Genealogical ancestors, admixture, and population history

This project develops and applies mathematical models of the process of genetic admixture, with an emphasis on understanding the structure of genealogies for individuals chosen at random from an admixed population. The project also develops new ways of understanding the timing and magnitude of the genetic contributions that have been made by source groups to an admixed population.

The research advances knowledge relevant to the study of human population history as well as population genetics in other species. The project supports undergraduate, graduate, and postdoctoral training and mentoring; development and dissemination tools for analyzing admixture through shared software, seminars and conferences; and public and community science education and engagement.

The project introduces new quantities useful for investigating admixture, studying distributions of the numbers of genealogical ancestors from specified source populations. It evaluates these quantities in mathematical models of admixture, using recursion equations that incorporate features such as changes over time in the admixture process, multiple models of mate choice, and source populations that contribute different numbers of males and females to the admixed population.

Through multidisciplinary interactions, the project will also deepen the understanding of the genetic history of specific populations. The new models from the project contribute mathematical theory and statistical methods to the study of admixture in human population genetics. Further, as admixture processes in non-human species share mathematical similarities with admixture processes in humans, the project additionally contributes tools useful for studying phenomena of hybridization and introgression in natural and agricultural populations.

This project includes funding from NSF programs: SBE Postdoctoral Research Fellowships (SBE/Office of the Assistant Director), Evolutionary Processes (BIO/Division of Environmental Biology), and Mathematical Biology (MPS/Division of Mathematical Sciences).

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.