Gifford, DR, Krašovec, R, Aston, E, Belavkin, RV, Channon, A ORCID: 0000-0001-9224-4931 and Knight, CG (2018) Environmental pleiotropy and demographic history direct adaptation under antibiotic selection. Heredity, 121 (5). pp. 438-448. ISSN 1365-2540

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Abstract

Evolutionary rescue following environmental change requires mutations permitting population growth in the new environment. If change is severe enough to prevent most of the population reproducing, rescue becomes reliant on mutations already present. If change is sustained, the fitness effects in both environments, and how they are associated-termed 'environmental pleiotropy'-may determine which alleles are ultimately favoured. A population's demographic history-its size over time-influences the variation present. Although demographic history is known to affect the probability of evolutionary rescue, how it interacts with environmental pleiotropy during severe and sustained environmental change remains unexplored. Here, we demonstrate how these factors interact during antibiotic resistance evolution, a key example of evolutionary rescue fuelled by pre-existing mutations with pleiotropic fitness effects. We combine published data with novel simulations to characterise environmental pleiotropy and its effects on resistance evolution under different demographic histories. Comparisons among resistance alleles typically revealed no correlation for fitness-i.e., neutral pleiotropy-above and below the sensitive strain's minimum inhibitory concentration. Resistance allele frequency following experimental evolution showed opposing correlations with their fitness effects in the presence and absence of antibiotic. Simulations demonstrated that effects of environmental pleiotropy on allele frequencies depended on demographic history. At the population level, the major influence of environmental pleiotropy was on mean fitness, rather than the probability of evolutionary rescue or diversity. Our work suggests that determining both environmental pleiotropy and demographic history is critical for predicting resistance evolution, and we discuss the practicalities of this during in vivo evolution.

Item Type: Article
Additional Information: This is the final published version of the article (version of record). It first appeared online via Springer at http://doi.org/10.1038/s41437-018-0137-3 - please refer to any applicable terms of use of the publisher.
Divisions: Faculty of Natural Sciences > School of Computing and Maths
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Depositing User: Symplectic
Date Deposited: 05 Oct 2018 09:04
Last Modified: 25 Oct 2018 09:25
URI: http://eprints.keele.ac.uk/id/eprint/5404

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