GEO series

Spatial and single-cell transcriptomics reveal the reorganization of cerebellar microglia with aging

GSE290806 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2025/12/06 Platform GPL24247

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: Spatial and single-cell transcriptomics reveal the reorganization of cerebellar microglia with agingCell reports · 2025

Summary (written by the submitters)

Aging induces region-specific functional decline across the brain. The cerebellum, critical for motor coordination and cognitive function, undergoes significant structural and functional changes with age. The molecular mechanisms driving cerebellar aging—particularly the role of cerebellar glia, including microglia—remain poorly understood.

Read the full summary ↓

Here, we used single-nuclei RNA sequencing (snRNA-seq), microglial bulk RNA-seq, and multiplexed error-robust fluorescence in situ hybridization (MERFISH) to characterize transcriptional changes associated with cellular aging in the mouse cerebellum. We discovered that microglia exhibited the most pronounced age-related changes of all cell types and that their transcriptional signatures pointed to enhanced neuroprotective immune activation and reduced lipid-droplet accumulation compared to hippocampal microglia. Furthermore, cerebellar microglia in aged mice, compared to young mice, were found in closer proximity to granule cells. This relationship was characterized using the newly defined neuron-associated microglia score, which captures proximity-dependent transcriptional changes and suggests a novel microglial responsiveness. These findings underscore the unique adaptations of the cerebellum during aging and its potential resilience to Alzheimer’s disease (AD) related pathology, providing crucial insight into region-specific mechanisms that may shape disease susceptibility.

Published in

Spatial and single-cell transcriptomics reveal the reorganization of cerebellar microglia with aging

Tsai AP, Henze DE, Ramirez Lopez E et al. · Cell reports 2025 · PMID 41307999 · doi:10.1016/j.celrep.2025.116624

This dataset

Open GSE290806 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 GSE290806_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 PRJNA1230151 and SRA study SRP567111. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41307999) ↗

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

GSM8822326 CB_12FN
GSM8822327 CB_12G
GSM8822328 CB_12MN
GSM8822329 CB_18FN
GSM8822330 CB_18G
GSM8822331 CB_18MN
GSM8822332 CB_24FN
GSM8822333 CB_24G
GSM8822334 CB_24MN
GSM8822335 CB_3FN
GSM8822336 CB_3G
GSM8822337 CB_3MN

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