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Single cell transcriptomic changes in the THY-Tau22 mouse model of Alzheimer's disease at 17 months of age

GSE285506 Mus musculus (mouse) Single-cell RNA-seq 16 samples Submitted 2025/01/06 Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 16 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
16 samples: 16 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
Temporal transcriptomic changes in the THY-Tau22 mouse model of tauopathy display cell type- and sex-specific differencesActa neuropathologica communications · 2025
Summary (written by the submitters)
Alzheimer's disease (AD) displays sex-specific differences in prevalence and progression, but the underlying molecular mechanisms remain unclear. To investigate sex-dependent molecular changes associated with tau pathology at a late disease stage, we performed single-cell RNA sequencing on cortical tissue from 17-month-old THY-Tau22 mice and wildtype littermates of both sexes.
Read the full summary ↓
The analysis revealed extensive sex-specific and sex-dimorphic transcriptomic alterations across multiple cell types, with particularly pronounced changes in microglia and oligodendrocytes. Key pathways affected in a sex-dependent manner included RNA processing and splicing, stress response pathways, neurotransmitter signaling, and protein degradation pathways. Network analysis identified the genes Clu, Mbp, Fos and Junb as potential regulatory hubs. Multiple genes with established implications in AD, including the long non-coding RNA gene MALAT1, showed concordant sex-specific changes when compared with both earlier time points and human AD data. This study provides a comprehensive characterization of sex-dependent transcriptomic changes in late-stage tau pathology, revealing new insights into the interplay between AD-like pathology and biological sex.
Published in
Temporal transcriptomic changes in the THY-Tau22 mouse model of tauopathy display cell type- and sex-specific differences
Ali M, Garcia P, Lunkes LP et al. · Acta neuropathologica communications 2025 · PMID 40336141 · doi:10.1186/s40478-025-02013-z
This dataset
Open GSE285506 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 GSE285506_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 PRJNA1204102 and SRA study SRP554291. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40336141) ↗
Study design
16 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 16 sample titles: 16 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
Datasets on a similar topic

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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.