Discovering and Analyzing Development and Age-Associated CNAs in the All of Us Cohort

摘要 个体中的基因组变异可以是遗传的(即，通过生殖系传播)或 由受精卵后细胞中的突变产生的，这导致任何个体中没有两个细胞具有相同的 基因组。克隆性造血是血液中与年龄相关的体细胞克隆生长的现象。是这样的 其结果与全因死亡率、血癌风险和心血管疾病的增加有关。 但降低了患阿尔茨海默氏症的风险。在提议的项目中，我们将发现和分析体细胞 CNV使用我们所有队列中的全基因组测序(WGS)数据。我们将把CNVpytor应用于所有 美国WGS数据发现体细胞CNV并将发现的CNV作为资源提供给ALL的研究人员 我们的研究人员工作台。该资源将包括CNV、已处理文件和小文件的分层列表 对于CNV的即时手动检查，以及包含如何访问的示例的文档和视频教程， 检查、分析和可视化IGV中发现的CNV。此外，我们还将包括CNV的分层 类型(即，缺失、重复、LOH)按年龄划分，定义其可能出现的年龄，确定其精确的 断点，并分析断点处的序列以揭示其可能的来源。完成所述的 该项目将导致对我们所有队列中的个体血液中的体细胞CNV进行大规模评估 并将为此类体细胞CNV的病因学提供新的见解。所开发的方法可以是 应用于未来产生的数据，因为我们所有人都扩大了样本收集。 1

Abstract Genomic variants in an individual may be either inherited (i.e., transmitted through the germline) or generated by mutagenesis in post-zygotic cells, which results in no two cells in any individual having the same genome. Clonal hematopoiesis is the phenomenon of age-related outgrowth of somatic clones in the blood. Such an outgrowth has been associated with increased all-cause mortality, risk of blood cancer and cardiovascular diseases but reduced risks of Alzheimer’s disease. In the proposed project we will discover and analyze somatic CNVs using whole genome sequencing (WGS) data in the All of Us cohort. We will apply CNVpytor to all All of Us WGS data to discover somatic CNVs and provide discovered CNVs as a resource to researchers in the All of Us Researcher Workbench. The resource will include a tiered list of CNVs, processed and small sized files for instant manual inspection of CNVs, and documentation and video tutorial with examples how to access, inspect, analyze and visualize the discovered CNVs in IGV. Additionally, we will include stratification of CNV types (i.e., deletions, duplications, LOHs) by age, defining their likely age of occurrence, determining their precise breakpoints, and analyzing sequences at the breakpoints to reveal their likely origin. Completing the described project will result in a large-scale assessment of somatic CNVs in the blood of individuals in the All of Us cohort and will provide a new insight into the etiology of such somatic CNVs. The developed methodologies can be applied to data generated in the future, as All of Us expands the collection of samples. 1