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Transcriptional control of Sulf1 by WT1 primes epicardial signalling and fate by modifying extracellular heparan sulfate status [CUT&Run]

GSE299998 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 18 samples Submitted 2026/08/06 Platform GPL19057
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 18 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
18 samples: 18 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
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)
Considering the transcriptional correlations we observed between WT1 and 6-O-endosulfatases in the epicardium, we sought to elucidate whether WT1 regulates 6-O-endosulfatase expression directly and how its binding may differ between Sulf1 and Sulf2 in the epicardium. We employed CUT&RUN-seq experiments that mapped genome-wide binding sites of WT1 and histone modifications in cultured epicardial cells (MEC1).
Read the full summary ↓
We identified weak, although variable, binding of WT1 to the Sulf1 promoter and significant WT1 binding to an intronic enhancer, marked by active chromatin modification H3K27ac, located in intron 1 of the Sulf1 gene. Interestingly, the CUT&RUN-seq experiments also revealed significant binding of WT1 to the third intron of the Sulf2 gene, displaying chromatin accessibility without any histone marks or gene activity.
This dataset
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.

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 GSE299998_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1278682 and SRA study SRP592594. Searching any of these in the dataset finder brings you back here.

Study design
18 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 18 sample titles: 18 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.