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Lung-innervating neurons expressing TMC3 control broncho-constriction and dilation with direct impact on lung tidal volume (RNA-Seq)

GSE232496 Mus musculus (mouse) Single-cell RNA-seq 30 samples Submitted 2025/12/31 Platform GPL21103

At a glance

Single-cell RNA-seq · mouse · 30 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: 30 samples: 6 conditions, mostly with about 5 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.

Summary (written by the submitters)

Sensory neurons of the vagal ganglia (VG) innervate lungs and play a critical role in maintaining airway homeostasis. However, specific VG neurons that innervate lungs, and mechanisms by which these neurons sense and respond to airway insults, are not well understood. Here, we identify a subpopulation of lung-innervating VG neurons defined by their expression of TMC3.

Read the full summary ↓

Single cell transcriptomics illuminated several subpopulations of TMC3+ VGs afferents, revealing distinct Piezo2 and Trpv1-expressing subclusters. Furthermore, TMC3 deficiency in VG neurons leads to global and subcluster specific transcriptional changes involved in metabolic and ion channel function. Importantly, we show that broncho-constriction and dilation can be modulated through inhibition or activation of TMC3+ VG neurons with a direct impact on lung tidal volume. Together, our data show that TMC3 is a marker of specific lung-innervating neurons and may play a pivotal role in maintaining fundamental inspiratory and expiratory processes.

This dataset

Open GSE232496 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 GSE232496_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 PRJNA972451 and SRA study SRP437592. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly with about 5 replicates each

wt_Thoracic ×5 ko_Thoracic ×5 wt_Lumbar ×5 ko_Lumbar ×5 wt_Nodose ×5 ko_Nodose ×5

Supports a between-group comparison across 30 samples.

How we read this: 6 replicated groups read from 30 sample titles; they account for 30 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

GSM7346220 wt_Thoracic_rep1 wt_Thoracic
GSM7346221 wt_Thoracic_rep2 wt_Thoracic
GSM7346222 wt_Thoracic_rep3 wt_Thoracic
GSM7346223 wt_Thoracic_rep4 wt_Thoracic
GSM7346224 wt_Thoracic_rep5 wt_Thoracic
GSM7346225 ko_Thoracic_rep1 ko_Thoracic
GSM7346226 ko_Thoracic_rep2 ko_Thoracic
GSM7346227 ko_Thoracic_rep3 ko_Thoracic
GSM7346228 ko_Thoracic_rep4 ko_Thoracic
GSM7346229 ko_Thoracic_rep5 ko_Thoracic
GSM7346230 wt_Lumbar_rep1 wt_Lumbar
GSM7346231 wt_Lumbar_rep2 wt_Lumbar
GSM7346232 wt_Lumbar_rep3 wt_Lumbar
GSM7346233 wt_Lumbar_rep4 wt_Lumbar
GSM7346234 wt_Lumbar_rep5 wt_Lumbar
GSM7346235 ko_Lumbar_rep1 ko_Lumbar
GSM7346236 ko_Lumbar_rep2 ko_Lumbar
GSM7346237 ko_Lumbar_rep3 ko_Lumbar
GSM7346238 ko_Lumbar_rep4 ko_Lumbar
GSM7346239 ko_Lumbar_rep5 ko_Lumbar
GSM7346240 wt_Nodose_rep1 wt_Nodose
GSM7346241 wt_Nodose_rep2 wt_Nodose
GSM7346242 wt_Nodose_rep3 wt_Nodose
GSM7346243 wt_Nodose_rep4 wt_Nodose
GSM7346244 wt_Nodose_rep5 wt_Nodose
GSM7346245 ko_Nodose_rep1 ko_Nodose
GSM7346246 ko_Nodose_rep2 ko_Nodose
GSM7346247 ko_Nodose_rep3 ko_Nodose
GSM7346248 ko_Nodose_rep4 ko_Nodose
GSM7346249 ko_Nodose_rep5 ko_Nodose

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