In vitro binding energies capture Klf4 occupancy across the human genome

Transcription factors (TFs) regulate gene expression by binding to specific genomic loci determined by DNA sequence. Their sequence specificity is commonly summarized by a consensus binding motif. However, eukaryotic genomes contain billions of low-affinity DNA sequences to which TFs associate with a sequence-dependent binding energy. We currently lack insight into how the genomic sequence defines this spectrum of binding energies and the resulting pattern of TF localization. Here, we set out to obtain a quantitative understanding of sequence-dependent TF binding to both motif and nonmotif sequences. We achieve this by first pursuing accurate measurements of physical binding energies of human TF Krüppel-like factor 4 (Klf4) to a library of short DNA sequences in a fluorescence-anisotropy-based bulk competitive binding assay. Second, we show that the highly nonlinear sequence dependence of Klf4 binding energies can be captured by combining a linear model of binding energies with an Ising model of the coupled recognition of nucleotides by a TF. In this model, nucleotide-TF interfaces collectively switch between two states, weak binding and strong nucleotide-specific binding, and the states of neighboring interfaces are coupled with [Formula: see text]. We find that this statistical mechanics model parameterized by our in vitro measurements captures Klf4 binding patterns on an individual long DNA molecule stretched in the optical tweezer, and is predictive for Klf4 occupancy across the entire human genome without additional fit parameters.

Authors

Institutions

Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2026-10-26
DOI
https://doi.org/10.1073/pnas.2538133123
Primary Topic
Diffusion and Search Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In vitro binding energies capture Klf4 occupancy across the human genome

Anthony A. Hyman, Jonas Neipel, Yahor Savich, Frank Jülicher et al.
2 links
Proceedings of the National Academy of Sciences
Diffusion and Search Dynamics
article

In vitro binding energies capture Klf4 occupancy across the human genome

Anthony A. Hyman, Jonas Neipel, Yahor Savich, Frank Jülicher, Stephan W. Grill, Anne Schwager, Douglas Diehl
article en

Abstract

Transcription factors (TFs) regulate gene expression by binding to specific genomic loci determined by DNA sequence. Their sequence specificity is commonly summarized by a consensus binding motif. However, eukaryotic genomes contain billions of low-affinity DNA sequences to which TFs associate with a sequence-dependent binding energy. We currently lack insight into how the genomic sequence defines this spectrum of binding energies and the resulting pattern of TF localization. Here, we set out to obtain a quantitative understanding of sequence-dependent TF binding to both motif and nonmotif sequences. We achieve this by first pursuing accurate measurements of physical binding energies of human TF Krüppel-like factor 4 (Klf4) to a library of short DNA sequences in a fluorescence-anisotropy-based bulk competitive binding assay. Second, we show that the highly nonlinear sequence dependence of Klf4 binding energies can be captured by combining a linear model of binding energies with an Ising model of the coupled recognition of nucleotides by a TF. In this model, nucleotide-TF interfaces collectively switch between two states, weak binding and strong nucleotide-specific binding, and the states of neighboring interfaces are coupled with [Formula: see text]. We find that this statistical mechanics model parameterized by our in vitro measurements captures Klf4 binding patterns on an individual long DNA molecule stretched in the optical tweezer, and is predictive for Klf4 occupancy across the entire human genome without additional fit parameters.

Proceedings of the National Academy of SciencesVol. 123(44)
Max Planck Institute for the Physics of Complex Systems (DE), Center for Systems Biology Dresden (DE), Max Planck Institute of Molecular Cell Biology and Genetics (DE), Physics of Life (DE), Technische Universität Dresden (DE)
Openalex Percentile: Top 96%
Diffusion and Search Dynamics
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.

Laika access coming soon