High-throughput detection of transcriptomic and epitranscriptomic variation and kinetics using MarathonRT

项目摘要 一种高效超进行性逆转录酶的发现及其特性 (MarathonRT)现在使开发高通量方法以实现准确的端到端成为可能 结束长RNA转录本的测序，从而保留替代方案的信息内容 在保留位置连接信息的同时拼接、编辑和修饰异构体， 从而使人们能够区分复杂混合物中的RNA异构体，而不需要映射到 参考基因组。这种类型的技术对于破译POST的作用至关重要 发育阶段、细胞和组织控制过程中的转录RNA加工事件 高等生物中基因表达的特异性和调控。它必须足够 高效和准确地为用于单次测序的长读测序方法提供动力 细胞RNAseq，特别是当转录多样化作为时间的函数被监测时。这个 该提案的前两个目标集中在高通量检测RNA修饰上 (如2-O-甲基和N7-甲基鸟苷)。在第一个目标中，一个独特的马拉松RT 引物延伸协议将与经过训练的突变图谱算法相结合，以 识别特定RNA修饰的位置和化学特性，报告 在长阅读测序过程中能够以高吞吐量识别的修饰签名 (捷运-莫德塞克)。在第二个目标中，MRT-ModSeq将在未知的RNA上进行测试，在那里它 将用于预测具有挑战性的长转录本上的修改位置以及 这些预测将直接使用质谱学进行评估。后半部分 提案的重点是确定Long上链接的替代剪接和编辑站点 复杂细胞混合物中的转录本。在AIM 3中，马拉松RT将被合并到一个 用于准确分析高度丰富和处理多样性的 复杂的麻痹(Para)基因，它编码100多万个可能的加工变体， 其中的子集对于钠通道的电压选通是必不可少的。这为我们搭建了舞台 对于目标4，其中工作流程的敏感度必须进一步优化并与数据合并 适用于时间分辨单细胞应用的分析策略。产生的方法将 通过监测细胞应激诱导的全长转录信号进行测试。

Project Summary The discovery and characterization of an efficient, ultraprocessive reverse transcriptase (MarathonRT) now makes it possible to develop high-throughput methods for accurate end-to- end sequencing of long RNA transcripts, thereby preserving information content on alternative splicing, editing and modification isoforms while conserving positional linkage information, thereby enabling one to distinguish RNA isoforms in complex mixtures without mapping to a reference genome. This type of technology is essential for deciphering the role of post- transcriptional RNA processing events during control of developmental stage, cell and tissue specificity and regulation of gene expression in higher organisms. It must be sufficiently efficient and accurate to power the long-read sequencing approaches that are used in single- cell RNAseq, particularly when transcript diversification is monitored as a function of time. The first two aims of the proposal are focused on high-throughput detection of RNA modifications (such as 2-O-methyl groups and N7-methyl guanosines). In the first aim, a unique MarathonRT primer extension protocol will be combined with a trained mutational profiling algorithm to recognize the positions and chemical identities of specific RNA modifications, reporting a modification signature that can be recognized at high throughput during long-read sequencing (MRT-ModSeq). In the second aim, MRT-ModSeq will be tested on unknown RNAs, where it will be used to predict sites of modifications on challenging long transcripts and robustness of the predictions will be directly evaluated using mass spectrometry. The second half of the proposal is focused on identification of linked alternative splicing and editing sites on long transcripts within complex cellular mixtures. In aim 3, MarathonRT will be incorporated into a workflow for accurately profiling the relative abundance and processing diversity of the highly complex paralytic (para) gene, which encodes more than 1 million possible processing variants, a subset of which are essential for the voltage-gating of a sodium channel. This sets the stage for Aim 4, in which sensitivity of the workflow must be further optimized and merged with data analysis strategies suitable for time-resolved single cell applications. The resulting method will be tested by monitoring full-length transcriptomic signatures induced by cell stress.