Integrative Transcriptomic and Metabolomic Analysis Reveal Mechanisms Underlying Differential Fecundity in Yangtze...

Differential fecundity in goats is a complex trait governed by coordinated molecular regulation across reproductive and endocrine tissues. In this study, we performed integrated metabolomic profiling of follicular fluid, serum, thyroid tissue, and uterine luminal fluid together with transcriptomic sequencing of follicular, thyroid, and uterine horn tissues from high-fecundity (HF) and low-fecundity (LF) Yangtze River Delta White goats. In addition, weighted gene co-expression network analysis (WGCNA) was conducted to elucidate the molecular mechanisms underlying differential litter size. High-fecundity goats exhibited enhanced follicular steroidogenesis, superior corpus luteum function, and more stable hypothalamic-pituitary-thyroid (HPT) axis activity, accompanied by increased uterine gland density and greater myometrial thickness. Metabolomic profiling identified 6640 metabolites displaying tissue-specific differential abundance patterns. Pathway enrichment analysis highlighted steroid hormone biosynthesis and energy metabolism in follicular fluid, PPAR signaling and tyrosine metabolism in thyroid tissue, and glycerophospholipid and one-carbon metabolism in uterine luminal fluid as major pathways associated with fecundity. Transcriptomic analysis identified 1596 differentially expressed genes (DEGs), including 20 genes shared across all examined tissues, constituting a systemic molecular signature associated with fecundity. WGCNA further revealed three functional tissue axes associated with follicular development (ELOVL4, INHA, NR5A2), thyroid endocrine regulation (GRHL2, NAPRT), and uterine receptivity (RSPO1, AGTR2, PTGER3). Low-fecundity-associated modules were predominantly concentrated in follicular and thyroid tissues, whereas the high-fecundity-specific module was mainly enriched in uterine horn. These findings provide a multi-tissue molecular framework underlying differential fecundity in goats and identify candidate hub genes and metabolites that may serve as candidate biomarkers for fecundity assessment and selective breeding programs.