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OMICS-Based Approaches in Plant Biotechnology

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OMICS-Based Approaches in Plant Biotechnology

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Burgeoning world population, decreased water supply and land resources, coupled with climate change, result in severe stress conditions and a great threat to the global food supply. To meet these challenges, exploring Omics Technologies could lead to improved yields of cereals, tubers and grasses that may ensure food security. Improvement of yields through crop improvement and biotechnological means are the need-of-the-hour, and the current book “OMICS-Based Approaches in Plant Biotechnology”, reviews the advanced concepts on breeding strategies, OMICS technologies (genomics, transcriptomics and metabolomics) and bioinformatics that help to glean the potential candidate genes/molecules to address unsolved problems related to plant and agricultural crops. The first six chapters of the book are focused on genomics and cover sequencing, functional genomics with examples on insecticide resistant genes, mutation breeding and miRNA technologies. Recent advances in metabolomics studies are elucidated in the next 3 chapters followed by 5 chapters on bioinformatics and advanced techniques in plant biotechnology and crop breeding. The information contained in the volume will help plant breeders, plant biotechnologists, plant biochemists, agriculture scientists and researchers in using this applied research to focus on better crop breeding and stress adaptation strategies.

Introduction xiii

Part 1: Genomics 1

1 Exploring Genomics Research in the Context of Some Underutilized Legumes—A Review 3
Patrush Lepcha, Pittala Ranjith Kumar and N. Sathyanarayana

1.1 Introduction 3

1.2 Velvet Bean [Mucuna pruriens (L.) DC. var. utilis (Wall. ex Wight)] Baker ex Burck 4

1.3 Psophocarpus tetragonolobus (L.) DC. 7

1.4 Vigna umbellata (Thunb.) Ohwiet. Ohashi 8

1.5 Lablab purpureus (L.) Sweet 9

1.6 Avenues for Future Research 10

1.7 Conclusions 12

Acknowledgments 12

References 12

2 Overview of Insecticidal Genes Used in Crop Improvement Program 19
Neeraj Kumar Dubey, Prashant Kumar Singh, Satyendra Kumar Yadav and Kunwar Deelip Singh

2.1 Introduction 19

2.2 Insect-Resistant Transgenic Model Plant 21

2.3 Insect-Resistant Transgenic Dicot Plants 27

2.4 Insect-Resistant Transgenic Monocot Plants 34

2.5 Working Principle of Insecticidal Genes Used in Transgenic Plant Preparation 39

2.6 Discussion 41

References 42

3 Advances in Crop Improvement: Use of miRNA Technologies for Crop Improvement 55
Clarissa Challam, N. Nandhakumar and Hemant Balasaheb Kardile

3.1 Introduction 56

3.2 Discovery of miRNAs 56

3.3 Evolution and Organization of Plant miRNAs 57

3.4 Identification of Plant miRNAs 58

3.5 miRNA vs. siRNA 59

3.6 Biogenesis of miRNAs and Their Regulatory Action in Plants 60

3.7 Application of miRNA for Crop Improvement 61

3.8 Concluding Remarks 62

References 70

4 Gene Discovery by Forward Genetic Approach in the Era of High-Throughput Sequencing 75
Vivek Thakur and Samart Wanchana

4.1 Introduction 75

4.2 Mutagens Differ for Type and Density of Induced Mutations 76

4.3 High-Throughput Sequencing is Getting Better and Cheaper 77

4.4 Mapping-by-Sequencing 77

4.5 Different Mapping Populations for Specific Need 81

4.6 Effect of Mutagen Type on Mapping 83

4.7 Effect of Bulk Size and Sequencing Coverage on Mapping 83

4.8 Challenges in Variant Calling 85

4.9 Cases Where Genome Sequence is either Unavailable or Highly Diverged 85

4.10 Bioinformatics Tools for Mapping-by-Sequencing Analysis 86

Acknowledgments 87

References 87

5 Functional Genomics of Thermotolerant Plants 91
Nagendra Nath Das

5.1 Introduction 91

5.2 Functional Genomics in Plants 93

5.3 Thermotolerant Plants 94

5.4 Studies on Functional Genomics of Thermotolerant Plants 98

5.5 Concluding Remarks 99

Abbreviations 100

References 100

Part 2: Metabolomics 105

6 A Workflow in Single Cell-Type Metabolomics: From Data Pre-Processing and Statistical Analysis to Biological Insights 107
Biswapriya B. Misra

6.1 Introduction 108

6.2 Methods and Data 109

6.2.1 Source of Data 109

6.2.2 Processing of Raw Mass Spectrometry Data 109

6.2.3 Statistical Analyses 109

6.2.4 Pathway Enrichment and Clustering Analysis 110

6.3 Results 110

6.3.1 Design of the Study and Data Analysis 110

6.3.2 The Guard Cell Metabolomics Dataset 110

6.3.3 Multivariate Analysis for Insights into Data Pre-Processing 113

6.3.4 Effect of Data Normalization Methods 119

6.4 Discussion 122

6.5 Conclusion 124

Conflicts of Interest 124

Acknowledgment 125

References 125

7 Metabolite Profiling and Metabolomics of Plant Systems Using 1H NMR and GC-MS 129
Manu Shree, Maneesh Lingwan and Shyam K. Masakapalli

