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Transcriptomic Cell Type Specificity of Local Cortical Circuits

GSE261436 Mus musculus (mouse) Single-nucleus RNA-seq 21 samples Submitted 2024/09/19 Platform GPL24247
At a glance

Single-nucleus RNA-seq · mouse · 21 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
21 samples: 5 conditions, mostly with about 4 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
Transcriptomic cell-type specificity of local cortical circuitsNeuron · 2024
Summary (written by the submitters)
The complex functions of the neocortex rely on networks of interconnected excitatory and inhibitory interneurons, each of which are composed of multiple neuron types. Prior studies have established rules of local connectivity between major subclasses of inhibitory and excitatory cortical neurons, but the advent of single-cell transcriptomic technologies has revealed a remarkable diversity in transcriptomic neuronal subtypes.
Read the full summary ↓
Is there specificity of synaptic connections between cortical neurons classified at the level of transcriptomic subtypes, as might be expected if the different types mediate different functions? Here we present a novel method that links transcriptomic cell type to anatomical connectivity, “Single Transcriptome Assisted Rabies Tracing” (START). START combines monosynaptic rabies tracing and single-nuclei RNA sequencing (snRNA-seq) to identify the transcriptomic cell types providing monosynaptic inputs to defined populations of neurons. We employed START in conjunction with Cre driver mouse lines to transcriptomically characterize 35,717 neurons providing monosynaptic input to 5 different layer-specific excitatory cortical neuron populations in mouse V1. At the subclass level, we observed results consistent with findings from prior studies that resolve neuronal subclasses using antibody staining, Cre-expressing mouse lines, or morphological characterization. With improved neuronal subtype granularity achieved with START, we demonstrate transcriptomic subtype specificity of inhibitory inputs to various subclasses of excitatory neurons. These results establish local connectivity rules at the resolution of transcriptomic inhibitory cell types.
Published in
Transcriptomic cell-type specificity of local cortical circuits
Patiño M, Rossa MA, Lagos WN et al. · Neuron 2024 · PMID 39353431 · doi:10.1016/j.neuron.2024.09.003
This dataset
Open GSE261436 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 GSE261436_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 PRJNA1086941 and SRA study SRP494850. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39353431) ↗
Study design
5 conditions, mostly with about 4 replicates each
STNP ×5 STS ×4 STSC ×4 STT ×4 STNT ×4

Supports a between-group comparison across 21 samples.

How we read this: 5 replicated groups read from 21 sample titles; they account for 21 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
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