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Regulatory principles of human mitochondrial gene expression revealed by kinetic analysis of the RNA life cycle

GSE224662 Homo sapiens (human) RNA-seq (gene expression) 98 samples Submitted 2025/01/21 Platform GPL18573Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 98 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
98 samples: 95 distinct titles, 3 of them repeatedGroups 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
A kinetic dichotomy between mitochondrial and nuclear gene expression processesMolecular cell · 2024
Summary (written by the submitters)
Mitochondria play a critical role in cellular metabolism primarily through hosting the oxidative phosphorylation (OXPHOS) machinery that is encoded by mitochondrial DNA (mtDNA) and nuclear DNA, with each gene expression system being regulated by a distinct set of mechanisms. In this study, we performed a quantitative analysis of the mitochondrial messenger RNA (mt-mRNA) life cycle to gain insights into the principles underlying the regulation of mtDNA-encoded protein abundance.
Read the full summary ↓
Our analysis revealed a unique balance between the rapid turnover and high accumulation of mt-mRNA, leading to a 700-fold higher transcriptional output compared to nuclear-encoded OXPHOS genes. Additionally, we observed that mt-mRNA processing and its association to the mitochondrial ribosome occur rapidly and that these processes are linked mechanistically. These data resulted in a model of mtDNA expression that is predictive across cell lines, revealing that differential turnover and translation efficiencies are the major contributors to mitochondrial-encoded protein synthesis. Applying this framework to a disease model of Leigh syndrome,  French–Canadian type, we found that the responsible nuclear-encoded gene, LRPPRC, disrupts OXPHOS biogenesis predominantly through altering mt-mRNA stability.  Our findings provide a comprehensive view of the intricate regulatory mechanisms governing mtDNA-encoded protein synthesis, highlighting the importance of quantitatively analyzing the mitochondrial RNA life cycle for decoding the regulatory principles of mtDNA expression.
Published in
A kinetic dichotomy between mitochondrial and nuclear gene expression processes
McShane E, Couvillion M, Ietswaart R et al. · Molecular cell 2024 · PMID 38503286 · doi:10.1016/j.molcel.2024.02.028
This dataset
Open GSE224662 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 GSE224662_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 PRJNA932025 and SRA study SRP421223. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38503286) ↗
Study design
95 distinct titles, 3 of them repeated
RNAseq_K562 ×2 MitoRP_K562 ×2 CytoRP_K562 ×2

How we read this: Read from 98 sample titles: 95 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

+ 58 more — browse all 98 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.