Going from Genetic Associations to Identification of Causative Genes

从遗传关联到致病基因的识别

• 批准号: 10555812
• 负责人: Allan I Pack
• 金额: $ 66.63万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10555812
• 关键词: 3-Dimensional; ATAC-seq; Adipocytes; Affect; Anatomy; Animal Model; Animals; Astrocytes; Behavior; Biological; Biological Assay; Biological Models; CRISPR/Cas technology; Candidate Disease Gene; Cells; Chromatin; Chromatin Loop; Chromosome Mapping; Clinical; Communities; Complement; Complex; Data; Disease; Drosophila genus; Drowsiness; Enhancers; Excessive Daytime Sleepiness; Fatty acid glycerol esters; Fishes; Gene Expression; Gene Targeting; Genes; Genetic; Genome; Genomics; Genotype; Goals; Human; Image; Induced pluripotent stem cell derived neurons; Investments; Knock-out; Knowledge; Link; Magnetic Resonance Imaging; Maps; Medicine; Mesenchymal Stem Cells; Methods; Modeling; Mus; Neuroglia; Neurons; Obesity; Obstructive Sleep Apnea; Osteoblasts; Pathway interactions; Patients; Phenotype; Process; Quantitative Trait Loci; RNA Interference; RNA interference screen; Research; Resolution; Resources; Risk; Risk Factors; Sampling; Severities; Shapes; Signal Transduction; Site; Sleep; Sleep Apnea Syndromes; Sleep Fragmentations; Sleep disturbances; Sleeplessness; Testing; Tongue; Transposase; Validation; Variant; Zebrafish; candidate identification; causal variant; cell type; clinical translation; craniofacial; disorder risk; diverse data; fly; follow-up; gene function; genetic association; genetic variant; genome wide association study; genome-wide; genomic locus; in silico; knock-down; knockout gene; multidimensional data; novel; precision medicine; programs; promoter; sleep behavior; trait; transcriptome sequencing

ABSTRACT Many studies, including analyses in this overall Program of research, have conducted genome-wide association studies (GWAS) to identify genes and loci associated with complex disease. While a number of genetic association signals have been uncovered, the challenge of identifying causative genes at these genetic loci remains. As such, the goal of this Project is to move from GWAS association to identification of causal effector genes relevant to obstructive sleep apnea (OSA) and excessive sleepiness, two key traits studied in this Program. To fill this critical gap in evidence this Project combines state-of-the-art approaches in cell-based and animal models. Analyses will begin by interrogating genetic loci from recent GWAS on OSA and sleepiness, and be extended to evaluate loci from ongoing analyses, including those in Projects 01 and 03. In Aim 1, we will conduct in silico physical `variant to gene mapping' based on our established Assay for Transposase Accessible Chromatin sequencing (ATAC-seq) plus genome-wide promotor-focused Capture C data on relevant cell types - osteoblasts and adipocytes (for anatomy; relevant to Project 01) and neurons and primary astrocytes (for sleepiness; relevant to Project 03). These 3D Genomics analyses will identify the most likely causal genes and variants by determining which candidates at implicated loci directly interact with regions of open chromatin. After identifying likely causal genes and variants, follow-up analyses in animal models will be performed to understand if candidate effector genes act by affecting OSA-related anatomy in mice (Aim 2) and sleep behavior reflective of sleepiness and disturbed sleep in Drosophila and zebrafish (Aim 3). Specifically, Aim 2 will utilize the novel multivariate genotype-phenotype mapping pipeline we developed to identify causal genes affecting OSA risk through effects on craniofacial shape and/or tongue fat. In applying this method, this Aim leverages both existing and newly generated data in a large sample of Diversity Outbred mice with genetic data and anatomical traits quantified via imaging. This cutting-edge approach facilitates determination of the effects of multiple genes on multivariate phenotypes using high-dimensional data to compare directions, not just magnitudes, of associations. For sleepiness, Aim 3 will utilize Drosophila RNAi lines to study the impact of knocking-down candidate genes on sleep-related phenotypes (including sleep amounts, sleep fragmentation, and sleep drive). Then, genes shown to affect sleep in Drosophila will be validated in a vertebrate model by utilizing CRISPR-Cas9 methods to knock-out these same genes in zebrafish and studying the effects on similar sleep phenotypes. Taken together, results in this Project and the other projects in this Program will provide essential knowledge about effector genes for OSA and for sleepiness in OSA in humans. This knowledge is crucial for understanding the biological and clinical impact of GWAS associations, and will facilitate more efficient clinical translation and incorporation of genetic evidence into precision medicine approaches to OSA, as well as provide an important resource for the broader scientific community and proof of principle for the field of applied genomics in OSA.

摘要 许多研究，包括本研究总体计划中的分析，都在全基因组范围内进行了研究。 关联研究（GWAS），以确定与复杂疾病相关的基因和位点。虽然一些 遗传关联信号已经被发现，在这些遗传关联信号中识别致病基因的挑战是， Locus仍然存在。因此，本项目的目标是从GWAS关联转向因果关系识别 与阻塞性睡眠呼吸暂停（OSA）和过度嗜睡相关的效应基因，这是本研究中研究的两个关键特征。 程序.为了填补这一关键的证据空白，该项目结合了基于细胞的最先进的方法， 动物模型分析将开始，通过询问最近GWAS中关于OSA和嗜睡的遗传位点， 扩展到评估正在进行的分析中的位点，包括项目01和03中的位点。在目标1中，我们 根据我们建立的转座酶可重复性测定法，进行计算机物理“变体到基因作图” 染色质测序（ATAC-seq）和全基因组启动子聚焦Capture C相关细胞类型数据 - 成骨细胞和脂肪细胞（用于解剖学;与项目01相关）以及神经元和初级星形胶质细胞（用于 #21403;，与项目相关）。这些3D基因组学分析将确定最可能的致病基因， 通过确定在相关基因座的哪些候选者直接与开放染色质区域相互作用来确定突变。后 识别可能的致病基因和变异，将在动物模型中进行后续分析，以了解 如果候选效应基因通过影响小鼠中与OSA相关的解剖结构（目标2）和睡眠行为反应而起作用， 果蝇和斑马鱼的嗜睡和睡眠障碍（目标3）。具体来说，目标2将利用小说 我们开发了多变量基因型-表型作图管道，以确定影响OSA风险的致病基因 通过影响颅面形状和/或舌头脂肪。在应用这种方法时，本目标利用现有的 在具有遗传数据和解剖特征的大样本Diversity Outbred小鼠中， 通过成像定量。这种尖端的方法有助于确定多个基因对 多变量表型使用高维数据来比较关联的方向，而不仅仅是幅度。 对于嗜睡，Aim 3将利用果蝇RNAi系来研究敲低候选基因的影响 睡眠相关的表型（包括睡眠量，睡眠片段和睡眠驱动）。然后，基因 将在脊椎动物模型中通过利用CRISPR-Cas9方法验证， 在斑马鱼中敲除这些相同的基因，并研究对类似睡眠表型的影响。综合起来看， 本项目的研究成果和本项目的其他研究成果将提供有关效应基因的基本知识 和睡眠呼吸暂停综合症患者的嗜睡程度。这些知识对于理解生物学和 GWAS关联的临床影响，并将促进更有效的临床翻译和整合 基因证据进入精确医学方法OSA，以及提供了一个重要的资源， 更广泛的科学界和应用基因组学在OSA领域的原则证明。