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bioRxiv · 10.1101/2020.09.03.282251

Inferring number of populations and changes in connectivity under the n-island model

Abstract

Inferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, thus ignoring population structure. Alternatively, structure is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate), which can be estimated using the PSMC method of Li and Durbin (2011) for a single diploid individual. For an isolated population, the IICR matches the population size history, which is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme. Our automated method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise-stationary symmetrical island models, in which we assume a fixed number of time periods during which gene flow is constant. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the widely accepted view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.

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Arredondo Soto, A., Mourato, B., Nguyen, K., Boitard, S., Rodriguez Valcarce, W. R., Nous, C., Mazet, O., Chikhi, L.. 2020-09-04. Inferring number of populations and changes in connectivity under the n-island model. https://doi.org/10.1101/2020.09.03.282251

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