植物关联分析方法的研究进展

Advances on Methodologies for Genome-wide Association Studies in Plants

关联分析在人类和动植物遗传研究中的应用日益广泛,新方法及其软件包不断涌现。为对其更好选择和应用,本文综述了关联分析的主要方法及其软件包。首先,介绍了群体结构对关联分析的影响;其次,重点介绍了单位点关联分析、多位点关联分析、上位性和多性状关联分析方法及其软件包;最后,展望了关联分析的发展动向。应当指出,基于群体结构和多基因整体背景控制的全基因组单标记快速扫描算法在目前的实际资料分析中应用较广泛,与其结果互补的是假阳性率较高的非参数方法。但是,今后的方法应当是以多位点模型、环境互作、上位性检验和多个相关性状联合分析为主。这为今后的理论与应用研究提供了有益信息。

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 methodologies 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 interaction, epistatic detection and multivariate analysis. Our purpose was to provide beneficial information in theoretical and applied researches.