WEGS: a cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome

Bhérer, Claude; Eveleigh, Robert; Trajanoska, Katerina; St-Cry, Janick; Paccard, Antoine; Ravindran, Praveen Nadukkalam; Caron, Elizabeth; Asbah, Nimara Bader; Wei, Claire; Baumgartner, Iris; Schindewolf, Marc; Döring, Yvonne; Perley, Danielle; Lefebvre, François; Lepage, Pierre; Bourgey, Mathieu; Bourque, Guillaume; Ragoussis, Jiannis; Mooser, Vincent and Taliun, Daniel (2023). WEGS: a cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome (In Press) (bioRxiv). Cold Spring Harbor Laboratory 10.1101/2023.04.27.538531

Preview

Text 2023.04.27.538531v1.full.pdf - Published Version Available under License Creative Commons: Attribution-No Derivative Works (CC-BY-ND). Download (2MB) | Preview

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 novel, 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.

Interest & Impact

Downloads

5 since deposited on 20 Dec 2023
5 in the past 12 months

Citations

5 Citations in Web of Science ®
6 Citations in Scopus

Search

in Google Scholar™

Services

Actions (login required)

Edit item

Actions (login required)

Edit item