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  3. A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome.
 

A cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome.

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BORIS DOI
10.48350/192680
Date of Publication
February 7, 2024
Publication Type
Article
Division/Institute

Universitätsklinik fü...

Contributor
Bhérer, Claude
Eveleigh, Robert
Trajanoska, Katerina
St-Cyr, Janick
Paccard, Antoine
Nadukkalam Ravindran, Praveen
Caron, Elizabeth
Bader Asbah, Nimara
McClelland, Peyton
Wei, Clare
Baumgartner, Iris
Universitätsklinik für Angiologie
Department for BioMedical Research, Forschungsgruppe Angiologie
Schindewolf, Marc
Universitätsklinik für Angiologie
Department for BioMedical Research (DBMR)
Döring, Yvonne
Universitätsklinik für Angiologie
Department for BioMedical Research, Forschungsgruppe Angiologie
Perley, Danielle
Lefebvre, François
Lepage, Pierre
Bourgey, Mathieu
Bourque, Guillaume
Ragoussis, Jiannis
Mooser, Vincent
Taliun, Daniel
Subject(s)

600 - Technology::610...

Series
NPJ genomic medicine
ISSN or ISBN (if monograph)
2056-7944
Publisher
Springer Nature
Language
English
Publisher DOI
10.1038/s41525-024-00390-3
PubMed ID
38326393
Description
Whole genome sequencing (WGS) at high-depth (30X) allows the accurate discovery of variants in the coding and non-coding DNA regions and helps elucidate the genetic underpinnings of human health and diseases. Yet, due to the prohibitive cost of high-depth WGS, most large-scale genetic association studies use genotyping arrays or high-depth whole exome sequencing (WES). Here we propose a cost-effective method which we call "Whole Exome Genome Sequencing" (WEGS), that combines low-depth WGS and high-depth WES with up to 8 samples pooled and sequenced simultaneously (multiplexed). We experimentally assess the performance of WEGS with four different depth of coverage and sample multiplexing configurations. We show that the optimal WEGS configurations are 1.7-2.0 times cheaper than standard WES (no-plexing), 1.8-2.1 times cheaper than high-depth WGS, reach similar recall and precision rates in detecting coding variants as WES, and capture more population-specific variants in the rest of the genome that are difficult to recover when using genotype imputation methods. We apply WEGS to 862 patients with peripheral artery disease and show that it directly assesses more known disease-associated variants than a typical genotyping array and thousands of non-imputable variants per disease-associated locus.
Handle
https://boris-portal.unibe.ch/handle/20.500.12422/174251
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s41525-024-00390-3.pdftextAdobe PDF1.57 MBpublishedOpen
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