Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

40 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization.

ABSTRACT: Purpose: Description of a spike-adjusting-method (SAM) to normalize ChIP-seq data . Methods: We performed ChIP-seq of POLR3D and POLR2B with mouse liver supplemented with 2.5% of human DNA. Human DNA will be used as an internal control for ChIP-seq quantification. Results: We show that using the SAM for ChIP-seq quantification improve similarity of POLR3D and POLR2B ChIP-seq replicates samples and improve difference between samples originate from different conditions. Conclusions: The SAM improves comparison of ChIP-seq samples, either by increasing similarity between replicates or by emphasise differences between conditions. Chromatin Immuno-precipitations were performed with antibodies directed against POLR3D (Pol III) and POLR2B (Pol II) using mouse liver material supplemented with human DNA. Immuno-precipitated DNA was next sequenced using Illumina HiSeq. Three different concentrations of human spiked DNA were tested for the Pol III ChIP (2.5%, 5% and 10%). We also sequenced the corresponding inputs (crosslinked DNA from mouse liver). Two concentrations of human spiked DNA (5% and 10%) were tested for the Pol 2 ChIP. We also sequenced the corresponding inputs (crosslinked DNA from mouse liver).

ORGANISM(S): Mus musculus

SUBMITTER: Gergana Bounova

PROVIDER: E-GEOD-52049 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Similar Datasets

Quantifying ChIP-seq data: a spiking method providing an internal reference for sample-to-sample normalization.

Project description:Purpose: Description of a spike-adjusting-method (SAM) to normalize ChIP-seq data . Methods: We performed ChIP-seq of POLR3D and POLR2B with mouse liver supplemented with 2.5% of human DNA. Human DNA will be used as an internal control for ChIP-seq quantification. Results: We show that using the SAM for ChIP-seq quantification improve similarity of POLR3D and POLR2B ChIP-seq replicates samples and improve difference between samples originate from different conditions. Conclusions: The SAM improves comparison of ChIP-seq samples, either by increasing similarity between replicates or by emphasise differences between conditions.

2014-04-02 | GSE52049 | GEO

POLR3G and POLR3GL-RNA polymerase III target genes

Project description:Purpose: Characterization of the target genes of two versions of the Polymerase III (pol III), one containing POLR3G subunit or POLR3GL subunit, in different tissues. Methods: We performed ChIP_seq of POLR3D and the two variants subunits, POLR3G and POLR3GL in Human IMR90 cells, Mouse liver and Mouse Hepatocarcinoma Hepa 1-6 cells in order to locate and analyse total pol III, POLR3G and POLR3GL-containing pol III in various tissues. Results: We show that POLR3G- as well as POLR3GL-containing pol III are present in cultured cell lines and in normal mouse liver, although the relative amounts of the two forms vary, with the POLR3G-containing pol III relatively more abundant in dividing cells. Both forms of pol III occupy the same target genes, in very constant proportions within one cell line, suggesting that the two forms of pol III have similar function with regard to specificity for target genes. Conclusions: POLR3G and POLR3GL occupy the same target genes, but they are differentially expressed under different conditions and in different cell types. Pol III target genes in human IMR cells, Mouse liver, and Mouse Hepatocarcinoma cells were identified by chromatin Immuno-precipitation followed by deep sequencing using Illumina HiSeq. For Human IMR90 cells, we used antibodies against POLR3D, POLR3G, POLR3GL and BDP1. For Mouse data, we targeted POLR3D, POLR3G and POLR3GL and did ChIP_seq replicates. We also sequenced the corresponding inputs (crosslinked DNA of IMR90 cells, Mouse liver, and Mouse Hepatocarcinoma cells). This represents a total of 20 samples.

2013-10-01 | E-GEOD-47849 | biostudies-arrayexpress

Genome-wide MAF1-dependent regulation of RNA polymerase III transcription [RNA-Seq]

Project description:In higher eukaryotes, an important mechanism to tune translation in different tissues and conditions is mTORC1-dependent regulation of tRNAs transcription by RNA polymerase III (Pol III), as the relative amount of tRNAs tightly coordinates with the translational needs of the cell. mTORC1 contributes to regulate protein synthesis through its direct substrate MAF1, which functions as a negative regulator of Pol III transcription in response to stimuli such as serum starvation or rapamycin treatment. Here, we applied ChIP-seq to examine the Pol III occupancy profile in human fibroblasts and report evidence of a genome wide, MAF1-dependent coordinated response to favorable or stress growth conditions. Strikingly, while a set of genes is extremely responsive in terms of Pol III binding, other genes are mostly unperturbed, yet associated with transcriptionally engaged polymerases as revealed by nascent EU-labeled RNA-seq (neuRNA-seq). As shown by DamIP-seq, the responsiveness of a subset of genes is tightly connected to the rapid and transient interaction of MAF1 with DNA-bound Pol III. We performed duplicate ChIP-seq experiments for the Rpc4 (POLR3D) subunit of RNA polymerase III in IMR90hTert cells grown in the presence of fetal bovine serum (FBS), serum starved (SS), serum starved and treated with insulin (SS+I), serum starved and treated with insulin and rapamycin (SS+R+I). Additional ChIP-seq profiles were generated in cells treated with MAF1 siRNAs and serum starved. MAF1 binding was addressed by DamIP-seq, using two replicates per clone of IMR90hTert cells expressing HA-tagged MAF1-DamK9A (2 different clones) or EGFP-DamK9A (2 different clones). To monitor dynamic transcription profiles we did neusRNA-seq in IMR90hTert cells EU-labeled or mock (DMSO)-labeled. For both DamIP-seq and neusRNA-seq, cells were either unperturbed or serum starved.

