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METTL3-dependent m6A RNA methylation represses transposable elements derived enhancers to suppress naïve pluripotency in human pluripotent stem cells

GSE275738 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 72 samples Submitted 2025/04/16 Platform GPL20301Platform GPL11154Platform GPL21290Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 72 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
72 samples: 24 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
METTL3-dependent m6A RNA methylation regulates transposable elements and represses human naïve pluripotency through transposable element-derived enhancersNucleic acids research · 2025
SuperSeries — this record groups several sub-series.
Summary (written by the submitters)
This SuperSeries is composed of the SubSeries listed below.
Published in
METTL3-dependent m6A RNA methylation regulates transposable elements and represses human naïve pluripotency through transposable element-derived enhancers
Zhang W, Fu H, Huang Y et al. · Nucleic acids research 2025 · PMID 40298111 · doi:10.1093/nar/gkaf349
This dataset
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.

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 GSE275738_RAW.tar (it can run to tens of gigabytes).

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.

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1152872 and SRA study SRP529376. Searching any of these in the dataset finder brings you back here.

Study design
24 conditions, mostly in duplicate
METTL3 iKO hEPSC Clone 1 with DOX, ×2 METTL3 iKO hEPSC Clone 1 in Passage 2 without… ×2 METTL3 iKO hEPSC Clone 1 in Passage 3 without… ×2 METTL3 iKO hEPSC Clone 2 with DOX, ×2 METTL3 iKO hEPSC Clone 2 in Passage 2 without… ×2 METTL3 iKO hEPSC Clone 2 in Passage 3 without… ×2 METTL3 iKO primed hESC Clone 1 with DOX, ×2 METTL3 iKO primed hESC Clone 1 in Passage 2 w… ×2 +40 more

Supports a case/control comparison: 2 samples read as cases, 2 as controls.

How we read this: 24 replicated groups read from 72 sample titles; they account for 48 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

+ 32 more — browse all 72 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.