biostudies-literatureArikawa LMCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo2961https://www.ebi.ac.uk/biostudies/studies/S-EPMC12828016biostudies-literatureUnknown16(1)The world has recognized the significance of sustainable animal production, especially in terms of mitigating methane emissions. Developing strategies to mitigate methane without compromising productivity presents a significant challenge for nutritionists and breeders. However, measuring methane emissions at the individual level can be expensive and laborious. Therefore, the use of genomic approaches combined with whole-genome information may be an alternative to overcome these challenges. This study aimed to use sequencing data to carry out GWAS to identify genomic regions and candidate genes involved in biological processes and metabolic pathways of enteric methane emission-related traits (ME: daily methane emission, RME: residual methane emission, MY: methane yield, MI: methane intensity, and MM: methane metabolic). For this, 1042 Nellore animals with phenotypic information and 2744 imputed for sequence genotypes belonging to three breeding programs from Brazil were used. The SNP significance was estimated through frequentist statistics using the single-step GBLUP approach. For ME, a total of 27 significant SNPs were deemed significant (p < 3.55 × 10 ^- 6), harboring 89 positional candidate genes. For RME, 21 SNPs showed significant association, and 48 genes were mapped. Regarding MY, 20 SNPs were deemed significant and surrounded 76 candidate genes. For MI, 5 significant SNPs mapped 15 potential candidate genes, while in MM, 10 significant SNPs were located near 50 positional candidate genes. Various statistically significant SNPs and genomic regions on BTA 5, 6, 8, 10, 11, 13, 19, and 27 were shared between methane emission-related traits. Comparing QTL regions affecting methane-related traits showed common genomic regions with QTL previously related to feed efficiency, growth, and enteric methane emission. In general, the potential candidate genes (DUOX1, DUOX2, FRMD4A, NOS2, CHRNB3, CHRNA6, CALM2, EPCAM, MSH2, MSH6, KCNK12, MUC4, MUC20, LDHAL6B, SLC20A2, LIPC, EDNRA, ACOXL, MAP4K4, IL1R1, IL1R2, PLCB3, ESRRA, and BAD) are involved in several biological processes and signaling pathways related to gastrointestinal motility, salivary secretion, enteric nervous system, mucosal barrier integrity, epithelial transport, olfactory receptors, lipid metabolism, oxidative stress, cAMP, cGMP-PKG, MAPK cascade, among others. Our results highlight the complexity of methane emission as a polygenic phenotype, suggesting that bovine genetics can modulate methane emissions by controlling the ruminal ecosystem. These findings may serve as a basis for future research focused on developing selection strategies for more sustainable beef cattle production.Scientific reportsWhole-genome sequencing GWAS reveals bovine genomic effects on enteric methane emissions in beef cattle.PMC128280160012017/10630-22023/17818-8Silva JABorges MSMota LFMValente JPSSoares TLSFonseca LFSAlbuquerque LGNasner SLCFernandes Junior GAPelaez AMArikawa LMMercadante MEZfalseWhole-genome sequencing GWAS reveals bovine genomic effects on enteric methane emissions in beef cattle.The world has recognized the significance of sustainable animal production, especially in terms of mitigating methane emissions. Developing strategies to mitigate methane without compromising productivity presents a significant challenge for nutritionists and breeders. However, measuring methane emissions at the individual level can be expensive and laborious. Therefore, the use of genomic approaches combined with whole-genome information may be an alternative to overcome these challenges. This study aimed to use sequencing data to carry out GWAS to identify genomic regions and candidate genes involved in biological processes and metabolic pathways of enteric methane emission-related traits (ME: daily methane emission, RME: residual methane emission, MY: methane yield, MI: methane intensity, and MM: methane metabolic). For this, 1042 Nellore animals with phenotypic information and 2744 imputed for sequence genotypes belonging to three breeding programs from Brazil were used. The SNP significance was estimated through frequentist statistics using the single-step GBLUP approach. For ME, a total of 27 significant SNPs were deemed significant (p < 3.55 × 10 ^- 6), harboring 89 positional candidate genes. For RME, 21 SNPs showed significant association, and 48 genes were mapped. Regarding MY, 20 SNPs were deemed significant and surrounded 76 candidate genes. For MI, 5 significant SNPs mapped 15 potential candidate genes, while in MM, 10 significant SNPs were located near 50 positional candidate genes. Various statistically significant SNPs and genomic regions on BTA 5, 6, 8, 10, 11, 13, 19, and 27 were shared between methane emission-related traits. Comparing QTL regions affecting methane-related traits showed common genomic regions with QTL previously related to feed efficiency, growth, and enteric methane emission. In general, the potential candidate genes (DUOX1, DUOX2, FRMD4A, NOS2, CHRNB3, CHRNA6, CALM2, EPCAM, MSH2, MSH6, KCNK12, MUC4, MUC20, LDHAL6B, SLC20A2, LIPC, EDNRA, ACOXL, MAP4K4, IL1R1, IL1R2, PLCB3, ESRRA, and BAD) are involved in several biological processes and signaling pathways related to gastrointestinal motility, salivary secretion, enteric nervous system, mucosal barrier integrity, epithelial transport, olfactory receptors, lipid metabolism, oxidative stress, cAMP, cGMP-PKG, MAPK cascade, among others. Our results highlight the complexity of methane emission as a polygenic phenotype, suggesting that bovine genetics can modulate methane emissions by controlling the ruminal ecosystem. These findings may serve as a basis for future research focused on developing selection strategies for more sustainable beef cattle production.2025-01-01T00:00:00Z2025 Dec2026-06-05T03:25:51.795Z2026-06-05T03:12:01.025ZS-EPMC128280164140787910.1038/s41598-025-32815-z