Basic Forestry and Proteomics Research Center, College of Life Science, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
Basic Forestry and Proteomics Research Center, College of Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
Genome Biol. 2021 Jan 7;22(1):22. doi: 10.1186/s13059-020-02241-7.
There are no comprehensive methods to identify N-methyladenosine (mA) at single-base resolution for every single transcript, which is necessary for the estimation of mA abundance. We develop a new pipeline called Nanom6A for the identification and quantification of mA modification at single-base resolution using Nanopore direct RNA sequencing based on an XGBoost model. We validate our method using methylated RNA immunoprecipitation sequencing (MeRIP-Seq) and mA-sensitive RNA-endoribonuclease-facilitated sequencing (m6A-REF-seq), confirming high accuracy. Using this method, we provide a transcriptome-wide quantification of mA modification in stem-differentiating xylem and reveal that different alternative polyadenylation (APA) usage shows a different ratio of mA.
目前还没有全面的方法能够在单个转录本水平上识别 N6-甲基腺嘌呤(m6A),而这对于 m6A 丰度的估计是必要的。我们开发了一种新的称为 Nanom6A 的方法,用于使用基于纳米孔直接 RNA 测序的 XGBoost 模型在单个碱基分辨率上识别和定量 m6A 修饰。我们使用甲基化 RNA 免疫沉淀测序(MeRIP-Seq)和 m6A 敏感的 RNA 内切核酸酶辅助测序(m6A-REF-seq)验证了我们的方法,确认了高准确性。使用这种方法,我们提供了茎分化木质部中 m6A 修饰的全转录组定量,并揭示了不同的可变多聚腺苷酸化(APA)使用显示出不同的 m6A 比率。