Detecting past changes of effective population size

55Citations
Citations of this article
130Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Understanding and predicting population abundance is a major challenge confronting scientists. Several genetic models have been developed using microsatellite markers to estimate the present and ancestral effective population sizes. However, to get an overview on the evolution of population requires that past fluctuation of population size be traceable. To address the question, we developed a new model estimating the past changes of effective population size from microsatellite by resolving coalescence theory and using approximate likelihoods in a Monte Carlo Markov Chain approach. The efficiency of the model and its sensitivity to gene flow and to assumptions on the mutational process were checked using simulated data and analysis. The model was found especially useful to provide evidence of transient changes of population size in the past. The times at which some past demographic events cannot be detected because they are too ancient and the risk that gene flow may suggest the false detection of a bottleneck are discussed considering the distribution of coalescence times. The method was applied on real data sets from several Atlantic salmon populations. The method called VarEff (Variation of Effective size) was implemented in the R package VarEff and is made available at https://qgsp.jouy.inra.fr and at http://cran.r-project.org/web/packages/VarEff. © 2014 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.

Cite

CITATION STYLE

APA

Nikolic, N., & Chevalet, C. (2014). Detecting past changes of effective population size. Evolutionary Applications, 7(6), 663–681. https://doi.org/10.1111/eva.12170

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free