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Specificity protein 6 governs human cytotrophoblast fate decisions and trophoblast stem cell establishment by targeting MSX2 regulatory elements [ChIP-seq]

GSE236794 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2024/03/11 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 20 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
20 samples: 9 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.
Summary (written by the submitters)
The commitment and differentiation of human placental progenitor cytotrophoblast (CT) cells are crucial for a successful pregnancy, but the underlying regulatory mechanism remains poorly understood. Here we identified the transcription factor (TF), Specificity protein 6 (SP6), as a human species-specific trophoblast lineage TF expressed in human placental CT cells.
Read the full summary ↓
Using pluripotent stem cells as a model, we demonstrated that SP6 governs CT generation and the establishment of trophoblast stem cells (TSCs) and discovered msh homeobox 2 (MSX2) as the downstream effector in these events. Mechanistically, we showed that SP6 interacts with histone acetyltransferase P300 to modulate the landscape of H3K27ac at targeted regulatory elements, thereby favoring transcriptional activation and facilitating CT cell fate decisions and TSC maintenance. Our results established SP6 as a novel regulator of the human trophoblast lineage and implied its regulatory role in placental development and the pathogenies of placental diseases.
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 GSE236794_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 PRJNA992441 and SRA study SRP448072. Searching any of these in the dataset finder brings you back here.

Study design
9 conditions, mostly in duplicate
G3M,CON,H3K27me3 ×2 G3M,SP6KO,H3K27me3 ×2 G3M,CON,H3K4me3 ×2 G3M,SP6KO,H3K4me3 ×2 G3MS6G,HA ×2 G3M,CON,H3K27ac_SI ×2 G3M,SP6KO,H3K27ac_SI ×2 G3M,CON,P300_SI ×2 +3 more

Supports a between-group comparison across 18 samples.

How we read this: 9 replicated groups read from 20 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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