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  Predicting mutational routes to new adaptive phenotypes

Lind, P. A., Libby, E., Herzog, J., & Rainey, P. B. (2019). Predicting mutational routes to new adaptive phenotypes. eLife, 8: e38822. Retrieved from https://doi.org/10.7554/eLife.38822.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0002-C8F8-5 Version Permalink: http://hdl.handle.net/21.11116/0000-0002-C8F9-4
Genre: Journal Article

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https://elifesciences.org/articles/38822 (Publisher version)
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 Creators:
Lind, Peter A., Author
Libby, Eric, Author
Herzog, Jenny, Author
Rainey, Paul B.1, Author              
Wittkopp, Patricia J., Contributor
Affiliations:
1Department Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_2421699              

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Free keywords: Pseudomonas fluorescens, experimental evolution, genetic architecture, wrinkly spreader, c-di-GMP, evolutionary forecasting
 Abstract: Predicting evolutionary change poses numerous challenges. Here we take advantage of the model bacterium Pseudomonas fluorescens in which the genotype-to-phenotype map determining evolution of the adaptive ‘wrinkly spreader’ (WS) type is known. We present mathematical descriptions of three necessary regulatory pathways and use these to predict both the rate at which each mutational route is used and the expected mutational targets. To test predictions, mutation rates and targets were determined for each pathway. Unanticipated mutational hotspots caused experimental observations to depart from predictions but additional data led to refined models. A mismatch was observed between the spectra of WS-causing mutations obtained with and without selection due to low fitness of previously undetected WS-causing mutations. Our findings contribute toward the development of mechanistic models for forecasting evolution, highlight current limitations, and draw attention to challenges in predicting locus-specific mutational biases and fitness effects.

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Language(s): eng - English
 Dates: 2018-06-032018-11-282019-01-082019
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
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Project name : Marsden Fund Council
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Funding organization : Royal Society of New Zealand

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Title: eLife
Source Genre: Journal
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Publ. Info: Cambridge : eLife Sciences Publications
Pages: - Volume / Issue: 8 Sequence Number: e38822 Start / End Page: - Identifier: ISSN: 2050-084X
CoNE: https://pure.mpg.de/cone/journals/resource/2050-084X