Genomic regions adopt heritable epigenetic states with unique histone modifications, resulting in bistable gene expression without changes to the underlying DNA sequence. The significance of chromatin conformational dynamics to epigenetic stability is not well understood. We introduce a kinetic model to simulate the dynamic fluctuation of histone modifications. The model explicitly incorporates the impact of chemical modifications on chromatin stability as well as the contribution of chromatin contacts to the cooperativity of chemical reactions. Leveraging the model's computational efficiency, we study the disparate time scales of chromatin relaxation and epigenetic spread to account for the recent discovery of both liquid and gel-like properties of chromatin. Strikingly different results were obtained for the steady state and kinetic behavior of histone modification patterns in fast and slow chromatin structural relaxation regimes. Our study suggests that the timescale of chromatin conformational dynamics maybe an important axis that biology fine tunes to regulate epigenetic stability.
Genome-wide chromosome conformation capture (Hi-C) experiments have revealed many structural features of chromatin across multiple length scales. Further understanding genome organization requires relating these discoveries to the mechanisms that establish chromatin structures and reconstructing these structures in three dimensions, but both objectives are difficult to achieve with existing algorithms that are often computationally expensive. To alleviate this challenge, we present an algorithm that efficiently converts Hi-C data into contact energies, which measure the interaction strength between genomic loci brought into proximity. Contact energies are local quantities unaffected by the topological constraints that correlate Hi-C contact probabilities. Thus, extracting contact energies from Hi-C contact probabilities distills the biologically unique information contained in the data. We show that contact energies reveal the location of chromatin loop anchors, support a phase separation mechanism for genome compartmentalization, and parameterize polymer simulations that predict three-dimensional chromatin structures. Therefore, we anticipate that contact energy extraction will unleash the full potential of Hi-C data and that our inversion algorithm will facilitate the widespread adoption of contact energy analysis.
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