A Stochastic Model for the Formation of Spatial Methylation Patterns

A Stochastic Model for the Formation of Spatial Methylation Patterns
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空间甲基化模式形成的随机模型

DOI:
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发表时间:
2017
期刊:
Computational Methods in Systems Biology
影响因子:
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通讯作者:
V. Wolf
V. Wolf
中科院分区:
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文献类型:
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作者:
Alexander Lück;Pascal Giehr;J. Walter;V. Wolf

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DNA甲基化是一种表观遗传机制,其在发育中的重要作用已被广泛认识。这种表观遗传修饰导致了基因表达的可遗传变化,而不是DNA序列编码的。控制DNA甲基化的潜在机制还只有一部分人知道,最近已经提出了不同的DNA甲基化的酶活性机制模型。在这里,我们扩展了现有的隐马尔可夫模型(HMM),通过描述空间甲基化模式随时间的变化来描述DNA甲基化的发生,并提出了几个具有不同邻域依赖性的模型。我们对应用于亚硫酸盐测序测量的隐马尔可夫模型进行了数值分析,并准确地预测了野生型数据。此外,我们还发现了酶活性依赖于左侧5‘邻域而不是右侧3’邻域的证据。
DNA methylation is an epigenetic mechanism whose important role in development has been widely recognized. This epigenetic modification results in heritable changes in gene expression not encoded by the DNA sequence. The underlying mechanisms controlling DNA methylation are only partly understood and recently different mechanistic models of enzyme activities responsible for DNA methylation have been proposed. Here we extend existing Hidden Markov Models (HMMs) for DNA methylation by describing the occurrence of spatial methylation patterns over time and propose several models with different neighborhood dependencies. We perform numerical analysis of the HMMs applied to bisulfite sequencing measurements and accurately predict wild-type data. In addition, we find evidence that the enzymes' activities depend on the left 5' neighborhood but not on the right 3' neighborhood.
DOI: --
发表时间: 1990-02
期刊: Genetics
影响因子: 3.3
作者:
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