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Revealing epigenetic patterns in gene regulation through integrative analysis of epigenetic interaction network

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Abstract

Chromatin components and DNA methylation play important roles in regulation of gene expression in mammalian genomes. However, the mechanism underlying how they regulate gene transcription, independently or synergistically, remains largely unknown. We constructed an epigenetic interaction network (EIN) of chromatin components, DNA methylation and gene expression by combining partial correlation coefficient with Pearson correlation coefficient. In EIN, we identified nine direct factors for gene expression. They constitute three interaction modules which synergistically affect gene expression. We introduced a new combination strategy to test how these direct factors in each module regulate gene expression synergistically. We found two inter-attracted patterns and one inter-repulsed patterns among the three modules. Furthermore, we identified 22 indirect factors for gene expression which have effect on gene expression via direct factors. DNA methylation, for example, could regulate gene expression through H3K4me3 and Pol II. Our approach has the potential to help in uncovering inherent relationships between epigenetic factors and gene transcription and guiding experiment.

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Abbreviations

EIN:

Epigenetic interaction network

HGPs:

High-expression gene promoters

LGPs:

Low-expression gene promoters

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Acknowledgments

We would like to thank Dr. Yaoping Lei and Jingyuan Fu for revising the manuscript. This work was supported in part by National Natural Science Foundation of China (61075023) and Natural Science Foundation of Heilongjiang Province (C201012).

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Authors and Affiliations

  1. Academy of Fundamental and Interdisciplinary Science, Harbin Institute of Technology, Harbin, 150080, China

    Jianzhong Su & Shengqiang Liu

  2. College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, China

    Jianzhong Su, Yunfeng Qi, Xueting Wu, Jie Lv, Hongbo Liu, Ruijie Zhang & Yan Zhang

  3. Department of Mathematics, Harbin Institute of Technology, Harbin, 150001, China

    Jianzhong Su

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  1. Jianzhong Su
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  2. Yunfeng Qi
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Electronic supplementary material

Below is the link to the electronic supplementary material.

11033_2011_910_MOESM1_ESM.doc

The relationship pairs between two regulators from the SET C with opposite signs of their Pearson correlation coefficient and partial correlation coefficient (doc 172 kb)

11033_2011_910_MOESM2_ESM.doc

Distribution of correlation coefficient value of all paired factors among 43 factors of SET C in 16 003 human gene promoters (doc 62 kb)

Indirect pathways of indirect factors to gene expression via direct factors from A1 to A22 (doc 1566 kb)

11033_2011_910_MOESM4_ESM.doc

Gene distribution and gene expression proportion of different combination patterns of the regulators in indirect pathway of indirect regulators respectively (doc 7056 kb)

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Su, J., Qi, Y., Liu, S. et al. Revealing epigenetic patterns in gene regulation through integrative analysis of epigenetic interaction network. Mol Biol Rep 39, 1701–1712 (2012). https://doi.org/10.1007/s11033-011-0910-3

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