Data from: Selection biases the prevalence and type of epistasis along adaptive trajectories

The contribution to an organism's phenotype from one genetic locus may depend upon the status of other loci. Such epistatic interactions among loci are now recognized as fundamental to shaping the process of adaptation in evolving populations. Although little is known about the structure of epistasis in most organisms, recent experiments with bacterial populations have concluded that antagonistic interactions abound and tend to de-accelerate the pace of adaptation over time. Here, we use the NK model of fitness landscapes to examine how natural selection biases the mutations that substitute during evolution based on their epistatic interactions. We find that, even when beneficial mutations are rare, these biases are strong and change substantially throughout the course of adaptation. In particular, epistasis is less prevalent than the neutral expectation early in adaptation and much more prevalent later, with a concomitant shift from predominantly antagonistic interactions early in adaptation to synergistic and sign epistasis later in adaptation. We observe the same patterns when re-analyzing data from a recent microbial evolution experiment. These results show that when the order of substitutions is not known, standard methods of analysis may suggest that epistasis retards adaptation when in fact it accelerates it.

Identifier
DOI https://doi.org/10.5061/dryad.f468j
PID https://nbn-resolving.org/urn:nbn:nl:ui:13-06-by6s
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:83845
Provenance
Creator Draghi, Jeremy A.; Plotkin, Joshua B.
Publisher Data Archiving and Networked Services (DANS)
Publication Year 2013
Rights info:eu-repo/semantics/openAccess; License: http://creativecommons.org/publicdomain/zero/1.0; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Representation
Resource Type Dataset
Discipline Life Sciences; Medicine