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Connectome-seq: High-throughput Mapping of Neuronal Connectivity at Single-Synapse Resolution via Barcode Sequencing

GSE285978 Mus musculus (mouse) Single-cell RNA-seq 46 samples Submitted 2025/12/31 Platform GPL34328
At a glance

Single-cell RNA-seq · mouse · 46 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
46 samples: 6 conditions, mostly with about 7 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
Connectome-seq: High-throughput Mapping of Neuronal Connectivity at Single-Synapse Resolution via Barcode SequencingbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Understanding neuronal connectivity at single-cell resolution remains a fundamental challenge in neuroscience, with current methods constrained by an inherent trade-off between throughput and synaptic precision. Here we present Connectome-seq, a high-throughput method that combines engineered synaptic proteins, RNA barcoding, and single-compartment sequencing to map neuronal connectivity at single-synapse resolution.
Read the full summary ↓
We validate this approach in the mouse pontocerebellar circuit, successfully identifying thousands of connections including the predominant excitatory projections from pontine neurons to cerebellar granule cells, while also revealing potentially novel synaptic partnerships. By enabling systematic mapping of neuronal connectivity across brain regions with single-cell precision, Connectome-seq provides a scalable platform for comprehensive circuit analysis across different experimental conditions and biological states. This advance in connectivity mapping methodology opens new possibilities for understanding circuit organization in complex mammalian brains.
Published in
Connectome-seq: High-throughput Mapping of Neuronal Connectivity at Single-Synapse Resolution via Barcode Sequencing
Chen D, Isakova A, Wan ZJ et al. · bioRxiv : the preprint server for biology 2025 · PMID 41030982 · doi:10.1101/2025.02.13.638129
This dataset
Open GSE285978 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 GSE285978_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 PRJNA1207100 and SRA study SRP555620. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41030982) ↗
Study design
6 conditions, mostly with about 7 replicates each
Cerebellum synaptosome PreNB, ×9 Cerebellum synaptosome PostNB, ×9 Cerebellum nucleus mRNA, ×7 Cerebellum nucleus PostNB, ×7 Pons nucleus mRNA, ×7 Pons nucleus PreNB, ×7

Supports a between-group comparison across 46 samples.

How we read this: 6 replicated groups read from 46 sample titles; they account for 46 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

+ 6 more — browse all 46 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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