Reconstructing recent and ancient gene flow events and their impact on biological processes and traits
Approved Research ID: 98362
Approval date: April 17th 2023
A central goal of human genetics is to understand the link between genotypic and phenotypic variation, including disease risk and human adaptation. Over the past decade, researchers have discovered thousands of disease and adaptive variants by performing genome-wide association studies and scans of natural selection that can inform new diagnostics and treatments. However, many populations with mixed ancestry (or admixed groups) such as South Asians, are often excluded from these surveys due to methodological challenges for analyzing admixed genomes. In this proposal, we develop computational and statistical methods to characterize population mixture across multiple timescales in diverse populations. These methods include identifying the ancestry of chromosomal segments across the genome (i.e., local ancestry) and leveraging this information to localize disease variants and targets of selection. We will also develop a framework to examine the mutation rate and spectrum across ancestry backgrounds and over time. We will evaluate and apply the method to the UK Biobank data and make the summary statistics and software we develop available for use to other researchers. Application of our methods to rich UK Biobank dataset will reveal novel associations and deepen our understanding of population history and genetic architecture of complex traits.