Literature DB >> 22332770

Evolutionary insight from whole-genome sequencing of experimentally evolved microbes.

Jeremy R Dettman1, Nicolas Rodrigue, Anita H Melnyk, Alex Wong, Susan F Bailey, Rees Kassen.   

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.
© 2012 Blackwell Publishing Ltd.

Mesh:

Year:  2012        PMID: 22332770     DOI: 10.1111/j.1365-294X.2012.05484.x

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  69 in total

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5.  Bypass of genetic constraints during mutator evolution to antibiotic resistance.

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6.  Adaptation and heterogeneity of Escherichia coli MC1000 growing in complex environments.

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7.  The underlying structure of adaptation under strong selection in 12 experimental yeast populations.

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Review 8.  The dawn of evolutionary genome engineering.

Authors:  Csaba Pál; Balázs Papp; György Pósfai
Journal:  Nat Rev Genet       Date:  2014-05-28       Impact factor: 53.242

9.  Evolutionary genomics of epidemic and nonepidemic strains of Pseudomonas aeruginosa.

Authors:  Jeremy R Dettman; Nicolas Rodrigue; Shawn D Aaron; Rees Kassen
Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-09       Impact factor: 11.205

Review 10.  The functional basis of adaptive evolution in chemostats.

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Journal:  FEMS Microbiol Rev       Date:  2014-12-04       Impact factor: 16.408

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