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Critical mutation rate in a population with horizontal gene transfer
Author(s) -
Elizabeth Aston,
Alastair Chan,
Roman V. Belavkin,
Danna R. Gifford,
Rok Krašovec,
Christopher G. Knight
Publication year - 2017
Language(s) - English
Resource type - Conference proceedings
DOI - 10.7551/ecal_a_074
Subject(s) - biology , horizontal gene transfer , population , mutation rate , robustness (evolution) , crossover , genetics , evolutionary biology , mutation , population size , exponential growth , genetic fitness , gene , phylogenetics , computer science , demography , mathematics , machine learning , mathematical analysis , sociology
Horizontal gene transfer (HGT) enables segments of DNA to be transferred between individuals in a population in addition to from parent to child. It is a prominent process in bacterial reproduction. Existing in silico models have succeeded in predicting when HGT will occur in evolving bacterial populations, and have utilised the concept of HGT in evolutionary algorithms. Here we present a genetic algorithm designed to model the process of bacterial evolution in a fitness landscape in which individuals with greater mutational robustness can outcompete those with higher fitness when a critical mutation rate (CMR) is exceeded. We show that the CMR has an exponential dependence on population size and can be lowered by HGT in both clonal and non-clonal populations. A population reproducing clonally has a higher CMR than one in which individuals undergo crossover. Allowing HGT only from donors with a non-zero fitness prevents HGT from lowering the CMR. In all cases the change in CMR with population size is grea...

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