bioRxivGenomicsPreprint
Epigenome-informed Polymer Modeling Reveals Chromosome Folding Landscapes across Distinct Genetic and Epigenetic Contexts
Abstract
Three-dimensional (3D) genome organization is critical for gene regulation, enabling long-range interactions between genes and distal regulatory elements. Genomic structural variations and epigenetic differences can perturb this organization, contributing to phenotypic variation and tissue-specific gene regulation. Prior studies have assessed the impact of these genetic and epigenetic changes on 3D genome folding, primarily using population-averaged features such as topologically associating domains and loops. However, growing evidence from single-cell and live-imaging studies indicates that chromosomes are highly dynamic and exist as heterogeneous ensembles of conformations. Here, we applied an epigenetic-state-informed polymer modeling framework to generate chromosomal conformational ensembles directly from cell- and tissue-specific epigenomic data. The resulting ensembles reproduced experimental Hi-C maps across cell lines and tissue types. Comparison of these conformational ensembles revealed that, although polymer dynamics were conserved across cell lines, their folding landscapes diverged. These differences arose primarily from cell-line-specific chromatin-state interaction networks and were concentrated in rare, long-lived contacts. Furthermore, modeling a TAD-boundary-disrupting deletion without re-optimizing the model parameters indicated a shift in the chromatin conformational ensemble from predominantly insulated to predominantly fused states. The modeled deletion also selectively strengthened active chromatin contacts and differentially disrupted enhancer contacts involving neighboring genes. Finally, comparison of two tissue types from the same donor revealed epigenetically driven rewiring of chromatin-state interaction networks. These findings establish chromosomal conformational ensembles as a sensitive readout of genome reorganization across distinct genetic and epigenetic contexts.
- organism: human
- assay: Hi-C
- assay: DNA methylation
- research focus: chromatin & epigenetic regulation
- approach: deep learning
- approach: statistical model
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