Integrated Metabolomic and Transcriptomic Analyses of Longissimus Thoracis Muscle Provide Insights into Metabolic...

Meat quality is an important economic trait in beef cattle and is influenced by breed-related metabolic characteristics. Yanbian cattle (YB) are valued for desirable meat quality, whereas Yanhuang cattle (YH), developed using Limousin cattle as the paternal line and Yanbian cattle as the maternal line, exhibit improved growth performance and carcass yield. However, the molecular basis underlying metabolic variation between these two genetically related cattle populations remains unclear. In this study, longissimus thoracis muscle samples from six animals per breed were analyzed using LC-MS/MS-based metabolomics and GC×GC-TOF/MS-based volatile compound profiling, and a subset of three samples per breed from the same cohort was selected for transcriptomic sequencing. A total of 1697 metabolites were detected. Based on the screening criteria of VIP > 1 and p < 0.05, 202 candidate metabolites were identified, among which 11 remained statistically significant after false discovery rate (FDR) correction. Volatile compound profiling detected 1333 and 1516 compounds in YB and YH, respectively, of which 809 were shared. Based on the same screening criteria, 39 candidate volatile compounds were identified, although none remained significant after FDR correction. Transcriptomic analysis identified 360 differentially expressed genes using |log₂FC| > 1 and adjusted p < 0.05, with enrichment mainly observed in pathways associated with carbohydrate metabolism, lipid turnover, and energy utilization. Integrative analyses indicated that amino acid-related metabolites, including phenylpyruvate, 2-aminobenzoic acid, and asparagine, were more closely associated with candidate volatile compounds than metabolites involved in central carbon metabolism. Several genes involved in lipid metabolism, energy metabolism, and muscle structure, including DGAT2, MGLL, CRYAB, CSRP3, AGPAT2, PHKA1, AMPD1, and PGM2L1, were associated with distinct metabolic modules. These findings provide an exploratory view of breed-related metabolic variation and identify candidate molecular features for future validation.