The biomedical landscape of genomic structural variation in the qatari population
Aliyev EPapers in this archive, Syed NPapers in this archive, Visconti APapers in this archive, Aliyev TPapers in this archive, Belkadi APapers in this archive, Ghorbani MPapers in this archive, Rossi NPapers in this archive, Naeem HPapers in this archive, Gandhi GDPapers in this archive, Thareja GPapers in this archive, Al-Maraghi APapers in this archive, Aamer WPapers in this archive, Ibrahim AAPapers in this archive, Shaath RPapers in this archive, Al-Ajli FOPapers in this archive, Razali RMPapers in this archive, Sedlazeck FJPapers in this archive, Davila SPapers in this archive, Akil APapers in this archive, Suhre KPapers in this archive, Mokrab YPapers in this archive, Falchi MPapers in this archive, Fakhro KAPapers in this archive
Abstract
We present a large-scale study of structural variation (SV) in the Qatari population, based on short-read whole-genome sequencing (WGS) of 6,141 individuals, identifying 153,946 variants across 5 classes reflecting the region’s diversity and evolutionary history. Leveraging consanguinity and biobank phenotypes, we identify >180 putative gene knockouts, and use proteomics to show functional consequences in homozygotes. Conversely, 52 genes show significant depletion of homozygous deletions, eight of which cause severe pediatric disease or murine embryonic lethality. Examining phenotypic extremes uncovers several non-exonic homozygous deletions with large effect, including in SPIRE2 (creatinine), MAGI2 (leanness) and a chr19 microRNA cluster (extreme obesity). Further, SV-GWAS reveals gene-trait associations independent of SNPs, including at ACY1 (acetylation), SLC2A9 (uric acid), UGT1A8 (bilirubin) and ZNF251 (alanine aminotransferase). Notably, 3.2% of Qataris carry findings in medically actionable genes, one-third attributable to SVs. Our findings offer a rich SV reference for a globally understudied population, and demonstrate the utility of consanguineous biobanks for studying SVs in health and disease. All common SVs and tag-SNPs are provided as imputation resource.
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