, followed by MYB, BHLH, and AP2-ERF TF. For the validation of the transcriptome, they isolated, cloned, and overexpressed LWD1 and WUSCHEL TFs in W. somnifera by the transient transformation method (Tripathi et al., 2017). Also, it was concluded that LWD1 and WUSCHEL TFs were involved in the synthesis of withanolides, as suggested by the increased level of withaferin A after overexpression (Tripathi et al., 2017). The information provided in the berry transcriptome data (project Id PRJNA408054) from W. somnifera led to the identification and isolation of a novel transcription factor, the early light inducible transcription factor (WsELI) (Tripathi et al., 2019). Transcriptome analysis also revealed transcripts associated with 143 metabolic pathways with a higher number of transcripts linked to flavanoid, phenylpropanoid, and steroid pathways. Also, transcripts of methyltransferases, glycosyltransferases, and cytochrome p450 were found in a tissue-specific manner. Transcription factor genes such as WRKY, MADS, ELI, and MYB were also observed and their role in the global regulation of the secondary metabolic pathway was elucidated (Tripathi et al., 2019). The leaf transcriptome of W. somnifera after the exogenous application of SA was also done to reveal the signaling mechanism involved in the formation of secondary metabolites. Elicitation was applied to increase the level of secondary metabolites in plant cell cultures (Dasgupta et al., 2014). Exogenous application of SA was found to enhance disease resistance and pathogenesis-related gene expression in various plant species. For the large-scale in vitro production of withanolides and other secondary metabolites, salicylic acid and methyl jasmonate are

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TABLE 3 Transcriptome-based studies for improvement of W. somnifera. Variety of W. somnifera used

Sequencing technology

Tissues

Major findings

References

Jawahar (Indian cultivar)

EST library

In vitro generates leaf and root

Genes related to photosynthesis, pathogenesis, and withanolide biosynthesis were identified.

Senthil et al. (2010)

Jawahar Asgandh 20

Illumina Hiseq2000

In vitro grown adventitious root and leaf

In vitro root and leaf extracts of W. somnifera have antioxidant and antiproliferative activity against cancerous cell lines, respectively.

Senthil et al. (2015)

NMITLI-101

454 GS FLX Titanium

Leaf and root tissues from 1 year field grown plant

Identification of genes involved in biosynthetic pathway of withanolides along with modifying enzymes such as UGTs, CYPs, and methyltransferases provide basis of future research.

Gupta et al. (2013)

NA

Illumina Genome Analyzer IIx sequencer

Salicylic acid elicited leaf tissues

Expression pattern of pathogenesis-related (PR) genes along with accumulation of different withanolides after salicylic acid treatment was studied.

Dasgupta et al. (2014)

NMITLI-101 NMITLI-118 NMITLI-135

454-GS FLX sequencing

Leaf and root tissues from field grown plants of 1 year

Different chemotypes of Withania have differential accumulation patterns of withanolides.

Gupta et al. (2015)

NMITLI-101

454-GS FLX sequencing

Leaf and root tissues

Study of differential expression of transcription factors in Withania somnifera revealed that WDR and WUSCHEL were maximally expressed TF.

Tripathi et al. (2017)

NMITLI-118

Illumina Genome Analyzer II

Fruit (berry) from field grown plant

Comparative study of three different tissue (leaf, berry, and roots) of W. somnifera with other Solanaceae members (Nicotiana, Solanum, and Capsicum) provided metabolome regulation of major biosynthetic pathways.

Tripathi et al. (2019)

widely used elicitors in the culture media (Dasgupta et al., 2014). From the transcriptomic data, it was clear that the production of withanoside V, withaferin A, and withanolide A in the leaf tissues of W. somnifera was reported to be induced after the application of exogenous salicylic acid (Dasgupta et al., 2014).

5.2.6 EST and transcriptome analysis to identify genes involved in withanolide biosynthesis Expressed sequence tag (EST) analysis provides the gene index of an organism and helps in the isolation of genes responsible for the formation of enzymes in the secondary metabolite biosynthesis. This is a simple, less-expensive, and rapid technique in comparison to conventional sequencing approaches (Ohlrogge and Benning, 2000; Pop and Salzberg, 2008). The first step in the identification of genes by using the EST-based approach is the construction of a cDNA library of W. somnifera leaf and root tissues and its sequencing to find out tissue-specific sequences (Gupta et al., 2013). By using this approach, several candidate genes that code for different enzymes of the MVA pathway such as HMG CoA synthase, SQE, and OSCs and enzymes of the MEP pathway such as CDP-MEK were identified. This EST approach enhances our knowledge of the secondary metabolite synthesis in W. somnifera and its regulation to some extent. But many CYP450s and glucosyltransferases that were involved in the final steps of different withanolide biosynthesis are yet to be identified and characterized (Senthil et al., 2010) The advancement of the NGS approach, the transcriptomic analysis of the leaf and root tissues was performed to increase our understanding related to withanolide (major and important secondary metabolite in Withania genus) biosynthesis. Differentially expressed methyltransferases, cytochrome P450s, and glycosyltransferase were identified from the

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transcriptomic data related to withanolide biosynthesis. Many transcription factors were also identified that may regulate some important steps of withanolide biosynthesis. This information provides a path for differential metabolic engineeringrelated strategies that would enhance specific withanolide production (Gupta et al., 2013, 2015). In addition to the abovementioned leaf versus root, transcriptome analysis was carried out to identify the participating genes of the secondary metabolite synthetic pathway in W. somnifera. The leaf transcriptome of W. somnifera after exogenous application of SA was also done to reveal the signaling mechanism involved in the formation of secondary metabolites. Elicitation was applied to increase the level of secondary metabolites in plant cell cultures. The exogenous application of SA was found to enhance disease resistance and pathogenesis-related gene expression in various plant species. For large-scale in vitro production of withanolides and other secondary metabolites, salicylic acid and methyl jasmonate are widely used elicitors in the culture media. From the transcriptomic data it was clear that the production of withanoside V, withaferin A, and withanolide A in leaf tissues of W. somnifera was reported to be induced after the application of exogenous salicylic acid (Dasgupta et al., 2014). Comparative transcriptome of leaf and root tissues to study the difference in withanolide content and its nature between different chemotypes of W. somnifera was performed by Gupta et al. (2015). In the study, it was also observed that silencing the enzyme WsDWF5a that catalyzes the biosynthesis of 24-methylene cholesterol results in a low yield of withaferin A. The study confirmed that 24-methylene cholesterol is a major precursor molecule for the synthesis of withanolide. The study provided a large genomic resource to identify chemotype and tissue-specific withanolide synthesis. The comparative transcriptome analysis of in vitro cultured W. somnifera was carried out by Senthil et al. (2015). In this study, the enzyme of the first major step in the isoprenoid pathway, that is, HMGR, was found to be expressed after 1 month of in vitro root culture. The expression was highest in the fourth day of culture while the expressions of FPPS and CAS were found to be elevated in leaves throughout the in vitro shoots in comparison to the roots. The expression levels of squalene epoxidase and glucosyltransferase were found to be increased in in vitro roots rather than in leaf tissues. In this study, a public data resource, withanomics was also developed that gives a searchable interface for the transcriptome data related to W. somnifera. It includes transcriptome sequences (root and leaf) and leaf (in vitro) and root (in vitro) sequences as well as EST sequences.

5.3 Application of in vitro methods Withanolides are synthesized from multiple shoot cultures at varying concentrations that depend on the different growth hormones applied exogenously in culture media (Sabir et al., 2007). In the shoot culture, withanolide G, withanolide I, traces of withanolide D, and withanolide E were identified (Roja et al., 1991). In another study, the increased accumulation of withaferin A and withanolide D was detected from regenerated shoots supplemented with 4% sucrose while the accumulation of withaferin A was observed in a liquid regeneration medium supplemented with 10% coconut milk (Ray and Jha, 2001). In addition to shoot culture, different withanolides were also produced via root culture, among which withanolide D was isolated and identified. Agrobacterium tumefaciens-mediated transformation of W. somnifera and the transformed organ culture method by using the wild-type nopaline and octopine strains of Agrobacterium were also established (Ray and Jha, 1999). Shooty teratomas with altered phenotypes were spontaneously obtained from nopaline strain-infected galls and were able to synthesize both the major withanolides (withaferin A and withanolide D) in basal media. On the other hand, the accumulation of withanolide D was detected from rooty teratomas developed after infection with octopine and nopaline strains of A. tumefaciens. In vitro synthesis of withanolides was also reported from multiple shoots, and root cultures by direct rhizogenesis of leaves, callus tissue, and single cell suspension cultures of W. somnifera (Sabir et al., 2008). Increases in the withanolide A content in multiple shoot cultures in comparison to field-grown plants was also reported in this study. The study also reported the low withanolide content in the callus and suspension cultures of W. somnifera. Normally, withanolide A accumulated mainly in the roots in low proportions compared to other withanolides. Sangwan et al. (2007) demonstrated the biogenesis of withanolide A in the shoot cultures of W. somnifera that can occur at levels matching those in native roots. They established the in vitro shoot cultures of W. somnifera and used nodes as the explant. The plant hormone BAP and kinetin were used in different concentrations, producing morphogenetic responses. The results revealed that the enhanced de novo biosynthesis of withanolide A occurred in in vitro grown shoots as compared to control (field grown) shoots. These results were further confirmed by radiolabeling. Sabir et al. (2011) reported the ability of biotransformation of withanolides by cell suspension cultures of W. somnifera. In this study, withaferin A, withanolide A, and withanone were used as precursor substrates and synchronous cell suspension lines of W. somnifera were incubated with them. Mass spectrometry, IR, and NMR were used for the determination of structures of withanolide molecules that were present. They observed the interconversion of withanolide A to withanone by TLC. Also, some trace amounts of unknown compounds were detected in the culture. The study proposed that the

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transformation appeared due to be substitution of the 20-OH group to 17-OH in withanolide A; cytochrome P450 enzymes may be responsible for this biotransformation. Transformed root lines, callus lines, and root callus lines of W. somnifera also accumulate withasteroids. Higher withaferin A content accumulated in the transformed root lines while both withaferin A and withanolide D accumulated in all the root callus lines. Callus lines grew faster than the transformed root lines and produced both withanolides (Bandyopadhyay et al., 2007). Murthy et al. (2008) established a transformed hairy root culture of W. somnifera in an MS-based liquid medium for the production of secondary compounds. It was found that the concentration of withanolide A in transformed roots was elevated as compared to nontransformed cultured roots. It was also observed that overexpressing the squalene synthase gene of Arabidopsis thaliana significantly enhanced the withanolide content in the hairy root culture of the Withania species (Mirjalili et al., 2011). The effects of different macro elements was demonstrated and maximum production of withanolide A was recorded in the absence of NH4 with moderate concentration of NO3 (Murthy and Praveen, 2013). The effect of different types of salts on in vitro grown shoots and the callus of W. somnifera was determined by Sabir et al. (2012). Different salts such as KCl, NaCl, KNO3, NaNO3, and CaCl2 were used in varied concentrations for this experiment. The results revealed that there was an increase in the activity of antioxidant enzymes. Interestingly, in the higher concentrations of calcium chloride the activity of antioxidants, and enzymes were highest as compared to the other salts. Thus, the study proposed that calcium was more harmful than other salts in the medium and both the enzymatic and nonezymatic systems of the cell were involved in combating salt stress. During biotic and abiotic stress conditions, secondary metabolites are accumulated in plants. Hence, by application of biotic and abiotic elicitors, the accumulation of metabolites can be stimulated. Sivanandhan et al. (2012) investigated the effect of chitosan (biotic elicitor) and AlCl3 (abiotic elicitor) on withanolide production and found that chitosan is more effective than AlCl3 in increasing the level of all withanolides from the leaf callus-derived adventitious roots. A similar experiment was carried out by Sivanandhan et al. (2013) using SA and MeJA as elicitors in the hairy root culture of W. somnifera, resulting in the increased production of withaferin, withanone, and withanolide A. In addition to the hairy root culture, a higher accumulation of withanolides was observed in the adventitious root culture of W. somnifera after SA treatment. For the optimization of different factors required for the sustainable production of withanolides, different concentrations of carbon sources, organic matter, and seaweed extracts were studied in a cell suspension culture of W. somnifera. By using Gracilaria edulis extract, withanolide production (withanolide A, withanolide B, withaferin A, and withanone) was achieved. The organic additive L-glutamine in combination with picloram and KN also enhanced withanolide synthesis. Sucrose was proved to be a factor responsible for the highest withanolide production. Murthy and Praveen (2013) showed that adventitious root culturing of W. somnifera in a half-strength MS medium supplemented with 2% (w/v) sucrose (pH 5.5) is suitable for the production of withanolide A. It was also reported that optimization of the in vitro culture conditions provided a scope to obtain increased production of withanolide A by the adventitious root culture. The combined effects of elicitors (CdCl2, AlCl3, and chitosan) and precursors (cholesterol, mevalonic acid, and squalene) were assessed on withanolide production. Their higher accumulation was detected in a cell suspension culture utilizing the shake-flask culture system as well as the bioreactor culture system in W. somnifera. In vitro shoot cultures of W. somnifera were used to study the effect of cadmium toxicity by Mishra et al. (2014). Different concentrations of cadmium sulfate were applied to the shoot cultures of W. somnifera to explore the effect of cadmium on the metabolic and adaptive processes of the plant. The results indicated that Cd interfered with NPK uptake in the plant and thus induced necrosis, stunted growth, and chlorosis in in vitro shoots. Isozymic pattern, sugar metabolism, photosynthetic pigments, phenolics, tocopherol, reduced glutathione, flavonoids, nonprotein thiol, ascorbate, and proline were also modulated under the effect of Cd stress. These results suggested that enzymatic and nonenzymatic processes were involved in the management of Cd stress. By using the biotic elicitor Aspergillus homogenate, withaferin A content in the hairy root cultures was enhanced by inoculating the A. rhizogenes culture in the seedling explants of W. somnifera (Varghese et al., 2014). In vitro production of withaferin A in W. ashwagandha, was reported in in vitro and ex vitro plants compared to control (field grown) plants (Mir et al., 2014).

