← BioTransfer GEO Dataset Finder
GEO series

IL-22 induces Paneth cell metaplasia in the colonic epithelium of ulcerative colitis, promoting wound healing via REG3A

GSE311760 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/12/02 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
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.
Summary (written by the submitters)
Paneth cell metaplasia (PCM) is a phenomenon in which Paneth cells, typically found in the small intestine, appear in the colonic epithelium of patients with ulcerative colitis (UC). Our study demonstrates that the PCM occurrence correlates with disease duration and active inflammation. Furthermore, we reveal that the inflammation-induced cytokine IL-22 suppresses Notch signaling, thereby promoting PCM formation in the colonic epithelium while simultaneously inducing REG3A expression in metaplastic niches.
Read the full summary ↓
In vitro, we show that Reg3a directly enhances cell proliferation and promotes wound healing using mouse colonic organoids. In vivo, Reg3aΔIEC mice in both acute and chronic DSS-induced colitis models exhibit delayed wound healing. Additionally, studies conducted with patient-derived human colonic organoids revealed that REG3A administration stimulates cell proliferation and accelerates wound healing. These findings underscore a novel protective role of PCM-mediated REG3A in the colonic epithelium of patients with UC.
This dataset
Open GSE311760 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 GSE311760_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 PRJNA1370882 and SRA study SRP649691. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
SY8_con ×3 SY8_IL22 ×3 SF11_con ×3 SF11_IL22 ×3 SF13_con ×3 SF13_IL22 ×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
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.