Michael M. DesaiDepartment of Organismic and Evolutionary Biology
Northwest Building, Room 435.20
52 Oxford Street, Cambridge, MA 02138
Phone: (617) 496-3613, Fax: (617) 496-2995,
Natural selection and other evolutionary forces lead to particular patterns of evolutionary dynamics, and they leave characteristic signatures on the genetic variation within populations. My group uses a combination of theory and experiments to study the dynamics and population genetics of natural selection in asexual populations such as microbes and viruses.
Theory: Evolutionary Dynamics and Population Genetics
A main goal of our theoretical work is to fill this gap in our understanding of the action of selection when linkage is important. This involves building theoretical models of evolutionary dynamics, and considering population genetics in the context of these models. Because selection tends to amplify the effects of rare mutations, this often involves situations where fluctuations are crucial, and out-of-equilibrium behavior is important. We have introduced several new approaches to analyzing evolutionary dynamics in such situations by developing techniques to understand the statistical behavior of large numbers of interacting random processes that are driven by fluctuations in a few rare types. This work has opened up new ways to understand the structure of genealogies and thus the statistics of genetic variation in these populations. We are using this approach to construct various types of effective coalescent approaches that provide a general framework for analyzing sequence data in the presence of selection.
A main challenge of experimental evolution is that much of the important dynamics that determines the long-term fate of individual mutations happens when those mutations are rare and therefore hard to observe experimentally. We have developed a system that allows us to quickly detect certain types of mutations when they are at frequencies of a fraction of a percent within a population, allowing us to directly observe these dynamics of certain rare mutants. This class of observable mutations provides a useful probe into evolutionary dynamics that can then be further supplemented by targeted sequencing efforts.
A second challenge is that some types of events are very unlikely to happen on laboratory timescales, but could still be crucial for long-term evolution of natural populations. There is also an inherent randomness to evolution, so identical populations will often evolve very differently. These problems inspired us to develop high-throughput approaches to experimental evolution that allow us to maintain thousands of evolving lines simultaneously. This has allowed us to observe classes of mutational events that are thought to be quite important in nature, but are rare enough that they have not been seen in a systematic way in earlier experiments. It also gives us power to make use of the information contained in the variation we observe in outcomes between identically evolved populations. We are currently taking advantage of these high-throughput techniques to investigate a variety of questions, such as the role of geographic structure in adaptation and the statistical structure of epistasis among beneficial mutations.
Weissman, D.W., Desai, M.M., Fisher, D.S., and Feldman, M.W. The Rate at Which Asexual Popualtions Cross Fitness Valleys. Theoretical Population Biology. 75:286-300 (2009).
Desai, M.M. Reverse Evolution and Evolutionary Memory. Nature Genetics 41:142-3 (2009).
Gresham, D., Desai, M.M., Tucker, C.M., Jenq, H.T., Pai, D.A., Ware, A., DeSevo, C.G., Botstein, D., and Dunham, M.J. The Repertoire and Dynamics of Evolutionary Adaptations to Controlled Nutrient-Limited Environments in Yeast. PLoS Genetics 4: e1000303 (2008).
Desai, M.M. and Plotkin, J.B. Finite Site Effects on the Polymorphism Frequency Spectrum Under Directional Selection. Genetics 180:2175-91 (2008).
Fogle, C.A., Nagle, J.L., and Desai, M.M. Clonal Interference, Multiple Mutations, and Adaptation in Large Asexual Populations. Genetics 180:2163-73 (2008).
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