GEO series

Spatial distribution and chromatin accessibility determine the therapeutic capacity of microglial subsets during neurodegeneration [scRNAseq1_LPS_ABX]

GSE296026 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2025/04/30 Platform GPL13112

At a glance

Single-cell RNA-seq · mouse · 12 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 12 samples: 12 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: Response of spatially defined microglia states with distinct chromatin accessibility in a mouse model of Alzheimer's diseaseNature neuroscience · 2025

Summary (written by the submitters)

Microglial spatial heterogeneity remains a crucial yet poorly studied question in light of potential cell-directed therapies for Alzheimer's disease (AD). Little is known about the dynamics of spatially distinct microglia states, which are either adjacent or non-associated with the plaque site, and their selective contributions to neurodegeneration in vivo.

Read the full summary ↓

So far, research has essentially focused on pathology-associated microglia. Here, we combined novel multicolour fluorescence fate mapping, single-cell transcriptional analysis, epigenetic profiling, advanced immunohistochemistry and computational modelling to comprehensively characterize the relation of plaque-associated and non-plaque-associated microglia during neurodegeneration in female mice. This approach enabled us to identify and characterize non-plaque-associated microglia as a unique and highly dynamic microglial state in a mouse model of AD. Non-plaque-associated microglia modulate network expansion, quickly adapt to environmental cues and their transition to plaque-associated microglia can be specifically modulated during disease, contrary to their reputation as a passive bystander subpopulation. This description of the dynamics of spatially segregated microglial states and their distinct molecular features may therefore open promising new avenues for state-specific therapeutic interventions during neurodegeneration.

Published in

Response of spatially defined microglia states with distinct chromatin accessibility in a mouse model of Alzheimer's disease

Ardura-Fabregat A, Bosch LFP, Wogram E et al. · Nature neuroscience 2025 · PMID 40659845 · doi:10.1038/s41593-025-02006-0

This dataset

Open GSE296026 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 GSE296026_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 PRJNA1257334 and SRA study SRP582402. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40659845) ↗

Study design

12 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 12 sample titles: 12 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

GSM8963593 scRNAseq, Microglia, early stage AD, untreated, CD11c negative
GSM8963594 scRNAseq, Microglia, early stage AD, untreated, CD11c positive
GSM8963595 scRNAseq, Microglia, early stage AD, LPS treated_ CD11c negative
GSM8963596 scRNAseq, Microglia_early stage AD, LPS treated, CD11c positive
GSM8963597 scRNAseq, Microglia, early stage AD, Abx treated_ CD11c negative
GSM8963598 scRNAseq, Microglia, early stage AD, Abx treated_ CD11c positive
GSM8963599 scRNAseq, Microglia, late stage AD, untreated, CD11c negative
GSM8963600 scRNAseq, Microglia, late stage AD, untreated, CD11c positive
GSM8963601 scRNAseq, Microglia, late stage AD, Abx treated, CD11c negative
GSM8963602 scRNAseq, Microglia, late stage AD, Abx treated, CD11c positive
GSM8963603 scRNAseq, Microglia, late stage AD, LPS treated, CD11c negative
GSM8963604 scRNAseq, Microglia, late stage AD, LPS treated, CD11c positive

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GSE273797 Pathophysiology of microglial-driven neurodegeneration in Histiocytosis [Proj_11769] 20 samples shares neurodegeneration, microglial
GSE332798 Transcriptomic profiling of morphine and LPS exposure across mouse brain regions 208 samples shares lps
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