Quantifying phenotypic and genetic variation for cow fertility phenotypes in American Simmental using total herd reporting data.

Reproduction plays a major role in the production efficiency of livestock species. However, cow-centric reproductive traits tend to be lowly heritable and are not expressed until later in an animal's lifetime, making phenotypic selection alone inefficient at generating genetic gain. Genetic progress can be accelerated by focusing selection on the predicted genetic component of reproductive traits using Expected Progeny Differences. We used the American Simmental Association's performance and Total Herd Enrollment data, made up of 533,155 calving records from 303,158 females (132,403 cows and 170,755 heifers), 33,732 of which are genotyped, to explore three continuous and two discrete phenotypes focused on quantifying early and sustained fertility in beef cows. We analyzed calving date (CD) (cow's CD relative to the start of the calving season), calving interval (CI) (days between calves), first calving interval (FCI) (CI observation between the first and second calving record for a female), heifer pregnancy (HP) (did the animal calve as 2-yr-old), and discrete early calving (DEC) (did animal calve in the first 30 d of the calving season) as distinct, but correlated measures of fertility. This dataset provides insight into population-wide trends related to cow attrition, calving season lengths, and phenotypic variation in fertility. We used pedigree and genomic REML to estimate these six phenotypes' genetic, permanent environment, and temporary environmental variance components. Pedigree-estimated heritabilities were 0.06 (± 0.000011) for CD, (0.04 ± 0.000005) for CI, 0.07 (± 0.000016) for DEC, 0.05 ± 0.000041 for FCI, and 0.23 (± 0.000099) for HP, consistent with other fertility traits across beef and dairy cattle. The incorporation of genomics increased the heritability estimate for HP (0.24 ± 0.000098) and decreased the estimate for FCI (0.04 ± 0.000029). Positive phenotypic and genetic correlations were found among these phenotypes (rG = 0.01 to 0.96). These results call for further work in optimizing genetic predictions and exploration of the genetic architecture through genome-wide studies. Whole herd reporting date frameworks represent opportunities for measuring new reproductive phenotypes, but their utility in genetic evaluations will rely on novel trait initiatives and consistent recording that captures more detailed data.