Abstract
COVID-19 CG is an open resource for tracking SARS-CoV-2 single-nucleotide variations (SNVs) and lineages while filtering by location, date, gene, and mutation of interest. COVID-19 CG provides significant time, labor, and cost-saving utility to diverse projects on SARS-CoV-2 transmission, evolution, emergence, immune interactions, diagnostics, therapeutics, vaccines, and intervention tracking. Here, we describe case studies in which users can interrogate (1) SNVs in the SARS-CoV-2 Spike receptor binding domain (RBD) across different geographic regions to inform the design and testing of therapeutics, (2) SNVs that may impact the sensitivity of commonly used diagnostic primers, and (3) the recent emergence of a dominant lineage harboring an S477N RBD mutation in Australia. To accelerate COVID-19 research and public health efforts, COVID-19 CG will be continually upgraded with new features for users to quickly and reliably pinpoint mutations as the virus evolves throughout the pandemic and in response to therapeutic and public health interventions.
Competing Interest Statement
Shing Hei Zhan is a Co-founder and Director of Bioinformatics at Fusion Genomics Corporation, which develops molecular diagnostic assays for infectious diseases. The other authors declare no competing interests.
Footnotes
Lead Contact Benjamin E. Deverman, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, 75 Ames St, Cambridge, MA 02142, Phone (626) 755-7523, bdeverma{at}broadinstitute.org
Supplementary file added to acknowledge all of the contributors of SARS-CoV-2 data to GISAID.