5.4 Marker-based approaches The advancement and exploitation of different types of molecular markers have been very useful in the prediction of DNA polymorphism and are considered among the most significant successes in the area of molecular genetics (Semagn et al., 2006). Marker-based approaches were applied to study the selection and identification of differences in the genotypic diversity of W. somnifera (Dhar et al., 2006). From the group of molecular markers, AFLP (amplified fragment length polymorphism) is a proven marker for the correlation of data generated from DNA fingerprinting with the phytochemical marker (Vos et al., 1995; Negi et al., 2000, 2006; Diaz et al., 2003; Campbell et al., 2003; Dhar et al., 2006). Chaurasiya et al. (2009) studied the variation in the phytochemical content of different accessions of W. somnifera Dhar et al. (2006)

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analyzed the polymorphism in these accessions by AFLP. The results suggested the interrelationship between phtytochemicals and genotypes (Chaurasiya et al., 2009). Synthetic seeds were produced, regenerated, and analyzed by applying RAPD and ISSR markers, suggesting the monomorphism between the regenerated and the mother plant (Fatima et al., 2013). RAPD and AFLP were used to assess the genetic diversity among different accessions of W. somnifera from India, suggesting a correlation in the variation in morphology of different accessions and polymorphisms (Chaurasiya et al., 2009; Mir et al., 2011). ISSR (intersimple sequence repeats) belongs to the third-generation marker system. Along with ISSR, studies with polymorphic primers suggested a high degree of polymorphism among 12 genotypes of W. somnifera (Bamhania et al., 2013). The RAPD technique considers both coding and noncoding regions of the genome and thus proved to be a better approach in comparison to sequence-based analyses (Chaurasiya et al., 2009). The RAPD method was utilized by Arif et al. (2010) to reveal variations in desert plants along with W. somnifera. This analysis provided 1–10 major bands for single plant species. Chemical, morphological, and RAPD analyses in W. somnifera accessions revealed 75% polymorphism among the accessions (Khanna et al., 2014). RAPD and ISSR revealed 47.89% polymorphism among different accessions from India with 90% homogeneity among the members of the same accessions (Khan and Shah, 2016). Among 16 different accessions of W. somnifera, 81% polymorphism was recorded, as revealed by ISSR- and RAPD-based analyses (Tripathi et al., 2012). The RAPD and ISSR analysis of regenerated shoots from the clonal propagation of in vitro grown cultures suggested a homogeneity in the genotypes (Nayak et al., 2013). Variations also exist in organisms based on isozymes (variants of specific enzymes). These isozymes are exploited as a means to detect genetic variations (Michelmore and Hulbert, 1987). In W. somnifera, RAPD and isozymes were used as tools to assess genetic diversity, revealing that a high level of diversity exists in W. somnifera plants from different geographical locations in India (Chaurasiya et al., 2009). Genetic diversity within different accessions of W. somnifera from the Tamil Nadu state were assessed by isozymes and RFLP, which revealed the polymorphism in molecular markers. This suggested the existence of genetic diversity among these accessions (Aslam et al., 2010). Among a variety of molecular markers, simple sequence repeats (SSR)/microsatellites, which are mainly tandem repeats of 1–6 nucleotide long DNA sequences, proved to have a great role in genetics and plant breeding due to hypervariability, codominant nature, reproducibility, relative abundance, good coverage of genome, inheritance, etc.

6

Conclusions and future perspectives

The wide presence of therapeutic agents in W. somnifera makes it a fascinating plant for research. Various approaches were applied by researchers to improve the important traits of this medicinally important plant. Metabolic engineering and synthetic biology approaches are important tools for the increased production of withanolides. Protocols were well developed and applied successfully for both transient as well as stable Agrobacterium-mediated transformation. Overexpression and silencing pathway genes are the approaches applied to deduce the role of these genes in the regulation of the key steps of withanolide biosynthesis. In vitro tissue culture approaches are contributing in the assessment of the role of different elicitors in withanolide production. In silico approaches such as transcriptomics will allow in-depth analysis and prediction of novel candidate genes involved in biosynthetic pathways and their regulation, which will further enhance our understanding related to medicinally important compounds such as withanolides. Sequencing approaches are very successful in the isolation of a full-length gene, thus supportive in understanding the role of a gene. Molecular breeding and marker-assisted approaches are useful in the extensive improvement of a crop. The genetic diversity of W. somnifera was predicted by a number of researchers, based on markers such as AFLP, ISSR, SSR, and RAPD. This will enhance our knowledge and be helpful in the selection and improvement of W. somnifera with a better production of withanolides. Widening the range of techniques for more rapid, accurate, and noninvasive genotyping and phenotyping, along with metabolic engineering approaches, will be very helpful in improvement of the levels of pharmacologically important compounds in W. somnifera. Merging of datasets from genetic resources and mapping information from transcriptomic and multivariate analyses of individual tissues of W. somnifera populations will help the scientific community to produce W. somnifera with novel traits and improved metabolites.

Acknowledgments The authors are thankful to CSIR, DBT, DST, and NMITLI for various financial grants awarded for various studies discussed in the chapter. The authors are also thankful to all the lab colleagues who contributed on this plant.

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Senthil, K., Jayakodi, M., Thirugnanasambantham, P., Lee, S.C., Duraisamy, P., Purushotham, P.M., Rajasekaran, K., Charles, S.N., Roy, I.M., Nagappan, A.K., Kim, G.S., 2015. Transcriptome analysis reveals in vitro cultured Withania somnifera leaf and root tissues as a promising source for targeted withanolide biosynthesis. BMC Genomics 16, 1–16. Sharma, L.K., Madina, B.R., Chaturvedi, P., Sangwan, R.S., Tuli, R., 2007. Molecular cloning and characterization of one member of 3β-hydroxy sterol glucosyltransferase gene family in Withania somnifera. Arch. Biochem. Biophys. 460, 48–55. Singh, N., Bhalla, M., de Jager, P., Gilca, M., 2011. An overview on ashwagandha: a Rasayana (Rejuvenator) of Ayurveda. Afr. J. Tradit. Complement. Altern. Med. 8, 208–213. Singh, S., Pal, S., Shanker, K., Chanotiya, C.S., Gupta, M.M., Dwivedi, U.N., Shasany, A.K., 2014. Sterol partitioning by HMGR and DXR for routing intermediates toward withanolide biosynthesis. Physiol. Plant. 152, 617–633. Singh, G., Tiwari, M., Singh, S.P., Singh, S., Trivedi, P.K., Misra, P., 2016. Silencing of sterol glycosyltransferases modulates the withanolide biosynthesis and leads to compromised basal immunity of Withania somnifera. Sci. Rep. 6, 1–13. Singh, G., Tiwari, M., Singh, S.P., Singh, R., Singh, S., Shirke, P.A., Trivedi, P.K., Misra, P., 2017a. Sterol glycosyltransferases required for adaptation of Withania somnifera at high temperature. Physiol. Plant. 160, 297–311. Singh, A.K., Kumar, S.R., Dwivedi, V., Rai, A., Pal, S., Shasany, A.K., Nagegowda, D.A., 2017b. A WRKY transcription factor from Withania somnifera regulates triterpenoid withanolide accumulation and biotic stress tolerance through modulation of phytosterol and defense pathways. New Phytol. 215, 1115–1131. Sivanandhan, G., Arun, M., Mayavan, S., Rajesh, M., Mariashibu, T.S., Manickavasagam, M., Selvaraj, N., Ganapathi, A., 2012. Chitosan enhances withanolides production in adventitious root cultures of Withania somnifera (L.) Dunal. Ind. Crop Prod. 3, 124–129. Sivanandhan, G., Dev, G.K., Jeyaraj, M., Rajesh, M., Arjunan, A., Muthuselvam, M., Manickavasagam, M., Selvaraj, N., Ganapathi, A., 2013. Increased production of withanolide A, withanone, and withaferin A in hairy root cultures of Withania somnifera (L.) Dunal elicited with methyl jasmonate and salicylic acid. Plant Cell Tiss. Org. Cult. 114, 121–129. Smil, V., 2001. Feeding the World: A Challenge for the Twenty-First Century. MIT Press.

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Srivastava, S., Sangwan, R.S., Tripathi, S., Mishra, B., Narnoliya, L.K., Misra, L.N., Sangwan, N.S., 2015. Light and auxin responsive cytochrome P450s from Withania somnifera Dunal: cloning, expression and molecular modeling of two pairs of homologue genes with differential regulation. Protoplasma 252, 1421–1437. The Plant List, 2013. Version 1.1. Available at:http://www.theplantlist.org/. (Accessed 10 March 2019). Tiwari, P., Sangwan, R.S., Mishra, B.N., Sabir, F., Sangwan, N.S., 2014. Molecular cloning and biochemical characterization of a recombinant sterol 3-Oglucosyltransferase from Gymnema sylvestre R. Br. catalyzing biosynthesis of steryl glucosides. Biomed. Res. Int. 14, 1–14. Tripathi, N., Saini, N., Mehto, V., Kumar, S., Tiwari, S., 2012. Assessment of genetic diversity among Withania somnifera collected from central India using RAPD and ISSR analysis. Med. Aromatic Plant Sci. Biotechnol. 6, 33–39. Tripathi, S., Jadaun, J., Chandra, M., Sangwan, N., 2016. Medicinal plant transcriptomes: the new gateways for accelerated understanding of plant secondary metabolism. Plant Genet. Resources 14 (4), 256–269. https://doi.org/10.1017/S1479262116000162. Tripathi, S., Sangwan, R.S., Narnoliya, L.K., Srivastava, Y., Mishra, B., Sangwan, N.S., 2017. Transcription factor repertoire in Ashwagandha (Withania somnifera) through analytics of transcriptomic resources: insights into regulation of development and withanolide metabolism. Sci. Rep. 7, 1–17. Tripathi, S., Sangwan, R.S., Mishra, B., Jadaun, J.S., Sangwan, N.S., 2019. Berry transcriptome: insights into a novel resource to understand development dependent secondary metabolism in Withania somnifera (Ashwagandha). Physiol. Plant. Udayakumar, R., Kasthurirengan, S., Mariashibu, T.S., Rajesh, M., Anbazhagan, V.R., Kim, S.C., Ganapathi, A., Choi, C.W., 2009. Hypoglycaemic and hypolipidaemic effects of Withania somnifera root and leaf extracts on alloxan-induced diabetic rats. Int. J. Mol. Sci. 10, 2367–2382. Uddin, Q., Samiulla, L., Singh, V.K., Jamil, S.S., 2012. Phytochemical and pharmacological profile of Withania somnifera Dunal: a review. J. Appl. Pharm. Sci. 2, 170–175. Varghese, S., Keshavachandran, R., Baby, B., Nazeem, P.A., 2014. Genetic transformation in ashwagandha (Withania somnifera (L.) Dunal) for hairy root induction and enhancement of secondary metabolites. J. Trop. Agric. 52, 47–53. Vos, P., Iiogers, R., Bleeker, M., Van De Lee, T., Homes, M., Frijters, A., Pot, J., Peleman, J., Kulper, M., Jabcau, M., 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acid Res. 23, 4407–4414.

