OMICS-Based Approaches in Plant Biotechnology
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portes grátis
OMICS-Based Approaches in Plant Biotechnology
Kumar, Garlapati Vijay; Banerjee, Rintu; Kumar, S.P. Jeevan
John Wiley & Sons Inc
03/2019
348
Dura
Inglês
9781119509936
15 a 20 dias
632
Descrição não disponível.
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-a-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
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-a-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
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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-a-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
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-a-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
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