Efficiency of genome-wide association study in random cross populations

Abstract

Genome-wide association studies (GWAS) with plant species have employed inbred lines panels. Our objectives were to present additional quantitative genetics theory for GWAS, evaluate the relative efficiency of GWAS in non-inbred and inbred populations and in an inbred lines panel, and assess factors affecting GWAS. Fifty samples of 400 individuals from populations with linkage disequilibrium were simulated. Individuals were genotyped for 10,000 single nucleotide polymorphisms (SNPs) and phenotyped for traits controlled by 10 quantitative trait loci (QTLs) and 90 minor genes, assuming different degrees of dominance and heritabilities of 40 and 80%. The average SNP density was 0.1 centiMorgan and the QTL heritabilities ranged from 3.2 to 11.8%. To increase the QTL detection power, the additive-dominance model must be fitted for traits controlled by dominance effects but must not be fitted for traits showing no dominance. The power of detection was maximized increasing the sample size to 400 and the false discovery rate (FDR) to 5%. The average power of detection for the low, intermediate, and high heritability QTLs were 9.7, 32.7, and 87.7%, respectively. Under sample size of 400 the observed FDR was equal to or lower than the specified level of significance. The association mapping was highly precise. The analysis of the inbred random cross population provided essentially the same results from the non-inbred population. The inbred lines panel provided the best results concerning the low and intermediate heritability QTL detection power, FDR, and mapping precision. The FDR is mainly affected by population structure, compared to relationship information.