OMICS-Based Approaches in Plant Biotechnology

Name: OMICS-Based Approaches in Plant Biotechnology
Brand: Wiley-ISTE
Price: 190.99 EUR
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Rintu Banerjee Garlapati Vijay Kumar S. P. Jeevan Kumar(Herausgeber*in)

Wiley-ISTE (Verlag)

1. Auflage

Erschienen am 13. Februar 2019

348 Seiten

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Inhalt

Cover
Title Page
Copyright Page
Contents
Introduction
Part 1: Genomics
1 Exploring Genomics Research in the Context of Some Underutilized Legumes-A Review
1.1 Introduction
1.2 Velvet Bean [Mucuna pruriens (L.) DC. var. utilis (Wall. ex Wight)] Baker ex Burck
1.3 Psophocarpus tetragonolobus (L.) DC.
1.4 Vigna umbellata (Thunb.) Ohwiet. Ohashi
1.5 Lablab purpureus (L.) Sweet
1.6 Avenues for Future Research
1.7 Conclusions
Acknowledgments
References
2 Overview of Insecticidal Genes Used in Crop Improvement Program
2.1 Introduction
2.2 Insect-Resistant Transgenic Model Plant
2.3 Insect-Resistant Transgenic Dicot Plants
2.4 Insect-Resistant Transgenic Monocot Plants
2.5 Working Principle of Insecticidal Genes Used in Transgenic Plant Preparation
2.6 Discussion
References
3 Advances in Crop Improvement: Use of miRNA Technologies for Crop Improvement
3.1 Introduction
3.2 Discovery of miRNAs
3.3 Evolution and Organization of Plant miRNAs
3.4 Identification of Plant miRNAs
3.5 miRNA vs. siRNA
3.6 Biogenesis of miRNAs and Their Regulatory Action in Plants
3.7 Application of miRNA for Crop Improvement
3.8 Concluding Remarks
References
4 Gene Discovery by Forward Genetic Approach in the Era of High-Throughput Sequencing
4.1 Introduction
4.2 Mutagens Differ for Type and Density of Induced Mutations
4.3 High-Throughput Sequencing is Getting Better and Cheaper
4.4 Mapping-by-Sequencing
4.5 Different Mapping Populations for Specific Need
4.6 Effect of Mutagen Type on Mapping
4.7 Effect of Bulk Size and Sequencing Coverage on Mapping
4.8 Challenges in Variant Calling
4.9 Cases Where Genome Sequence is either Unavailable or Highly Diverged
4.10 Bioinformatics Tools for Mapping-by-Sequencing Analysis
Acknowledgments
References
5 Functional Genomics of Thermotolerant Plants
5.1 Introduction
5.2 Functional Genomics in Plants
5.3 Thermotolerant Plants
5.4 Studies on Functional Genomics of Thermotolerant Plants
5.5 Concluding Remarks
Abbreviations
References
Part 2: Metabolomics
6 A Workflow in Single Cell-Type Metabolomics: From Data Pre-Processing and Statistical Analysis to Biological Insights
6.1 Introduction
6.2 Methods and Data
6.2.1 Source of Data
6.2.2 Processing of Raw Mass Spectrometry Data
6.2.3 Statistical Analyses
6.2.4 Pathway Enrichment and Clustering Analysis
6.3 Results
6.3.1 Design of the Study and Data Analysis
6.3.2 The Guard Cell Metabolomics Dataset
6.3.3 Multivariate Analysis for Insights into Data Pre-Processing
6.3.4 Effect of Data Normalization Methods
6.4 Discussion
6.5 Conclusion
Conflicts of Interest
Acknowledgment
References
7 Metabolite Profiling and Metabolomics of Plant Systems Using 1H NMR and GC-MS
7.1 Introduction
7.2 Materials and Methods
7.2.1 1H NMR-Based Metabolite Profiling of Plant Samples
7.2.1.1 Metabolite Extraction
7.2.1.2 1H NMR Spectroscopy
7.2.1.3 Qualitative and Quantitative Analysis of NMR Signals
7.2.2 Gas Chromatography-Mass Spectroscopy (GC-MS) Based Metabolite Profiling
7.2.2.1 Sample Preparation
7.2.2.2 GC-MS Data Acquisition
7.2.2.3 GC-MS Data Pretreatment and Metabolite Profiling
7.2.2.4 Validation of Identified Metabolites
7.2.3 Multivariate Data Analysis
7.3 Selected Applications of Metabolomics and Metabolite Profiling
Acknowledgments
Competing Interests
References
8 OMICS-Based Approaches for Elucidation of Picrosides Biosynthesis in Picrorhiza kurroa
8.1 Introduction
8.2 Cross-Talk of Picrosides Biosynthesis Among Different Tissues of P. kurroa
8.3 Strategies Used for the Elucidation of Picrosides Biosynthetic Route in P. kurroa
8.3.1 Retro-Biosynthetic Approach
8.3.2 In Vitro Feeding of Different Precursors and Inhibitors
8.3.3 Metabolomics of Natural Variant Chemotypes of P. kurroa
8.4 Strategies Used for Shortlisting Key/Candidate Genes Involved in Picrosides Biosynthesis
8.4.1 Comparative Genomics
8.4.2 Differential Next-Generation Sequencing (NGS) Transcriptomes and Expression Levels of Pathway Genes Vis-à-Vis Picrosides Content
8.5 Complete Architecture of Picrosides Biosynthetic Pathway
8.6 Challenges and Future Perspectives
Abbreviations
References
9 Relevance of Poly-Omics in System Biology Studies of Industrial Crops
