Abstract
Genome-wide association (GWA) analysis is a powerful tool to identify individual loci underlying the complex traits. However, application of GWAS in natural population comes with challenges, especially power loss due to population strati1cation. Here, we introduce a bivariate analysis approach to a public GWAS dataset of Arabidopsis thaliana. Using this powerful approach, 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 associated statistics from our GWAS and expression QTL (eQTL) scans, we predicted and replicated a candidate gene AT1G11560 that potentially causes this association. Further analysis with flowering-time-related genes indicates that this locus is also co-selected with many flowering-time-related genes. Our study demonstrates the eZciency of multi-phenotype analysis to uncover hidden genetic loci masked by population structure. The discovered pleiotropic genotype-phenotype map provides new insights into understanding the genetic correlation of complex traits.