T7 RNA polymerase engineering and RNA amplification

T7 RNA 聚合酶工程和 RNA 扩增

基本信息

  • 批准号:
    7502612
  • 负责人:
  • 金额:
    $ 67.66万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2004
  • 资助国家:
    美国
  • 起止时间:
    2004-08-01 至 2010-08-31
  • 项目状态:
    已结题

项目摘要

Expanding use of microarray systems for global gene expression profiling is leading biological research, providing diagnostic and prognostic value to physicians and facilitating target discovery during drug and vaccine development. There is strong interest in extending this microarray capability to more RNA-limited material to the point that a single cell can be profiled with confidence. The most widely used method for preparing samples for microarray analysis, which uses cDNA synthesis from mRNA followed by T7 RNA polymerase-based amplification, currently lacks the necessary sensitivity to meet these emerging needs. To overcome these methodological limitations, we propose to increase the final amplified RNA yield by 1) improving the efficiency of T7 RNA polymerase using structure-based engineering with directed evolution of function, 2) by optimizing the design of the promoter-template construct for specific amplification needs and 3) by re-standardization of cDNA synthesis for lower RNA inputs. The combined improvements are expected to lower the cell-limited RNA sample requirement by 100-fold compared to current, commercially available kits. This will enable microarray gene analysis with as little as 1 ng of total RNA with a single round of amplification or microarray profiling from a single cell (-10 pg of total RNA) after two rounds of amplification.
微阵列系统在全球基因表达谱分析中的广泛应用正在引领生物学研究,

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Andrew D Ellington其他文献

Endowing cells with logic and memory
赋予细胞逻辑和记忆
  • DOI:
    10.1038/nbt.2573
  • 发表时间:
    2013-05-08
  • 期刊:
  • 影响因子:
    41.700
  • 作者:
    Andre C Maranhao;Andrew D Ellington
  • 通讯作者:
    Andrew D Ellington
Overview of Receptors from Combinatorial Nucleic Acid and Protein Libraries
组合核酸和蛋白质文库的受体概述
Back to the future of nucleic acid self-amplification
回到核酸自扩增的未来
  • DOI:
    10.1038/nchembio0409-200
  • 发表时间:
    2009-04-01
  • 期刊:
  • 影响因子:
    13.700
  • 作者:
    Andrew D Ellington
  • 通讯作者:
    Andrew D Ellington
Molecular evolution picks up the PACE
分子进化加快了步伐
  • DOI:
    10.1038/nbt.1884
  • 发表时间:
    2011-06-07
  • 期刊:
  • 影响因子:
    41.700
  • 作者:
    Adam J Meyer;Andrew D Ellington
  • 通讯作者:
    Andrew D Ellington

Andrew D Ellington的其他文献

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{{ truncateString('Andrew D Ellington', 18)}}的其他基金

Directed evolution of broadly fungible biosensors
广泛可替代生物传感器的定向进化
  • 批准号:
    10587024
  • 财政年份:
    2023
  • 资助金额:
    $ 67.66万
  • 项目类别:
Directed evolution of polymerases that can read and write extremely long sequences
聚合酶的定向进化可以读取和写入极长的序列
  • 批准号:
    10170542
  • 财政年份:
    2020
  • 资助金额:
    $ 67.66万
  • 项目类别:
Directed evolution of polymerases that can read and write extremely long sequences
聚合酶的定向进化可以读取和写入极长的序列
  • 批准号:
    10548111
  • 财政年份:
    2020
  • 资助金额:
    $ 67.66万
  • 项目类别:
Directed evolution of polymerases that can read and write extremely long sequences
聚合酶的定向进化可以读取和写入极长的序列
  • 批准号:
    9885765
  • 财政年份:
    2020
  • 资助金额:
    $ 67.66万
  • 项目类别:
Synthetic biology for the chemogenetic manipulation of pain pathways
用于疼痛通路化学遗传学操纵的合成生物学
  • 批准号:
    10017883
  • 财政年份:
    2019
  • 资助金额:
    $ 67.66万
  • 项目类别:
Synthetic biology for controlled release
控制释放的合成生物学
  • 批准号:
    9926117
  • 财政年份:
    2019
  • 资助金额:
    $ 67.66万
  • 项目类别:
Synthetic biology for the chemogenetic manipulation of pain pathways
用于疼痛通路化学遗传学操纵的合成生物学
  • 批准号:
    9895148
  • 财政年份:
    2019
  • 资助金额:
    $ 67.66万
  • 项目类别:
Synthetic biology for controlled release
控制释放的合成生物学
  • 批准号:
    10376300
  • 财政年份:
    2019
  • 资助金额:
    $ 67.66万
  • 项目类别:
Synthetic biology for controlled release
控制释放的合成生物学
  • 批准号:
    10113359
  • 财政年份:
    2019
  • 资助金额:
    $ 67.66万
  • 项目类别:
A robust ionotropic activator for brain-wide manipulation of neuronal function
一种强大的离子型激活剂,用于全脑操纵神经元功能
  • 批准号:
    9145668
  • 财政年份:
    2015
  • 资助金额:
    $ 67.66万
  • 项目类别:

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