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Molecular and cellular rhythms in excitatory and inhibitory neurons in the mouse prefrontal cortex

GSE287818 Mus musculus (mouse) RNA-seq (gene expression) 114 samples Submitted 2025/01/27 Platform GPL9185
At a glance

RNA-seq (gene expression) · mouse · 114 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
114 samples: 114 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
Molecular and cellular rhythms in excitatory and inhibitory neurons in the mouse prefrontal cortexCerebral cortex (New York, N.Y. : 1991) · 2025
Summary (written by the submitters)
While studies have shown that there are rhythms in gene expression in the prefrontal cortex (PFC), the contribution of different cell types and potential variation by sex has not been determined. Of particular interest are excitatory pyramidal cells and inhibitory parvalbumin (PV) interneurons, as interactions between these cell types are essential for maintaining the excitation/inhibition balance.
Read the full summary ↓
Here, we identify cell-type specific rhythms in the translatome of PV and pyramidal cells in the mouse PFC and assess rhythms in PV cell electrophysiology. We find that while core molecular clock genes are conserved and synchronized between cell types, pyramidal cells have nearly twice as many rhythmic transcripts as PV cells (35% vs. 18%). Rhythmic transcripts in pyramidal cells also show a high degree of overlap between sexes, whereas in PV cells, rhythmic transcripts are largely distinct between sexes. Additionally, we find sex-specific effects of phase on action potential properties in PV cells. This study demonstrates that rhythms in gene expression and electrophysiological properties in the PFC vary by both cell type and sex. Moreover, the biological processes associated with rhythmic transcripts may provide insight into the unique functions of rhythms in these cells, as well as their selective vulnerabilities to circadian disruption.
Published in
Molecular and cellular rhythms in excitatory and inhibitory neurons in the mouse prefrontal cortex
Burns JN, Jenkins AK, Yin R et al. · Cerebral cortex (New York, N.Y. : 1991) 2025 · PMID 40684350 · doi:10.1093/cercor/bhaf188
This dataset
Open GSE287818 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 GSE287818_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 PRJNA1214766 and SRA study SRP559422. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40684350) ↗
Study design
114 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 114 sample titles: 114 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

+ 74 more — browse all 114 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.