Literature DB >> 12399403

Evaluating the impact of population bottlenecks in experimental evolution.

Lindi M Wahl1, Philip J Gerrish, Ivan Saika-Voivod.   

Abstract

Experimental evolution involves severe, periodic reductions in population size when fresh media are inoculated during serial transfer. These bottlenecks affect the dynamics of evolution, reducing the probability that a beneficial mutation will reach fixation. We quantify the impact of these bottlenecks on the evolutionary dynamics, for populations that grow exponentially between transfers and for populations in which growth is curbed by a resource-limited environment. We find that in both cases, mutations that survive bottlenecks are equally likely to occur, per unit time, at all times during the growth phase. We estimate the total fraction of beneficial mutations that are lost due to bottlenecks during experimental evolution protocols and derive the "optimal" dilution ratio, the ratio that maximizes the number of surviving beneficial mutations. Although more severe dilution ratios are often used in the literature, we find that a ratio of 0.1-0.2 minimizes the chances that rare beneficial mutations are lost. Finally, we provide a number of useful approximate results and illustrate our approach with applications to experimental evolution protocols in the literature.

Mesh:

Year:  2002        PMID: 12399403      PMCID: PMC1462272     

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


  17 in total

1.  Test tube evolution catches time in a bottle.

Authors:  T Appenzeller
Journal:  Science       Date:  1999-06-25       Impact factor: 47.728

2.  The probability that beneficial mutations are lost in populations with periodic bottlenecks.

Authors:  L M Wahl; P J Gerrish
Journal:  Evolution       Date:  2001-12       Impact factor: 3.694

3.  Evolution by small steps and rugged landscapes in the RNA virus phi6.

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Journal:  Genetics       Date:  1999-03       Impact factor: 4.562

4.  Evolution in Mendelian Populations.

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5.  Adaptive radiation in a heterogeneous environment.

Authors:  P B Rainey; M Travisano
Journal:  Nature       Date:  1998-07-02       Impact factor: 49.962

6.  The probability of fixation in populations of changing size.

Authors:  S P Otto; M C Whitlock
Journal:  Genetics       Date:  1997-06       Impact factor: 4.562

7.  Evolution of high mutation rates in experimental populations of E. coli.

Authors:  P D Sniegowski; P J Gerrish; R E Lenski
Journal:  Nature       Date:  1997-06-12       Impact factor: 49.962

8.  Reducing antibiotic resistance.

Authors:  S J Schrag; V Perrot
Journal:  Nature       Date:  1996-05-09       Impact factor: 49.962

9.  Microbial evolution in a simple unstructured environment: genetic differentiation in Escherichia coli.

Authors:  R F Rosenzweig; R R Sharp; D S Treves; J Adams
Journal:  Genetics       Date:  1994-08       Impact factor: 4.562

10.  Compensatory mutations, antibiotic resistance and the population genetics of adaptive evolution in bacteria.

Authors:  B R Levin; V Perrot; N Walker
Journal:  Genetics       Date:  2000-03       Impact factor: 4.562

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  55 in total

1.  Experimental evolution of a facultative thermophile from a mesophilic ancestor.

Authors:  Ian K Blaby; Benjamin J Lyons; Ewa Wroclawska-Hughes; Grier C F Phillips; Tyler P Pyle; Stephen G Chamberlin; Steven A Benner; Thomas J Lyons; Valérie de Crécy-Lagard; Eudes de Crécy
Journal:  Appl Environ Microbiol       Date:  2011-10-21       Impact factor: 4.792

2.  Combining mathematical models and statistical methods to understand and predict the dynamics of antibiotic-sensitive mutants in a population of resistant bacteria during experimental evolution.

Authors:  Leen De Gelder; José M Ponciano; Zaid Abdo; Paul Joyce; Larry J Forney; Eva M Top
Journal:  Genetics       Date:  2004-11       Impact factor: 4.562

3.  Modeling the impact of periodic bottlenecks, unidirectional mutation, and observational error in experimental evolution.

Authors:  Paul Joyce; Zaid Abdo; José M Ponciano; Leen De Gelder; Larry J Forney; Eva M Top
Journal:  J Math Biol       Date:  2004-12-20       Impact factor: 2.259

4.  Fixation probability favors increased fecundity over reduced generation time.

Authors:  L M Wahl; C S DeHaan
Journal:  Genetics       Date:  2004-10       Impact factor: 4.562

5.  Mutations of intermediate effect are responsible for adaptation in evolving Pseudomonas fluorescens populations.

Authors:  Rowan D H Barrett; R Craig MacLean; Graham Bell
Journal:  Biol Lett       Date:  2006-06-22       Impact factor: 3.703

6.  The population biology of bacterial plasmids: a hidden Markov model approach.

Authors:  José M Ponciano; Leen De Gelder; Eva M Top; Paul Joyce
Journal:  Genetics       Date:  2006-12-06       Impact factor: 4.562

7.  The distribution of beneficial mutant effects under strong selection.

Authors:  Rowan D H Barrett; Leithen K M'Gonigle; Sarah P Otto
Journal:  Genetics       Date:  2006-10-08       Impact factor: 4.562

8.  The effect of spatial structure on adaptation in Escherichia coli.

Authors:  Lilia Perfeito; M Inês Pereira; Paulo R A Campos; Isabel Gordo
Journal:  Biol Lett       Date:  2008-02-23       Impact factor: 3.703

9.  Fixation probabilities when generation times are variable: the burst death model.

Authors:  J E Hubbarde; G Wild; L M Wahl
Journal:  Genetics       Date:  2007-05-04       Impact factor: 4.562

Review 10.  The fixation probability of beneficial mutations.

Authors:  Z Patwa; L M Wahl
Journal:  J R Soc Interface       Date:  2008-11-06       Impact factor: 4.118

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