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An analysis and prediction of nucleosome positioning based on information content

Chromosome Research volume 21, pages 63–74 (2013)Cite this article

Abstract

Nucleosome positioning plays a key role in the regulation of many biological processes. In this study, the statistical difference of information content was investigated in nucleosome and linker DNA regions across eukaryotic organisms. By analyzing the information redundancy, D k , in Saccharomyces cerevisiae, Drosophila melanogaster, and Caenorhabditis elegans genomes, the short-range dominance of nucleotide correlation in nucleosome and linker DNA regions was confirmed. Significant difference of the D k value between the nucleosome and linker DNA regions was also found. The underlying reason for many successful oligonucleotide-based predictions of nucleosome positioning in eukaryotic model organisms may be attributed to the short-range dominance of nucleotide correlation in the nucleosome and linker DNA regions. When applying power spectrum analysis to the nucleosome and linker DNA regions, some obvious differences in sequence periodic signals were observed. The parameter F k was introduced to describe particular base correlation. Furthermore, the support vector machine combining F k was used to classify nucleosome and linker DNA regions in Homo sapiens, Oryzias latipes, C. elegans, Candida albicans, and S. cerevisiae. Independent test demonstrated that a good performance can be achieved by using this algorithm. This result further revealed that base correlation information has an important role in nucleosome positioning.

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Abbreviations

MNase-chip:

Micrococcal nuclease coupled with microarrays

MNase-Seq:

Micrococcal nuclease coupled with sequencing techniques

SVM:

Support vector machine

FFT:

Fast Fourier transform

auROC:

Area under the ROC curve

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Acknowledgments

We would like to acknowledge HongYu Zhao and Xiangjun Cui for many helpful discussions. This work was supported by the Natural Science Foundation of China (61072129, 61271448, 61102162) and the Natural Science Foundation of Inner Mongolia (2011MS0504).

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Affiliations

  1. School of Physical Science and Technology, Inner Mongolia University, Hohhot, 010021, China

    Yong-qiang Xing

  2. School of Mathematics, Physics and Biological Engineering, Inner Mongolia University of Science and Technology, Baotou, 014010, China

    Yong-qiang Xing, Guo-qing Liu, Xiu-juan Zhao & Lu Cai

  3. Inner Mongolia Key Laboratory of Biomass-Energy Conversion, Baotou, 014010, China

    Lu Cai

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  1. Yong-qiang Xing
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  2. Guo-qing Liu
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  3. Xiu-juan Zhao
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  4. Lu Cai
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Correspondence to Lu Cai.

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Responsible Editor: Tatsuo Fukagawa.

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Xing, Yq., Liu, Gq., Zhao, Xj. et al. An analysis and prediction of nucleosome positioning based on information content. Chromosome Res 21, 63–74 (2013). https://doi.org/10.1007/s10577-013-9338-z

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  • DOI: https://doi.org/10.1007/s10577-013-9338-z

Keywords

  • Nucleosome positioning
  • Information content
  • Power spectrum analysis
  • Support vector machine