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Combinatorial Transcriptional Control in Blood Stem/Progenitor Cells: Genome-wide Analysis of 10 major Transcriptional Regulators

GSE22178 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 11 samples Submitted 2010/10/07 Platform GPL9250
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 11 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
11 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)
Combinatorial transcription factor (TF) interactions control cellular phenotypes and therefore underpin stem cell formation, maintenance and differentiation. Here we report the genome-wide binding patterns and combinatorial interactions for 10 key regulators of blood stem/progenitor cells (Scl/Tal1, Lyl1, Lmo2, Gata2, Runx1, Meis1, Pu.1, Erg, Fli-1, Gfi1b) thus providing the most comprehensive TF dataset for any adult stem/progenitor cell type to date.
Read the full summary ↓
Genome-wide computational analysis of complex binding patterns followed by functional validation revealed the following: First, a previously unrecognized combinatorial interaction between a heptad of TFs (Scl, Lyl1, Lmo2, Gata2, Runx1, Erg, Fli-1). Second, we implicate direct protein-protein interactions between four key regulators (Runx1, Gata2, Scl, Erg) in stabilising complex binding to DNA. Third, Runx1+/-::Gata2+/- compound heterozygous mice are not viable with severe haematopoietic defects at midgestation. Taken together, this study demonstrates the power of genome-wide analysis in generating novel functional insights into the transcriptional control of stem and progenitor cells.
This dataset
Open GSE22178 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE22178_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 PRJNA127555 and SRA study SRP002575. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 20887958) ↗
Samples in this study

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+ 11 more — browse all 11 samples with per-sample file links →

Datasets on a similar topic

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