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Wahlund effects and sex-biased dispersal in Ixodes ricinus, the European vector of Lyme borreliosis: new tools for old data.

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Abstract

Population genetics can help us better understand species microevolution and population biology, but inferences made from the genetic polymorphisms of field-collected organisms critically rely on sampling design. The population structure of the tick Ixodes ricinus L. (Acari, Ixodidae), a commonly encountered ectoparasite and the principal vector of human
Lyme disease in Europe, has been the focus of some study, but many ecological aspects of this species remain poorly understood. Here, we apply a Bayesian clustering approach to observed and simulated data to examine within-population structure in I. ricinus, and to re-analyse patterns of sex-biased dispersal based on this substructure. We found between 18 and 27 distinct clusters within each of the 12 subsamples examined with a significant drop of heterozygote deficits. Parallel analyses on a comparable species, the seabird tick Ixodes uriae, indicated that these clusters can reflect important ecological features of the species (i.e., local host-associations). Analyses that considered the within-population clustering pattern of I. ricinus showed reversed patterns of sex-biased dispersal as compared to raw data (i.e., female-biased instead of male-biased dispersal). Simulated data supported the hypothesis that these scale-dependant patterns could be due to a combination of sex-specific dispersal and mortality. These different results raise new questions on the dispersal and host use strategies of I. ricinus and the potential importance of these ecological features for
disease transmission. Furthermore, this work underlines the importance of taking into account patterns of genetic substructure when investigating sex-biased dispersal in natural populations.

Copyright 2010 Elsevier B.V. All rights reserved.

Infect Genet Evol. 2010 Oct;10(7):989-97. doi: 10.1016/j.meegid.2010.06.003. Epub 2010 Jun 19. Research Support, Non-U.S. Gov’t

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