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Evolutionary genomics based on PacBio HiFi long-read sequencing data reveals the importance of structural variants in shaping population-specific differences between Chinese and Indian rhesus macaques (Macaca mulatta)

Maruki, T.; Versoza, C. J.; Jensen, J. D.; Pfeifer, S. P.

2026-05-29 evolutionary biology
10.64898/2026.05.27.728199 bioRxiv
Show abstract

Rhesus macaques (Macaca mulatta) are the most widely used non-human primate model for translational research relevant to human health and disease. Although several genetically distinct populations have been recognized across the species extensive habitat range in Asia, the majority of biomedical studies in the United States and abroad focuses on individuals of either Chinese or Indian descent. Notably, phenotypic differences exist between these two populations which can influence biomedical research outcomes; however, the genetic basis and molecular mechanisms underlying these differences are generally not well understood. Based on novel PacBio HiFi long-read sequencing data from 20 rhesus macaques -- ten of Chinese origin and ten of Indian origin -- we here characterize the genome-wide landscape of structural variation in these two biomedically-relevant populations. Our results highlight differences in the structural variant landscape affecting genes involved in neural communication and signaling pathways, in line with the known differences in temperament between the two populations. Furthermore, while the majority of discovered structural variants were located in intergenic and non-coding regions of the genome, 15 of the discovered population-specific structural variants were predicted to exhibit a high functional effect on genes associated with human disease, indicating that they may play an important role in shaping the differences in disease susceptibility between the populations. Taken together, by providing detailed insights into population-specific structural variation, this genomic resource will aid the design and interpretation of future studies aiming to link genotype, phenotype, and fitness in the context of human health and disease, and facilitate broader comparative analyses of structural variation as a force shaping genome evolution across primates.

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