March 12th, Claudia Bank: Shifting fitness landscapes in response to altered environments

About Claudia:

Claudia Bank

Claudia Bank

Claudia Bank is a postdoc in Jeffrey Jensen’s lab at the École Polytéchnique Fédérale de Lausanne in Switzerland, and currently spending a semester at UC Berkeley as a Simons- Berkeley fellow in the program “Evolutionary Biology and the Theory of Computing”. Following a Master’s degree in Mathematics from Germany, she obtained her PhD in Population Genetics under the supervision of Joachim Hermisson in Vienna, Austria.

Claudia’s research is focused on the study of evolution – and in particular, the population genetics of adaptation and speciation – at the interface between theoretical and empirical biology. The approaches she uses involve theoretical modeling, computational methods, and statistical data analysis.

Talk: Shifting fitness landscapes in response to altered environments

One of the most controversial questions in evolutionary biology is the role of adaptation in molecular evolution. After decades of debate between selectionists and neutralists, new high-throughput methods are beginning to illuminate the full distribution of fitness effects of new mutations. Here, we shed light on the adaptive potential in Saccharomyces cerevisiae by presenting systematic high-throughput fitness measurements for 560 point mutations in a region of Hsp90 under six environmental conditions. Under elevated salinity, we observe numerous beneficial mutations, all of which are observed to be associated with high costs of adaptation. We thus demonstrate that an essential protein can harbor adaptive potential upon an environmental challenge, and report a remarkable fit of the data to Fisher’s geometric model. In addition, we compare the differences in the DFEs resulting from mutations covering 1, 2 and 3 nucleotide steps from the wild type – showing that multiple-step mutations harbor more potential for adaptation in challenging environments, but also tend to be more deleterious in the standard environment. We utilize a Bayesian MCMC modeling framework to evaluate the statistical significance of the results – showing a remarkable accuracy of the experimental approach that allows us, e.g., to identify a deleterious synonymous mutation under standard conditions.

Seminar details

Wednesday March 12th, 2014
1:00 PM Lunch (sign up below)
1:15 PM Seminar
Location: Clark Center S360
If you would like to speak with Claudia, contact Pleuni Pennings (pleuni@stanford.edu)

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