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首页> 外文期刊>IEEE/ACM transactions on computational biology and bioinformatics >Hidden Markov Modelling Reveals Neighborhood Dependence of Dnmt3a and 3b Activity
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Hidden Markov Modelling Reveals Neighborhood Dependence of Dnmt3a and 3b Activity

机译：隐藏的马尔可夫建模揭示了Dnmt3a和3b活动的邻域依赖性

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摘要

DNA methylation is an epigenetic mark whose important role in development has been widely recognized. This epigenetic modification results in heritable information not encoded by the DNA sequence. The underlying mechanisms controlling DNA methylation are only partly understood. Several 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 dependences. Furthermore, we investigate correlations between the neighborhood dependence and other genomic information. We perform numerical analysis of the HMMs applied to comprehensive hairpin and non-hairpin bisulfite sequencing measurements and accurately predict wild-type data. We find evidence that the activities of Dnmt3a and Dnmt3b responsible for de novo methylation depend on 5' (left) but not on 3' (right) neighboring CpGs in a sequencing string.
机译：DNA甲基化是一种表观遗传标记，其在发育中的重要作用已得到广泛认可。这种表观遗传修饰导致可遗传的信息没有被DNA序列编码。仅部分了解控制DNA甲基化的潜在机制。已经提出了几种负责DNA甲基化的酶活性的机理模型。在这里，我们通过描述随时间变化的空间甲基化模式的出现，扩展了现有的DNA甲基化隐马尔可夫模型（HMM），并提出了几种具有不同邻域依赖性的模型。此外，我们调查邻域依赖性和其他基因组信息之间的相关性。我们对应用于综合发夹和非发夹亚硫酸氢盐测序测量的HMM进行数值分析，并准确预测野生型数据。我们发现证据表明，负责从头甲基化的Dnmt3a和Dnmt3b的活性取决于5'（左），而不取决于3'（右）测序序列中的相邻CpG。

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