Genome-wide association studies (GWAS) have been widely used in human, animal and plant genetics, and many new approaches and their softwares have been developed in recent years. To make a better use of the GWAS methods in applied research, in this study we summarized the advances on methodologies and softwares for GWAS. First, LD score regression was introduced to investigate the effect of population structure on GWAS. Then, the main approaches and their softwares for GWAS in plants were reviewed, including a single-locus model, a multi-locus model, epistasis, and multiple correlated traits. Finally, we prospected the future developments in GWAS. It should be noted that, in real data analysis at present, the method-ologies for genome-wide single-marker scan under polygenic background and population structure controls are widely used, and the corresponding results are complementary to those derived from non-parameter approaches with high false discovery rate. However, the future approaches for GWAS should be based on the multi-locus genetic model, QTN-by-environment in-teraction, epistatic detection and multivariate analysis. Our purpose was to provide beneficial information in theoretical and applied researches.
Genome-wide association studyEpistasisMixed linear modelMulti-locus model
国家科技期刊平台
NSTL
万方数据
维普
