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Collective unstructured interactions drive chromatin binding of transcription factors. [CUT&RUN]

GSE300854 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 40 samples Submitted 2026/03/20 Platform GPL34284
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 40 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
40 samples: 20 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
Unstructured transcription factor interactions enable emergent specificityScience (New York, N.Y.) · 2026
Summary (written by the submitters)
Eukaryotic transcription factors (TFs) contain both structured DNA-binding domains (DBDs) and intrinsically disordered regions (IDRs). While the structures and sequence preferences of DBDs have been extensively characterized, the role of IDR-mediated interactions in chromatin binding and nuclear organization remains poorly understood, in part because these interactions have been difficult to measure in living cells.
Read the full summary ↓
Here, we use a recently developed single-molecule technique, proximity-assisted photoactivation (PAPA), to investigate how IDRs influence TF associations with each other and with chromatin, focusing on the factors Sp1 and Klf1. We find that the number and patterning of aromatic and basic residues within IDRs govern both TF self-association and chromatin binding. Unexpectedly, the isolated DBD of Sp1 binds chromatin very weakly and non-specifically. The isolated IDR, by contrast, interacts poorly with chromatin-bound wild-type Sp1, yet this interaction is enhanced when even minimal DNA-binding capacity is restored. Strikingly, replacing Sp1's native DBD with those of heterologous TFs recovers both IDR-mediated interactions and chromatin association, despite divergent sequence preferences. PAPA measurements also reveal extensive heterotypic interactions between wild-type Sp1 and other TFs. Together, these results establish PAPA as a powerful method for studying unstructured interactions in their native context and suggest that IDRs participate in widespread cooperative associations scaffolded by transient DBD-DNA contacts, which concentrate disordered regions along chromatin. In contrast to classical models, we propose that TF specificity in vivo emerges not solely from DBD sequence preferences, but from a constellation of weak, dynamic, and diverse interactions mediated by IDRs.
Published in
Unstructured transcription factor interactions enable emergent specificity
Abidi AA, Cattoglio C, Tang NN et al. · Science (New York, N.Y.) 2026 · PMID 41855276 · doi:10.1126/science.aeb6487
This dataset
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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 GSE300854_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 PRJNA1282208 and SRA study SRP594632. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41855276) ↗
Study design
20 conditions, mostly in duplicate
Parental cell line, mouse anti-FLAG, ×2 Parental cell line, rabbit anti-FLAG, ×2 Parental cell line, rabbit anti-V5, ×2 Parental cell line, mouse anti-V5, ×2 Induced Sp1 mutant line, anti-FLAG, ×2 Induced wild type Sp1 line, anti-FLAG, ×2 Induced wild type Sp1 line, rabbit anti-V5, ×2 Induced wild type Sp1 line, mouse anti-V5, ×2 +12 more

Supports a case/control comparison: 24 samples read as cases, 8 as controls.

How we read this: 20 replicated groups read from 40 sample titles; they account for 40 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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