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ZENODO
Dataset . 2016
License: CC 0
Data sources: ZENODO
DRYAD
Dataset . 2016
License: CC 0
Data sources: Datacite
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Data from: Diverse phenotypic and genetic responses to short-term selection in evolving Escherichia coli populations

Authors: Dillon, Marcus M.; Rouillard, Nicholas P.; Van Dam, Brian; Gallet, Romain; Cooper, Vaughn S.;

Data from: Diverse phenotypic and genetic responses to short-term selection in evolving Escherichia coli populations

Abstract

Beneficial mutations fuel adaptation by altering phenotypes that enhance the fit of organisms to their environment. However, the phenotypic effects of mutations often depend on ecological context, making the distribution of effects across multiple environments essential to understanding the true nature of beneficial mutations. Studies that address both the genetic basis and ecological consequences of adaptive mutations remain rare. Here, we characterize the direct and pleiotropic fitness effects of a collection of 21 first-step beneficial mutants derived from naïve and adapted genotypes used in a long-term experimental evolution of Escherichia coli. Whole-genome sequencing was able to identify the majority of beneficial mutations. In contrast to previous studies, we find diverse fitness effects of mutations selected in a simple environment and few cases of genetic parallelism. The pleiotropic effects of these mutations were predominantly positive but some mutants were highly antagonistic in alternative environments. Further, the fitness effects of mutations derived from the adapted genotypes were dramatically reduced in nearly all environments. These findings suggest that many beneficial variants are accessible from a single point on the fitness landscape, and the fixation of alternative beneficial mutations may have dramatic consequences for niche breadth reduction via metabolic erosion.

Supplementary Dataset 1: Data summary of alternative fitness metricsSummary of raw cell counts for the reference strain (Nai, Naf) and the mutant (Nbi, Nbf) at the beginning and end of each competition, along with calculations of growth rate difference between the two strains (Δrab), number of generations elapsed by the reference strain (G), selection coefficients (s), and Malthusian fitness (w). Raw cell counts at the end of the competition are multiplied by 106 to account for three days of 1:100 dilution and growth, but selection coefficients and Malthusian fitness are not corrected for the marker effect, as was the case for the Malthusian fitness data presented in the main text.SupplementaryDataset1.xlsxSupplementaryDataset2: Summary of mutation identification and filteringSummary of all putative mutations derived from REL606 and REL1206 that were identified by breseq prior to manual filtration. Mutations that passed our manual filtration criteria are highlighted using bolded text and the justification for discarding all of the remaining mutations is presented in each respective row.SupplementaryDataset2.xlsx

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Keywords

niche breadth, Beneficial mutations, adaptive history

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selected citations
These citations are derived from selected sources.
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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