Tavares Rafael de Cesaris Araujo, Mahadeshwar Gandhar, Wan Han, Pyle Anna Marie
Department of Chemistry, Yale University, New Haven, CT, 06511, USA.
Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06511, USA.
bioRxiv. 2023 May 25:2023.05.25.542276. doi: 10.1101/2023.05.25.542276.
Chemical modifications are essential regulatory elements that modulate the behavior and function of cellular RNAs. Despite recent advances in sequencing-based RNA modification mapping, methods combining accuracy and speed are still lacking. Here, we introduce MRT- ModSeq for rapid, simultaneous detection of multiple RNA modifications using MarathonRT. MRT-ModSeq employs distinct divalent cofactors to generate 2-D mutational profiles that are highly dependent on nucleotide identity and modification type. As a proof of concept, we use the MRT fingerprints of well-studied rRNAs to implement a general workflow for detecting RNA modifications. MRT-ModSeq rapidly detects positions of diverse modifications across a RNA transcript, enabling assignment of m1acp3Y, m1A, m3U, m7G and 2'-OMe locations through mutation-rate filtering and machine learning. m1A sites in sparsely modified targets, such as MALAT1 and PRUNE1 could also be detected. MRT-ModSeq can be trained on natural and synthetic transcripts to expedite detection of diverse RNA modification subtypes across targets of interest.
化学修饰是调节细胞RNA行为和功能的重要调控元件。尽管基于测序的RNA修饰图谱绘制最近取得了进展，但仍缺乏兼具准确性和速度的方法。在此，我们介绍了MRT-ModSeq，它利用MarathonRT实现对多种RNA修饰的快速同步检测。MRT-ModSeq采用不同的二价辅因子生成二维突变图谱，该图谱高度依赖于核苷酸身份和修饰类型。作为概念验证，我们利用经过充分研究的rRNA的MRT指纹来实现检测RNA修饰的通用工作流程。MRT-ModSeq能快速检测RNA转录本上各种修饰的位置，通过突变率过滤和机器学习实现对m1acp3Y、m1A、m3U、m7G和2'-OMe位置的定位。在修饰较少的靶标（如MALAT1和PRUNE1）中的m1A位点也能被检测到。MRT-ModSeq可以在天然和合成转录本上进行训练，以加快对感兴趣靶标中不同RNA修饰亚型的检测。
