School of Plant Sciences and Food Security, Tel Aviv University, Haim Levanon, Tel Aviv, Israel.
Genome Biol. 2020 Aug 6;21(1):194. doi: 10.1186/s13059-020-02099-9.
Cytosine methylome data is commonly generated through next-generation sequencing, with analyses averaging methylation states of individual reads. We propose an alternative method of analysing single-read methylome data. Using this method, we identify patterns relating to the mechanism of two plant non-CG-methylating enzymes, CMT2 and DRM2. CMT2-methylated regions show higher stochasticity, while DRM2-methylated regions have higher variation among cells. Based on these patterns, we develop a classifier that predicts enzyme activity in different species and tissues. To facilitate further single-read analyses, we develop a genome browser, SRBrowse, optimised for visualising and analysing sequencing data at single-read resolution.
胞嘧啶甲基化组数据通常通过下一代测序生成，分析方法平均化了各个读取的甲基化状态。我们提出了一种分析单读甲基化组数据的替代方法。使用这种方法，我们确定了与两种植物非 CG 甲基化酶 CMT2 和 DRM2 的作用机制相关的模式。CMT2 甲基化区域显示出更高的随机性，而 DRM2 甲基化区域在细胞间具有更高的变异性。基于这些模式，我们开发了一种可以预测不同物种和组织中酶活性的分类器。为了促进进一步的单读分析，我们开发了一个基因组浏览器 SRBrowse，优化了用于在单读分辨率下可视化和分析测序数据。
