Expanding whole exome resequencing into non-human primates

Abstract

Background: Complete exome resequencing has the power to greatly expand our understanding of non-human primate genomes. This includes both a better appreciation of the variation that exists in non-human primate model species, but also an improved annotation of their genomes. By developing an understanding of the variation between individuals, non-human primate models of human disease can be better developed. This effort is hindered largely by the lack of comprehensive information on specific non-human primate genetic variation and the costs of generating these data. If the tools that have been developed in humans for complete exome resequencing can be applied to closely related non-human primate species, then these difficulties can be circumvented.

Results: Using a human whole exome enrichment technique, chimpanzee and rhesus macaque samples were captured alongside a human sample and sequenced using standard next-generation methodologies. The results from the three species were then compared for efficacy. The chimpanzee sample showed similar coverage levels and distributions following exome capture based on the human genome as the human sample. The rhesus macaque sample showed significant coverage in protein-coding sequence but significantly less in untranslated regions. Both chimpanzee and rhesus macaque showed significant numbers of frameshift mutations compared to self-genomes and suggest a need for further annotation.

Conclusions: Current whole exome resequencing technologies can successfully be used to identify coding-region variation in non-human primates extending into old world monkeys. In addition to identifying variation, whole exome resequencing can aid in better annotation of non-human primate genomes.

Figure 1

Human coverage compared to cross-species coverage. (a,b) Scatter plots showing the coverage level for each coding exon from human sample reads on human genome annotation compared to chimpanzee sample reads on human genome annotation (a) or rhesus sample reads on human genome annotation (b). (c,d) Histograms showing the difference between human and cross-species coverage, chimpanzee (c) or rhesus macaque (d), demonstrating the effects of species bias in capture efficacy.

Figure 2

Coverage compared to divergence. (a,b) Scatter plots showing the relationship between coverage and divergence from human for each coding exon in chimpanzee (a) and rhesus macaque (b). (c,d) Scatter plots also show the relationship between divergence from human and coverage differences between human and chimpanzee (c) and rhesus macaque (d).