Transcriptomic Profiling of Hypoxia-Adaptive Responses in Tibetan Goat Fibroblasts.

The Tibetan goat () exhibits remarkable adaptations to high-altitude hypoxia, yet the molecular mechanisms remain unclear. This study integrates RNA-seq, WGCNA, and machine learning to explore gene-environment interactions (G × E) in hypoxia adaptation. Fibroblasts from the Tibetan goat and Yunling goat were cultured under hypoxic (1% O) and normoxic (21% O) conditions, respectively. This identified 68 breed-specific (G), 100 oxygen-responsive (E), and 620 interaction-driven (I) Differentially Expressed Genes (DEGs). The notably higher number of interaction-driven DEGs compared to other effects highlights transcriptional plasticity. We defined two gene sets: Environmental Stress Genes ( = 632, E ∪ I) and Genetic Adaptation Genes ( = 659, G ∪ I). The former were significantly enriched in pathways related to oxidative stress defense and metabolic adaptation, while the latter showed prominent enrichment in pathways associated with vascular remodeling and transcriptional regulation. emerged as a key regulatory factor in both gene sets, interacting with and to form the core of the protein-protein interaction (PPI) network. Machine learning identified , , and as critical genes. WGCNA identified key modules in hypoxia adaptation, where , , and promote the stabilization of and metabolic adaptation through the HIF-1 signaling pathway and glycolysis. These findings underscore the pivotal role of gene-environment interactions in hypoxic adaptation, offering novel perspectives for both livestock breeding programs and biomedical research initiatives.