ENGLISH

OMICS-Based Approached for Plant Biotechnology

Book information

Publisher
Incorporated, John Wiley & Sons
Year
2019
ISBN
9781119509981, 111950998X, 9781119509936
Language
english
Format
PDF
Filesize
4 MB (4166878 bytes)
Pages
346\346
Time added
2020-02-15 03:35:36

Description

Content: 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 Plants2.4 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 Sequencing4.1 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 6.3.1 Design of the Study and Data Analysis6.3.2 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

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