Genetics of energy allocation to growth in Angus cattle: trait derivation, model comparison, and relationships with feed efficiency and body composition traits

Abstract Background Improving feed efficiency while understanding resource-allocation trade-offs remains a challenge in livestock breeding. We defined an energy allocation coefficient to growth ( α ) as the ratio of estimated net energy retained in growth to net energy available after accounting for predicted maintenance requirements and investigated its genetic background in American Angus cattle. We compared a two-step (TS) approach, treating α as a derived pseudo-phenotype in linear animal models, with a one-step (OS) approach, jointly estimating breeding values and variance components through a nonlinear energy-balance model. Genetic parameters were estimated using pedigree- and genomic-based models, and genetic relationships with growth, feed efficiency, and body composition traits were evaluated. Results The derived α averaged 0.77 ± 0.28 and ranged from 0.07 to 3.10. Log( α ) was heritable (h² ≈ 0.13–0.20), with highly consistent breeding value rankings across approaches ( ρ > 0.94). Genetic correlations were 0.63 ± 0.03 with average daily gain, −​0.80 ± 0.02 with feed conversion ratio, −​0.54 ± 0.03 with residual feed intake, and 0.61 ± 0.03 with residual average daily gain, indicating substantial but incomplete genetic overlap with conventional growth and feed efficiency traits. The genetic correlation with dry matter intake was weak (−​0.14 ± 0.04) and close to zero with body composition traits (−​0.13 to 0.04). Conclusions The α is a derived indicator of relative energy allocation toward growth, calculated using a nutritional energy-balance framework, and contains additive genetic variation in American Angus cattle. Despite modest differences in variance partitioning between TS and OS, the underlying genetic signal was largely consistent across model formulations. The TS framework is compatible with standard genetic evaluation procedures and provides a practical approach for genetic analysis of this derived coefficient. The incomplete genetic overlap between α and conventional feed efficiency traits supports further evaluation of α as a complementary indicator of efficiency from a resource-allocation perspective. Future work should evaluate its relationships with health, reproduction, and resilience-related traits to determine whether α provides additional information for investigating resource-allocation trade-offs and future breeding applications.