Euchromatin forms condensed domains with short active regions on the surface
Paggi, J. M.; Zhang, B.
Show abstract
Technological advances in chromatin structure characterization have continually refined our understanding of transcriptional regulation in eukaryotic systems. Despite these developments, achieving nucleosome-resolution structural characterization remains a significant challenge. As a result, it remains unclear what structural features distinguish active enhancers and promoters and how these elements are organized. To address this, we developed a simulation framework that leverages high-resolution Region-Capture Micro-C (RCMC) contact maps to infer conformational ensembles of megabase-scale chromatin segments at nucleosome resolution. A key component of this framework is a balancing strategy tailored for Micro-C data, which identifies per-nucleosome variation in contact density, in contrast to existing methods that assume uniform contact density. Our model accurately reproduces contact frequencies observed in RCMC data, pairwise spatial distances measured via chromatin tracing, and local structural motifs observed in imaging studies. The high spatial and genomic resolution of the inferred structures reveal a striking departure from the classical view of euchromatin as uniformly open. Instead, euchromatin generally folds into compact domains, consistent with the "packing domains" observed in imaging studies. These domains are further organized into disordered, insulated clusters of approximately 50 nucleosomes, resembling nucleosome clutches. Notably, kilobase-scale regions surrounding active promoters and enhancers often protrude from these condensed domains, becoming highly accessible. This spatial arrangement effectively compartmentalizes regulatory elements from the surrounding chromatin, facilitating protein binding and promoting enhancer-promoter communication. The distinct structural features of euchromatin revealed here offer new insights into enhancer regulation and may help explain their enigmatic behavior.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Developing a general AI model for integrating diverse genomic modalities and comprehensive genomic knowledge 96%
- Peripheral heterochromatin tethering is required for chromatin-based nuclear mechanical response 95%
- Shaping the Genome via Lengthwise Compaction, Phase Separation, and Lamina Adhesion 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.