Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic1. To understand the pathogenicity and antigenic potential of SARS-CoV-2 and to develop therapeutic tools, it is essential to profile the full repertoire of its expressed proteins. The current map of SARS-CoV-2 coding capacity is based on computational predictions and relies on homology with other coronaviruses. As the protein complement varies among coronaviruses, especially in regard to the variety of accessory proteins, it is crucial to characterize the specific range of SARS-CoV-2 proteins in an unbiased and open-ended manner. Here, using a suite of ribosome-profiling techniques2–4, we present a high-resolution map of coding regions in the SARS-CoV-2 genome, which enables 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 that are likely to have a regulatory role, several in-frame internal ORFs 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; instead, virus translation dominates host translation because of the high levels of viral transcripts. Our work provides a resource that will form the basis of future functional studies.
Original language | English |
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Pages (from-to) | 125-130 |
Number of pages | 6 |
Journal | Nature |
Volume | 589 |
Issue number | 7840 |
DOIs | |
State | Published - 7 Jan 2021 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020, The Author(s), under exclusive licence to Springer Nature Limited.
Funding
Acknowledgements We thank Stern-Ginossar laboratory members, I. Ulitsky and S. Schwartz for providing valuable feedback; E. Zehavi, M. Shnayder, I. Ulitsky and N. Gil for technical assistance; E. Wyler for the Calu3 cells; and I. Cohen-Gihon for sharing sequencing and bioinformatics data. This study was supported by the Ben B. and Joyce E. Eisenberg Foundation. Work in the Stern-Ginossar lab is supported by ERC-CoG-2019-864012 and by the ISF grant no. 1526/18. S.W.-G. is the recipient of the HSFP fellowship, EMBO non-stipendiary Long-Term Fellowship, the Gruss-Lipper Postdoctoral Fellowship, the Zuckerman STEM Leadership Program and the Rothschild Postdoctoral Fellowship. N.S.-G. is an incumbent of the Skirball Career Development Chair in New Scientists and is a member of EMBO Young Investigator Program.
Funders | Funder number |
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Joyce E. Eisenberg Foundation | ERC-CoG-2019-864012 |
European Molecular Biology Organization | |
Horizon 2020 Framework Programme | 638142, 864012 |
Israel Science Foundation | 1526/18 |