Literature DB >> 22850060

Estimating the number of one-step beneficial mutations.

Andrzej J Wojtowicz1, Craig R Miller, Paul Joyce.   

Abstract

Mutations that confer a selective advantage to an organism are the raw material upon which natural selection acts. The number of such mutations that are available is a central quantity of interest for understanding the tempo and trajectory of adaptive evolution. While this quantity is typically unknown, it can be estimated with varying levels of accuracy based on data obtained experimentally. We propose a method for estimating the number of beneficial mutations that accounts for the evolutionary forces that generate the data. Our model-based parametric approach is compared to an adjusted nonparametric abundance-based coverage estimator. We show that, in general, our estimator performs better. When the number of mutations is small, however, the performances of the two estimators are similar.

Entities:  

Mesh:

Year:  2012        PMID: 22850060      PMCID: PMC5563373          DOI: 10.1515/1544-6115.1788

Source DB:  PubMed          Journal:  Stat Appl Genet Mol Biol        ISSN: 1544-6115


  20 in total

1.  Fitness effects of fixed beneficial mutations in microbial populations.

Authors:  Daniel E Rozen; J Arjan G M de Visser; Philip J Gerrish
Journal:  Curr Biol       Date:  2002-06-25       Impact factor: 10.834

2.  The distribution of fitness effects of new beneficial mutations in Pseudomonas fluorescens.

Authors:  Michael J McDonald; Tim F Cooper; Hubertus J E Beaumont; Paul B Rainey
Journal:  Biol Lett       Date:  2010-07-21       Impact factor: 3.703

3.  A new method for estimating the size of small populations from genetic mark-recapture data.

Authors:  Craig R Miller; Paul Joyce; Lisette P Waits
Journal:  Mol Ecol       Date:  2005-06       Impact factor: 6.185

4.  Model of effectively neutral mutations in which selective constraint is incorporated.

Authors:  M Kimura
Journal:  Proc Natl Acad Sci U S A       Date:  1979-07       Impact factor: 11.205

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.  High frequency of mutations that expand the host range of an RNA virus.

Authors:  Martin T Ferris; Paul Joyce; Christina L Burch
Journal:  Genetics       Date:  2007-04-03       Impact factor: 4.562

7.  Distribution of fitness effects among beneficial mutations before selection in experimental populations of bacteria.

Authors:  Rees Kassen; Thomas Bataillon
Journal:  Nat Genet       Date:  2006-03-19       Impact factor: 38.330

8.  A general extreme value theory model for the adaptation of DNA sequences under strong selection and weak mutation.

Authors:  Paul Joyce; Darin R Rokyta; Craig J Beisel; H Allen Orr
Journal:  Genetics       Date:  2008-09-14       Impact factor: 4.562

9.  Estimating the population size for capture-recapture data with unequal catchability.

Authors:  A Chao
Journal:  Biometrics       Date:  1987-12       Impact factor: 2.571

10.  The distribution of fitness effects of beneficial mutations in Pseudomonas aeruginosa.

Authors:  R Craig MacLean; Angus Buckling
Journal:  PLoS Genet       Date:  2009-03-06       Impact factor: 5.917

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