2016-02-15 | E-GEOD-73929 | biostudies-arrayexpress

Genome-wide MAF1-dependent regulation of RNA polymerase III transcription [ChIP-Seq]

2016-02-15 | E-GEOD-73926 | biostudies-arrayexpress

Genome-wide MAF1-dependent regulation of RNA polymerase III transcription [DamIP-Seq]

2016-02-15 | E-GEOD-73928 | biostudies-arrayexpress

CTCF promotes RNA pol II pausing and links DNA methylation to alternative splicing

Project description:This SuperSeries is composed of the following subset Series: GSE31485: CTCF promotes RNA pol II pausing and links DNA methylation to alternative splicing [ChIP-Seq] GSE31486: CTCF promotes RNA pol II pausing and links DNA methylation to alternative splicing [RNA-Seq] Refer to individual Series

2011-10-05 | E-GEOD-31278 | biostudies-arrayexpress

Cancer growth and metastasis gene pathways are regulated by Methyl-CpG Binding Domain Protein 2 (Mbd2) in liver cancer and are altered by the ubiquitous methyl donor S-adenosyl methionine (SAM)

Project description:Perpose:We examined here whether SAM, which alters DNA methylation dynamics, interferes with the activity of Methyl-CpG Binding Domain Protein 2(Mbd2). Methods: mRNA of MBD2 knocked down of Skhep1 and HepG2 cells were generated by deep sequencing using Illumina GAIIx. DNA enriched by our designed microarray of MBD2 knocked down Skhep1 and HepG2 cells were also generated by deep sequencing using Illumina GAIIx. ChIP (Chromatin immunoprecipitation) was performed using ChIP-IT Express Kit with MBD2 antibody of SAM treated Skhep1, HepG2 and NorHep cells. concluds: SAM treatment results in reduction and redistribution of Mbd2 binding across genomic features in liver cancer cells, which is different from the response in untransformed liver cells. There is significant overlap between genes whose Mbd2 binding, DNA methylation and transcription are altered by Mbd2 depletion or SAM treatment. These data suggest that Mbd2 has a cancer specific footprint in binding, DNA methylation and transcription in liver cancer cells that is altered by SAM treatment. SAM selective impact on liver cancer cells is partially mediated by altering cancer specific Mbd2 binding. These data provide a molecular rationale for using either SAM or other Mbd2 modulators for treating/preventing liver cancer.

2021-02-10 | GSE166416 | GEO

POLR3G and POLR3GL-RNA polymerase III target genes

2013-10-01 | GSE47849 | GEO

Establishment of a novel in vitro transcription assay

Project description:RNA Polymerase II (Pol II) transcriptional recycling is an underappreciated mechanism for which the required factors and contributions to overall gene expression levels are poorly understood. We describe an in vitro methodology facilitating unbiased identification of putative RNA Pol II transcriptional recycling factors and quantitative measurement of transcriptional output from recycled transcriptional components. By combing our in vitro transcription assays with other experiments (e.g. in vivo dynamic ChIP-seq assays), we identified PAF1 complex components as drivers for transcription recycling, revealing a new layer in controlling Pol II-dependent transcription. Our findings also point to RNA Pol II transcription recycling as a mechanism that functions aberrantly in disease states such as cancer, and indicate the potential to target factors such as PAF1 that drive RNA Pol II recycling in cancer.

2021-11-03 | PXD027143 | Pride

Establishment of a novel in vitro transcription assay

Project description:RNA Polymerase II (Pol II) transcriptional recycling is an underappreciated mechanism for which the required factors and contributions to overall gene expression levels are poorly understood. We describe an in vitro methodology facilitating unbiased identification of putative RNA Pol II transcriptional recycling factors and quantitative measurement of transcriptional output from recycled transcriptional components. By combing our in vitro transcription assays with other experiments (e.g. in vivo dynamic ChIP-seq assays), we identified PAF1 complex components and phospho-MED1 as drivers for transcription recycling, revealing a new layer in controlling Pol II-dependent transcription. Our findings also point to RNA Pol II transcription recycling as a mechanism that functions aberrantly in disease states such as cancer, and indicate the potential to target factors such as PAF1 and phospho-MED1 that drive RNA Pol II recycling in cancer.

2021-11-03 | PXD017881 | 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