Abstract #W71
Section: Breeding and Genetics
Session: Breeding and Genetics: Genomic methods and application - Beef
Format: Poster
Day/Time: Wednesday 7:30 AM–9:30 AM
Location: Gatlin Ballroom
Session: Breeding and Genetics: Genomic methods and application - Beef
Format: Poster
Day/Time: Wednesday 7:30 AM–9:30 AM
Location: Gatlin Ballroom
# W71
Genomic-polygenic and genomic predictions of direct and maternal effects for growth traits in a multibreed Angus-Brahman cattle population.
Mauricio Elzo*1, Milton Thomas2, Dwain Johnson1, Carlos Martinez1, Cliff Lamb1, Owen Rae1, Jerry Wasdin1, Joseph Driver1, 1University of Florida, Gainesville, FL, 2Colorado State University, Fort Collins, CO.
Key Words: cattle, genomic, growth
Genomic-polygenic and genomic predictions of direct and maternal effects for growth traits in a multibreed Angus-Brahman cattle population.
Mauricio Elzo*1, Milton Thomas2, Dwain Johnson1, Carlos Martinez1, Cliff Lamb1, Owen Rae1, Jerry Wasdin1, Joseph Driver1, 1University of Florida, Gainesville, FL, 2Colorado State University, Fort Collins, CO.
The objectives of this research were to compare variance components, genetic parameters, and EBV rankings for birth weight (BW) direct and maternal, weaning weight (WW) direct and maternal, and postweaning gain from 205 d to 365 d (WG) direct using 3 genomic-polygenic and one polygenic model. In addition, trends in EBV were evaluated for each trait and model as Brahman fraction increased from 0% to 100%. The Angus-Brahman multibreed data set included 5,264 animals born between 1987 and 2013. Genomic-polygenic models 1 (GP1; pedigree relationships for all animals; genomic relationships for genotyped animals), 2 (GP2; pedigree relationships for non-genotyped animals only; genomic relationships for genotyped animals), and 3 (GP3; no pedigree relationships; genomic relationships for genotyped animals) used actual and imputed genotypes from 46,768 SNP markers. Variance components and genetic parameters were estimated using REML procedures. Estimates of variance components and genetic parameters from GP1 were the most similar to those from the polygenic model, followed by those from GP2, and the least similar (particularly for maternal traits) were those from GP3. Similarly, the highest rank correlations were those between animal EBV from the polygenic model and GP1 (0.98 to 0.99), followed by those from GP1 and GP2 (0.82 to 0.94) and lastly by those from the polygenic model and GP2 (0.81 to 0.94). Model GP3 performed poorly for maternal traits due to ignoring calf-dam relationships (−0.12 to 0.23). These results indicated that the polygenic model and genomic-polygenic model 1 should be preferred. High genotyping costs could still make the polygenic model preferable for commercial beef cattle operations. Brahman animals tended to have higher EBV for BW direct and WW direct, and lower EBV for WG direct, BW maternal, and WW maternal. However, low regression coefficients for EBV on Brahman fraction ensured that high, medium, and low EBV animals from all breed compositions existed for all growth traits in this multibreed population.
Key Words: cattle, genomic, growth