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T follicular helper cells transiently unlock a plasticity state in germinal centre B cells during the humoral immune response

GSE298426 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 37 samples Submitted 2025/10/29 Platform GPL24247Platform GPL34328
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 37 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
37 samples: 35 distinct titles, 1 of them repeatedGroups 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)
During the germinal centre (GC) reaction, mature B cells undergo rapid and reversible phenotypic shifts that are essential for adaptive immunity. Here we report that GC B cells, unlike other mature B cells, transiently acquire a unique epigenetic plasticity, demonstrated by their enhanced capacity to reprogram to induced pluripotent stem cells.
Read the full summary ↓
This plasticity depends on T follicular helper (TFH) cells and is not due to increased proliferation or MYC activation. Instead, it involves weakening of B-cell identity and derepression of stem and progenitor programs driven by NF-κB and other TFH-derived signals. Thus, physiological GC plasticity is tightly constrained by the affinity maturation process of positive selection. Loss of histone 1, a chromatin compaction regulator restricting the accessibility of embryonic stem cell programs, further enhances GC plasticity by bypassing this gatekeeping mechanism. Importantly, patients with B-cell lymphoma enriched for GC plasticity signatures had worse outcomes, suggesting that this mechanism may also contribute to lymphoma aggressiveness.
This dataset
Open GSE298426 in finder → Find more mouse RNA-seq 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 GSE298426_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 PRJNA1269325 and SRA study SRP588502. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
35 distinct titles, 1 of them repeated
scRNA_WT_Control ×3

How we read this: Read from 37 sample titles: 35 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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