Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Expression profile and Histone H3 K4, K9, K27, K36 tri-methylation occupancy through the whole genome between control and AMPK knockdown Hep3B cells

ABSTRACT: Expression profile and Histone H3 K4, K9, K27, K36 tri-methylation occupancy through the whole genome between control and AMPK knockdown Hep3B cells

PROVIDER: PRJNA380925 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR5388680.fastq.gz	Fastqsanger.gz
	SRR5388690.fastq.gz	Fastqsanger.gz
	SRR5388700.fastq.gz	Fastqsanger.gz
	SRR5388710.fastq.gz	Fastqsanger.gz
	SRR5388720.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 106

Similar Datasets

Domain model explains propagation dynamics and stability of K27 and K36 methylation landscape

Project description:Chromatin states must be stably maintained during cell proliferation to uphold cellular identity and genome integrity. Inheritance of histone modifications across cell division is thought to be central in this process. However, the histone modification landscape is challenged by the incorporation of new unmodified histones during each cell cycle and the principles that govern heritability remain poorly defined. Here, we take a quantitative approach and develop a reusable computational model that describes propagation of K27 and K36 methylation states. We measure combinatorial K27 and K36 methylation patterns by quantitative mass spectrometry on subsequent generations of histones in the presence and absence of enzymatic inhibition. Our modelling rejects active global demethylation and invoke the existence of 8 domains defined by distinct methylation endpoints. We find that K27me3 on pre- existing histones stimulates the rate of de novo K27me3 establishment, supporting a read-write mechanism in timely chromatin restoration. Finally, we provide a detailed, quantitative picture of the mutual antagonism between K27 and K37 methylation, and propose that this antagonism enhance the stability of epigenetic states across cell division.

2020-01-29 | PXD014807 | Pride

Expression profile and Histone H3 K4, K9, K27, K36 tri-methylation occupancy through the whole genome between control and AMPK knockdown Hep3B cells

Project description:This SuperSeries is composed of the SubSeries listed below.

2022-03-26 | GSE97191 | GEO

Domain model explain propagation dynamics and stability of K27 and K36 methylation landscapes

Project description:Chromatin states must be stably maintained during cell proliferation to uphold cellular identity and genome integrity. Inheritance of histone modifications across cell division is thought to be central in this process. However, the histone modification landscape is challenged by the incorporation new unmodified histones during each cell cycle and the principles that govern heritability remain poorly defined. Here, we take a quantitative approach and develop a reusable computational model that describes propagation of K27 and K36 methylation states. We measure combinatorial K27 and K36 methylation patterns by quantitative mass spectrometry on subsequent generations of histones in the presence and absence of enzymatic inhibition. Our modelling rejects active global demethylation and invoke the existence of 8 domains defined by distinct methylation endpoints. We find that K27me3 on pre-existing histones stimulates the rate of de novo K27me3 establishment, supporting a read-write mechanism in timely chromatin restoration. Finally, we provide a detailed, quantitative picture of the mutual antagonism between K27 and K37 methylation, and propose that this antagonism enhance the stability of epigenetic states across cell division.

2020-04-08 | GSE135029 | GEO

Chromatin immunoprecipitation of human centromeric protein A, histone3 K4 and K9 modifications, HP1a and HP1g

Project description:Chromatin Immunoprecipitation of centromeric protein A, histone3 K4 and K9 modifications, HP1a and HP1g

2010-02-27 | E-TABM-705 | biostudies-arrayexpress

Domain model explain propagation dynamics and stability of K27 and K36 methylation landscapes

Project description:Domain model explain propagation dynamics and stability of K27 and K36 methylation landscapes

| PRJNA557439 | ENA

Global Mapping of Histone H3 K4 and K27 Trimethylation: Lineage Fate Determination of Differentiating CD4+ T Cells

Project description:Multipotential naïve CD4+ T cells differentiate into distinct lineages including Th1, Th2, Th17, and inducible T regulatory (iTreg) cells. The remarkable diversity of CD4+ T cells begs the question whether the observed changes reflect terminal differentiation with heritable epigenetic modifications or plasticity in T cell responses. We generated genome-wide histone H3 lysine 4 (H3K4) and lysine 27 (H3K27) trimethylation maps in naïve, Th1, Th2, Th17, iTreg, and natural (n)Treg cells. We find that while modifications of signature cytokine genes (Ifng, Il4, and Il17) partially conform to the expectation of lineage commitment, critical transcription factors such as Tbx21 exhibit a broad spectrum of epigenetic states, consistent with our demonstration of T-bet and IFN-γ induction in nTreg cells. Our data suggest an epigenetic mechanism underlying the specificity and plasticity of effector and regulatory T cells and also provide a framework for understanding complexity of CD4+ T helper cell differentiation. genome-wide analysis of histone H3 K4 and K27 trimethylation in different sub-lineages of mouse CD4+ T cells. (12 samples in total)

2009-01-21 | E-GEOD-14254 | biostudies-arrayexpress

Histone 3 K9 and K27 acetylation of enhancers in response to thyroid hormone

Project description:Histone 3 K9 and K27 acetylation of enhancers in response to thyroid hormone

| PRJNA528027 | ENA

Nitrosopumilus sp. K4 strain:K4

Project description:Nitrosopumilus sp. K4 strain:K4 Genome sequencing

| PRJNA683739 | ENA

Methanothermobacter sp. K4 strain:K4

Project description:Methanothermobacter sp. K4 strain:K4 Genome sequencing and assembly

| PRJNA801147 | ENA

β-Carotene enhances the expression of inflammation-related genes and histone H3 K9 acetylation, K4 dimethylation, and K36 trimethylation around these genes in juvenile macrophage-like THP-1 cells.

Project description:β-Carotene is converted into vitamin A in the body and can remove reactive oxygen species. However, it is still unclear whether β-carotene alters the expression levels of inflammation-related genes in macrophages and how this is regulated. In the present study, we investigated whether the administration of β-carotene under hyperglycemic conditions altered the expression level of inflammation-related genes and whether any observed differences were associated with changes in histone modifications in juvenile macrophage-like THP-1 cells. THP-1 cells (from a human monocytic leukemia cell line) were cultured in low glucose (5 mM), high glucose (25 mM), or high glucose (25 mM) + β-carotene (5 μM) media for 1 day, and mRNA expression levels of genes related to oxidative stress and inflammation, and histone modifications were determined by mRNA microarray and qRT-PCR analyses, and chromatin immunoprecipitation assays, respectively. The expression of inflammation-related genes, such as IL31RA, CD38, and NCF1B, and inflammation-associated signaling pathway genes, such as ITGAL, PRAM1, and CSF3R, were upregulated by β-carotene under high-glucose conditions. Under these conditions, histone H3 lysine 4 (K4) demethylation, H3K36 trimethylation, and H3K9 acetylation around the CD38, NCF1B, and ITGAL genes were higher in β-carotene-treated cells than in untreated cells. Treatment of juvenile macrophage-like THP-1 cells with β-carotene under these high glucose conditions induced the expression of inflammation-related genes, K9 acetylation, and K4 di- and K36 trimethylation of histone H3 around these genes.

| S-EPMC9388881 | biostudies-literature

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