Literature DB >> 16887160

Non-equilibrium theory of the allele frequency spectrum.

Steven N Evans1, Yelena Shvets, Montgomery Slatkin.   

Abstract

A forward diffusion equation describing the evolution of the allele frequency spectrum is presented. The influx of mutations is accounted for by imposing a suitable boundary condition. For a Wright-Fisher diffusion with or without selection and varying population size, the boundary condition is lim(x downward arrow0)xf(x,t)=thetarho(t), where f(.,t) is the frequency spectrum of derived alleles at independent loci at time t and rho(t) is the relative population size at time t. When population size and selection intensity are independent of time, the forward equation is equivalent to the backwards diffusion usually used to derive the frequency spectrum, but this approach allows computation of the time dependence of the spectrum both before an equilibrium is attained and when population size and selection intensity vary with time. From the diffusion equation, a set of ordinary differential equations for the moments of f(.,t) is derived and the expected spectrum of a finite sample is expressed in terms of those moments. The use of the forward equation is illustrated by considering neutral and selected alleles in a highly simplified model of human history. For example, it is shown that approximately 30% of the expected total heterozygosity of neutral loci is attributable to mutations that arose since the onset of population growth in roughly the last 150,000 years.

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Year:  2006        PMID: 16887160     DOI: 10.1016/j.tpb.2006.06.005

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  39 in total

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Journal:  Genetics       Date:  2007-07-01       Impact factor: 4.562

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5.  Identifying signatures of selection in genetic time series.

Authors:  Alison F Feder; Sergey Kryazhimskiy; Joshua B Plotkin
Journal:  Genetics       Date:  2013-12-06       Impact factor: 4.562

6.  General triallelic frequency spectrum under demographic models with variable population size.

Authors:  Paul A Jenkins; Jonas W Mueller; Yun S Song
Journal:  Genetics       Date:  2013-11-08       Impact factor: 4.562

7.  Transition Densities and Sample Frequency Spectra of Diffusion Processes with Selection and Variable Population Size.

Authors:  Daniel Živković; Matthias Steinrücken; Yun S Song; Wolfgang Stephan
Journal:  Genetics       Date:  2015-04-14       Impact factor: 4.562

8.  Inferring Very Recent Population Growth Rate from Population-Scale Sequencing Data: Using a Large-Sample Coalescent Estimator.

Authors:  Hua Chen; Jody Hey; Kun Chen
Journal:  Mol Biol Evol       Date:  2015-07-16       Impact factor: 16.240

9.  Inferring the Joint Demographic History of Multiple Populations: Beyond the Diffusion Approximation.

Authors:  Julien Jouganous; Will Long; Aaron P Ragsdale; Simon Gravel
Journal:  Genetics       Date:  2017-05-11       Impact factor: 4.562

10.  Estimating selection intensity on synonymous codon usage in a nonequilibrium population.

Authors:  Kai Zeng; Brian Charlesworth
Journal:  Genetics       Date:  2009-07-20       Impact factor: 4.562

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