Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

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, simple measures of their structure are used as statistics in empirical applications. Epistasis is one of the most relevant features of fitness landscapes. Here we propose a new natural measure of the amount of epistasis based on the correlation of fitness effects of mutations. This measure has a natural interpretation, captures well the interaction between mutations and can be obtained analytically for most landscape models. We discuss how this measure is related to previous measures of epistasis (number of peaks, roughness/slope, fraction of sign epistasis, Fourier-Walsh spectrum) and how it can be easily extended to landscapes with missing data or with fitness ranks only. Furthermore, the dependence of the correlation of fitness effects on mutational distance contains interesting information about the patterns of epistasis. This dependence can be used to uncover the amount and nature of epistatic interactions in a landscape or to discriminate between different landscape models.

Original publication

DOI

10.1016/j.jtbi.2016.01.037

Type

Journal article

Journal

Journal of theoretical biology

Publication Date

05/2016

Volume

396

Pages

132 - 143

Addresses

Evolution Paris-Seine (UMR 7138) and Atelier de Bio-Informatique, UPMC, Paris, France; SMILE, CIRB (UMR 7241), Collège de France, Paris, France; The Pirbright Institute, Woking, United Kingdom. Electronic address: luca.ferretti@gmail.com.

Keywords

Epistasis, Genetic, Genotype, Mutation, Models, Genetic