Establishing and benchmarking advanced methods to comprehensively characterize somatic genome variation in single human cells

建立先进方法并对其进行基准测试,以全面表征单个人类细胞的体细胞基因组变异

基本信息

  • 批准号:
    10880109
  • 负责人:
  • 金额:
    $ 17.48万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-09-01 至 2024-03-31
  • 项目状态:
    已结题

项目摘要

Abstract Understanding somatic genomic variation presents unique challenges, primarily stemming from the individual rarity of most somatic mutations across cells in a multicellular organism. Hence, both sensitivity and accuracy (due to the need to distinguish somatic variation from noise) become crucially important. The Analysis of bulk DNA, even with ultraprecise approaches, only ascertains a portion of the human genome. The analysis of single cells, either by cloning or in vitro whole- genome amplification (WGA), enables discovering theoretically all mutations in a cell independent of their frequency in bulk. However, amplifying single cell genomes in vitro represents still a significant challenge in terms of accuracy of amplification. The novel PTA technique (primary template directed amplification) offers substantially improved quality of amplified DNA. However, PTA produces a relatively small amount of DNA fragments of moderate length. This limits the application of long read sequencing. Long read sequencing is expected to be the most comprehensive approach to somatic mutation detection. In the parent award project, we will, first, produce clonally expanded iPSC lines from several different tissues of a live donor, to study somatic mutation of all types using non-enzymatically amplified genomic DNA. Second, we will address a significant shortcoming of the analysis of single cell genomes, which is the lack of direct information about the exact type of cell being analyzed, or about potential functional consequences of mutations in that cell. For that, we will benchmark the new ResolveOme method, that can analyze in parallel the genome and transcriptome of a single cell. Third, we will address the challenge of high-throughput analysis of single cells to detect somatic structural variants. Specifically, we will establish and benchmark for SMaHT the Strand-seq method that allows for high-throughput detection and characterization of structural variants (SVs) in single cells. Together, this will address 3 critical needs in the analysis of somatic mutations in normal tissues: comprehensive mosaic mutation discovery, phenotyping the cell harboring mutations and directly assessing functional consequences of mutations, and accurate and high-throughput detection of SVs. For this Supplement project, we will grow up an already-existing fibroblast line from a live donor, as well as five already existing clonally expanded iPSC lines derived from that fibroblast line. We will distribute cells from these lines to the GCCs of the SMaHT consortium, to be deep-sequenced for the purpose of benchmarking on a resource for which already pre-validated somatic variants at known tissue allele frequencies exist.
摘要 了解体细胞基因组变异提出了独特的挑战,主要源于 在多细胞生物体中,大多数体细胞突变的个体罕见性。因此,我们认为, 灵敏度和准确度(由于需要区分体细胞变异和噪声)都变得 至关重要。对大量DNA的分析,即使使用超精确的方法,也只能得到 人类基因组的一部分。单细胞分析,无论是通过克隆还是体外全细胞分析, 基因组扩增(WGA),理论上能够独立地发现细胞中的所有突变 大量的频率。然而,在体外扩增单细胞基因组仍然是一个很好的方法。 在放大精度方面存在重大挑战。新型PTA技术(主要 模板定向扩增)提供了扩增DNA的显著改善的质量。然而,在这方面, PTA产生相对少量的中等长度的DNA片段。这限制了 长读序测序的应用。长读段测序有望成为 体细胞突变检测的综合方法。在家长奖励项目中,我们将首先, 从活体供体的几种不同组织中产生克隆扩增的iPSC系,以研究 使用非酶促扩增的基因组DNA的所有类型的体细胞突变。二是 解决了单细胞基因组分析的一个显著缺点,即缺乏直接的 关于被分析的细胞的确切类型的信息,或关于潜在功能的信息, 这些细胞突变的后果。为此,我们将基准新的ResolveOme方法, 可以同时分析单个细胞的基因组和转录组。第三,我们将解决 单细胞高通量分析检测体细胞结构变异的挑战。 具体来说,我们将为SMaHT建立和基准测试Strand-seq方法, 单细胞中结构变异体(SV)的高通量检测和表征。 总之,这将解决正常组织中体细胞突变分析的3个关键需求: 全面的嵌合突变发现,对携带突变的细胞进行表型分析,并直接 评估突变的功能后果,以及准确和高通量检测 SV。 对于这个补充项目,我们将从活体供体中培育出一个已经存在的成纤维细胞系, 以及五个已经存在的源自该成纤维细胞系的克隆扩增的iPSC系。我们 将把这些细胞系的细胞分配给SMaHT财团的GCC,进行深度测序 为了对已经预先验证的体细胞变体的资源进行基准测试, 在已知的组织中存在等位基因频率。

