4.8 Article

Toward a unified physical model of nucleosome patterns flanking transcription start sites

出版社

NATL ACAD SCIENCES
DOI: 10.1073/pnas.1214048110

关键词

nucleosome maps; chromatin structure; quantitative biology

资金

  1. Bavarian Center for Molecular Biosystems
  2. German Excellence Initiative
  3. Deutsche Forschungsgemeinschaft [SFB 1032]
  4. Leopoldina Postdoctoral Scholarship

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Recent genome-wide maps of nucleosome positions in different eukaryotes revealed patterns around transcription start sites featuring a nucleosome-free region flanked by a periodic modulation of the nucleosome density. For Saccharomyces cerevisiae, the average in vivo pattern was previously shown to be quantitatively described by a nucleosome gas model based on the statistical positioning mechanism. However, this simple physical description is challenged by the fact that the pattern differs quantitatively between species and by recent experiments that appear incompatible with statistical positioning, indicating important roles for chromatin remodelers. We undertake a data-driven search for a unified physical model to describe the nucleosome patterns of 12 yeast species and also consider an extension of the model to capture remodeling effects. We are led to a nucleosome gas that takes into account nucleosome breathing, i.e., transient unwrapping of nucleosomal DNA segments. This known biophysical property of nucleosomes rationalizes a pressure-induced dependence of the effective nucleosome size that is suggested by the data. By fitting this model to the data, we find an average energy cost for DNA unwrapping consistent with previous biophysical experiments. Although the available data are not sufficient to reconstruct chromatin remodeling mechanisms, a minimal model extension by one mechanism yields an active nucleosome gas that can rationalize the behavior of systems with reduced histone-DNA ratio and remodeler knockouts. We therefore establish a basis for a physical description of nucleosome patterns that can serve as a null model for sequence-specific effects at individual genes and in models of transcription regulation.

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