Genetic Interactions and Fitness Landscapes

Darwinian fitness of genotypes in a natural population is very hard to measure in practice. To address this challenge, we developed quantitative tools to make inference about epistatic gene interactions when the fitness landscape is only incompletely determined, for example, due to imprecise measurements or partial observations. We demonstrate that higher order genetic interactions can often be inferred for fitness rank orders, where all genotypes are ordered according to fitness, and even for partial fitness orders. In this talk, I will present a complete characterization of rank orders that imply higher order epistasis and an efficient algorithm for detecting such interactions, and show how this can be applied to detect interactions in various biological settings. I will also describe the progress we have made on the way to achieve a similar characterization for fitness graphs and partial fitness orders, and conclude with open problems.