DNA-guided transcription factor interactions extend human gene regulatory code

In the same way that the mRNA-binding specificities of transfer RNAs define the genetic code, the DNA-binding specificities of transcription factors (TFs) form the molecular basis of the gene regulatory code<sup>1,2</sup>. The human gene regulatory code is much more complex than the genetic code, in particular because there are more than 1,600 TFs that commonly interact with each other. TF-TF interactions are required for specifying cell fate and executing cell-type-specific transcriptional programs. Despite this, the landscape of interactions between DNA-bound TFs is poorly defined. Here we map the biochemical interactions between DNA-bound TFs using CAP-SELEX, a method that can simultaneously identify individual TF binding preferences, TF-TF interactions and the DNA sequences that are bound by the interacting complexes. A screen of more than 58,000 TF-TF pairs identified 2,198 interacting TF pairs, 1,329 of which preferentially bound to their motifs arranged in a distinct spacing and/or orientation. We also discovered 1,131 TF-TF composite motifs that were markedly different from the motifs of the individual TFs. In total, we estimate that the screen identified between 18% and 47% of all human TF-TF motifs. The novel composite motifs we found were enriched in cell-type-specific elements, active in vivo and more likely to be formed between developmentally co-expressed TFs. Furthermore, TFs that define embryonic axes commonly interacted with different TFs and bound to distinct motifs, explaining how TFs with a similar specificity can define distinct cell types along developmental axes.

Authors

Institutions

Publication Details

Journal
Nature
Published
2025-04-09
DOI
https://doi.org/10.1038/s41586-025-08844-z
Citations
34
Primary Topic
Genomics and Chromatin Dynamics
Type
article
Field-Weighted Citation Impact
27.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DNA-guided transcription factor interactions extend human gene regulatory code

Yimeng Yin, Evgeny Z. Kvon, Sarah Amalia Teichmann, Ilya L. Sokolov et al.
34 citations
Nature
Genomics and Chromatin Dynamics
27.40
article

DNA-guided transcription factor interactions extend human gene regulatory code

Yimeng Yin, Evgeny Z. Kvon, Sarah Amalia Teichmann, Ilya L. Sokolov, Jussi Taipale, J. Patrick Pett, Ekaterina Morgunova, Grace Bower, Zhiyuan Xie, Yue Xue, Yinan Chen, Ayşe Derya Cavga, А. Н. Попов, Maria Osmala, Kai Wang
article en
34 citations

Abstract

In the same way that the mRNA-binding specificities of transfer RNAs define the genetic code, the DNA-binding specificities of transcription factors (TFs) form the molecular basis of the gene regulatory code<sup>1,2</sup>. The human gene regulatory code is much more complex than the genetic code, in particular because there are more than 1,600 TFs that commonly interact with each other. TF-TF interactions are required for specifying cell fate and executing cell-type-specific transcriptional programs. Despite this, the landscape of interactions between DNA-bound TFs is poorly defined. Here we map the biochemical interactions between DNA-bound TFs using CAP-SELEX, a method that can simultaneously identify individual TF binding preferences, TF-TF interactions and the DNA sequences that are bound by the interacting complexes. A screen of more than 58,000 TF-TF pairs identified 2,198 interacting TF pairs, 1,329 of which preferentially bound to their motifs arranged in a distinct spacing and/or orientation. We also discovered 1,131 TF-TF composite motifs that were markedly different from the motifs of the individual TFs. In total, we estimate that the screen identified between 18% and 47% of all human TF-TF motifs. The novel composite motifs we found were enriched in cell-type-specific elements, active in vivo and more likely to be formed between developmentally co-expressed TFs. Furthermore, TFs that define embryonic axes commonly interacted with different TFs and bound to distinct motifs, explaining how TFs with a similar specificity can define distinct cell types along developmental axes.

NatureVol. 641(8065)
Tongji University (CN), University of Helsinki (FI), University of California, Irvine (US), Wellcome/MRC Cambridge Stem Cell Institute (GB), University of Cambridge (GB), European Synchrotron Radiation Facility (FR), Wellcome Sanger Institute (GB), Karolinska Institutet (SE), Wihuri Research Institute (FI), Shanghai East Hospital (CN), Genomics (United Kingdom) (GB), State Key Laboratory of Cardiovascular Disease
Openalex Percentile: Top 0%
Genomics and Chromatin Dynamics
27.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.