Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows

Connor, Ryan; Shakya, Migun; Yarmosh, David A.; Maier, Wolfgang; Martin, Ross; Bradford, Rebecca; Brister, J. Rodney; Chain, Patrick S. G.; Copeland, Courtney A.; di Iulio, Julia; Hu, Bin; Ebert, Philip; Gunti, Jonathan; Jin, Yumi; Katz, Kenneth S.; Kochergin, Andrey; LaRosa, Tré; Li, Jiani; Li, Po-E; Lo, Chien-Chi; Rashid, Sujatha; Maiorova, Evguenia S.; Xiao, Chunlin; Zalunin, Vadim; Purcell, Lisa; Pruitt, Kim D.

doi:10.3390/v16030430

Title: Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows

Journal Article · 11 March 2024 · Viruses

DOI: https://doi.org/10.3390/v16030430 · OSTI ID:2470558

^[1]; Shakya, Migun ^[2];

^[3];

^[4]; Martin, Ross ^[5];

^[3]; Brister, J. Rodney ^[1];

^[2]; Copeland, Courtney A. ^[6];

^[7];

^[2]; Ebert, Philip ^[8]; Gunti, Jonathan ^[1]; Jin, Yumi ^[1]; Katz, Kenneth S. ^[1]; Kochergin, Andrey ^[1]; LaRosa, Tré ^[6]; Li, Jiani ^[5];

^[2];

^[2] more »

National Institutes of Health (NIH), Bethesda, MD (United States). National Library of Medicine (NLM), National Center for Biotechnology Information (NCBI)
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
American Type Culture Collection, Manassas, VA (United States); BEI Resources, Manassas, VA (United States)
University of Freiburg (Germany)
Gilead Sciences, Foster City, CA (United States)
Deloitte Consulting LLP, Rosslyn, VA (United States)
Vir Biotechnology Inc., San Francisco, CA (United States)
Eli Lilly and Company, Indianapolis, IN (United States)
American Type Culture Collection, Manassas, VA (United States)

Genomic sequencing of clinical samples to identify emerging variants of SARS-CoV-2 has been a key public health tool for curbing the spread of the virus. As a result, an unprecedented number of SARS-CoV-2 genomes were sequenced during the COVID-19 pandemic, which allowed for rapid identification of genetic variants, enabling the timely design and testing of therapies and deployment of new vaccine formulations to combat the new variants. However, despite the technological advances of deep sequencing, the analysis of the raw sequence data generated globally is neither standardized nor consistent, leading to vastly disparate sequences that may impact identification of variants. Here, we show that for both Illumina and Oxford Nanopore sequencing platforms, downstream bioinformatic protocols used by industry, government, and academic groups resulted in different virus sequences from same sample. These bioinformatic workflows produced consensus genomes with differences in single nucleotide polymorphisms, inclusion and exclusion of insertions, and/or deletions, despite using the same raw sequence as input datasets. Here, we compared and characterized such discrepancies and propose a specific suite of parameters and protocols that should be adopted across the field. Consistent results from bioinformatic workflows are fundamental to SARS-CoV-2 and future pathogen surveillance efforts, including pandemic preparation, to allow for a data-driven and timely public health response.

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Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: European Union Horizon 2020; National Institutes of Health (NIH); USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 2470558

Journal Information:: Viruses, Journal Name: Viruses Journal Issue: 3 Vol. 16; ISSN 1999-4915

Publisher:: MDPICopyright Statement

Country of Publication:: United States

Language:: English

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