Chapter 18

Approaches for conservation and improvement of Himalayan plant genetic resources Amit Chawla, Amit Kumar, Ashish Warghat, Sanatsujat Singh, Shashi Bhushan, Ram Kumar Sharma, Amita Bhattacharya and Sanjay Kumar CSIR-Institute of Himalayan Bioresource Technology, Palampur, Himachal Pradesh, India

1 Introduction Mountains are well recognized as treasure houses of biological diversity that have been contributing significantly to the functioning of the global ecosystem. The highest mountain range on earth, the Himalaya, is a biodiversity hotspot that harbors an estimated 10,381 plant species (including lower groups). Among these, 33% are endemic to Himalaya. Further, the Indian Himalaya region (IHR) comprises more than 1748 plant species (angiosperms 1685, gymnosperms 12, and pteridophytes 51) with reported medicinal uses (Samant et al., 2007). Many of these plants have immense therapeutic value in the Ayurvedic, Unani, Tibetan, and other traditional systems of medicine. There has been an increasing awareness about the benefits of herbals in the last few decades. Therefore, the utilization of these plants has increased several-fold in various plant-based pharmaceutical industries in the last few decades. There has also been a quantum increase in the global demand for herbals from the Himalayan region (Bhat et al., 2013). It is estimated that around 90% of medicinal plant species are extracted from the wild in the Himalaya, and out of this, 69% of the material is collected through destructive harvesting (Samant et al., 2007; Bhat et al., 2013). As a result, a number of Himalayan plants now figure in the IUCN Red List of rare, endangered, and threatened medicinal plants and require urgent conservation efforts (Rana and Samant, 2010; Goraya, 2011). The Himalaya not only controls the climatic regime of the Indian subcontinent (Krishnan et al., 2019), but also provides goods and services critical for the livelihood of people inhabiting the region (Xu et al., 2019). Unfortunately, this gigantic but fragile mountain range is under threat owing to large-scale habitat degradation, loss of species, spread of invasive species, and the heightened consequences of changing climatic conditions. As a result, the plant genetic resources of the region are being depleted at unprecedented rates. The major reasons for the decline in the populations of medicinal plants, land races of crop plants, wild relatives of crop plants, and other wild species are developmental activities such as road construction, tourism, air pollution, overharvesting for commercial purposes, and high intensity of grazing by cattle. Modern varieties, which are genetically uniform and vulnerable, are replacing the highly diverse local cultivars and landraces in the traditional agro-ecosystems of Himalaya. With an urgent need to conserve these habitats, the collection, conservation, and evaluation of the existing diversity of Himalayan plant species have assumed greater importance. This will not only establish a sustainable stock of wild resources for the future, but will also help in enriching the indigenous germplasm for sustainable utilization. Until now, various approaches have been adopted for the conservation of plant genetic resources. These include the establishment of systems for inventorying existing diversity, monitoring their status, and coordinated conservation practices based on in situ and ex situ strategies. The scope of applying these and other recent technologies in the conservation and improvement of plant genetic resources of Himalaya is discussed in this chapter. Successful case studies and examples from our current research are also discussed.

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Strategies for the conservation and improvement of plant genetic resources

Traditionally, in situ conservation efforts have utilized the demarcation of protected areas, whereas ex situ conservation efforts have included in vitro approaches, gene banks, and storage of propagules. However, conservation efforts have taken new dimensions with the advent of new technologies in recent years. As per the need of the hour, these new approaches have been integrated with traditional but well-developed methods of conservation. These are briefly described in the following sections.

2.1 Geospatial and imaging technologies The planning and decision making for the conservation and management of plant genetic resources require judicious and sustainable utilization. In this context, knowledge of the availability, distribution pattern, and overall status of the plant resources in a region is a prime requisite for successful conservation. For this purpose, various geospatial techniques such as geographic information systems (GIS) and remote sensing (RS) are widely used at present.

2.1.1 Geographic information system technologies GIS is a set of software and hardware capable of creating and analyzing any kind of geographic information, which includes acquisition and compilation through visualization, queries, and analysis for modeling objectives, sharing, or archiving (Longley et al., 2010). One example of this technology is the “species-specific distribution maps” of floral resources. Such maps can be prepared using geographical coordinates of their occurrence records in a GIS environment. These help in understanding the nature and pattern of the spatial distribution of plant resources for inventorying its overall status and subsequent conservation and management. A total of 1141 such maps have been prepared for the flora of the western Himalayan region depicting its spatial distribution (Kumar et al., 2010). Similarly, the potential of GIS for mapping potential areas with high species richness has been demonstrated for guiding floristic surveys (Malik et al., 2015). A GIS-based village level climate change vulnerability profile was prepared for the Bengal Duars region of Eastern Himalaya (Sam and Chakma, 2018). Web GIS or Internet GIS is another geospatial technology that provides the opportunity for online access of the spatial data of a region. Using the ArcGIS Server 9.3 platform, a web GIS application (KSIS) was developed for the Kangra district of Himachal Pradesh, India. This application can be accessed for multilayered GIS queries corresponding to primary and secondary types of spatial and nonspatial data such as that related to flora, topography, administrative maps, and satellite images (Kumar et al., 2013b). Ecological niche modeling (ENM) is another relevant approach for the conservation and management of plant resources. ENM is a “species distribution empirical model” relating field observations to environmental predictor variables (Warren and Seifert, 2011). It provides information on suitable habitats for the occurrence of a particular plant species. This is advantageous in the case of rare, threatened, endangered, and commercially important plants. The ENM approach was used for prioritizing the areas having a probable distribution of Sinopodophyllum hexandrum, a critically endangered Himalayan species. It also provided a suitability index for their in situ conservation in nature (Banerjee et al. 2017). ENM has also been used for mapping the potential distribution of invasive tree species (Sapium sebiferum) in western Himalaya ( Jaryan et al., 2013).

2.1.2 Remote sensing technologies Remote sensing is defined as the science and techniques of obtaining information about an object, land area, phenomenon, or ecosystem process acquired by a device that is not in contact with the object, area, or phenomenon under investigation (Lillesand et al., 2015). Satellite images are used to prepare land use/land cover (LuLc) maps of a region so that this can serve as a baseline data for several applications. The forest gaps identified in LuLc maps can be targeted for afforestation programs. These maps are also key inputs for climate change modeling studies. The landscape ecological analysis coupled with LuLc leads can enhance the understanding of landscape compositions and the extent of fragmentation of natural vegetation. The changes detected using temporal LuLc show the nature and extent of changes in the landscapes and may be induced by either natural factors or humans. Based on these changes, appropriate action plans are formulated as corrective measures. The detailed ground truth-based LuLc maps of Kangra (Kumar et al., 2007), Kinnaur (Chawla et al., 2012), the Solang nala watershed (Kumar et al. 2011a), and the Pangi area (Kumar et al., 2013a) of Himachal Pradesh, India, were prepared using various (IRS 1D, IRS P6, and Quick bird) kinds of satellite data. These LuLc maps provided information on forest types and landscape characterizations of the above-mentioned regions. Maps of apple orchards in the Spiti valley (Kumar et al., 2008) and bamboo resources in the Kangra, Hamirpur, and Una districts of Himachal Pradesh (Kumar and Uniyal, 2008) were also generated. These are examples of LuLc prepared for resource mapping. In other applications, the interannual vegetation productivity (greening versus browning) for the Himalayan region was derived using remotesensing, time-series vegetation indices (Mishra and Mainali, 2017). The remotely sensed data along with the modeled climate data of the Himalayan region were then used to model the ecological niche of Betula utilis (Bobrowski et al.,

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2018). Similarly, the spatial patterns of timberline in the Uttarakhand, India, were studied using remote-sensing techniques (Sah and Sharma, 2018). These applications are the outcome of conventional remote sensing, which has dependencies on coarser to moderate spatial resolution satellite data. These satellite images are multispectral, consisting of few and broad spectral bands that pose limitations in terms of spectral resolutions. In contrast, the new generation “hyperspectral sensors” simultaneously record reflectance from targeted objects in a large number of narrow adjacent spectral bands of the electromagnetic spectrum. Thus, these are more appropriate in extracting biophysical and biochemical properties as well as yield information on plants and can even discriminate between plant species (Upadhyay and Kumar, 2018). A repository of spectral signatures of plants is a prerequisite for such hyperspectral remote sensing (Fig. 1). In this regard, a hyperspectral library of commonly occurring Himalayan plant species was developed (Manjunath et al., 2014). The menu-driven graphical user interface (GUI) was developed in the .Net programming environment for accessing information on approximately 80 plant species such as spectral details, spectral graphs, species spectral narrowband indices, species biochemical parameters, general information of species, observation details, plant photographs, etc. A hyperspectral image to discriminate forest tree and shrub species is shown in Fig. 2. In another application, the field hyperspectral data was analyzed in a nondestructive way to manage and monitor tea (Camellia sinensis) plantations, owing to the potential of hyperspectral remote sensing to detect certain parameters influencing tea garden management. These parameters included plant type, age, growth stage, pruning, light conditions, and disease incidence (Kumar et al., 2013a). Further, the application of unmanned aerial systems (UAS) imagery for the species-level mapping of vegetation in the Himalaya using a hierarchical geographic object-based image analysis (GEOBIA) method was carried out for Langtang National Park in central Nepal (Mishra et al., 2018).

FIG. 1 Spectral signatures of some of the tropical tree species of the Himalayan region.

FIG. 2 A hyperspectral image acquired for a forest patch.

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2.1.3 Thermal imaging for species discrimination Thermal remote sensing deals with the acquisition, processing, and interpretation of data (images) acquired in the thermal infrared (TIR) region, primarily using 8–14 μm wavelengths of the electromagnetic spectrum. Thermal imaging is based on radiation emitted from the surface of target objects. Any object above absolute zero (0 K or 273.15 °C) is known to emit radiation in the infrared range from its surface, and can be detssected using hand-held portable sensors or aerial or satellite deployed sensors. This technology has a range of applications such as the estimation of crop stress to its most recent integration in precision farming. Leaf epidermis (including cell wall material and cell membrane characteristics) and leaf water content chiefly influence emittances in the TIR region. Thermal imaging of leaves is based on the leaf energy balance equation, that is, leaf temperature is dependent on transpiration from leaves ( Jones et al., 2009; Gerhards et al., 2016). Estimating the thermal profile of medicinal plants under natural field conditions is very challenging due to highly fluctuating environmental factors such as air temperature, humidity, vapor pressure deficit, wind speed, and incident/scattered radiation. Recently, thermal imaging has been utilized for species discrimination based on leaf and canopy thermal properties. TIR has an advantage over hyperspectral “visual near infrared short wave infrared (VNIR-SWIR, 0.4–2.5 μm) because it relies on the fact that the spectral response of leaves is dominated by plant tissues of external surfaces such as the cuticular membrane and outer cell walls. In VNIR-SWIR remote sensing, however, the wavelength absorption features are dominated by pigments and water within the leaf volume (da Luz and Crowley, 2010). Different species have characteristic unique spectral features due to differences in the chemical composition of their surface tissues (da Luz and Crowley, 2007). Besides, VNIR-SWIR does not produce distinctive signatures unique to individual plant species because it is based on constituents present in all plants. Moreover, it is difficult to translate the observations VNIR-SWIR has taken in the laboratory to canopy scale in field conditions (Hestir et al., 2008). Therefore, TIR has a potential for species discrimination applications. In a pioneering study, da Luz and Crowley (2010) identified 50 species on the basis of TIR spectral profiles and highlighted its potential for species identification. Ullah et al. (2012) demonstrated the utility of middle infrared (MIR) and TIR bands for reliable species discrimination in 13 broad-leaved species at the laboratory level. Rock et al. (2016) utilized emissive TIR spectroscopy to successfully discriminate eight different plant species under field conditions and advocated the suitability of TIR for species discrimination. In our study, different subalpine and alpine species were screened for the TIR profiles of their leaves and canopies (Fig. 3). Based on different levels of adaptations of various species

FIG. 3 Thermal profiles of leaves and canopies of medicinal plants growing in their natural habitats (clockwise from top left: Picrorhiza kurrooa, Rosularia alpestris, Rhododendron anthopogon, Potentilla argyrophylla).

