GxE

Incorporating multiple meteorological variables into genetic evaluation models for growth traits in American Angus cattle

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Abstract

The performance of beef cattle raised outdoors under extensive conditions is directly influenced by the environmental conditions in which they are exposed to. Meteorological variables provide useful proxies for characterizing these environments. Previous studies have reported greater variability in genetic and phenotypic trends in herds exposed to greater environmental fluctuations. In this context, the main objective of this study was to evaluate the effects of different farming environments on growth traits of American Angus cattle. Farming environments were characterized using daily meteorological data from NASA Power corresponding to the GPS coordinates of 35 American Angus herds across the country. These herds had 574,550 weaning weight records collected between 1990 and 2019. A principal component analysis (PCA) was performed on birth herd-year-season combinations using daily means of eight meteorological variables. The scaled squared cosine (coss2) of the first component, which explained 54.7% of the total variance, was used as a proxy for the herd-year-season environment of the animals' recorded performances. The effect of environment on 205-day adjusted weaning weight (WW205) was first evaluated using a pedigree-based animal model that included the fixed effects of age of the dam, calf sex, the combined effect of herd-birth year, and the combined effect of coss2-season. The coss² values were treated as a categorical variable with seven levels: six equal intervals between 0 and 0.6, and one level for the interval (0.6,1]. From this model, it was observed that the average WW205 decreased from the lowest to the highest values of coss2, with a difference of approximately 43.5 kg. A second analysis employed a reaction norm model with the same fixed effects (excluding coss2-season), in which breeding values were regressed on coss2 using a third-order Legendre orthogonal polynomial. This approach enabled predictions of genetic merit across environmental conditions and facilitated the study of genotype-by-environment (GxE) interactions. From this second model, it was observed that the heritability estimates were highest (h² ∈ [0.66,0.74], ±0.007) at the extreme values of coss². From the interval [0.1, 0.9] of coss², the h2 estimates decrease from 0.60 (± 0.006) to 0.39 (± 0.007). The genetic correlations among breeding values at 10 equidistant points of coss2 (from 0 to 1) varied from 0.98 to -0.19. The lowest correlations were observed between more extreme values of coss2. At lower values of coss2 (< 0.4), the genetic correlations decreased to 0.92, 0.77, and 0.43, indicating substantial GxE interactions. Overall, incorporating multiple meteorological variables into genetic evaluation models enabled more detailed characterization of non-genetic effects and GxE interactions. Accounting for such information can improve the accuracy of selection decisions and facilitate the choice of breeding animals best suited to specific environmental conditions.

Keywords: 2026

How to Cite:

Rovere, G., Garcia, A., Valle de Souza, S., Rowan, T., Brito, L., Lourenco, D., Cuyabano, B. & Gondro, C., (2026) “Incorporating multiple meteorological variables into genetic evaluation models for growth traits in American Angus cattle”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2285419. doi: https://doi.org/10.31274/wcgalp.23695

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