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Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis
The novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after emerging in Wuhan, China. Here we analyzed public host and viral RNA sequencing data to better understand how SARS-CoV-2 interacts with human respiratory cells. We iden...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8128904/ https://www.ncbi.nlm.nih.gov/pubmed/34002013 http://dx.doi.org/10.1038/s42003-021-02095-0 |
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author | Ferrarini, Mariana G. Lal, Avantika Rebollo, Rita Gruber, Andreas J. Guarracino, Andrea Gonzalez, Itziar Martinez Floyd, Taylor de Oliveira, Daniel Siqueira Shanklin, Justin Beausoleil, Ethan Pusa, Taneli Pickett, Brett E. Aguiar-Pulido, Vanessa |
author_facet | Ferrarini, Mariana G. Lal, Avantika Rebollo, Rita Gruber, Andreas J. Guarracino, Andrea Gonzalez, Itziar Martinez Floyd, Taylor de Oliveira, Daniel Siqueira Shanklin, Justin Beausoleil, Ethan Pusa, Taneli Pickett, Brett E. Aguiar-Pulido, Vanessa |
author_sort | Ferrarini, Mariana G. |
collection | PubMed |
description | The novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after emerging in Wuhan, China. Here we analyzed public host and viral RNA sequencing data to better understand how SARS-CoV-2 interacts with human respiratory cells. We identified genes, isoforms and transposable element families that are specifically altered in SARS-CoV-2-infected respiratory cells. Well-known immunoregulatory genes including CSF2, IL32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were upregulated. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as the heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) and eukaryotic initiation factor 4 (eIF4b). We also identified a viral sequence variant with a statistically significant skew associated with age of infection, that may contribute to intracellular host–pathogen interactions. These findings can help identify host mechanisms that can be targeted by prophylactics and/or therapeutics to reduce the severity of COVID-19. |
format | Online Article Text |
id | pubmed-8128904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-81289042021-05-27 Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis Ferrarini, Mariana G. Lal, Avantika Rebollo, Rita Gruber, Andreas J. Guarracino, Andrea Gonzalez, Itziar Martinez Floyd, Taylor de Oliveira, Daniel Siqueira Shanklin, Justin Beausoleil, Ethan Pusa, Taneli Pickett, Brett E. Aguiar-Pulido, Vanessa Commun Biol Article The novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after emerging in Wuhan, China. Here we analyzed public host and viral RNA sequencing data to better understand how SARS-CoV-2 interacts with human respiratory cells. We identified genes, isoforms and transposable element families that are specifically altered in SARS-CoV-2-infected respiratory cells. Well-known immunoregulatory genes including CSF2, IL32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were upregulated. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as the heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) and eukaryotic initiation factor 4 (eIF4b). We also identified a viral sequence variant with a statistically significant skew associated with age of infection, that may contribute to intracellular host–pathogen interactions. These findings can help identify host mechanisms that can be targeted by prophylactics and/or therapeutics to reduce the severity of COVID-19. Nature Publishing Group UK 2021-05-17 /pmc/articles/PMC8128904/ /pubmed/34002013 http://dx.doi.org/10.1038/s42003-021-02095-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Ferrarini, Mariana G. Lal, Avantika Rebollo, Rita Gruber, Andreas J. Guarracino, Andrea Gonzalez, Itziar Martinez Floyd, Taylor de Oliveira, Daniel Siqueira Shanklin, Justin Beausoleil, Ethan Pusa, Taneli Pickett, Brett E. Aguiar-Pulido, Vanessa Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis |
title | Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis |
title_full | Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis |
title_fullStr | Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis |
title_full_unstemmed | Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis |
title_short | Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis |
title_sort | genome-wide bioinformatic analyses predict key host and viral factors in sars-cov-2 pathogenesis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8128904/ https://www.ncbi.nlm.nih.gov/pubmed/34002013 http://dx.doi.org/10.1038/s42003-021-02095-0 |
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