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Defective RNA processing and ELOA-mediated transcriptional elongation in reversible cellular senescence suggest aging by transcription

GSE297352 Homo sapiens (human) RNA-seq (gene expression) 58 samples Submitted 2025/12/22 Platform GPL34382Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 58 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
58 samples: 58 samples, each with a distinct title — no replicated groupsGroups 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
Defective RNA processing and ELOA-mediated transcriptional elongation in reversible cellular senescence suggest aging by transcriptionMolecular cell · 2025
Summary (written by the submitters)
Elongation factors control post-initiation steps of transcription by RNA polymerase II (RNAPII). We have established distinct mechanistic roles for the essential elongation factors PAF1, NELF, SPT5, and SPT6 via acute depletion of each individually in auxin-inducible degron lines. Here, we leverage these degron lines to explore the regulatory intersection of elongation control and mRNA processing.
Read the full summary ↓
Integrating long- and short-read RNA-seq data to quantify transcript isoform usage at single-molecule resolution, we identify elongation factor-specific RNA processing regulons including a cellular senescence-enriched regulon shared by NELF and SPT6. We then show that long-term depletion of NELF or SPT6 results in reversible growth arrest following early upregulation of a small group of genes, which include the senescence-associated genes CDKN1A (p21) and CCN2. We perform genetic suppressor screens that implicate the elongation factor Elongin A (ELOA) in NELF or SPT6 depletion-induced growth arrest. ELOA KO suppresses NELF depletion-induced mRNA processing defects and the 3’ extension of RNAPII occupancy past transcription end sites (TES) at genes induced by NELF depletion. ELOA also occupies TES-proximal regions under normal conditions, and acute ELOA depletion results in a loss of RNAPII processivity at the 3’ end of genes, opposing the effects of NELF or SPT6 depletion. Finally, we demonstrate that genetic ELOA loss confers a growth advantage to aging human primary dermal fibroblasts. These findings establish the existence of novel ELOA-dependent mechanisms regulating transcription termination-coupled processes, and links these to the complex phenomena of cellular senescence and aging.
Published in
Defective RNA processing and ELOA-mediated transcriptional elongation in reversible cellular senescence suggest aging by transcription
Parast S, Wang S, Iwanaszko M et al. · Molecular cell 2025 · PMID 41418754 · doi:10.1016/j.molcel.2025.11.021
This dataset
Open GSE297352 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 GSE297352_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 PRJNA1263612 and SRA study SRP585728. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41418754) ↗
Study design
58 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 58 sample titles: 58 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

+ 18 more — browse all 58 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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