About: Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis

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About: Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis
Creator	Lal, Ferrarini, &
Source	BioRxiv
abstract	The novel betacoronavirus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after initially emerging in Wuhan, China. Here we applied a novel, comprehensive bioinformatic strategy to public RNA sequencing and viral genome sequencing data, to better understand how SARS-CoV-2 interacts with human cells. To our knowledge, this is the first meta-analysis to predict host factors that play a specific role in SARS-CoV-2 pathogenesis, distinct from other respiratory viruses. We identified differentially expressed genes, isoforms and transposable element families specifically altered in SARS-CoV-2 infected cells. Well-known immunoregulators including CSF2, IL-32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were overexpressed. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as hnRNPA1, PABPC1 and eIF4b, which may play important roles in the viral life cycle. We also detected four viral sequence variants in the spike, polymerase, and nonstructural proteins that correlate with severity of COVID-19. The host factors we identified likely represent important mechanisms in the disease profile of this pathogen, and could be targeted by prophylactics and/or therapeutics against SARS-CoV-2. Graphical Abstract
has issue date	2020-08-19(xsd:dateTime)
bibo:doi	10.1101/2020.07.28.225581
has license	biorxiv
sha1sum (hex)	485823ec809e68d06c8f741b9d97c612a88d3621
schema:url	https://doi.org/10.1101/2020.07.28.225581
resource representing a document's title	Genome-wide bioinformatic analyses predict key host and viral factors in SARS-CoV-2 pathogenesis
schema:publication	bioRxiv
resource representing a document's body	covid:485823ec809e68d06c8f741b9d97c612a88d3621#body_text
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