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A recombinant TACI-Fc fusion protein targets IgA plasma cells in a mouse model of systemic lupus erythematosus

GSE299922 Mus musculus (mouse) RNA-seq (gene expression) 58 samples Submitted 2026/05/14 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 58 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
58 samples: 8 conditions, mostly with about 7 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)
BAFF and APRIL play an important role in driving systemic lupus erythematosus (SLE) immunopathogenesis and kidney damage in lupus nephritis (LN); however, the underlying immune mechanisms contributing to disease pathology and the factors that increase risk of end organ damage are poorly understood. To investigate molecular profiles during the progression of LN, we carried out gene expression analysis on kidneys and spleens from lupus-prone NZM2328 mice treated for four weeks from the time of disease onset.
Read the full summary ↓
We focused on female mice treated with BAFF and BAFF/APRIL inhibitors alongside cyclophosphamide as a standard therapy to identify mechanisms associated with improved renal outcomes. Inhibition of BAFF alone had a limited impact on gene expression profiles of diseased mice, decreasing myeloid cell and increasing metabolic gene signatures. However, targeting both BAFF and APRIL through competitive inhibition with a TACI-Fc fusion protein significantly altered immune populations in the spleen and depleted IgA plasma cells and also decreased pro-inflammatory immune cells and cytokines in the kidneys of diseased mice. All therapies had a broad impact on kidney pathology through reduction of proteinuria. Targeting both BAFF and APRIL is necessary to reduce autoreactive plasma cell generation and kidney inflammation effectively and especially to decrease IgA secreting plasma cells. The impact of targeting both members of the BAFF family of cytokines in lupus-prone NZM2328 mice provides support for its application in the treatment of human LN.
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 GSE299922_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 PRJNA1277327 and SRA study SRP592335. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly with about 7 replicates each
Kidney_Control_Fc ×8 Spleen_Control_Fc ×8 Kidney_anti_BAFF ×7 Kidney_TACI_Fc ×7 Kidney_Cyclo ×7 Spleen_anti_BAFF ×7 Spleen_TACI_Fc ×7 Spleen_Cyclo ×7

Supports a between-group comparison across 58 samples.

How we read this: 8 replicated groups read from 58 sample titles; they account for 58 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

+ 18 more — browse all 58 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.