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RNA-seq analysis of pulmonary arterial smooth muscle cells (PASMCs), bronchial smooth muscle cells(BSMCs) and venous SMCs in the lung

GSE301478 Mus musculus (mouse) RNA-seq (gene expression) 9 samples Submitted 2026/04/11 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 9 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
9 samples: 3 × BSMCs vs 3 × PASMCs vs 3 × SmMCllGroups 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
Cell Type-Specific Targeting of Different Smooth Muscle Cell Populations by Intersectional GeneticsCirculation · 2026
Summary (written by the submitters)
Information about the differences among arterial, venous, and bronchial smooth muscle cells (SMCs) in the lung is particularly valuable, as these distinct SMC populations are differentially affected in pulmonary diseases such as asthma, chronic obstructive pulmonary disease (COPD), and pulmonary arterial hypertension (PAH).
Read the full summary ↓
To directly compare these SMC subtypes, we employed a combination of genetic tools and fluorescence-activated cell sorting (FACS) isolation strategies.We generated an ASMC-effector mouse line by combining Cspg4/Acta2 intersectional genetics, enabling specific targeting of vascular SMCs, including pulmonary arterial SMCs (PASMCs). To target non-vascular SMCs, including bronchial SMCs (BSMCs), we generated the NVSMC-effector mouse line using Chrm2/Acta2 intersectional genetics. As no driver specific to venous vascular SMCs (VVSMCs) is currently available, we used the transgenic reporter line [Tg(Acta2-GFP)], which labels all pulmonary SMCs, including venous SMCs.
Published in
Cell Type-Specific Targeting of Different Smooth Muscle Cell Populations by Intersectional Genetics
Wang L, Staps M, Günther S et al. · Circulation 2026 · PMID 41969103 · doi:10.1161/CIRCULATIONAHA.125.076318
This dataset
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.

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 GSE301478_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1285307 and SRA study SRP597332. Searching any of these in the dataset finder brings you back here.

Study design
3 × BSMCs vs 3 × PASMCs vs 3 × SmMCll

Supports a between-group comparison across 9 samples.

How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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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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.