Usefulness of multi-breed models in genetic evaluation of direct and maternal calving ease in Holstein and Belgian Blue Walloon purebreds and crossbreds

The objective of this study was to verify the feasibility of a joint genetic evaluation system for calving ease trait of Belgian Blue (BBB) and Holstein (HOL) Walloon cattle based on data of purebred and crossbred animals. Variance components and derived genetic parameters for purebred BBB and HOL animals were estimated by using single-breed linear animal models. This analysis showed clear genetic differences between breeds. Estimates of direct and maternal heritabilities (±standard error) were 0.34 (±0.02) and 0.09 (±0.01) for BBB, respectively, but only 0.09 (±0.01) and 0.04 (±0.01) for HOL, respectively. Moreover, a significant negative genetic correlation between direct and maternal effects was obtained in both breeds: −0.46 (±0.04) for BBB and −0.29 (±0.11) for HOL. Variance components and derived genetic parameters for purebred BBB and HOL and crossbred BBB × HOL cattle were then estimated by using two multi-breed linear animal models: a multi-breed model based on a random regression test-day model (Model MBV), and a multi-breed model based on the random regression multi-breed model (Model MBSM). Both multi-breed models use different functions of breed proportions as random regressions, thereby enabling modelling different additive effects according to animal's breed composition. The main difference between these models is the way in which relationships between breeds are accounted for in the genetic (co)variance structure. Genetic parameters differed between single-breed and multi-breed analysis, but are similar to the literature. For BBB, estimates of direct and maternal heritabilities (±SE) were 0.45 (±0.07) and 0.08 (±0.01) by using Model MBV, and 0.45 (±0.08) and 0.09 (±0.02) for Model MBSM, respectively. For HOL, these estimates were 0.18 (±0.04) and 0.05 (±0.01) using Model MBV, and 0.16 (±0.04) and 0.05 (±0.01) for Model MBSM, respectively. Reliability gains (up to 25%) indicated that the use of crossbred data in the multi-breed models had a positive influence on the estimation of genetic merit of purebred animals. A slight re-ranking of purebred sires and maternal grandsires was observed between single-breed and multi-breed models. Moreover, both multi-breed models can be considered as quasi-equivalent models because they performed almost equally well with respect to MSE and correlations, for purebred and crossbred animals.