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Chromatin Landscape Instructs Precise Transcription Factor Regulome during Embryonic Lineage Specification [CUT&RUN]

GSE250176 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 42 samples Submitted 2024/04/01 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 42 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
Mus musculus (mouse)
Samples
42 samples: 14 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
Chromatin landscape instructs precise transcription factor regulome during embryonic lineage specificationCell reports · 2024
Summary (written by the submitters)
Embryos, originating from fertilized eggs, undergo continuous cell division and differentiation, accompanied by dramatic changes in transcription, translation, and metabolism. Epigenetic information and transcription factors (TFs) play indispensable roles in regulating these processes. Recently, the trophoblast regulator TFAP2C was identified as crucial in initiating early cell fate decisions.
Read the full summary ↓
However, Tfap2c transcripts persist in both the inner cell mass (ICM) and trophectoderm (TE) of blastocysts, prompting inquiry into its function in post-lineage establishment. In this study, we delineate the dynamics of TFAP2C during the mouse peri-implantation stage and elucidate its collaboration with the key lineage regulators CDX2 and NANOG. Importantly, we propose that de novo formation of H3K9me3 in the extraembryonic ectoderm during implantation antagonizes TFAP2C binding to crucial developmental genes, thereby maintaining its lineage identity. Together, this research highlights the plasticity of the epigenetic environment in designating the genomic binding of highly adaptable lineage-specific TFs and regulating embryonic cell fates.
Published in
Chromatin landscape instructs precise transcription factor regulome during embryonic lineage specification
Wang L, Yi S, Cui X et al. · Cell reports 2024 · PMID 38643480 · doi:10.1016/j.celrep.2024.114136
This dataset
Open GSE250176 in finder → Find more mouse 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 GSE250176_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 PRJNA1052604 and SRA study SRP477937. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38643480) ↗
Study design
14 conditions, mostly in duplicate
CDX2_E6.5_ExE ×3 NANOG_E6.5_Epi ×3 CDX2_Morula ×2 CDX2_TE ×2 CDX2_TSC ×2 NANOG_Morula ×2 NANOG_ICM ×2 NANOG_ESC ×2 +18 more

Supports a between-group comparison across 30 samples.

How we read this: 14 replicated groups read from 42 sample titles; they account for 30 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

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