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

使用 MarathonRT 高通量检测转录组和表观转录组变异和动力学

• 批准号: 10276105
• 负责人: Brenton R. Graveley
• 金额: $ 100.51万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-17 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10276105
• 关键词: Algorithms; Alternative Splicing; Catalytic RNA; Cell Cycle Kinetics; Cell physiology; Cells; Cellular Stress; Chemicals; Chromatin; Complementary DNA; Complex; Complex Mixtures; DNA; DNA Damage; Data Analyses; Dependence; Detection; Development; Digestion; Disease; Doxorubicin; Drosophila genus; Event; Evolution; Gene Expression; Gene Expression Regulation; Genes; Guanosine; Health; Heat-Shock Response; Human; Individual; Ions; Kinetics; Label; Length; Life; Link; Mass Spectrum Analysis; Medicine; Messenger RNA; Metabolic; Metals; Methodology; Methods; Modeling; Modification; Monitor; Mutation; Nucleotides; Organism; Paralysed; Pathway interactions; Play; Population; Population Heterogeneity; Positioning Attribute; Post-Transcriptional RNA Processing; Primer Extension; Principal Investigator; Process; Protein Isoforms; Protocols documentation; Pseudouridine; RNA; RNA chemical synthesis; RNA-Directed DNA Polymerase; RNase P; Repetitive Sequence; Reporting; Role; Sampling; Site; Sodium Channel; Specificity; Structure; System; Technology; Testing; Thiouridine; Time; Tissues; Training; Transcript; Transfer RNA; Translations; Validation; Variant; cDNA Library; cofactor; computational suite; epitranscriptomics; implementation facilitation; indexing; interest; machine learning algorithm; methyl group; nuclease; performance tests; preservation; programs; reference genome; sequencing platform; single-cell RNA sequencing; transcriptome; transcriptome sequencing; transcriptomics; viral RNA; voltage

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.

项目摘要 有效的超级处理逆转录酶的发现和表征 （Marathonrt）现在可以开发高通量方法，以端对到准确 长RNA转录本的结束测序，从而保留有关替代方案的信息内容 在保护位置链接信息的同时，拼接，编辑和修改同工型， 从而使人们能够在复杂混合物中区分RNA同工型，而无需映射到 参考基因组。这种类型的技术对于破译后的作用至关重要。 在控制发育阶段，细胞和组织控制过程中的转录RNA处理事件 较高生物体中基因表达的特异性和调节。它必须足够 有效且准确，为单一使用的长阅读测序方法供电 细胞RNASEQ，尤其是当转录物多样化作为时间的函数监测时。这 该提案的前两个目标集中于对RNA修饰的高通量检测 （例如2-O-甲基基和N7甲基鸟嘌呤）。在第一个目标中，一个独特的马拉松 引物扩展方案将与受过训练的突变分析算法结合使用 识别特定RNA修饰的位置和化学身份，报告 在长阅读测序期间，可以在高吞吐量上识别的修改签名 （MRT-MODSEQ）。在第二个目标中，将在未知的RNA上测试MRT-Modseq 将用于预测有关挑战长的成绩单和鲁棒性的修改位点 预测将使用质谱直接评估。后半部分 提案的重点是识别长时间的链接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，Marathonrt将纳入 工作流程，以准确分析高度的相对丰度和处理多样性 复杂的瘫痪（Para）基因编码超过100万个可能的处理变体， 其中的子集对于钠通道的电压门控至关重要。这设定了舞台 对于AIM 4，必须进一步优化工作流的灵敏度并与数据合并 分析策略适用于时间分辨的单细胞应用。结果方法将 通过监测细胞应激诱导的全长转录组特征来测试。