Evaluating mtDNA patterns of genetic isolation using a re-sampling procedure: A case study on Italian populations

Anagnostou, Paolo; Capocasa, Marco; Dominici, Valentina; Montinaro, Francesco; Coia, Valentina; Destro‐Bisol, Giovanni

doi:10.1080/03014460.2016.1181784

Cited by 6 publications

(1 citation statement)

References 39 publications

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“…Our dataset includes 610 healthy unrelated adult individuals from 28 European populations (Table 1), nine of which with clear signatures of genetic isolation [15–17]. The remaining populations were chosen using the following three criteria: (i) geographic proximity with the isolated populations; (ii) geographic coverage of the European continent; (iii) sample size of at least 10 individuals.…”

Section: Methodsmentioning

confidence: 99%

Inter-individual genomic heterogeneity within European population isolates

et al. 2019

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A number of studies carried out since the early ‘70s has investigated the effects of isolation on genetic variation within and among human populations in diverse geographical contexts. However, no extensive analysis has been carried out on the heterogeneity among genomes within isolated populations. This issue is worth exploring since events of recent admixture and/or subdivision could potentially disrupt the genetic homogeneity which is to be expected when isolation is prolonged and constant over time. Here, we analyze literature data relative to 87,815 autosomal single-nucleotide polymorphisms, which were obtained from a total of 28 European populations. Our results challenge the traditional paradigm of population isolates as structured as genetically (and genomically) uniform entities. In fact, focusing on the distribution of variance of intra-population diversity measures across individuals, we show that the inter-individual heterogeneity of isolated populations is at least comparable to the open ones. More in particular, three small and highly inbred isolates (Sappada, Sauris and Timau in Northeastern Italy) were found to be characterized by levels of inter-individual heterogeneity largely exceeding that of all other populations, possibly due to relatively recent events of genetic introgression. Finally, we propose a way to monitor the effects of inter-individual heterogeneity in disease-gene association studies.

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Section: Methodsmentioning

confidence: 99%