7.1 Introduction 129

7.2 Materials and Methods 131

7.2.1 1H NMR-Based Metabolite Profiling of Plant Samples 132

7.2.1.1 Metabolite Extraction 132

7.2.1.2 1H NMR Spectroscopy 132

7.2.1.3 Qualitative and Quantitative Analysis of NMR Signals 134

7.2.2 Gas Chromatography–Mass Spectroscopy (GC-MS) Based Metabolite Profiling 134

7.2.2.1 Sample Preparation 134

7.2.2.2 GC-MS Data Acquisition 135

7.2.2.3 GC-MS Data Pretreatment and Metabolite Profiling 136

7.2.2.4 Validation of Identified Metabolites 136

7.2.3 Multivariate Data Analysis 137

7.3 Selected Applications of Metabolomics and Metabolite Profiling 139

Acknowledgments 140

Competing Interests 140

References 140

8 OMICS-Based Approaches for Elucidation of Picrosides Biosynthesis in Picrorhiza kurroa 145
Varun Kumar

8.1 Introduction 146

8.2 Cross-Talk of Picrosides Biosynthesis Among Different Tissues of P. kurroa 148

8.3 Strategies Used for the Elucidation of Picrosides Biosynthetic Route in P. kurroa 148

8.3.1 Retro-Biosynthetic Approach 149

8.3.2 In Vitro Feeding of Different Precursors and Inhibitors 149

8.3.3 Metabolomics of Natural Variant Chemotypes of P. kurroa 150

8.4 Strategies Used for Shortlisting Key/Candidate Genes Involved in Picrosides Biosynthesis 151

8.4.1 Comparative Genomics 151

8.4.2 Differential Next-Generation Sequencing (NGS) Transcriptomes and Expression Levels of Pathway Genes Vis-à-Vis Picrosides Content 152

8.5 Complete Architecture of Picrosides Biosynthetic Pathway 153

8.6 Challenges and Future Perspectives 161

Abbreviations 162

References 163

9 Relevance of Poly-Omics in System Biology Studies of Industrial Crops 167
Nagendra Nath Das

9.1 Introduction 167

9.2 System Biology of Crops 169

9.3 Industrial Crops 171

9.4 Poly-Omics Application in System Biology Studies of Industrial Crops 176

9.5 Concluding Remarks 177

Abbreviations 177

References 178

Part 3: Bioinformatics 183

10 Emerging Advances in Computational Omics Tools for Systems Analysis of Gramineae Family Grass Species and Their Abiotic Stress Responsive Functions 185
Pandiyan Muthuramalingam, Rajendran Jeyasri, Dhamodharan Kalaiyarasi, Subramani Pandian, Subramanian Radhesh Krishnan, Lakkakula Satish, Shunmugiah Karutha Pandian and Manikandan Ramesh

10.1 Introduction 186

10.2 Gramineae Family Grass Species 187

10.2.1 Oryza sativa 187

10.2.2 Setaria italica 187

10.2.3 Sorghum bicolor 188

10.2.4 Zea mays 188

10.3 Abiotic Stress 188

10.4 Emerging Sequencing Technologies 198

10.4.1 NGS-Based Genomic and RNA Sequencing 199

10.4.2 Tanscriptome Analysis Based on NGS 200

10.4.3 High-Throughput Omics Layers 201

10.5 Omics Resource in Poaceae Species 202

10.6 Role of Functional Omics in Dissecting the Stress Physiology of Gramineae Members 203

10.7 Systems Analysis in Gramineae Plant Species 204

10.8 Nutritional Omics of Gramineae Species 205

10.9 Future Prospects 205

10.10 Conclusion 206

Acknowledgments 207

References 207

11 OMIC Technologies in Bioethanol Production: An Indian Context 217
Pulkit A. Srivastava and Ragothaman M. Yennamalli

11.1 Introduction 217

11.2 Indian Scenario 219

11.3 Cellulolytic Enzymes Producing Bacterial Strains Isolated from India 220

11.3.1 Bacillus Genus of Lignocellulolytic Degrading Enzymes 222

11.3.2 Bhargavaea cecembensis 222

11.3.3 Streptomyces Genus for Hydrolytic Enzymes 230

11.4 Biomass Sources Native to India 230

11.4.1 Albizia lucida (Moj) 230

11.4.2 Areca catechu (Betel Nut) 231

11.4.3 Arundo donax (Giant Reed) 231

11.4.4 Pennisetum purpureum (Napier Grass) 231

11.4.5 Brassica Family of Biomass Crops 231

11.4.6 Cajanus cajan (Pigeon Pea)/Cenchrus americanus (Pearl Millet)/Corchorus capsularis (Jute)/

Lens culinaris (Lentil)/Saccharum officinarum (Sugarcane)/Triticum sp. (Wheat)/Zea mays (Maize) 232

