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Single-cell genomics of the mouse olfactory cortex reveals contrasts with neocortex and ancestral signatures of cell type evolution

GSE239477 Mus musculus (mouse) Single-cell RNA-seq 72 samples Submitted 2025/02/01 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 72 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
72 samples: 72 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
Single-cell genomics of the mouse olfactory cortex reveals contrasts with neocortex and ancestral signatures of cell type evolutionNature neuroscience · 2025
Summary (written by the submitters)
Understanding the molecular logic of cortical cell-type diversity can illuminate cortical circuit function and evolution. Here, we performed single-nucleus transcriptome and chromatin accessibility analyses to compare neurons across three- to six-layered cortical areas of adult mice and across tetrapod species. We found that, in contrast to the six-layered neocortex, glutamatergic neurons of the three-layered mouse olfactory (piriform) cortex displayed continuous rather than discrete variation in transcriptomic profiles.
Read the full summary ↓
Subsets of piriform and neocortical glutamatergic cells with conserved transcriptomic profiles were distinguished by distinct, area-specific epigenetic states. Furthermore, we identified a prominent population of immature neurons in piriform cortex and observed that, in contrast to the neocortex, piriform cortex exhibited divergence between glutamatergic cells in lab versus wild-derived mice. Finally, we showed that piriform neurons displayed greater transcriptomic similarity to cortical neurons of turtles, lizards, and salamanders than to those of the neocortex. In summary, despite over 200 million years of co-evolution alongside the neocortex, olfactory cortex neurons retain molecular signatures of ancestral cortical identity.
Published in
Single-cell genomics of the mouse olfactory cortex reveals contrasts with neocortex and ancestral signatures of cell type evolution
Zeppilli S, Gurrola AO, Demetci P et al. · Nature neuroscience 2025 · PMID 40200010 · doi:10.1038/s41593-025-01924-3
This dataset
Open GSE239477 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 GSE239477_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 PRJNA999360 and SRA study SRP451834. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40200010) ↗
Study design
72 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 72 sample titles: 72 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

+ 32 more — browse all 72 samples with per-sample file links →

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.