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B Cell-Intrinsic Type I Interferon Signaling Contributes to Defective Vaccine [GEX]

GSE304898 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/02/19 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 12 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.
Paper
B cell-intrinsic type I interferon signaling contributes to defective antibody responses to a model antigen during persistent LCMV infectionCell reports · 2026
Summary (written by the submitters)
Affinity maturation and vaccine efficacy are compromised during chronic viral infections, yet the underlying mechanisms remain unclear. Using the LCMV Cl13 model, we show that IFN-I signaling in B cells plays a central role. IFN-I promotes early B cell activation but reduces clonal diversity and delays IgG1⁺ B cell entry into germinal centers, impairing high-affinity clone selection.
Read the full summary ↓
Deletion of IFNAR1 in B cells partially restores NP-specific IGHV1-72 usage and GC access but fails to fully rescue affinity maturation, suggesting a contribution of extrinsic factors. Somatic hypermutation remains elevated in both genotypes, though slightly reduced in IFNAR1⁻/⁻ B cells. BASELINe analysis indicates weaker selection pressure in CDRs, potentially reflecting impaired affinity-based selection. This defect correlates with a reduced TFR/TFH ratio. Our results show that intrinsic and extrinsic IFN-I-dependent mechanisms synergize to disrupt B cell fate. These findings establish IFN-I as a key regulator of humoral immunity and highlight mechanisms underlying poor vaccine response.
Published in
B cell-intrinsic type I interferon signaling contributes to defective antibody responses to a model antigen during persistent LCMV infection
Laulhé X, Adda-Bouchard Y, Lopez G et al. · Cell reports 2026 · PMID 41865370 · doi:10.1016/j.celrep.2026.117145
This dataset
Open GSE304898 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 GSE304898_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 PRJNA1295942 and SRA study SRP606664. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41865370) ↗
Study design
12 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 12 sample titles: 12 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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