LAUSR

Abstract Over the past decade, genome-wide association studies (GWASs) have successfully identified hundreds of genetic variants associated with economically important production traits in beef cattle. Environmental factors, such as farm, year, and season, have been included in GWASs to represent systematic effects that can mask environmentally specific genetic effects. Genome-wide gene × environment interaction (GWEI) studies have emerged in recent years, although few have been conducted for livestock because of the considerable associated challenges. Because of the popularity of meta-analyses in GWASs, these analyses have also been applied to detect genotype by environment (G × E) interactions. In this study, we use a meta-analytic approach based on a mixed model to combine five years, which were defined as multiple environments, to identify novel genes involved in G × E interactions for carcass weight (CW) and bone weight (BW) in Chinese Simmental beef cattle. We found two and five novel candidate genes for CW trait and BW trait, respectively. These genes were RIMS2, PRKAR2B, GPR133, AKAP1, PCDH10, and AADAT, with PRKAR2B overlapping for the two carcass traits.