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Molecular, anatomical, and functional organization of lung interoceptors

GSE186180 Mus musculus (mouse) RNA-seq (gene expression) 136 samples Submitted 2024/10/15 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 136 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
136 samples
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)
Interoceptors are the sensory neurons that monitor internal organs and states, essential for physiological homeostasis and generating interoception.Here, we describe a comprehensive, high-quality molecular atlas of interoceptors of the mouse lung, identifing 10 molecular subtypes, which differ in developmental origin, myelination, receptive fields, and cell contacts in the organ.
Read the full summary ↓
Each subtype expresses a unique but overlapping combination of sensory receptors that detect diverse physiological and pathological stimuli, and each can signal to distinct sets of lung cells including immune cells, forming an intricate local neuroimmune interaction network. Functional interrogation of two mechanosensory subtypes reveals exquisitely-specific homeostatic roles in breathing, one regulating inspiratory time and the other inspiratory flow. These suggest that lung interoceptors encode diverse and dynamic sensory information rivaling that of canonical exteroceptors, and this information is used to drive myriad local cellular interactions and enable precision control of breathing, while providing only vague perceptions of oragn states.
This dataset
Open GSE186180 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 GSE186180_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA772785 and SRA study SRP342183. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
A cohort of 136 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run N5 … N173 and carry no group information.

Samples in this study

+ 96 more — browse all 136 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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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.