CoVigator-A Knowledge Base for Navigating SARS-CoV-2 Genomic Variants
Overview
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Background: The outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in the global COVID-19 pandemic. The urgency for an effective SARS-CoV-2 vaccine has led to the development of the first series of vaccines at unprecedented speed. The discovery of SARS-CoV-2 spike-glycoprotein mutants, however, and consequentially the potential to escape vaccine-induced protection and increased infectivity, demonstrates the persisting importance of monitoring SARS-CoV-2 mutations to enable early detection and tracking of genomic variants of concern.
Results: We developed the CoVigator tool with three components: (1) a knowledge base that collects new SARS-CoV-2 genomic data, processes it and stores its results; (2) a comprehensive variant calling pipeline; (3) an interactive dashboard highlighting the most relevant findings. The knowledge base routinely downloads and processes virus genome assemblies or raw sequencing data from the COVID-19 Data Portal (C19DP) and the European Nucleotide Archive (ENA), respectively. The results of variant calling are visualized through the dashboard in the form of tables and customizable graphs, making it a versatile tool for tracking SARS-CoV-2 variants. We put a special emphasis on the identification of intrahost mutations and make available to the community what is, to the best of our knowledge, the largest dataset on SARS-CoV-2 intrahost mutations. In the spirit of open data, all CoVigator results are available for download. The CoVigator dashboard is accessible via covigator.tron-mainz.de.
Conclusions: With increasing demand worldwide in genome surveillance for tracking the spread of SARS-CoV-2, CoVigator will be a valuable resource of an up-to-date list of mutations, which can be incorporated into global efforts.
Rogozin I, Saura A, Poliakov E, Bykova A, Roche-Lima A, Pavlov Y Int J Mol Sci. 2024; 25(7).
PMID: 38612505 PMC: 11011937. DOI: 10.3390/ijms25073696.
VIPERA: Viral Intra-Patient Evolution Reporting and Analysis.
Alvarez-Herrera M, Sevilla J, Ruiz-Rodriguez P, Vergara A, Vila J, Cano-Jimenez P Virus Evol. 2024; 10(1):veae018.
PMID: 38510921 PMC: 10953798. DOI: 10.1093/ve/veae018.