Evolutionary insight from whole‐genome sequencing of experimentally evolved microbes

DETTMAN, JEREMY R.; RODRIGUE, NICOLAS; MELNYK, ANITA H.; WONG, ALEX; BAILEY, SUSAN F.; KASSEN, REES

doi:10.1111/j.1365-294x.2012.05484.x

Cited by 160Evolution and Genetic DynamicsGenomics and Phylogenetic StudiesLanguage and cultural evolution

Evolutionary insight from whole‐genome sequencing of experimentally evolved microbes

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DETTMAN, JEREMY R., RODRIGUE, NICOLAS, MELNYK, ANITA H., WONG, ALEX, BAILEY, SUSAN F., KASSEN, REES·2012·Molecular Ecology

DOI 10.1111/j.1365-294x.2012.05484.x

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Abstract

Experimental evolution (EE) combined with whole‐genome sequencing (WGS) has become a compelling approach to study the fundamental mechanisms and processes that drive evolution. Most EE‐WGS studies published to date have used microbes, owing to their ease of propagation and manipulation in the laboratory and relatively small genome sizes. These experiments are particularly suited to answer long‐standing questions such as: How many mutations underlie adaptive evolution, and how are they distributed across the genome and through time? Are there general rules or principles governing which genes contribute to adaptation, and are certain kinds of genes more likely to be targets than others? How common is epistasis among adaptive mutations, and what does this reveal about the variety of genetic routes to adaptation? How common is parallel evolution, where the same mutations evolve repeatedly and independently in response to similar selective pressures? Here, we summarize the significant findings of this body of work, identify important emerging trends and propose promising directions for future research. We also outline an example of a computational pipeline for use in EE‐WGS studies, based on freely available bioinformatics tools.

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Selection for improved fitness in a specialized environment often leads to significant trade-offs in other stressful or selective conditions.
“It should be noted that selection for improved fitness in a specialized environment often leads to significant trade-offs in other stressful or selective conditions [19].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [19]

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J . R . D E T T M A N E T A L . Ó 2012 Blackwell Publishing Ltd 1365294x, 2012, 9, Downloaded from https://onlinelibrary.wiley.com/doi/10.1111/j.1365-294X.2012.05484.x by Readcube (Labtiva Inc.), Wiley Online Library on [16/08/2023]. See the Terms and Conditions (https://onlinelibrary.wiley.com/terms-and-conditions) on Wiley Online Library for rules of use; OA articles are governed by the applicable Creative Commons License · DOI

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Authors: DETTMAN, J. R., RODRIGUE, N., MELNYK, A. H., WONG, A., BAILEY, S. F., & KASSEN, R.
Affiliations: University of Ottawa (CA)
Agriculture and Agri-Food Canada (CA)
Carleton University (CA)
Corresponding author: DETTMAN, JEREMY R.
ORCID: RODRIGUE, NICOLAS
WONG, ALEX
BAILEY, SUSAN F.
KASSEN, REES
Venue: Molecular Ecology
Publisher: Wiley
Published: 2012-02-14
Volume: 21
Issue: 9
Pages: 2058-2077
ISSN: 0962-1083 (ISSN-L)
1365-294X
DOI: 10.1111/j.1365-294x.2012.05484.x
OpenAlex: W1813843188
Cited by: 160
References: 126
Citations by year: 2026: 4 · 2025: 4 · 2024: 23 · 2023: 3 · 2022: 4 · 2021: 8 · 2020: 3 · 2019: 13 · 2018: 9 · 2017: 14 · 2016: 17 · 2015: 17 · 2014: 19 · 2013: 18 · 2012: 4
FWCI: 2.27
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
doi.wiley.com/10.1002/tdm_license_1.1 (tdm, 1295 d)
Locations: Molecular Ecology (publishedVersion)
PubMed (publishedVersion)
Carleton University's Institutional Repository (MacOdrum Library, Carleton University) (submittedVersion, other-oa)
Funders: Natural Sciences and Engineering Research Council of Canada
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Social Sciences › Cultural Studies › Language and cultural evolution
Keywords: experimental evolution, whole genome sequencing, adaptive mutation, epistasis, parallel evolution, computational pipeline, bioinformatics software, microbial evolution
MeSH terms: Bacteria, Chromosome Mapping, Chromosomes, Bacterial, Fungi, Chromosomes, Fungal, Genome, Bacterial, Genome, Fungal, Sequence Analysis, DNA, Directed Molecular Evolution, Evolution, Molecular, High-Throughput Nucleotide Sequencing

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Evolutionary insight from whole‐genome sequencing of experimentally evolved microbes

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