9.1 Introduction
9.2 System Biology of Crops
9.3 Industrial Crops
9.4 Poly-Omics Application in System Biology Studies of Industrial Crops
9.5 Concluding Remarks
Abbreviations
References
Part 3: Bioinformatics
10 Emerging Advances in Computational Omics Tools for Systems Analysis of Gramineae Family Grass Species and Their Abiotic Stress Responsive Functions
10.1 Introduction
10.2 Gramineae Family Grass Species
10.2.1 Oryza sativa
10.2.2 Setaria italica
10.2.3 Sorghum bicolor
10.2.4 Zea mays
10.3 Abiotic Stress
10.4 Emerging Sequencing Technologies
10.4.1 NGS-Based Genomic and RNA Sequencing
10.4.2 Tanscriptome Analysis Based on NGS
10.4.3 High-Throughput Omics Layers
10.5 Omics Resource in Poaceae Species
10.6 Role of Functional Omics in Dissecting the Stress Physiology of Gramineae Members
10.7 Systems Analysis in Gramineae Plant Species
10.8 Nutritional Omics of Gramineae Species
10.9 Future Prospects
10.10 Conclusion
Acknowledgments
References
11 OMIC Technologies in Bioethanol Production: An Indian Context
11.1 Introduction
11.2 Indian Scenario
11.3 Cellulolytic Enzymes Producing Bacterial Strains Isolated from India
11.3.1 Bacillus Genus of Lignocellulolytic Degrading Enzymes
11.3.2 Bhargavaea cecembensis
11.3.3 Streptomyces Genus for Hydrolytic Enzymes
11.4 Biomass Sources Native to India
11.4.1 Albizia lucida (Moj)
11.4.2 Areca catechu (Betel Nut)
11.4.3 Arundo donax (Giant Reed)
11.4.4 Pennisetum purpureum (Napier Grass)
11.4.5 Brassica Family of Biomass Crops
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)
11.4.7 Medicago sativa (Alfalfa)
11.4.8 Manihot esculenta (Cassava)/Salix viminalis (Basket Willow)/Setaria italica (Foxtail Millet)/ Setaria viridis (Green Foxtail)
11.4.9 Vetiveria zizanioides (Vetiver or Khas)
11.4.10 Millets and Sorghum bicolor (Sorghum)
11.5 Omics Data and Its Application to Bioethanol Production
11.6 Conclusion
References
Part 4: Advances in Crop Improvement: Emerging Technologies
12 Genome Editing: New Breeding Technologies in Plants
12.1 Introduction: Genome Editing
12.2 GE: The Basics
12.2.1 Nonhomologous End-Joining (NHEJ)
12.2.2 Homology Directed Repair (HR)
12.3 Engineered Nucleases: The Key Players in GE
12.3.1 Meganucleases
12.3.2 Zinc-Finger Nucleases
12.3.3 Transcription Activator-Like Effector Nucleases
12.3.4 CRISPR/Cas System: The Forerunner
12.4 Targeted Mutations and Practical Considerations
12.4.1 Targeted Mutations
12.4.2 Steps Involved
12.4.2.1 Selection of Target Sequence
12.4.2.2 Designing Nucleases
12.4.2.3 Transformation
12.4.2.4 Screening for Mutation
12.5 New Era: CRISPR/Cas9
12.5.1 Vector Construction
12.5.2 Delivery Methods
12.5.3 CRISPR/Cas Variants
12.5.3.1 SpCas9 Nickases (nSpCas9)
12.5.3.2 Cas9 Variant without Endonuclease Activity
12.5.3.3 FokI Fused Catalytically Inactive Cas9
12.5.3.4 Naturally Available and Engineered Cas9 Variants with Altered PAM
12.5.3.5 Cas9 Variants for Increased On-Target Effect
12.5.3.6 CRISPR/Cpf1
12.6 GE for Improving Economic Traits
12.6.1 Development of Next-Generation Smart Climate Resilient Crops
12.6.2 Breaking Yield Incompatibility Barriers and Hybrid Breeding
12.6.3 Creating New Variation through Engineered QTLs
12.6.4 Transcriptional Regulation
12.6.5 GE for Noncoding RNA, microRNA
12.6.6 Epigenetic Modifications
12.6.7 Gene Dosage Effect
12.7 Biosafety of GE Plants
12.8 What's Next: Prospects
References
13 Regulation of Gene Expression by Global Methylation Pattern in Plants Development
13.1 Introduction
13.2 Nucleic Acid Methylation Targets in the Genome
13.3 Nucleic Acid Methyl Transferase (DNMtase)
13.4 Genomic DNA Methylation and Expression Pattern
13.5 Pattern of DNA Methylation in Early Plant Life
13.6 DNA Methylation Pattern in Mushroom
13.7 Methylation Pattern in Tumor
13.8 DNA Methylation Analysis Approaches
13.8.1 Locus-Specific DNA Methylation
13.8.2 Genome-Wide and Global DNA Methylation
13.8.3 Whole Genome Sequence Analysis by Bioinformatics Analysis
References
14 High-Throughput Phenotyping: Potential Tool for Genomics
14.1 Introduction
14.2 Relation of Phenotype, Genotype, and Environment
14.3 Features of HTP
14.4 HTP Pipeline and Platforms
14.5 Controlled Environment-Based Phenotyping
14.6 Field-Based High-Throughput Plant Phenotyping (Fb-HTPP)
14.7 Applications of HTP
14.7.1 Marker-Assisted Selection and QTL Detection
14.7.2 Forward and Reverse Genetics
14.7.3 New Breeding Techniques
14.7.3.1 Envirotyping
14.8 Conclusion and Future Thrust
References
Index
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