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Transcription Elongation Factor SPT6 Maintains Epidermal Homeostasis and Suppresses Skin Inflammation in Mice

GSE294435 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2026/03/26 Platform GPL34290
At a glance

Single-cell RNA-seq · mouse · 2 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
2 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
SPT6 maintains epidermal homeostasis by inhibiting an NF-κB-positive feedback loop to prevent excessive inflammationCellular & molecular immunology · 2026
Summary (written by the submitters)
We employed single-cell RNA sequencing (scRNA-seq) using 10x Genomics technology to investigate the impact of Supt6 epidermis-specific knockout on epidermal homeostasis in mice. The histone chaperone SPT6 is a central regulator of genomic stability. Our previous studies have shown that SPT6 promotes epidermal differentiation by regulating transcriptional elongation in human epidermal stem/progenitor cells, but its in vivo role remains unclear.
Read the full summary ↓
Our research has discovered for the first time that the transcriptional elongation factor SPT6 regulates skin inflammation, hair follicle development, and wound healing, providing a novel therapeutic target for clinical treatment of psoriasis and related skin disorders.
Published in
SPT6 maintains epidermal homeostasis by inhibiting an NF-κB-positive feedback loop to prevent excessive inflammation
Sun Y, Xu S, Wang D et al. · Cellular & molecular immunology 2026 · PMID 41922599 · doi:10.1038/s41423-026-01410-1
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 GSE294435_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: 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 PRJNA1249452 and SRA study SRP577866. Searching any of these in the dataset finder brings you back here.

Samples in this study

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