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Pathogenetic mechanisms of muscle-specific ribosomes in dilated cardiomyopathy (AC16 RNA-seq)

GSE302553 Homo sapiens (human) RNA-seq (gene expression) 42 samples Submitted 2025/11/14 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 42 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
42 samples: 16 conditions, mostly in triplicateGroups 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
Pathogenetic mechanisms of muscle-specific ribosomes in dilated cardiomyopathyNature cardiovascular research · 2026
Summary (written by the submitters)
The heart employs a specialized ribosome in its muscle cells to translate genetic information into proteins, a fundamental adaptation with an elusive physiological role. Its significance is underscored by the discovery of neonatal patients suffering from often fatal heart failure caused by rare biallelic variants in RPL3L, a muscle-specific ribosomal protein that replaces the ubiquitous RPL3 in cardiac ribosomes.
Read the full summary ↓
RPL3L-linked heart failure represents the only known human disease arising from mutations in tissue-specific ribosomes, yet the underlying pathogenetic mechanisms remain poorly understood despite an increasing number of reported cases. While the autosomal recessive inheritance pattern suggests a loss-of-function mechanism, Rpl3l-knockout mice display only mild phenotypes, attributed to up-regulation of the ubiquitous Rpl3. Interestingly, living human knockouts of RPL3L have been identified. Here, we report two new cases of RPL3L-linked severe neonatal heart failure and uncover an unusual pathogenetic mechanism through integrated analyses of population genetic data, patient cardiac tissue, and isogenic cells expressing RPL3L variants. Our findings demonstrate that patient hearts lack sufficient RPL3 compensation. Moreover, contrary to a simple loss-of-function mechanism often associated with autosomal recessive diseases, RPL3L-linked disease is driven by a combination of gain-of-toxicity and loss-of-function. Most patients harbor a recurrent toxic missense variant alongside a non-recurrent variant. The non-recurrent variant is often loss-of-function and enables partial compensation through RPL3, similar to Rpl3l-knockout mice. However, the recurrent missense variant exhibits increased affinity for the RPL3/RPL3L chaperone GRWD1 and 60S biogenesis factors, retains 28S rRNA in the nucleus, disrupts ribosome biogenesis, and induces severe cellular toxicity that extends beyond the loss of ribosomes. These findings elucidate the pathogenetic mechanisms underlying muscle-specific ribosome dysfunction in neonatal heart failure, providing critical insights for genetic screening and therapeutic development. Our findings also suggest that gain-of-toxicity mechanisms may be more widespread in autosomal recessive diseases, especially for those involving genes with paralogs.
Published in
Pathogenetic mechanisms of muscle-specific ribosomes in dilated cardiomyopathy
Murphy MR, Ganapathi M, Rotlevi ER et al. · Nature cardiovascular research 2026 · PMID 41495453 · doi:10.1038/s44161-025-00761-8
This dataset
Open GSE302553 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 GSE302553_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 PRJNA1291178 and SRA study SRP600655. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41495453) ↗
Study design
16 conditions, mostly in triplicate
AC16 cells expressing dox-inducible scrambled… ×3 AC16 cells expressing dox-inducible shRPL3, r… ×3 AC16 cells expressing dox-inducible shRPL3 an… ×3 AC16 cells expressing dox-inducible shRPL3 an… ×3 AC16 cells expressing dox-inducible shRPL3 an… ×3 AC16 cells expressing dox-inducible shRPL3 an… ×3 AC16 cells expressing dox-inducible shRPL3 an… ×3 AC16 cells expressing dox-inducible shRPL3 an… ×3 +9 more

Supports a between-group comparison across 41 samples.

How we read this: 16 replicated groups read from 42 sample titles; they account for 41 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

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