Improving Breeding Value Reliability with Genomic Data in Breeding Groups of Charolais.

The aim of this study was to assess the impact of incorporating genomic data using the single-step genomic best linear unbiased prediction (ssGBLUP) method compared to the best linear unbiased prediction (BLUP) method on the reliability of breeding values for age at first calving, calving interval, and productive longevity at 78 months in Charolais cattle. The study included 48,590 purebred Charolais individuals classified into four subgroups based on genotyping and performance records. The results showed that considering genotypes significantly improved genomic estimated breeding values (GEBV) reliability across all categories except nongenotyped individuals. For young genotyped individuals, the increase in reliability was up to 27% for both sexes. The highest average reliability was achieved for genotyped proven bulls and cows with performance records, and the inclusion of genomic data further improved the reliability by up to 22% and 21% for cows and bulls, respectively. The gain in reliability was observed mainly during the first three calvings, and then the differences decreased. The imported individuals showed lower estimated breeding values (EBV) and GEBV reliabilities than the domestic population, probably due to the weak genetic connection with the domestic population. However, when the progeny of imported heifers were sired by domestic bulls, the reliability increased by up to 24%. For nongenotyped individuals, only a slight increase in reliability was observed; however, the number of genotyped individuals in the population was still relatively small.

Genetic Parameters for a Weighted Analysis of Survivability in Dairy Cattle.

The genetic parameters for the survival of Holstein cows, analysed in nine consecutive time periods during the first three calving intervals, were estimated. The earlier the animals are culled, the more they are informationally underestimated. This undervaluing can be remedied by using a weighted analysis that balances the amount of information. If the method of estimating breeding values changes, the genetic parameters will also change. The Holstein cattle dataset from 2005 to 2017 used in this study included 1,813,636 survival records from 298,290 cows. The pedigree with three generations of ancestors included 660,476 individuals. Linear repeatability models estimated genetic parameters for overall and functional survivability. Due to weights, heritability increased from 0.013 to 0.057. Repeatability with weights was 0.505. The standard deviations of breeding values were 1.75 and 2.18 without weights and 6.04 and 6.20 with weights. Including weights in the calculation increased the additive variance proportion and the breeding values' reliabilities. We conclude that the main contribution of the weighted method we have presented is to compensate for the lack of records in culled individuals with a positive impact on the reliability of the breeding value.