Reconstructing Evolutionary History from Genomic Patterns of DNA Polymorphism
DNA variation among individuals reflects the culmination of evolutionary processes – mutation, recombination, migration, natural selection, and genetic drift – acting over many generations. As a result, the ability to survey variation at loci from throughout the genome provides unprecedented opportunities to understand evolution. Our laboratory integrates population genetic analyses of genome-wide polymorphism patterns with advances in computational genomics to reconstruct evolutionary processes in humans. Special emphasis is placed on combining variation across different classes of DNA variation, including single nucleotide polymorphisms (SNPs) microsatellites, and large-scale copy number variants (CNVs). Because these loci mutate at different rates, they reveal evolutionary events on contrasting timescales. Using this logic, we are developing new ways of comparing and combining variation at these loci to (i) find genes responsible for human adaptation, (ii) reconstruct human migration history, and (iii) identify genes that contribute to complex human diseases. Our first step toward the latter effort has been to describe linkage disequilibrium – the association between different loci, which determines the power of association studies of common diseases – between SNPs and microsatellites across the human genome for the first time (in a collaborative effort with Dr. Jim Weber at Prevention Genetics).
Peicheng Jing and Ryan Haasl are contributing to this project.