NIH R01 · 2025
Microbial Adaptation and the Statistics of Epistasis and Pleiotropy
PROJECT SUMMARY/ABSTRACT The overall goal of my research program is to understand adaptation in microbial populations, using a combination of mathematical modeling and high-throughput experimental evolution in budding yeast. At root, we aim to predict how evolution chooses probabilistically among different mutational trajectories, to determine the rate and outcomes of adaptation. In the short term, evolution depends primarily on the distribution of fitness effects of individual mutations. However, on longer timescales epistatic interactions between mutations can be crucial. Similarly, mutations often have different fitness effects in different environments (“pleiotropy for fitness”). This…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.