Statistically robust methylation calling for whole-transcriptome bisulfite sequencing reveals distinct methylation patterns for mouse RNAs [mRNA bisulfite sequencing]. Mus musculus

(Cytosine-5) RNA methylation plays an important role in several biologically and pathologically relevant processes. However, owing to methodological limitations, the transcriptome-wide distribution of this mark has remained largely unknown. We have previously established RNA bisulfite sequencing as a method for the analysis of RNA (cytosine-5) methylation patterns at single-base resolution. Furthermore, next-generation sequencing has provided opportunities to establish transcriptome-wide maps of this modification. We have now established a computational approach that integrates tailored filtering and data-driven statistical modelling to eliminate many of the artifacts that are known to be associated with bisulfite sequencing. Using RNAs from mouse embryonic stem cells we have performed a comprehensive methylation analysis of mouse tRNAs, rRNAs and mRNAs. Our approach identified all known methylation marks in tRNA and two previously unknown but evolutionary conserved marks in 28S rRNA. Furthermore, the catalytic activities of the Dnmt2 tRNA methyltransferase could be resolved at single-base resolution. Of note, mRNAs were found to be very sparsely methylated or not methylated at all, which provides an important reference for further studies. Our approach can be used to profile (cytosine-5) RNA methylation patterns in many experimental contexts be important for understanding the function of (cytosine-5) RNA methylation in RNA biology and in human disease. Overall design: mRNA bisulfite sequencing of Tet1-/-,Tet2-/-,Tet3-/- embryonic stem cells were generated by deep sequencing, in triplicate, using Illumina

（胞嘧啶-5）RNA甲基化（(Cytosine-5) RNA methylation）在多种生物学及病理相关过程中发挥关键作用。然而受限于方法学瓶颈，该修饰在全转录组范围内的分布特征迄今仍未被充分探明。我们此前已建立RNA亚硫酸氢盐测序（RNA bisulfite sequencing）技术，可实现单碱基分辨率（single-base resolution）下的RNA（胞嘧啶-5）甲基化模式分析。此外，下一代测序（next-generation sequencing）技术为构建该修饰的全转录组图谱提供了可行途径。本研究现已开发一种整合定制化过滤与数据驱动统计建模的计算方法，可有效消除已知与亚硫酸氢盐测序相关的各类测序伪影（artifacts）。我们利用小鼠胚胎干细胞的RNA样品，对小鼠转运RNA（transfer RNA, tRNA）、核糖体RNA（ribosomal RNA, rRNA）及信使RNA（messenger RNA, mRNA）开展了全面的甲基化分析。本方法成功鉴定出tRNA中所有已知的甲基化修饰位点，并在28S rRNA中发现两处此前未被报道但进化保守的甲基化标记。此外，Dnmt2 tRNA甲基转移酶（Dnmt2 tRNA methyltransferase）的催化活性可通过本方法实现单碱基分辨率解析。值得注意的是，mRNA仅呈现极稀疏的甲基化修饰，或完全未发生甲基化，这为后续相关研究提供了重要参考依据。本方法可应用于多种实验场景下的（胞嘧啶-5）RNA甲基化模式分析，对阐明（胞嘧啶-5）RNA甲基化在RNA生物学及人类疾病中的功能具有重要意义。整体实验设计：对Tet1-/-、Tet2-/-、Tet3-/-小鼠胚胎干细胞开展mRNA亚硫酸氢盐测序，采用Illumina测序平台进行三次生物学重复的深度测序。