Abstract
This study aimed to investigate the changes in the meat quality characteristics of Duolang sheep using rumen metagenomic and muscle metabolomic analyses across different age groups. A total of 24 three-month-old male Duolang sheep were selected and reared, and samples of longissimus thoracis muscle and rumen contents were collected at 4, 6, and 8 months of age to evaluate meat quality, metabolites, rumen metagenome, and volatile fatty acids (VFAs). The results indicated that the lightness (L*(45min)) and yellowness (b*(45min)) of the longissimus thoracis muscle at 45 min post-slaughter were significantly higher at 4 and 6 months than at 8 months of age (p < 0.05). In terms of ruminal VFAs, butyrate concentration was significantly higher at 6 months than at 4 months (p < 0.05), and valerate concentration exhibited a quadratic relationship with age (p = 0.02). With increasing age, the relative abundances of Prevotella and Fibrobacter increased, whereas those of Methanobrevibacter and Bacteroides decreased (p < 0.05), leading to shifts in functional pathways related to amino acid, lipid, and carbohydrate and energy metabolism. Untargeted metabolomics revealed that muscle betaine and inosine peaked at 4 months of age, whereas L-arginine, L-proline, and inosinic acid were most abundant at 6 months of age (p < 0.05). Correlation analysis revealed that the b*(45min) was positively associated with ruminal concentrations of propionate, butyrate, and valerate, as well as with the relative abundances of key Selenomonadales taxa (p < 0.05). Inosinic acid exhibited a positive correlation with the abundance of the genus Sodaliphilus and ruminal butyrate concentration (p < 0.05), while Sodaliphilus abundance was negatively correlated with inosine (p < 0.05). In summary, this study demonstrates that age-related variations in the meat quality of Duolang sheep are closely associated with rumen microbial ecology and muscle metabolites, offering novel insights into the molecular mechanisms underlying meat quality formation and identifying potential biomarkers.