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Time-series RNA-seq of U2OS cells following CCCP-induced mitochondrial damage and recovery upon drug washout

GSE342354 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/08/05 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × Human U2OS cells, untreated control (WT), Biol vs 3 × Human U2OS cells, 50 μM CCCP for 30 min (CCCP), Biol vs 3 × Human U2OS cells, 50 μM CCCP for 30 min followed by 1 h washout (W1H), Biol vs 3 × Human U2OS cells, 50 μM CCCP for 30 min followed by 6 h washout (W6H), BiolGroups 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)
Mitochondria are continuously exposed to damage that contributes to aging and disease. While prolonged mitochondrial damage triggers mitophagy, how cells respond to transient damage remains unclear. To investigate the transcriptional programs underlying transient mitochondrial damage and subsequent recovery, we performed time-series RNA-seq analysis in human U2OS cells treated with the mitochondrial uncoupler CCCP.
Read the full summary ↓
Four groups were analyzed: untreated control (WT), 50 μM CCCP for 30 min (CCCP), 50 μM CCCP for 30 min followed by 1 h washout (W1H), 50 μM CCCP for 30 min followed by 6 h washout (W6H). Each condition was analyzed in triplicate. This dataset reveals the dynamic transcriptional landscape during mitochondrial damage and recovery, highlighting the activation of stress-responsive transcription factors and antioxidant defense pathways that facilitate mitochondrial repair.
This dataset
Open GSE342354 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 GSE342354_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 PRJNA1507420 and SRA study SRP724128. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × Human U2OS cells, untreated control (WT), Biol vs 3 × Human U2OS cells, 50 μM CCCP for 30 min (CCCP), Biol vs 3 × Human U2OS cells, 50 μM CCCP for 30 min followed by 1 h washout (W1H), Biol vs 3 × Human U2OS cells, 50 μM CCCP for 30 min followed by 6 h washout (W6H), Biol

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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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.