Genomic Patterns of Polymorphism in Primates

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With the completion of the HapMap project and the ongoing efforts of the 1000 genomes project, a nearly comprehensive catalog of DNA sequence variants will soon become available for human populations. These data will be very informative for elucidating the historical forces that have shaped patterns of variation over time. To help put this information in perspective, this study proposes to gather large-scale sequence polymorphism data from a broad panel of eight primate species. Importantly, this panel includes species that are of fundamental interest to biomedical research and have genome sequencing projects that are completed or underway. A major goal is to infer the relative influence of a number of population genetic processes that differentially affect the X chromosome versus autosomes, such as changes in population size and sex-biased migration, natural selection (e.g., background and positive directional selection), and sexual selection (i.e., higher variance in male versus female reproductive success). To develop a comparative framework, the chosen set of 8 primate species represents a wide range of different mating strategies and dispersal patterns, including monogamous pairs (e.g., gibbons), single male multi-female groups (gorillas, orangutans, baboons), and multi-male multi-female groups (chimps, baboons, macaques). To disentangle the relative influence of demographic and selective forces, this study targets a combination of 300 genic and non-genic regions on the X chromosome and autosomes. The experimental design employs DNA capture arrays to enrich for 1.8 Mb of target DNA from 10 individuals from each species. The target DNA will then be sequenced to a depth of 40-80-fold coverage through massively parallel sequencing technology. The quality of the next generation sequence data will be assessed through comparison with 100 Kb of PCR-amplified DNA sequenced by conventional Sanger methodology. This study will help determine to what extent behavioral observations and morphological measurements are predictive of genomic patterns of variation, and what role natural selection plays in shaping fine-scale patterns of genetic variability. This information will also serve as a model for the population genetics of human variation. Moreover, it is essential for elucidating the factors that have affected genetic variation in species that serve as major biomedical models for humans. Establishing baseline levels of neutral polymorphism and linkage disequilibrium in these species will facilitate the proper design and analysis of both candidate gene studies and genome-wide association studies to identify the genetic determinants of complex traits.