New method for surname studies of ancient patrilineal population structures, and possible application to improvement of Y-chromosome sampling |
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Authors: | Manni Franz Toupance Bruno Sabbagh Audrey Heyer Evelyne |
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Affiliation: | Equipe de Génétique des Populations, Département Hommes, Natures, Sociétés (UMR5145 CNRS), Unité d'Eco-Anthropologie, Musée de l'Homme MNHN, Paris 75016, France. manni@mnhn.fr |
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Abstract: | Several studies showed that surnames are good markers to infer patrilineal genetic structures of populations, both on regional and microregional scales. As a case study, the spatial patterns of the 9,929 most common surnames of the Netherlands were analyzed by a clustering method called self-organizing maps (SOMs). The resulting clusters grouped surnames with a similar geographic distribution and origin. The analysis was shown to be in agreement with already known features of Dutch surnames, such as 1) the geographic distribution of some well-known locative suffixes, 2) historical census data, 3) the distribution of foreign surnames, and 4) polyphyletic surnames. Thus, these results validate the SOM clustering of surnames, and allow for the generalization of the technique. This method can be applied as a new strategy for a better Y-chromosome sampling design in retrospective population genetics studies, since the idenfication of surnames with a defined geographic origin enables the selection of the living descendants of those families settled, centuries ago, in a given area. In other words, it becomes possible to virtually sample the population as it was when surnames started to be in use. We show that, in a given location, the descendants of those individuals who inhabited the area at the time of origin of surnames can be as low as approximately 20%. This finding suggests 1) the major role played by recent migrations that are likely to have distorted or even defaced ancient genetic patterns, and 2) that standard-designed samplings can hardly portray a reliable picture of the ancient Y-chromosome variability of European populations. |
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Keywords: | Kohonen maps demography population genetics sampling design census migrations |
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