Epistasis and constraints in fitness landscapes

TL;DR

This paper introduces new measures to quantify epistasis and constraints in high-dimensional fitness landscapes, aiding the understanding of genetic interactions and evolutionary pathways.

Contribution

It proposes two novel sets of measures for epistasis and constraints, with analytical properties and applications to experimental landscapes.

Findings

New measures effectively capture epistasis and constraints.

Measures can discriminate between different fitness landscape models.

Application to experimental data reveals insights into genetic interactions.

Abstract

Genotypic fitness landscapes are constructed by assessing the fitness of all possible combinations of a given number of mutations. In the last years, several experimental fitness landscapes have been completely resolved. As fitness landscapes are high-dimensional, their characterization relies on simple measures of their structure, which can be used as statistics in empirical applications. Here we propose two new sets of measures that explicitly capture two relevant features of fitness landscapes: epistasis and constraints. The first set contains new measures for epistasis based on the correlation of fitness effects of mutations. They have a natural interpretation, capture well the interaction between mutations, can be obtained analytically for most landscape models and can therefore be used to discriminate between different models. The second set contains measures of evolutionary constraints based on "chains" of forced mutations along fitness-increasing paths. Some of these measures are non-monotonic in the amount of epistatic interactions, but have instead a maximum for intermediate values. We further characterize the relationships of these measures to the ones that were previous proposed (e.g. number of peaks, roughness/slope, fraction of non-additive components, etc). Finally, we show how these measures can help uncovering the amount and the nature of epistatic interactions in two experimental landscapes.