Open AccessInter-individual genomic heterogeneity within European population isolates
Author(s) -
Paolo Anagnostou,
Valentina Dominici,
Cinzia Battaggia,
Alessandro Lisi,
Stefania Sarno,
Alessio Boattini,
Carla Maria Calò,
Paolo Francalacci,
Giuseppe Vona,
Sergio Tofanelli,
Miguel G. Vilar,
Vincenza Colonna,
Luca Pagani,
Giovanni Destro Bisol
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0214564
Subject(s) - biology , population , evolutionary biology , genetics , computational biology , medicine , environmental health
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.