GxE

Enviromics-based modeling of genotype-by-environment-by-management interactions applied to pasture-raised beef cattle

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Abstract

Pasture-raised beef cattle face wide environmental and management variability, which challenges genetic evaluation and selection. We propose an enviromics-based framework to assess genotype-by-environment-by-management (GxExM) interactions in Nellore cattle raised on pasture across Brazil. The dataset integrated animal-level records, including pedigree (n = 2,104,030; 25 generations) and genomic data (n = 72,958; 93,386 SNPs), along with farm-level descriptors of environment (climate, soil, elevation) and management practices collected across 60 farms enrolled in the Embrapa-Geneplus breeding program. Phenotypic records (n = 391,871) were available for yearling weight (YW), scrotal circumference (SC), age at first calving (AFC), ribeye area (REA), backfat thickness (FAT), and marbling score (MARB). Management information was collected via electronic surveys and covered 24 practices related to technical assistance, soil management and conservation, feed supplementation, and reproductive strategies. Statistical analyses followed a two-step approach. (1) Environmental and management factors were used to define environmental conditions (EC) by grouping farms with similar attributes using a divisive hierarchical clustering algorithm. Clustering metrics, alongside genetic (co)variance supplementary analyses, supported the selection of the two-cluster solution (ENV1 and ENV2) for subsequent analyses. (2) For each phenotypic trait, a bi-variate ssGBLUP model was fitted to estimate (co)variance components and breeding values. Genetic correlations and comparisons of genomic estimated breeding values (GEBV) for bulls between ENV1 and ENV2 were used to evaluate GxExM interactions. The lowest genetic correlations were observed for AFC (0.32 ± 0.09), followed by YW (0.39 ± 0.01) and REA (0.65 ± 0.08), which indicates stronger GxExM interactions for these traits, whereas MARB (0.96 ± 0.03), FAT (0.86 ± 0.08), and SC (0.81 ± 0.04) indicate weaker interactions. Spearman's rank correlations between GEBVs of bulls with ≥5 offspring in both ECs further supported these results, showing 0.43, 0.57, and 0.75 for AFC, YW, and REA, respectively. Among bulls with high-accuracy GEBV (≥ 90th percentile), the percentage of top-ranked animals was lowest in the top 1% for all traits and increased toward the top 25% rankings. Specifically, values ranged from 10-53% for AFC, 16-55% for YW, and 35-70% for REA, were intermediate for SC (52-80%), and consistently high for FAT (72-88%) and MARB (86-94%). These findings provide strong evidence of GxExM interactions affecting key growth, reproductive, and carcass traits in pasture-raised beef cattle, particularly for AFC, YW, and REA. Low Spearman's correlations between GEBVs of bulls and pronounced re-ranking among top-ranking bulls between ECs underscore the magnitude of these interactions. The integration of farm-level environmental and management factors into genetic evaluations can be critical to improve selection decisions, enhance genetic gains, and foster sustainable and resilient beef cattle production.

Keywords: 2026

How to Cite:

Santana, T., Veroneze, R., Menezes, G. & Rosa, G., (2026) “Enviromics-based modeling of genotype-by-environment-by-management interactions applied to pasture-raised beef cattle”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2283965. doi: https://doi.org/10.31274/wcgalp.23541

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