Literature DB >> 12525686

The solitary wave of asexual evolution.

Igor M Rouzine1, John Wakeley, John M Coffin.   

Abstract

Using a previously undescribed approach, we develop an analytic model that predicts whether an asexual population accumulates advantageous or deleterious mutations over time and the rate at which either process occurs. The model considers a large number of linked identical loci, or nucleotide sites; assumes that the selection coefficient per site is much less than the mutation rate per genome; and includes back and compensating mutations. Using analysis and Monte Carlo simulations, we demonstrate the accuracy of our results over almost the entire range of population sizes. Two limiting cases of our results, when either deleterious or advantageous mutations can be neglected, correspond to the Fisher-Muller effect and Muller's ratchet, respectively. By comparing predictions of our model (no recombination) to those of simple single-locus models (strong recombination), we show that the accumulation of advantageous mutations is slowed by linkage over a broad, finite range of population size. This supports the view of Fisher and Muller, who argued in the 1930s that progressive evolution of organisms is slowed because loci at which beneficial mutations can occur are often linked together on the same chromosome. These results follow from our main finding, that distribution of sequences over the mutation number evolves as a traveling wave whose speed and width depend on population size and other parameters. The model explains a logarithmic dependence of steady-state fitness on the population size reported recently for an RNA virus.

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Year:  2003        PMID: 12525686      PMCID: PMC141040          DOI: 10.1073/pnas.242719299

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  38 in total

Review 1.  Transition between stochastic evolution and deterministic evolution in the presence of selection: general theory and application to virology.

Authors:  I M Rouzine; A Rodrigo; J M Coffin
Journal:  Microbiol Mol Biol Rev       Date:  2001-03       Impact factor: 11.056

Review 2.  Fixation of new alleles and the extinction of small populations: drift load, beneficial alleles, and sexual selection.

Authors:  M C Whitlock
Journal:  Evolution       Date:  2000-12       Impact factor: 3.694

3.  The Average Number of Generations until Fixation of a Mutant Gene in a Finite Population.

Authors:  M Kimura; T Ohta
Journal:  Genetics       Date:  1969-03       Impact factor: 4.562

4.  Exponential fitness gains of RNA virus populations are limited by bottleneck effects.

Authors:  I S Novella; J Quer; E Domingo; J J Holland
Journal:  J Virol       Date:  1999-02       Impact factor: 5.103

5.  The evolution of recombination: removing the limits to natural selection.

Authors:  S P Otto; N H Barton
Journal:  Genetics       Date:  1997-10       Impact factor: 4.562

6.  Compensating for our load of mutations: freezing the meltdown of small populations.

Authors:  A Poon; S P Otto
Journal:  Evolution       Date:  2000-10       Impact factor: 3.694

7.  Reducing antibiotic resistance.

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

8.  Rates of spontaneous mutation among RNA viruses.

Authors:  J W Drake
Journal:  Proc Natl Acad Sci U S A       Date:  1993-05-01       Impact factor: 11.205

9.  The accumulation of deleterious genes in a population--Muller's Ratchet.

Authors:  J Haigh
Journal:  Theor Popul Biol       Date:  1978-10       Impact factor: 1.570

10.  The effect of linkage on limits to artificial selection.

Authors:  W G Hill; A Robertson
Journal:  Genet Res       Date:  1966-12       Impact factor: 1.588

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  92 in total

1.  An asymptotic maximum principle for essentially linear evolution models.

Authors:  Ellen Baake; Michael Baake; Anton Bovier; Markus Klein
Journal:  J Math Biol       Date:  2004-08-20       Impact factor: 2.259

2.  Model-based inference of recombination hotspots in a highly variable oncogene [corrected].

Authors:  G Greenspan; D Geiger; F Gotch; M Bower; S Patterson; M Nelson; B Gazzard; J Stebbing
Journal:  J Mol Evol       Date:  2004-03       Impact factor: 2.395

3.  Dynamics of HIV-1 recombination in its natural target cells.

Authors:  David N Levy; Grace M Aldrovandi; Olaf Kutsch; George M Shaw
Journal:  Proc Natl Acad Sci U S A       Date:  2004-03-09       Impact factor: 11.205

4.  Real time forecasting of near-future evolution.

Authors:  Philip J Gerrish; Paul D Sniegowski
Journal:  J R Soc Interface       Date:  2012-04-18       Impact factor: 4.118

5.  Distribution of fixed beneficial mutations and the rate of adaptation in asexual populations.

Authors:  Benjamin H Good; Igor M Rouzine; Daniel J Balick; Oskar Hallatschek; Michael M Desai
Journal:  Proc Natl Acad Sci U S A       Date:  2012-02-27       Impact factor: 11.205

6.  Chance and risk in adaptive evolution.

Authors:  Michael Lässig
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-12       Impact factor: 11.205

7.  Fast stochastic algorithm for simulating evolutionary population dynamics.

Authors:  William H Mather; Jeff Hasty; Lev S Tsimring
Journal:  Bioinformatics       Date:  2012-03-21       Impact factor: 6.937

8.  Dynamic mutation-selection balance as an evolutionary attractor.

Authors:  Sidhartha Goyal; Daniel J Balick; Elizabeth R Jerison; Richard A Neher; Boris I Shraiman; Michael M Desai
Journal:  Genetics       Date:  2012-06-01       Impact factor: 4.562

Review 9.  Beneficial mutations and the dynamics of adaptation in asexual populations.

Authors:  Paul D Sniegowski; Philip J Gerrish
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2010-04-27       Impact factor: 6.237

10.  The noisy edge of traveling waves.

Authors:  Oskar Hallatschek
Journal:  Proc Natl Acad Sci U S A       Date:  2010-12-27       Impact factor: 11.205

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