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Study of 5mC-DNA, m6A-RNA and RNA-expression in HeLa, ES and EB [RNAseq in Mettl14KO and rescued in E14TG2a ES/EB]

GSE272789 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/01/10 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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
Fine-tuning of gene expression through the Mettl3-Mettl14-Dnmt1 axis controls ESC differentiationCell · 2025
Summary (written by the submitters)
Marking of DNA, histones, and RNA is central to gene expression regulation in development and disease. Recent evidence links m6A, installed on RNA by the METTL3-METTL14 methyltransferase complex, to histone modifications, but the link between m6A and DNA methylation remains scarcely explored. This study shows that METTL3-METTL14 recruits the DNA methyltransferase DNMT1 to chromatin for gene-body methylation.
Read the full summary ↓
We identify a set of genes whose expression is fine-tuned by both gene-body 5mC, which promotes transcription, and m6A, which destabilizes transcripts. We demonstrate that METTL3-METTL14-dependent 5mC and m6A are both essential for the differentiation of embryonic stems cells to embryoid bodies and that the upregulation of key differentiation genes during early differentiation depends on the dynamic balance between increased 5mC and decreased m6A. Our findings add a surprising new dimension to our understanding of how epigenetics and epitranscriptomics combine to regulate gene expression and impact development, most likely among other biological processes.
Published in
Fine-tuning of gene expression through the Mettl3-Mettl14-Dnmt1 axis controls ESC differentiation
Quarto G, Li Greci A, Bizet M et al. · Cell 2025 · PMID 39826545 · doi:10.1016/j.cell.2024.12.009
This dataset
Open GSE272789 in finder → Find more mouse 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 GSE272789_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 PRJNA1138740 and SRA study SRP521390. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39826545) ↗
Study design
6 conditions, mostly in triplicate
EBd8-Mettl14KO ×3 EBd8-Mettl14KOR442K ×3 EBd8-WT ×3 ES-Mettl14KO ×3 ES-Mettl14KOR442K ×3 ES-WT ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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