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Connecting microRNA genes to the core transcriptional regulatory circuitry of embryonic stem cells

GSE11724 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 25 samples Submitted 2008/07/30 Platform GPL9185
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 25 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
25 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
MicroRNAs (miRNAs) are crucial for normal embryonic stem (ES) cell self-renewal and cellular differentiation, but how miRNA gene expression is controlled by the key transcriptional regulators of ES cells has not been established. We describe here a new map of the transcriptional regulatory circuitry of ES cells that incorporates both protein-coding and miRNA genes, and which is based on high-resolution ChIP-seq data, systematic identification of miRNA promoters, and quantitative sequencing of short transcripts in multiple cell types.
Read the full summary ↓
We find that the key ES cell transcription factors are associated with promoters for most miRNAs that are preferentially expressed in ES cells and with promoters for a set of silent miRNA genes. This silent set of miRNA genes is co-occupied by Polycomb Group proteins in ES cells and expressed in a tissue-specific fashion in differentiated cells. These data reveal how key ES cell transcription factors promote the miRNA expression program that contributes to self-renewal and cellular differentiation, and integrate miRNAs and their targets into an expanded model of the regulatory circuitry controlling ES cell identity. Keywords: ChIP-seq analysis of ES cell transcriptional regulators and chromatin modifications. Cell-type comparison of short RNA transcritome. Analysis of changes in short RNA transcritome upon Oct4 ablation.
This dataset
Open GSE11724 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE11724_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA106023 and SRA study SRP000712. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 18692474) ↗
Samples in this study

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+ 25 more — browse all 25 samples with per-sample file links →

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