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Moderate Genetic Diversity of MHC Genes in an Isolated Small Population of Black-and-White Snub-Nosed Monkeys ( Rhinopithecus bieti ).

Jibing YanChunmei SongJiaqi LiangYanni LaJiandong LaiRuliang PanZhi-Pang HuangBaoguo LiPei Zhang
Published in: Animals : an open access journal from MDPI (2024)
Genetic diversity is an essential indicator that echoes the natural selection and environmental adaptation of a species. Isolated small populations are vulnerable to genetic drift, inbreeding, and limited gene flow; thus, assessing their genetic diversity is critical in conservation. In this study, we studied the genetic diversity of black-and-white snub-nosed monkeys ( Rhinopithecus bieti ) using neutral microsatellites and five adaptive major histocompatibility complex (MHC) genes. Two DQA1 alleles, two DQB1 alleles, two DRB1 alleles, two DRB5 alleles, and three DPB1 alleles were isolated from a population. The results indicate that neutral microsatellites demonstrate a high degree of heterozygosity and polymorphism, while adaptive MHC genes display a high degree of heterozygosity and moderate polymorphism. The results also show that balancing selection has prominently influenced the MHC diversity of the species during evolution: (1) significant positive selection is identified at several amino acid sites (primarily at and near antigen-binding sites) of the DRB1 , DRB5 , and DQB1 genes; (2) phylogenetic analyses display the patterns of trans-species evolution for all MHC loci. This study provides valuable genetic diversity insights into black-and-white snub-nosed monkeys, which dwell at the highest altitude and have experienced the harshest environmental selection of all primates globally since the Pleistocene. Such results provide valuable scientific evidence and a reference for making or amending conservation strategies for this endangered primate species.
Keyphrases
  • genetic diversity
  • genome wide
  • genome wide identification
  • dna methylation
  • bioinformatics analysis
  • copy number
  • high intensity
  • genome wide analysis
  • gene expression
  • transcription factor