Genetic characterization of Greek population isolates reveals strong genetic drift at missense and trait-associated variants
Panoutsopoulou KPapers in this archive, Hatzikotoulas KPapers in this archive, Xifara DKPapers in this archive, Colonna VPapers in this archive, Farmaki AEPapers in this archive, Ritchie GRPapers in this archive, Southam LPapers in this archive, Gilly APapers in this archive, Tachmazidou IPapers in this archive, Fatumo SPapers in this archive, Matchan APapers in this archive, Rayner NWPapers in this archive, Ntalla IPapers in this archive, Mezzavilla MPapers in this archive, Chen YPapers in this archive, Kiagiadaki CPapers in this archive, Zengini EPapers in this archive, Mamakou VPapers in this archive, Athanasiadis APapers in this archive, Giannakopoulou MPapers in this archive, Kariakli VEPapers in this archive, Nsubuga RNPapers in this archive, Karabarinde APapers in this archive, Sandhu MPapers in this archive, McVean GPapers in this archive, Tyler-Smith CPapers in this archive, Tsafantakis EPapers in this archive, Karaleftheri MPapers in this archive, Xue YPapers in this archive, Dedoussis GPapers in this archive, Zeggini EPapers in this archive
Abstract
Isolated populations are emerging as a powerful study design in the search for low frequency and rare variant associations with complex phenotypes. Here we genotype 2,296 samples from two isolated Greek populations, the Pomak villages (HELIC-Pomak) in the North of Greece; and the Mylopotamos villages (HELIC-MANOLIS) on Crete. We compare their genomic characteristics to the general Greek population and establish them as genetic isolates. In the MANOLIS cohort we observe an enrichment of missense variants amongst the variants that have drifted up in frequency by >5 fold. In the Pomak cohort we find novel associations at variants on chr11p15.4 showing large allele frequency increases (from 0.2% in the general Greek population to 4.6% in the isolate) with haematological traits, for example with mean corpuscular volume (rs7116019, p=2.3×10−26). We replicate this association in a second set of Pomak samples (combined p=2.0×10−36). We demonstrate significant power gains in detecting medical trait associations.
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