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Female Mice with an Xist Deletion in B Cells Can Develop Lupus-Associated Phenotypes

GSE266417 Mus musculus (mouse) RNA-seq (gene expression) 28 samples Submitted 2026/05/15 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 28 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
28 samples: 7 conditions, mostly in triplicateGroups 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)
Systemic lupus erythematosus (SLE) is a female-biased autoimmune disease. X-Chromosome Inactivation (XCI) dosage compensates X-linked genes in females. Disrupted localization of Xist, a critical regulator of XCI, and aberrant expression of X-linked genes in female SLE patients and SLE mouse models suggest that XCI impairment contributes to disease.
Read the full summary ↓
To test this, we conditionally deleted Xist in B cells (Xist cKO mice). Remarkably, some female Xist cKO mice spontaneously develop SLE phenotypes, including expansion of activated B cell subsets, development of disease-associated autoantibodies, and glomerulonephritis. Moreover, female Xist cKO mice with chemically induced SLE developed more activated B cells and dsDNA autoantibodies compared to treated wildtype female mice. Activated B cells from Xist cKO mice with SLE phenotypes have increased expression of X-linked immunity genes implicated in female-biased SLE. Our findings demonstrate that perturbations in B cell XCI maintenance directly contribute to female-biased SLE via upregulation of X-linked immunity-related genes.
This dataset
Open GSE266417 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 GSE266417_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 PRJNA1107144 and SRA study SRP505448. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly in triplicate
CD23+ B cells, WT, ×6 B220- CD138+ Long-Lived Plasma Cells, WT, ×6 CD11c+ Age-Associated B cells, WT, ×4 CD23+ B cells, Xist cKO Low dsDNA, ×3 CD23+ B cells, Xist cKO High dsDNA, ×3 CD11c+ Age-Associated B cells, Xist cKO High … ×3 B220- CD138+ Long-Lived Plasma Cells, Xist cK… ×3

Supports a between-group comparison across 28 samples.

How we read this: 7 replicated groups read from 28 sample titles; they account for 28 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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