PS1-4. Comparison of Single- and Multi-trait Models Including Additive and Dominance Effects for Cattle Carcass Quality Traits in Brangus Population.

Abstract Genetic parameter estimates for carcass quality traits and their use in the evaluation of carcass quality is of considerable importance in the genetic improvement of beef cattle. Although many studies have shown that dominance genetic effects are an important component of phenotypic values, traditional genetic evaluation methods used to estimate the genetic parameters ignore dominance (nonadditive) and consider additive genetic effects only. The objective of this study was to compare the predictive ability of single- and multi-trait genomic prediction models including additive and dominance effects for the following carcass quality traits: rib eye area (REA), intramuscular fat (IMF) and fat thickness (FAT) from 740 Brangus heifers that were registered with International Brangus Breeders Association. BovineSNP50 Infinium BeadChips for SNP markers coded as 0, 1, or 2, based on the number of B alleles at each locus were used to genotype each heifer. After quality control of SNP markers, 35351 SNP markers were used to obtain heritability and genetic correlation estimates between REA, IMF and FAT traits. The package BGLR with Multitrait function in R language was used to obtain heritability estimates and genetic correlations between REA, IMF and FAT traits. Brangus heifers were randomly clustered into 10-fold cross-validation to quantify the correlations between actual and predicted values from single- or multi-trait GBLUP genomic prediction models including additive and dominance effects. Additive and dominance heritability estimates from multi-trait GBLUP were 0.25, 0.29 and 0.21; and 0.20, 0.14 and 0.20, whereas the single-trait GBLUP estimates were 0.26, 0.30 and 0.23; and 0.20, 0.13 and 0.21 for REA, IMF and FAT traits, respectively. Additive and dominance heritability estimates from single- and multi-trait GBLUP models were quite similar for REA, IMF and FAT traits. In the single- and multi-trait GBLUP analysis, additive heritability estimates were higher than or similar to dominance heritability estimates for REA, IMF and FAT traits. Genetic correlations between REA and IMF (0.04), and between IMF and FT (0.30) were quite low; however, genetic correlation between REA and FT (0.53) was moderate. Genetic correlations indicated the positive genetic association between REA, IMF and FAT traits. The prediction abilities of single-trait GBLUP with dominance effect (0.333, 0.407 and 0.280) and multi-trait GBLUP with dominance effect (0.332, 0.402 and 0.274) in cross-validation data sets were quite similar for REA, IMF and FAT traits, respectively.