GEO series

Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibility (Bulk-RNAseq)

GSE311539 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2026/03/26 Platform GPL34290

At a glance

RNA-seq (gene expression) · mouse · 10 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: 10 samples: 5 × CT vs 5 × WYGroups 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: Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibilityCell · 2026

Summary (written by the submitters)

The gut epithelium exhibits regional specialization critical for its function and susceptibility to disease, as gut diseases localize to specific regions of the organ. However, how regionalization is established and its influence on disease susceptibility remain poorly understood. Here, we investigate the role of the gut microbiome—which comprises all microorganisms residing in the gut lumen and is itself regionalized—in regulating regionalization of the colon.

Read the full summary ↓

We demonstrate that the regional identity of colonocytes is disrupted in mice lacking a microbiome. Mechanistically, we show that the proximal colonic microbiome produces high levels of nicotinic acid, which induces Pparα expression to establish proximal colonocyte identity. Furthermore, we find that microbiome-driven proximal identity confers protection against tissue injury in the mouse. Finally, we show that colon regionalization and the loss of proximal identity during disease are also present in human.

Published in

Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibility

Rispal J, Garcia JR, Palikuqi B et al. · Cell 2026 · PMID 41812662 · doi:10.1016/j.cell.2026.02.007

This dataset

Open GSE311539 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 GSE311539_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 PRJNA1369825 and SRA study SRP649099. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41812662) ↗

Study design

5 × CT vs 5 × WY

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 10 sample titles; they account for 10 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

GSM9326713 CT1 CT
GSM9326714 CT2 CT
GSM9326715 CT3 CT
GSM9326716 CT4 CT
GSM9326717 CT5 CT
GSM9326718 WY6 WY
GSM9326719 WY7 WY
GSM9326720 WY8 WY
GSM9326721 WY9 WY
GSM9326722 WY10 WY

Datasets on a similar topic

GSE285762 Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibility (Bulk-RNAseq) 18 samples shares microbiome-produced, susceptibility, bulk-rnaseq, nicotinic, controls, regional, identity, injury
GSE285770 Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibility (scRNAseq) 13 samples shares microbiome-produced, susceptibility, nicotinic, controls, regional, identity, injury
GSE311538 Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibility (Colon and Cecum scRNAseq) 8 samples shares microbiome-produced, susceptibility, nicotinic, controls, regional, identity, injury
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GSE249946 Reduced cardiac antioxidant defenses mediate increased susceptibility to workload-induced myocardial injury in males with genetic cardiomyopathy. 17 samples shares susceptibility, injury
GSE319377 Preterm Birth Increases Susceptibility to Hyperglycemia-Induced Kidney Injury with Sex-Specific Differences in Structural and Molecular Responses 14 samples shares susceptibility, injury
GSE306861 ALDH2 inhibition reprograms tubular epithelial cell metabolism and promotes renal injury susceptibility 8 samples shares susceptibility, injury
GSE330309 Impact of Sex Chromosomes and Gonad Type in Stress Susceptibility in Corticostriatal Brain Regions 96 samples shares susceptibility

Search all mouse RNA-seq datasets in GEO →

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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.