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Abstract

Chromatin is a hierarchically structured fiber that regulates gene expression. Consisting of a complex network of DNA and proteins, chromatin is host to dynamic modes that facilitate genomic packaging. A comprehensive description of chromatin structure and dynamics is invaluable for a fundamental understanding of how inheritable genetic diseases originate. We now know that genetic diseases can result from epigenomic phenomena which alter the thermodynamics of the nucleosome, the fundamental unit of chromatin. Therefore, it is important to not only establish a physical description of the link between nucleosome physics and the structure of the chromatin fiber, but also the factors which alter said link. Within the last few decades, imaging and chromosome conformation capture techniques have revealed a number of structural and statistical features of the packaged chromatin fiber at a hitherto unavailable level of resolution. In this work, we deploy a comprehensive, multi-scale modeling approach to bridge the gap between chromatin structure length scales: from the nucleosome to the supramolecular chromatin fiber. We begin by quantifying the anisotropic interaction potential between nucleosomes to reconcile discrepancies in experimental endeavors. This nucleosome pair-interaction serves as the backbone for the development of a new coarse-grained model, known as the 1-Cylinder-Per-Nucleosome model (1CPN). Through free energy analysis of the 1CPN model, varying both linker DNA lengths and the linker histone, we determine that the level of description for mesoscopic structures of chromatin can be reduced to a three-nucleosome repeat unit. Through this result, we introduce a statistical framework to grow large chains of chromatin that we use to determine the correlation length, in kbp, of nucleosome-level dynamics. Lastly, we implement our findings into a machine vision workflow to determine the in situ structure of chromatin from ChromSTEM results. Taken together, this dissertation describes a comprehensive bottom-up modeling approach to chromatin structure that reveals unique motifs that arise from nucleosome-level physics

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