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Wnt Regulates Cellular Differentiation and Retinoid Metabolism Genes in the Mouse Stomach

GSE314919 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/12/29 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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)
Background & Aims: While recognized as a key regulator of gastrointestinal tissues, Wnt function in the stomach is poorly understood. This study aimed to define Wnt functions and identify Wnt-regulated genes in the stomach. Methods: Wnt signaling was localized using reporter mice. Proliferation was studied after canonical Wnt inhibition in vivo using Sox2-CreERT2; Ctnnb1fl/fl mice and in vitro using gastric organoid cultures.
Read the full summary ↓
Wnt-regulated genes and potential effector pathways were identified by bulk RNAseq analysis of corpus and antral organoids 24 hours after Wnt inhibition. Retinoid metabolic components were localized in control and Wnt-inhibited mouse stomach by immunostaining. Results: Wnt signaling cells mapped to the base and proliferative region in both corpus and antrum. Wnt inhibition in vivo reduced proliferation and led to gastric stem cell loss. Cell signature analysis of RNAseq data revealed that gastric organoids adopt a surface cell transcriptional profile following Wnt inhibition instead of a basal cell profile. Furthermore, retinoid metabolism terms were differentially expressed after Wnt inhibition, with both corpus and antrum displaying decreased expression of retinoic acid target genes. Immunostaining mouse stomach showed differential localization of retinoid metabolic components in luminal pit cells (ALDH3A1), and basal chief/deep mucous cells (STRA6), with expression changes after b-catenin deletion consistent with the organoid analysis. Conclusion: Wnt signaling is required for gastric stem cell survival and promotes differentiation of cell types at the gland base. Retinoid metabolism is a candidate Wnt-regulated pathway, with cell-specific expression of key components. Localization of the retinol transporter STRA6 to high-Wnt cells at the gland base suggests that they are retinoic acid signaling cells.
This dataset
Open GSE314919 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 GSE314919_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 PRJNA1393106 and SRA study SRP657745. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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 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.