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RNA-seq of retinal microglia and non-microglial retina cells in WT (Bmal1f/f) and microglial Bmal1-KO (Bmal1-mg/-mg) mice

GSE282175 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/07/28 Platform GPL34328
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 × Microglia, Bmal1-mg/-mg, vs 5 × Retina, Bmal1-mg/-mg, vs 4 × Microglia, Bmal1f/f, vs 4 × Retina, Bmal1f/f,Groups 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
Microglial Bmal1 Contributes to Diurnal Physiology and Retinal HomeostasisGlia · 2025
Summary (written by the submitters)
We discovered that Bmal1 knockdown in retinal microglia alters their diurnal clock gene expression, inflammatory gene expression, and morphology. Furthermore, we found that this disruption of diurnal physiology in microglia results in reduced scotopic visual function, retinal neurodegeneration, and abnormal wheel running behavior in mice, suggesting that maintenance of the microglial clock contributes to retinal homeostasis.
Read the full summary ↓
Subsequently, we investigated transcriptional alterations in retinal microglia and non-microglial cells in the retina to uncover gene expression patterns that may explain these clock-dependent phenotypes and potentially identify homeostatic neuro-glial signaling mechanisms dependent on microglial clock biology.
Published in
Microglial Bmal1 Contributes to Diurnal Physiology and Retinal Homeostasis
Pfeifer CW, Santeford A, Apte RS · Glia 2025 · PMID 40642906 · doi:10.1002/glia.70061
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 GSE282175_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 PRJNA1187531 and SRA study SRP545898. Searching any of these in the dataset finder brings you back here.

Study design
5 × Microglia, Bmal1-mg/-mg, vs 5 × Retina, Bmal1-mg/-mg, vs 4 × Microglia, Bmal1f/f, vs 4 × Retina, Bmal1f/f,

Supports a between-group comparison across 18 samples.

How we read this: 4 replicated groups read from 18 sample titles; they account for 18 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
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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.