Use of a Sire MGS model to disentangle paternal and maternal origins of genetic variance in lifetime productivity of tropical dairy cattle

Abstract Data from 80,713 first-calving cows (1984 to1989) of the Holstein, Mambi, and Siboney breeds, belonging to seven large dairy enterprises in Cuba and progenies of 1,297 sires, were analyzed. For each cow, the average across all lactations for at least 14 years after first calving was defined as individual productivity (PI), and the corresponding lifetime sum as accumulated productivity (PA); both traits were. Two genetic models were fitted: a classical Animal Model (M1) and a Sire maternal grandsire model (Sire MGS; M2), aimed at partitioning additive genetic variance into paternal and maternal-line components. Heritability estimates under model M1 were moderate (h2 ≈ 0.135 to 0.140), whereas M2 yielded higher values (h2 ≈ 0.158 to 0.170), reflecting increased additive variance due to a better connectedness across herds. Using estimated breeding values (EBV) for PI and PA, a global cow merit index (H1) was defined under M1. Under M2, a parental index (IM2) combining four standardized predictors (paternal and maternal-grandsire EBV for PI and PA) was constructed. Multiple regression of H1 on IM2 showed that the paternal and maternal-grandsire paths accounted for 73% and 27% of the variation, respectively, indicating a non-negligible maternal-line contribution. Model M2 provided the best overall fit according to information criteria and cross validation using two independent subsamples and the full population yielded correlations of 0.870 to 0.881, demonstrating strong predictive ability and stability of IM2 rankings. These results support the Sire MGS model as a structural extension of the Animal Model for breeding programs targeting lifetime productivity in tropical dairy cattle.