Next-Generation Sequencing-Based RiboMethSeq Protocol for Analysis of tRNA 2'-O-Methylation.
Next-Generation Sequencing-Based RiboMethSeq Protocol for Analysis of tRNA 2'-O-Methylation.
复制标题
DOI：
10.3390/biom7010013
复制
发表时间：
2017-02-09
期刊：
影响因子：
5.5
通讯作者：
Motorin Y
中科院分区：
文献类型：
--
作者：
Marchand V;Pichot F;Thüring K;Ayadi L;Freund I;Dalpke A;Helm M;Motorin Y
通过传统的物理化学方法分析RNA修饰是劳动密集型的，需要大量的输入材料，并且只能逐点测量。近年来，基于下一代测序（NGS）的定性和定量方法的发展为分析各种细胞RNA物种开辟了新的视角。基于Illumina测序的RiboMethSeq方案最初被开发并成功应用于核糖体RNA (rRNA) 2 ' - o -甲基化的定位。该方法在不同物种和不同生长条件下的rRNA修饰的定量分析中也取得了很好的结果。然而，到目前为止，RiboMethSeq仅用于rRNA，整个测序和分析管道仅适用于这种长且相当保守的RNA物种。要深入了解RNA修饰功能，需要对其他重要的RNA物种，即转移RNA （trna）进行大规模和全局的分析数据集，众所周知，转移RNA含有多种功能重要的修饰残基。在这里，我们评估了RiboMethSeq方案在大肠杆菌和酿酒酵母中tRNA 2 ' - o -甲基化分析中的应用。经过对生物信息学管道的仔细优化，RiboMethSeq被证明适用于不同tRNA物种中已知修饰位置的甲基化率的相对定量。
Analysis of RNA modifications by traditional physico-chemical approaches is labor intensive, requires substantial amounts of input material and only allows site-by-site measurements. The recent development of qualitative and quantitative approaches based on next-generation sequencing (NGS) opens new perspectives for the analysis of various cellular RNA species. The Illumina sequencing-based RiboMethSeq protocol was initially developed and successfully applied for mapping of ribosomal RNA (rRNA) 2′-O-methylations. This method also gives excellent results in the quantitative analysis of rRNA modifications in different species and under varying growth conditions. However, until now, RiboMethSeq was only employed for rRNA, and the whole sequencing and analysis pipeline was only adapted to this long and rather conserved RNA species. A deep understanding of RNA modification functions requires large and global analysis datasets for other important RNA species, namely for transfer RNAs (tRNAs), which are well known to contain a great variety of functionally-important modified residues. Here, we evaluated the application of the RiboMethSeq protocol for the analysis of tRNA 2′-O-methylation in Escherichia coli and in Saccharomyces cerevisiae. After a careful optimization of the bioinformatic pipeline, RiboMethSeq proved to be suitable for relative quantification of methylation rates for known modified positions in different tRNA species.