PSIV-29 Identifying candidate genes and QTL associated with enteric methane emission-related traits in Nellore cattle using sequencing data.

Abstract Developing strategies to mitigate methane emissions without compromising animal productivity is crucial for promoting sustainable agricultural practices. However, enteric methane measurements at the individual animal level are expensive and labor-intensive. Therefore, using 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 a genome-wide association study (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, and MI: methane intensity). For this, 1,042 Nellore animals with phenotypic information and 2,744 imputed sequence genotypes belonging to three breeding programs from Brazil were used. After quality control filtering, a total of 2,591,217 SNPs and all 2,744 samples were retained for further analyses. In the GWAS analyses, single-trait models were fit using the single-step GBLUP approach to identify significant SNPs associated with each trait by back-solving for SNP effects. Significant associations were determined using a genome-wide Bonferroni correction based on the number of independent chromosomal segments (p < 3.55 × 10⁻⁶). For ME, a total of 27 SNPs were deemed significant, surrounding 89 positional candidate genes (within 250 kb up- and down-stream from the SNPs). For RME, 21 SNP were significant, close to 48 positional candidate genes. Regarding MY, 20 SNPs were significant, near to 76 positional candidate genes. For MI, 5 significant SNPs were located close to 15 positional candidate genes. Significant SNPs on BTA 5, 6, 8, 10, 11, 13, 19, and 27 were shared between methane emission-related traits. Mapping QTL harboring ±500 kb from the SNPs associated with methane-related traits identified overlapping genomic regions with previously reported QTL for feed efficiency, growth, and enteric methane emission. The potential candidate genes in these regions were DUOX1, DUOX2, FRMD4A, NOS2, CHRNB3, CHRNA6, CALM2, EPCAM, MSH2, MSH6, KCNK12, MUC4, MUC20, LDHAL6B, SLC20A2, LIPC, EDNRA, ACOXL, MAP4K4, IL1R1, and IL1R2. In general, these genes are involved in several biological processes and signaling pathways related to gastrointestinal motility, salivary secretion, the enteric nervous system, mucosal barrier integrity, epithelial transport, 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 enteric methane emissions by controlling the ruminal ecosystem. These findings could lead to advancements in sustainable beef cattle production, assisting in the development of selection strategies to mitigate greenhouse gas emissions. This work was supported by the Foundation for Research Support of the State of São Paulo (FAPESP - Grant #2017/10630–2, #2018/20002–6, #2023/17818-8, and #2024/16663-3).