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The coding capacity of SARS-CoV-2.
Metadata
Journalnature42.778Date
2020 Sep 09
20 days ago
Type
Journal Article
Volume
2020-Sep-09 / :
Author
Finkel Y 1, Mizrahi O 1, Nachshon A 1, Weingarten-Gabbay S 2, 3, Morgenstern D 4, Yahalom-Ronen Y 5, Tamir H 5, Achdout H 5, Stein D 6, Israeli O 6, Beth-Din A 6, Melamed S 5, Weiss S 5, Israely T 5, Paran N 5, Schwartz M 1, Stern-Ginossar N 7
Affiliation
  • 2. Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
  • 3. Department of Organismal and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA.
  • 4. de Botton Institute for Protein Profiling, The Nancy and Stephen Grand Israel National Center for Personalised Medicine, Weizmann Institute of Science, Rehovot, 76100, Israel.
  • 5. Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona, 74100, Israel.
  • 6. Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research, Ness Ziona, 74100, Israel.
  • 7. Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, 76100, Israel. [email protected]
Doi
PMIDMESH
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing Coronavirus disease 19 (COVID-19) pandemic1. In order to understand SARS-CoV-2 pathogenicity and antigenic potential, and to develop therapeutic tools, it is essential to portray the full repertoire of its expressed proteins. The SARS-CoV-2 coding capacity map is currently based on computational predictions and relies on homology to other coronaviruses. Since coronaviruses differ in their protein array, especially in the variety of accessory proteins, it is crucial to characterize the specific collection of SARS-CoV-2 proteins in an unbiased and open-ended manner. Using a suite of ribosome profiling techniques2-4, we present a high-resolution map of the SARS-CoV-2 coding regions, allowing us to accurately quantify the expression of canonical viral open reading frames (ORFs) and to identify 23 unannotated viral ORFs. These ORFs include upstream ORFs (uORFs) that are likely playing a regulatory role, several in-frame internal ORFs lying within existing ORFs, resulting in N-terminally truncated products, as well as internal out-of-frame ORFs, which generate novel polypeptides. We further show that viral mRNAs are not translated more efficiently than host mRNAs; rather, virus translation dominates host translation due to high levels of viral transcripts. Our work provides a rich resource, which will form the basis of future functional studies.
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