Article ; Online: Rapid automated validation, annotation and publication of SARS-CoV-2 sequences to GenBank.
Database : the journal of biological databases and curation
2022 Volume 2022
Abstract: Rapid response to the current coronavirus disease 2019 (COVID-19) pandemic requires fast dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequence data in order to align diagnostic tests and vaccines with the natural ... ...
| Abstract | Rapid response to the current coronavirus disease 2019 (COVID-19) pandemic requires fast dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequence data in order to align diagnostic tests and vaccines with the natural evolution of the virus as it spreads through the world. To facilitate this, the National Library of Medicine's National Center for Biotechnology Information developed an automated pipeline for the deposition and quick processing of SARS-CoV-2 genome assemblies into GenBank for the user community. The pipeline ensures the collection of contextual information about the virus source, assesses sequence quality and annotates descriptive biological features, such as protein-coding regions and mature peptides. The process promotes standardized nomenclature and creates and publishes fully processed GenBank files within minutes of deposition. The software has processed and published 982 454 annotated SARS-CoV-2 sequences, as of 21 October 2021. This development addresses the needs of the scientific community as the sequencing of SARS-CoV-2 genomes increases and will facilitate unrestricted access to and usability of SARS-CoV-2 genomic sequence data, providing important reagents for scientific and public health activities in response to the COVID-19 pandemic. Database URL https://submit.ncbi.nlm.nih.gov/sarscov2/genbank/. |
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| MeSH term(s) | COVID-19/epidemiology ; COVID-19/genetics ; Databases, Nucleic Acid ; Genome, Viral/genetics ; Humans ; Pandemics ; SARS-CoV-2/genetics |
| Language | English |
| Publishing date | 2022-03-17 |
| Publishing country | England |
| Document type | Journal Article ; Research Support, N.I.H., Extramural |
| ZDB-ID | 2496706-3 |
| ISSN | 1758-0463 ; 1758-0463 |
| ISSN (online) | 1758-0463 |
| ISSN | 1758-0463 |
| DOI | 10.1093/database/baac006 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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