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. 2025 Apr 30:16:1576966.
doi: 10.3389/fgene.2025.1576966. eCollection 2025.

Genetic architecture of thermotolerance traits in beef cattle: a novel integration of SNP and breed-of-origin effects

Gabriel A Zayas  1 , Camila Santos Rojas  1 , Eduardo E Rodriguez  1 , Aakilah S Hernandez  2 , Ashley M Beard  1 , Fahad Rafiq  1 , Kaitlyn M Sarlo Davila  3 , Raluca G Mateescu  1
Affiliations

Genetic architecture of thermotolerance traits in beef cattle: a novel integration of SNP and breed-of-origin effects

Gabriel A Zayas et al. Front Genet. .

Abstract

Background: Rising temperatures increasingly expose beef cattle to heat stress, reducing productivity and welfare, especially in tropical climates. Crossbreeding Bos t. taurus and Bos t. indicus has emerged as a critical strategy to balance the production efficiency of taurine breeds with the superior thermotolerance of indicine breeds. Understanding the genetic architecture of thermotolerance traits is essential for improving heat resilience in beef cattle populations.

Methods: Phenotypes for short hair length (SHL, undercoat) and long hair length (LHL, topcoat), sweat gland area (SGA), and thermal stress slope (TSS), a measure of body temperature fluctuations under heat stress, were collected from 3,962 crossbred Angus-Brahman heifers. Heifers were genotyped, and breed-of-origin (BOA) for each marker was determined using LAMP-LD. Genome-wide association studies were conducted using SNP-only, BOA-only, and integrated SNP + BOA models to identify quantitative trait loci (QTLs) associated with thermotolerance traits. Genes in QTL regions were used for functional enrichment analysis using Gene Ontology (GO) and KEGG pathways.

Results: Significant QTLs for SHL and LHL were identified on BTA20, overlapping the PRLR gene. A QTL on BTA19 for SHL and LHL was driven solely by BOA effects, with Brahman BOA associated with shorter hair lengths. For SGA, six suggestive QTLs were detected, predominantly linked to Angus-derived alleles associated with reduced sweat gland area. For TSS, a significant QTL on BTA1 exhibited a strong BOA effect, with Angus BOA associated with higher TSS values, indicative of reduced thermoregulatory efficiency. Integrated SNP + BOA models provided greater resolution and revealed novel QTLs compared to single-effect models. Functional enrichment using GO and KEGG identified MAPK and estrogen signaling pathways in both LHL and TSS, indicating potential overlap in the biological processes influencing hair length and thermoregulation.

Conclusion: This study demonstrates the value of integrating BOA with SNP-based models to uncover the genetic architecture of thermotolerance traits in beef cattle. By better capturing breed-specific contributions, these findings enhance our understanding of thermoregulation and provide actionable insights for improving heat resilience in cattle.

Keywords: GWAS; PRLR; crossbreeding; heat stress; thermotolerance.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Manhattan plots from GWAS for long hair length using (a) SNP-based, (b) BOA-based, and (c) SNP + BOA combined analyses. The -log10(p-values) are plotted across chromosomes, with green and red dashed lines representing the suggestive threshold (1/number of SNPs) and genome-wide significance threshold (Bonferroni correction, α = 0.1), respectively.
FIGURE 2
FIGURE 2
Manhattan plots from GWAS for short hair length using (a) SNP-based, (b) BOA-based, and (c) SNP + BOA combined analyses. The -log10(p-values) are plotted across chromosomes, with green and red dashed lines representing the suggestive threshold (1/number of SNPs) and genome-wide significance threshold (Bonferroni correction, α = 0.1), respectively.
FIGURE 3
FIGURE 3
Manhattan plots from GWAS for sweat gland area using (a) SNP-based, (b) BOA-based, and (c) SNP + BOA combined analyses. The -log10(p-values) are plotted across chromosomes, with green and red dashed lines representing the suggestive threshold (1/number of SNPs) and genome-wide significance threshold (Bonferroni correction, α = 0.1), respectively.
FIGURE 4
FIGURE 4
Manhattan plots from GWAS for thermal stress slope (TSS) using (a) SNP-based, (b) BOA-based, and (c) SNP + BOA combined analyses. The -log10(p-values) are plotted across chromosomes, with green and red dashed lines representing the suggestive threshold (1/number of SNPs) and genome-wide significance threshold (Bonferroni correction, α = 0.1), respectively.
See this image and copyright information in PMC

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