Doctoral Public Lecture | Mojgan Ezadian

Student Name: Mojgan Ezadian
Program: Mathematics
Thesis Title: Estimating mutation rate and effect size: a stochastic framework for microbial evolution

Room: MC 204

Abstract: This thesis investigates how mutations accumulate in laboratory experiments and how their outcomes can be interpreted. Using a combination of mathematical modeling and largescale simulations, we developed approaches to estimate key evolutionary parameters, including mutation rates and the distribution of fitness effects (DFE). First, we present a pure-birth simulation to estimate the spontaneous mutation rate to a mutator phenotype. Studies on the effects of positive and negative selection in mutation accumulation (MA) experiments demonstrate that beneficial mutations are substantially over-represented—an effect known as selection bias. To address this, we extend discrete- and continuous-time stochastic models to evaluate how realistic offspring distributions amplify selection bias in MA experiments and propose correction methods to recover the underlying DFE. Finally, we introduce multitype branching process models to capture the dynamics of interacting lineages, providing a general framework for studying the emergence of rare types through interactions. Across all approaches, we combine mathematical analysis with large-scale simulations to validate theoretical predictions and offer practical correction strategies for experimental data.

Please contact the Graduate Assistant in the program for further information: https://grad.uwo.ca/about_us/program_contacts.cfm.