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Predicting mutational routes to new adaptive phenotypes
Umeå University, Faculty of Science and Technology, Department of Molecular Biology (Faculty of Science and Technology). New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand. (Peter Lind)ORCID iD: 0000-0003-1510-8324
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics. New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand ; 3 Santa Fe Institute, New Mexico, United States. (Eric Libby)
2019 (English)In: eLIFE, E-ISSN 2050-084X, Vol. 8, p. 1-31, article id e38822Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
eLife Sciences Publications , 2019. Vol. 8, p. 1-31, article id e38822
Keywords [en]
evolutionary forecasting, pseudomonas, biofilm, genetics
National Category
Evolutionary Biology Microbiology Other Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-155079DOI: 10.7554/eLife.38822ISI: 000455079000001Scopus ID: 2-s2.0-85059925871OAI: oai:DiVA.org:umu-155079DiVA, id: diva2:1276381
Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2023-03-23Bibliographically approved

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Lind, Peter ALibby, Eric

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CiteExportLink to record
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Citation style
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