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The impact of sampling schemes on the site frequency spectrum in nonequilibrium subdivided populations


Haubold,  Bernhard
Research Group Bioinformatics, Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Städler, T., Haubold, B., Merino, C., Stephan, W., & Pfaffelhuber, P. (2009). The impact of sampling schemes on the site frequency spectrum in nonequilibrium subdivided populations. Genetics, 182(1), 205-216. doi:10.1534/genetics.108.094904.

Using coalescent simulations, we study the impact. of three different sampling schemes on patterns of neutral diversity in structured populations. Specifically, we are interested in two summary statistics based on the site frequency spectrum as a function of migration rate, demographic history of the entire substructured population (including timing and magnitude of specieswide expansions), and the sampling scheme. Using Simulations implementing both finite-island and two-dimensional stepping-stone spatial Structure, we demonstrate strong effects of the sampling scheme on Tajima's D (D-T) and Fu and Li's D (D-FL) statistics, particularly Under specieswide (range) expansions. Pooled samples yield average D-T and D-FL values that are generally intermediate between those of local and scattered samples. Local samples (and to a lesser extent, pooled samples) are influenced by local, rapid coalescence events in the underlying coalescent process. These processes result in lower proportions of external branch lengths and hence lower proportions of singletons, explaining our finding that the sampling scheme affects DFL More than it does D-T. Under specieswide expansion scenarios, these effects of spatial sampling may persist up to very high levels of gene How (Nm > 25), implying that local samples cannot be regarded as being drawn from a panmictic Population. Importantly, many data sets on humans, Drosophila, and plants contain signatures of specieswide expansions and effects of sampling scheme that are predicted by our simulation results. This suggests that validating the assumption of panmixia is crucial if robust demographic inferences are to be made from local or pooled samples. However, future studies should consider adopting a framework that explicitly accounts for the genealogical effects of population subdivision and empirical sampling schemes.