GEO series

Single-Cell RNA sequencing reveals clonally-expanded CD4+ tissue-resident memory T cells in Histidyl-tRNA Synthetase-induced myositis [1]

GSE335819 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2026/07/17 Platform GPL30173

At a glance

Single-cell RNA-seq · human · 16 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 16 samples: 5 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)

The precise mechanisms underlying the pathogenesis of idiopathic inflammatory myopathy (IIM) remain undefined. However, there has been increasing recognition that tissue-resident memory cells (TRMs) play an important role in the pathogenesis of systemic autoimmune disease. In IIM, TRM-associated transcriptional signatures have been reported, but on a very limited basis.

Read the full summary ↓

By using multimodal single-cell RNA sequencing analysis in our established murine model of histidyl-tRNA synthetase (HRS)-induced myositis, we identified a prominent population of CD4+ TRMs in inflamed skeletal muscle. Muscle CD4+ TRMs exhibited high expression of genes encoding Cd69, Cxcr6, Runx3, and Prdm1, alongside low expression of Klf2, Ccr7, Sell, S1pr1, and Tcf7—a profile that is generally consistent with previous reports of TRM gene signature and that we validate through comparison to transcriptomic profiles of human muscle tissue. Detailed pathway analysis in our model indicates that muscle CD4+ TRMs contribute to innate immune regulatory pathways enriched for TNF and IFN-γ signaling. Furthermore, analysis of TCR clonotype distribution and CDR3 sequence similarity revealed pronounced clonal expansion of CD4⁺ TRMs relative to other T-cell subsets—a pattern that remained stable from 2 to 6 weeks post-immunization. Collectively, these results suggest a potential role for CD4+ TRMs in the pathogenesis of autoimmune myositis.

This dataset

Open GSE335819 in finder → Find more human 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 GSE335819_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1479637 and SRA study SRP710597. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

5 conditions, mostly in triplicate

Ctrl # ×4 IBM ×3 NM ×3 ASyS ×3 DM ×3

Supports a between-group comparison across 16 samples.

How we read this: 5 replicated groups read from 16 sample titles; they account for 16 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

GSM9821637 IBM1 IBM
GSM9821638 NM1 NM
GSM9821639 ASyS1 ASyS
GSM9821640 DM1 DM
GSM9821641 DM2 DM
GSM9821642 ASyS2 ASyS
GSM9821643 ASyS3 ASyS
GSM9821644 IBM2 IBM
GSM9821645 NM2 NM
GSM9821646 NM3 NM
GSM9821647 DM3 DM
GSM9821648 IBM4 IBM
GSM9821649 Ctrl #1 Ctrl #
GSM9821650 Ctrl #2 Ctrl #
GSM9821651 Ctrl #3 Ctrl #
GSM9821652 Ctrl #4 Ctrl #

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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.