Genomic dissection of methane emission traits in cattle: A meta-GWAS and heritability analysis across populations - Sare Golpasand; Navid Ghavi Hossein-Zadeh; Shahrokh Ghovvati (PLoS ONE, 2026)
Enteric methane emissions from ruminants represent a significant contributor to agricultural greenhouse gases, necessitating precise genetic tools to guide mitigation strategies. This study aimed to identify genomic regions and estimate heritability parameters associated with methane-related traits in cattle through an integrated meta-analytical framework. The meta-analysis of the genome-wide association studies (meta-GWAS) was carried out with the METAL software, combining SNP level data extracted from published studies. Simultaneously, a distinct random effects meta-analysis of genomic and pedigree-based heritability estimates was performed using Comprehensive Meta-Analysis software. Functional analysis of the post-GWAS, including: Gene Ontology, KEGG, and network-based enrichment analysis, was also performed to describe the biological context of significant genes. The meta-GWAS identified 74 significant SNPs that were significant for the traits of methane, which are related to 113 candidate genes. Functional enrichment analyses revealed pathways related to metabolism, immune response, ion transport, and host–microbiome interactions. The KEGG metabolic pathway emerged as a highly enriched term, encompassing key genes such as: ALDH7A1 , CYP51A1 , P4HA2 , and SHPK , which are involved in amino acid catabolism, lipid processing, and redox regulation functions critical to energy balance and digestive efficiency. Network analysis with Cytoscape has revealed TRPV3, TRPV1, ANK3, PKD2 and SHPK as network hub genes. Heritability meta-analysis indicated that methane production exhibited the moderate genomic (h 2 = 0.296) and pedigree-based (h 2 = 0.299) heritability estimations, and methane yield was also found to have moderate and high heritability. The findings highlight the potential for methane-related traits as viable targets for genetic selection. This research demonstrates the value of integrating functional genomics and quantitative genetic approaches to enhance understanding of the biological and heritable components of methane emissions, providing a robust foundation for an environmentally sustainable livestock breeding program.