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SRF promotes long-range chromatin loop formation and stem cell pluripotency

GSE255733 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 30 samples Submitted 2024/10/09 Platform GPL24247Platform GPL34475Platform GPL30172Platform GPL21103
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 30 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
30 samples: 9 conditions, mostly in duplicateGroups 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)
Serum response factor (SRF) is a transcription factor essential for cell proliferation, differentiation, and migration, and is required for primitive streak and mesoderm formation in the embryo. The canonical roles of SRF are mediated by a diverse set of context-dependent cofactors. Here we show that SRF physically interacts with CTCF and cohesin subunits at TAD boundaries and loop anchors.
Read the full summary ↓
SRF reinforces the insulation of TADs and promotes the formation of long-range chromatin loops. In ES cells, SRF associates with Oct4, Sox2, and Nanog and contributes to the formation of 3D pluripotency hubs. Our findings reveal new roles of SRF in higher-order chromatin organization.
This dataset
Open GSE255733 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 GSE255733_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 PRJNA1076243 and SRA study SRP489684. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 conditions, mostly in duplicate
HiC_ES_WT ×2 HiC_ES_SRF_KO_Cre ×2 HiC_CM_WT ×2 HiC_CM_SRF_KO_Cre ×2 ChIP_ES_SRF_KO_SRF_control ×2 RNA_CM_WT_day3 ×2 RNA_CM_SRF_KO_day3 ×2 ATAC_CM_WT_day4 ×2 +13 more

Supports a between-group comparison across 18 samples.

How we read this: 9 replicated groups read from 30 sample titles; they account for 18 of them. 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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