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A MOZ-TIF2 leukemic mouse model displays KAT6 inhibitor-sensitive H3K23 propionylation and dysregulation of a set of highly active developmental genes [RNA-seq]

GSE260638 Mus musculus (mouse) RNA-seq (gene expression) 40 samples Submitted 2024/07/03 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 40 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
40 samples: 15 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
A MOZ-TIF2 leukemia mouse model displays KAT6-dependent H3K23 propionylation and overexpression of a set of active developmental genesProceedings of the National Academy of Sciences of the United States of America · 2024
Summary (written by the submitters)
Aberrant regulation of chromatin modifiers is a common occurrence across many cancer types, and a key priority is to determine how specific alteration of these proteins, often enzymes, can be targeted therapeutically. MOZ, a histone acyltransferase, is recurrently fused to coactivators CBP, p300, and TIF2 in cases of Acute Myeloid Leukemia (AML).
Read the full summary ↓
Using either pharmacological inhibition or targeted protein degradation in a mouse model for MOZ-TIF2-driven leukemia, we show that KAT6 (MOZ/MORF) enzymatic activity and the MOZ-TIF2 protein are necessary for indefinite proliferation in cell culture. Interestingly, MOZ enzymatic activity is selectively required in MOZ-TIF2 cells, as murine MLL-AF9 leukemic cells show no sensitivity to the WM-1119 MOZ inhibitor. MOZ-TIF2 directly regulates a small subset of genes encoding developmental transcription factors, augmenting their high expression. Transcription levels of these genes positively correlate with enrichment of histone H3 propionylation at lysine 23 (H3K23pr), a recently appreciated histone acylation associated with gene activation. Unexpectedly, we also show that MOZ-TIF2 and MLL-AF9 regulate transcription of largely non-overlapping gene sets, and their cellular models exhibit distinct sensitivities to multiple small molecule inhibitors directed against AML pathways. This is despite the shared genetic pathways of wild-type MOZ and MLL. Overall, our data provide insight into how aberrant regulation of MOZ contributes to leukemogenesis. We anticipate these experiments will inform future work identifying targeted therapies in the treatment of AML and other diseases involving MOZ-induced transcriptional dysregulation.
Published in
A MOZ-TIF2 leukemia mouse model displays KAT6-dependent H3K23 propionylation and overexpression of a set of active developmental genes
Smolko AE, Sullivan DW, Olsen SN et al. · Proceedings of the National Academy of Sciences of the United States of America 2024 · PMID 38889153 · doi:10.1073/pnas.2405905121
This dataset
Open GSE260638 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 GSE260638_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1082387 and SRA study SRP492698. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38889153) ↗
Study design
15 conditions, mostly in duplicate
MLL-AF9, mouse 1B, DMSO, ×3 MLL-AF9, mouse 1D, DMSO, ×3 MOZ-TIF2, mouse #1, DMSO, ×3 MOZ-TIF2, mouse #2553, DMSO, ×3 MOZ-TIF2, mouse #1, WM-1119 1 uM 1 hour, ×3 MOZ-TIF2, mouse #2553, WM-1119 1 uM 1 hour, ×3 FKBPV12-HA-MOZ-TIF2 LSK cells, control, ×2 FKBPV12-HA-MOZ-TIF2 LSK cells, 500 nM dTAG 2 … ×2 +11 more

Supports a case/control comparison: 6 samples read as cases, 20 as controls.

How we read this: 15 replicated groups read from 40 sample titles; they account for 36 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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