Sequence features accurately predict genome-wide MeCP2 binding in vivo

H. Tomas Rube; Wooje Lee; Miroslav Hejna; Huaiyang Chen; Dag H. Yasui; John F. Hess; Janine M. Lasalle; Jun S. Song; Qizhi Gong

doi:10.1038/ncomms11025

Sequence features accurately predict genome-wide MeCP2 binding in vivo

H. Tomas Rube, Wooje Lee, Miroslav Hejna, Huaiyang Chen, Dag H. Yasui, John F. Hess, Janine M. Lasalle, Jun S. Song, Qizhi Gong

Research output: Contribution to journal › Article › peer-review

Abstract

Methyl-CpG binding protein 2 (MeCP2) is critical for proper brain development and expressed at near-histone levels in neurons, but the mechanism of its genomic localization remains poorly understood. Using high-resolution MeCP2-binding data, we show that DNA sequence features alone can predict binding with 88% accuracy. Integrating MeCP2 binding and DNA methylation in a probabilistic graphical model, we demonstrate that previously reported genome-wide association with methylation is in part due to MeCP2"™ s affinity to GC-rich chromatin, a result replicated using published data. Furthermore, MeCP2 co-localizes with nucleosomes. Finally, MeCP2 binding downstream of promoters correlates with increased expression in Mecp2-deficient neurons.

Original language	English (US)
Article number	11025
Journal	Nature communications
Volume	7
DOIs	https://doi.org/10.1038/ncomms11025
State	Published - Mar 24 2016

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

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10.1038/ncomms11025

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abstract = "Methyl-CpG binding protein 2 (MeCP2) is critical for proper brain development and expressed at near-histone levels in neurons, but the mechanism of its genomic localization remains poorly understood. Using high-resolution MeCP2-binding data, we show that DNA sequence features alone can predict binding with 88% accuracy. Integrating MeCP2 binding and DNA methylation in a probabilistic graphical model, we demonstrate that previously reported genome-wide association with methylation is in part due to MeCP2{"}{\texttrademark} s affinity to GC-rich chromatin, a result replicated using published data. Furthermore, MeCP2 co-localizes with nucleosomes. Finally, MeCP2 binding downstream of promoters correlates with increased expression in Mecp2-deficient neurons.",

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T1 - Sequence features accurately predict genome-wide MeCP2 binding in vivo

AU - Rube, H. Tomas

AU - Lee, Wooje

AU - Hejna, Miroslav

AU - Chen, Huaiyang

AU - Yasui, Dag H.

AU - Hess, John F.

AU - Lasalle, Janine M.

AU - Song, Jun S.

AU - Gong, Qizhi

PY - 2016/3/24

Y1 - 2016/3/24

N2 - Methyl-CpG binding protein 2 (MeCP2) is critical for proper brain development and expressed at near-histone levels in neurons, but the mechanism of its genomic localization remains poorly understood. Using high-resolution MeCP2-binding data, we show that DNA sequence features alone can predict binding with 88% accuracy. Integrating MeCP2 binding and DNA methylation in a probabilistic graphical model, we demonstrate that previously reported genome-wide association with methylation is in part due to MeCP2"™ s affinity to GC-rich chromatin, a result replicated using published data. Furthermore, MeCP2 co-localizes with nucleosomes. Finally, MeCP2 binding downstream of promoters correlates with increased expression in Mecp2-deficient neurons.

AB - Methyl-CpG binding protein 2 (MeCP2) is critical for proper brain development and expressed at near-histone levels in neurons, but the mechanism of its genomic localization remains poorly understood. Using high-resolution MeCP2-binding data, we show that DNA sequence features alone can predict binding with 88% accuracy. Integrating MeCP2 binding and DNA methylation in a probabilistic graphical model, we demonstrate that previously reported genome-wide association with methylation is in part due to MeCP2"™ s affinity to GC-rich chromatin, a result replicated using published data. Furthermore, MeCP2 co-localizes with nucleosomes. Finally, MeCP2 binding downstream of promoters correlates with increased expression in Mecp2-deficient neurons.

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Sequence features accurately predict genome-wide MeCP2 binding in vivo

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