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to harsh conditions of high altitude, the responses were different and showed varying temperature profiles of their leaves and canopies. The interspecific and intraspecific emissivity responses in TIR showed the potential to understand the level of adaptation of these species to different types of stress prevalent in the region. In view of the above, it is recommended that TIR should be utilized along with VNIR-SWIR hyperspectral imaging for effective species discrimination, and that methods be optimized for field-level recordings. Such studies could be utilized for distinguishing vegetation types during floristic mapping programs. Further, leaf physiological parameters such as transpiration rate, stomatal conductance, and water potential should also be estimated for inter- and intraspecific comparisons.

2.2 Functional trait-based approach for conservation of threatened species A plant functional trait is any morphological, anatomical, physiological, or phenological parameter affecting the individual performance such as growth, reproduction, and survival. It can be measured at the cellular or whole organism level (Violle et al., 2007; P
erez-Harguindeguy et al., 2013). Species-level traits are estimated as the mean of individual traits assessed at the scale of population (Perronne et al., 2017), and are interpreted in reference to local environmental conditions. A functional trait-based approach for the conservation of threatened species requires the identification and measurement of traits relevant to the targeted threatened species and could be used to understand the vulnerability of such species. The knowledge of the right set of functional traits coupled with associated environmental variables can facilitate an understanding of factors governing the population fitness and species persistence. This in turn can help in the conservation of species. Alvarez-Yepiz et al. (2019) identified some key traits of the cycad Dioon sonorense on the basis of its influence on population vitality and broad ecosystem functions. These included physiological traits such as water use efficiency and nitrogen fixation, as these can indicate the efficiency of resource use. Morphological traits such as sclerophylly indicate decreased water loss and increased protection against herbivory, whereas phenological traits such as evergreen leaves indicate increased nutrient retention in water and nutrient-limited habitats. The information from such traits suggest the measures that can be adopted for the survival of populations. These include providing artificial shading or protection from nurse plants for seedling survival, especially during the first few months of development. The types of conspecific interactions also have important ramifications as they can guide the selection of appropriate microsites for seedling establishment, species restoration, and reintroduction efforts. Vandewalle et al. (2010) stressed the use of functional traits as potential biodiversity indicators and their incorporation in monitoring schemes. Besides providing a framework based on functional trait indices, a strategy on how these traits can be used to monitor the responses of biodiversity to different drivers of land use change was illustrated. Its use in complementing the existing biodiversity monitoring schemes was also shown. Lohbeck et al. (2018) suggested the importance of studying functional traits to understand the site requirements of a particular crop species. They found that vegetation cover and above ground biomass impose strong positive effects on soil health by increasing soil organic carbon and reducing soil erosion. They further hypothesized that functional ecology can help in designing strategies to restore degraded land for the growth of selected crop species. We used this approach to carry out a study on Dactylorhiza hatagirea, a terrestrial orchid endemic to the Himalayas (Fig. 4). The plant has become threatened in its habitat due to indiscriminate harvesting of its medicinally important tubers (Pant and Rinchen, 2012). A total of 23 D. hatagirea-dominated plant communities were studied. Its population density and functional traits were estimated. Functional traits such as plant height, specific leaf area (SLA), leaf N%, leaf dry matter content (LDMC), biomass per plant, and mass of different parts (root mass, shoot mass, and inflorescence mass), specific shoot length (SSL), inflorescence length fraction (ILF), number of flowers and fruits per plant, flowers per unit length (FPL), and fruiting percentage were measured. All these traits are indicative of the plant’s vegetative and reproductive performance. A low population density of highly disturbed D. hatagirea populations was found to have higher values for plant height (28.21  6.66 cm), specific shoot length (51.38  22.59 cm/g), SLA (282.8  35.18 cm2/g), and leaf nitrogen content (2.89  0.47%) compared to less disturbed populations (Table 1). This suggested an increase in plant performance due to high levels of disturbance (Thakur et al., 2018). An increase in fruit set per individual plant (43.85  17.21%) in such populations was also recorded. This is a measure of reproductive success, though these had fewer flowers per individual (15.46  5.01) and shorter inflorescence length per individual (9.13  2.22 cm), ILF (0.26  0.004), and FPL (1.62  034) (Table 1). The increased growth performance and reproductive success attained by D. hatagirea populations under tremendous disturbance pressures indicate their good recovery potential. Therefore, the study helped to identify populations that would

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FIG. 4 Dactylorhiza hatagirea plants growing in their natural habitat.

TABLE 1 A comparison of functional traits observed under low disturbance and high disturbance sites (see Thakur et al. (2018) for the estimations). S.no.

Functional traits

Low disturbance sites

High disturbance sites

1

Population density (per m )

23.57  11.17

2.97  1.74

2

Plant height (cm)

21.06  6.02

28.21  6.66

3

Specific shoot length (cm/g)

30.85  11.95

51.38  22.59

4

2

Specific leaf area (SLA, cm /g)

230.1  29.17

282.8  35.18

5

Leaf nitrogen content (%)

2.21  0.28

2.89  0.47

6

Flowers per individual

27.15  7.92

15.46  5.01

7

Inflorescence length per individual (cm)

12.31  2.67

9.13  2.22

8

Inflorescence length fraction (ILF)

0.37  0.06

0.26  0.04

9

Flowers per unit length (FPL)

2.24  0.58

1.62  0.34

10

Fruit set (%)

19.67  9.58

43.85  17.21

2

Values are provided as average  standard deviation.

have the potential to recover after a disturbance, if conserved. Such populations could therefore be targeted for intense conservation efforts. Further, the complementation of the study of functional traits with a study of habitat parameters can lead to the development of cultivation practices for target species. Moreover, the integrated study could also lead to the identification of sites for reintroduction of the plant to reverse its threatened status in the wild.

2.3 Micropropagation as a method for sustainable resource generation Micropropagation or in vitro propagation of threatened plants has been a time-tested and effective method of ex situ conservation (Reed et al., 2011). The method exploits the totipotent nature of a plant cell to produce new individuals from either protoplasts, cells, undifferentiated masses of cells (callus), small pieces of tissue, and/or excised organs. After the usefulness of the method was first established, micropropagation has been extensively used in agriculture, forestry, and horticulture for the large-scale production of disease-free planting materials of high quality (Oseni et al., 2018). It is also the most effective method of eliminating viruses from valuable horticulture crops, rescuing somatic hybrids and hybrids generated through

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conventional breeding, developing transgenic plants for desired traits, and gene pyramiding. The method has tremendous industrial applications. It can be used as a nondestructive approach for producing secondary metabolites from medicinally important plants in vitro for their upscaling in bioreactors (Ziv, 2005). Micropropagation has proven particularly effective in the ex situ conservation of a number of endangered plants. Particularly, in plants where seeds or other propagules are not easily available, micropropagation offers an alternative route for either the replenishment of rapidly dwindling populations or the generation of alternative resources of medicinally important secondary metabolites (Reed et al., 2011). Therefore, micropropagation has been used for the ex situ conservation of a few endangered western Himalayan plants. An example of this is Arnebia euchroma, a Himalayan herb that has become critically endangered because of indiscriminate harvesting. The belowground parts of the plant yield napthoquinone, a red-colored edible dye. Manjkhola et al. (2005) attempted to conserve this plant through organogenesis, embryogenesis, and synthetic seed production. Later, Pal and Chaudhury (2010) and Malik et al. (2010a,b, 2014) developed micropropagation systems for the plant with an aim to generate an alternative resource base for napthoquinones. In another endangered Himalayan plant, Rheum emodi of the family Polygonaceae, Lal and Ahuja (1993) tried to assess the feasibility of micropropagation in a liquid culture. The plant has been the subject of indiscriminate harvesting because of the predominance of medicinally important anthraquinones in its rhizomes. The same group also used the rhizomes of micropropagated R. emodi plants for qualitative and quantitative analysis of anthraquinone derivatives. Aconitum heterophyllum of the family Ranunculaceae is another medicinally important plant that has become endangered because of the ruthless exploitation of its belowground rhizomes. The alkaloids present in the rhizomes are extensively used in various traditional systems of medicine, particularly Ayurveda. Therefore, Giri et al. (1993), Jabeen et al. (2006), and Belwal et al. (2016) developed micropropagation systems as effective routes for the ex situ conservation of the plant. Picrorhiza kurroa is an endangered medicinal herb of the western Himalaya. The plant has suffered from extensive harvesting by various pharmaceutical companies. The roots and rhizomes of the plant contain picrosides I and II, known for their hepatoprotective properties. Therefore, micropropagation of the plant was attempted by different workers with the aim to develop an alternative resource base for these compounds. In this regard, Lal et al. (1988) were the first to report clonal propagation of the plant by shoot tip culture. Thereafter, there were a few more reports on micropropagation (Lal and Ahuja, 1996; Chandra et al., 2006; Sood and Chauhan, 2009; Jan et al., 2009). Different explants were used in these studies. Therefore, in a totally different approach, segments of leaves of tissue culture-raised plants were used to regenerate a large number of in vitro plants of P. kurroa for reintroduction back into the natural habitat (Patial et al., 2012, 2017). The group rehabilitated several thousand micropropagated plants of P. kurroa in their natural habitat with the help of a medicinal plant collector for the first time (Fig. 5).

FIG. 5 Micropropagation of Picrorhiza kurroa: (A) shoot multiplication, (B) rooting of in vitro shoots, (C) hardening under greenhouse conditions, (D) micropropagated plants transferred to medicinal plant collector, and (E) rehabilitation in natural habitat.

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While micropropagation is an effective approach for the ex situ conservation of endangered Himalayan plants, researchers have failed to rehabilitate the micropropagated plants of a number of species back into their natural habitats. Critical analysis of these failures has revealed a number of aspects that need to be dealt with during rehabilitation. These include: (i) proper hardening of the micropropagated plants, (ii) identification of correct habitat niches for reintroduction of the plants, (iii) identification of possible threats that the reintroduced plant may face at the identified habitat niche, (iv) reintroduction of a minimum critical population of plants for self-sustenance, and (ii) collaborations with medicinal plant collectors, Himalayan tribes, and other stakeholders to protect the reintroduced micropropagated plants from major threats identified at their natural habitat. Although micropropagation should be attempted for more and more plants prioritized under the threatened category, the method should be restricted to only the ones that face extinction due to reproductive barriers or lack of vegetative propagation methods.

