Genomic analysis reveals hidden heterogeneity within human population isolates

04 Pubblicazione in atti di convegno
Dominici Valentina, BATTAGGIA BURATTINI Cinzia, Pagani Luca, Pettener Davide, Sarno Stefania, Boattini Alessio, Francalacci Paolo, Colonna Vincenza, Vona Giuseppe, Calò Carla, Tofanelli Sergio, DESTRO-BISOL Giovanni, Anagnostou Paolo

Studying groups subject to barriers to gene flow provides a unique opportunity to understand how
inbreeding, genetic drift and selection have shaped the structure of human genetic diversity.
Currently, the consequences of genetic isolation may be better studied using genome wide approaches
(GWA), such as those based on SNP microarrays which enable the simultaneous analysis of very
large numbers of loci distributed across chromosomes. Despite the considerable body of knowledge
on human genetic isolates, variation occurring among individuals within isolated populations has not
been yet thoroughly investigated. This issue is worth exploring since events of recent admixture and
presence of sub-structure could potentially disrupt the genetic homogeneity which is expected when

isolation is prolonged and constant over time. In a previous study, we have compared intra and inter-
population variation measures combining novel and literature data relative to 87,818 autosomal SNPs

in 14 open populations and 10 geographic and/or linguistic European isolates. Here, we expand our
dataset to a total of 27 groups and move our focus to the variation among individual genomes within
populations. Using four measures of within population diversity (homozygosity, identity-by-state and
length and number of runs of homozygosity), we observed a significantly higher level of variation
among the German-speakers of the linguistic islands of Sappada, Sauris and Timau and North
Sardinians. These same populations show a noticeable among individual variation for ancestry
components. Caveats, significance and implications of our results are discussed in relation to both
microevolutionary aspects and bio-medical applications.

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