Genome Sequencing by Natural DNA Synthesis on Amplified DNA Clones

通过对扩增的 DNA 克隆进行天然 DNA 合成进行基因组测序

基本信息

  • 批准号:
    7533414
  • 负责人:
  • 金额:
    $ 59.91万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2008
  • 资助国家:
    美国
  • 起止时间:
    2008-08-19 至 2012-05-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): We propose to combine the best proven aspects of SBS with streamlined methods for DNA amplification and high-speed fluorescence imaging to develop and implement a platform for rapid and inexpensive genome resequencing and de novo sequencing. Our platform is called "Natural Sequencing by Synthesis" (nSBS). Amplified DNA molecular clones will be sequenced in massive parallel by cyclic sequencing by synthesis using DNA polymerases and mostly natural nucleotides. The key is to use a small percentage of a cleavable fluorescently-labeled nucleotide along with the natural nucleotide in the cyclic base-by-base DNA sequencing by synthesis process for sequence detection. Not only will the fluorescently-labeled nucleotide incorporation be sparse but the fluorescent moiety will also be cleaved off after each imaging step. This will minimize the modification of the natural structure of the extending DNA template and ensure that DNA synthesis will not be significantly affected. With this strategy, homopolymer tracts can be sequenced and very long read lengths can be achieved. We present a concept for a new breakthrough technology called natural DNA sequencing by synthesis (nSBS). We also present several other breakthrough innovations: 1) In situ massive parallel amplification of single DNA molecules with micro fabricated arrays and rapid assembly of DNA templates. 2) The usage of an automaton to validate and optimize the new nSBS chemistry for cyclic sequencing by synthesis using DNA polymerases and commercially available nucleotides and nucleotides we will design and synthesize for efficient incorporation; 3) The decoupling of the reaction from detection to make the system scalable to very high-density arrays for whole genome sequencing. Since much higher density arrays can be used and only one enzyme (DNA polymerase) will be used, much less reagent will be needed. This will result in dramatic improvement of throughput and reduction in reagent cost. 4) The implementation of a double barrel paired-end strategy and new algorithms for de novo sequence assembly. In the long run this technology will have a great potential to enable very accurate re-sequencing and de novo sequencing of genomes at high speed and much lower cost for biomedical research and personalized medicine. PROJECT HEALTH RELEVANCE We propose to develop a breakthrough DNA sequencing technology called DNA sequencing by natural DNA synthesis (nSBS). We will combine streamlined methods for genome-scale DNA amplification with the new sequencing chemistry to engineer a sequencing platform for ultra-fast and low-cost human genome sequencing so that routine sequencing of individual human genomes can be performed for biomedical applications and personalized medicine.
描述(由申请人提供):我们建议将SBS的最佳验证方面与简化的DNA扩增和高速荧光成像方法相结合,以开发和实施快速和廉价的基因组重测序和从头测序平台。我们的平台被称为“自然合成测序”(nSBS)。扩增的DNA分子克隆将通过DNA聚合酶和大部分天然核苷酸合成的循环测序进行大量平行测序。关键是利用一小部分可切割荧光标记的核苷酸与天然核苷酸一起,通过合成过程进行环碱基对碱基DNA测序,以进行序列检测。不仅荧光标记的核苷酸结合是稀疏的,而且荧光部分也将在每个成像步骤后被切割掉。这将最大限度地减少对延伸DNA模板的自然结构的修改,并确保DNA合成不会受到显着影响。使用这种策略,可以对均聚物束进行测序,并且可以实现很长的读取长度。我们提出了一种新的突破性技术的概念,称为自然DNA合成测序(nSBS)。我们还提出了其他几项突破性创新:1)利用微阵列和DNA模板的快速组装来原位大规模平行扩增单个DNA分子。2)使用自动机来验证和优化新的nSBS化学,通过使用DNA聚合酶和市售核苷酸以及我们将设计和合成的核苷酸来进行循环测序;3)反应与检测解耦,使系统可扩展到非常高密度的全基因组测序阵列。由于可以使用更高密度的阵列,并且只使用一种酶(DNA聚合酶),因此所需的试剂要少得多。这将导致吞吐量的显著提高和试剂成本的降低。4)实现双筒对端策略和新的从头序列装配算法。从长远来看,这项技术将具有巨大的潜力,可以实现非常精确的基因组重测序和高速从头测序,并大大降低生物医学研究和个性化医疗的成本。我们建议开发一种突破性的DNA测序技术,称为自然DNA合成DNA测序(nSBS)。我们将把基因组级DNA扩增的简化方法与新的测序化学结合起来,设计出一个超快速、低成本的人类基因组测序平台,从而使个体人类基因组的常规测序可以用于生物医学应用和个性化医疗。

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)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

XIAOHUA HUANG其他文献

XIAOHUA HUANG的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('XIAOHUA HUANG', 18)}}的其他基金

Nanopore Direct Single-Molecule Protein Sequencing
纳米孔直接单分子蛋白质测序
  • 批准号:
    9751935
  • 财政年份:
    2018
  • 资助金额:
    $ 59.91万
  • 项目类别:
Nanopore Direct Single-Molecule Protein Sequencing
纳米孔直接单分子蛋白质测序
  • 批准号:
    9920763
  • 财政年份:
    2018
  • 资助金额:
    $ 59.91万
  • 项目类别:
Single-stranded sequencing using microfluidic reactors (SISSOR)
使用微流体反应器(SISSOR)进行单链测序
  • 批准号:
    9277501
  • 财政年份:
    2014
  • 资助金额:
    $ 59.91万
  • 项目类别:
Single-stranded sequencing using microfluidic reactors (SISSOR)
使用微流体反应器(SISSOR)进行单链测序
  • 批准号:
    8753802
  • 财政年份:
    2014
  • 资助金额:
    $ 59.91万
  • 项目类别:
Direct real-time single molecule DNA sequencing
直接实时单分子DNA测序
  • 批准号:
    8134459
  • 财政年份:
    2010
  • 资助金额:
    $ 59.91万
  • 项目类别:
Direct real-time single molecule DNA sequencing
直接实时单分子DNA测序
  • 批准号:
    8502023
  • 财政年份:
    2010
  • 资助金额:
    $ 59.91万
  • 项目类别:
Direct real-time single molecule DNA sequencing
直接实时单分子DNA测序
  • 批准号:
    7979700
  • 财政年份:
    2010
  • 资助金额:
    $ 59.91万
  • 项目类别:
Genome Sequencing by Natural DNA Synthesis on Amplified DNA Clones
通过对扩增的 DNA 克隆进行天然 DNA 合成进行基因组测序
  • 批准号:
    7923447
  • 财政年份:
    2009
  • 资助金额:
    $ 59.91万
  • 项目类别:
Genome Sequencing by Natural DNA Synthesis on Amplified DNA Clones
通过对扩增的 DNA 克隆进行天然 DNA 合成进行基因组测序
  • 批准号:
    8119145
  • 财政年份:
    2008
  • 资助金额:
    $ 59.91万
  • 项目类别:
Genome Sequencing by Natural DNA Synthesis on Amplified DNA Clones
通过对扩增的 DNA 克隆进行天然 DNA 合成进行基因组测序
  • 批准号:
    7676229
  • 财政年份:
    2008
  • 资助金额:
    $ 59.91万
  • 项目类别:

相似海外基金

DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Research Grant
CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 59.91万
  • 项目类别:
    Continuing Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了