LC/MS-Based Direct RNA Sequencing with Concomitant Capability to Sequence Multiple Base Modifications at Single-base Resolution

基于 LC/MS 的直接 RNA 测序，同时能够以单碱基分辨率对多个碱基修饰进行测序

• 批准号: 10217648
• 负责人: Shenglong Zhang
• 金额: $ 35万
• 依托单位: NEW YORK INST OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-03 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10217648
• 关键词: 16S ribosomal RNA sequencing; Address; Affect; American; Communities; Complementary DNA; Complex; Databases; Development; Diabetes Mellitus; Disease; Disease model; Escherichia coli; Frequencies; Genetic Transcription; Goals; Gold; Health; High-Throughput RNA Sequencing; Human; Hydrophobicity; Knowledge; Label; Length; Link; Location; Mass Spectrum Analysis; Metabolic Diseases; Methods; Methylation; Modification; Mus; Non-Insulin-Dependent Diabetes Mellitus; Nucleotides; Obesity; Organism; Peptides; Performance; Phenylalanine-Specific tRNA; Population; Positioning Attribute; Post-Transcriptional RNA Processing; Protein Isoforms; Proteomics; RNA; RNA Sequences; Reading; Regulation; Research; Research Personnel; Resolution; Ribosomal RNA; Running; Sampling; Site; Tail; Techniques; Technology; Testing; Time; Tissues; Transcript; Transfer RNA; Variant; Work; Yeasts; automated algorithm; base; cell type; comparative; epitranscriptomics; experimental study; genome-wide; human disease; improved; in vivo; instrument; malignant breast neoplasm; nervous system disorder; nucleobase; reading difficulties; reconstruction; reference genome; tool; transcriptome; transcriptome sequencing; two-dimensional; 16S ribosomal RNA sequencing; Address; Affect; American; Communities; Complementary DNA; Complex; Databases; Development; Diabetes Mellitus; Disease; Disease model; Escherichia coli; Frequencies; Genetic Transcription; Goals; Gold; Health; High-Throughput RNA Sequencing; Human; Hydrophobicity; Knowledge; Label; Length; Link; Location; Mass Spectrum Analysis; Metabolic Diseases; Methods; Methylation; Modification; Mus; Non-Insulin-Dependent Diabetes Mellitus; Nucleotides; Obesity; Organism; Peptides; Performance; Phenylalanine-Specific tRNA; Population; Positioning Attribute; Post-Transcriptional RNA Processing; Protein Isoforms; Proteomics; RNA; RNA Sequences; Reading; Regulation; Research; Research Personnel; Resolution; Ribosomal RNA; Running; Sampling; Site; Tail; Techniques; Technology; Testing; Time; Tissues; Transcript; Transfer RNA; Variant; Work; Yeasts; automated algorithm; base; cell type; comparative; epitranscriptomics; experimental study; genome-wide; human disease; improved; in vivo; instrument; malignant breast neoplasm; nervous system disorder; nucleobase; reading difficulties; reconstruction; reference genome; tool; transcriptome; transcriptome sequencing; two-dimensional

Project Summary Aberrant RNA base modifications have been correlated with the development of major diseases including breast cancer, type-2 diabetes, obesity, and neurological disorders, each affecting millions of Americans. However, these modifications are undetectable by current high-throughput RNA sequencing technologies, which do not directly sequence RNAs, but instead sequence cDNAs that only contain the four canonical deoxynucleotides. Other tools to sequence nucleobase modifications in RNA are usually tailored for a single specific modified nucleotide and cannot provide single-base-resolution spatial information for modifications. Thus, very few of the over 160 identified RNA modifications have been studied. To better understand RNA with its rich modifications, we have been developing a mass spectrometry (MS)-based 2-dimensional hydrophobic end-labeling sequencing strategy (2-D HELS MS Seq) as: 1) a de novo and accurate method to directly sequence RNA and 2) a general method to sequence all base modifications in any RNA type at single-base resolution. The method can currently sequence purified or mixed samples of short synthetic RNAs and simultaneously identify, locate, and quantify the frequency of a specific modification in a population. In this proposal, we focus on improving read-length, throughput, and sensitivity to sequence rare RNA modifications, quantify post-transcriptional base modifications, and detect active isoforms of mixed cellular RNA samples. We propose to (a) de novo MS sequence specific and total cellular tRNA (<100 nt) as proof-of-concept examples (Aim 1), (b) de novo sequence complex endogenous RNA samples (up to 100 strands, 950 nt per run) (Aim 2), and (c) quantify genome wide post- transcriptional RNA modifications in metabolic disease models (Aim 3). This project is highly significant as successful accomplishment of the proposed work will 1) bring the power of MS-based laddering technology to RNA, thus providing a method comparable to analysis of peptide modifications in proteomics, that can reveal the identity and position of various RNA modifications, 2) allow direct and de novo RNA sequencing without cDNA synthesis, and 3) allow accurate reading of multiple base modifications at single nucleotide resolution in one experiment without prior knowledge of sequences and modifications, helping to address a long-standing unmet need in the broad field of epitranscriptomics. Our tool will promote better understanding of functions of post- transcriptional modifications and isoforms including their correlations to human diseases; we will develop the method into a gold standard for verifying other techniques for sequencing and annotating genome-wide base modifications, thereby helping to build more accurate and inclusive reference epitranscriptomic databases.

项目摘要 异常RNA碱的修饰与包括乳房在内的主要疾病的发展有关 癌症，2型糖尿病，肥胖和神经系统疾病，每种都会影响数百万美国人。然而， 当前的高通量RNA测序技术无法检测到这些修饰 直接序列RNA，而是仅包含四个规范脱氧核苷酸的序列cDNA。 通常针对单个特定的修饰来定制RNA中核苷酶修饰的其他工具 核苷酸，无法提供单基分辨率的空间信息进行修改。因此，很少 已经研究了超过160个已鉴定的RNA修饰。为了更好地理解RNA的丰富修改， 我们一直在开发质谱（MS）的二维疏水最终标记测序 策略（2-D HELS MS SEQ）AS：1）直接序列RNA和2）一般的从头和准确的方法 在单碱基分辨率下任何RNA类型中所有基本修饰的方法。该方法当前可以 序列纯化或混合样品的短合成RNA，同时识别，定位和量化 人群中特定修改的频率。在此建议中，我们专注于改善阅读长度， 吞吐量和对序列稀有RNA修饰的敏感性，量化转录后碱的修饰， 并检测混合细胞RNA样品的活性同工型。我们建议（a）从头序列特定 总细胞tRNA（<100 nt）作为概念验证示例（AIM 1），（b）从头序列复合物 内源性RNA样品（最多100股，每行950 nt）（AIM 2），（c）量化基因组宽后 - 代谢疾病模型中的转录RNA修饰（AIM 3）。这个项目非常重要，因为 拟议的工作的成功完成1）将基于MS的梯子技术的力量带到 RNA，因此提供了一种与蛋白质组学中肽修饰的分析相媲美的方法，可以揭示 各种RNA修饰的身份和位置，2）允许无cDNA的直接和DE从头和从头开始测序 合成，3）允许在一个单核苷酸分辨率下准确读取多个碱基修饰 实验没有序列和修改的先验知识，有助于解决长期的未安装 在表面参考组学的广泛领域需要。我们的工具将促进对邮政功能的更好理解 - 转录修饰和同工型，包括它们与人类疾病的相关性；我们将发展 将方法纳入金标准，用于验证其他技术用于测序和注释全基因组基础的技术 修改，从而有助于构建更准确和包容的参考表面参考数据库。