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Ptpn2 limits plasma cell fate and antiviral immunity by integrating B cell receptor and IFN-γ signals in B cells

GSE300933 Mus musculus (mouse) RNA-seq (gene expression) 23 samples Submitted 2026/07/07 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 23 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
23 samples: 6 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.
Summary (written by the submitters)
B cell activation and subsequent plasma cell differentiation are two crucial processes in the establishment of long-term immunity. Understanding the signaling pathways that regulate B cell function and terminal differentiation is crucial to human health. Ptpn2 is a protein tyrosine phosphatase whose role in limiting immune cell activation is well chatacterized.
Read the full summary ↓
However, it is not known whether Ptpn2 plays a cell-intrinsic role in regulating B cell development and activation. Using a Ptpn2 B-cell-specific knockout mouse model we have discovered a novel role for Ptpn2 in negatively regulating both BCR and IFN-gamma signaling in B cells. As a result, the absence of Ptpn2 leads to the enhanced terminal differentiation of B cells into plasma cells. Consequently, mice lacking Ptpn2 in B cells present improved antibody responses against viral infections, such as Influenza A virus. Overall, our results reveal a novel role for Ptpn2 in B cell activation, highlighting its potential as a therapeutic target to optimize vaccine responses and enhance immunity against infectious diseases.
This dataset
Open GSE300933 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 GSE300933_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1282684 and SRA study SRP594895. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 4 replicates each
NSWT ×4 NSKO ×4 aIgMKO ×4 IFNgWT ×4 IFNgKO ×4 aIgMWT ×3

Supports a between-group comparison across 23 samples.

How we read this: 6 replicated groups read from 23 sample titles; they account for 23 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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