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Proceedings of the National Academy of Sciences of the United States of America
Sep 18, 2012;109 (38): E2514-22.

Sequence-based prediction of single nucleosome positioning and genome-wide nucleosome occupancy.

Thijn van der Heijden, Joke J F A van Vugt, Colin Logie, John van Noort
Author Information
  1. Thijn van der Heijden: Physics of Life Processes, Leiden University, Leiden, The Netherlands. Heijdent@physics.leidenuniv.nl
PMID: 22908247 DOI: 10.1073/pnas.1205659109

Abstract

Nucleosome positioning dictates eukaryotic DNA compaction and access. To predict nucleosome positions in a statistical mechanics model, we exploited the knowledge that nucleosomes favor DNA sequences with specific periodically occurring dinucleotides. Our model is the first to capture both dyad position within a few base pairs, and free binding energy within 2 k(B)T, for all the known nucleosome positioning sequences. By applying Percus's equation to the derived energy landscape, we isolate sequence effects on genome-wide nucleosome occupancy from other factors that may influence nucleosome positioning. For both in vitro and in vivo systems, three parameters suffice to predict nucleosome occupancy with correlation coefficients of respectively 0.74 and 0.66. As predicted, we find the largest deviations in vivo around transcription start sites. This relatively simple algorithm can be used to guide future studies on the influence of DNA sequence on chromatin organization.

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MeSH Term

Algorithms
Animals
Chickens
Chromatin
Chromatin Assembly and Disassembly
Computational Biology
DNA
Erythrocytes
Genome, Fungal
Histones
Models, Statistical
Nucleosomes
Nucleotides
Probability
Saccharomyces cerevisiae
Sequence Analysis, DNA
Thermodynamics
Transcription Initiation Site
Transcription, Genetic

Chemicals

Chromatin
Histones
Nucleosomes
Nucleotides
DNA
Journal Article
Article has an altmetric score of 12

Word Cloud

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