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Engineering a superactivator of smooth muscle gene expression with the Myocardin condensate forming region [ChIP-seq]

GSE294913 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2025/09/02 Platform GPL17021
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 15 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
15 samples: 15 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.
Paper
Engineering a serum response factor superactivator of smooth muscle gene expression with a condensate-forming domainProceedings of the National Academy of Sciences of the United States of America · 2025
Summary (written by the submitters)
Differentiation of smooth muscle cells (SMCs) is accompanied by the expression of a battery of genes controlled by serum response factor (SRF), a ubiquitous transcription factor with weak intrinsic transcriptional activity. Myocardin (MYOCD) is a potent transcriptional coactivator that activates smooth muscle differentiation through its association with SRF.
Read the full summary ↓
MYOCD forms condensates through its highly disordered transcription activation domain (TAD), whereas SRF displays a diffuse distribution within the nucleus. SRF is recruited to nuclear condensates by the TAD of MYOCD (MYOCD-TAD), thereby triggering the smooth muscle gene program. Swapping the weak TAD of SRF with that of MYOCD enables SRF to form condensates and acquire the ability to reprogram fibroblasts to SMCs. SRF-MYOCD-TAD chimeric protein exhibits stronger transcriptional activity on smooth muscle genes than MYOCD. Using protein proximity labelling, quantitative proteomics and super-resolution confocal microscopy, we show that MYOCD-TAD condensates aggregate chromatin remodelers, RNA polymerases, and mRNA processing factors to drive smooth muscle gene expression. These findings provide insights into the mechanisms whereby nuclear condensates promote tissue-specific gene expression and point toward a strategy for engineering superactivators leveraging transcriptional condensates.
Published in
Engineering a serum response factor superactivator of smooth muscle gene expression with a condensate-forming domain
Gan P, Zhou X, Shah AM et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 40953276 · doi:10.1073/pnas.2514363122
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 GSE294913_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 PRJNA1252029 and SRA study SRP579416. Searching any of these in the dataset finder brings you back here.

Study design
15 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 15 sample titles: 15 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.