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ZENODO
Dataset . 2012
License: CC 0
Data sources: ZENODO
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Research@WUR
Dataset . 2012
Data sources: Research@WUR
DRYAD
Dataset . 2012
License: CC 0
Data sources: Datacite
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Data from: Model and test in a fungus of the probability that beneficial mutations survive drift

Authors: Gifford, D.R.; de Visser, Arjan; Wahl, L.M.;

Data from: Model and test in a fungus of the probability that beneficial mutations survive drift

Abstract

Determining the probability of fixation of beneficial mutations is critically important for building predictive models of adaptive evolution. Despite considerable theoretical work, models of fixation probability have stood untested for nearly a century. However, recent advances in experimental and theoretical techniques permit the development of models with testable predictions. We developed a new model for the probability of surviving genetic drift, a major component of fixation probability, for novel beneficial mutations in the fungus Aspergillus nidulans, based on the life-history characteristics of its colony growth on a solid surface. We tested the model by measuring the probability of surviving drift in 11 adapted strains introduced into wild-type populations of different densities. We found that the probability of surviving drift increased with mutant invasion fitness, and decreased with wild-type density, as expected. The model accurately predicted the survival probability for the majority of mutants, yielding one of the first direct tests of the extinction probability of beneficial mutations.

mgr-escape-and-sector-dataMGR, escape and sector data

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Netherlands
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Keywords

Aspergillus nidulans

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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