GEO series

Endothelial derived, secreted long non-coding RNAs Gadlor1 and Gadlor2 aggravate cardiac remodeling

GSE213612 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2024/08/26 Platform GPL17021

At a glance

RNA-seq (gene expression) · mouse · 20 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: Mus musculus (mouse)
Samples: 20 samples: 20 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: Endothelial derived, secreted long non-coding RNAs Gadlor1 and Gadlor2 aggravate cardiac remodelingMolecular therapy. Nucleic acids · 2024

Summary (written by the submitters)

Background: Pathological cardiac overload triggers maladaptive myocardial remodeling that predisposes to the development of heart failure. The contribution of long non-coding RNAs (lncRNAs) to intercellular signaling during cardiac remodeling is largely unknown. Methods: We analyzed the expression of Gadlor 1 and Gadlor2 lncRNAs in mouse hearts, mouse cardiac cells, extracellular vesicles (EVs), human failing hearts as well as patient serum.

Read the full summary ↓

Gadlor knock-out (KO) mice were generated and analyzed. The effect of Gadlor knock-out and Gadlor overexpression during cardiac pressure overload induced by transverse aortic constriction (TAC) was analyzed by echocardiography, histological analyses and RNA sequencing in isolated cardiac cells. Gadlor1/2 interaction partners were identified by RNA antisense purification coupled with mass-spectrometry (RAP-MS). Results: In the heart, the related lncRNAs Gadlor1 and 2 are mainly expressed in endothelial cells and to a lesser extent in fibroblasts. Gadlor1/2 are upregulated in failing mouse hearts as well as in the myocardium and in serum of heart failure patients. Interestingly, Gadlor1 and 2 are secreted from endothelial cells within EVs, which are taken up by cardiomyocytes. Gadlor-KO mice exerted reduced cardiomyocyte hypertrophy, diminished myocardial fibrosis and improved cardiac function, but paradoxically suffered from sudden death during prolonged overload. Gadlor overexpression, in turn, triggered hypertrophy, fibrosis and cardiac dysfunction. Mechanistically, Gadlor1 and Gadlor2 inhibit angiogenic gene expression in endothelial cells, while promoting the expression of pro-fibrotic genes in cardiac fibroblasts. In cardiomyocytes, Gadlor1/2 upregulate mitochondrial genes, but downregulate angiogenesis genes, while interacting with the transcriptional regulator Glyr1 and the calcium/calmodulin-dependent protein kinase type II (CaMKII), entailing cardiomyocyte hypertrophy and perturbed cardiomyocyte calcium dynamics. Conclusions: We describe that Gadlor1 and 2, two related, novel lncRNAs, are upregulated in cardiac pathological overload and are secreted from endothelial cells within EVs. Gadlor1/2 induce cardiac dysfunction, cardiomyocyte hypertrophy and myocardial fibrosis by exerting heterocellular effects on cardiac cellular gene-expression and by affecting calcium dynamics in cardiomyocytes, which take up the Gadlor1/2 by EV mediated transfer from endothelial cells. Targeted inhibition of Gadlor lncRNAs in endothelial cells or fibroblasts might serve as therapeutic strategy in the future.

Published in

Endothelial derived, secreted long non-coding RNAs Gadlor1 and Gadlor2 aggravate cardiac remodeling

Keles M, Grein S, Froese N et al. · Molecular therapy. Nucleic acids 2024 · PMID 39281699 · doi:10.1016/j.omtn.2024.102306

This dataset

Open GSE213612 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 GSE213612_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 PRJNA879919 and SRA study SRP396900. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39281699) ↗

Study design

20 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 20 sample titles: 20 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

GSM6589844 WT-31-EC_1
GSM6589845 WT-32-EC_1
GSM6589846 WT-34-EC_1
GSM6589847 WT-35-EC_1
GSM6589848 KO-105-EC_1
GSM6589849 KO-108-EC_1
GSM6589850 KO-131-EC_1
GSM6589851 KO-133-EC_1
GSM6589852 WT-260-FB_1
GSM6589853 WT-277-FB_1
GSM6589854 WT-283-FB_1
GSM6589855 KO-240-FB_1
GSM6589856 KO-241-FB_1
GSM6589857 KO-242-FB_1
GSM6589858 WT-CM1_1
GSM6589859 WT-CM2_1
GSM6589860 WT-CM6_1
GSM6589861 KO-CM1_1
GSM6589862 KO-CM2_1
GSM6589863 KO-CM3_1

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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.