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Adenosine to Inosine RNA editing level in ADAR1-deficient or hypoxia-exposed human pulmonary artery endothelial cells

GSE281541 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/10/08 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 12 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
Homo sapiens (human)
Samples
12 samples: 3 × Hu-siNC vs 3 × Hu-siADAR1 vs 3 × Hu_Nx vs 3 × Hu_HxGroups 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
Endothelial ADAR1 Deficit Induces the NOCT-IRF7 Axis in Pulmonary HypertensionCirculation research · 2026
Summary (written by the submitters)
Hypoxia is a PH trigger which significantly downregulates ADAR1 and reduces A-to-(I)G editing in human PAECs. By RNA sequencing of PAECs after ADAR1 knockdown, we have identified the circadian gene Nocturnin (NOCT) as a direct ADAR1 target. NOCT carries two active A-to-I RNA editing sites in the 3’UTR. In addition, hypoxia significantly reduced A-to-G editing in human PAECs
Published in
Endothelial ADAR1 Deficit Induces the NOCT-IRF7 Axis in Pulmonary Hypertension
Woodcock CC, Maroli G, Kim H et al. · Circulation research 2026 · PMID 41342206 · doi:10.1161/CIRCRESAHA.125.326277
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 GSE281541_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 PRJNA1184349 and SRA study SRP544351. Searching any of these in the dataset finder brings you back here.

Study design
3 × Hu-siNC vs 3 × Hu-siADAR1 vs 3 × Hu_Nx vs 3 × Hu_Hx

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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