Genome-Wide Association Studies

ISBN-13: 9781071622360 / Angielski / Twarda / 2022

Opis

This detailed collection explores genome-wide association studies (GWAS), which have revolutionized the investigation of complex traits over the past decade and have unveiled numerous useful genotype–phenotype associations in plants. The book describes the key concepts and methods underlying GWAS, including the genetic architecture underlying variation for phenotypic traits, the structure of genetic variation in plants, technologies for capturing genetic information, study designs, and the statistical models and bioinformatics tools used for data analysis. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of invaluable implementation advice that leads to the most fruitful research results. 

Authoritative and practical, Genome-Wide Association Studies serves as an extremely valuable resource for the plant research community by rendering GWAS analysis less challenging and more accessible to a broader group of users.

Spis treści

Part I: Reviews and Overviews

 

1. Designing a Genome-Wide Association Study: Main Steps and Critical Decisions

            François Belzile and Davoud Torkamaneh

 

2. Preparation and Curation of Phenotypic Datasets

            Santiago Alvarez Prado, Fernando Hernandez, Ana Laura Achilli, and Agustina Amelong

 

3. Genotyping Platforms for Genome-Wide Association Studies: Options and Practical Considerations

            David L. Hyten

 

4. Genome-Wide Association Study Statistical Models: A Review

            Mohsen Yoosefzadeh-Najafabadi, Milad Eskandari, Francois Belzile, and Davoud Torkamaneh

 

5. Interpretation of Manhattan Plots and Other Outputs of Genome-Wide Association Studies

            Jiabo Wang, Jianming Yu, Alexander E. Lipka, and Zhiwu Zhang

 

Part II: Phenotypic Data for GWAS

 

6. Preparation and Curation of Multi-Year, Multi-Location, Multi-Trait Datasets

            Amina Abed and Zakaria Kehel

 

7. Development, Preparation, and Curation of High-Throughput Phenotypic Data for Genome-Wide Association Studies: A Sample Pipeline in R

            Pasquale Tripodi

 

8. Preparation and Curation of Omics Data for Genome-Wide Association Studies

            Feng Zhu, Alisdair R. Fernie, and Federico Scossa

 

Part III: Genotypic Data and Assessment of Population Structure

 

9. Producing High-Quality Single Nucleotide Polymorphism Data for Genome-Wide Association Studies

            Philipp E. Bayer, Mitchell Gill, Monica F. Danilevicz, and David Edwards

 

10. A Practical Guide to Using Structural Variants for Genome-Wide Association Studies

            Marc-André Lemay and Sidiki Malle

 

11. Data Integration, Imputation, and Meta-Analysis for Genome-Wide Association Studies

            Reem Joukhadar and Hans D. Daetwyler

 

12. Population Structure and Relatedness for Genome-Wide Association Studies

            Sidiki Malle

 

Part IV: Bioinformatics Tools for GWAS

 

13. Performing Genome-Wide Association Studies with Multiple Models Using GAPIT

            Jiabo Wang, You Tang, and Zhiwu Zhang

 

14. Performing Genome-Wide Association Studies Using rMVP

            Xiaolei Liu, Lilin Yin, Haohao Zhang, Xinyun Li, and Shuhong Zhao

 

Part V: Identification of Candidate Genes and Validation

 

15. Identification and Validation of Candidate Genes from Genome-Wide Association Studies

            Elise Albert and Christopher Sauvage

 

16. Biparental Crossing and QTL Mapping for Genome-Wide Association Studies Validation

            Pawan L. Kulwal and Ravinder Singh

 

17. Development of Breeder Friendly KASP Markers from Genome-Wide Association Studies Results

            Manar Makhoul and Christian Obermeier

 

Part VI: Case Studies

 

18. Mapping Major Disease Resistance Genes in Soybean by Genome-Wide Association Studies

            Everton Geraldo Capote Ferreira and Francismar Côrrea Marcelino-Guimarães

 

19. GWAS Case Studies in Wheat

            Deepmala Sehgal and Susanne Dreisigacker

 

20. Plant Microbiome-Based Genome-Wide Association Studies

            Siwen Deng, Michael A. Meier, Daniel Caddell, Jinliang Yang, and Devin Coleman-Derr