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Genome-wide CRISPR screen identifies Menin and SUZ12 as regulators of human developmental timing [CUT&RUN]

GSE279033 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 32 samples Submitted 2025/06/26 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 32 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
32 samples: 16 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
Genome-wide CRISPR screen identifies Menin and SUZ12 as regulators of human developmental timingNature cell biology · 2025
Summary (written by the submitters)
Embryonic development follows a sequence of events that is broadly conserved across species, yet the pace of development is highly variable. Compared to most other species, humans exhibit a slower pace that is largely recapitulated in in vitro stem cell models, suggesting a cell-intrinsic clock that tracks time. Using the directed differentiation of human embryonic stem cells (hESCs) into neuroectoderm as a proxy for developmental timing, we performed a whole-genome CRISPR-Cas9 screen and found that epigenetic factors MEN1 and SUZ12 modulate the speed of hESC neural differentiation.
Read the full summary ↓
Genetic and pharmacological loss-of-function of MEN1 or SUZ12 accelerates the acquisition of neural fate by altering the balance of activating H3K4me3 and repressive H3K27me3 chromatin modifications at bivalent promoters and thereby priming a faster activation of developmental genes upon differentiation. The acceleration effect is also observed in definitive endoderm, cardiomyocyte, and neuronal differentiations. These results indicate that chromatin bivalency acts a general driver of human-specific timing across all major germ layers and developmental stages. Furthermore, our study uncovers a novel functional cooperation between MEN1 and SUZ12 as a key mechanism for the temporal regulation of developmental programs.
Published in
Genome-wide CRISPR screen identifies Menin and SUZ12 as regulators of human developmental timing
Xu N, Cho HS, Hackland JOS et al. · Nature cell biology 2025 · PMID 40897805 · doi:10.1038/s41556-025-01751-5
This dataset
Open GSE279033 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE279033_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1170193 and SRA study SRP537164. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40897805) ↗
Study design
16 conditions, mostly in duplicate
Menin_H9_d0_CUT&RUN ×2 MLL1_H9_d0_CUT&RUN ×2 SUZ12_H9_d0_CUT&RUN ×2 IgG_H9_d0_CUT&RUN ×2 H3K4me3_H9_d0_CUT&RUN ×2 H3K27me3_H9_d0_CUT&RUN ×2 H3K4me3_MEN1_d0_CUT&RUN ×2 H3K27me3_MEN1_d0_CUT&RUN ×2 +8 more

Supports a between-group comparison across 32 samples.

How we read this: 16 replicated groups read from 32 sample titles; they account for 32 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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