GEO series

The Splicing Factor PTBP1 Interacts with RUNX1 and is Required for Leukemia Cell Survival [CUT&Tag]

GSE308248 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 13 samples Submitted 2025/11/11 Platform GPL21697

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 13 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: 13 samples: 13 samples, each with a distinct title — no replicated groupsGroups 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: The splicing factor PTBP1 interacts with RUNX1 and is required for leukemia cell survivalLeukemia · 2026

Summary (written by the submitters)

Runt-related Transcription Factor 1 (RUNX1) is essential for definitive hematopoiesis and is among the most frequently mutated genes in leukemia. Previous work from our lab demonstrated that Histone Deacetylase 1 (HDAC1), a known RUNX1 partner, is unexpectedly required for active transcription suggesting a non-histone role for HDAC1 regulating components of the RUNX1 complex.

Read the full summary ↓

Here, we use proteomics, genomics, and long-read transcriptomics to identify novel RUNX1 interacting partners and decipher their role in gene regulation and RNA splicing in leukemia cells. We demonstrate that Polypyrimidine Tract Binding Protein 1 (PTBP1) interacts with RUNX1 in an HDAC1-dependent manner. Chromatin profiling revealed extensive genome-wide overlap in sites occupied by RUNX1 and PTBP1, with significant enrichment at promoters of actively transcribed genes. Loss of PTBP1 in AML cells led to widespread alterations in RNA splicing and decreased expression of genes whose promoters are bound by both factors, including metabolic genes. In agreement with these findings, we found that loss of PTBP1 reduced glycolysis and glucose uptake and ultimately caused cell death. Based on our data, we propose that the interaction between RUNX1 and PTBP1 facilitates expression of metabolic proteins essential for leukemia cell growth and survival.

Published in

The splicing factor PTBP1 interacts with RUNX1 and is required for leukemia cell survival

Dhir A, Ethell A, Watkins R et al. · Leukemia 2026 · PMID 41214140 · doi:10.1038/s41375-025-02799-w

This dataset

Open GSE308248 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 GSE308248_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 PRJNA1329290 and SRA study SRP620846. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41214140) ↗

Study design

13 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 13 sample titles: 13 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

GSM9240917 MOLM-13, PTBP1, biol rep 1 (CUT&Tag)
GSM9240918 MOLM-13, PTBP1, biol rep 2 (CUT&Tag)
GSM9240919 MOLM-13, RUNX1, biol rep 1 (CUT&Tag)
GSM9240920 MOLM-13, RUNX1, biol rep 2 (CUT&Tag)
GSM9240921 MOLM-13, IgG (CUT&Tag)
GSM9240922 MOLM-13, PTBP1, biol rep 1 (CUT&Run)
GSM9240923 MOLM-13, PTBP1, biol rep 2 (CUT&Run)
GSM9240924 MOLM-13, IgG, biol rep 1 (CUT&Run)
GSM9240925 MOLM-13, IgG, biol rep 2 (CUT&Run)
GSM9240926 MOLM-13, H3K27me3, biol rep 1 (CUT&Run)
GSM9240927 MOLM-13, H3K27me3, biol rep 2 (CUT&Run)
GSM9240928 MOLM-13, RUNX1, biol rep 1 (CUT&Run)
GSM9240929 MOLM-13, RUNX1, biol rep 2 (CUT&Run)

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