Context Increasing use of genomic information in the genetic evaluation of livestock has stimulated interest in analyses combining data from multiple breeds. This can increase the size of the reference population and increase the accuracy of predicted breeding values. In particular, it is relevant for breeds with small numbers of records that are genetically similar to the other breeds in the analysis. Aims Evaluate the scope for multi-breed genetic evaluation of tropically adapted beef cattle in Australia. Methods Data comprised records for 25 traits measured for three breeds of tropically adapted Australian beef cattle, namely Brahman, Droughtmaster and Santa Gertrudis. After quality control and edits, allele counts for 75,932 genomic markers were available for 68,200 individuals. Univariate analyses were performed fitting standard BREEDPLAN models accounting for the genetic differences among the base populations for different breeds by fitting metafounders. Estimation of variance components was followed by single-step best linear unbiased prediction analyses performed considering all records or omitting records on the youngest individuals, so-called focal animals. Contrasting results from ‘part’ and ‘whole’ analyses allowed calculation of the linear regression (LR) statistics proposed for the validation of predicted breeding values. Key results Comparing LR statistics from single- and multi-breed analyses clearly demonstrated the gains in information possible from utilising records for closely related breeds. Whereas there were only small differences for Brahman, increases in population accuracy were consistent for Droughtmaster, amounting to 0.065 on average across traits. Corresponding gains for Santa Gertrudis were, on average, 0.032, with values being close to zero for traits with many records. Conclusions Owing to crossbreeding with Brahman in creating the Droughtmaster and Santa Gertrudis breeds, the three tropically adapted breeds are sufficiently similar genetically for simple, joint multi-breed analyses prediction of breeding values to be advantageous, in particular for Droughtmaster. Implications Multi-breed analyses can increase the accuracy of genomic evaluation and enlarge the pool of selection candidates for individual producers.
Meyer et al. (Mon,) studied this question.