Dual-trait genomic analysis in highly stratified Arabidopsis thaliana populations using genome-wide association summary statistics

文献类型： 外文期刊

第一作者： Feng, Xiao

作者： Feng, Xiao;Li, Ting;Yao, Yue;Li, Jiabei;Charati, Hadi;Shen, Xia;Feng, Xiao;Ning, Zheng;Xu, Weilin;Wan, Qianhui;Shen, Xia;Zan, Yanjun;Xu, Weilin;Wan, Qianhui;Zeng, Dongyu;Liu, Yang;Zeng, Ziyi;Shen, Xia

作者机构：

期刊名称：HEREDITY （ 影响因子：3.8； 五年影响因子：3.7 ）

ISSN： 0018-067X

年卷期： 2024 年

页码：

收录情况： SCI

摘要： Genome-wide association study (GWAS) is a powerful tool to identify genomic loci underlying complex traits. However, the application in natural populations comes with challenges, especially power loss due to population stratification. Here, we introduce a bivariate analysis approach to a GWAS dataset of Arabidopsis thaliana. We demonstrate the efficiency of dual-phenotype analysis to uncover hidden genetic loci masked by population structure via a series of simulations. In real data analysis, a common allele, strongly confounded with population structure, is discovered to be associated with late flowering and slow maturation of the plant. The discovered genetic effect on flowering time is further replicated in independent datasets. Using Mendelian randomization analysis based on summary statistics from our GWAS and expression QTL scans, we predicted and replicated a candidate gene AT1G11560 that potentially causes this association. Further analysis indicates that this locus is co-selected with flowering-time-related genes. The discovered pleiotropic genotype-phenotype map provides new insights into understanding the genetic correlation of complex traits.

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