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

基本信息

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
项目类别：
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

项目摘要

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.

抽象的结构变体（SVS）定义为≥50个DNA核动脉的重排，是通用的主要来源人类之间的多样性以及神经精神疾病（NPDS）结构的重要组成部分。尽管具有病因的意义，但对SV形成的后果知之甚少基因组由于有准确措施的死亡，以评估跨基因组收益的影响或损失的损失 DNA（“剂量灵敏度”）。相比之下，基因中突变肠的强大模型是从中得出的单核苷酸变体（SNV），基因组的频率比SV高约200倍。这些基因内基因组内的负功能丧失突变的负选择的指标（例如，基因组的LOEUF 汇总数据库[GNOMAD]）对于跨NPD和Mendelian的基因发现至关重要疾病。相比之下，缺乏SVS的等效度量阻碍了发现。这种更新寻求建立基于基础工具，基因组变异的地图以及完成的NPD的关联研究在现在的最初资助期间，定义了潜水员全球人口的SV景观，确定它们对个人和跨disorder 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研究计划的合并研究团队开发了可以扩展到数百万个人的新工具和资源。我们将首先使用我们的GATK-SV和GATK-GCNV工具生成> 2.6的汇总和协调SV呼叫具有基因组和外显子组测序数据的百万样品，以创建潜水员的额外SV地图人群。然后，我们将采用新的统计方法来预测SV突变率并开发全基因组剂量敏感性（AIM 1）。这些新的SV变体类和剂量敏感性指标将是在387,675例中，整合到基于家庭的和病例对照的关联研究中队列收集（AIM 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要计划研究当前在NPD中代表性不足的潜水员人群中NPD的尺寸研究。最后，我们将使用创新的新方法来调查已加密的SV的影响从现有技术中发现，但现在可以进行长阅读测序，我们将应用新的分析方法探索其对NPD的潜在影响（AIM 3）。总体而言，每个目标都解决了当前神经精神病学基因组学和任何一个领域的成功将代表着重要的进步场地。我们已经组建了一个在计算和统计领域的所有领域的杰出专家团队基因组学以及神经精神疾病的表型维度，并在此结论建议将以空前的规模产生新颖的工具和资源，以定义目前无法解释的NPD遗传结构。