A Unified Computational Framework for Modeling Genome-wide Nucleosome Landscape

Nucleosomes form the fundamental building blocks of eukaryotic chromatin. The precise role of DNA sequence in governing the genome-wide distribution of nucleosomes has been controversial. We develop a unified computational framework, based on the statistical mechanics model of one-dimensional hard rods and the cross-entropy method for optimization, for simultaneously learning nucleosome number and nucleosome-positioning energy from genome-wide nucleosome maps. In contrast to other previous studies, our model can predict both in-vitro and in-vivo nucleosome maps in S. cerevisiae. We rigorously quantify the contribution of hitherto-debated sequence features, including G+C content, 10.5-bp periodicity, and poly(dA:dT) tracts, to three distinct aspects of genome-wide nucleosome landscape: occupancy, translational and rotational positioning. Applying our method to in-vivo nucleosome maps further demonstrates that, for a subset of genes, the regularly-spaced nucleosome arrays observed around transcription start sites can be partially recapitulated by DNA sequence alone. Finally, in-vivo nucleosome occupancy derived from MNase-seq experiments around transcription termination sites can be mostly explained by the genomic sequence. [BIORXIV/2017/202580]