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.

Background: Efficiency is characterized by maximum productivity with lower inputs and minimal waste, resulting in greater output with the same or even fewer resources. In livestock, more efficient animals in converting food into protein may improve the economic efficiency of production systems, as feed costs represent a significant expense in beef production. Thus, the present study aimed to use imputed whole-genome sequencing (WGS) data to perform a genome-wide association study (GWAS) in order to identify genomic regions and potential candidate genes involved in the biological processes and metabolic pathways associated with feed efficiency-related traits (RFI: residual feed intake, DMI: dry matter intake, FE: feed efficiency, FC: feed conversion, and RWG: residual weight gain) in Nellore cattle. Results: The GWAS identified significant SNPs associated with feed efficiency traits in Nellore cattle. A total of 42 SNPs were detected for RFI, 10 for DMI, 99 for FC, 15 for FE, and 3 for RWG, distributed in different autosomes. Annotation analysis identified several candidate genes, and the prioritization highlighted 21, 9, 68, 23, and 8 key genes for RFI, DMI, FC, FE, and RWG, respectively. The prioritized candidate genes are involved in muscle development, lipid metabolism, response to oxidative stress, nutrient metabolism, neurotransmission, and oxidative phosphorylation. Additionally, enrichment analysis indicated that these genes act in several signaling pathways related to signal transduction, the nervous system, the endocrine system, energy metabolism, the digestive system, and nutrient metabolism. Conclusion: The use of imputed WGS data in GWAS analyses enabled the broad identification of regions and candidate genes throughout the genome that regulate expression of feed efficiency-related traits in Nellore cattle. Our results provide new perspectives into the molecular mechanisms underlying feed efficiency in Nellore cattle, offering a genetic basis to guide the breeding of efficient animals, thereby optimizing resource utilization and the profitability of production systems.