Macaca is of great importance in evolutionary and biomedical research. Aiming at elucidating genetic diversity patterns and potential biomedical applications of macaques, we characterized single nucleotide variations (SNVs) of six Macaca species based on the reference genome of Macaca mulatta. Using eight whole-genome sequences, representing the most comprehensive genomic SNV study in Macaca to date, we focused on discovery and comparison of nonsynonymous SNVs (nsSNVs) with bioinformatic tools. We observed that SNV distribution patterns were generally congruent among the eight individuals. Outlier tests of nsSNV distribution patterns detected 319 bins with significantly distinct genetic divergence among macaques, including differences in genes associated with taste transduction, homologous recombination, and fat and protein digestion. Genes with specific nsSNVs in various macaques were differentially enriched for metabolism pathways, such as glycolysis, protein digestion and absorption. On average, 24.95% and 11.67% specific nsSNVs were putatively deleterious according to PolyPhen2 and SIFT4G, respectively, among which the shared deleterious SNVs were located in 564–1981 genes. These genes displayed enrichment signals in the ‘obesity-related traits’ disease category for all surveyed macaques, confirming that they were suitable models for obesity related studies. Additional enriched disease categories were observed in some macaques, exhibiting promising potential for biomedical application. Positively selected genes identified by PAML in most tested Macaca species played roles in immune and nervous system, growth and development, and fat metabolism. We propose that metabolism and body size play important roles in the evolutionary adaptation of macaques.
CITATION STYLE
Li, J., Fan, Z., Sun, T., Peng, C., Yue, B., & Li, J. (2018). Comparative genome-wide survey of single nucleotide variation uncovers the genetic diversity and potential biomedical applications among Six macaca species. International Journal of Molecular Sciences, 19(10). https://doi.org/10.3390/ijms19103123
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