Genome-wide analysis reveals key SNPs linked to local adaptation in Chinese pig breeds, suggesting climate resilience strategies.
Local adaptation allows animal populations to persist in diverse and changing environments, yet its genomic underpinnings remain poorly characterized in livestock. Chinese indigenous pigs, renowned for their rich phenotypic and ecological diversity, offer a powerful model for investigating environmental adaptation. Here, we integrated whole-genome resequencing data, environmental variables, genotype–environment association (GEA) analyses, and functional annotation to explore the adaptive genomic landscape of 46 native pig breeds across China. Based on 578 individuals and 17.7 million SNPs, we performed genome-wide GEA using latent factor mixed models (LFMMs), identifying 8644 SNPs significantly associated with environmental factors, including 310 linked to precipitation in the wettest quarter (BIO16). Redundancy analysis (RDA) and gradient forest modeling identified BIO16 as a major environmental driver of genomic variation. Functional annotation of BIO16-associated SNPs revealed significant enrichment in regulatory elements and genes highly expressed in the lung, spleen, hypothalamus, and intestine, implicating immune and metabolic pathways in local adaptation. Among the candidate loci, MS4A7 exhibited strong association signals, population differentiation, and tissue-specific regulation, suggesting a role in precipitation-mediated adaptation. This work enhances our understanding of livestock adaptation and informs climate-resilient conservation and breeding strategies.
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Liu et al. (2025) studied this question.
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