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RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus
SARS-CoV-2 genomic and subgenomic RNA (sgRNA) transcripts hijack the host cell's machinery. Subcellular localization of its viral RNA could, thus, play important roles in viral replication and host antiviral immune response. We perform computational modeling of SARS-CoV-2 viral RNA subcellular...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305881/ https://www.ncbi.nlm.nih.gov/pubmed/32673562 http://dx.doi.org/10.1016/j.cels.2020.06.008 |
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author | Wu, Kevin E. Fazal, Furqan M. Parker, Kevin R. Zou, James Chang, Howard Y. |
author_facet | Wu, Kevin E. Fazal, Furqan M. Parker, Kevin R. Zou, James Chang, Howard Y. |
author_sort | Wu, Kevin E. |
collection | PubMed |
description | SARS-CoV-2 genomic and subgenomic RNA (sgRNA) transcripts hijack the host cell's machinery. Subcellular localization of its viral RNA could, thus, play important roles in viral replication and host antiviral immune response. We perform computational modeling of SARS-CoV-2 viral RNA subcellular residency across eight subcellular neighborhoods. We compare hundreds of SARS-CoV-2 genomes with the human transcriptome and other coronaviruses. We predict the SARS-CoV-2 RNA genome and sgRNAs to be enriched toward the host mitochondrial matrix and nucleolus, and that the 5′ and 3′ viral untranslated regions contain the strongest, most distinct localization signals. We interpret the mitochondrial residency signal as an indicator of intracellular RNA trafficking with respect to double-membrane vesicles, a critical stage in the coronavirus life cycle. Our computational analysis serves as a hypothesis generation tool to suggest models for SARS-CoV-2 biology and inform experimental efforts to combat the virus. A record of this paper’s Transparent Peer Review process is included in the . |
format | Online Article Text |
id | pubmed-7305881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Authors. Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73058812020-06-22 RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus Wu, Kevin E. Fazal, Furqan M. Parker, Kevin R. Zou, James Chang, Howard Y. Cell Syst Brief Report SARS-CoV-2 genomic and subgenomic RNA (sgRNA) transcripts hijack the host cell's machinery. Subcellular localization of its viral RNA could, thus, play important roles in viral replication and host antiviral immune response. We perform computational modeling of SARS-CoV-2 viral RNA subcellular residency across eight subcellular neighborhoods. We compare hundreds of SARS-CoV-2 genomes with the human transcriptome and other coronaviruses. We predict the SARS-CoV-2 RNA genome and sgRNAs to be enriched toward the host mitochondrial matrix and nucleolus, and that the 5′ and 3′ viral untranslated regions contain the strongest, most distinct localization signals. We interpret the mitochondrial residency signal as an indicator of intracellular RNA trafficking with respect to double-membrane vesicles, a critical stage in the coronavirus life cycle. Our computational analysis serves as a hypothesis generation tool to suggest models for SARS-CoV-2 biology and inform experimental efforts to combat the virus. A record of this paper’s Transparent Peer Review process is included in the . The Authors. Published by Elsevier Inc. 2020-07-22 2020-06-20 /pmc/articles/PMC7305881/ /pubmed/32673562 http://dx.doi.org/10.1016/j.cels.2020.06.008 Text en © 2020 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Brief Report Wu, Kevin E. Fazal, Furqan M. Parker, Kevin R. Zou, James Chang, Howard Y. RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus |
title | RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus |
title_full | RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus |
title_fullStr | RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus |
title_full_unstemmed | RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus |
title_short | RNA-GPS Predicts SARS-CoV-2 RNA Residency to Host Mitochondria and Nucleolus |
title_sort | rna-gps predicts sars-cov-2 rna residency to host mitochondria and nucleolus |
topic | Brief Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305881/ https://www.ncbi.nlm.nih.gov/pubmed/32673562 http://dx.doi.org/10.1016/j.cels.2020.06.008 |
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