Department of Agronomy, Iowa State University, Ames, IA, 50010, USA.
Department of Crop and Soil Sciences, Washington State University, Pullman, WA, 99164, USA.
Plant Genome. 2021 Mar;14(1):e20077. doi: 10.1002/tpg2.20077. Epub 2021 Jan 13.
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.
全基因组关联研究（GWAS）已发展成为研究复杂性状的强大而普遍的工具。在很大程度上，这得益于基因组技术的进步，使我们能够在不同的遗传材料中检测全基因组的遗传变异。混合模型框架的发展与简单的方法相比，大大减少了假阳性的数量。在此基础上，此后开发了许多方法来提高 GWAS 的计算速度或提高统计能力。这些方法已经允许检测与传统农学表型或生化和分子表型相关的基因组变异。反过来，这些关联可用于基因克隆，并通过标记辅助选择或遗传工程加速作物育种。目前的研究课题包括稀有变异分析、综合关联、优化 GWAS 模型的选择以及利用 GWAS 结果来推进对生物过程的认识。这些领域的持续研究将促进 GWAS 方法及其应用的进一步发展。
