Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Full-length transcriptome sequencing in Pseudorasbora parva

PROVIDER: PRJNA684765 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR13340258_1.fastq.gz	Fastqsanger.gz
	SRR13340258_2.fastq.gz	Fastqsanger.gz
	SRR13340259_1.fastq.gz	Fastqsanger.gz
	SRR13340259_2.fastq.gz	Fastqsanger.gz
	SRR13340260_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 53

Similar Datasets

Project description:Pseudorasbora parva genome sequencing

| PRJNA868748 | ENA

Pseudorasbora parva

Project description:Pseudorasbora parva overview

| PRJNA377788 | ENA

Pseudorasbora parva

Project description:Pseudorasbora parva alternate pseudohaplotype genome sequencing

| PRJNA843928 | ENA

Pseudorasbora parva

Project description:Pseudorasbora parva principal pseudohaplotype genome sequencing

| PRJNA843929 | ENA

Pseudorasbora parva

Project description:Pseudorasbora parva Raw sequence reads

| PRJNA799666 | ENA

Project description:Full length transcriptome sequencing

| PRJNA893453 | ENA

Transcriptome profiling of renal glomeruli from Parva-fl/fl*hNPHS2Cre and WT mice

Project description:Podocyte specific knockout mice for Parva (Parva-fl/fl*hNPHS2Cre) were generated. Transcriptome profiling (RNA-Seq) and differential gene expression analysis of isolated renal glomeruli from KO and WT mice was performed. Parva KO mice showed transcriptional changes associated with podocyte and glomerular disease.

2022-01-20 | GSE181690 | GEO

Project description:Full-length transcriptome

| PRJNA859128 | ENA

Project description:Cell full-length transcriptome sequencing

| PRJNA931920 | ENA

Long-read transcriptome sequencing reveals abundant promoter diversity in distinct molecular subtypes of gastric cancer

Project description:Deregulated gene expression is a hallmark of cancer, however most studies to date have analyzed short-read RNA-sequencing data with inherent limitations. Here, we combine PacBio long-read isoform sequencing (Iso-Seq) and Illumina paired-end short read RNA sequencing to comprehensively survey the transcriptome of gastric cancer (GC), a leading cause of global cancer mortality. We performed full-length transcriptome analysis across 10 GC cell lines covering four major GC molecular subtypes (chromosomal unstable, Epstein-Barr positive, genome stable and microsatellite unstable). We identify 60,239 non-redundant full-length transcripts, of which >66% are novel compared to current transcriptome databases. Novel isoforms are more likely to be cell-line and subtype specific, expressed at lower levels with larger number of exons, with longer isoform/coding sequence lengths. Most novel isoforms utilize an alternate first exon, and compared to other alternative splicing categories are expressed at higher levels and exhibit higher variability. Collectively, we observe alternate promoter usage in 25% of detected genes, with the majority (84.2%) of known/novel promoter pairs exhibiting potential changes in their coding sequences. Mapping these alternate promoters to TCGA GC samples, we identify several cancer-associated isoforms, including novel variants of oncogenes. Tumor-specific transcript isoforms tend to alter protein coding sequences to a larger extent than other isoforms. Analysis of outcome data suggests that novel isoforms may impart additional prognostic information. Our results provide a rich resource of full-length transcriptome data for deeper studies of GC and other gastrointestinal malignancies.

2021-02-02 | PXD023373 | Pride

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