Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ChIP-sequencing of the IRF1 transcription factor in lung cancer cell lines after stimulation with IFNγ

ABSTRACT: ChIP-sequencing of the IRF1 transcription factor in lung cancer cell lines after stimulation with IFNγ

PROVIDER: PRJNA772770 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

STAT1 and IRF1 enrichment in naive and primed HeLa cells upon IFNγ treatment

Project description:STAT1 and IRF1 transcription factor enrichment by CUT&RUN. HeLa cells were primed with IFNγ for 24 hours, followed with IFNγ washout. After 48h, naïve and primed cells were induced by IFNγ for 1h and 3h. Cells were harvested at indicated time points and processed for CUT&RUN

2023-05-06 | E-MTAB-12625 | biostudies-arrayexpress

ChIP-sequencing of the IRF1 transcription factor in lung cancer cell lines after stimulation with IFNγ

Project description:We performed chromatin immnoprecipitation followed by sequencing (ChIP-Seq) of IRF1 in different LC cell lines.

2023-03-16 | GSE186168 | GEO

IRF1 and IFNγ regulated gene expression in A549 lung epithelial cells

Project description:Identification and comparison of genes induced by IRF1 ectopic expression versus IFNγ treatment in A549 lung epithelial fibroblasts.

2022-02-02 | GSE181861 | GEO

Lung cancer cell lines before and after stimulation with IFNγ

Project description:Lung cancer cell lines before and after stimulation with IFNγ

| PRJNA772768 | ENA

mRNA sequencing of lung cancer cell lines before and after stimulation with IFNγ

Project description:We performed RNA sequencing to assess changes in gene expression in lung cancer cell lines. Total RNA was extracted from the cells, before and after stimulation with IFNγ, using standard approaches. RNA-sequencing data performed in this work was performed and analyzed at the CNAG-CRG.

2023-03-16 | GSE186169 | GEO

IRF1 and IFNγ regulated gene expression in A549 lung epithelial cells

Project description:IRF1 and IFNγ regulated gene expression in A549 lung epithelial cells

| PRJNA753768 | ENA

mRNA sequencing of lung cancer cell lines before and after stimulation with IFNγ

Project description:mRNA sequencing of lung cancer cell lines before and after stimulation with IFNγ

| PRJNA772771 | ENA

STAT1 and IRF1 enrichment in naive and primed HeLa cells upon IFNγ treatment

Project description:STAT1 and IRF1 enrichment in naive and primed HeLa cells upon IFNγ treatment

| PRJEB59934 | ENA

The transcription factor IRF1 and guanylate-binding proteins target activation of the AIM2 inflammasome by Francisella infection

Project description:Inflammasomes are critical for mounting host defense against pathogens. The molecular mechanisms that control activation of the AIM2 inflammasome in response to different cytosolic pathogens remain unclear. Here we found that the transcription factor IRF1 was required for the activation of the AIM2 inflammasome during infection with the Francisella tularensis subspecies novicida (F. novicida), whereas engagement of the AIM2 inflammasome by mouse cytomegalovirus (MCMV) or transfected double-stranded DNA did not require IRF1. Infection of F. novicida detected by the DNA sensor cGAS and its adaptor STING induced type I interferon-dependent expression of IRF1, which drove the expression of guanylate-binding proteins (GBPs); this led to intracellular killing of bacteria and DNA release. Our results reveal a specific requirement for IRF1 and GBPs in the liberation of DNA for AIM2 sensing depending on the pathogen encountered by the cell. We used microarrays to explore the gene expression profiles differentially expressed in Francisella-infected bone marrow-derived macrophages (BMDMs) isolated from Irf1-/-, Ifnar1-/-, Aim2-/- and wild-type mice.

2015-03-04 | E-GEOD-66461 | biostudies-arrayexpress

IFNγ induces a dynamic and complex transcriptional, chromatin and enhancer landscape

Project description:Aims and methods: To analyze how IFNγ induces coding and non-coding nascent transcriptional changes, SNU-seq is used to measure genome-wide changes in nascent transcription in untreated, 0.5hr, 2hr and 24hr IFNγ treated Hep3B cells. SNU-seq identifies the last transcribed nucleotide at near single-nucleotide resolution. 3'-end RNA-seq is used to examine RNA levels. ChIPmentation and ATAC-seq are used to assess the differential chromatin landscape upon IFNγ treatments, measuring H3K27ac, H3K4me3 and CTCF genome-wide changes as well as DNA accessibility in untreated, 0.5hr, 2hr and 24hr IFNγ treated Hep3B cells. Higher-order chromatin structure is investigated upon IFNγ treatments using Capture-C to measure promoter interactions of three gene promoters; IRF1, STAT1, and CD274. Results: 3'-end RNA-seq reveals IFNγ stimulated genes. SNU-seq identifies dynamic transcription at genes and non-coding intergenic regions and is used to demonstrate differential APA upon IFNγ treatments. By measuring transcription at nucleosome depleted regions, differential enhancer activity was demonstrated. IFNγ induces hundreds of methylation changes and thousands of acetylation changes over 24hrs. Unlike H3K4me3 which is deposited at late timepoints, H3K27ac is dynamically deposited. This acetylation is sometimes sustained throughout 24hrs but is often transiently deposited. CTCF shows very few binding changes throughout the timecourse. IFNγ induces significant changes in promoter:enhancer interactions at IRF1 and STAT1. The CD274 promoter loops to the nearest gene promoter; PLGRKT.

2021-10-12 | GSE172053 | 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