Genomic Patterns of Polymorphism in Primates

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.