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A spatial code governs olfactory receptor choice and aligns sensory maps in the nose and brain

GSE297068 synthetic construct; Mus musculus RNA-seq (gene expression) 291 samples Submitted 2026/04/21 Platform GPL31217Platform GPL24247Platform GPL28330Platform GPL34290
At a glance

RNA-seq (gene expression) · synthetic construct; Mus musculus · 291 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
synthetic construct; Mus musculus
Samples
291 samples: 93 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
A spatial code governs olfactory receptor choice and aligns sensory maps in the nose and brainCell · 2026
Summary (written by the submitters)
Although topographical maps organize many peripheral sensory systems, mouse olfactory sensory neurons (OSNs) are thought to randomly choose which one of ~1,100 possible olfactory receptors (ORs) to express, with spatial organization in the olfactory epithelium limited to a handful of broad anatomical zones that modestly restrict OR choice.
Read the full summary ↓
Here we reveal that each OR is instead expressed at a unique mean dorsoventral position, thereby instantiating a stereotyped receptor map in the olfactory epithelium. OSN dorsoventral identities are encoded by a coherent gene expression program, which includes key transcription factors and axon guidance molecules; use of this program reflects a dorsoventral gradient in retinoic acid signaling, translates each physical location into a spatially appropriate distribution of potential OR choices, and aligns receptor maps in the nose and brain. Spatial order in the olfactory system, therefore, arises from a continuously varying transcriptional code that precisely organizes the many discrete channels responsible for smell.
Published in
A spatial code governs olfactory receptor choice and aligns sensory maps in the nose and brain
Brann DH, Tsukahara T, Tau C et al. · Cell 2026 · PMID 42054991 · doi:10.1016/j.cell.2026.03.051
This dataset
Open GSE297068 in finder → Find more 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 GSE297068_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 PRJNA1260542 and SRA study SRP583999. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42054991) ↗
Study design
93 conditions, mostly in duplicate
propanal ×10 ethyl_acetate ×8 hexyl_acetate ×8 octanal ×8 acetic_acid ×6 ethyl_butyrate ×6 ethyl_tiglate ×6 CAST_DPG30m ×4 +125 more

Supports a between-group comparison across 251 samples.

How we read this: 93 replicated groups read from 291 sample titles; they account for 251 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

+ 251 more — browse all 291 samples with per-sample file links →

Datasets on a similar topic

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