GEO series

Gene expression profile at single cell level of lung from TRAF5 knockout mouse with Systemic Lupus Erythematosus-associated Pulmonary Arterial Hypertension (SLE-PAH)

GSE276751 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2025/08/31 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 2 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 2 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)

Pulmonary arterial hypertension (PAH) is a severe complication that significantly impacts the prognosis of patients with systemic lupus erythematosus (SLE). SLE-PAH has high mortality and morbidity but poorly understood pathogenesis. Our goal is to identify novel susceptibility genes associated with SLE-PAH by performing genetic analyses on large cohorts and validating the functional significance.

Read the full summary ↓

On the genetic level, Whole Exome Sequencing (WES) and Sanger sequencing were performed on the discovery and validation cohorts to identify susceptibility genes associated with SLE-PAH; At the transcriptional level, the expression of susceptibility gene was examined by RNA-seq and RT-qPCR. TRAF5 knockout mice were compared with control after induction of the previously established SLE-PAH model, and the protective effects of TRAF5 overexpression were evaluated. Single-cell RNA sequencing (scRNA-seq) analyses were conducted on lung tissues to investigate pulmonary cellular population. In vitro interventional studies involving TRAF5 knockdown in pulmonary arterial endothelial cells (PAECs) were performed to further investigate its functions. Supporting data from both the discovery and validation cohorts revealed a total of 7 deleterious variants on TRAF5 in 8 cases of SLE-PAH (n=226), with none found in the health control group (HC, n=934). There was decreased TRAF5 expression at the transcriptional level (n=120) compared to SLE-nonPAH (n=116) and HC (n=20). Mice with TRAF5 knockout exhibited more severe pulmonary hypertension, right ventricular hypertrophy, and early mortality. scRNA-seq analyses of lung tissue in knockout mice revealed significantly decreased TRAF5 expression and increased apoptosis in arterial ECs, with distinct pathways identified. In vitro interventional studies confirmed that TRAF5 deficiency caused dysfunction in PAECs, regulating the BMP/TGF-β pathway. Endothelial-targeted overexpression of TRAF5 attenuated PH in model mice.

This dataset

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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 GSE276751_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 PRJNA1158800 and SRA study SRP531655. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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