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Pde10a gates light responses in the SCN to regulate circadian photoentrainment

GSE287917 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/01/23 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 5 conditions, mostly with about 4 replicates eachGroups 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)
Earth's rotation around its axis provides the principal cue for synchronizing the circadian clock with environmental light. A common feature of the clock is the lack of responsiveness to light during the daytime hours. To investigate the interaction between the circadian clock and light, we analyzed the transcriptomic profiles of the suprachiasmatic nucleus (SCN) in mice across different circadian times under constant darkness (DD) and in response to light exposure.
Read the full summary ↓
We classified SCN neurons into 10 molecularly defined subtypes and described an elaborate transcriptional program both in DD and in response to light. Notably, we uncovered that the SCN exhibits significant transcriptomic responsiveness to light during daytime, the so-called behavioral “dead zone”. We further identified Pde10a, involved in cAMP signaling, as the first critical component for gating SCN responsiveness to light across the day and for maintaining robust daily oscillations under regular light-dark conditions.
This dataset
Open GSE287917 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 GSE287917_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 PRJNA1215276 and SRA study SRP559642. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly with about 4 replicates each
SCN_L_CT6 ×4 SCN_D_CT22 ×4 SCN_D_CT14 ×4 SCN_L_CT14 ×3 SCN_D_CT6 ×2 SCN_L_CT22 ×1

Supports a between-group comparison across 17 samples.

How we read this: 5 replicated groups read from 18 sample titles; they account for 17 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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