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Neuronal conversion of pre-labeled astrocyte using adeno-asociated viruses in vivo

GSE288733 Mus musculus (mouse) Single-cell RNA-seq 18 samples Submitted 2025/11/09 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 18 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. 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
18 samples: 6 conditions, mostly in triplicateGroups 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
MicroRNA-mediated neuronal detargeting alters astrocyte cell fate conversion trajectories in vivoCommunications biology · 2025
Summary (written by the submitters)
Neuronal reprogramming using adeno-associated viruses (AAVs) carrying a GFAP mini-promoter to drive neurogenic transcription factor expression in astrocytes in vivo were refuted due to off-target neuronal expression. Here, we show successful neuronal conversion of pre-labeled astrocytes using AAV-GFAP to express phospho-deficient Ascl1SA6, and demonstrate that miR124 target sites reduce off-target neuronal expression.
Read the full summary ↓
Finally, single cell transcriptomic and pseudotime trajectory analyses confirmed Ascl1SA6-driven astrocyte-to-neuron conversion, and more limited oligodendrocyte conversion events
Published in
MicroRNA-mediated neuronal detargeting alters astrocyte cell fate conversion trajectories in vivo
Ghazale H, Parga Pazos M, Jung S et al. · Communications biology 2025 · PMID 41350397 · doi:10.1038/s42003-025-09169-3
This dataset
Open GSE288733 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 GSE288733_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 PRJNA1219162 and SRA study SRP561523. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41350397) ↗
Study design
6 conditions, mostly in triplicate
GFAPsh-SA6-iCre-miR124T, 7 days post injectio… ×3 GFAPsh-iCre-miR124T, 7 days post injection n ×3 GFAPsh-SA6-iCre, 50 days post injection n ×3 GFAPsh-iCre-miR124T, 50 days post injection n ×3 GFAPsh-SA6-iCre-miR124T, 50 days post injecti… ×3 GFAPsh-SA6-iCre, 7 days post injection n ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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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.