Status and prospects of genome-wide association studies in plants
- PMID: 33442955
- DOI: 10.1002/tpg2.20077
Status and prospects of genome-wide association studies in plants
Abstract
Genome-wide association studies (GWAS) have developed into a powerful and ubiquitous tool for the investigation of complex traits. In large part, this was fueled by advances in genomic technology, enabling us to examine genome-wide genetic variants across diverse genetic materials. The development of the mixed model framework for GWAS dramatically reduced the number of false positives compared with naïve methods. Building on this foundation, many methods have since been developed to increase computational speed or improve statistical power in GWAS. These methods have allowed the detection of genomic variants associated with either traditional agronomic phenotypes or biochemical and molecular phenotypes. In turn, these associations enable applications in gene cloning and in accelerated crop breeding through marker assisted selection or genetic engineering. Current topics of investigation include rare-variant analysis, synthetic associations, optimizing the choice of GWAS model, and utilizing GWAS results to advance knowledge of biological processes. Ongoing research in these areas will facilitate further advances in GWAS methods and their applications.
© 2020 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.
References
REFERENCES
-
- Abasht, B., & Lamont, S. J. (2007). Genome-wide association analysis reveals cryptic alleles as an important factor in heterosis for fatness in chicken F2 population. Animal Genetics, 38, 491-498. https://doi.org/10.1111/j.1365-2052.2007.01642.x
-
- Aranzana, M. J., Kim, S., Zhao, K., Bakker, E., Horton, M., Jakob, K., … Nordborg, M. (2005). Genome-wide association mapping in Arabidopsis identifies previously known flowering time and pathogen resistance genes. PLoS Genetics, 1, e60. https://doi.org/10.1371/journal.pgen.0010060
-
- Aulchenko, Y. S., De Koning, D.-J., & Haley, C. (2007). Genomewide rapid association using mixed model and regression: A fast and simple method for genomewide pedigree-based quantitative trait loci association analysis. Genetics, 177, 577-585. https://doi.org/10.1534/genetics.107.075614
-
- Beló, A., Zheng, P., Luck, S., Shen, B., Meyer, D. J., Li, B., … Rafalski, A. (2008). Whole genome scan detects an allelic variant of fad2 associated with increased oleic acid levels in maize. Molecular Genetics and Genomics, 279, 1-10. https://doi.org/10.1007/s00438-007-0289-y
-
- Benjamini, Y., & Heller, R. (2007). False discovery rates for spatial signals. Journal of the American Statistical Association, 102, 1272-1281. https://doi.org/10.1198/016214507000000941
Publication types
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
