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Comprehensive Sequencing and Analysis of Variation in NHLBI Cohorts

Comprehensive Sequencing and Analysis of Variation in NHLBI Cohorts
NHLBI 队列的综合测序和变异分析
批准号:
7941983
负责人:
David Altshuler
金额:
$1471.24万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2012-09-30

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项目成果

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中文摘要
翻译
描述(由申请人提供):我们建议创建表型样本中最大的DNA序列变异目录,并率先将这种深度和规模的数据应用于关键心血管表型的分析。我们建议这样做:(1)在10,000个表型样本中的每个样本中进行全面的测序(在基因组或外显子组范围内,如与项目指导委员会合作确定的);(2)在20,000个额外样本中快速对初始的一组新变异体进行基因分型;以及(3)向研究界提供原始数据、带注释的变异体以及变异检测、验证和与表型关联的框架。该项目的最终目标是创建一个数据和分析资源,为随后多年对多种心血管表型的等位基因频率变异的全谱询问奠定基础。 公共卫生相关性:拟议的项目旨在全面描述人类基因组中功能上最相关和最可解释的部分(外显子组)的DNA序列变异,并使这些发现与NHLBI队列样本中测量的大量心血管疾病和临床表型的下游关联。这将使深入检查已知的风险基因座成为可能,并发现许多以前在图谱研究中遗漏的新基因座--导致新的生物假说、新的药物靶点和改进的临床预测。
英文摘要
DESCRIPTION (provided by applicant): We propose to create what will be the largest catalogue of DNA sequence variation in phenotyped samples and to pioneer the application of this depth and scale of data to the analysis of key cardiovascular phenotypes. We propose to do this by (1) performing comprehensive sequencing (on a genome- or exome-wide scale, as determined in collaboration with the Project Steering Committee) in each of 10,000 phenotyped samples; (2) rapidly genotyping an initial set of novel variants in 20,000 additional samples, and (3) making available to the research community raw data, annotated variants, and a framework for variant detection, validation and association to phenotypes. The ultimate goal of this project is to create a data and analytic resource that will lay the groundwork for subsequent interrogation of the full spectrum of allele frequency variation in a wide array of cardiovascular phenotypes for many subsequent years. PUBLIC HEALTH RELEVANCE: The proposed project aims to comprehensively describe DNA sequence variation in the most functionally relevant and interpretable portion of the human genome (the exome), and to enable downstream association of these findings to the vast collection of cardiovascular disease and clinical phenotypes measured in NHLBI cohort samples. This will make possible deep inspection of known risk loci and discovery of many new loci previously missed in mapping studies - leading to new biologic hypothesis, new drug targets, and improved clinical prediction.
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