Leveraging genome-wide association analyses with chip and imputed data emerges potential pleiotropic region for four duck growth traits

Average daily gain (ADG), body weight (BW), primary feather length (PRF) and breast depth (BD) are economically important traits in duck production, and understanding the genetic architecture of these traits remains limited. Genome-wide association studies (GWAS) can provide insight into the genetic mechanism underlying these traits. Increasing the power of GWAS by applying approaches such as genotype imputation can improve the ability to detect quantitative trait loci associations with polygenic traits. To increase the power of detecting marker-trait associations in this study, we also exploited imputed data and on a larger sample size. The objective of this study was to investigate marker-trait associations for ADG, BW, PRF and BD in ducks. First, we conducted univariate GWA analyses using chip data (hence medium density data) using 45 K autosomal SNPs and 1445 ducks from single breeding line. Second, we exploited imputed data with a larger sample size (13020) from the same line and performed univariate analyses. Comparison of SNP signals between the medium density and imputed data identified 63 common SNPs that were co-localized on chromosome 4. Several functional candidate genes such as PPARGC1A, LDB2 and LCORL were found within or close to the identified region. Indeed, the LCORL-NCAPG region has been reported in many mammalian species to be related to growth. Considering results from both analyses, current findings propose novel putative pleiotropic candidate quantitative trait loci (QTL) with the associated genes for the traits we analysed while identifying the most promising QTL region on chromosome 4.