Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Severe acute respiratory syndrome coronavirus 2

ABSTRACT: Analysis of SARS-CoV-2 known and novel subgenomic mRNAs in cell culture, animal model, and clinical samples using LeTRS, a bioinformatic tool to identify unique sequence identifiers

PROVIDER: PRJNA699398 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR14584411_1.fastq.gz	Fastqsanger.gz
	SRR14584411_2.fastq.gz	Fastqsanger.gz
	SRR14584412_1.fastq.gz	Fastqsanger.gz
	SRR14584412_2.fastq.gz	Fastqsanger.gz
	SRR14584413_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 152

Similar Datasets

Applying defective interfering viral genome bioinformatics for detection of coronavirus subgenomic RNAs

Project description:Coronavirus RNA-dependent RNA polymerases produce subgenomic RNAs (sgRNAs) that encode viral structural and accessory proteins. The kinetics and efficiency of sgRNAs production during viral replication in different cell types or sgRNA transcription by individual viral strains or variants are yet to be studied to shed light on fundamental mechanisms necessary for viral replication. User-friendly bioinformatic tools to detect and quantify sgRNA production are urgently needed to study a growing number of next-generation sequencing (NGS) data of SARS-CoV-2. Starting from DI-tector, a bioinformatic tool for the detection of viral defective interfering genomes, here we introduced sgDI-tector to identify and quantify sgRNA in SARS-CoV-2 NGS data. This new tool allowed detection of sgRNA without initial knowledge of the transcription-regulatory sequences. As a proof of principle, we analyzed new data sets and successfully detected the nested set of sgRNAs produced with the ranking M>ORF3a>N>ORF6>ORF7a>ORF8>S>E>ORF7b. Our study also compared, for the first time for SARS-CoV-2, the level of sgRNA production with other types of viral RNA products such as defective interfering viral genomes.

2021-12-28 | GSE180632 | GEO

Severe acute respiratory syndrome coronavirus 2

Project description:Benchmark datasets for technical evaluation of SARS-CoV-2 bioinformatic analysis workflows

| PRJNA763390 | ENA

Severe acute respiratory syndrome coronavirus 2

Project description:Animal model study for COVID-19 using Syrian hamsters

| PRJDB14262 | ENA

Project description:Digital sequencing using structured unique molecular identifiers

| PRJNA844028 | ENA

Project description:Digital RNA sequencing using unique molecular identifiers

| PRJNA967219 | ENA

CRISPR_RSL

Project description:CRISPR/Cas9 screening using unique molecular identifiers

| PRJEB18436 | ENA

Sequencing Universal Human Reference RNA by Smart-seq and early barcoding library preparation methods

Project description:Many library preparation methods are available for gene expression quantification. Here, we sequenced and analysed Universal Human Reference RNA (UHRR) prepared using Smart-Seq2, TruSeq (public data) and a protocol using unique molecular identifiers (UMIs) that all include the ERCC spike-in mRNAs to investigate the effects of amplification bias on expression quantification.

2016-05-13 | GSE75823 | GEO

Characterisation of the transcriptome and proteome of SARS-CoV-2 using direct RNA sequencing and tandem mass spectrometry reveals evidence for a cell passage induced in-frame deletion in the spike glycoprotein that removes the furin-like cleavage site.

Project description:Direct RNA sequencing using an Oxford Nanopore MinION characterised the transcriptome of SARS-CoV-2 grown in Vero E6 cells. This cell line is being widely used to propagate the novel coronavirus. The viral transcriptome was analysed using a recently developed ORF-centric pipeline. This revealed the pattern of viral transcripts, (i.e. subgenomic mRNAs), generally fitted the predicted replication and transcription model for coronaviruses. A 24 nt in-frame deletion was detected in subgenomic mRNAs encoding the spike (S) glycoprotein. This feature was identified in over half of the mapped transcripts and was predicted to remove a proposed furin cleavage site from the S glycoprotein. This motif directs cleavage of the S glycoprotein into functional subunits during virus entry or exit. Cleavage of the S glycoprotein can be a barrier to zoonotic coronavirus transmission and affect viral pathogenicity. Allied to this transcriptome analysis, tandem mass spectrometry was used to identify over 500 viral peptides and 44 phosphopeptides, covering almost all of the proteins predicted to be encoded by the SARS-CoV-2 genome, including peptides unique to the deleted variant of the S glycoprotein. Detection of an apparently viable deletion in the furin cleavage site of the S glycoprotein reinforces the point that this and other regions of SARS-CoV-2 proteins may readily mutate. This is of clear significance given the interest in the S glycoprotein as a potential vaccine target and the observation that the furin cleavage site likely contributes strongly to the pathogenesis and zoonosis of this virus. The viral genome sequence should be carefully monitored during the growth of viral stocks for research, animal challenge models and, potentially, in clinical samples. Such variations may result in different levels of virulence, morbidity and mortality.

2020-03-31 | PXD018241 | Pride

Sequencing Universal Human Reference RNA by Smart-seq and early barcoding library preparation methods

2016-05-13 | E-GEOD-75823 | biostudies-arrayexpress

The short- and long-range RNA Interactome of SARS-CoV-2

Project description:The Coronaviridae are a family of positive- strand RNA viruses that includes SARS-CoV-2, the etiologic agent of the COVID-19 pandemic. Bearing the largest single stranded RNA genome in nature, coronaviruses are critically dependent on long-distance RNA-RNA interactions to regulate the viral transcription and replication pathways. Here we experimentally mapped the in vivo long-range RNA interactome of the full-length SARS-CoV-2 genome and the subgenomic mRNAs. We uncover a network of RNA-RNA interactions spanning tens of thousands of nucleotides that facilitate the unique transcription mode of coronaviruses, and reveal that the viral genome adopts alternative topologies inside cells and undergoes genome cyclization. Moreover, we discover long RNA-bridges between adjacent open reading frames that encircle the programmed ribosomal frame-shifting element, and demonstrate their conservation in vivo for the related MERS-CoV. Finally, the SARS-CoV-2 genome and subgenomic mRNAs engage in different sets of interactions with cellular RNAs. Our findings illuminate RNA-based mechanisms governing replication, discontinuous transcription, and translation of coronaviruses, and will aid future efforts to develop antiviral strategies.

2020-10-21 | GSE154662 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data