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Longitudinal Machine Learning and snRNA-Seq Reveal Stroke-Specific Behavioral and Transcriptional Signatures

GSE348719 Mus musculus (mouse) Single-nucleus RNA-seq 10 samples Submitted 2026/09/28 Platform GPL34290

At a glance

Single-nucleus RNA-seq · mouse · 10 samples

What it is: Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism: Mus musculus (mouse)
Samples: 10 samples
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)

Ischemic stroke is a leading cause of death and disability worldwide, with over 690,000 new cases each year. While cortical stroke (CS) patients typically develop symptoms such as hemiparesis and speech impairments, white matter stroke (WMS) often presents with more subtle cognitive deficits. Despite comprising 30% of all strokes and being a leading cause of vascular dementia that affects 90% of the population above age 65, WMS remains poorly understood.

Read the full summary ↓

In preclinical studies, current rodent behavioral assessments lack comprehensive, unbiased methods to characterize these functional deficits. Additionally, little is known about the underlying molecular mechanisms, hampering the development of effective treatment options. To address these limitations, we employed Motion Sequencing (MoSeq), an unsupervised machine learning approach, to longitudinally assess behavioral changes in mouse models of CS and WMS. MoSeq effectively captured distinct behavioral phenotypes, revealing that CS mice exhibited primarily motor impairments that partially recovered during the chronic phase, whereas WMS mice developed progressively worsening cognitive deficits. These changes were consistent across age and sex groups, though more pronounced in aged and male mice. Single-nucleus RNA sequencing revealed corresponding molecular signatures, with CS tissue transitioning from inflammatory to homeostatic gene expression at the chronic phase, while WMS tissue showed sustained downregulation of myelination-related pathways. Gene ontology analysis further identified transcriptomic changes in synaptic signaling, myelination, and inflammation that aligned with the behavioral deficits observed in each stroke subtype. This integrated behavioral and molecular characterization provides insights for developing targeted, subtype-specific therapies for the heterogenous stroke survivor population.

This dataset

Open GSE348719 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 GSE348719_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 PRJNA1535966 and SRA study SRP740474. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 10 more — browse all 10 samples with per-sample file links →

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