Unveiling the Genomic Landscape of Yan Goose (Anser cygnoides): Insights into Population History and Selection Signatures for Growth and Adaptation

The Yan goose (YE, Anser cygnoides) is a valuable indigenous poultry genetic resource, renowned for its superior meat quality and environmental adaptability. Despite its economic importance, the genetic basis underlying these adaptive traits remains unclear. In this study, we employed whole-genome resequencing (WGS) to perform high-throughput sequencing on a conserved population of 15 samples. Bioinformatic analyses were conducted to systematically evaluate the population’s genetic structure, and a genome-wide scan for selection signals related to economically significant traits was performed using the integrated haplotype score (iHS) method. An average of 4.43 million high-quality SNPs were identified, which were predominantly located in intergenic and intronic regions. Population structure analysis revealed a close genetic relationship within the conserved population of YE, with no significant lineage stratification observed. Pairwise sequentially Markovian coalescent (PSMC) analysis indicated that the YE underwent a severe genetic bottleneck during the Last Glacial Maximum (LGM), followed by gradual population recovery in the early Neolithic period. Genome-wide selection signal scanning identified multiple genomic regions under strong selection, annotating key genes associated with growth and development (e.g., GHRL, AKT1, and MAPK3), lipid deposition (e.g., PLPP4, SAMD8, and LPIN1), and disease resistance and stress resilience (e.g., TP53, STAT3). Functional enrichment analysis revealed significant enrichment of these genes in pathways related to glycerophospholipid metabolism (p < 0.01), purine metabolism (p < 0.01), and immune response (p < 0.01). This study not only provides a theoretical foundation for the scientific conservation of the YE germplasm resources but also offers valuable genomic resources for identifying functional genes underlying important economic traits and advancing molecular breeding strategies.