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Cis-regulatory chromatin loops analysis identifies GRHL3 as a master regulator of surface epithelium commitment

GSE270184 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2024/06/25 Platform GPL20795
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 16 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
16 samples
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
Retinoic acid drives surface epithelium fate determination through the TCF7-MSX2 axisCellular and molecular life sciences : CMLS · 2024
Summary (written by the submitters)
Understanding the regulatory network of cell fate acquisition remains a major challenge. Using the induction of surface epithelium (SE) from human embryonic stem cells as a paradigm, we show that the dynamic changes in morphology-related genes (MRGs) closely correspond to SE fate transitions. The marked remodeling of cytoskeleton indicates the initiation of SE differentiation.
Read the full summary ↓
By integrating promoter interactions, epigenomic features, and transcriptome, we delineate an SE-specific cis-regulatory network and identify grainyhead-like 3 (GRHL3) as an initiation factor sufficient to drive SE commitment. Mechanically, GRHL3 primes the SE chromatin accessibility landscape and activates SE-initiating gene expression. In addition, the evaluation of GRHL3-mediated promoter interactions unveils a positive feedback loop of GRHL3 and bone morphogenetic protein 4 on SE fate decisions. Our work proposes a concept that MRGs could be used to identify cell fate transitions and provides insights into regulatory principles of SE lineage development and stem cell?based regenerative medicine.
Published in
Retinoic acid drives surface epithelium fate determination through the TCF7-MSX2 axis
Huang H, Liu J, An F et al. · Cellular and molecular life sciences : CMLS 2024 · PMID 39725818 · doi:10.1007/s00018-024-05525-4
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 GSE270184_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 PRJNA1125389 and SRA study SRP514782. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 16 more — browse all 16 samples with per-sample file links →

Datasets on a similar topic

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