Genome-wide copy number variation drives adaptive evolution in Macaca mulatta populations
Yun Liu1, Lin Zhang1, Xianlin Jin1
1Key Laboratory of Bio-Resources and Eco-Environment (Ministry of Education), College of Life Sciences, Sichuan University, Chengdu, Sichuan 610065, China.
None:
Copy number variation (CNV) represents a significant contributor to intraspecific genomic diversity, yet remains under-characterized in rhesus macaque (Macaca mulatta) populations. In this study, we performed whole-genome sequencing of 8 M. m. lasiotis individuals and integrated these with 6 subspecies-representative genomes, yielding a comparative dataset of 60 rhesus macaque genomes. Utilizing a read-depth-based approach for CNV detection, our analysis identified ∼59.6 Mb (2.2% of the reference genome) exhibiting CNV. We established a comprehensive CNV map consisting of 1,272 nonoverlapping CNV regions (CNVRs) across the M. mulatta genome. Hierarchical clustering analysis revealed discordance between CNVR-derived population structure and SNV-based phylogenetic relationships among Chinese subspecies. Comparative genomic analysis identified highly differentiated CNVRs between Indian and Chinese populations enriched for genes associated with immune response and xenobiotic metabolism. Subspecies-specific CNVRs (su_CNVRs) showed functional enrichment in pathways related to environmental adaptation and phenotypic variation. Notably, M. m. tcheliensis exhibited higher gene copies in METRNL and FBP1/FBP2 genes than other subspecies, potentially helping it adapt to cold environments and enhance gluconeogenesis capacity under food scarcity in the cold season. Furthermore, we identified 6 body size-associated genes with considerable CNV among different subspecies, highlighting CNV-mediated regulation of body size in M. mulatta subspecies. This investigation not only elucidates the evolutionary significance of CNVs in shaping genomic architecture and adaptive traits in M. mulatta, but also establishes a foundational resource for future population genetics studies utilizing structural variation markers.
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