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Transcriptomic Signatures Reveal Overlapping Shared and DistinctYet State-Specific Preoptic Neuronal Ensembles Activated by Anesthesia and Sleep

GSE337822 Mus musculus (mouse) Single-nucleus RNA-seq 20 samples Submitted 2026/07/07 Platform GPL24247
At a glance

Single-nucleus RNA-seq · mouse · 20 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
20 samples: 5 × OxyControl; female F vs 5 × OxyControl; male M vs 5 × isoflurane treatment; female F vs 5 × isoflurane treatment; male MGroups 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)
General anesthesia and non-rapid-eye-movement (NREM) sleep share overlapping neuronal circuitry within the preoptic area (POA), yet they are fundamentally distinct states. We performed single nucleus RNA sequencing (snRNA-seq) on the POA from adult C57BL/6J mice after 30-minutes of breathing either 1.2% isoflurane in oxygen or an oxygen control.
Read the full summary ↓
Cell clusters were identified by projecting to the existing cellular taxonomy established in our previously published POA snRNA-seq dataset of recovery sleep (GEO: GSE243489) and transcriptional changes in rapid primary response genes (rPRGs) was used to define isoflurane-activated or isoflurane-inhibited clusters. Finally, multiplex fluorescence in situ hybridization was performed to independently corroborate the snRNA-seq results.
This dataset
Open GSE337822 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 GSE337822_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 PRJNA1491233 and SRA study SRP715920. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 × OxyControl; female F vs 5 × OxyControl; male M vs 5 × isoflurane treatment; female F vs 5 × isoflurane treatment; male M

Supports a between-group comparison across 20 samples.

How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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.