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B cell-intrinsic IFN-g promotes CD11c+ age-associated B cell differentiation and compromises affinity-based germinal center selection in lupus

GSE271698 Mus musculus (mouse) RNA-seq (gene expression) 1 samples Submitted 2024/07/13 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 1 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
1 samples
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)
Lupus patients respond less efficiently to vaccinations and are more susceptible to infections. Previously, we have shown, in lupus models, that excessive CD11c+ age-associated B cells (ABCs) not only contribute to autoantibody production but also compromise antigen-specific germinal center (GC) B cell selection and affinity maturation by promoting aberrant T cell activation.
Read the full summary ↓
Yet, how CD11c+ ABC differentiation is regulated is not fully understood. Here we show that B cell-intrinsic IFN-γ is required for excessive CD11c+ ABC differentiation in lupus mice. B cell-intrinsic IFN-γ is mainly produced by CD11c+ ABCs. IFN-γ-deficiency leads to decreased expression of ABC characteristic genes, including Zeb2, an ABC-specific transcription factor recently described. We further show that ablating IFN-γ can normalize T cell overactivation and rescue antigen-specific GC responses in lupus mice. Our study offers insight into the crucial role of B cell-intrinsic IFN-γ in promoting CD11c+ ABC differentiation and compromising affinity-based germinal center selection and affinity maturation in lupus, providing a potential target for lupus treatment.
This dataset
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.

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 GSE271698_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1132944 and SRA study SRP518497. Searching any of these in the dataset finder brings you back here.

Samples in this study

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