Epistasis and empirical fitness landscapes

Biologists tend to focus on nuances — to the point that Rutherford considered the field as stamp-collecting — and very local properties of systems, leading at times to rather reductionist views. These approaches are useful for connecting to experiment, but can be shown to underspecify conceptual models that need a more holistic approach. In the case of fitness landscapes, the metric that biologists study is epistasis — the amount of between locus interactions — and is usually considered for the interaction of just two loci at a time; although Beerenwinkel et al. (2007a,b) have recently introduced a geometric theory of gene interaction for considering epistasis across any number of loci. In contrast, more holistic measures can be as simple as the number of peaks in the landscape, or the computational or as complicated as the global combinatorial features of interest to theoretical computer scientists. In this post I discuss connections between the two and provide a brief overview of the empirical work on fitness landscapes.

Epistasis in fitness graphs of two loci. Arrows point from lower fitness to higher fitness, and AB always has higher fitness than ab. From left to right no epistasis, sign epistasis, reverse sign epistasis.

Epistasis in fitness graphs of two loci. Arrows point from lower fitness to higher fitness, and AB always has higher fitness than ab. From left to right no epistasis, sign epistasis, reverse sign epistasis.


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