Platform for transcriptome-wide RNA modification identification in long reads

长读段中全转录组 RNA 修饰识别平台

• 批准号: 10335266
• 负责人: Alison Tang
• 金额: $ 0.44万
• 依托单位: UNIVERSITY OF CALIFORNIA SANTA CRUZ
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-24 至 2022-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10335266
• 关键词: Address; Adenosine; Affect; Alternative Splicing; Amino Acids; Atlases; Base Sequence; Benchmarking; Biology; Blood; Brain; Brain Diseases; Breast; Cell Line; Cells; Characteristics; Chimeric Proteins; Codon Nucleotides; Complementary DNA; Computational Biology; Computational algorithm; Computer software; Computing Methodologies; Data; Data Analyses; Data Set; Databases; Detection; Disease; Disease Progression; Doctor of Philosophy; Enzymes; Exons; Functional disorder; Guanosine; Human; Inosine; Label; Learning; Length; Link; Literature; Lung; Lung Adenocarcinoma; Malignant Neoplasms; Maps; Measures; Mediating; Messenger RNA; Methods; Modeling; Modification; Motor Neurons; Neurons; Normal tissue morphology; Nucleotides; Pattern; Permeability; Poly(A) Tail; Polyadenylation; Polymerase; Positioning Attribute; Property; Protein Isoforms; RNA; RNA Editing; RNA Processing; RNA Splicing; Regulation; Research Personnel; Reverse Transcriptase Polymerase Chain Reaction; Role; Science; Signal Transduction; Site; Structure; System; Techniques; Testing; Time; Tissue atlas; Tissues; Training; Transcript; Work; adenosine deaminase; base; base editing; career; computer framework; computerized tools; cost; cost effective; functional outcomes; human tissue; insight; knock-down; mRNA Precursor; machine learning method; nanopore; neuron loss; skills; software development; success; tool; transcriptome; transcriptome sequencing

Project Summary RNA modifications are pervasive throughout the human transcriptome and affect transcript stability, localization, and function. In particular, ADAR-mediated adenosine-to-inosine (A-to-I) edits in RNA have been shown to affect pre-mRNA splicing and alter codon sequence. Amino acid changes caused by inosines have been implicated in various deleterious conditions, which include cancer and diseases of the brain. However, previous literature mapping inosine positions in high-throughput were only able to do so inside the limited context provided by short RNA-Seq reads. As modifications can be transcript-specific, elucidating the association of inosines with full mRNA isoforms is crucial for a more rigorous understanding of the role of inosine modifications in the tissues of our body and, more broadly, disease. Therefore, I propose to investiate A-to-I editing in the context of diseased and non-diseased systems using full-length mRNA nanopore sequencing. The nanopore is able to sequence whole RNA strands by converting changes in electrical current caused by RNA translocating through the pore into nucleotide sequence. ​Aim 1 leverages high-accuracy nanopore cDNA sequencing of cellular systems with and without ADAR knockdown to interrogate ADAR function and A-to-I-induced changes to transcript expression changes. To accomplish the latter, I will develop workflows to determine isoform structure from noisy, long reads. In addition to sequencing full-length transcripts, nanopore native RNA (nvRNA) sequencing informs on RNA modifications, as modified nucleotides appear as subtle alteration in current signal with respect to canonical nucleotides. As such, ​Aim 2 ​employs a generalizable approach to producing cost-effective training data for systematically understanding how inosines alter current signals in nanopores. I will use a Cas13b-ADAR fusion protein (REPAIRv2) to create site-specific edits and then perform nvRNA sequencing on the edited transcriptome. Site-specific A-to-I editing allows this approach to create a labelled inosine dataset in nvRNA signal from which I can develop computational algorithms to reliably identify inosines in nvRNA data. The REPAIRv2 approach to can be generalized to eventually identify any RNA modification with nanopores. ​Aim 3 will elucidate how A-to-I editing differs between tissues. I will sequence 4 normal tissue types with nvRNA sequencing, generating a map of A-to-I edits in conjunction with isoform usage using the software I am developing. Taken together, the fulfillment of these aims will not only provide further insights on elusive ADAR mechanism, but also create workflows for nanopore data analysis and a platform for the study of any modification. As I work toward my Ph.D. with this interdisciplinary project, I will gain invaluable skills in experimental and computational biology that will prepare me for a career in science.

项目概要 RNA 修饰普遍存在于整个人类转录组中并影响转录稳定性， 定位和功能。特别是，ADAR 介导的 RNA 中的腺苷到肌苷 (A-to-I) 编辑已被证实 显示出影响前 mRNA 剪接并改变密码子序列。肌苷引起的氨基酸变化 与各种有害疾病有关，其中包括癌症和脑部疾病。然而， 以前的文献在高通量中绘制肌苷位置只能在有限的范围内完成 由短 RNA-Seq 读取提供的上下文。由于修饰可以是转录本特异性的，因此阐明了 肌苷与完整 mRNA 亚型的关联对于更严格地理解肌苷的作用至关重要 肌苷对我们身体组织的改变，更广泛地说，对疾病的改变。因此我建议调查 使用全长 mRNA 纳米孔在患病和非患病系统中进行 A-to-I 编辑 测序。纳米孔能够通过转换电流的变化来对整个 RNA 链进行测序 由RNA通过孔转位至核苷酸序列引起。​目标 1 利用高精度 对有或没有 ADAR 敲低的细胞系统进行纳米孔 cDNA 测序以询问 ADAR 功能和 A 到 I 诱导的转录表达变化。为了实现后者，我将开发 从嘈杂的长读取中确定异构体结构的工作流程。除了全长测序外 转录本、纳米孔天然 RNA (nvRNA) 测序可提供 RNA 修饰（如修饰核苷酸）的信息 表现为当前信号相对于规范核苷酸的细微改变。因此，​目标 2​采用了 生成具有成本效益的培训数据的通用方法，用于系统地了解肌苷如何 改变纳米孔中的电流信号。我将使用 Cas13b-ADAR 融合蛋白 (REPAIRv2) 来创建位点特异性 编辑，然后对编辑后的转录组进行 nvRNA 测序。特定于站点的 A 到 I 编辑允许这样做 在 nvRNA 信号中创建标记肌苷数据集的方法，我可以从中开发计算 可靠识别 nvRNA 数据中肌苷的算法。 REPAIRv2 方法可以推广到 最终识别出任何带有纳米孔的 RNA 修饰。​目标 3 将阐明 A 到 I 编辑的不同之处 组织之间。我将使用 nvRNA 测序对 4 种正常组织类型进行测序，生成 A 到 I 的图谱 使用我正在开发的软件结合异构体的使用进行编辑。综合起来，实现 这些目标不仅将为难以捉摸的 ADAR 机制提供进一步的见解，而且还将创建工作流程 纳米孔数据分析和任何修饰研究的平台。当我努力攻读博士学位时。与这个 跨学科项目，我将获得实验和计算生物学方面的宝贵技能，为 我从事科学事业。