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 Israely, Nir Paran, Michal Schwartz and Noam Stern-Ginossar ()
Additional contact information
Yaara Finkel: Weizmann Institute of Science
Orel Mizrahi: Weizmann Institute of Science
Aharon Nachshon: Weizmann Institute of Science
Shira Weingarten-Gabbay: Broad Institute of MIT and Harvard
David Morgenstern: The Nancy and Stephen Grand Israel National Center for Personalised Medicine, Weizmann Institute of Science
Yfat Yahalom-Ronen: Israel Institute for Biological Research
Hadas Tamir: Israel Institute for Biological Research
Hagit Achdout: Israel Institute for Biological Research
Dana Stein: Israel Institute for Biological Research
Ofir Israeli: Israel Institute for Biological Research
Adi Beth-Din: Israel Institute for Biological Research
Sharon Melamed: Israel Institute for Biological Research
Shay Weiss: Israel Institute for Biological Research
Tomer Israely: Israel Institute for Biological Research
Nir Paran: Israel Institute for Biological Research
Michal Schwartz: Weizmann Institute of Science
Noam Stern-Ginossar: Weizmann Institute of Science

Nature, 2021, vol. 589, issue 7840, 125-130

Abstract: 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.

Date: 2021
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DOI: 10.1038/s41586-020-2739-1

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