CAREER: Dynamic models of isolation and admixture for community-scale population genomic inference

Cuny City College, New York NY

Investigators

Abstract

The rate at which one can increasingly obtain large amounts of DNA data quickly and easily has far outpaced the rate at which computational performance increases over time (Moore's law). To bridge the gap between this impending flood of data and our ability to analyze it, this research will develop computational tools and models that can accommodate the complexity inherent in analyzing genomic data at the level of multiple individuals across different species. This will allow answering long-standing and previously intractable questions about how communities of species form, what creates biodiversity, and how groups of species respond to climate change. The modeling and tool development will focus on the cyclical history of climate change that dominated the Earth for the last two million years with an emphasis on how the resulting cycles of species habitat retraction, expansion and extinction shape the genomic patterns of whole communities. The impending flood of genomic data will also transform society with the increasing availability of personal genomics kits. To anticipate how the public will increasingly become de facto scientific participants through personal genomics, the research will demonstrate the power, complexities and cautions of population genomic inference as applied to humans by implementing a genomic participant-based human population genomics course and three public events. Participants will optionally obtain vast amounts of non-medically relevant genomic data from themselves and this experiential component will enable communicating to the public about a wide array of complex issues relevant to medicine, history, evolution, ethics, statistics and information literacy.