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 }}

Alexander Eckehart Urban其他文献

Alexander Eckehart Urban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('Alexander Eckehart Urban', 18)}}的其他基金

Establishing and benchmarking advanced methods to comprehensively characterize somatic genome variation in single human cells
建立先进方法并对其进行基准测试,以全面表征单个人类细胞的体细胞基因组变异
  • 批准号:
    10662975
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
Project 4
项目4
  • 批准号:
    8914814
  • 财政年份:
    2014
  • 资助金额:
    $ 17.48万
  • 项目类别:
Genomic and epigenomic effects of large CNV in neurons from iPSC
iPSC 神经元中大 CNV 的基因组和表观基因组效应
  • 批准号:
    8357036
  • 财政年份:
    2012
  • 资助金额:
    $ 17.48万
  • 项目类别:
Project 4
项目4
  • 批准号:
    8918721
  • 财政年份:
  • 资助金额:
    $ 17.48万
  • 项目类别:
Project 4
项目4
  • 批准号:
    9322561
  • 财政年份:
  • 资助金额:
    $ 17.48万
  • 项目类别:
Project 4
项目4
  • 批准号:
    9547905
  • 财政年份:
  • 资助金额:
    $ 17.48万
  • 项目类别:
Project 4
项目4
  • 批准号:
    9100823
  • 财政年份:
  • 资助金额:
    $ 17.48万
  • 项目类别:

相似国自然基金

企业绩效评价的DEA-Benchmarking方法及动态博弈研究
  • 批准号:
    70571028
  • 批准年份:
    2005
  • 资助金额:
    16.5 万元
  • 项目类别:
    面上项目

相似海外基金

An innovative EDI data, insights & peer benchmarking platform enabling global business leaders to build data-led EDI strategies, plans and budgets.
创新的 EDI 数据、见解
  • 批准号:
    10100319
  • 财政年份:
    2024
  • 资助金额:
    $ 17.48万
  • 项目类别:
    Collaborative R&D
BioSynth Trust: Developing understanding and confidence in flow cytometry benchmarking synthetic datasets to improve clinical and cell therapy diagnos
BioSynth Trust:发展对流式细胞仪基准合成数据集的理解和信心,以改善临床和细胞治疗诊断
  • 批准号:
    2796588
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
    Studentship
Collaborative Research: SHF: Medium: A Comprehensive Modeling Framework for Cross-Layer Benchmarking of In-Memory Computing Fabrics: From Devices to Applications
协作研究:SHF:Medium:内存计算结构跨层基准测试的综合建模框架:从设备到应用程序
  • 批准号:
    2347024
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
    Standard Grant
Elements: CausalBench: A Cyberinfrastructure for Causal-Learning Benchmarking for Efficacy, Reproducibility, and Scientific Collaboration
要素:CausalBench:用于因果学习基准测试的网络基础设施,以实现有效性、可重复性和科学协作
  • 批准号:
    2311716
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
    Standard Grant
Benchmarking collisional rates and hot electron transport in high-intensity laser-matter interaction
高强度激光-物质相互作用中碰撞率和热电子传输的基准测试
  • 批准号:
    2892813
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
    Studentship
FET: Medium: Quantum Algorithms, Complexity, Testing and Benchmarking
FET:中:量子算法、复杂性、测试和基准测试
  • 批准号:
    2311733
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
    Continuing Grant
Collaborative Research: BeeHive: A Cross-Problem Benchmarking Framework for Network Biology
合作研究:BeeHive:网络生物学的跨问题基准框架
  • 批准号:
    2233969
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
    Continuing Grant
Establishing and benchmarking advanced methods to comprehensively characterize somatic genome variation in single human cells
建立先进方法并对其进行基准测试,以全面表征单个人类细胞的体细胞基因组变异
  • 批准号:
    10662975
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
QUARREFOUR - Benchmarking Multi-core Quantum Computing Systems
QUARREFOUR - 多核量子计算系统基准测试
  • 批准号:
    10074653
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
    Collaborative R&D
Benchmarking Quantum Advantage
量子优势基准测试
  • 批准号:
    EP/Y004418/1
  • 财政年份:
    2023
  • 资助金额:
    $ 17.48万
  • 项目类别:
    Research Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了