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DOT1L provides transcriptional memory through PRC1.1 antagonism [RNA-seq]

GSE260456 Mus musculus (mouse) RNA-seq (gene expression) 180 samples Submitted 2025/11/23 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 180 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
180 samples: 58 conditions, mostly in triplicateGroups 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
Low-loss hollow-core silica/air photonic bandgap fibreNature · 2003
Summary (written by the submitters)
DOT1L and Menin are essential cofactors for the oncogenic activity of MLL-fusion proteins (MLL-FPs) in leukaemia. However, the mechanisms underpinning the therapeutic effects of their inhibitors remain unclear. Here, we identify a critical role for the non-canonical Polycomb repressive complex 1.1 (PRC1.1) in mediating the cellular responses to DOT1L and Menin inhibitors.
Read the full summary ↓
Menin inhibition induces PRC1.1-dependent deposition of H2AK119ub to silence a subset of MLL-FP targets, whereas DOT1L inhibition results in a genome-wide increase in H2AK119ub. We show that enhanced PRC1.1 activity arises specifically from the progressive loss of DOT1L-mediated H3K79 methylation, independent of MLL-FP displacement or transcriptional repression. This regulatory crosstalk is conserved across cell types and is driven by direct biochemical antagonism between H3K79 methylation and PRC1.1 activity. Together, our findings establish DOT1L as a component of transcriptional memory co-opted in leukaemia and suggest it serves as the missing link balancing the opposing forces of the MLL-Polycomb system.
Published in
Low-loss hollow-core silica/air photonic bandgap fibre
Smith CM, Venkataraman N, Gallagher MT et al. · Nature 2003 · PMID 12904788 · doi:10.1038/nature01849
This dataset
Open GSE260456 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 GSE260456_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 PRJNA1081797 and SRA study SRP492287. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 12904788) ↗
Study design
58 conditions, mostly in triplicate
HUDEP-2 Control - DMSO ×4 HUDEP-2 Control - SGC0946 5uM ×4 K562 Control - DMSO ×4 K562 Control - SGC0946 5uM ×4 ESC Control - DMSO ×4 ESC Control - SGC0946 5uM ×4 NTVKO PCGF1 KO DMSO ×3 NTVKO PCGF1 KO SGC0946 3uM ×3 +50 more

Supports a between-group comparison across 180 samples.

How we read this: 58 replicated groups read from 180 sample titles; they account for 180 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

+ 140 more — browse all 180 samples with per-sample file links →

Datasets on a similar topic

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