Going from Genetic Associations to Identification of Causative Genes

摘要 许多研究，包括这个总体研究计划中的分析，已经在全基因组范围内进行 关联研究，以确定与复杂疾病相关的基因和基因座。虽然有一些人 遗传关联信号已经被发现，在这些基因中识别致病基因的挑战 遗迹仍然存在。因此，本项目的目标是从GWAS关联转移到因果关系的识别 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性状 程序。为了填补证据上的这一关键空白，该项目将基于细胞的最先进方法和 动物模型。分析将从询问最近的GWAOSA和嗜睡的遗传基因座开始，以及 将其扩展到评估正在进行的分析中的位置，包括项目01和03中的位置。在目标1中，我们将 根据我们建立的转座酶可及性检测方法，在电子计算机物理上进行“变异到基因作图” 染色质测序(ATAC-SEQ)加上全基因组启动子集中捕获相关细胞类型的C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 嗜睡；与项目03有关)。这些3D基因组分析将识别最有可能的致病基因和 通过确定相关基因座上的哪些候选基因直接与开放染色质区域相互作用而产生变异。之后 识别可能的致病基因和变异，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的OSA相关解剖(目标2)和反映睡眠行为而起作用 果蝇和斑马鱼的嗜睡和睡眠紊乱(目标3)。具体地说，《目标2》将利用这部小说 我们开发了多变量基因-表型作图管道来识别影响OSA风险的原因基因 通过对头面部形状和/或舌头脂肪的影响。在应用这种方法时，这一目标利用了现有的 以及在具有遗传数据和解剖特征的多样性近交系小鼠的大样本中新产生的数据 通过成像进行量化。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，而不仅仅是大小。 对于嗜睡，目标3将利用果蝇RNAi系来研究击倒候选基因的影响 与睡眠相关的表型(包括睡眠数量、睡眠碎片和睡眠驱动力)。然后，基因 将利用CRISPR-Cas9方法在脊椎动物模型中验证影响果蝇睡眠的方法 在斑马鱼中敲除这些相同的基因，并研究它们对类似睡眠表型的影响。加在一起， 本项目和本计划中其他项目的结果将提供有关效应器基因的基本知识 对阻塞性睡眠呼吸暂停综合征和人类阻塞性睡眠呼吸暂停综合征的嗜睡。这一知识对于理解生物和 GWAS协会的临床影响，并将促进更有效的临床翻译和纳入 将遗传证据转化为精准医学方法，为阻塞性睡眠呼吸暂停综合征提供重要资源 更广泛的科学界和OSA应用基因组学领域的原则证明。

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.