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Structural and functional basis of PU.1-BAF interaction enables targeting of lineage-specific transcription [RNA-seq]

GSE304680 Homo sapiens (human) RNA-seq (gene expression) 25 samples Submitted 2025/08/07 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 25 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
Homo sapiens (human)
Samples
25 samples: 8 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.
Summary (written by the submitters)
Transcription factors (TFs) regulate gene expression by engaging chromatin remodeling complexes, yet the structural principles governing these critical interactions remain poorly defined. Here, we uncover the molecular mechanism by which lineage-specific pioneer transcription factor PU.1 (encoded by SPI1) directly engages the BAF (mSWI/SNF) chromatin remodeling complex.
Read the full summary ↓
First, using a variety of genomic approaches, we establish that BAF collaborates with PU.1 to regulate transcription in AML cells. Then, using a combination of biochemistry and biophysics, mass spectrometry-based protein footprinting, and crystallography, we map the PU.1-BAF60A interface to a disordered region of PU.1 that adopts a helical conformation upon binding to the YEATS-like domain of BAF60A. Disruption of this functionally critical interface via knockdown abrogates the ability of PU.1 to rescue cell viability. Finally, we conducted a high-throughput screen that yielded small molecules which selectively bind BAF60A and disrupt PU.1 binding. Co-crystal structures reveal distinct compound binding modes that converge on a critical PU.1-BAF60A interaction hotspot. These findings define, for the first time, the structural interface between a pioneer transcription factor and the BAF complex and establish a platform that enables targeting transcription factor-chromatin remodeling complex interactions in cancer.
This dataset
Open GSE304680 in finder → Find more human 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 GSE304680_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 PRJNA1302316 and SRA study SRP607148. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
MV411,DMSO,24h,RNAseq,biol ×3 MV411,FHT1015,24h,RNAseq,biol ×3 THP1,DMSO,24h,RNAseq,biol ×3 THP1,Compound49,24h,RNAseq,biol ×3 MV411,PU1,NTC,NoDox,RNAseq,biol ×3 MV411,PU1,shRNA1,Dox,RNAseq,biol ×3 MV411,PU1,shRNA2,Dox,RNAseq,biol ×3 MV411,PU1,shRNA3,Dox,RNAseq,biol ×3 +1 more

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 25 sample titles; they account for 24 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
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