Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: HepG2 glycobiology modification RNA-seq

PROVIDER: PRJNA747040 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR15171150_1.fastq.gz	Fastqsanger.gz
	SRR15171150_2.fastq.gz	Fastqsanger.gz
	SRR15171151_1.fastq.gz	Fastqsanger.gz
	SRR15171151_2.fastq.gz	Fastqsanger.gz
	SRR15171152_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 30

Similar Datasets

Homo sapiens

Project description:HepG2 cells RNA-Seq

| PRJNA261268 | ENA

Project description:sgTET2 HepG2 RNA-seq

| PRJNA781771 | ENA

N6-methyladenosine modification is not a general trait of positive-sense RNA viral genomes

Project description:Despite the nuclear localization of the m6A machinery, the genomes of multiple exclusively-cytoplasmic RNA viruses, such as chikungunya (CHIKV) and dengue (DENV), are reported to be extensively m6A-modified. However, these findings are mostly based on m6A-seq, an antibody-dependent technique with a high rate of false positives. Here, we addressed the presence of m6A in CHIKV and DENV RNAs. For this, we combined m6A-seq and the antibody-independent SELECT and nanopore direct RNA sequencing techniques with functional, molecular, and mutagenesis studies. Following this comprehensive analysis, we found no evidence of m6A modification in CHIKV or DENV transcripts. Furthermore, depletion of key components of the host m6A machinery did not affect CHIKV or DENV infection. Moreover, CHIKV or DENV infection had no effect on the m6A machinery’s localization. Our results challenge the prevailing notion that m6A modification is a general feature of cytoplasmic RNA viruses and underscore the importance of validating RNA modifications with orthogonal approaches.

2024-01-25 | MTBLS6978 | MetaboLights

Elucidation of the epitranscriptomic RNA modification landscape of chikungunya virus

Project description:The genomes of positive-sense (+) single-stranded RNA (ssRNA) viruses are believed to be subjected to a wide range of RNA modifications. In this study, we focused on the chikungunya virus (CHIKV) as a model (+) ssRNA virus to study the landscape of viral RNA modification in infected human cells. Among the 32 distinct RNA modifications analyzed by mass spectrometry, inosine was found enriched in the genomic CHIKV RNA. However, orthogonal validation by Illumina RNA-seq analyses did not identify any inosine modification along the CHIKV RNA genome. Moreover, CHIKV infection did not alter the expression of ADAR1 isoforms, the enzymes that catalyze the adenosine to inosine conversion. Together, this study highlights the importance of a multidisciplinary approach to assess the presence of RNAmodifications in viral RNA genomes.

2024-06-11 | MTBLS8697 | MetaboLights

RNA-Seq in HepG2-shNC and HepG2-shLINC01977 cells

Project description:RNA-Seq in HepG2-shNC and HepG2-shLINC01977 cells

| PRJNA945072 | ENA

Single Cell triple omics sequencing reveals genetic and epigenetic heterogeneity in hepatocellular carcinoma

Project description:Single cell genome, DNA methylome, and transcriptome sequencing has been achieved separately. However, to analyze the regulation of RNA expression by genetic and epigenetic factors within an individual cell, it is necessary to analyze these omics simultaneously from the same single cell. Here we developed a single cell triple omics sequencing technique- scTrio-seq, to analyze the genome, DNA methylome, and transcriptome concurrently of a mammalian cell. 6 single human HepG2 cell line cells were sequenced using the newly developed scTrio-seq, other 2 HepG2 cells were sequenced using scRNA-seq and other 2 HepG2 cells were sequenced using scRRBS as technique control. 6 single mouse embryonic stem cells (mESCs) were sequenced using the newly developted scTrio-seq. Meanwhile, two scRNA-seq and two scRRBS were also completed using two mESCs separately. 26 single cells from hepatocellular carcinoma were sequenced using scTrio-seq to analyze the regulation relations between three omics of cancer cells.

2016-03-01 | E-GEOD-65364 | biostudies-arrayexpress

Project description:The RNA-seq of HepG2 cells

| PRJNA939506 | ENA

Project description:HepG2 CD133+ cells RNA-seq data

| PRJNA641543 | ENA

small RNA-seq in HepG2 cells

Project description:small RNA-seq in HepG2 cells

| PRJNA547632 | ENA

Genome-wide microRNA-expression analysis after p53 activation in hepatocellular carcinoma

Project description:In order to characterize the differentially expressed miRNAs after the p53 activation , small RNA-seq were used after the overexpression of p53 in HepG2 cells. Four samples of HepG2 cells were subjected to small RNA-seq in two biological replicates.The HepG2 cells were treated with 1Âµg/ml doxorubicin for 24 hours to induce the expression of p53. The experimental group(dox-treated HepG2ï¼HepG2_24h_rep1 and HepG2_24h_rep2) and control group(untreated HepG2: HepG2_0h_rep1 and HepG2_0h_rep2) were subjected to small RNA-seq to identify the p53-regulated miRNAs.

2015-11-03 | E-GEOD-74588 | biostudies-arrayexpress

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