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A dynamic gene regulatory code drives synaptic development of hippocampal granule cells [SS2]

GSE292261 Mus musculus (mouse) Single-cell RNA-seq 576 samples Submitted 2025/09/21 Platform GPL30172Platform GPL19057
At a glance

Single-cell RNA-seq · mouse · 576 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
576 samples: 34 conditions, mostly with about 12 replicates eachGroups 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
A dynamic gene regulatory code drives synaptic development of hippocampal granule cellsScience advances · 2025
Summary (written by the submitters)
Connecting neurons into functional circuits requires the formation, maturation, and plasticity of synapses. While advances have been made in identifying individual genes regulating synapse development, the molecular programs orchestrating their action during circuit integration of neurons remain poorly understood. Here, we have employed a single-cell RNA sequencing (scRNAseq) method (Smart-seq2) to study the development of hippocampal GCs.
Read the full summary ↓
GCs represent the first relay in the hippocampal tri-synaptic loop and play an essential role in processing spatial representations and memory acquisition. This study provides a high temporal resolution analysis of the transcriptome of GCs during early postnatal development (P5, P7, P10, P15, and P28). Together, these findings highlight the networks of key TFs and target genes orchestrating GC synapse development.
Published in
A dynamic gene regulatory code drives synaptic development of hippocampal granule cells
Lorente-Echeverría B, Daaboul D, Vandensteen J et al. · Science advances 2025 · PMID 41124261 · doi:10.1126/sciadv.adx5140
This dataset
Open GSE292261 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 GSE292261_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 PRJNA1237782 and SRA study SRP571885. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41124261) ↗
Study design
34 conditions, mostly with about 12 replicates each
GCs, Rbp4-Cre, SS2, DG_P5_A ×12 GCs, Rbp4-Cre, SS2, DG_P5_B ×12 GCs, Rbp4-Cre, SS2, DG_P5_C ×12 GCs, Rbp4-Cre, SS2, DG_P5_D ×12 GCs, Rbp4-Cre, SS2, DG_P5_E ×12 GCs, Rbp4-Cre, SS2, DG_P5_F ×12 GCs, Rbp4-Cre, SS2, DG_P5_G ×12 GCs, Rbp4-Cre, SS2, DG_P5_H ×12 +26 more

Supports a between-group comparison across 400 samples.

How we read this: 34 replicated groups read from the first 400 of 576 sample titles; they account for 400 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

+ 536 more — browse all 576 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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