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和鉴定 （MarathonRT）现在可以开发高通量方法，用于精确的端到端检测。 长RNA转录物的末端测序，从而保留替代RNA转录物上的信息内容。 剪接、编辑和修饰同种型，同时保留位置连锁信息， 从而使人们能够区分复杂混合物中的RNA同种型，而不需要映射到 参考基因组。这种类型的技术是必不可少的破译后的作用- 在发育阶段、细胞和组织控制期间的转录RNA加工事件 高等生物基因表达的特异性和调控。概念必须是十分 高效且准确地为单次测序中使用的长读序测序方法提供动力， 细胞RNAseq，特别是当监测转录物多样化作为时间的函数时。的 该提案的前两个目标集中在RNA修饰的高通量检测上 (such作为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 引物延伸方案将与经训练的突变谱分析算法组合， 识别特定RNA修饰的位置和化学身份，报告 可以在长读序测序期间以高通量识别的修饰特征 （MRT-ModSeq）。在第二个目标中，MRT-ModSeq将在未知RNA上进行测试，其中它 将用于预测挑战性长转录本上的修饰位点和 将使用质谱法直接评估预测。下半年 一项提案的重点是确定长链可变剪接和编辑位点， 复杂细胞混合物中的转录物。在目标3中，MarathonRT将被纳入一个 工作流程，以准确地剖析相对丰度和加工多样性的高度 复杂麻痹（帕拉）基因，编码超过100万种可能的加工变体， 其中的一个亚类对于钠通道的电压门控是必需的。这就为 对于目标4，必须进一步优化工作流程的灵敏度并将其与数据合并 适用于时间分辨单细胞应用的分析策略。所得到的方法将 通过监测由细胞应激诱导的全长转录组签名来测试。

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.