GEO series

Single-cell RNA sequencing of small intestinal organoid self-organization [scRNA-Seq]

GSE329635 Mus musculus (mouse) Single-cell RNA-seq 10 samples Submitted 2026/06/30 Platform GPL19057

At a glance

Single-cell RNA-seq · mouse · 10 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 10 samples: 9 distinct titles, 1 of them repeatedGroups 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)

The mouse small intestinal epithelium is composed of diverse cell types that interact to regulate signaling, cell patterning, and tissue form and function. The self-organization of small intestinal organoids, starting from a single cell (0 h) to a budded crypt-villus structure (96–108 h), recapitulates aspects of such multicellular intestinal morphogenesis.

Read the full summary ↓

To characterize the cell states and lineage trajectories underlying organoid self-organization, we performed single-cell RNA sequencing of intestinal organoids in a high-resolution time course. Organoids derived from mouse duodenal epithelium were dissociated to single cells and seeded to initiate organoid formation, followed by sampling for sequencing at 12-hour intervals from 24 to 108 h. This dataset captures dynamic changes in cell state composition during organoid development. Early time points (24–36 h) reveal a population of reprogramming cells characterized by loss of mature lineage markers, followed by the emergence and differentiation of major intestinal lineages, including absorptive, secretory, and stem cell populations. A secretory progenitor population emerges by 48 h, which gives rise to both exocrine (Paneth and goblet cells) and endocrine lineages (enteroendocrine progenitors and differentiated enteroendocrine cell types). Absorptive and stem cell lineages continue their differentiation and maturation following their emergence at 48–72 h. Overall, this dataset provides a comprehensive resource for studying cell state transitions and lineage specification during intestinal organoid self-organization and recapitulates key features of epithelial differentiation observed in vivo.

This dataset

Open GSE329635 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 GSE329635_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: 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 PRJNA1460361 and SRA study SRP696316. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

9 distinct titles, 1 of them repeated

mSIorg_36h ×2

How we read this: Read from 10 sample titles: 9 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

GSM9707907 mSIorg_0h
GSM9707908 mSIorg_24h
GSM9707909 mSIorg_36h_1
GSM9707910 mSIorg_36h_2
GSM9707911 mSIorg_48h
GSM9707912 mSIorg_60h
GSM9707913 mSIorg_72h
GSM9707914 mSIorg_84h
GSM9707915 mSIorg_96h
GSM9707916 mSIorg_108h

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