11.4.7 Medicago sativa (Alfalfa) 232

11.4.8 Manihot esculenta (Cassava)/Salix viminalis (Basket Willow)/Setaria italica (Foxtail Millet)/ Setaria viridis (Green Foxtail) 232

11.4.9 Vetiveria zizanioides (Vetiver or Khas) 232

11.4.10 Millets and Sorghum bicolor (Sorghum) 233

11.5 Omics Data and Its Application to Bioethanol Production 233

11.6 Conclusion 239

References 239

Part 4: Advances in Crop Improvement: Emerging Technologies 245

12 Genome Editing: New Breeding Technologies in Plants 247
Kalyani M. Barbadikar, Supriya B. Aglawe, Satendra K. Mangrauthia, M. Sheshu Madhav and S.P. Jeevan Kumar

12.1 Introduction: Genome Editing 248

12.2 GE: The Basics 249

12.2.1 Nonhomologous End-Joining (NHEJ) 250

12.2.2 Homology Directed Repair (HR) 251

12.3 Engineered Nucleases: The Key Players in GE 251

12.3.1 Meganucleases 251

12.3.2 Zinc-Finger Nucleases 256

12.3.3 Transcription Activator-Like Effector Nucleases 257

12.3.4 CRISPR/Cas System: The Forerunner 258

12.4 Targeted Mutations and Practical Considerations 259

12.4.1 Targeted Mutations 259

12.4.2 Steps Involved 260

12.4.2.1 Selection of Target Sequence 261

12.4.2.2 Designing Nucleases 262

12.4.2.3 Transformation 263

12.4.2.4 Screening for Mutation 264

12.5 New Era: CRISPR/Cas9 264

12.5.1 Vector Construction 264

12.5.2 Delivery Methods 266

12.5.3 CRISPR/Cas Variants 266

12.5.3.1 SpCas9 Nickases (nSpCas9) 266

12.5.3.2 Cas9 Variant without Endonuclease Activity 266

12.5.3.3 FokI Fused Catalytically Inactive Cas9 267

12.5.3.4 Naturally Available and Engineered Cas9 Variants with Altered PAM 268

12.5.3.5 Cas9 Variants for Increased On-Target Effect 268

12.5.3.6 CRISPR/Cpf1 268

12.6 GE for Improving Economic Traits 269

12.6.1 Development of Next-Generation Smart Climate Resilient Crops 271

12.6.2 Breaking Yield Incompatibility Barriers and Hybrid Breeding 271

12.6.3 Creating New Variation through Engineered QTLs 271

12.6.4 Transcriptional Regulation 272

12.6.5 GE for Noncoding RNA, microRNA 272

12.6.6 Epigenetic Modifications 273

12.6.7 Gene Dosage Effect 273

12.7 Biosafety of GE Plants 273

12.8 What’s Next: Prospects 276

References 276

13 Regulation of Gene Expression by Global Methylation Pattern in Plants Development 287
Vrijesh Kumar Yadav, Krishan Mohan Rai, Nishant Kumar and Vikash Kumar Yadav

13.1 Introduction 288

13.2 Nucleic Acid Methylation Targets in the Genome 289

13.3 Nucleic Acid Methyl Transferase (DNMtase) 290

13.4 Genomic DNA Methylation and Expression Pattern 291

13.5 Pattern of DNA Methylation in Early Plant Life 292

13.6 DNA Methylation Pattern in Mushroom 293

13.7 Methylation Pattern in Tumor 294

13.8 DNA Methylation Analysis Approaches 294

13.8.1 Locus-Specific DNA Methylation 295

13.8.2 Genome-Wide and Global DNA Methylation 295

13.8.3 Whole Genome Sequence Analysis by Bioinformatics Analysis 296

References 297

14 High-Throughput Phenotyping: Potential Tool for Genomics 303
Kalyani M. Barbadikar, Divya Balakrishnan, C. Gireesh, Hemant Kardile, Tejas C. Bosamia and Ankita Mishra

14.1 Introduction 304

14.2 Relation of Phenotype, Genotype, and Environment 304

14.3 Features of HTP 306

14.4 HTP Pipeline and Platforms 310

14.5 Controlled Environment-Based Phenotyping 311

14.6 Field-Based High-Throughput Plant Phenotyping (Fb-HTPP) 311

14.7 Applications of HTP 313

14.7.1 Marker-Assisted Selection and QTL Detection 314

14.7.2 Forward and Reverse Genetics 315

14.7.3 New Breeding Techniques 315

14.7.3.1 Envirotyping 315

14.8 Conclusion and Future Thrust 316

References 316

Index 323