Literature DB >> 25395665

The impact of macroscopic epistasis on long-term evolutionary dynamics.

Benjamin H Good1, Michael M Desai2.   

Abstract

Genetic interactions can strongly influence the fitness effects of individual mutations, yet the impact of these epistatic interactions on evolutionary dynamics remains poorly understood. Here we investigate the evolutionary role of epistasis over 50,000 generations in a well-studied laboratory evolution experiment in Escherichia coli. The extensive duration of this experiment provides a unique window into the effects of epistasis during long-term adaptation to a constant environment. Guided by analytical results in the weak-mutation limit, we develop a computational framework to assess the compatibility of a given epistatic model with the observed patterns of fitness gain and mutation accumulation through time. We find that a decelerating fitness trajectory alone provides little power to distinguish between competing models, including those that lack any direct epistatic interactions between mutations. However, when combined with the mutation trajectory, these observables place strong constraints on the set of possible models of epistasis, ruling out many existing explanations of the data. Instead, we find that the data are consistent with a "two-epoch" model of adaptation, in which an initial burst of diminishing-returns epistasis is followed by a steady accumulation of mutations under a constant distribution of fitness effects. Our results highlight the need for additional DNA sequencing of these populations, as well as for more sophisticated models of epistasis that are compatible with all of the experimental data.
Copyright © 2015 by the Genetics Society of America.

Entities:  

Keywords:  diminishing returns; epistasis; experimental evolution

Mesh:

Year:  2014        PMID: 25395665      PMCID: PMC4286683          DOI: 10.1534/genetics.114.172460

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  45 in total

1.  Long-Term Experimental Evolution in Escherichia coli. VIII. Dynamics of a Balanced Polymorphism.

Authors:  Daniel E Rozen; Richard E Lenski
Journal:  Am Nat       Date:  2000-01       Impact factor: 3.926

2.  Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence.

Authors:  Justin B Kinney; Anand Murugan; Curtis G Callan; Edward C Cox
Journal:  Proc Natl Acad Sci U S A       Date:  2010-05-03       Impact factor: 11.205

3.  Epistatic buffering of fitness loss in yeast double deletion strains.

Authors:  Lukasz Jasnos; Ryszard Korona
Journal:  Nat Genet       Date:  2007-02-25       Impact factor: 38.330

4.  Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletions.

Authors:  Robert P St Onge; Ramamurthy Mani; Julia Oh; Michael Proctor; Eula Fung; Ronald W Davis; Corey Nislow; Frederick P Roth; Guri Giaever
Journal:  Nat Genet       Date:  2007-01-07       Impact factor: 38.330

5.  An equivalence principle for the incorporation of favorable mutations in asexual populations.

Authors:  Matthew Hegreness; Noam Shoresh; Daniel Hartl; Roy Kishony
Journal:  Science       Date:  2006-03-17       Impact factor: 47.728

6.  Long-term dynamics of adaptation in asexual populations.

Authors:  Michael J Wiser; Noah Ribeck; Richard E Lenski
Journal:  Science       Date:  2013-11-14       Impact factor: 47.728

7.  Genome evolution and adaptation in a long-term experiment with Escherichia coli.

Authors:  Jeffrey E Barrick; Dong Su Yu; Sung Ho Yoon; Haeyoung Jeong; Tae Kwang Oh; Dominique Schneider; Richard E Lenski; Jihyun F Kim
Journal:  Nature       Date:  2009-10-18       Impact factor: 49.962

8.  Modular epistasis in yeast metabolism.

Authors:  Daniel Segrè; Alexander Deluna; George M Church; Roy Kishony
Journal:  Nat Genet       Date:  2004-12-12       Impact factor: 38.330

9.  Understanding the evolutionary fate of finite populations: the dynamics of mutational effects.

Authors:  Olin K Silander; Olivier Tenaillon; Lin Chao
Journal:  PLoS Biol       Date:  2007-04       Impact factor: 8.029

10.  A bayesian MCMC approach to assess the complete distribution of fitness effects of new mutations: uncovering the potential for adaptive walks in challenging environments.

Authors:  Claudia Bank; Ryan T Hietpas; Alex Wong; Daniel N Bolon; Jeffrey D Jensen
Journal:  Genetics       Date:  2014-01-07       Impact factor: 4.562

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  29 in total

Review 1.  Effective models and the search for quantitative principles in microbial evolution.

Authors:  Benjamin H Good; Oskar Hallatschek
Journal:  Curr Opin Microbiol       Date:  2018-12-06       Impact factor: 7.934

2.  Patterns and Mechanisms of Diminishing Returns from Beneficial Mutations.

Authors:  Xinzhu Wei; Jianzhi Zhang
Journal:  Mol Biol Evol       Date:  2019-05-01       Impact factor: 16.240

3.  The Nonstationary Dynamics of Fitness Distributions: Asexual Model with Epistasis and Standing Variation.

Authors:  Guillaume Martin; Lionel Roques
Journal:  Genetics       Date:  2016-10-21       Impact factor: 4.562

4.  Adaptation limits ecological diversification and promotes ecological tinkering during the competition for substitutable resources.

Authors:  Benjamin H Good; Stephen Martis; Oskar Hallatschek
Journal:  Proc Natl Acad Sci U S A       Date:  2018-10-15       Impact factor: 11.205

5.  Evolution of Mutation Rates in Rapidly Adapting Asexual Populations.

Authors:  Benjamin H Good; Michael M Desai
Journal:  Genetics       Date:  2016-09-19       Impact factor: 4.562

6.  Mutation bias can shape adaptation in large asexual populations experiencing clonal interference.

Authors:  Kevin Gomez; Jason Bertram; Joanna Masel
Journal:  Proc Biol Sci       Date:  2020-10-21       Impact factor: 5.349

Review 7.  Genomic investigations of evolutionary dynamics and epistasis in microbial evolution experiments.

Authors:  Elizabeth R Jerison; Michael M Desai
Journal:  Curr Opin Genet Dev       Date:  2015-09-14       Impact factor: 5.578

8.  Detecting epistasis from an ensemble of adapting populations.

Authors:  David M McCandlish; Jakub Otwinowski; Joshua B Plotkin
Journal:  Evolution       Date:  2015-08-20       Impact factor: 3.694

9.  Recombination Alters the Dynamics of Adaptation on Standing Variation in Laboratory Yeast Populations.

Authors:  Katya Kosheleva; Michael M Desai
Journal:  Mol Biol Evol       Date:  2018-01-01       Impact factor: 16.240

Review 10.  The causes of evolvability and their evolution.

Authors:  Joshua L Payne; Andreas Wagner
Journal:  Nat Rev Genet       Date:  2019-01       Impact factor: 53.242

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