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Cellular Senescence in the Absence of Galactic Cosmic-Ray Muons

GSE310137 Homo sapiens (human) RNA-seq (gene expression) 60 samples Submitted 2026/06/04 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 60 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
60 samples: 30 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
Cellular Senescence in the Absence of Galactic Cosmic-Ray MuonsAging and disease · 2026
Summary (written by the submitters)
Cellular senescence is a protective stress-response that halts cell proliferation to prevent the accumulation of damage. Life on Earth evolved in the presence of constant, low-dose, unavoidable genotoxic stress caused by highly penetrating muons generated by cosmic rays. However, how cosmic background radiation (CBR) shapes senescence remains unclear.
Read the full summary ↓
We exploited the Canfranc Deep Underground Laboratory (LSC-DUL), which is located 850 meters beneath the Spanish Pyrenees, to compare senescence phenomena in near-surface versus muon-depleted deep underground environments. The LSC-DUL provides 2,450 meters of water-equivalent shielding, reducing the flux of cosmic-ray muons by five orders of magnitude. Human cancer and noncancer cells were subjected to replicative, mitotic, and oxidative insults with diverse DNA damage response (DDR) activation potencies. Muon deprivation modestly but significantly reduced progression to late, lysosome-dependent SA--gal-positive states after low-DDR replicative stressors. However, high-DDR regimens were largely insensitive to the environment. Transcriptomic signatures of senescent states and the qualitative composition of senescence-associated secretory phenotypes (SASPs) were broadly conserved. Conceptually, stressed cells enter a shallow transcriptional and SASP-positive senescent basin that is permissive across CBR conditions. However, they cross a “CBR barrier” into a deeper SA--gal+ attractor less efficiently when ambient radiogenic noise is depleted and DDR amplitude is low. The robust inertia of high DDR damage readily overrides this barrier, ensuring the immediate occupation of the SA--gal+ fate regardless of the muonic environment. Our findings identify cosmogenic muons as evolutionary radiobiological calibrators of senescence decision-making in the near-surface biosphere. They also generate testable predictions for senescence operability in habitats lacking Earth’s characteristic muon flux, such as the Moon and Mars.
Published in
Cellular Senescence in the Absence of Galactic Cosmic-Ray Muons
Llop-Hernández À, López J, Verdura S et al. · Aging and disease 2026 · PMID 42234970 · doi:10.14336/AD.2026.0025
This dataset
Open GSE310137 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 GSE310137_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 PRJNA1365187 and SRA study SRP645160. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42234970) ↗
Study design
30 conditions, mostly in duplicate
A549 cells, proliferative control, day 1, AGL, ×2 A549 cells, proliferative control, day 1, DUL, ×2 A549 cells, alisertib 100 nmol/L, day 3, AGL, ×2 A549 cells, alisertib 500 nmol/L, day 3, AGL, ×2 A549 cells, bleomycin 20 umol/L, day 3, AGL, ×2 A549 cells, bleomycin 5 umol/L, day 3, AGL, ×2 A549 cells, proliferative control, day 3, AGL, ×2 A549 cells, Palboclib 1 umol/L, day 3, AGL, ×2 +22 more

Supports a between-group comparison across 60 samples.

How we read this: 30 replicated groups read from 60 sample titles; they account for 60 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

+ 20 more — browse all 60 samples with per-sample file links →

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.