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Science AdvancesBiophysicsPeer-reviewed journal article

Gene-scale in vitro reconstitution reveals histone acetylation directly controls chromatin architecture

Yohsuke T. FukaiiD, Tomoya KujiraiiD, Masatoshi WakamoriiD, Setsuko Kanamura, Lisa Yamauchi, Somayeh Zeraati, Satoshi MoritaiD, Chiharu TanegashimaiD, Mitsutaka KadotaiD, Mikako ShirouzuiD, Hitoshi KurumizakaiD, Takashi UmeharaiD, Kyogo KawaguchiiD

PDFDOIPreprint

Abstract

Chromatin organization plays a crucial role in gene regulation [1, 2, 3], but disentangling the contributions of various epigenetic components to gene-scale chromatin structure remains challenging. While in vitro chromatin reconstitution enables controlled studies on the effect of bio-chemical factors on the structure, current methods are either limited to short arrays or lack control over histone modification patterns. Here we directly test how histone modification affects higher-order chromatin architecture by characterizing gene-scale reconstituted chromatin using single-molecule microscopy and in vitro Hi-C. We reconstitute 20-kilobase chromatin arrays with histone modification patterns controlled at 12-nucleosome resolution, achieving complete assembly of 96 nucleosomes in the designed order as confirmed by atomic force microscopy and longread sequencing. Observing end-to-end fluctuations of the reconstituted arrays, we find that increasing the density of acetylated nucleosomes leads to larger structural fluctuations with longer relaxation times, consistent with the predictions of a polymer model with hydrodynamic interactions. We demonstrate through in vitro Hi-C how acetylation reduces contact frequency between nucleosomes and induces open conformations. In heterogeneously modified arrays, differential contact probabilities between acetylated and unmodified regions lead to distinct structural domains. The results establish the physical principles by which histone modifications directly modulate chromatin architecture through altered nucleosome-nucleosome interactions, providing a quantitative framework for understanding and engineering genome organization.

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