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Accelerated RNA polymerase II elongation drives endothelial transition and plaque vulnerability: pharmacological targeting of the super elongation complex [RNA-seq]

GSE330229 Mus musculus (mouse) Single-nucleus RNA-seq 24 samples Submitted 2026/08/01 Platform GPL24247
At a glance

Single-nucleus RNA-seq · mouse · 24 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
24 samples: 6 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.
Summary (written by the submitters)
Atherosclerotic plaque rupture is a major cause of myocardial infarction and stroke, yet the mechanisms governing plaque stability remain incompletely understood. Endothelial activation can trigger endothelial-to-mesenchymal transition, a program linked to endothelial dysfunction and lesion vulnerability. Here we investigated whether transcriptional pause release and RNA polymerase II elongation constitute an early regulatory layer that promotes endothelial-to-mesenchymal transition and atherosclerosis.
Read the full summary ↓
Analysis of human plaque single-nucleus transcriptomics indicated increased expression of super elongation complex components in endothelial cells with a transition signature. In primary human endothelial cell models, pharmacological inhibition of the super elongation complex attenuated induction of mesenchymal markers. AFF4, pCDK9, and pSMAD2/3, showed physical interaction during endothelial transition. Genome-wide profiling of RNA polymerase II occupancy revealed reduced promoter-proximal pausing during early transition, accompanied by a rapid increase in nascent transcriptional elongation rates. Super elongation complex inhibition restored pausing and suppressed fast-responding transition-associated target genes. In a human cardiac organoid model, inhibition of the super elongation complex prevented EndMT-induced fibrillar collagen deposition and reduction in cardiomyocyte beating rate. In a hyperlipidemic Pcsk9 gain-of-function mouse model, super elongation complex inhibition administered both prophylactically and therapeutically after established atherosclerosis reduced plaque burden and improved features associated with vulnerability. Finally, analysis of 1,048 human plaque segments from the Athero-Express biobank showed significant associations between the elongation axis and multiple vulnerability-related plaque traits. Together, these findings identify rapid transcriptional elongation as a mechanistic driver of endothelial plasticity and features of plaque vulnerability and support targeting the elongation machinery as a potential strategy to stabilize atherosclerotic disease.
This dataset
Open GSE330229 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 GSE330229_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 PRJNA1463192 and SRA study SRP698322. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 4 replicates each
HFD/KL-2_therapeutic_n ×5 HFD/DMSO_preventive_n ×4 NormalChow_preventive_n ×4 NormalChow_therapeutic_n ×4 HFD/DMSO_therapeutic_n ×4 HFD/KL-2_preventive_n ×3

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 sample titles; they account for 24 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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