책임운영기관 농촌진흥청 국립축산과학원

Carcass weight (CW) is a major determinant of beef yield and market value in Korea, yet the genetic basis of this trait remains largely unexplored in cattle from Jeju Island. In this study, we performed a genome-wide association study (GWAS) using both a mixed linear model (MLM) and the FarmCPU approach, followed by pathway and network analyses to identify loci and biological functions underlying CW variation. A total of 256 Jeju cattle (92 Jeju Black and 164 Jeju Black × Hanwoo crossbreds) were initially sampled. One crossbred sample failed genotyping, leaving 255 animals (92 Jeju Black and 163 crossbreds) for analysis. Animals were genotyped using the Illumina BovineSNP50 v3 BeadChip, and 39,055 high-quality single nucleotide polymorphisms (SNPs) were retained after quality control. The MLM analysis detected no genome-wide significant associations, whereas the FarmCPU analysis identified six significant loci on Bos taurus chromosomes 3, 5, 6, 10, and 13, each explaining 2.55–9.58% of the phenotypic variance. Candidate genes located near these loci included EIF2B3, HECTD3, SOX5, KLF6, PHACTR3, and two uncharacterized protein-coding genes. Functional enrichment analysis identified biologically relevant pathways including lysine degradation, tryptophan metabolism, glycerolipid metabolism, fatty acid biosynthesis, extracellular matrix–receptor interaction, and signaling cascades such as PI3K–Akt and Rap1, although most pathways were not statistically significant after FDR correction. Protein–protein interaction (PPI) network analysis using STRING highlighted modules of signaling, extracellular matrix, and metabolic genes. These clusters suggest that coordinated interactions among these pathways contribute to carcass growth and development. These findings provide new insights into the molecular basis of CW in Jeju Black and Hanwoo × Jeju Black crossbred cattle and identify candidate genes and pathways that may be useful for genomic selection and the sustainable improvement of Jeju Black cattle populations.