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Effect of the Mutated p.H222P A-type Lamins on Gene Expression in Both Patient-Derived Cardiomyocytes and Mouse Models of Dilated Cardiomyopathy

GSE289418 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2025/02/17 Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
10 samples: 3 × hiPSCs-CMs LMNA corr.H222P vs 3 × mCM Lmna vs 2 × hiPSCs-CMs LMNA H222P vs 2 × mCM WTGroups 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)
Mutation on A-type lamins encoding gene can lead to a wide-range of diseases called laminopathies, including dilated cardiomyopathy. Nuclear lamins are integral to a physical continuum connecting the extracellular environment and the nuclear interior, playing a crucial role in load-bearing tissues like the heart to preserve mechanical integrity and genome stability.
Read the full summary ↓
To investigate the impact of the LMNA p.H222P mutation on gene expression, we conducteed bulk RNA-seq in hiPSCs-derived cardiomyocytes and mouse cardiomyocytes, both carrying this mutation. Our results reveal that the LMNA p.H222P mutation leads to dysregulated gene expression, which may contribute to LMNA cardiomyopathy pathogenesis.
This dataset
Open GSE289418 in finder → Find more 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 GSE289418_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 PRJNA1222883 and SRA study SRP563478. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × hiPSCs-CMs LMNA corr.H222P vs 3 × mCM Lmna vs 2 × hiPSCs-CMs LMNA H222P vs 2 × mCM WT

Supports a between-group comparison across 10 samples.

How we read this: 4 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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