2.4 Importance of adventitious roots and hairy roots in conservation Adventitious roots have gained importance due to their rapid growth rate and easy extraction of marker compounds (Murthy et al., 2016). Natural roots developing from differentiated cells of any organ (such as the leaf, root, or stem) are termed adventitious roots. These roots are a good source of phytochemicals due to their genetic and biosynthetic stability, their potential for high biomass production, and specific metabolite synthesis (Cui et al., 2011). The use of bioreactors, especially balloon-type bubble bioreactors, to cultivate Panax ginseng and Echinacea purpurea adventitious roots paved the way for the large-scale production of organ cultures (Paek et al., 2005; Wu et al., 2007). Hairy roots are used as a powerful biotechnological tool for the large-scale production of high-value secondary metabolites (Talano et al., 2012). These roots are formed as a result of infection of any plant part by Agrobacterium rhizogenes, a Gram-negative soil bacteria. The rol genes (rolA, rolB, rolC, and rolD) present on the T-DNA region of the Ri plasmid of the A. rhizogenes are responsible for the development of hairy roots in infected plants. Hairy roots are genetically more stable with the ability to grow indefinitely without the use of exogenous growth regulators. Therefore, hairy roots have been induced on explants such as leaves, segments of leaves and internodes, stems, etc., for the production of secondary metabolites, monoclonal antibodies (Cardon et al., 2019), phytoremediation (Daspute et al., 2019), metabolic engineering, and regeneration of complete plants (Dhiman et al., 2018). Hairy roots, which can be developed from any explant, are genetically stable, fast growing, and can be cultivated in hormone-free media (Srivastava and Srivastava, 2007; Banerjee et al., 2012). These have the potential to produce large quantities of valuable secondary metabolites such as alkaloids, terpenoids, steroidal compounds, phenolics, etc. (Muranaka and Saito, 2010). Hairy roots are fast emerging as a valuable alternative to true roots, and have the potential to alleviate the need for uprooting medicinal plants for their secondary metabolite-rich belowground parts. Thus, hairy roots have become an integral part of many ex situ conservation programs, and have been developed in hundreds of plant species for medicinally important metabolites. These include Himalayan plants such as Aconitum heterophyllum (Giri et al., 1997), Anisodus luridus (Qin et al., 2014), Berberis aristata (Brijwal and Tamta, 2015), Mirabilis himalaica (Lan et al., 2015), Picrorhiza kurroa (Mishra et al., 2011) etc. An appreciable increase in the amount of secondary metabolites by up to several-fold has been reported in many of these cultures. These findings have paved the way for a stable system for continuous production of specific secondary metabolites without damaging valuable Himalayan plants (Dhiman et al., 2018). Appreciable amounts of secondary metabolites have been produced in hairy root cultures by manipulating culture conditions, media components, precursor feeding, biotic and abiotic elicitors, type of bacterial strain, and through genetic engineering (Stiles and Liu, 2013; Mehrotra et al., 2018). Such optimizations have led to the enhanced production of secondary metabolites in the hairy roots of many plant species (Malik, 2017). Extensive optimization for the scale up of hairy roots in bioreactors have also been attempted, wherein the maintenance of low hydrodynamic stress but high volumetric oxygen has been found crucial. A popular example of this is the large-scale production of the hairy roots of Camptotheca acuminata in airlift mesh draught-type bioreactors by the company ROOTec Bioactives at Witterswil in Switzerland (Dhiman et al., 2018). Hairy roots can also serve as excellent models for in-depth understanding of the basic mechanisms governing secondary metabolite production in roots. The hairy root culture conditions can be manipulated for enhanced production of valuable secondary metabolites. These can be further upscaled using bioreactors. It can also be used for the biotransformation of lowvalue precursors into high-value phytochemicals. The approach can be utilized as an alternative source of secondary metabolites without damaging or uprooting an endangered plant. Thus, the hairy root approach is an important biotechnological tool for the ex situ conservation of endangered plants.

2.5 In vitro production of quality medicinal and aromatic plant ingredients Medicinal and aromatic plants synthesize a variety of phytochemicals/bioactives that have been catering to the needs of human beings for centuries. Hence, medicinal and aromatic plants have been an integral part of traditional systems of

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medicine in every society. In general, the bioactive compounds, also known as secondary metabolites, are produced by plants for their own defense and survival under various biotic and abiotic challenges (Gea et al., 2018). These compounds are produced at relatively very low quantities during specific developmental stages and under specific conditions such as seasonal, stress, or nutritional (Verpoorte, 2000; Malik et al. 2014). Human beings have primarily extracted these secondary metabolites from either roots, bark, and/or whole plants and used them as nutraceuticals, additives, pharmaceuticals, pesticides, colorants, aromatics, or cosmetics. More than 60% of global trade by volume in medicinal and aromatic plants is based on wild collection. An estimated >6.0% compound annual growth rate of the world market for botanical and plant-derived drugs from the present $29.4 billion to $39.6 billion is envisaged by 2022 (Lawson, 2017). The continuous rise in use of herbal ingredients is causing either the complete destruction of such plant bioresources or huge reductions in natural plant populations. Most of these plant resources are now listed under rare, endangered, and threatened species (RET) in the Red List data book (Ved and Goraya, 2008). In this regard, secondary metabolite production through plant cells and tissue culture technology is a sustainable and alternative route to balance the present demand–supply ratio. In vitro production systems not only help in the conservation of commercially valuable plant bioresources, but they also provide an effective and feasible means of getting uniform quality raw materials with stable and defined metabolic profiles. Such technologies are replicated even at the industrial scale using conventional or specialized bioreactor systems (Baque et al., 2012; Georgiev et al., 2013). The basic purpose of a bioreactor and/or fermentor is to provide a controlled environment for optimum biomass and metabolic yield. Mostly, the production of secondary metabolites by an in vitro culture system occurs in a two-step process, that is, biomass accumulation and secondary metabolite synthesis (Gonc¸alves and Romano, 2018). The production is based on the selection of any type of culture system such as callus, cell suspension, and/or dedifferentiated organs such as shoots, adventitious roots, somatic embryos, etc. However, the profile and yield of secondary metabolites by the cell or organ culture as compared to native plants is not always similar, probably due to changes in the production system (Baque et al., 2012). Cells, tissues, or organs of commercially important plants have been used in vitro to produce ingredients of uniform quality and stable metabolic profiles. Shikonin derivative production using in vitro Lithospermum erythrorhizon cell cultures in bioreactors is the first successful industrial-scale attempt in Japan (Tabata et al., 1974). In order to find an alternative plant source to meet the large demands of this product, other members of the Boraginaceae family were exploited for the production of shikonin derivatives. A. euchroma being reported to contain higher pigment content compared to L. erythrorhizon is a good example of an alternative source of shikonins (Ge et al., 2003). Besides shikonin, cell suspension cultures of A. euchroma have also been reported to possess traces of acetylshikonin and β-acetoxyisovalerylshikonin (Sharma et al., 2008). A process for the production of naphthoquinone pigments using A. euchroma cell culture was developed by our group (Fig. 6). Besides the optimization of media components, a number of factors such as light condition, temperature, pH, type of inoculum, precursor, and

FIG. 6 In vitro production of naphthoquinone pigments from Arnebia euchroma cell cultures.

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intermediates were found to affect the overall pigment yield (Malik et al., 2008, 2011; Kumar et al., 2011b). Even the shikonin biosynthetic pathway genes were elucidated by our group (Singh et al., 2010), where 3-hydroxy-3-methylglutaryl-CoA reductase and p-hydroxybenzoate-m-geranyltransferase were found to play critical roles in shikonin biosynthesis. The current approach suggests that upscaling the metabolite production through cell culture can efficiently balance the demand and supply chain of the phytochemical ingredients. In addition, the sustainable bioreactor-scale cultivation with a stable and definite metabolic profile for extended periods at the industrial level need to be worked out for particular species.

2.6 Hydroponic and aeroponic cultivation of medicinal plants Medicinal plant cultivation under controlled conditions of hydroponic and aeroponic systems for secondary metabolite production has significantly gained acceptance among entrepreneurs in recent years and offers opportunities for large-scale biomass production. These systems have the potential for “year round” crop production and also ensuring food safety and biosecurity as well as considerably reduced inputs of water supply, pesticides, and herbicides (Hayden, 2006). These cultivation systems offer an opportunity to produce quality biomass, with an advantage of cutting short the growth cycle of medicinal plants. The hydroponic technique utilizes a nutrient medium to grow plants, whereas a fine mist of nutrient solution is used to grow plants in an aeroponic system. These systems provide optimum control of growing conditions, including temperature, nutrient level, pH, humidity, misting frequency and duration, and oxygen availability, to the root zone environment. These qualities endow these systems with the potential to become a viable commercial method for the cultivation of high-value medicinal root crops, which avoids some general difficulties associated with cultivation in soil.

2.6.1 Picrorhiza kurroa Royle ex Benth: A case study A cultivation method for Picrorhiza kurroa, an important medicinal herb valued for its pharmaceutically valued picroside I and picroside II, under hydroponic and aeroponic conditions was developed for the first time for the production of quality biomass (Fig. 7). The findings revealed enhanced contents of picroside I and II in the leaves

FIG. 7 Cultivation of P. kurroa under aeroponic and hydroponic conditions.

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(3.79%) and stems (1.34%) of aeroponically treated plants as compared to the control. Significant amounts of picrosides were also found in the rootlets of treated plants (picroside I: 1.45%; picroside II: 0.22%). Even in hydroponic conditions, the picroside I content (1.19%) was enhanced in the rhizome of treated plants. Changes in picroside content in hydroponic and aeroponic systems using root zone temperature (10 °C) were probably due to a difference in the nutrient metabolism. Such a difference has been explained by Chandra et al. (2014), Sakamoto and Suzuki (2015), and Salachas et al. (2015). Both hydroponic and aeroponic cultivation systems allow the accurate manipulation of environmental conditions, thereby offering increased production and improved quality of crops. In particular, nutrient solution characteristics such as temperature, pH, electrical conductivity, and oxygen content can be manipulated according to the specific requirements of plants. The methods also have the potential to produce quality material in a reduced time duration. The nutrient solution is the fundamental component in hydroponic and aeroponic systems. The electrical conductivity of the nutrient solution allows the growth of the plant. Moreover, the accurate supply of nutrient solution and the regulation of pH lead to the production of quality biomass. Therefore, these cultivation methods can increase crop yields while reducing the unit cost of production. Besides economic benefits, these systems can facilitate the conservation of water and generate employment.

2.7 Importance of genetic diversity in conservation of biodiversity Genetic diversity is also known as “genetic polymorphism.” It is defined as the quantification of the measure of genetic variability present in a population. In simple terms, genetic diversity represents the variations present in the DNA sequences of different individuals of the same species. New genetic variants are added to every generation due to spontaneous and random mutations. Thus, genetic diversity reveals the equilibrium between a loss of variations and mutations, the fundamental source of biodiversity (Hughes et al., 2008). In other words, it represents the balance between the new and lost genetic variants (Ellegren and Galtier, 2016). The variation observed in genetic diversity is because the rate of mutation is not constant in genomes and species (Hodgkinson and Eyre-Walker, 2011; Lynch, 2010). Loci with neutral alleles are affected by genetic drift, leading to fluctuations of allele frequency. Thus, genetic diversity is governed by the fixation and rate of allele loss. In an idealized population, all individuals contribute equally to reproduction (panmictic population); however, real populations do not behave like panmictic populations. Therefore, the concept of effective population size (Ne) emerged, wherein the ideal population shows the same genetic diversity as the population of interest (Ellegren and Galtier, 2016). Previously, high genetic diversity among species was reported using allozymes. This was further confirmed by using DNA markers. With the advent of high-throughput, next-generation sequencing (NGS) technologies, the whole genome sequence information of large and complex plant genomes along with nonmodel plants species is available. These are fundamental sources of biological information for plant research. The large-scale genomic data available today give information about questions related to genetic diversity such as the population history of a species, the prevalence of linkage effects, and the impact of a mating system. NGS plays a key role in the development and creation of large-scale genomic resources (molecular markers such as SSRs and SNPs), making genetic diversity analysis studies more robust. Some of the information on chloroplast DNA (cpDNA) of plants is being utilized for ecological studies of plants because cpDNA is inherited from the maternal parent, has a low mutation frequency, and rarely undergoes recombination. The genetic diversity estimation based on cpDNA gives information about the evolutionary history of a plant species while also revealing the possible route of recolonization, gene flow, and diversification events. This type of approach for genetic diversity analysis is being utilized for ecologically, medicinally, and commercially important plant species. It is widely accepted that the genetic polymorphism of a species is shaped by its demographic history as well as biotic and abiotic changes. Any change in the effective population size (Ne) affects genetic diversity and a bottleneck causes the rapid decay of heterozygosity due to enhanced fluctuation of the allele frequency in a population. This results in genetic drift or randomness of reproduction and survival of individuals even under selection pressure (Romiguier et al., 2014). Inbreeding and genetic bottlenecks affect the genetic diversity of endangered species and also reduce the ability of the population to survive under stressful conditions. Therefore, the importance of genetic diversity in fragmented and endangered populations is being realized in the fields of conservation genetics, ecology restoration, and related fields. Classical studies in conservation and evolutionary biology have revealed the huge impact of genetic diversity on ecological processes such as community structure, primary productivity, population recovery from damage, and interspecific competitions. The ecological consequences of biodiversity are important, but little information is available on how genetic diversity and other factors affect various ecological processes (Hughes et al., 2008). Therefore, efforts are needed to understand the impact of genetic diversity on the mechanism underlying ecological consequences. Genetic diversity within a

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population helps to improve the growth and stability of the population while also affecting the ecological processes and interactions among communities (Hughes et al., 2008). Therefore, the impact of genetic diversity on ecological consequences can be easily understood in agronomy, wherein genetically diverse material is planted in the same field to increase yields (Wolfe, 1985).

