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Heterogenous microglial reactivity contrasts with stable vascular transcriptional programs in mouse models of Alzheimer’s, CADASIL, and Traumatic Brain Injury (Main dataset)

GSE300113 Mus musculus (mouse) Single-cell RNA-seq 59 samples Submitted 2026/04/30 Platform GPL30172
At a glance

Single-cell RNA-seq · mouse · 59 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. 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
59 samples: 20 conditions, mostly in triplicateGroups 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)
The extent to which the cerebrovasculature is affected in various brain disorders is still not well understood. To address this, we established a transcriptomic repository of major vascular cell types and microglia to compare the transcriptomic response in mouse models of three human brain disorders linked to neuroinflammation and associated vascular reactivity: Alzheimer’s disease (AD), traumatic brain injury (TBI), and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL).
Read the full summary ↓
Single-cell analysis of >250,000 cells at different disease stages led to identification of two previously unknown vascular cell subtypes, expanded the endothelial zonation spectrum and allowed for a detailed analysis of the molecular responses in the vascular cells and microglia. Surprisingly, all vascular cell types remained transcriptomically normal across the three conditions, while microglia exhibited significant, disease-specific transcriptional changes. Notably, microglial responses converged between late-stage TBI and AD, offering new insights into the predisposition for neurodegeneration following TBI.
This dataset
Open GSE300113 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 GSE300113_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 PRJNA1279045 and SRA study SRP592872. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 conditions, mostly in triplicate
brain vasc_WT_12 months ×4 brain vasc_NLGF_3 months ×3 brain vasc_WT_3 months ×3 brain vasc_NLGF_12 months ×3 brain vasc_NLGF_6 months ×3 brain vasc_WT_6 months ×3 brain vasc_Tg350_9 months ×3 brain vasc_Tg350_3 months ×3 +12 more

Supports a between-group comparison across 59 samples.

How we read this: 20 replicated groups read from 59 sample titles; they account for 59 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

+ 19 more — browse all 59 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.