A logic-circuit framework for mapping long-range interaction networks to 3D chromatin conformations

Area of Science:

• Genomics and Bioinformatics
• Computational Biology
• Biophysics

Background:

• Eukaryotic genomes form complex 3D structures via long-range DNA interactions.
• Interpreting how multiple interactions shape overall chromatin conformation remains a challenge.
• Existing models struggle to link local interaction motifs to global conformational readouts.

Purpose of the Study:

• To develop a physics-grounded framework for analyzing 3D genome organization.
• To represent complex chromatin interactions as a circuit network.
• To connect local interaction topology to measurable conformational statistics.

Main Methods:

• Utilized a minimal harmonic polymer model and Gaussian covariance formalism.
• Developed a 3D genome circuit representation to map effective interaction strength (EIS).
• Analyzed motif-level interaction patterns and their contribution to EIS.
• Derived analytical methods to quantify coordinated proximity changes between DNA loci.

Main Results:

• Introduced a circuit representation where graph topology dictates circuit operations.
• Connected EIS to experimental statistics like contact probabilities and loop stability.
• Quantified enhancer-promoter proximity coordination and estimated Shh-ZRS interaction strength.
• Provided a method to analyze effects of perturbations like anchor deletion or tether addition.

Conclusions:

• The motif-level circuit representation offers physics-grounded design rules for 3D genome interpretation.
• This framework elucidates how local DNA loop topology influences global chromatin conformation.
• Enables quantitative analysis of how interaction strength and perturbations affect genome organization.