2.7.1 Genomic resource creation and genetic diversity analysis in Himalayan plants Habitat destruction, landscape degradation, and huge losses of biodiversity due to anthropogenic activities and climate change are major global challenges (Breed et al., 2019). Therefore, conservation biologists are now focused on the restoration of fragmented and small populations while minimizing inbreeding/harmful impacts and maximizing the retention of genetic diversity. A few examples on the genetic variability, conservation, and restoration of medicinal plant populations of Himalaya are discussed below. Sinopodophyllum hexandrum (Royle) T.S. Ying (Syn Podophyllum hexandrum Royle), commonly known as the Himalayan Mayapple, is distributed in temperate and alpine regions of the Himalayas, and is known for its anticancer properties. The roots and rhizomes of the plant contain podophyllotoxin (4.3%), used for the semisynthesis of anticancer drugs (Tyler et al., 1988). The size of its natural populations is declining at an alarming rate due to habitat fragmentation and overexploitation. Biological factors such as long dormancy and poor natural regeneration also contribute to the small size of the natural populations. The plant is now placed under the “endangered” category (Ved and Goraya, 2008). To conserve the genetic diversity of P. hexandrum, an evaluation of genetic variations in different geographical locations is needed to identify the elite germplasm with maximum genetic variability. Twenty novel unigene-derived SSR markers from P. hexandrum transcripts were developed and 24 populations comprising 209 individuals representing the whole Indian Himalayan region were analyzed for genetic diversity using AFLP markers (Nag et al., 2012, 2015). Principal component analysis, neighbor joining clustering, and structure analysis using 866 polymorphic regions revealed two major genetic populations with moderate genetic differentiation and high gene flow. These results revealed that P. hexandrum populations in the Indian Himalayas are intermixed and diversity is restricted to within populations. The authors also concluded two possibilities for the population structure of P. hexandrum. The first one is that all the populations of the Indian Himalayas are remnants of an ancient population. The second is that these populations might have originated from two different genetic populations that coexisted earlier but separated subsequently due to natural selection. The primary goal to understand and conserve genetic diversity is to protect and restore the status of endangered plants species, wherein genetic diversity characterization and population structure analyses are gaining tremendous attention. Aquilaria malaccensis is an endangered Himalayan plant with high economic values that is now reported to have become “extinct in the wild” in Assam (Northeast). It is only growing in the home gardens of a few states of India. Home garden plantations of rare and endangered plants are a proven and effective method of ex situ conservation (Kabir and Webb, 2008). The nonavailability of genomic resources in A. malaccensis is hampering its genetic improvement. Therefore, 18 novel SSR markers were developed from enriched genomic libraries. These were validated in 45 individuals (three populations) of A. malaccensis. The analysis revealed the utility of these markers in genetic diversity and population structure analysis of the elite germplasm of the plant (Singh et al., 2014). In another study on the genetic diversity of A. malaccensis, 127 plants collected from the home gardens of three states of Northeast India were characterized using AFLP markers (Singh et al., 2015). Approximately 916 polymorphic fragments were identified, revealing high genetic diversity (71.85%), low genetic differentiation (Fst: 0.069), and high gene flow. Furthermore, high genetic variations within the population revealed that most of the variation lay within the population and not between populations. Structure, principal coordinate analysis, and neighbor joining grouped all the accession into two groups and revealed high intermixing between the populations. Perhaps the most interesting observation of the study was the identification of five genetically diverse populations based on diversity inferences, which can be exploited in the conservation of A. malaccensis. Pteris cretica is found in the Himalayan and central Mountain regions of India. It has the capacity to accumulate and tolerate high concentrations of arsenic and can be utilized as a model plant to study how plants capture heavy metals from the soil. For genetic diversity analysis, 33 genomic SSRs were developed and utilized to evaluate six populations (48 individuals) of the western Himalayas. High genetic diversity within the population but low genetic differentiation were recorded for these populations (Kumar et al., 2015). The high genetic diversity present in this apomictic fern probably allows other plants to adapt and grow in various environmental stresses. In another study, Singh and Kumar (2019) developed a set of highly polymorphic genic SSR markers in P. kurroa. In order to expedite the conservation of natural

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populations of P. kurroa, understanding its genetic diversity was needed. Therefore, the diversity of 28 individuals from three different locations was analyzed and clustering of the individuals revealed a spatial population structure in P. kurroa. Morus alba L. is a highly heterogeneous tree due to its out breeding nature and is distributed in tropical, subtropical, and temperate zones. However, it is believed that the species originated from the lower slopes of the Himalayas (Awasthi et al., 2004). Therefore, an evaluation of the population growing in the Himalayan region was important. Bajpai et al. (2014) collected 56 wild Morus alba plants from 14 different locations and performed a genetic structure analysis. Overall, high genetic diversity was recorded and an analysis of the molecular variance (AMOVA) revealed a variation of around 80% within the collection sites. Further, STRUCTURE and BARRIER results revealed significant differentiation and high to restricted gene flow in the populations while also indicating a natural fragmentation in the Himalayas (trans). The “Himalayan region” was found to be the center of diversity for the mulberry. In flowering plants, only a few species have morphologically different sex chromosomes, and the early determination of the sex of the plant has commercial applications. Seabuckthorn is a dioecious plant; unfortunately, identification of the gender of the seabuckthorn is difficult until flowering. Therefore, Korekar et al. in 2012 developed female-specific (HrX1 & HrX2) PCR-based markers (Sequence based RAPD) to determine the sex of the seabuckthorn at the vegetative stage. Genomic data have the potential to reveal adaptive variations, the key conservative units in plant genomes. However, these are difficult to predict in rare and endangered plants. Population genomics, on the other hand, offer a detailed molecular picture of species lineages, even for nonmodel organisms, for their conservation. For example, Trillium govanianum is an endangered medicinal herb native to the Himalayas. However, the genetic diversity of this plant is less studied due to the nonavailability of genomic information. Therefore, a large dataset of genomic sequences was generated in this plant via transcriptome sequencing of multiple tissues. Approximately 11.5 Gb high-quality reads were generated and assembled into 69,174 transcripts. Differentially expressed genes were identified in various steroidal saponins and other secondary metabolite pathways. Moreover, a few transcription factors such as bHLH, MYB-related, NAC, FAR1, bZIP, B3,s and WRKY regulating various important pathways were also identified. Interestingly, the generated data can be utilized to mine functionally important markers to enhance molecular breeding efforts and conservation strategies in Trillium govanianum (Singh et al., 2017).

2.8 Gene banks, captive cultivation, and varietal improvement of threatened medicinal plants Pharmaceutical industries involved in drug development rely on huge quantities of raw produce for the bulk production of drugs. This has resulted in the unprecedented exploitation of medicinal plant resources in the wild. There is considerable loss of populations in the case of plants where underground stems (stolons, tubers, bulbs, corms, or rhizomes) and/or roots are of economic value. The situation is worse for medicinal plant species that have perennial growth habits and are adapted to specific niches based on their climatic requirements. On account of overexploitation of their natural populations in the wild, such medicinal plants are now under the category of threatened species. Picrorhiza kurroa, Podophyllum hexandrum, Trillium govanianum, Fritillaria roylei, and Valeriana jatamansi are glaring examples of such species that are harvested from the wild in the Himalayas. The establishment of gene banks can achieve sustenance of these economically important medicinal plants and bring these species out of the threatened category. The strategy requires the collection of germplasm resources from diverse locations; the organization and establishment of germplasm accessions in the field; the characterization of germplasm resources on a morphological, biochemical, and molecular basis; the establishment of a seed-to-seed cycle of the respective species; the generation of genetic variations crucial for the fitness of the population; germplasm appraisal for identifying superior plant types; and the standardization of propagation techniques for the reintroduction of species in their niche environments. Field gene banks are active germplasm sites and contribute significantly to the sustainable utilization of valuable but threatened plant species for future improvement. The evaluation of germplasm resources in the gene banks over the years has led to the identification of sources of resistance to insect pests and diseases, tolerance to abiotic stresses, and the identification of yield-contributing traits among different accessions in the gene bank. In this regard, our group is actively involved in the collection of different accessions of threatened medicinal plant species of Picrorhiza kurroa, Podophyllum hexandrum, Trillium govanianum, Fritillaria roylei, and Valeriana jatamansi from different locations in the wild. These are being established in field gene banks at the Centre for High Altitude Biology (CeHAB), Ribling, Lahaul, and Spiti (H.P.), India. To date, 701 accessions of 48 populations representing a wider geographical distribution of rare endangered and threatened species have been included in the gene bank (Anonymous, 2018). To restrict the collection of threatened plants from the wild, one target is to bring these species under captive cultivation. Therefore, our group targeted the endangered medicinal plants P. kurroa, P. hexandrum, T. govanianum, and F. roylei for

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captive cultivation under the CSIR phytopharma mission (CSIR, India). Farmers were encouraged to cultivate these medicinal plants along with other agriculture crops in their fields through awareness programs. Planting materials were supplied to farmers and farmers’ groups and a buyback mechanism was ensured at reasonable prices. Mass multiplication protocols of the selected plants were developed and nurseries were raised for captive cultivation. With the advent of plant breeding from selections to hybridization and molecular breeding, focus is required for varietal improvement programs of medicinal plants through: l

l

l

l

l

l

Selection parameters for quick screening at the nursery stages for various biotic and abiotic stresses to accelerate breeding programs. Germplasm appraisal for identifying sources of resistance to diseases and insect pests, tolerance to abiotic stresses, and the identification of yield-contributing traits. Information regarding the pollination behavior of the species will help in understanding the genetic basis of inheritance of different traits in medicinal plants. Parameters defining the plant ideotype with the increased harvest index of medicinal plants are required to maximize yields. Chemical quality parameters based on the availability of bioactive compounds need to be defined to meet the demands of the industry. DNA-based markers associated with the traits of interest, such as EST-SSR and SNP (single nucleotide polymorphism) need to be developed and utilized to develop high-density genetic linkage maps to analyze important QTLs and facilitate marker-assisted selection in medicinal plant species.

2.9 Metabolic engineering for modulating primary and secondary metabolisms A high altitude (HA) environment is characterized by extremes of variables such as large diurnal fluctuations of temperature, high wind velocity, high irradiance, reduced partial pressure of gases, limited nutrient and water supply (physiological drought due to low temperatures), etc. Therefore, a study of the adaptive plasticity and survival strategies in plants growing in extreme HA environments is drawing considerable attention. In addition to the effect on the primary metabolism, the extreme HA environment is likely to influence the secondary metabolism in plants and hence the production of bioactive molecules. Bioprospection of novel genes/enzymes and transcriptome studies vis-a`-vis secondary metabolite production could possibly reveal the mechanistic and regulation of the secondary metabolism in plants. The information not only identifies the factors limiting the synthesis of bioactive molecules, but also assists in the design and optimization of the processes for synthesizing these compounds in a suitable heterologous system. Secondary products in plants are synthesized from primary products of photosynthesis through divergent pathways. Therefore, it is quite reasonable to compare the photosynthetic capabilities of plants growing at high and low altitude (LA). In a radiotracer study, the primary products of photosynthesis were compared in barley and wheat growing at HA and LA. Significantly higher carboxylase and oxygenase activities of rubisco, phosphoenolpyruvate carboxylase (PEPCase), aspartate aminotransferase (AspAT), and glutamine synthetase (GS) were recorded at HA (Kumar et al., 2006). Data showed that carbon (C) skeletons produced in a PEPCase-catalyzed reaction could be utilized for nitrogen (N) assimilation through the joint activity of AspAT and GS. This photosynthetic shift tends to conserve C and N in HA-grown plants. The translation of this novel C sequestration pathway through heterologous coexpression of PEPCase, AspAT, and GS resulted in improved shoot biomass and seed yield as well as a higher capacity to reassimilate photorespired CO2 and NH3 in transgenic Arabidopsis thaliana (Kaachra et al., 2018). Changes in metabolite flux and/or gene expression cause alterations in the primary metabolism, which in turn impacts the secondary metabolism. The installation of this novel C sequestration pathway is expected to modulate the production of bioactive molecules in the target plant species growing at HA. Plants at higher altitude are exposed to high photon flux densities (PFDs) at low or high temperatures and are hence more prone to photodamage (Berry and Bjorkman, 1980). In addition, both high and low temperatures accelerate the formation of reactive oxygen species (ROS) and this leads to cellular damage and blocks the repair process (Wise, 1995; Apel and Hirt, 2004; Murata et al., 2007). To avoid such damage, most HA ecotypes produce more antioxidants than those that grow at LA. In this regard, a novel superoxide dismutase (PotSOD), the first of the ROS scavenging enzymes, was obtained from Potentilla atrosanguinea. The enzyme was found to function at 121 °C to subzero temperatures (Kumar et al., 2002; Vyas and Kumar, 2005a,b). However, even this thermostable PotSOD lost activity when exposed to higher temperatures for longer periods, thereby necessitating enzyme engineering for enhanced thermostability. A total of seven different mutants of PotSOD were created by amino acid substitution at targeted positions. Of these mutations, the replacement of Cys-95 by

