课题基金 / 基金详情

项目摘要

项目成果

Shenglong Zhang的其他基金

相似基金

相关文献

中文摘要
翻译
项目总结 一个具有各种不同修饰的RNA序列构成了RNA的“真实”信息内容。中的缺陷 RNA修饰可以解释100种人类疾病,如乳腺癌、2型糖尿病和肥胖症, 影响数以百万计的美国人。尽管它很重要,但RNA的真实序列,即身份和位置 全长RNA中的每个核苷酸组成单元(无论是否修改)仍然是一个谜,主要是 因为缺乏一种通用的方法来直接对任何核苷酸进行测序,特别是修饰的核苷酸 (包括未知的)在单核苷酸分辨率下。没有一种现有技术可以对所有修改进行排序 同时在大规模或转录水平上揭示真实的RNA序列。 使RNA修饰研究复杂化的是,已经发现了170种修饰类型,以及 并不是所有的核苷酸修饰都在其RNA位点被完全修饰为100%。他们扯平了 无法被基于NGS的技术检测到,这些技术需要将RNA转换为没有 修改信息。用于映射RNA修改的工具仅限于几个流行的修改,并且 通常一次只能分析一种修改类型。质谱学(MS)是目前唯一的技术 这可以表征所有的RNA修饰;然而,传统的MS方法丢失了关于 修饰核苷酸的定位和共生。 为了解决这些悬而未决的问题,我们最近开发了一系列新颖的下一代质量 基于光谱的测序(NextGen MassSpec-Seq)方法可以直接重新测序 不含cDNA的tRNAs,可以同时对所有的核苷酸修饰进行测序和量化。对于 在这项提议的持续时间内,我们将进一步开发下一代MassSpec-Seq以在 不同的蜂窝甚至疾病条件,使其可扩展到高吞吐量,并扩展其 应用程序同时对任何RNA类型上的所有修饰进行定量测序和映射 转录水平。具体地说,我们建议开发用于大规模全长从头测序的MS TRNAs与所有不同的核苷酸修饰(目标1)一起,使MS能够同时测序和 量化多个RNA修饰,允许在单核苷酸和化学计量学上进行定量测绘 Precision(目标2),扩展NextGen MassSpec-Seq,并将其与高通量NGS测序相结合,以实现 在转录水平上对不同的RNA修饰进行直接测序(目标3)。我们的工具将解决一个长期的- 如何揭示“真实”的RNA序列并为研究RNA提供一种变革性的工具 修饰,这将促进更好地理解转录后修饰的功能及其 与RNA相关疾病和大流行的相关性。
英文摘要
PROJECT SUMMARY An RNA sequence with all its diverse modifications constitutes ‘true’ information content of the RNA. Defects in RNA modifications account for >100 human diseases, such as breast cancer, type-2 diabetes and obesity, affecting millions of Americans. Despite its significance, the true sequence of a RNA, i.e., identity and location of each and every nucleotide building block (modified or not) within a full-length RNA, remains a mystery, mainly because of the lack of a general method to directly sequence any nucleotide, especially modified nucleotides (including unknown ones) at single-nucleotide resolution. No existing technology can sequence all modifications simultaneously to unfold the true RNA sequences at a large scale or the transcriptomic level. What complicates RNA modification studies is that >170 modification types have been discovered, and not all of nucleotide modifications are modified completely to 100% at their RNA sites. They are even undetectable by NGS-based technologies, which require the conversion of RNA to cDNAs that do not have any modification information. Tools to map RNA modifications are limited only to a few popular modifications, and can usually analyze only one modification type at a time. Mass spectrometry (MS) is currently the only technique that can characterize all RNA modifications; however, conventional MS methods lose information regarding the location and co-occurrence of modified nucleotides. To resolve these outstanding issues, we have recently developed a series of novel next generation mass spectrometry-based sequencing (NextGen MassSpec-Seq) approaches that can de novo directly sequence tRNAs without a cDNA and can sequence and quantify all nucleotide modifications simultaneously. For the duration of this proposal, we will further develop NextGen MassSpec-Seq to sequence tRNAs efficiently in different cellular and even disease conditions, make it scalable toward high throughput, and expand its application to simultaneously sequence and map all modifications quantitatively on any RNA type and at the transcriptomic level. Specifically, we propose to develop MS for large-scale de novo sequencing of full-length tRNAs, together with all diverse nucleotide modifications (Aim 1), empower MS to simultaneously sequence and quantify multiple RNA modifications, allowing quantitative mapping at single nucleotide and stoichiometric precision (Aim 2), scale up NextGen MassSpec-Seq and combine it with high-throughput NGS sequencing for direct sequencing of diverse RNA modifications at the transcriptomic level (Aim 3). Our tool will address a long- standing issue of how to reveal the ‘true” RNA sequences and provide a transformative tool for studying RNA modifications, which will promote better understanding of functions of post-transcriptional modifications and their correlations to RNA-related diseases and pandemics.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
LC/MS-Based Direct RNA Sequencing with Concomitant Capability to Sequence Multiple Base Modifications at Single-base Resolution
  • 批准号:
    10217648
  • 项目类别:
  • 资助金额:
    $35.0万
  • 财政年份:
    2020
  • 负责人:
    Shenglong Zhang
  • 依托单位:
海外基金