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Context-Dependent and Gene-Specific Role of Chromatin Architecture Mediated by Histone Modifiers and Loop-extrusion Machinery

GSE288605 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 96 samples Submitted 2025/03/31 Platform GPL24247Platform GPL30172Platform GPL34290
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 96 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
96 samples: 36 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)
Loop-extrusion machinery, comprising the cohesin complex and CTCC-binding factor CTCF, organizes the interphase chromosomes into topologically associating domains (TADs) and loops, but acute depletion of components of this machinery results in variable transcriptional changes in different cell types, highlighting the complex relationship between chromatin organization and gene regulation.
Read the full summary ↓
Here, we systematically investigated the role of 3D genome architecture in gene regulation in mouse embryonic stem cells under various perturbation conditions. We found that acute depletion of cohesin or CTCF disrupts the formation of TADs, but affects gene regulation in a gene-specific and context-dependent manner. Furthermore, the loop extrusion machinery was dispensable for transcription from most genes in steady state, consistent with prior results, but became critical for a large number of genes during transition of cellular states. Through a genome-wide CRISPR screen, we uncovered multiple factors that can modulate the role of loop extrusion machinery in gene regulation in a gene-specific manner. Among them were the MORF acetyltransferase complex members (Kat6b, Ing5, Brpf1), which could antagonize the transcriptional insulation mediated CTCF and cohesin complex at developmental genes. Interestingly, inhibition of Kat6b partially rescues the insulator defects in cells lacking the cohesin loader Nipbl, mutations of which are responsible for the developmental disorder Cornelia de Lange syndrome. Taken together, our findings uncovered interplays between the loop extrusion machinery and histone modifying complex that underscore the context-dependent and gene-specific role of the 3D genome.
This dataset
Open GSE288605 in finder → Find more mouse RNA-seq 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 GSE288605_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 PRJNA1218676 and SRA study SRP561272. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
36 conditions, mostly in duplicate
4CBS_Rad21 ×2 Kat6bKo_Rad21 ×2 ctcf_2il_k27ac ×2 ctcf_2ildtag_k27ac ×2 ctcf_diff_k27ac ×2 ctcf_diffdtag_k27ac ×2 rad21_2il_k27ac ×2 rad21_2ildtag_k27ac ×2 +32 more

Supports a between-group comparison across 72 samples.

How we read this: 36 replicated groups read from the first 76 of 96 sample titles; they account for 72 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

+ 56 more — browse all 96 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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