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Gene Regulatory Programs that Specify Age-Related Differences during Thymocyte Development (ATAC-Seq)

GSE267918 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 32 samples Submitted 2025/06/04 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 32 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
32 samples: 8 conditions, mostly with about 4 replicates eachGroups 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
Gene-regulatory programs that specify age-related differences during thymocyte developmentCell reports · 2025
Summary (written by the submitters)
T cell development is fundamental to immune system establishment, yet how this development changes with age remains poorly understood. Here, we construct a transcriptional and epigenetic atlas of T cell developmental programs in neonatal and adult mice, revealing the ontogeny of divergent gene regulatory programs. We identify a gene module that diverges with age from the earliest stages of genesis and includes programs that govern effector response and cell cycle regulation.
Read the full summary ↓
Interestingly, the epigenetic atlas reveals that neonates possess more accessible chromatin during early thymocyte development, likely establishing poised gene expression programs that manifest later in thymocyte development. Finally, we leverage this atlas, employing a CRISPR-based perturbation approach coupled with single-cell RNA sequencing as a readout to uncover a conserved transcriptional regulator, Zbtb20, that contributes to age-dependent differences in T cell development. Taken together, our study defines transcriptional and epigenetic programs that regulate age-specific differences in T-cell development.
Published in
Gene-regulatory programs that specify age-related differences during thymocyte development
Ganapathi Sankaran D, Zhu H, Maymi VI et al. · Cell reports 2025 · PMID 40570375 · doi:10.1016/j.celrep.2025.115903
This dataset
Open GSE267918 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 GSE267918_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 PRJNA1113646 and SRA study SRP508816. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40570375) ↗
Study design
8 conditions, mostly with about 4 replicates each
Adult_Thymus_Double_Negative_ATAC ×4 Adult_Thymus_Double_Positive_ATAC ×4 Adult_Thymus_Single_Positive_ATAC ×4 Adult_Spleen_CD8+_T_cell ×4 Neonate_Thymus_Double_Negative_ATAC ×4 Neonate_Thymus_Double_Positive_ATAC ×4 Neonate_Thymus_Single_Positive_ATAC ×4 Neonate_Spleen_CD8+_T_cell ×4

Supports a between-group comparison across 32 samples.

How we read this: 8 replicated groups read from 32 sample titles; they account for 32 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
Datasets on a similar topic

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