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Ala enhanced the thermostability two-fold as compared to the native PotSOD enzyme. The engineered enzyme was a kinetically stable protein that was functional at subzero temperatures to >50 °C and also tolerated autoclaving (Kumar et al., 2012). The engineered PotSOD has industrial relevance and can be used for developing abiotic stress (high temperature and drought) tolerant transgenic plants. Transcript and transcriptome analyses of plant species growing at HA vis-a`-vis secondary metabolite biosynthesis are effective strategies to identify the gene and gene suites involved in the production of bioactive molecules. One such work was carried out for a HA plant, Picrorhiza kurrooa Royle ex Benth, a small, perennial herb well known for its hepatoprotective properties. The presence of picrosides, which are iridoid glycosides, is responsible for the hepatoprotective role of P. kurrooa. The iridane skeleton of monoterpene that originates in the iridoid moiety is synthesized by the mevalonate (MVA) as well as 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways. The plant also used the phenylpropanoid pathway for picroside biosynthesis. However, to understand the effect of temperature on the picroside biosynthetic pathway, highthroughput de novo transcriptome sequencing and analyses of P. kurroa plants at high temperature (25 °C) and low temperature (15 °C) were carried out (Gahlan et al., 2012). Data showed intense transcriptome adjustment in response to temperature. There was overexpression of monooxygenase activity, 2-iron, 2-sulfur cluster binding, cobalamin binding, aminobutyraldehyde dehydrogenase activity, purine transmembrane transporter activity, and copper-binding activities at 15 °C. Exclusive representation of transcripts associated with the response to heat, biotic stimulus, and lipid catabolic process was recorded at 25 °C. Transcripts for redox, glycogen biosynthetic process, biosynthetic processes, and proteinchromophore linkage were exclusively represented at 15 °C while transcripts for response to stress, response to stimulus, the phytosteroid metabolic process, and the brassinosteroid metabolic process were upregulated at 25 °C but the upregulation of various pathway genes was recorded at 15 °C. High temperature stress appeared to impose a penalty on the accumulation of picrosides in the plant. In yet another study, transcriptome analysis was carried out for the rhizome tissue of Sinopodophyllum hexandrum at 15 °C and 25 °C. S hexandrum is an endangered medicinal herb valued for its bioactive constituent, podophyllotoxin. Transcriptome data revealed the temperature-mediated molecular responses, including those associated with podophyllotoxin biosynthesis. At 15 °C, there was representation of transcripts for growth, development, and podophyllotoxin biosynthesis, but at 25 °C, stress-responsive transcripts were prevalent. Potential candidate podophyllotoxin biosynthesis pathway genes were identified through in-depth analyses of CYP, MT, and UGT genes (Kumari et al., 2014). Besides these two species, the secondary metabolite pathway genes of other plant species growing in the upper reaches of the Himalayan region were also cloned and analyzed. The work laid the foundation to understand the molecular basis of shikonin production in Arnebia euchroma (Royle) (Singh et al., 2010) and steviol glycoside biosynthesis in Stevia rebaudiana (Kumar et al., 2012b). Although advances in the fields of molecular biology and sequencing technologies have identified and characterized key role players in the biosynthesis of bioactive molecules, a few critical questions still remain unanswered. For example, the partitioning of the primary metabolism for the secondary metabolism in response to environmental cues is not clearly understood as yet. Also, there is a need to understand different variables influencing the rate flux along with diverse feedback and regulatory interactions operating between different metabolic pathways. Nevertheless, the integration of stimulation modeling, genomics, proteomics, metabolomics, and synthetic biology holds promise to further unravel the complexities of metabolic pathways and the translation of the same into a suitable system for socioeconomic benefit.

2.10 Technological advancements Recent technological developments in the fields of imaging and automation have added new dimensions to research on the conservation and improvement of global plant genetic resources. High-throughput techniques are advancing rapidly in the domains of next-generation sequencing, gene editing, and plant phenomics. In this regard, advanced detectors with high-resolution imaging capabilities are finding applications in crops as well as improved species discrimination, stage detection in plant growth cycle (e.g., predicting the leaf primordia of potato tubers, Rady et al., 2018), and tracing plant disease symptoms (Behmann et al., 2018), species diversity, and forest health ( Jha et al., 2019). Similarly, the integration of hyperspectral and LiDAR data is being utilized for the classification of tree species and also the delineation of individual tree crowns (Dalponte et al., 2019). Advanced CMOS detectors with better imaging capabilities on proposed future Sentinel satellite missions are expected to replace the presently employed CCDs (having limitations in resolution) onboard satellites. Hyperspectral remote sensing is envisaged to discriminate many commercially important alpine medicinal plant species growing in the pristine environment of the Himalaya. Moreover, current technologies involving fluorescence and Raman spectroscopy can functionally increase the hyperspectral remote sensing spectral range and will therefore add new dimensions in plant discrimination and crop vigor assessments under field conditions. The feasibility of satellite-based hyperspectral TIR missions with applications in areas such as species and crop

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discrimination is also expected to enable the analysis of dynamic processes in heterogeneous landscapes, soil composition and dynamics, vegetation state (Udelhoven et al., 2017), biochemical traits (Qi et al., 2018), etc. Advances in imaging technologies have resulted in the development of high-throughput field phenomics, and are now essential components of crop genetic improvement programs. The identification of traits predicting heat and drought tolerance is now possible through advanced infrared hyperspectral imaging, and this has important applications in crop phenomics (Chen et al., 2019). UAV-based thermal imaging for high-throughput field phenotyping of black poplar response to drought (Ludovisi et al., 2017) and mobile high-throughput field phenotyping for bunch detection and counting in grapevines (Milella et al., 2019) utilize the latest imaging technologies and have greater and more precise automation. Such highthroughput automation has also found applications in plant tissue culture for scaling up the in vitro propagation of plants. Automated scale up and commercial plant production of somatic embryos of conifers (Egertsdotter et al., 2019) and a novel automated transplanting system are some examples of advancements in plant tissue culture (Lee et al., 2019). The current advances in biotechnology also relate to gene editing, which has the potential for high-efficiency genome engineering across crop plants. With these technologies, it is now possible to discover novel traits and expedite the development of desired traits in target crops as a major step toward global food security (Haque et al., 2018; Sadeek et al., 2019). Tailor-made plants expressing any desirable trait have been made possible by advanced genome editing technologies such as zinc finger nucleases (ZFNs) and transcription activator-such as effector nucleases (TALENs). However, these technologies are expensive, time-consuming, and complex. In contrast, the precise targeting of genes by the clustered regularly interspaced short palindromic repeat (CRISPR) and the associated 9 (Cas9) is a simpler and time-effective method of genome editing (Karkute et al., 2017; Jaganathan et al., 2018). The CRISPR/Cas9 technology has the potential to circumvent the problems associated with transgenic technology without compromising on any of the desired traits. The CRISPR/Cas9 module is comprised of a nonspecific Cas9 nuclease and a guide RNA. The guide RNA guides the Cas9 to specific locations in the genome of the target plant to create double-strand breaks. These breaks are then subsequently repaired though mutations involving either insertion or deletion. Because a major drawback of this technology is off-site targeting by the guide RNA, several new Cas9 cassettes such as Nmcas9, Sacas9, and Stcas9 have been recently developed for improved target specificity and reduced cleavage at off-site targets. The specificity and efficiency of the method have also been increased by the use of Cas9 enzymes of bacterial origin. The technology has already started yielding results in some horticultural, ornamental, and medicinal plants. For example, CRISPR/Cas9 technology was used to manipulate the biosynthetic pathways of the insecticidal compounds present in CpYGFP-gene-expressing, transgenic Chrysanthemum morifolium with an aim to obtain novel, broad spectrum, and more efficient insecticides because this ornamental plant is also an important source of insecticides (Kishi-Kaboshi et al., 2017). The genome of the medicinal plant Salvia miltiorrhiza was also edited through CRISPR/Cas9. In the study, the diterpene synthase gene (SmCPS1) involved in tanshinone biosynthesis was knocked out, and plants lacking tanshinones were successfully developed (Li et al., 2017). The studies laid the path for genome editing for the improved biosynthesis of secondary metabolites (Xiong et al., 2015). Unlike the time-consuming transgenic technology where monogenic traits are generally targeted and stacked through gene pyramiding, CRISPR/Cas9 can target multiple genes in a plant genome. CRISPR/Cas9 facilitates a time-effective editing of polygenic traits. Therefore, it can be effectively used to engineer metabolites in various medicinal plants of the Himalayan flora. However, information on whole genome and/or transcriptome sequences coupled with the availability of efficient transformation and regeneration systems are the major requirements of CRISPR/Cas9. The technology holds tremendous promise, yet specific guidelines governing the development and use of genetically edited crops are a major requirement that needs to resolved by the governments of different countries. Thus, recent technological developments in high-throughput NGS and other molecular biology technologies have provided greater opportunities to identify and characterize a large number of genes involved in important metabolite pathways. However, linking genotype to phenotype, predicting gene regulations, and ascertaining mutations require the utilization of vast genomic information and encompass the incorporation of intraspecific and environmental variability. The analyses of such information can lead to new insights of the functioning of a genome. However, working with these enormously huge datasets is challenging, and new and efficient approaches for data analysis are required. Big data analytics in genomics is an emerging research area with the development of fast and sophisticated analysis algorithms. Such algorithms include machine learning, where data analytical techniques are applied to multidimensional datasets for predictive modeling to understand the whole genome or for gene editing. Further, “deep learning,” an automated procedure that is a variant of machine learning algorithms, uses neural networks to extract novel features from the generated datasets. It is fast emerging as a potential tool for the study of genomics, image processing, and phenomics.

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3 Conclusion In conclusion, an integrated approach including conventional as well as emerging technologies should be the present path for the effective conservation of Himalayan plant genetic resources. The latest ecological analysis methods coupled with whole genome and transcriptome sequencing, metabolic engineering, artificial intelligence, and big data analytics should become an integral part of programs for the conservation and genetic improvement of the Himalayan plant wealth for future generations. Further, increased interdisciplinary collaboration and an interinstitutional focus for a concerted effort to this effect is urgently required.

Acknowledgment The financial support provided by the Council of Scientific and Industrial Research, New Delhi, concerning the Phytopharmaceutical, Aroma, and Nutraceutical Mission and the Agri Nutri Biotech theme and the Department of Biotechnology, Government of India, are acknowledged.

