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Passive shaping of intra- and intercellular m6A dynamics via mRNA metabolism

GSE272629 Mus musculus (mouse) RNA-seq (gene expression) 128 samples Submitted 2024/07/25 Platform GPL24247Platform GPL24676Platform GPL17021
At a glance

RNA-seq (gene expression) · mouse · 128 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
Mus musculus (mouse)
Samples
128 samples: 100 distinct titles, 28 of them repeatedGroups 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
Passive shaping of intra- and intercellular m6A dynamics via mRNA metabolismeLife · 2025
Summary (written by the submitters)
m6A is the most widespread mRNA modification and is primarily implicated in controlling mRNA stability. Fundamental questions pertaining to m6A are the extent to which it is dynamically modulated within cells and across stimuli, and the forces underlying such modulation. Prior work has focused on investigating active mechanisms governing m6A levels, such as recruitment of m6A writers or erasers leading to either ‘global’ or ‘site-specific’ modulation.
Read the full summary ↓
Here, we propose that changes in m6A levels across subcellular compartments and biological trajectories may result from passive changes in gene-level mRNA metabolism. To predict the intricate interdependencies between m6A levels, mRNA localization, and mRNA decay, we establish a differential model ‘m6ADyn’ encompassing mRNA transcription, methylation, export, and m6A-dependent and independent degradation. We validate the predictions of m6ADyn in the context of intracellular m6A dynamics, where m6ADyn predicts associations between relative mRNA localization and m6A levels, which we experimentally confirm. We further explore m6ADyn predictions pertaining to changes in m6A levels upon controlled perturbations of mRNA metabolism, which we also experimentally confirm. Finally, we demonstrate the relevance of m6ADyn in the context of cellular heat stress response, where genes subjected to altered mRNA product and export also display predictable changes in m6A levels, consistent with m6ADyn predictions. Our findings establish a framework for dissecting m6A dynamics and suggest the role of passive dynamics in shaping m6A levels in mammalian systems.
Published in
Passive shaping of intra- and intercellular m6A dynamics via mRNA metabolism
Dierks D, Shachar R, Nir R et al. · eLife 2025 · PMID 40586779 · doi:10.7554/eLife.100448
This dataset
Open GSE272629 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 GSE272629_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 PRJNA1137857 and SRA study SRP520960. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40586779) ↗
Study design
100 distinct titles, 28 of them repeated
3t3_Input_cyto ×2 3t3_Input_nuc ×2 3t3_IP_cyto ×2 3t3_IP_nuc ×2 HSTC_pmef_wt_frac_rna_seq_cyt ×2 HSTC_pmef_wt_frac_rna_seq_nuc ×2 frac_mef_input_cyt_ctrl ×2 frac_mef_input_nuc_ctrl ×2 +20 more

How we read this: Read from 128 sample titles: 100 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

+ 88 more — browse all 128 samples with per-sample file links →

Datasets on a similar topic

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