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Transcriptomic Changes in the Lacrimal Glands of a Sjogren's Disease Animal Model Highlight Key Molecular Mediators and Altered Biological Functions Underpinning Glandular Inflammation and Hypofunction

GSE309371 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/03/11 Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 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.
Paper
Transcriptomic changes in the lacrimal glands of a Sjogren's disease animal model highlight key molecular mediators and altered biological functions underpinning glandular inflammation and hypofunctionFrontiers in ophthalmology · 2026
Summary (written by the submitters)
Sjogren’s disease (SjD) is a chronic autoimmune condition that targets the lacrimal glands (LGs), resulting in aqueous-deficient dry eye disease (DED). Insufficient or low-grade tear secretion onto the ocular surface affects the normal physiology of the cornea and conjunctiva and can result in ocular surface damage. Herein, we evaluated the transcriptomic profiles of diseased versus healthy LGs to investigate the underlying molecular mechanisms underscoring LG autoimmune inflammation and secretory hypofunction.
Read the full summary ↓
The number of differentially expressed genes between NOR (diseased animal model/strain) and BALB/c (control strain) mice increased in correlation with the development and progression of dacryoadenitis. The most significantly upregulated pathways were primarily related to immune responses, emphasizing the activation of cellular and cytokine-mediated inflammatory responses. Several cytokines, transcription factors, and toll-like receptors were significantly predicted to drive most of the differential gene expression observed across our datasets. Biological processes involving the migration, recruitment, and activation of lymphocytes, but also lipid metabolism, were most significantly impacted in our disease model. Many of the identified dysregulated genes and affected biological functions were similarly regulated in the differential expression datasets of other transcriptomic based studies of SjD patients and mouse models. Taken together, our data reveals that chronic inflammation induces significant alterations to the LG transcriptome, promoting the recruitment of immune cells into the LG and the overactivation of inflammatory responses that severely impedes normal secretory function. Future studies targeting some of the discovered key dysregulated molecules/pathways could open up potential therapeutic avenues for the treatment of chronic LG inflammation and secretory hypofunction.
Published in
Transcriptomic changes in the lacrimal glands of a Sjogren's disease animal model highlight key molecular mediators and altered biological functions underpinning glandular inflammation and hypofunction
Toribio D, Morokuma J, Tai A et al. · Frontiers in ophthalmology 2026 · PMID 41908638 · doi:10.3389/fopht.2026.1697924
This dataset
Open GSE309371 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 GSE309371_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 PRJNA1335259 and SRA study SRP628379. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41908638) ↗
Study design
6 conditions, mostly in triplicate
NOD_3wk_LG_biol ×3 NOD_8wk_LG_biol ×3 NOD_16wk_LG_biol ×3 BALB/c_3wk_LG_biol ×3 BALB/c_8wk_LG_biol ×3 BALB/c_16wk_LG_biol ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
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