Literature DB >> 23718226

The demographic history of populations experiencing asymmetric gene flow: combining simulated and empirical data.

I Paz-Vinas1, E Quéméré, L Chikhi, G Loot, S Blanchet.   

Abstract

Population structure can significantly affect genetic-based demographic inferences, generating spurious bottleneck-like signals. Previous studies have typically assumed island or stepping-stone models, which are characterized by symmetric gene flow. However, many organisms are characterized by asymmetric gene flow. Here, we combined simulated and empirical data to test whether asymmetric gene flow affects the inference of past demographic changes. Through the analysis of simulated genetic data with three methods (i.e. bottleneck, M-ratio and msvar), we demonstrated that asymmetric gene flow biases past demographic changes. Most biases were towards spurious signals of expansion, albeit their strength depended on values of effective population size and migration rate. It is noteworthy that the spurious signals of demographic changes also depended on the statistical approach underlying each of the three methods. For one of the three methods, biases induced by asymmetric gene flow were confirmed in an empirical multispecific data set involving four freshwater fish species (Squalius cephalus, Leuciscus burdigalensis, Gobio gobio and Phoxinus phoxinus). However, for the two other methods, strong signals of bottlenecks were detected for all species and across two rivers. This suggests that, although potentially biased by asymmetric gene flow, some of these methods were able to bypass this bias when a bottleneck actually occurred. Our results show that population structure and dispersal patterns have to be considered for proper inference of demographic changes from genetic data.
© 2013 John Wiley & Sons Ltd.

Entities:  

Keywords:  ABC; demographic change; fish; rivers; source-sink dynamics

Mesh:

Year:  2013        PMID: 23718226     DOI: 10.1111/mec.12321

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  16 in total

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5.  Combining genetic and demographic data for prioritizing conservation actions: insights from a threatened fish species.

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10.  Directional genetic differentiation and relative migration.

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