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Post-replicative chromatin accessibility predicts cell fate change.

GSE296014 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 81 samples Submitted 2026/02/19 Platform GPL19057
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 81 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
81 samples: 27 conditions, mostly in triplicateGroups 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
Post-replicative chromatin accessibility predicts cell fate changeStem cell reports · 2026
Summary (written by the submitters)
It has long been hypothesized that DNA replication is important in reconfiguring the chromatin landscape during cell identity changes in development, disease, and reprogramming contexts. There is now a large body of work showing that DNA replication indeed alters chromatin structure and composition, but a function for these changes has remained elusive.
Read the full summary ↓
Using replication-coupled ATAC-seq in differentiating embryonic stem cells and reprogramming mouse embryonic fibroblasts, we profiled replicated and unreplicated chromatin within the same cells and observed de novo chromatin opening specifically in the replicated fraction. These opening events created an accessibility landscape similar to that seen in the unreplicated fraction from later timepoints, especially in reprogramming. By parsing reprogramming fibroblasts based on proliferative history, we confirmed that reprogramming potential can be predicted by proliferation rate. This work bridges the gap between replication-induced structural chromatin changes and functional consequences by demonstrating that replication facilitates a “window of opportunity” that advances the chromatin landscape during cell identity change.
Published in
Post-replicative chromatin accessibility predicts cell fate change
Knudsen TE, Reverón-Gómez N, Biran A et al. · Stem cell reports 2026 · PMID 41720083 · doi:10.1016/j.stemcr.2026.102821
This dataset
Open GSE296014 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 GSE296014_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 PRJNA1257322 and SRA study SRP582389. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41720083) ↗
Study design
27 conditions, mostly in triplicate
MEF_6h_nascent_repliATAC ×3 MEF_6h_mature_repliATAC ×3 MEF_6h_bulk_ATAC ×3 MEF_12h_nascent_repliATAC ×3 MEF_12h_mature_repliATAC ×3 MEF_12h_bulk_ATAC ×3 MEF_36h_nascent_repliATAC ×3 MEF_36h_mature_repliATAC ×3 +19 more

Supports a between-group comparison across 81 samples.

How we read this: 27 replicated groups read from 81 sample titles; they account for 81 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

+ 41 more — browse all 81 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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