The coding capacity of SARS-CoV-2
By
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,
Noam Stern-Ginossar
Posted 07 May 2020
bioRxiv DOI: 10.1101/2020.05.07.082909
(published DOI: 10.1038/s41586-020-2739-1)
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing Coronavirus disease 19 (COVID-19) pandemic [1][1],[2][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][3]–[8][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 (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. ### Competing Interest Statement The authors have declared no competing interest. [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-8
Download data
- Downloaded 3,737 times
- Download rankings, all-time:
- Site-wide: 2,624
- In microbiology: 182
- Year to date:
- Site-wide: 13,829
- Since beginning of last month:
- Site-wide: 12,246
Altmetric data
Downloads over time
Distribution of downloads per paper, site-wide
PanLingua
News
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!