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Ontogeny of the spinal cord dorsal horn [scRNA-seq]

GSE291459 Mus musculus (mouse) Single-cell RNA-seq 29 samples Submitted 2025/08/22 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 29 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
29 samples: 29 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.
Paper
Ontogeny of the spinal cord dorsal hornScience (New York, N.Y.) · 2026
Summary (written by the submitters)
An exquisite example of form serving function is the dorsal horn of the spinal cord, the gateway to the central nervous system for sensory information from the body. Each sensory input to the dorsal horn targets a specific address within its laminated arrangement of diverse neuronal populations. However, it is not known how this organization emerges during development from an apparently homogenous pool of neural progenitors.
Read the full summary ↓
Here, we found that both the excitatory and inhibitory cell families of the mouse dorsal horn were born in successive waves as temporal cohorts. The excitatory families then settled into a chronotopic map that transformed their birth order into the dorsal laminae. Diversification of families into refined neuron types was mediated by a dorsal-ventral progenitor gradient of Zic transcription factors. This work uncovered fundamental temporal and spatial factors that establish the cell types and structure of the spinal cord dorsal horn.
Published in
Ontogeny of the spinal cord dorsal horn
Roome RB, Yadav A, Flores L et al. · Science (New York, N.Y.) 2026 · PMID 41505538 · doi:10.1126/science.adx5781
This dataset
Open GSE291459 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 GSE291459_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 PRJNA1233801 and SRA study SRP568984. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41505538) ↗
Study design
29 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 29 sample titles: 29 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

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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.