Integrating bulk and single-cell RNA sequencing with GWAS reveals regulatory networks underpinning complex traits in beef cattle

BACKGROUND: The genetic dissection of complex traits in livestock continues to pose a significant challenge in the field of animal genetics and breeding. Although traditional genome-wide association studies (GWAS) are capable of localizing genetic variants associated with specific traits, they are insufficient to elucidate the underlying physiological mechanisms. An integrated analysis of multi-trait GWAS and multi-transcriptomic data systematically identifies key tissues and cell types influencing complex traits in beef cattle and elucidates their genetic regulatory basis. RESULTS: We systematically mapped tissue- and cell-type-specific regulatory architectures underlying 20 economically important traits in beef cattle. Tissue-level analyses revealed distinct trait-tissue associations: fatty acid traits, including C16:0 and C20:4, were enriched in liver; carcass traits, including marbling score and carcass weight, in renal cortex/medulla and longissimus dorsi muscle; meat-quality traits such as pH in cartilaginous tissues; and total fat content in bone marrow. At cellular resolution, analysis of eight trait-associated tissues identified 38 discrete cell types. Myofibers were significantly associated with most carcass traits, including rib-eye area and backfat thickness, whereas hepatocytes emerged as key regulators of fatty acid and meat-quality traits, such as C16:0 and crude protein content. Transcription factor analysis identified cell-type-specific regulators: TBX15, SOX6, and TCF12 in myofibers; FOXA2 and NR1H4 in hepatocytes; and IRF8 and IKZF1 in microglia. Notably, hepatocytes and microglia showed complementary, trait-specific association patterns: hepatocytes were enriched for C16:0 associated saturated fatty-acid metabolic pathways, while microglia were enriched for C16:1 and unsaturated fatty-acid-related pathways, suggesting potential cross-tissue coordination in lipid regulation. CONCLUSIONS: Our study links specific tissues and cell types to phenotypic variation in beef cattle and identifies core transcriptional regulators and pathways driving trait variation. These cell-resolved maps provide mechanistic insight into how genetic variation shapes economically important traits, offering a valuable resource for functional studies, cell-informed precision breeding strategies, and the design of large-scale molecular phenotyping.