Scalable tool and comprehensive maps to interpret structural variation across the neuropsychiatric spectrum

可扩展的工具和综合图谱可解释整个神经精神谱系的结构变化

• 批准号: 10737203
• 负责人: MICHAEL E TALKOWSKI
• 金额: $ 74.44万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-10 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10737203
• 关键词: Address; Algorithms; All of Us Research Program; Alleles; Architecture; Area; Biology; Bipolar Disorder; Cells; Clinical; Code; Cognitive; Collection; Complement; Complex; Copy Number Polymorphism; Data; Data Set; Development; Dimensions; Disease; Emerging Technologies; Epilepsy; Etiology; Exons; Family; Frequencies; Funding; General Population; Genes; Genetic Predisposition to Disease; Genetic Variation; Genets; Genome; Genomic Segment; Genomics; Genotype; Goals; Human; Human Genome; Individual; Joints; Maps; Measures; Mediating; Mendelian disorder; Methods; Modeling; Mutation; Nature; Nucleotides; Phenotype; Point Mutation; Population; Population Heterogeneity; Process; Research; Research Project Grants; Resolution; Resources; Risk Factors; Sampling; Schizophrenia; Science; Short Tandem Repeat; Single Nucleotide Polymorphism; Source; Statistical Methods; Statistical Models; Structural Models; Technology; Untranslated RNA; Variant; aggregation database; analytical method; autism spectrum disorder; biobank; case control; cohort; computational pipelines; disorder risk; diverse data; dosage; exome; exome sequencing; genetic architecture; genome sequencing; genome-wide; genomic data; genomic variation; human disease; innovation; loss of function mutation; member; nervous system disorder; neuropsychiatric disorder; neuropsychiatry; new technology; novel; novel strategies; polygenic risk score; sex; success; tool

ABSTRACT Structural variants (SVs), defined as rearrangements of ≥50 DNA nucleotides, are a major source of genetic diversity among humans and an important component of the architecture of neuropsychiatric disorders (NPDs). Despite their etiological significance, remarkably little is known about the consequences of SV formation across the genome as there is a dearth of accurate measures to assess the genome-wide impact of gains or losses of DNA (‘dosage sensitivity’). In contrast, robust models of mutation intolerance in genes have been derived from single nucleotide variants (SNVs), which occur at ~200-fold higher frequency in the genome than SVs. These metrics of negative selection against loss-of-function mutations within genes (e.g., LOEUF from the genome aggregation database [gnomAD]) have been critical to gene and locus discovery across NPDs and Mendelian disorders. By contrast, the absence of equivalent measures for SVs has hindered discovery. This renewal seeks to build on the foundational tools, maps of genomic variation, and association studies across NPDs completed during the initial funding period to now define the landscape of SVs across diverse global populations and determine their relative contribution to the individual and cross-disorder NPD risk. To accomplish these goals, we will leverage the coalescence of massive-scale biobank and NPD study initiatives led by members of our research team with the development of new tools and resources that can scale to millions of individuals. We will first aggregate and harmonize SV callsets generated using our GATK-SV and GATK-gCNV tools across >2.6 million samples with genome and exome sequencing data to create expansive SV maps across diverse populations. We will then apply new statistical approaches to predict SV mutation rates and develop models of genome-wide dosage sensitivity (Aim 1). These new SV variant classes and dosage sensitivity metrics will be integrated into family-based and case-control association studies of NPDs across 387,675 cases from ongoing cohort collections (Aim 2). Notably, these datasets will include significant initiatives led by members of our team to investigate the dimensions of NPDs across diverse populations that are currently under-represented in NPD studies. Finally, we will use innovative new approaches to investigate the influence of SVs that have been cryptic to discovery from existing technologies but are now accessible to long-read sequencing and we will apply new analysis methods to explore their potential influence on NPDs (Aim 3). Overall, each aim addresses a current void in neuropsychiatric genomics and success in any one area would represent an important advance for the field. We have assembled an outstanding team of experts across all domains of computational and statistical genomics, as well as the phenotypic dimensions of neuropsychiatric conditions, and at its conclusion this proposal will yield novel tools and resources at an unprecedented scale to define an important component of the currently unexplained genetic architecture of NPDs.

摘要 结构变异（SV），定义为≥50个DNA核苷酸的重排，是遗传变异的主要来源。 人类的多样性和神经精神疾病（NPD）结构的重要组成部分。 尽管它们在病因学上具有重要意义，但对SV形成的后果知之甚少。 基因组，因为缺乏准确的措施来评估基因组范围内的增益或损失的影响， DNA（“剂量敏感性”）。与此相反，基因突变不耐受的稳健模型来自于 单核苷酸变异（SNV），其在基因组中的发生频率比SV高约200倍。这些 针对基因内功能丧失突变的负选择指标（例如，基因组LOEUF 聚合数据库[gnomAD]）对于跨NPD和孟德尔遗传学的基因和基因座发现至关重要。 紊乱相比之下，缺乏对SV的等效措施阻碍了发现。此次更新旨在 以基础工具、基因组变异图谱和已完成的NPD间关联研究为基础， 在最初的资助期间，现在定义了不同全球人群的SV景观， 确定它们对个体和交叉疾病NPD风险的相对贡献。为了实现这些目标， 我们将利用由我们的成员领导的大规模生物库和NPD研究计划的结合， 研究团队开发新的工具和资源，可以扩展到数百万人。我们将 首先聚合和协调使用我们的GATK-SV和GATK-gCNV工具在>2.6中生成的SV调用集 利用基因组和外显子组测序数据， 人口。然后，我们将应用新的统计方法来预测SV突变率，并建立SV突变模型。 全基因组剂量敏感性（Aim 1）。这些新的SV变体类别和剂量敏感性指标将被 纳入正在进行的387，675例NPD病例的基于家庭和病例对照关联研究 队列收集（目标2）。值得注意的是，这些数据集将包括由我们团队成员领导的重大举措 调查目前在NPD中代表性不足的不同人群的NPD维度 问题研究最后，我们将使用创新的新方法来调查SV的影响， 从现有技术中发现，但现在可以进行长读序测序，我们将应用新的 分析方法，以探索其对NPD的潜在影响（目标3）。总的来说，每个目标都针对一个当前的 神经精神基因组学的空白和任何一个领域的成功都将代表着神经精神病学的重要进展。 领域我们已经组建了一个杰出的专家团队，他们横跨计算和统计的各个领域。 基因组学，以及神经精神疾病的表型维度，并在其结论， 该提案将以前所未有的规模产生新的工具和资源，以确定 目前无法解释的NPD遗传结构。