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The coding capacity of SARS-CoV-2
Yaara Finkel; Orel Mizrahi; Aharon Nachshon; Shira Weingarten-Gabbay; David Morgenstern; Yfat Yahalom-Ronen; Hadas Tamir; Hagit Achdout; Dana Stein; Ofir Israeli; Adi Beth-Din; Sharon Melamed; Shay Weiss; Tomer Isrealy; Nir Paran; Michal Schwartz; Noam Stern-Ginossar.
Affiliation
  • Yaara Finkel; Department of Molecular Genetics, Weizmann Institute of Science
  • Orel Mizrahi; Department of Molecular Genetics, Weizmann Institute of Science
  • Aharon Nachshon; Department of Molecular Genetics, Weizmann Institute of Science
  • Shira Weingarten-Gabbay; Broad Institute of MIT and Harvard, Cambridge, Department of Organismal and Evolutionary Biology, Harvard University, Cambridge
  • David Morgenstern; de Botton Institute for Protein Profiling, The Nancy and Stephen Grand Israel National Center for Personalised Medicine, Weizmann Institute of Science
  • Yfat Yahalom-Ronen; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona
  • Hadas Tamir; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona
  • Hagit Achdout; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona
  • Dana Stein; Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research
  • Ofir Israeli; Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research
  • Adi Beth-Din; Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research
  • Sharon Melamed; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona
  • Shay Weiss; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona
  • Tomer Isrealy; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona
  • Nir Paran; Department of Infectious Diseases, Israel Institute for Biological Research, Ness Ziona
  • Michal Schwartz; Department of Molecular Genetics, Weizmann Institute of Science
  • Noam Stern-Ginossar; Department of Molecular Genetics, Weizmann Institute of Science
Preprint in En | PREPRINT-BIORXIV | ID: ppbiorxiv-082909
Journal article
A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
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ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing Coronavirus disease 19 (COVID-19) pandemic 1,2. In order to understand SARS-CoV-2 pathogenicity and antigenic potential, and to develop diagnostic and 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. Utilizing a suite of ribosome profiling techniques 3-8, 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 (ORF)s and to identify 23 novel unannotated viral translated 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. Overall, our work reveals the full coding capacity of SARS-CoV-2 genome, providing a rich resource, which will form the basis of future functional studies and diagnostic efforts.
License
cc_by_nc
Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Type of study: Prognostic_studies Language: En Year: 2020 Document type: Preprint
Full text: 1 Collection: 09-preprints Database: PREPRINT-BIORXIV Type of study: Prognostic_studies Language: En Year: 2020 Document type: Preprint
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