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Lost-of-function variants in the 1000 genomes data set and implications to GWAS

Lost-of-function variants in the 1000 genomes data set and implications to GWAS
1000 个基因组数据集中的功能丧失变异及其对 GWAS 的影响
批准号:
7882977
负责人:
HONGYU ZHAO
金额:
$26.2万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-09-13 至 2012-06-30

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中文摘要
翻译
描述(由申请人提供): 1000基因组计划是一个国际研究联盟,其目标是制作一份人类基因变异的详细地图,以支持主要测序工作的疾病研究。该项目涉及对来自世界各地的至少1000人的基因组进行测序,以促进发现和理解遗传变异,如单核苷酸多态和结构变异。该项目产生的数据将有助于发现基因组中包含与人类疾病风险相关的遗传变异的区域,就像之前HapMap项目等努力所尝试的那样。然而,在分析、注释和应用这些数据以指导与疾病和各种特征相关的变异的识别方面存在重大挑战。在这项应用中,我们将重点介绍功能丧失变异,因为它们代表了一类可能与复杂性状有关的主要遗传变异,我们相信对这些变异进行全面的表征并将所获得的知识提供给一般研究团体将有助于识别与复杂性状有关的基因。为了实现这一目标,我们将开发一条生物信息学管道,从1000个基因组数据中识别功能缺失变体,将它们与文献和公共数据库中积累的其他类型的信息相关联,如基因本体论、蛋白质相互作用、表达谱,研究在种群样本中获得这些变体的基因类型的最佳方法,并开发统计方法来纳入注释结果,以增加识别影响复杂特征的功能缺失变体的统计能力。我们将通过专注于功能丢失变体的独立应用程序以及通过与UCSC Genome浏览器团队合作在其浏览器上添加关于这些功能丢失变体的不同类型的信息来向公众传播方法和结果。我们相信,这一拟议的项目将为科学界带来非常宝贵的资源,这些资源可以显著提高我们对人类群体中功能变异缺失的了解,并利用这些知识更有效地改善人类健康。相关性:这项研究提案旨在为科学界产生非常宝贵的资源,这些资源可以显著增强我们对人类群体中功能变异丢失的了解,并利用这些知识更有效地改善人类健康。
英文摘要
DESCRIPTION (provided by applicant): The 1000 Genomes Project is an international research consortium whose aim is to produce a detailed map of human genetic variation to support disease studies with major sequencing effort. This project involves sequencing the genomes of at least a thousand people from around the world to facilitate the discovery and understanding of genetic variants such as single nucleotide polymorphisms and structural variants. The data generated from this project will help in the discovery of regions in the genome containing genetic variations associated with risk of human diseases as previously attempted by efforts such as the HapMap Project. However, there are significant challenges in the analysis, annotation, and applications of these data to guide the identifications of variants associated with diseases and various traits. In this application, we will focus on loss-of-function variants because they represent a major class of genetic variations that are potentially involved in complex traits, and we believe a comprehensive characterization of these variants and making the knowledge gained available to the general research community will facilitate the identifications of genes involved in complex traits. To accomplish this objective, we will develop a bioinformatics pipeline to identify loss-of-function variants from the 1000 genome data, associate them with other types of information accumulated in the literature and public databases, such as gene ontology, protein interactions, expression profiles, investigate the best approaches to attain the genotypes of these variants in population samples, and develop statistical methods to incorporate the annotation results to increase the statistical power to identify loss of function variants affecting complex traits. We will disseminate the methods and results to the public both through a stand-alone application focusing of loss of function variants as well as through collaboration with the UCSC Genome Browser team to add tracks on their browser to different types of information on these loss of function variants. We believe that this proposed project will generate very valuable resources to the scientific community that can significantly enhance our understanding of loss of function variants in human populations and use such knowledge to more effectively improve human health. RELEVANCE: The research proposal is developed to generate very valuable resources to the scientific community that can significantly enhance our understanding of loss of function variants in human populations and use such knowledge to more effectively improve human health.
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Statistical Methods for Genetic Risk Predictions across Diverse Populations
  • 批准号:
    10662188
  • 项目类别:
  • 资助金额:
    $56.87万
  • 财政年份:
    2022
  • 负责人:
    HONGYU ZHAO
  • 依托单位:
Statistical Methods for Genetic Risk Predictions across Diverse Populations
  • 批准号:
    10391800
  • 项目类别:
  • 资助金额:
    $57.92万
  • 财政年份:
    2022
  • 负责人:
    HONGYU ZHAO
  • 依托单位:
Data Management Core
  • 批准号:
    10698039
  • 项目类别:
  • 资助金额:
    $24.66万
  • 财政年份:
    2022
  • 负责人:
    HONGYU ZHAO
  • 依托单位:
Statistical Methods for Genetic Risk Predictions across Diverse Populations
  • 批准号:
    10731582
  • 项目类别:
  • 资助金额:
    $8.39万
  • 财政年份:
    2022
  • 负责人:
    HONGYU ZHAO
  • 依托单位:
海外基金