The Use of Targeted Marker Subsets to Account for Population Structure and Relatedness in Genome-Wide Association Studies of Maize (Zea mays L.).

ABSTRACT: A typical plant genome-wide association study (GWAS) uses a mixed linear model (MLM) that includes a trait as the response variable, a marker as an explanatory variable, and fixed and random effect covariates accounting for population structure and relatedness. Although effective in controlling for false positive signals, this model typically fails to detect signals that are correlated with population structure or are located in high linkage disequilibrium (LD) genomic regions. This result likely arises from each tested marker being used to estimate population structure and relatedness. Previous work has demonstrated that it is possible to increase the power of the MLM by estimating relatedness (i.e., kinship) with markers that are not located on the chromosome where the tested marker resi

SUBMITTER: Chen AH 

PROVIDER: S-EPMC4978891 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature