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Multiethnic catalog of structural variants and their translational impact for disease phenotypes across 19,652 genomes

Sedlazeck, F. J.; Yu, B.; Mansfield, A. J.; Chen, H.; Krasheninina, O.; Tin, A.; Qi, Q.; Zarate, S.; Traynelis, J.; Menon, V.; BCM HGSC Sequencing Lab, ; Hu, J.; doddapaneni, h. v.; Metcalf, G.; Coresh, J.; Kaplan, R.; muzny, d. m.; Jun, G.; Gibbs, R. A.; Salerno, W.; Boerwinkle, E.

2020-05-03 genomics
10.1101/2020.05.02.074096 bioRxiv
Show abstract

Genome sequencing at population scale provides unprecedented access to the genetic foundations of human phenotypic diversity, but genotype-phenotype association analyses limited to small variants have failed to comprehensively characterize the genetic architecture of human health and disease because they ignore structural variants (SVs) known to contribute to phenotypic variation and pathogenic conditions1-3. Here we demonstrate the significance of SVs when assessing genotype-phenotype associations and the importance of ethnic diversity in study design by analyzing SVs across 19,652 individuals and the translational impact on 4,156 aptamerbased proteomic measurements across 4,021 multi-ethnic samples. The majority of 304,533 SVs detected are rare, although we identified 2,336 protein-coding genes impacted by common SVs.\ We identified 64 significant SV-protein associations that comprise 36 cis- and 28 trans-acting relationships, and 21 distinct SV regions overlapped with genome-wide association study loci. These findings represent a more comprehensive mapping of regulatory and translational endophenotypes underlying health and disease.

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