It is widely believed that evolutionary processes are too slow to allow direct measurement of genetic changes. For this reason, most applications of evolutionary theory are historical in nature. A theory is tested by comparing its predictions to extant patterns of variation in nature, either within or across taxa. However, when evolutionary changes occur at a rapid pace, it is possible to directly test the dynamical predictions of evolutionary models. There are now many documented examples of rapidly evolving biological systems. One of our primary objectives is to construct and test models that predict observable changes in the genetic composition of populations. These "dynamical studies" augment historical analyses and directly address a wide range of fundamental questions in evolutionary biology.
At present, our laboratory is mainly concerned with quantitative trait evolution in the wildflower Mimulus guttatus (yellow monkeyflower). Given that most interesting traits are complex (influenced by both genes and the environment), quantitative genetics provides a natural framework for predicting trait evolution. We use a mixture of classical techniques (e.g. controlled crosses, inbreeding, and artificial selection), along with modern molecular approaches (e.g. QTL mapping). Principle questions are: (1) How do mutation, migration, genetic drift and natural selection interact to maintain genetic variation in nature? (2) What is the genetic architecture of variation in ecologically important traits such as flower size and pollen viability? (3) How does non-random mating, particularly the tendency of many plant species to self-fertilize, affect evolutionary change? and (4) Do genetic 'complexities' such as pleiotropy and epistasis qualitatively alter the evolutionary process?
A secondary interest in our laboratory is gene sequence evolution, with a particular focus on viral pathogens. Many viral pathogens, including the Human Immunodeficiency Virus (HIV), undergo extensive genetic evolution within a single host. Elucidating the causes and consequences of these genetic changes for disease transmission and pathogenesis is a major challenge for both evolutionary biology and epidemiology.