A high-throughput kit for detection of RNA modifications

用于检测 RNA 修饰的高通量试剂盒

基本信息

  • 批准号:
    8841998
  • 负责人:
  • 金额:
    $ 15万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-02-01 至 2016-01-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): The broad objective of this project is to develop an integrated wet-lab / dry-lab kit for high-throughput detection of RNA modifications. The final product will provide all required molecular biology reagents, a set of simple and robust experimental manipulations for facile analysis of modifications, and researcher-friendly analytic cloud-based software, requiring no special bioinformatics skills or computing hardware. Emerging data suggests that post-transcriptional modifications of many types of cellular RNA play an important and largely unexplored role in biology and in development and maintenance of the nervous system. In particular, a notable variety of neural diseases are due to specific defects in RNA modification, including autosomal recessive intellectual disability (ARID), non-syndromic X-linked mental retardation, myoclonus epilepsy ragged-red fibers (MERRF), mitochondrial encephalopathy lactic acidosis with stroke-like episodes (MELAS), and familial dysautonomia. Initial evidence for the links between RNA modification regulation and gene expression, mRNA splicing, nuclear export, and protein translation suggest much broader unknown effects given that modification states for most RNAs in most cell types are not well-defined. High-throughput RNA sequencing has revolutionized the study of gene expression, but it has not been widely applied to identifying most types of RNA modifications due to lack of methods for detection of modifications that are suitable for commercial use, and lack of methods for complex post-sequencing analytics. This Phase 1 proposal focuses on developing such methodology for three types of biologically relevant but relatively understudied RNA modifications, with the following Specific Aims: I. Develop methods for identifying RNA sites with m1A, m3C, or 2'-O-methylation. II. Develop an analysis pipeline to identify sites with 2'-O-methylation, m1A, or m3C. To achieve these aims, a novel biochemical approach will be employed for detecting and mapping 2'-O- methylation leveraging a known chemical reaction coupled with ligation methods to enrich for these sites. A distinct, novel approach will be applied to detect m1A, and m3C modifications, by differential analysis of reverse transcription between enzymatically treated samples. An integrated, cloud-based platform with custom analytic pipelines will be developed for processing and interpreting the RNA sequencing data to simplify complex analyses required to identify modifications with precision. Together, these all-inclusive kits will form both pre- and post-sequencing means for large-scale RNA modification detection with turn-key ease of use.
描述(由申请人提供):本项目的主要目标是开发一种用于高通量检测RNA修饰的集成湿实验室/干实验室试剂盒。最终产品将提供所有必需的分子生物学试剂,一套简单而强大的实验操作,用于轻松分析修改,以及研究人员友好的基于云的分析软件,不需要特殊的生物信息学技能或计算硬件。 新出现的数据表明,许多类型的细胞RNA的转录后修饰在生物学和神经系统的发育和维持中起着重要的和很大程度上未探索的作用。特别是,许多神经疾病是由于RNA修饰的特定缺陷引起的,包括常染色体隐性遗传性智力残疾(ARID)、非综合征性X连锁精神发育迟滞、肌阵挛癫痫破碎红纤维(MERRF)、线粒体脑病乳酸酸中毒伴中风样发作(MELAS)和家族性自主神经功能障碍。RNA修饰调控与基因表达、mRNA剪接、核输出和蛋白质翻译之间的联系的初步证据表明,鉴于大多数细胞类型中大多数RNA的修饰状态尚未明确定义,存在更广泛的未知效应。 高通量RNA测序已经彻底改变了基因表达的研究,但由于缺乏适合商业用途的修饰检测方法,以及缺乏复杂的测序后分析方法,它尚未广泛应用于鉴定大多数类型的RNA修饰。该第1阶段提案集中于开发用于三种类型的生物学相关但相对未充分研究的RNA修饰的此类方法,具有以下具体目的:I.开发用于识别具有m1A、m3 C或2 '-O-甲基化的RNA位点的方法。二.开发一个分析管道,以识别具有2 '-O-甲基化、m1A或m3 C的位点。 为了实现这些目标,将采用一种新的生物化学方法来检测和定位2 '-O-甲基化,利用已知的化学反应与连接方法结合来富集这些位点。将采用一种独特的、新颖的方法 通过酶处理样品之间逆转录的差异分析检测m1A和m3 C修饰。将开发一个具有定制分析管道的集成云平台,用于处理和解释RNA测序数据,以简化精确识别修饰所需的复杂分析。总之,这些全包式试剂盒将形成用于大规模RNA修饰检测的测序前和测序后手段,并具有交钥匙易用性。

项目成果

期刊论文数量(0)
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Patricia Chan其他文献

Patricia Chan的其他文献

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{{ truncateString('Patricia Chan', 18)}}的其他基金

Development of a Genotype-linked Antibiotic Resistance Platform for Real Time Pathogen Risk Classification and Epidemiology
开发用于实时病原体风险分类和流行病学的基因型相关抗生素耐药性平台
  • 批准号:
    9203025
  • 财政年份:
    2016
  • 资助金额:
    $ 15万
  • 项目类别:

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