Description
In the rapidly evolving landscape of crop genetics, the book, Harnessing Genomic Tools for Crop Improvement is an essential resource designed for researchers, students, and professionals seeking to leverage bioinformatics tools for precision breeding. This comprehensive manual provides step-by-step guidance on utilizing molecular data derived from genetics and breeding experiments, offering hands-on instructions for key software applications in genetic diversity analysis, QTL mapping, genome-wide association mapping, haplotype analysis and genomic selection.Beyond technical tutorials, the book explores cutting-edge bioinformatics tools such as sequence databases, BLAST, primer designing, and sequence alignment, ensuring users gain a holistic understanding of genomics-driven crop improvement. Definitions, terminology clarifications, and interpretation of the results help bridge the gap between theory and application, simplifying complex analyses.Whether you are a novice or an experienced researcher, this book equips you with the skills to analyze and apply genomic data effectively, making it an invaluable asset for transforming geneticists into genomicists in both plant and animal sciences.- Covers major advanced genomic tools software- Provides a step-by-step guide to run each software- Explains the basic terminology and interpretation of the output of each software
Table of Contents
1. Basic bioinformatics software: Sequence retrieval and sequence submission2. SSR and SNP identification and marker development3. NGS analysis: Variant calling and genome assembly 4. Genetic diversity and population structure analysis—DARwin, MEGA, and STRUCTURE5. QTL Mapping—QTL IciMapping, Windows QTL Cartographer and Mapchart6. Genome-wide association mapping tools: TASSEL and GAPIT7. Statistical models for genomic selection: Practical implementation using R8. Haplotype analysis software: HAPLOTYPE ANALYSIS, DnaSP, Haploview, and PopART9. Analysis of transcription factor (TF)-target gene regulatory networks10. Transcriptome analysis: RT-PCR and RNA-seq analysis11. MiRNA structure and target prediction tools12. Designing of guide RNA for CRISPR gene editing: A web based foundational approach13. Protein interaction network analysis: STRING and CYTOSCAPE14. Navigating in silico drug discovery: A hands-on guide with autodock vina and discovery studio15. Machine learning techniques for gene prediction
