Mid-Term Report Summary - EINME (Systematic investigation of epistasis in molecular evolution)
Mutations that occur in the genome impact the fitness of the organism, rarely improving its fate and, typically disrupting function and leading to severe consequences, such as disease. However, what happens when multiple mutations accumulate in the same genome is poorly understood. Do random mutations interact in some meaningful way? Or is their impact simply the sum of their individual contributions? Our project is aimed at answering these questions from a theoretical perspective and in a few controlled experiments. So far, in the confines of our project we first created a mathematical framework that allows us to model long-term effects of the interaction of mutations on protein evolution. We then used this model to understand a rich data set, which we obtained experimentally, where we introduced different combinations of mutations into a single protein and observed the impact of single mutations versus their combinations. We found that that interaction between mutations is crucial to explain the function of the protein with multiple mutations, for as many as 40% of observed genotypes. This result has implications for all studies that consider the effect of multiple genetic effects on the phenotype, such as the effect of multiple polymorphisms on diseases. However, whether or not such interactions pay a role in explaining complex human traits, such as complex disease, remains unknown.