Whole genome sequences in ethnically diverse individuals with functional assays and genome editing to characterize the biology of plasma lipids

项目概要/摘要 冠心病是世界范围内的主要死亡原因。血浆的遗传基础 脂质是冠心病最强的危险因素，它导致了关键的生物学和临床见解。大- 大规模深度覆盖的全基因组测序现在是可行的，并提供了表征全基因组的机会。 特定个体内的基因组变异。然而，对于任何一个个体，基因组的解释 变异受到以下因素的限制：1）种族特异性影响，2）功能影响的预测，特别是对于罕见的， 非编码变体。本R 01提案的目标是充分描述血脂的遗传基础 通过一种新的“反式组学”方法--用新的统计学方法补充全基因组测序， 遗传学和功能基因组学。在目标1中，我们将从大约10万个种族中发现新的基因组变异， 不同的个体，并与血脂。我们将互补地使用数据驱动的生物信息学 寻找新的基因区域。在目标2中，我们将改进家族性遗传病的基因组诊断， 高胆固醇血症，以重度高胆固醇血症为特征， 冠心病我们将结合种族，功能注释和多效性来开发一种新的 家族性高胆固醇血症的多基因模型。我们将联合模拟单基因和多基因 家族性高胆固醇血症的风险因素。在目标3中，我们确定了功能性罕见非编码 高胆固醇血症变异体的研究，包括基于细胞的大规模平行报告基因测定和基于CRISPR的方法。 我们将进一步利用这些见解来提高从全基因组序列中发现新基因的能力 分析.这项工作利用了NHLBI Trans-Omics for Precision Medicine中生成的数据 （TOPMed）程序。我们在全基因组序列分析，统计遗传学， 功能基因组学和心血管医学。该建议包括方法论，计算， 实验创新，并建立在研究人员与 优势互补。完成我们的目标将产生新的见解，为预防，诊断和治疗提供信息。 冠心病的治疗方法此外，我们将展示跨组学的广泛框架 分析，以确定因果相关的基因组变异的研究和临床遗传应用。

PROJECT SUMMARY / ABSTRACT Coronary heart disease is the leading cause of death worldwide. Characterizing the inherited basis of plasma lipids, the strongest risk factor for coronary heart disease, has led to key biological and clinical insights. Large- scale deep-coverage whole genome sequencing is now feasible and offers the opportunity to characterize full genomic variation within a given individual. For any one individual, however, the interpretation of genomic variation is limited by 1) ethnic-specific impacts, and 2) prediction of functional impact, particularly for rare, non-coding variants. The goal of this R01 proposal is to fully characterize the inherited basis of plasma lipids through a novel `trans-omics' approach – complementing whole genome sequencing with novel statistical genetics and functional genomics. In Aim 1, we will discover novel genomic variation from ~100,000 ethnically- diverse individuals and associate with plasma lipids. We will complementarily use data-driven bioinformatic approaches to identify novel genetic regions. In Aim 2, we will improve the genomic diagnosis of familial hypercholesterolemia, characterized by severe hypercholesterolemia and marked increased risk for premature coronary heart disease. We will incorporate ethnicity, functional annotations, and pleiotropy to develop a novel polygenic model for familial hypercholesterolemia. We will jointly model the monogenic and polygenic components for risk of familial hypercholesterolemia. In Aim 3, we identify functional rare non-coding hypercholesterolemia variants with cell-based massively parallel reporter assays and CRISPR-based methods. We will further use these insights to improve power for discovering novel genes from whole genome sequence analysis. This work leverages data being generated within the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We have extensive expertise in whole genome sequence analysis, statistical genetics, functional genomics, and cardiovascular medicine. This proposal includes methodological, computational, and experimental innovations, and builds on established collaborative relationships between investigators with complementary strengths. Completion of our aims will yield novel insights to inform prevention, diagnosis, and treatments for coronary heart disease. Furthermore, we will demonstrate broad framework for trans-omics analysis to identify causally relevant genomic variants for both research and clinical genetic applications.