Human Genetic Variation and Disease

 描述（由申请人提供）：我们将使用来自一组独特的多代犹他州家系的全基因组序列（WGS）来探索遗传变异的原因以及这种变异对疾病的后果。我们将估计42个三代家系的突变率和移动的元件反转录转座率，每个家系由祖父母、父母和大量后代组成（总共626个个体）。使用先进的方法来检测WGS数据中的单核苷酸变异、结构变异和移动的元件插入，我们将解决关于突变和移动的元件进化的基本问题：在一个大的、控制良好的家族集合中，突变和反转录转座的速率是多少？这些事件是如何受到父亲和母亲年龄的影响？这些比率的变化是否由遗传因素决定（例如，DNA修复基因）在家庭中分离？基因组背景的作用是什么（例如，GC含量，重组）在产生从头突变和逆转录转座？除了解决有关遗传变异的原因的问题，我们将通过分析大型多代犹他州家系中的WGS来解决变异的后果，其中存在大量的特定遗传性疾病。在单独的资助下，我们正在从至少3，000名系谱成员中获得WGS，作为犹他州基因组计划的一部分（PI是该计划的执行董事）。这些家庭是拥有800万成员的犹他州人口数据库的一部分，为孟德尔和复杂疾病的遗传分析提供了重要的优势，因为遗传异质性和环境异质性都大大降低了。此外，大型谱系提供了跟踪WGS中检测到的罕见变异跨代传播的可能性，因为它们有助于疾病病因，包括常见复杂疾病的病因。因此，它们为疾病基因鉴定提供了强大而独特的资源。我们已经开发了VAAST，pVAAST和Phevor算法，用于检测和表征这些家族中的致病基因。在这个项目中，我们将开发和修改这些方法来解决几个关键问题：非编码遗传变异在引起遗传性疾病中的作用是什么？结构变异（如拷贝数变异和基因组重排）在多大程度上导致遗传性疾病？如何有效地调整现有方法，以识别导致常见疾病易感性的多种变异？

 DESCRIPTION (provided by applicant): We will use whole-genome sequences (WGS) from a unique set of multigenerational Utah pedigrees to explore the causes of genetic variation and the consequences of this variation for disease. We will estimate the rates of mutation and mobile element retrotransposition in 42 three-generation pedigrees, each consisting of grandparents, parents, and large numbers of offspring (626 individuals in total). Using advanced methods to detect single nucleotide variants, structural variants, and mobile element insertions in WGS data, we will address fundamental questions about mutation and mobile element evolution: In a large, well-controlled set of families, what are the rates of mutation and retrotransposition? How are these events affected by paternal and maternal age? Is variation in these rates determined by genetic factors (e.g., DNA repair genes) that segregate in families? What is the role of genomic context (e.g., GC content, recombination) in generating de novo mutations and retrotranspositions? In addition to addressing questions about the causes of genetic variation, we will address the consequences of variation by analyzing WGS in large, multigenerational Utah pedigrees in which there is a strong excess of specific inherited diseases. Under separate funding, we are obtaining WGS from at least 3,000 pedigree members as part of the Utah Genome Project (of which the PI is the Executive Director). These families, which are part of the eight-million-member Utah Population Database, provide important advantages for the genetic analysis of Mendelian and complex diseases because genetic heterogeneity, as well as environmental heterogeneity, are both greatly reduced. Furthermore, large pedigrees offer the potential to follow the transmission of rare variants detected in WGS across generations as they contribute to disease causation, including the causation of common, complex diseases. They thus provide a powerful and unique resource for disease-gene identification. We have developed the VAAST, pVAAST, and Phevor algorithms for detecting and characterizing disease-causing genes in these families. In this project, we will develop and modify these methods to address several key questions: What is the role of noncoding genetic variation in causing inherited disease? To what extent does structural variation, such as copy number variants and genomic rearrangements, contribute to inherited disease? How can existing methods be effectively adapted to identify the multiple variants that underlie susceptibility to common diseases?