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The X-linked chromatin modifier SMC1A is deregulated in lupus female monocytes and promotes autoimmunity [RNA-Seq]

GSE279728 Homo sapiens (human) RNA-seq (gene expression) 61 samples Submitted 2025/09/01 Platform GPL24676Platform GPL20301Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 61 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
Homo sapiens (human)
Samples
61 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.
Paper
The sex-biased chromatin modifier SMC1A promotes autoimmunity by shaping inflammatory pathways in patients with SLENature communications · 2025
Summary (written by the submitters)
Biological sex underlines the onset of autoimmunity yet the underlying molecular mechanisms remain ill-defined. Female susceptibility is prominent in systemic lupus erythematosus (SLE), an autoimmune disease of substantial burden. Herein we demonstrate that SMC1A, a subunit of the cohesin complex that escapes X-chromosome inactivation, exhibits female-biased expression in monocytes from SLE patients and those cultured under lupus-inducing stimulus.
Read the full summary ↓
By altering SMC1A dosage, the expression of immune-related genes, particularly those responsive to lupus environment, was affected. Active enhancers of immune and inflammatory pathways showed widespread SMC1A redistribution in lupus-like monocytes, as revealed by integrated analysis of SMC1A binding, chromatin activity and accessibility. Our data support SMC1A as a sex-biased chromatin modifier that enhances inflammatory responses in lupus.
Published in
The sex-biased chromatin modifier SMC1A promotes autoimmunity by shaping inflammatory pathways in patients with SLE
Kosmara D, Papanikolaou S, Stathopoulou C et al. · Nature communications 2025 · PMID 41285778 · doi:10.1038/s41467-025-65309-7
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 GSE279728_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 PRJNA1174162 and SRA study SRP539154. Searching any of these in the dataset finder brings you back here.

Samples in this study

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