Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

SIMPLE SUMMARY: Complex traits that require observations over multiple time points for the same individual are called longitudinal traits. Understanding the genetic architecture of beef cattle growth cannot be limited simply to a genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the longitudinal weight–age using a growth curve approach. We compared three nonlinear models that described the body weight data of Chinese Simmental beef cattle. The parameters of the suitable model were treated as phenotypes of single-trait GWAS and multi-trait GWAS. We identified 87 significant single nucleotide polymorphisms (SNPs) associated with body weight. Many candidate genes associated with body weight were identified which may be useful for exploring the full genetic architecture underlying growth and development traits in livestock. ABSTRACT: The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R(2) = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.