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Unravelling the etiology of dilated cardiomyopathy through differential miRNA-mRNA interactome

GSE243406 Homo sapiens (human) Non-coding RNA profiling 15 samples Submitted 2024/05/29 Platform GPL18573
At a glance

Non-coding RNA profiling · human · 15 samples

What it is
Non-coding RNA profilingLevels of RNAs that do not code for proteins, such as miRNA or lncRNA.
Organism
Homo sapiens (human)
Samples
15 samples: 15 × 21sGroups 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
Unraveling the Etiology of Dilated Cardiomyopathy through Differential miRNA-mRNA InteractomeBiomolecules · 2024
Summary (written by the submitters)
Dilated cardiomyopathy (DCM) entails a broad group of diseases, acquired or genetic, that share a similar phenotype. The understanding of gene-specific pathogenetic mechanisms and the determination of the functional effects of each variant may tailor different therapeutic strategies. MicroRNAs (miRNAs) are short sequences of non-coding RNA that play an important role in the development of several cardiovascular diseases, including DCM.
Read the full summary ↓
Here, we applied mRNA and small RNA sequencing to identify the gene and miRNA signature from myocardial biopsies from four patients with DCM caused by volume overload (VCM) and four with ischemic DCM (ICM). Analysis showed five miRNAs and 112 mRNAs dysregulated in VCM vs ICM. Differentially expressed genes were positively enriched for extracellular matrix (ECM), mitochondria respiration-related, cardiac muscle contraction and fatty acid pathways in VCM vs ICM, and negatively enriched for immune response-related pathways, JAK-STAT and NF-kappa B signaling pathways in VCM vs ICM. miRNA-mRNA interaction analysis revealed four negatively correlated miRNA-target transcript pairs, miR-218-5p-DDX6, miR-218-5p-TT39C, miR-218-5p-SEMA4A and miR-494-3p-SGMS2. qRT-PCR validation showed a strong correlation between RNA-seq and qRT-PCR for these genes and miRNAs. These findings suggest that transcriptome signatures may distinguish distinct etiologies of DCM shedding light on underlying biological differences between VCM and ICM.
Published in
Unraveling the Etiology of Dilated Cardiomyopathy through Differential miRNA-mRNA Interactome
Bonet F, Hernandez-Torres F, Ramos-Sánchez M et al. · Biomolecules 2024 · PMID 38785931 · doi:10.3390/biom14050524
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 GSE243406_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.

Also filed as BioProject PRJNA1018441 and SRA study SRP461364. Searching any of these in the dataset finder brings you back here.

Study design
15 × 21s

Supports a between-group comparison across 15 samples.

How we read this: 1 replicated groups read from 15 sample titles; they account for 15 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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