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Deubiquitinase USP9X regulates Wnt-signaling to control CNS vascular formation and barrier maintenance [Human]

GSE281250 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2024/12/13 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples: 5 × siCtrl vs 5 × siUSP9XGroups 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)
Deubiquitinating enzymes play crucial roles in various cellular activities, yet their involvement in central nervous system (CNS) vascularization and barrier function remains elusive. Canonical Wnt signaling is essential for proper CNS vascularization and barrier maintenance. Using a loss-of-function screening for Wnt signaling activity, we identified ubiquitin-specific peptidase 9 X-linked (USP9X) as a key regulator in brain endothelial cells (BECs).
Read the full summary ↓
Endothelium-specific Usp9x knockout reduces Wnt-signaling activity, compromising CNS vascularization and barrier function during development. Activation of Wnt signaling rescues these defects. Mechanistically, we uncovered β-catenin as a direct substrate of USP9X, with USP9X catalyzing K48 polyubiquitin chains to stabilize β-catenin. In pathological models of impaired CNS vascular barrier function, including an intracerebral hemorrhage model and an oxygen-induced retinopathy model, loss of Usp9x intensifies barrier disruption, accentuating defects. This finding implicates USP9X as a critical regulator of CNS vascularization and barrier function through Wnt signaling, offering insights into CNS disease implications.
This dataset
Open GSE281250 in finder → Find more human 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 GSE281250_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 PRJNA1182804 and SRA study SRP543638. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 × siCtrl vs 5 × siUSP9X

Supports a between-group comparison across 10 samples.

How we read this: 2 replicated groups read from 10 sample titles; they account for 10 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
Datasets on a similar topic

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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.