This work will enhance our ability to use DNA or other genetic data to make inferences about population structure and population history. It will allow us, for instance, to answer questions like "How much migration has occurred between these populations?" or "When did these populations diverge from each other?" In order to do this, a body of mathematical models that are used to describe patterns of genetic variation within and between populations will be extended. Thus, a secondary impact of the project will be an advance in the fields applied mathematics and probability theory. Further, two books and an interactive web site will be produced. The aim of these is to promote the teaching of the branch of population genetics used by most workers but rarely taught, called coalescent theory. The theoretical aspects of the work will focus on the analysis of population models in which different events happen at vastly different rates. For example, if migration rates are high, then migration events will happen much more often than mutation events, which tend to be very rare. When such differences in time scale occur, the analyses are simpler and the mathematical models have properties that make them interesting in their own right. These simplifications will be used to produce a battery of methods and tests, which empirical population geneticists can employ to study the history of natural populations. The books will bring the teaching of population genetics up to date with current research methods and ideas. Specifically, they will use and advocate the modern genealogical, or coalescent, approach to the subject. The coalescent approach considers the genealogical history of a sample of genetic data, and thus can be better suited to empirical work than classical population genetic approaches which model entire populations.
This project was originally funded as a CAREER award, and was converted to a Presidential Early Career Award for Engineers and Scientists (PECASE) award in May 2004.