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Chapter 19

Molecular markers as tools to improve date palms Pushpa Kharb and Rakshita Singh Department of Molecular Biology, Biotechnology and Bioinformatics, College of Basic Sciences and Humanities, CCS Haryana Agricultural University, Hisar, Haryana, India

1 Introduction The date palm (Phoenix dactylifera L.) is a monocotyledonous woody, dioecious evergreen perennial plant (2n ¼ 36) belonging to the family Palmae (Arecaceae). It has the distinction of being one of the oldest fruit trees in the world (Zehdi et al., 2004a,b). It is native to Southern Iraq. It is a palm with a slender trunk, 70–100 ft in height. The trunk, strongly marked with the pruned stubs of old leaf bases, ends in a crown of long, graceful, and shining pinnate leaves. Flower buds develop during the winter in the axils of the leaves, just below the growing point, enveloped in a sheath or spathe that pushes through the fiber on the leaf base. The male inflorescence is crowded at the end of the rachis while branches of the inflorescence of the female cluster are less densely crowded at the end of the rachis. It is the major fruit crop of arid climate regions, cultivated mainly in North Africa, South Asia, the United States, and Australia. It needs less water than most other fruit crops and can tolerate a high salinity level up to 22,000 ppm. Wild date palms are seen growing even up to an altitude of 1500 m. Deep sandy loam soil is ideal for its growth. It grows best in a temperature of 25°C but survives well in a wide range of temperatures from 8°C to 50°C. It covers a surface area of about 800,000 ha and is important directly or indirectly for the life of about 100 million inhabitants of the world (Akkak et al., 2003). In India, nearly 0.3 million ha of land can be effectively utilized for its cultivation. Long dry summers and sufficient heat unit accumulation for the development and ripening of the fruit, sufficient water resources for irrigation, and production technology suitable for the Indian agro-climatic conditions make India quite suitable for its commercial cultivation. The extremely dry areas comprising Jaisalmer, Barmer, and the western parts of the Bikaner and Jodhpur districts are the potential regions for its cultivation, where enough heat summation units are available and precipitation is also minimal. It is an important plantation crop due to the nutritional qualities of the fruit. The female plants bear the fruits, which are highly nutritious and eaten fresh or dried. The fruit is rich in sugar, iron, potassium, calcium, and nicotinic acid. One kg of fully ripe fresh dates provides approximately 3150 cal. Thus, the date fruit can help supplement the dietary needs of desert people, where very few nutritive foods are available. The sap of the tree has been a source of intoxicating drink for Arabs, who call it the drink of life because it prevents them from cancer and heart diseases. Dates can also be dehydrated, ground, and mixed with grain to form a nutritious stock feed. In India, North Africa, and Ghana, the date palm is tapped for the sweet sap, which is converted into palm sugar (known as jaggery or gur), molasses, and alcoholic beverages. Date seeds are soaked and ground up for animal feed. In addition, all the parts of the tree yield products of economic value, being used variously for timber, furniture, basketry, fuel, rope, and packing materials. Its wood is used in paper making. More than 1000 varieties of dates are known to exist. However, only a few of them are commercially cultivated in different countries. Hillawi, Khadrawy, Sayer, Shamran, Medjool, Zaidi, Barhee, Khalas, Khunezi, Zaglool, Begam Jangi, etc., are some of the commercially cultivated varieties grown in different parts of the world. Biotechnology and genetic engineering hold great potential for plant breeding. During the past few years, new strategies based on marker-assisted selection have been proposed to reduce time and effort. Genetic markers are suitable entities that are associated with economically important traits and have been used by plant breeders as selection tools (Beckman and Soller, 1983; Paterson et al., 1991; Darvasi and Soller, 1994). The study of genetic diversity is thus a prerequisite in any breeding program for the selection of suitably diverse parents to obtain heterotic hybrids. During the last two decades, rapid progress has been made toward the development and application of molecular marker technology in plant genome analysis. Molecular markers are considered the best tools for the analysis of genetic diversity and cultivar identification. They are

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indifferent to the developmental stage or environment. Molecular marker analysis has been widely used for varietal identification. However, to obtain the fingerprints of closely related varieties or to have some characteristic differences, it is essential to obtain a very high level of polymorphism. So, it has become necessary to establish a common basis for assessing the relative effectiveness of the various marker systems currently available for identification and discrimination between different date palm varieties. Date palms can be propagated by seeds or by offshoots that arise chiefly near the base of the stem in the early years of the palm’s life. But the few off-shoots produced by individual trees limit the traditional propagation of this species. When grown from seeds, only about half the trees turn out to be females. Female plants start producing edible dates after 5 years and reach full production after 10–12 years. Due to the slow growing nature of the species, it is difficult to determine the sex of the tree before the first flowering, when they are about 5 years of age. The superfluous male plants are not only unproductive but also suppress the development of adjacent female plants and have to be uprooted. This major problem for farmers does not allow them to cultivate a sufficiently large number of productive female plants with only a minimal number of male plants, as one male is sufficient to pollinate 50 female plants when grown together. The development of a robust DNA marker system for sex identification at an early stage in the date palm can greatly facilitate the breeder/farmer in avoiding the 5-year cost of growing and maintaining more male plants than required.

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Role of molecular markers in the assessment of genetic diversity

Molecular marker technology offers a wide range of novel approaches to improve the efficiency of selection strategies and plant breeding. The technique exploits the fact that the marker locus identifies a chromosomal segment and enables that segment to be monitored in subsequent generations of selfing or crossing. They have advantages over traditional phenotypic markers because they are phenotypically neutral as alternate alleles at the molecular loci and cause no obvious changes in the phenotypic expression (Tanksley, 1983). Molecular markers are widely used for tagging economically important traits/ loci, genome analysis, genetic map construction, fingerprinting analysis, germplasm organization, and sex determination in dioecious plant species. Molecular markers can be broadly divided into two categories: (i) Protein markers (ii) DNA markers Although protein markers have been useful both in breeding practice (Ainsworth and Gale, 1981) and for the further development of marker-aided selection technology (Stauber et al., 1987), they have several general drawbacks such as expression on environmental conditions, the organ-specific presence of an isozyme, and the often-limited amount of detectable polymorphism, which often restrict their utility.

3

DNA markers

The assessment of polymorphism in a crop species is fundamental to its improvement and polymorphism in a nucleotide sequence is sufficient for it. These genetic variations are the results of the deletion or insertion of mutations and occur on an average once every 300–500 bp. Several kinds of molecular markers are available such as amplified fragment length polymorphism (AFLP), amplicon length polymorphism (ALP), arbitrarily primed PCR (AP-PCR), allele specific PCR (ASPCR), DNA amplification fingerprinting (DAF), random amplified polymorphic DNA (RAPD), restriction fragment length polymorphism (RFLP), specific amplicon polymorphism (SAP), sequence characterized amplified region (SCAR), singlestrand conformation polymorphism (SSCP), simple sequence length polymorphism (SSP), simple sequence repeat (SSR), sequence tagged sites (STS), etc. These DNA markers can be broadly classified into three groups: 1. Hybridization-based DNA markers such as RFLPs and oligonucleotide fingerprinting. 2. PCR-based DNA markers such as RAPDs, SSRs, STS, AFLP, ISSRs, SCAR, etc. 3. DNA chip and sequencing-based DNA markers such as single nucleotide polymorphism (SNPs). Studies on the use of these markers in date-palm crop improvement are given below:

3.1 Restriction fragment length polymorphism (RFLP) The relative ease with which DNA molecules can currently be cloned along with the availability of a wide range of restriction endonucleases have allowed the assay of a much greater length of the plant genome for genetic markers. DNA samples that differ from one another in base sequence or have been rearranged by insertions, deletions, or inversions

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produce restriction fragments of different sizes on enzyme digestion, and have therefore been termed “restriction fragment length polymorphism” (RFLP) (Grodzicker et al., 1974; Bostein et al., 1980). RFLP requires both large amounts of DNA and the isolation of informative probes that yield differences between the sources of DNA. The most frequent sources of probes for RFLP analysis include cDNA clones and microsatellites. The use of RFLP in the traditional form of hybridization of labeled probes to filter-bound DNA has been replaced by PCR-based techniques. Cornicquel and Mercier (1994) performed RFLP analysis of five elite cultivars of the date palm (cvs. Barhee, Deglet Nour, Khalassa, Khadrawy, and Medjool) using offshoot leaves surrounding the shoot tips used to initiate tissue culture. Total DNA digested by EcoR1 was hybridized with cDNA probes randomly selected from a cDNA library constructed from the highly organogenic calli of cv. Boustammi Noire, and with a heterologous 1.7 kb nuclear rDNA fragment amplified during the polymerase chain reaction (PCR) of jojoba genomic DNA. Discrimination among the fire cultivars was easily made with cDNA probe 1, which was highly polymorphic.

3.2 Amplified fragment length polymorphism (AFLP) The AFLP technique is based on the selective amplification of restriction fragments from a total restriction digest of genomic DNA (Vos et al., 1995). It is a combination of the characteristics of RFLP and RAPD techniques and generates a large number of bands that serve as the markers for fingerprint and trait analysis. Diaz et al. (2003) identified three date palm cultivars grown at Elche in Spain on the basis of AFLP using the Dice coefficient calculated from a similarity matrix. Five date palm cultivars from Egypt were characterized using AFLP (El-Khishin et al., 2003). An average of 72.17 amplicons per assay was observed and the total number of unique markers per cultivar varied between 13 and 51, indicating the molecular diversity. AFLPs have been used for cultivar identification in many crop species. El-Assar et al. (2005) studied genetic diversity in Egyptian date palm accessions collected from eight locations using four sets of AFLP. A total of 350 bands were scored, out of which 233 (66.6%) were polymorphic. Twenty seven Egyptian accessions and Medjool and Deglet Noor accessions from California could be classified into major clusters that represent a major group of date palm germplasms in North Africa. Jubrael et al. (2005) estimated the genetic diversity and relationship among 18 Iraqi date palm varieties through AFLP markers. A total of 122 polymorphic AFLP loci were scored with an average of 17.4 polymorphic loci per primer combination. Saker et al. (2006) employed AFLP markers to assess genetic variations that appeared in tissue culture-derived date palm offshoots. An analysis of AFLP banding patterns generated using 13 primer combinations pointed to minor genetic variations in the AFLP banding patterns. The percentage of genetic variations (polymorphism) in tissue culture-derived date palm offshoots belonging to the cultivars Sakkoty, Gandila, and Bertamoda was very low, as revealed by AFLP analysis. The low percentage of genetic variations confirms the genetic stability of tissue culture-derived dry date palm cultivars. Based on offshoot identification, and to determine genetic diversity and phylogenetic relationships, Khierallah et al. (2011) used AFLP fingerprinting to evaluate 18 date palm varieties (11 females and 7 males) collected from the center of Iraq. The varieties were observed to cluster independently of their geographic origin and of their phenotypic characteristics.

3.3 Random amplified polymorphic DNA (RAPD) RAPD analysis, a PCR-based molecular marker technique, was developed initially by Welsh and McClelland (1994) and Williams et al. (1990). These DNA markers are the result of the PCR amplification of random genomic DNA segments with a single primer (usually 10 nucleotides long) of arbitrary sequence. Polymorphism results from mutations or rearrangements either at or between the primer binding sites and are most frequently detected as the presence or absence of amplification products, thus behaving as dominant markers (Staub et al., 1996). Al-Khalifah and Askari (2003) carried out RAPD analysis to determine genetic relationships and diversity among 13 different cultivars of the date palm. The screening of 140 RAPD primers allowed the selection of 37 primers that revealed polymorphism, and the results were reproducible. They reported that Om-Hamman and Bareem were the two most closely related cultivars among the 13 cultivars with the highest value in the similarity matrix for Neiand Li’s coefficient (0.89). The average similarity among the 13 cultivars was more than 50%. Adawy et al. (2004) attempted to determine a molecular fingerprint characterizing each Egyptian date palm cultivar using RAPD. Bulked DNA samples were composed of different trees representing each cultivar from the Upper Egypt region. DNA profiling of five Upper Egypt Cultivars (Bertmoda,

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Gandila, Malikaby, Shameia, and Sakkoty) was carried out using 41 RAPD primer combinations exhibiting 259 amplicons and 18.9% polymorphism. A dendrogram was developed and unique markers characterizing each cultivar were identified. Toor et al. (2005) assessed the genetic variation in 20 accessions of the date palm using RAPD markers. A total of 34 decamer primers selected for RAPD analysis generated 191 amplicons, out of which 159 (83.24%) were polymorphic. An RAPD banding pattern was used to construct genetic similarity, which ranged from 0.433 to 0.760, while the average genetic similarity was 61.8%. Singh et al. (2006) reported a very high polymorphism (87.19%) by the RAPD analysis of 10 male and 20 female genotypes (belonging to two varieties) of the date palm using 31 RAPD primers Singh et al. (2006) used 31 RAPD primers to study polymorphism among 30 date palm genotypes [10 male; M1–M10, 10 female plants each of Khadrawi (K1–K10) and Shamran (S1–S10) varieties]. Average polymorphism across the 30 genotypes was 87.19  2.92. Rani et al. (2007) assessed the genetic diversity among 40 date palm genotypes using 29 RAPD primers. Average polymorphism across all the 40 date palm genotypes was found to be 99.12  0.62. Three RAPD Primers—OPA-09, OPB-18, and OPO-06—produced one unique allele (900, 350, and 250 bp, respectively), each capable of differentiating Medjool variety female plants from the male (nondescriptive) and female plants of other varieties used. Mirbahar et al. (2014) used 6 RAPD markers to analyze the genetic diversity and phylogenetic relationship among 25 date palm cultivars from Pakistan. The RAPD primers showed polymorphism among all date palm cultivars. The bands obtained were successfully used to differentiate the genotypes. Based on the pairwise comparison of amplification products, the genetic relationship was estimated. All date palm cultivars showed variation at the DNA level. The average genetic diversity among the date palm cultivars was 79.4%. Al-Khalifah and Shanavaskhan (2017) reported the use of RAPD primers for genetic diversity analysis in the date palm.

3.4 Microsatellites Microsatellites are small arrays (typically