The population genomics of rhesus macaques (Macaca mulatta) based on whole-genome sequences

  1. Jeffrey Rogers1,2
  1. 1Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas 77030, USA;
  2. 2Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA;
  3. 3University of Texas Health Science Center, Houston, Texas 77030, USA;
  4. 4Southwest National Primate Research Center, San Antonio, Texas 78227, USA;
  5. 5Department of Human Genetics, University of California, Los Angeles, California 90095, USA;
  6. 6Oregon National Primate Research Center, Beaverton, Oregon 97006, USA;
  7. 7North Carolina Museum of Natural Sciences, Raleigh, North Carolina 27601, USA;
  8. 8Biological and Biomedical Sciences, North Carolina Central University, Durham, North Carolina 27707, USA;
  9. 9Department of Evolutionary Anthropology, Duke University, Durham, North Carolina 27708, USA;
  10. 10Yerkes National Primate Research Center, Atlanta, Georgia 30322, USA;
  11. 11California National Primate Research Center, Davis, California 95616, USA;
  12. 12School of Mathematical and Natural Sciences, Arizona State University, Phoenix, Arizona 85004, USA;
  13. 13Tulane National Primate Research Center, Covington, Louisiana 70433, USA;
  14. 14Center for Stem Cell and Translational Medicine, Anhui University, Anhui, China 230601;
  15. 15Department of Neurobiology, Duke University, Durham, North Carolina 27708, USA;
  16. 16Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA;
  17. 17New England National Primate Research Center, Southborough, Massachusetts 01772, USA;
  18. 18Wisconsin National Primate Research Center, Madison, Wisconsin 53711, USA
  1. Corresponding author: Jr13{at}bcm.edu
  • Present addresses: 19Department of Genomic Medicine, MD Anderson Cancer Center, Houston, TX 77030, USA; 20Department of Pathology, Baylor College of Medicine, Houston, TX 77030, USA; 21Illumina Corporation, San Diego, CA 92122, USA; 22University of Mississippi Medical Center, Jackson, MS 39216, USA

Abstract

Rhesus macaques (Macaca mulatta) are the most widely used nonhuman primate in biomedical research, have the largest natural geographic distribution of any nonhuman primate, and have been the focus of much evolutionary and behavioral investigation. Consequently, rhesus macaques are one of the most thoroughly studied nonhuman primate species. However, little is known about genome-wide genetic variation in this species. A detailed understanding of extant genomic variation among rhesus macaques has implications for the use of this species as a model for studies of human health and disease, as well as for evolutionary population genomics. Whole-genome sequencing analysis of 133 rhesus macaques revealed more than 43.7 million single-nucleotide variants, including thousands predicted to alter protein sequences, transcript splicing, and transcription factor binding sites. Rhesus macaques exhibit 2.5-fold higher overall nucleotide diversity and slightly elevated putative functional variation compared with humans. This functional variation in macaques provides opportunities for analyses of coding and noncoding variation, and its cellular consequences. Despite modestly higher levels of nonsynonymous variation in the macaques, the estimated distribution of fitness effects and the ratio of nonsynonymous to synonymous variants suggest that purifying selection has had stronger effects in rhesus macaques than in humans. Demographic reconstructions indicate this species has experienced a consistently large but fluctuating population size. Overall, the results presented here provide new insights into the population genomics of nonhuman primates and expand genomic information directly relevant to primate models of human disease.

Footnotes

  • [Supplemental material is available for this article.]

  • Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.204255.116.

  • Freely available online through the Genome Research Open Access option.

  • Received January 11, 2016.
  • Accepted October 12, 2016.

This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

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