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Gut microbiota drives vitiligo-related oxidative stress in skin via the metabolite Hippuric Acid

GSE273242 Mus musculus (mouse) RNA-seq (gene expression) 38 samples Submitted 2024/08/21 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 38 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
38 samples: 6 conditions, mostly with about 9 replicates eachGroups 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
Gut microbiota dysbiosis orchestrates vitiligo-related oxidative stress through the metabolite hippuric acidMicrobiome · 2025
Summary (written by the submitters)
Vitiligo is a common autoimmune skin disorder. We constructed an induced vitiligo mouse model and performed bulk-RNA sequencing on the skin and 16S rRNA sequencing of feces from vitiligo mice and uninduced mice. Next, we performed skin bulk-RNA sequencing after treatment using ABX. Lastly, we subjected gut microbe-related metabolite hippuric acid to control mice and performed bulk-RNA sequencing on the skin to observe oxidative stress-related gene expression changes.
Published in
Gut microbiota dysbiosis orchestrates vitiligo-related oxidative stress through the metabolite hippuric acid
Ni Q, Xia L, Huang Y et al. · Microbiome 2025 · PMID 40329424 · doi:10.1186/s40168-025-02102-0
This dataset
Open GSE273242 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 GSE273242_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 PRJNA1140852 and SRA study SRP522571. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40329424) ↗
Study design
6 conditions, mostly with about 9 replicates each
Vitiligo ×9 Noinduction ×9 VitiligoABX ×6 NoinductionABX ×6 Ctrl-HA ×5 Vehicle ×3

Supports a between-group comparison across 38 samples.

How we read this: 6 replicated groups read from 38 sample titles; they account for 38 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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