Literature DB >> 18410538

Fixation probabilities depend on life history: fecundity, generation time and survival in a burst-death model.

H K Alexander1, L M Wahl1,2.   

Abstract

The burst-death model has been developed to describe the life history of organisms with variable generation times and a burst of a fixed number of offspring. The model also includes an optional constant clearance rate, such as washout from a chemostat, and the possibility of sustained periods of population growth followed by severe bottlenecks, as in serial passaging. In this model, a beneficial mutation can either increase the burst rate or the burst size, or reduce the clearance rate, thus increasing survival. In this article we examine the effects of these three possible mechanisms on both the Malthusian fitness and the fixation probability of the lineage. We find that equivalent relative increases in the burst rate or burst size confer equivalent increases in the Malthusian fitness of a lineage, whereas increasing survival typically has a more moderate effect on Malthusian fitness. In contrast, for beneficial mutations that confer the same increase in fitness, mutations that increase survival are the most likely to fix, followed by mutations that increase the burst rate. Mutations that increase the burst size are the least likely to fix. These results imply that mutant lineages with the highest Malthusian fitness are not, in many cases, the most likely to escape extinction.

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Year:  2008        PMID: 18410538     DOI: 10.1111/j.1558-5646.2008.00396.x

Source DB:  PubMed          Journal:  Evolution        ISSN: 0014-3820            Impact factor:   3.694


  10 in total

1.  Model and test in a fungus of the probability that beneficial mutations survive drift.

Authors:  Danna R Gifford; J Arjan G M de Visser; Lindi M Wahl
Journal:  Biol Lett       Date:  2012-06-27       Impact factor: 3.703

2.  Some consequences of demographic stochasticity in population genetics.

Authors:  Todd L Parsons; Christopher Quince; Joshua B Plotkin
Journal:  Genetics       Date:  2010-05-10       Impact factor: 4.562

Review 3.  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

4.  Fixation probability for lytic viruses: the attachment-lysis model.

Authors:  Z Patwa; L M Wahl
Journal:  Genetics       Date:  2008-08-30       Impact factor: 4.562

5.  Survival probability of beneficial mutations in bacterial batch culture.

Authors:  Lindi M Wahl; Anna Dai Zhu
Journal:  Genetics       Date:  2015-03-09       Impact factor: 4.562

6.  On selection in finite populations.

Authors:  Chai Molina; David J D Earn
Journal:  J Math Biol       Date:  2017-06-29       Impact factor: 2.259

7.  The phenotype-fitness map in experimental evolution of phages.

Authors:  James J Bull; Richard H Heineman; Claus O Wilke
Journal:  PLoS One       Date:  2011-11-22       Impact factor: 3.240

8.  Effects of Transmission Bottlenecks on the Diversity of Influenza A Virus.

Authors:  Daniel Sigal; Jennifer N S Reid; Lindi M Wahl
Journal:  Genetics       Date:  2018-09-04       Impact factor: 4.562

9.  What limits the evolutionary emergence of pathogens?

Authors:  S Gandon; M E Hochberg; R D Holt; T Day
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-01-19       Impact factor: 6.237

10.  Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments.

Authors:  Michael Schmutzer; Andreas Wagner
Journal:  PLoS Comput Biol       Date:  2020-10-26       Impact factor: 4.475

  10 in total

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