Genotype-environment interaction for milk production of Gyr cattle in Brazil and Colombia.

BACKGROUND: Genotype by environment interactions (G × E) can play an important role in cattle populations and should be included in breeding programs in order to select the best animals for different environments. OBJECTIVE: The aim of this study was to investigate the G × E for milk production of Gyr cattle in Brazil and Colombia by applying a reaction norm model used genomics information, and to identify genomic regions associated with milk production in the two countries. METHODS: The Brazilian and Colombian database included 464 animals (273 cows and 33 sires from Brazil and 158 cows from Colombia) and 27,505 SNPs. A two-trait animal model was used for milk yield adjusted to 305 days in Brazil and Colombia as a function of country of origin, which included genomic information obtained with a single-step genomic reaction norm model. The GIBBS3F90 and POSTGSf90 programs were used. RESULTS: The results obtained indicate G × E based on the reranking of bulls between Brazil and Colombia, demonstrating environmental differences between the two countries. The findings highlight the importance of considering the environment when choosing breeding animals in order to ensure the adequate performance of their progeny. Within this context, the reranking of bulls and the different SNPs associated with milk production in the two countries suggest that G × E is an important effect that should be included in the genetic evaluation of Dairy Gyr cattle in Brazil and Colombia. CONCLUSION: The Gyr breeding program can be optimized by choosing a selection environment that will allow maximum genetic progress in milk production in different environments within and between countries.

Improving accuracy of direct and maternal genetic effects in genomic evaluations using pooled boar semen: a simulation study1.

Pooling semen of multiple boars is commonly used in swine production systems. Compared with single boar systems, this technique changes family structure creating maternal half-sib families. The aim of this simulation study was to investigate how pooling semen affects the accuracy of estimating direct and maternal effects for individual piglet birth weight, in purebred pigs. Different scenarios of pooling semen were simulated by allowing the same female to mate from 1 to 6 boars, per insemination, whereas litter size was kept constant (N = 12). In each pooled boar scenario, genomic information was used to construct either the genomic relationship matrix (G) or to reconstruct pedigree in addition to G. Genotypes were generated for 60,000 SNPs evenly distributed across 18 autosomes. From the 5 simulated generations, only animals from generations 3 to 5 were genotyped (N = 36,000). Direct and maternal true breeding values (TBV) were computed as the sum of the effects of the 1,080 QTLs. Phenotypes were constructed as the sum of direct TBV, maternal TBV, an overall mean of 1.25 kg, and a residual effect. The simulated heritabilities for direct and maternal effects were 0.056 and 0.19, respectively, and the genetic correlation between both effects was -0.25. All simulations were replicated 5 times. Variance components and direct and maternal heritability were estimated using average information REML. Predictions were computed via pedigree-based BLUP and single-step genomic BLUP (ssGBLUP). Genotyped littermates in the last generation were used for validation. Prediction accuracies were calculated as correlations between EBV and TBV for direct (accdirect) and maternal (accmat) effects. When boars were known, accdirect were 0.21 (1 boar) and 0.26 (6 boars) for BLUP, whereas for ssGBLUP, they were 0.38 (1 boar) and 0.43 (6 boars). When boars were unknown, accdirect was lower in BLUP but similar in ssGBLUP. For the scenario with known boars, accmat was 0.58 and 0.63 for 1 and 6 boars, respectively, under ssGBLUP. For unknown boars, accmat was 0.63 for 2 boars and 0.62 for 6 boars in ssGBLUP. In general, accdirect and accmat were lower in the single-boar scenario compared with pooled semen scenarios, indicating that a half-sib structure is more adequate to estimate direct and maternal effects. Using pooled semen from multiple boars can help us to improve accuracy of predicting maternal and direct effects when maternal half-sib families are larger than 2.