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Updated: May 11, 2026

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
The demographic history of populations experiencing asymmetric gene flow: combining simulated and empirical data
I Paz-Vinas1, E Quéméré, L Chikhi
1Centre National de la Recherche Scientifique (CNRS), Station d'Écologie Expérimentale du CNRS à Moulis, USR 2936, Moulis, F-09200, France; Centre National de la Recherche Scientifique (CNRS), Université Paul Sabatier, École Nationale de Formation Agronomique (ENFA), UMR 5174 EDB (Laboratoire Évolution & Diversité Biologique), 118 route de Narbonne, Toulouse cedex 4, F-31062, France; Université de Toulouse, UPS, UMR 5174 (EDB), 118 route de Narbonne, Toulouse cedex 4, F-31062, France.
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.
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