When did human populations separate from each other? Did they go through bottlenecks? How much migration has there been between them? Answers to these questions about demographic history are encoded in the distribution of mutations within and between human populations. Sequences of entire genomes from hundreds of humans from around the world are now available, but reading the history recorded in these genomes requires new tools. This research will develop a computational method for learning demographic history from genomes that takes a novel approach to simulating not only the frequencies of mutations, but also the correlations between them. This research will also leverage existing genomic data to infer a detailed model for the demographic history of human populations within Africa, with a focus on Pygmy hunter-gatherers and neighboring agriculturalists.
Understanding African demographic history is key to understanding our species, because humans originated in Africa, and because Africa harbors more human diversity than any other region of the world. The demographic models developed in this research will unveil history and provide a framework for investigating human genetic adaptation to diverse environments. The computational method developed in this research will be applicable not only to humans, but also to other species. The method will be freely shared over the Internet, providing a powerful new tool for the population genomics community. In addition, the research will support and provide interdisciplinary training for a postdoctoral scientist, a graduate student, and two undergraduate students.
