Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches.

BACKGROUND: Genome-wide association studies (GWAS) have been extensively used to identify genomic regions associated with a variety of phenotypic traits in pigs. Until now, most GWAS have explored single-trait association models. Here, we conducted both single- and multi-trait GWAS and a meta-analysis for nine fatness and growth traits on 2004 pigs from four diverse populations, including a White Duroc × Erhualian F2 intercross population and Chinese Sutai, Laiwu and Erhualian populations.

RESULTS: We identified 44 chromosomal regions that were associated with the nine traits, including four genome-wide significant single nucleotide polymorphisms (SNPs) on SSC2 (SSC for Sus scrofa chromosome), 4, 7 and X. Compared to the single-population GWAS, the meta-analysis was less powerful for the identification of SNPs with population-specific effects but more powerful for the detection of SNPs with population-shared effects. Multiple-trait analysis reduced the power to detect trait-specific SNPs but significantly enhanced the power to identify common SNPs across traits. The SNP on SSC7 had pleiotropic effects on the nine traits in the F2 and Erhualian populations. Another pleiotropic SNP was observed on SSCX for these traits in the F2 and Sutai populations. Both population-specific and shared SNPs were identified in this study, thus reflecting the complex genetic architecture of pig growth and fatness traits.

CONCLUSIONS: We demonstrate that the multi-trait method and the meta-analysis on multiple populations can be used to increase the power of GWAS. The two significant SNPs on SSC7 and X had pleiotropic effects in the F2 , Erhualian and Sutai populations.