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Heart tube morphogenesis is regulated by segment-specific gene regulatory networks controlled by MEF2C [snATAC-seq]

GSE280538 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2024/11/04 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 12 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
12 samples: 12 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
MEF2C controls segment-specific gene regulatory networks that direct heart tube morphogenesisbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
The transcription factor MEF2C plays a critical role in the development of the linear heart tube, but the specific transcriptional networks controlled by MEF2C remain largely undefined. To address this, we performed combined single-nucleus RNA- and ATAC- sequencing on wild type and MEF2C-null embryos at distinct stages of development.
Read the full summary ↓
We identified a broadly “posteriorized” cardiac gene signature and chromatin landscape throughout the heart tube in the absence of MEF2C. By integrating our gene expression and chromatin accessibility data in a deep-learning based model, we were able to construct developmental trajectories for each of the outflow tract, ventricular, and inflow tract lineages and determined how each of these segment-specific trajectories were distinctly altered in the MEF2C-null embryos. We computationally identified potential segment-specific MEF2C-dependent enhancers. Using transgenesis in zebrafish embryos, we identified novel MEF2C-dependent enhancers with activity in the developing heart tube from among these candidates. Finally, using inferred gene regulatory networks we discovered a genetic interaction between MEF2C and the atrial nuclear hormone receptor NR2F2, revealing that the MEF2C-null heart malformations are partly driven by a transcriptional network with increased NR2F2 activity. These studies not only provide a rich description of the genomic regulation of early heart tube development, but provide a generalizable framework for using genetic mutants to dissect the transcriptional networks that govern developmental processes.
Published in
MEF2C controls segment-specific gene regulatory networks that direct heart tube morphogenesis
Muncie-Vasic JM, Sinha T, Clark AP et al. · bioRxiv : the preprint server for biology 2025 · PMID 39554149 · doi:10.1101/2024.11.01.621613
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 GSE280538_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 PRJNA1179365 and SRA study SRP541780. Searching any of these in the dataset finder brings you back here.

Study design
12 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 12 sample titles: 12 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.