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Polyamine-dependent metabolic shielding regulates alternative splicing

GSE255769 Homo sapiens (human) RNA-seq (gene expression) 144 samples Submitted 2025/11/11 Platform GPL16791Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 144 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
144 samples: 36 conditions, mostly with about 4 replicates eachGroups 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
Polyamine-dependent metabolic shielding regulates alternative splicingNature · 2026
Summary (written by the submitters)
Metabolites are central to cellular homeostasis. Whereas much emphasis has been placed on their relevance to meet energetic and biosynthetic demands, metabolic intermediates also function as signaling molecules. Here we show that polyamines, small polycations critical to cellular homeostasis1-3, regulate the process of alternative pre-mRNA splicing.
Read the full summary ↓
We find that the inhibition of polyamine synthesis increases the phosphorylation of spliceosomal proteins, concomitant with a remarkable perturbation of alternative splicing in cells and tissues. Mechanistically, molecular modeling combined with biochemical assays revealed that polyamines bind to acidic phosphorylatable motifs in splicing factors of the U2 snRNP SF3 subcomplex, thus preventing the action of kinases. The molecular process through which polyamines regulate protein phosphorylation is a phenomenon that we define as “metabolic shielding”.
Published in
Polyamine-dependent metabolic shielding regulates alternative splicing
Zabala-Letona A, Pujana-Vaquerizo M, Martinez-Laosa B et al. · Nature 2026 · PMID 41535471 · doi:10.1038/s41586-025-09965-1
This dataset
Open GSE255769 in finder → Find more 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 GSE255769_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 PRJNA1076496 and SRA study SRP489717. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41535471) ↗
Study design
36 conditions, mostly with about 4 replicates each
MESC cells, SAM486A, plate ×7 Gastrocnemius, Veh, ×5 Gastrocnemius, SAM486A, ×5 DU145 shAMD1 cells, DOX 48 hours, plate ×4 DU145 shAMD1 cells, noDOX, plate ×4 DU145 shAMD siSCR cells, noDOX, plate ×4 DU145 shAMD siSCR cells, DOX, plate ×4 DU145 shAMD siF3A3 cells, noDOX, plate ×4 +36 more

Supports a between-group comparison across 136 samples.

How we read this: 36 replicated groups read from 144 sample titles; they account for 136 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

+ 104 more — browse all 144 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.