Disease & heat resistance

Fine-mapping reveals candidate causal variants controlling genetic and environmental sensitivity of heifer rebreeding in tropical beef systems

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Abstract

Heifer rebreeding (HR) determines lifetime productivity in beef cattle by defining whether a female remains in the herd and contributes across multiple parities. In tropical grazing systems, seasonal forage availability, heat stress, and heterogeneous management intensify genotype-by-environment (GxE) interactions, reducing genetic evaluation accuracy and limiting genetic progress for HR. Despite its economic impact, its genetic basis, especially loci controlling fertility and environmental sensitivity, remains poorly characterized. Hence, this study dissected the geneticthe genetic basis of HR in Nellore heifers by integrating single-step genomic reaction norm models (ssGRN) and targeted fine-mapping for significant genomic regions using imputed whole-genome sequence (WGS) data. The dataset included 299,885 HR records evaluated after the first calving and genomic data for 21,456 females and 1,100 sires (n. 22,556). Animals were genotyped using SNP panels of varying densities and imputed to a high-density panel using 6,862 reference animals (imputation accuracy: 0.97). After quality control, all 22,556 genotyped animals had call-rate > 0.95 and 409,617 SNPs passed marker-level filters; remaining for subsequent analyses. GxE was quantified with a two-step ssGRN. First, a continuous environmental gradient (EG) was derived from contemporary-group solutions for yearling weight, capturing nutritional and management conditions for postpartum recovery. Then, ssGRN was applied within a Bayesian framework to estimate genetic parameters for the HR intercept (genetic potential) and slope (environmental responsiveness). SNP effects for intercept and slope were derived by back-solving genomic estimated breeding values, and significance was assessed using z-scores and computing p-values [p-value=2*(1-ϕ(|z-score|))]. SNPs were deemed significant at -log10(p-value)~5.0 based on the effective number of independent genomic segments. Fine-mapping was performed by imputing lead regions (±100 kb) to WGS using 243 key sires as reference, followed by Bayesian inference with FINEMAP. Variants were prioritized when posterior inclusion probability > 0.90 and log10(Bayes factor) > 3.5. Genomic regions affecting both genetic potential and environmental responsiveness were detected on BTA4 and BTA14, with additional intercept loci on BTAs 1, 3, 5, 6, 16, 22, 25 and 27 and slope loci on BTAs 2, 3, 6, 7, 8, 10, 11, 13, 17, 22, 28 and 29. Fine-mapping highlighted high-confidence variants in pathways related to puberty, ovarian function, and metabolic allocation. Key loci underpinning HR mapped KISS1, GNRHR and GHRH (cyclicity), IGF1, IGF2, IGFBP2 and IGFBP5 (somatotropic axis and energy use), and LEP, INSR, and ANGPTL4 (adiposity and metabolic state). MAPK3, PLAG1, and PMCH linked growth rate, nutrient partitioning, and reproductive recovery after calving. Across the EG, SNP effects changed in magnitude and direction, indicating widespread SNP-by-environment interactions. Integrating ssGRN-based GWAS with sequence-level fine-mapping indicated that HR was modulated by coordinated neuroendocrine and metabolic genes whose effects depend on environmental quality.

Keywords: 2026

How to Cite:

Albuquerque, L., Arikawa, L., Brito, L., Fonseca, P., Macedo Mota, L., Oliveira, H. & Santos, D., (2026) “Fine-mapping reveals candidate causal variants controlling genetic and environmental sensitivity of heifer rebreeding in tropical beef systems”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2284783. doi: https://doi.org/10.31274/wcgalp.23615

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