Abstract:
:Genetic data have been widely used to reconstruct the demographic history of populations, including the estimation of migration rates, divergence times and relative admixture contribution from different populations. Recently, increasing interest has been given to the ability of genetic data to distinguish alternative models. One of the issues that has plagued this kind of inference is that ancestral shared polymorphism is often difficult to separate from admixture or gene flow. Here, we applied an approximate Bayesian computation (ABC) approach to select the model that best fits microsatellite data among alternative splitting and admixture models. We performed a simulation study and showed that with reasonably large data sets (20 loci) it is possible to identify with a high level of accuracy the model that generated the data. This suggests that it is possible to distinguish genetic patterns due to past admixture events from those due to shared polymorphism (population split without admixture). We then apply this approach to microsatellite data from an endangered and endemic Iberian freshwater fish species, in which a clustering analysis suggested that one of the populations could be admixed. In contrast, our results suggest that the observed genetic patterns are better explained by a population split model without admixture.
journal_name
Heredity (Edinb)journal_title
Heredityauthors
Sousa VC,Beaumont MA,Fernandes P,Coelho MM,Chikhi Ldoi
10.1038/hdy.2011.116subject
Has Abstractpub_date
2012-05-01 00:00:00pages
521-30issue
5eissn
0018-067Xissn
1365-2540pii
hdy2011116journal_volume
108pub_type
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