Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases [ChIP-seq]

ABSTRACT: Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases [ChIP-seq]

PROVIDER: PRJNA989557 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR25084622.fastq.gz	Fastqsanger.gz
	SRR25084623.fastq.gz	Fastqsanger.gz
	SRR25084624.fastq.gz	Fastqsanger.gz
	SRR25084625.fastq.gz	Fastqsanger.gz
	SRR25084626.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 20

Similar Datasets

Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases

Project description:Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases

| PRJNA989553 | ENA

Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases [RNA-seq]

Project description:Sequence-to-expression approach to identify etiological non-coding DNA variations in P53 and cMYC-driven diseases [RNA-seq]

| PRJNA988153 | ENA

Gene expression analysis of cMyc-deficient CD8 T cells retrovirally overexpressing cMyc or AP4

2014-07-13 | GSE58079 | GEO

Gene expression analysis of cMyc-deficient CD8 T cells retrovirally overexpressing cMyc or AP4

Project description:To determine functional overlap between cMyc and AP4 in CD8+ T cell priming, we retrovirally expressed cMyc or AP4 in cMyc-deficient CD8+ T cells and examined gene expression after activation. Naive CD8+ T cells from Myc conditional knockout mice with a tamoxifen inducible Cre transgene were retrovirally transduced with Myc or AP4 followed by a treatment with 4-hydroxytamoxifen in the presence of IL-7 for 2 days. RNA was harvested 48 hours after restimulation of transduced cells with anti-CD3 antibody and gene expression was compared by microarray. CD8+ T cells from littermate wildtype mice that were transduced with an empty retrovirus were used as control.

2014-07-13 | E-GEOD-58079 | biostudies-arrayexpress

Dissection of cMyc+ GC-B cells

Project description:Transcriptomic profiling of the cMyc+ LZ-GC-B cell subpopulations delineated by flow-cytometry

2021-01-12 | GSE146987 | GEO

Transcriptome changes in human endothelial cells with reduced cMYC signaling.

Project description:Transcriptome profiling of human umbilical vein endothelial cells (HUVECs) transduced with lentiviruses encoding FLAG-CAS9 nuclease and control- (gCTL) or cMYC-targeting (gMYC) gRNAS to identify cMYC regulated genes.

2021-01-05 | GSE161815 | GEO

cMyc and Max ChIP-seq analysis in small cell lung carcinoma cells

Project description:cMyc and Max ChIP-seq analysis in a high MYC expressing small cell lung carcinoma cell line (H2171) and a low MYC expressing small cell lung carcinoma cell line (H128). H2171 cells (expressing high levels of cMyc protein) and H128 cells (expressing low levels of cMyc protein) were used to analyze how cMyc overexpression influences its genome-wide occupancy.

2012-09-25 | E-GEOD-41105 | biostudies-arrayexpress

Expression data in HT1080 cells treated with cMyc-shRNA or non-targeting control shRNA

Project description:cMyc is a master regulator of transcription in growing cells. Here, we used microarray to study global transcriptomic expression of cMyc knockdown HT1080 cells to investigate cMyc- regulated gene expression.

2017-06-26 | GSE60558 | GEO

The effect of non-coding DNA variations on P53 and cMYC competitive inhibition at cis-overlapping motifs.

Project description:Non-coding DNA variations play a critical role in increasing the risk for development of common complex diseases, and account for the majority of SNPs highly associated with cancer. However, it remains a challenge to identify etiologic variants and to predict their pathological effects on target gene expression for clinical purposes. Cis-overlapping motifs (COMs) are elements of enhancer regions that impact gene expression by enabling competitive binding and switching between transcription factors. Mutations within COMs are especially important when the involved transcription factors have opposing effects on gene regulation, like P53 tumor suppressor and cMYC proto-oncogene. In this study, genome-wide analysis of ChIP-seq data from human cancer and mouse embryonic cells identified a significant number of putative regulatory elements with signals for both P53 and cMYC. Each co-occupied element contains, on average, two COMs, and one common SNP every two COMs. Gene ontology of predicted target genes for COMs showed that the majority are involved in DNA damage, apoptosis, cell cycle regulation, and RNA processing. EMSA results showed that both cMYC and P53 bind to cis-overlapping motifs within a ChIP-seq co-occupied region in Chr12. In vitro functional analysis of selected co-occupied elements verified enhancer activity, and also showed that the occurrence of SNPs within three COMs significantly altered enhancer activity. We identified a list of COM-associated functional SNPs that are in close proximity to SNPs associated with common diseases in large population studies. These results suggest a potential molecular mechanism to identify etiologic regulatory mutations associated with common diseases.

| S-EPMC6281388 | biostudies-literature

Mutant p53, mutant KRAS and hyperactive CMYC downstream proteomic programs in lung, colon and pancreatic cancer cell lines

Project description:Human cancer cell lines indicated in the file names, with stably overexpressed Cas9 nuclease, were transfected with (C) control sgRNA or (P) TP53-specific sgRNA, (K) KRAS-specific sgRNA or (M) CMYC-specific sgRNA. Each experiment was done by transfection of sgRNA pair - control (C) or causing a NHEJ-mediated knock-out of the target genes (P, K or M). Samples for proteomics were collected 48h post sgRNA transfection without selection, in three biological replicates each (indicated with numbers 1-3). In cell lines with three activated oncogenes, three separate oncogene-targeting transfections were carried out.

2024-10-17 | PXD037398 | 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