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Inhibition of microglial SLC2A5 attenuates brain injury following acute ischemic stroke [RNA-Seq]

GSE289792 Mus musculus (mouse) Single-nucleus RNA-seq 12 samples Submitted 2025/11/08 Platform GPL24247
At a glance

Single-nucleus RNA-seq · mouse · 12 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). 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
12 samples: 3 × Microglia,OGD 6 hours, vs 3 × Slc2a5 KO Microglia,OGD 6 hours, vs 3 × Microglia,OGD 6 hours and recovery for 1 day, vs 3 × Slc2a5 KO Microglia,OGD 6 hours and recovery for 1 day,Groups 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 Slc2a5 in microglia plays a crucial role in the brain's injury response. In this study, we utilized single-cell RNA sequencing to examine the impact of Slc2a5 knockout on cell type-specific transcription in the brain. Additionally, we employed single-nucleus RNA sequencing to investigate the cell type-specific transcriptional changes in the brain 24 hours after transient middle cerebral artery occlusion (tMCAO) in response to ischemic stroke.
Read the full summary ↓
Furthermore, RNA sequencing was conducted to analyze the effects of oxygen-glucose deprivation (OGD) conditions on the transcriptional profiles of wild-type and Slc2a5 knockout microglia in vitro.
This dataset
Open GSE289792 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 GSE289792_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 PRJNA1224794 and SRA study SRP564390. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × Microglia,OGD 6 hours, vs 3 × Slc2a5 KO Microglia,OGD 6 hours, vs 3 × Microglia,OGD 6 hours and recovery for 1 day, vs 3 × Slc2a5 KO Microglia,OGD 6 hours and recovery for 1 day,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
Datasets on a similar topic

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