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Histone 3 lysine 9 methylation balance controls transient site-specific DNA amplification and genomic rearrangements of Mixed Lineage Leukemia (MLL)

GSE210480 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 60 samples Submitted 2024/08/02 Platform GPL21697Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 60 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
60 samples: 51 distinct titles, 9 of them repeatedGroups 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)
DNA amplifications and rearrangements are observed in cancer. In infant and adult leukemia as well as therapy-induced leukemia, MLL/KMT2A amplifications and translocations are prevalent. To date, the exact molecular contributor(s) to these alterations are unclear. In this study, we demonstrate that histone H3 K9 mono- and di-methylation (H3K9me1/2) balance at the MLL/KMT2A locus is regulating the amplifications and rearrangements.
Read the full summary ↓
This balance is controlled by the cross-talk between lysine demethylase KDM3B and methyltransferase G9a/EHMT2. KDM3B loss or chemical suppression increases H3K9me1/2 and reduced CTCF occupancy in KMT2A, and in turn, promotes amplification and rearrangements. Reducing CTCF levels was also sufficient to generate these alterations. Furthermore, Doxorubicin (Dox), which promotes MLL/KMT2A amplifications and rearrangements, suppresses KDM3B and CTCF protein levels. By suppressing G9a or overexpressing KDM3B, the Dox induced MLL/KMT2A alterations are rescued. Therefore, MLL/KMT2A induced amplifications and rearrangements are controlled by distinct epigenetic enzymes that are druggable, which has clinical implications.
This dataset
Open GSE210480 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 GSE210480_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 PRJNA865758 and SRA study SRP389730. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
51 distinct titles, 9 of them repeated
CTRLsiKDM3B_H3K9ME2 ×2 CTRLsiKDM3B_Input ×2 CTRLsiKDM3B_H3K9me1 ×2 siCT-CTCF-High ×2 siCT-INPUT ×2 CTRLsiKDM3B_H3K9me1_exp1 ×2 CTRLsiKDM3B_H3K9me2_exp1 ×2 CTRLsiKDM3B_Input_exp1 ×2 +1 more

How we read this: Read from 60 sample titles: 51 distinct titles with little repetition. 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

+ 20 more — browse all 60 samples with per-sample file links →

Datasets on a similar topic

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