Impact of genomic selection for growth and carcass traits on foot structure in Angus cattle

Abstract

Genomic evaluation improves accuracy and enables shorter generation intervals, accelerating genetic changes, possibly strengthening the antagonism between performance and less-selected traits. Our objective was to evaluate the impact of genomic selection for performance on foot structure in Angus cattle. Variance component estimation was done under the Bayesian approach (VCE) with partial or no genotypes, and with a new method based on predictivity (PRED) using all genotypes, this to examine changes in genetic parameters over time. The performance trait groups were growth (GT), carcass (CT), ultrasound carcass (uCT), and marbling (MT). Foot structure traits (FT) were foot angle (FA) and claw set (CS). Genetic parameters through VCE over 5-year intervals and using genotypes were obtained. From 2011-2015 to 2019-2022, changes in heritability were observed for CS (0.12 ± 0.01 to 0.16 ±, FA (0.18 ± 0.02 to 0.14 ± 0.01), carcass weight (0.30 ± 0.03 to 0.35 ± 0.04), marbling (0.43 ± 0.02 to 0.60 ± 0.04), and ultrasound backfat thickness (0.32 ± 0.01 to 0.38 ± 0.01). Changes in genetic correlations were found for CS-carcass weight (0.25 ± 0.15 to -0.04 ± 0.08), CS-rib eye area (0.20 ± 0.11 to -0.12 ± 0.08), and CS-weight at ultrasound scanning (0.12 ± 0.06 to 0.0 ± 0.03). For PRED, estimates from two 2-year slices showed that most GT and uCT heritabilities were lower than those from the last VCE interval (e.g., birth weight: 0.34 vs. 0.26). In comparison, FT heritabilities were higher (e.g., CS: 0.16 vs. 0.29). In general, all genetic correlations from PRED ranged from -0.15 to 0.10, whereas the values were between -0.15 and 0.05 in the last interval based on VCE. The predictivity method provides updated genetic parameters for young animals, whereas VCE estimates refer to the base population. Including genotypes had a strong impact on some estimates. Our results indicate that heritability estimates in recent generations for strongly selected traits have decreased compared to older generations. However, genetic correlations between foot structure and performance traits have consistently remained close to zero, likely due to the differences in selection intensity between these traits. While no strong antagonistic correlations were found, selecting multiple traits is crucial to maintain conformation while improving performance. Since the population structure changes due to genetic or environmental factors, updating the genetic parameters is vital for achieving expected genetic gains.