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Spatially-patterned and functional kidney assembloids recapitulate progenitor self-assembly and enable high-fidelity in vivo disease modeling

GSE264516 Mus musculus (mouse) RNA-seq (gene expression) 34 samples Submitted 2025/08/13 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 34 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
34 samples: 17 conditions, mostly in duplicateGroups 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
Spatially patterned kidney assembloids recapitulate progenitor self-assembly and enable high-fidelity in vivo disease modelingCell stem cell · 2025
Summary (written by the submitters)
The paired kidneys are the central organs of homeostasis for our body systems, the sophisticated structure and complex cells composition underpins kidneys’ functions. Here we report the generation of mouse kidney progenitor assembloid (KPA) with expandable nephron progenitor cells (NPC) and ureteric bud (UB). Unexpectedly, versatile renal interstitial cells can be induced in kidney progenitor assembloids.
Read the full summary ↓
Mechanistically, some NPC can be transdifferentiated into interstitial progenitor cells (IPCs) in KPA context, then induced IPCs differentiate into various renal interstitial cells. These kidney progenitors-based KPA highly resembled postnatal mouse kidneys with well pattern and showed essential renal physiological functions.
Published in
Spatially patterned kidney assembloids recapitulate progenitor self-assembly and enable high-fidelity in vivo disease modeling
Huang B, Medina P, He J et al. · Cell stem cell 2025 · PMID 40967224 · doi:10.1016/j.stem.2025.08.013
This dataset
Open GSE264516 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 GSE264516_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 PRJNA1102884 and SRA study SRP503166. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40967224) ↗
Study design
17 conditions, mostly in duplicate
E12.5 mKidney, ×2 E15.5 mKidney, ×2 P0 mKidney, ×2 P9 mKidney, ×2 P45 mKidney, ×2 D7 10% FBS explant, ×2 D17 Stage-based media-v0 explant, ×2 D3 Stage-based media-v1 explant, ×2 +9 more

Supports a between-group comparison across 34 samples.

How we read this: 17 replicated groups read from 34 sample titles; they account for 34 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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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.