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Pol II degradation activates cell death independently from the loss of transcription [DKO_wasting_RNAseq]

GSE283148 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2024/12/13 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 30 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
30 samples: 15 conditions, mostly in duplicateGroups 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
Pol II degradation activates cell death independently from the loss of transcriptionbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Pol II-mediated transcription is essential for eukaryotic life. While loss of transcription is thought to be universally lethal, the associated mechanisms promoting cell death are not yet known. Here, we show that death following loss of Pol II is not caused by loss of gene expression. Instead, death occurs in response to the loss of Pol II protein itself.
Read the full summary ↓
Loss of Pol II protein exclusively activates apoptosis, and using functional genomics, we identified a previously uncharacterized pathway, which we call the Pol II Degradation-dependent Apoptotic Response (PDAR). Using the genetic dependencies of PDAR, we identify clinically used drugs that owe their efficacy to a PDAR-dependent mechanism. Our findings unveil a novel apoptotic pathway that contributes to the efficacy of a wide array of anti-cancer therapies.
Published in
Pol II degradation activates cell death independently from the loss of transcription
Harper NW, Birdsall GA, Honeywell ME et al. · bioRxiv : the preprint server for biology 2025 · PMID 39713309 · doi:10.1101/2024.12.09.627542
This dataset
Open GSE283148 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 GSE283148_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 PRJNA1192245 and SRA study SRP548362. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39713309) ↗
Study design
15 conditions, mostly in duplicate
U2OS-BAX-BAK1 -/- cells, Day 0, ×2 U2OS-BAX-BAK1 -/- cells, Day 10, ×2 U2OS-BAX-BAK1 -/- cells, Day 2, ×2 U2OS-BAX-BAK1 -/- cells, Day 4, ×2 U2OS-BAX-BAK1 -/- cells, Day 6, ×2 U2OS-BAX-BAK1 -/- cells, Day 8, ×2 U2OS cells, Day 0, ×2 U2OS cells, Day 1, ×2 +7 more

Supports a between-group comparison across 30 samples.

How we read this: 15 replicated groups read from 30 sample titles; they account for 30 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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