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GLS1 governs vascular smooth muscle cell phenotypic switching and aortic dissection via glutamate metabolism

GSE324926 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/03/20 Platform GPL24676
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: 12 samples, each with a distinct title — no replicated groupsGroups 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
GLS1 governs vascular smooth muscle cell phenotypic switching and aortic dissection via glutamate metabolismJCI insight · 2026
Summary (written by the submitters)
To evaluate the roles of glutaminase 1 (GLS1) in vascular smooth muscle cells (VSMCs) phenotypic switching and aortic dissection (AD). Integrative transcriptomic analyses were performed to identify the candidate genes involved in VSMC phenotypic switching in AD. The expression of GLS1 in VSMCs was assessed by qRT-PCR, Western blot and immunofluorescence.
Read the full summary ↓
RNA-sequencing analysis was performed to recapitulate possible changes in the transcriptome profile of GLS1 in VSMCs. We identified GLS1 as a potential regulator in AD. GLS1 expression was significantly downregulated in VSMCs from both human AD aortic tissues and mouse models. Mechanistically, down-regulation of GLS1 impaired glutamate metabolism, leading to reduced levels of glutathione and α-ketoglutarate, thereby promoting mitochondrial dysfunction and accumulation of reactive oxygen species, which activated the PI3K/AKT pathway and ultimately triggered VSMC phenotypic switching. These findings revealed a critical role of GLS1-mediated glutamate metabolism in VSMC phenotypic switching and suggest a promising therapeutic target for AD.
Published in
GLS1 governs vascular smooth muscle cell phenotypic switching and aortic dissection via glutamate metabolism
Xie W, Ning C, Lu C et al. · JCI insight 2026 · PMID 42024443 · doi:10.1172/jci.insight.203575
This dataset
Open GSE324926 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 GSE324926_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 PRJNA1438102 and SRA study SRP684055. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42024443) ↗
Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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.