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MLL-AF9 lates transcriptional initiation in mixed lineage leukemic cells

GSE231814 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 92 samples Submitted 2024/07/15 Platform GPL24247Platform GPL24676Platform GPL11154Platform GPL16791
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 92 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
92 samples: 43 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
MLL-AF9 regulates transcriptional initiation in mixed lineage leukemic cellsThe Journal of biological chemistry · 2024
Summary (written by the submitters)
MLL-fusion proteins (MLL-FPs) are believed to maintain gene activation and induce mixed lineage leukemia (MLL) through aberrantly stimulating transcriptional elongation, but the underlying mechanisms are incompletely understood. Here we show that both MLL1 and AF9, one of the major fusion partners of MLL1, mainly occupy promoters and distal intergenic regions, exhibiting chromatin occupancy patterns resembling that of RNA polymerase II (Pol II) in HEL, a human cell line without MLL1 arrangement (MLLr).
Read the full summary ↓
MLL1 and AF9 only co-regulate over a dozen genes despite of their co-occupancy on thousands of genes. They do not interact with each other, and their chromatin occupancy is also independent of each other. Moreover, AF9 deficiency in HEL cells decreases global TBP occupancy while decreases CDK9 occupancy on a small number of genes, suggesting an accessory role of AF9 in CDK9 recruitment and a possible major role in transcriptional initiation via initiation factor recruitment. Importantly, MLL1 and MLL-AF9 occupy promoters and distal intergenic regions, exhibiting identical chromatin occupancy patterns in MLL cells, and MLL-AF9 deficiency decreased occupancy of TBP and TFIIE on major target genes of MLL-AF9 in iMA9, a murine acute myeloid leukemia (AML) cell line inducibly expressing MLL-AF9, suggesting that it can also regulate initiation. These results suggest that there is no difference between MLL1 and MLL-AF9 with respect to location and size of occupancy sites, contrary to what people have believed, and that MLL-AF9 may also regulate transcriptional initiation in addition to widely-believed elongation.
Published in
MLL-AF9 regulates transcriptional initiation in mixed lineage leukemic cells
Yang Z, Zhang G, Zhao R et al. · The Journal of biological chemistry 2024 · PMID 39002676 · doi:10.1016/j.jbc.2024.107566
This dataset
Open GSE231814 in finder → Find more 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 GSE231814_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 PRJNA967726 and SRA study SRP436210. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39002676) ↗
Study design
43 conditions, mostly in duplicate
Ctrl RNA-seq ×3 MLL1 KD RNA-seq ×3 HEL_MLL1shRNA1_Ctrl_MLL1 ×2 HEL_MLL1shRNA1_MLL1KD_MLL1 ×2 HEL_MLL1shRNA1_Ctrl_AF9 ×2 HEL_MLL1shRNA1_MLL1KD_AF9 ×2 HEL_MLL1shRNA1_Ctrl_CDK9 ×2 HEL_MLL1shRNA1_MLL1KD_CDK9 ×2 +39 more

Supports a between-group comparison across 88 samples.

How we read this: 43 replicated groups read from 92 sample titles; they account for 88 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

+ 52 more — browse all 92 samples with per-sample file links →

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