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Circadian rhythms in microglia mediate early life synaptic development in a sex-specific manner.

GSE308220 Mus musculus (mouse) RNA-seq (gene expression) 75 samples Submitted 2026/07/22 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 75 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
75 samples: 75 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.
Summary (written by the submitters)
Children today experience widespread circadian disruption from nighttime screen use and irregular sleep, yet how internal clocks shape brain development is unclear. Adolescence is a critical window when synaptic connectivity is refined, in part by microglia that engulf synaptic elements. Here, in adolescent mice, we show that hippocampal microglia exhibit diurnal transcriptional rhythms, with synaptic pruning gene expression peaking during the rest phase.
Read the full summary ↓
Inducible deletion of the core clock gene Bmal1 in microglia abolishes these rhythms and alters developing hippocampal synapses in a sex-dependent manner. In males, clock disruption increases synapse engulfment, reduces dendritic spine density, and decreases synaptic connectivity; females show similar reductions in synaptic connectivity without overt postsynaptic structural changes. Microglial clock disruption also induces broad, sex-specific changes in synapse-related gene expression that overlap with neurodevelopmental disorder pathways and lead to impaired memory and sociability, indicating microglial clocks as key regulators of developmental synapse refinement.
This dataset
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.

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 GSE308220_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1329246 and SRA study SRP620805. Searching any of these in the dataset finder brings you back here.

Study design
75 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 75 sample titles: 75 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

+ 35 more — browse all 75 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.