Variance component estimates for growth traits in beef cattle using selected variants from imputed low-pass sequence data.

A beef cattle population (n = 2,343) was used to assess the impact of variants identified from the imputed low-pass sequence (LPS) on the estimation of variance components and genetic parameters of birth weight (BWT) and post-weaning gain (PWG). Variants were selected based on functional impact and were partitioned into four groups (low, modifier, moderate, high) based on predicted functional impact and re-partitioned based on the consequence of mutation, such as missense and untranslated region variants, into six groups (G1-G6). Each subset was used to construct a genomic relationship matrix (GRM) for univariate animal models. Multiple analyses were conducted to compare the proportion of additive genetic variation explained by the different subsets individually and collectively, and these estimates were benchmarked against all LPS variants in a single GRM and array (e.g., GeneSeek Genomic Profiler 100K) genotypes. When all variants were included in a single GRM, heritability estimates for BWT and PWG were 0.43 ±â€…0.05 and 0.38 ±â€…0.05, respectively. Heritability estimates for BWT ranged from 0.10 to 0.42 dependent on which variant subsets were included. Similarly, estimates for PWG ranged from 0.05 to 0.38. Results showed that variants in the subsets modifier and G1 (untranslated region) yielded the highest heritability estimates and were similar to the inclusion of all variants, while estimates from GRM containing only variants in the categories High, G4 (non-coding transcript exon), and G6 (start and stop loss/gain) were the lowest. All variants combined provided similar heritability estimates to chip genotypes and provided minimal to no additional information when combined with chip data. This suggests that the chip single nucleotide polymorphisms and the variants from LPS predicted to be less consequential are in relatively high linkage disequilibrium with the underlying causal variants as a whole and sufficiently spread throughout the genome to capture larger proportions of additive genetic variation.

Animals from a crossbred beef cattle population were sequenced at low depth (i.e., 0.5×) and different subsets of selected imputed variants were investigated relative to their ability to explain variation in birth weight (BWT) and post-weaning gain (PWG). Variants were classified by both their predicted functional impact and by the consequence of the mutation and partitioned into subsets within these two criteria. When ~ 1 million variants were included in the same genomic relationship matrix, heritability estimates were similar to a 100k chip array. Heritability estimates for BWT ranged from 0.10 to 0.42 dependent on which variant subsets were included. Similarly, estimates for PWG ranged from 0.05 to 0.38. Differences in minor allele frequency were observed among subsets and these differences likely contributed to differences in heritability estimates. Results suggest that linkage disequilibrium between the variants categorized as being less consequential and underlying causal variants is high as indicated by the high percentage of variation explained.

Genetic parameter estimates for bull prolificacy and its relationship with scrotal circumference in a commercial beef cattle population.

The commercial beef cattle industry relies heavily on the use of natural service sires. When artificial insemination is deemed difficult to implement, multisire breeding pastures are used to increase reproductive rates in large breeding herds or to safe-guard against bull injury during the breeding season. Although each bull might be given an equal opportunity to produce offspring, evidence suggest that there is substantial variation in the number of calves sired by each bull in a breeding pasture. With the use of DNA-based paternity testing, correctly assigning calves to their respective sires in multisire pastures is possible and presents an opportunity to investigate the degree to which this trait complex is under genetic control. Field data from a large commercial ranch was used to estimate genetic parameters for calf count (CC; 574 records from 443 sires) and yearling scrotal circumference (SC; n = 1961) using univariate and bivariate animal models. Calf counts averaged 12.2 ± 10.7 and SC averaged 35.4 ± 2.30 cm. Bulls had an average of 1.30 records and there were 23.9 ± 11.1 bulls per contemporary group. The model for CC included fixed effects of age during the breeding season (in years) and contemporary group (concatenation of breeding pasture and year). Random effects included additive genetic and permanent environmental effects, and a residual. The model for SC included fixed effects of age (in days) and contemporary group (concatenation of month and year of measurement). Random effects included an additive genetic effect and a residual. Univariate model heritability estimates for CC and SC were 0.178 ± 0.142 and 0.455 ± 0.072, respectively. Similarly, the bivariate model resulted in heritability estimates for CC and SC of 0.184 ± 0.142 and 0.457 ± 0.072, respectively. Repeatability estimates for CC from univariate and bivariate models were 0.315 ± 0.080 and 0.317 ± 0.080, respectively. The estimate of genetic correlation between CC and SC was 0.268 ± 0.274. Heritability estimates suggest that both CC and SC would respond favorably to selection. Moreover, CC is lowly repeatable and although favorably correlated, SC appears to be weakly associated with CC.