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Loss of Nuclear Receptor Nr4a3 Alleviates Cellular Senescence to Promote Adult Direct Cardiac Reprogramming (ATAC-Seq)

GSE267447 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2025/08/22 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 16 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
16 samples: 16 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)
Direct cardiac reprogramming of fibroblast to cardiomyocytes represents a potential means of restoring cardiac function following injury. However, aged and adult fibroblast are less efficient for reprogramming compared with neonatal fibroblast. In this study, through the joint analysis of RNAseq and ATACseq, we found that compared with Neo-iCM, cardiac related features were down-regulated with aging, while fibrosis and SASP related genes were significantly up-regulated with aging.
Read the full summary ↓
Single-cell transcriptomics reveals a bifurcated trajectory of aged iCM reprogramming. Then, we screened 51 transcriptomic and epigenomic regulators of the barriers to aged-iCM reprogramming and found that Nuclear receptor subfamily 4 group A member 3 (Nr4a3), an pro-inflammatory transcription factor, induced cellular senescence to inhibit direct reprogramming during aging. Mechanistically, knockdown of Nr4a3 enhanced direct cardiac reprogramming by promoting cardiac gene programs and inhibiting fibrosis pathway and secretes SASP. In addition, knockdown of Nr4a3 promoted human reprogramming in primary ventricular human cardiac fibroblasts (HCFs) and improved heart function after MI.
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 GSE267447_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 PRJNA1111526 and SRA study SRP507623. Searching any of these in the dataset finder brings you back here.

Study design
16 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 16 sample titles: 16 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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