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Synthetic engineering demonstrates that synergy among enhancers involves an increase in transcriptionally productive enhancer-gene contacts [ChIP-Seq]

GSE306439 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 72 samples Submitted 2025/09/02 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 72 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
72 samples: 28 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)
Enhancers are non-coding cis-regulatory elements that control the expression of distally located genes in a tissue- and time-specific manner. Recent studies indicate that enhancers can differ in their underlying genetic architecture and regulatory properties. However, these different types of enhancers were previously investigated under rather variable conditions (e.g.
Read the full summary ↓
model organism, cell type, enhancer-promoter distance, type of target promoter, etc.), thus introducing confounding factors that make it difficult to discern the distinct regulatory properties of each enhancer type. To overcome these limitations, here we generated transgenic mouse embryonic stem cells (mESC) lines in which different types of synthetic enhancers (i.e. “typical” enhancer, CTCF-associated enhancer, enhancer cluster/super-enhancer) were built upon the same “core” neural enhancer and inserted at the same distance (i.e. 100 Kb) from a typical developmental gene (i.e. Gata6). Subsequently, the mESC lines were differentiated to systematically compare the regulatory properties of the different enhancer types under identical conditions. Regarding the CTCF-associated enhancer, our data revealed that the addition of a CTCF site to the “core” enhancer increased insulation and led to the formation of a smaller contact domain, while having a rather mild effect on enhancer-promoter contact frequency and target gene expression. On the other hand, in comparison to the “core” enhancer alone, the enhancer cluster synergistically increased target gene expression and burst fraction. Importantly, we found that, in contrast to previous models, the strong regulatory activity of the enhancer cluster can not be explained by changes in enhancer-promoter contact frequency or the formation of transcriptional condensates. Instead, our data suggest that the emergent regulatory properties of enhancer clustering preferentially entail an increase in RNA Polymerase II pause release and, thus, in the fraction of enhancer-promoter contacts that are transcriptionally productive.
This dataset
Open GSE306439 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 GSE306439_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 PRJNA1310639 and SRA study SRP612368. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
28 conditions, mostly in duplicate
WT_NPC_CTCF ×2 Enh-CBS_NPC_CTCF ×2 WT_NPC_Rad21 ×2 Enh-CBS_NPC_Rad21 ×2 WT_NPC_Med26 ×2 Enh_NPC_Med26 ×2 4xEnh_NPC_Med26 ×2 WT_NPC_p300 ×2 +36 more

Supports a between-group comparison across 56 samples.

How we read this: 28 replicated groups read from 72 sample titles; they account for 56 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

+ 32 more — browse all 72 samples with per-sample file links →

Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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