A rapid, cost-effective tailed amplicon method for sequencing SARS-CoV-2

Daryl M. Gohl, John Garbe, Patrick Grady, Jerry Daniel, Ray H.B. Watson, Benjamin Auch, Andrew Nelson, Sophia Yohe, Kenneth B. Beckman

Research output: Contribution to journalArticlepeer-review

Abstract

Background: The global COVID-19 pandemic has led to an urgent need for scalable methods for clinical diagnostics and viral tracking. Next generation sequencing technologies have enabled large-scale genomic surveillance of SARS-CoV-2 as thousands of isolates are being sequenced around the world and deposited in public data repositories. A number of methods using both short- and long-read technologies are currently being applied for SARS-CoV-2 sequencing, including amplicon approaches, metagenomic methods, and sequence capture or enrichment methods. Given the small genome size, the ability to sequence SARS-CoV-2 at scale is limited by the cost and labor associated with making sequencing libraries. Results: Here we describe a low-cost, streamlined, all amplicon-based method for sequencing SARS-CoV-2, which bypasses costly and time-consuming library preparation steps. We benchmark this tailed amplicon method against both the ARTIC amplicon protocol and sequence capture approaches and show that an optimized tailed amplicon approach achieves comparable amplicon balance, coverage metrics, and variant calls to the ARTIC v3 approach. Conclusions: The tailed amplicon method we describe represents a cost-effective and highly scalable method for SARS-CoV-2 sequencing.

Original languageEnglish (US)
Article number863
JournalBMC Genomics
Volume21
Issue number1
DOIs
StatePublished - Dec 2020

Bibliographical note

Funding Information:
We thank the staff of the University of Minnesota Genomics Center for helpful discussions and technical support. We thank Brandon Vanderbush for conducting QC on the SARS-CoV-2 samples and sequencing libraries. This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute. We thank Sean Wang and Matt Plumb from the Minnesota Department of Heath for helpful discussions and for sharing ARTIC v3 primers. We thank Amy Kistler from the Chan-Zuckerberg BioHub, Ryan Donohue, Julie Lau, and Roberto Catteneo from the Mayo Clinic, Jason Blanton from the Florida Department of Health, Yan Li and Suxiang Tong from the Centers for Disease Control and Prevention Pathogen Discover Lab, and Stacia Wyman from the University of California, Berkeley?s Innovative Genomics Institute for sharing unpublished results using the tailed amplicon method described here.

Publisher Copyright:
© 2020, The Author(s).

Keywords

  • COVID-19
  • Genome sequencing
  • SARS-CoV-2
  • Viral surveillance

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