Genetic parameters for carcass traits of progeny of beef bulls mated to dairy cows

Beef x dairy crossbred cattle (n = 615) were used to evaluate the effect of preharvest indicator traits and genotypes on the accuracy of estimated breeding values (EBVs) of seedstock candidates for selection. Genotypes for 100,000 single nucleotide polymorphisms were provided by the American Simmental Association of purebred and crossbred seedstock animals (n = 2,632). Five hundred and ninety-five of the 615 beef x dairy cattle had carcass camera and ultrasound data. Phenotypes were not used for any of the seedstock animals even though some may have had performance and ultrasound data. We estimated the genomic relationship matrix among 3,247 animals including both phenotyped and unphenotyped animals. We computed genetic parameters among 37 traits using 666 bivariate restricted maximum likelihood analyses. The accuracy of EBV depends on heritability. For the sake of brevity, we report accuracy for marbling as a proxy for other traits with similar heritability. We focus on accuracy for marbling because marbling is the primary determinant of carcass value. We computed EBV for all 3,247 animals for marbling based on camera data postharvest using best linear unbiased prediction. We report evidence of overlap in causative genes among postharvest carcass traits; marbling, ribeye area, yield grade, fat thickness, and hot carcass weight (HCW) based on genetic correlations. Genetic correlations range from -0.73 to 0.89. Several live animal traits (frame size, body weight and ultrasound fat thickness and ribeye area) were genetically correlated with postharvest traits; including HCW, ribeye area, yield grade, fat thickness, and marbling. Genetic correlations between pre- and postharvest traits ranged from -0.53 to 0.95. Accuracy for marbling ranged from 0.64 to 0.80 for animals with marbling recorded, and from 0.09 to 0.60 for animals without marbling recorded. The accuracy of animals without phenotypes was related to the genomic relationship between animals with phenotype and those without. Live animal traits were useful for predicting economically important carcass traits based on genetic correlations. The accuracy of EBV for seedstock animals that were not phenotyped was low, but this is consistent with theory, and accuracy is expected to increase with the addition of genotypes and carcass data from beef x dairy animals. Technological improvements in low-cost genotyping and sexed-semen have led to the utilization of beef bulls in dairy herds to produce beef x dairy progeny with improved carcass value compared to purebred dairy. A one-time collection of carcass data and genotypes on thousands of beef x dairy cattle might improve the accuracy of selecting beef bulls to mate with dairy cows into the foreseeable future. Low-cost genotyping platforms and sexed-semen have enabled the production of high breeding value dairy replacement heifers from a fraction of the herd representing the most elite cows. The remainder of the cow herd can be bred to beef bulls using male-sexed-semen. Camera carcass data postharvest and ultrasound carcass estimates preharvest (live animals) on beef x dairy animals combined with genotypes and ultrasound on seedstock animals may provide an efficient scheme for selecting beef bulls to mate to dairy cows in the future to maximize carcass value of the progeny. Genotypes are needed to link carcass data from previously harvested to seedstock bull selection candidates because pedigree is typically not available for beef x dairy cattle. We report that live animal ultrasound carcass estimates are predictive of postharvest economically important carcass traits. The accuracy of genetic evaluation of selection candidates without recorded carcass traits was low but is expected to increase with more genotypes and phenotypes on beef x dairy cattle. Genotypes, ultrasound estimates, and camera carcass data on thousands of beef x dairy cattle could enable increased accuracy of selection with periodic infusion of new phenotypes from future generations.