Unraveling the molecular pathology of retinal degeneration through single cell genomics

摘要： 这项建议的首要目标是了解遗传性视网膜变性的分子病理学。 (IRD)通过(A)生成人类视网膜细胞类型特定调控元件的地图，(B)利用这些地图来 识别视网膜调节元件内的非编码IRD致病突变，以及(C)深入了解 使用细胞和动物模型研究病理性非编码IRD突变的分子基础。红外线是 年轻人不可逆转失明的最常见原因，每3000人中就有1人受到影响。突变 在已知IRD相关基因的编码和剪接位点序列中，约有60%-65%的病例起作用 而其余40%-35%的案件目前尚未解决。非编码或调节性突变 序列被认为是这些未解决案件的很大比例的原因。尽管 Encode和Roadmap表观基因组学项目已经为 大多数身体组织，视网膜都被省略了。缺乏这些地图是识别IRD病因的一个主要限制 涉及视网膜细胞调控序列的突变。我们已经分析了整个基因组序列 (WGS)125个IRD家系；其中49个尚未解决，没有候选致病核苷酸 编码或剪接位点序列中的变化或结构变体(Sv)。这让我们假设 非编码变异在病理学中的参与。此外，我们亦可使用超过391个额外的税务局 WGS分析后仍未解决的家系。在此应用程序中，我们建议测试 假设大多数IRD的病理与非编码序列改变有关 未解决的血统。我们将进行以下研究：目的1，建立人类视网膜细胞类型特异性 使用我们开发的创新单细胞基因组学方法的调控元件图谱，目标2，排名 使用视网膜细胞类型特定的调控元件图和WGS来优先考虑候选致病变体 未解决的家系，目标3，验证高排名的非编码候选疾病导致的影响 通过患者IPSC来源的视网膜细胞类型的基因组结构背景下的变异 视网膜细胞模型和小鼠模型。这些研究将导致建立视网膜细胞类型特异性 高分辨率多组图谱，并可能首次识别涉及到的非编码变体 IRD的病理学。这些研究的结果将(1)大大加强我们对 视网膜细胞类型特异性调控网络的结构，(2)揭示了IRD背后的分子病理， (3)建立与视网膜相关的高度有价值的、公开可用的顺式调控元件数据集 退行性疾病作为视网膜疾病研究的资源，(4)改进患者的突变检测， 以及(5)促进税务局新疗法的发现和发展。我们已经组建了一个多学科的 在表观遗传学(REN)、基因组科学(Frazer)和税务局(IRD)方面拥有专业知识的杰出研究人员团队 遗传学和疾病建模(Ayagari)，他们处于很好的地位来完成这一雄心勃勃的项目。

Abstract: The overarching goal of this proposal is to understand the molecular pathology of inherited retinal degeneration (IRD) by (a) generating maps of human retinal cell type-specific regulatory elements, (b) utilizing these maps to identify non-coding IRD causative mutations within retinal regulatory elements, and (c) gaining insight into the molecular underpinnings of pathological non-coding IRD mutations using cellular and animal models. IRDs are the most common cause of irreversible blindness in young individuals affecting 1 in 3000 individuals. Mutations in coding and splice site sequences in known IRD associated genes contribute to about 60%-65% of cases while the remaining 40%-35% of cases are currently unresolved. Mutations in non-coding or regulatory sequences are suggested to be responsible for a large proportion of these unresolved cases. Although the ENCODE and Roadmap Epigenomics projects have generated detailed maps of regulatory elements for the majority of body tissues, retina is left out. Lack of these maps is a major limitation in identifying IRD causative mutations involving regulatory sequences in retinal cells. We have analyzed the whole genome sequence (WGS) of 125 pedigrees with IRD; of these, 49 remain unresolved with no candidate causative nucleotide changes or structural variants (SVs) in coding or splice site sequences. This leads us to hypothesize the involvement of non-coding variants in pathology. We also have access to more than 391 additional IRD pedigrees that remained unresolved after WGS analysis. In this application we propose to test the hypothesis that non-coding sequence changes are involved in IRD pathology for the majority of these unresolved pedigrees. We will conduct the following studies: Aim 1, establish human retinal cell type specific maps of regulatory elements using innovative single cell genomics methodologies we developed, Aim 2, rank prioritize candidate causative variants using the retinal cell type-specific regulatory element maps and WGS of unresolved pedigrees, Aim 3, validate the impact of high ranking non-coding candidate disease causing variants in the context of the genome architecture of retinal cell types by developing patient iPSC-derived retinal cell models and mouse models. These studies will result in the establishment of retinal cell type-specific high-resolution multi-omic maps and will potentially identify, for the first time, non-coding variants involved in the pathology of IRD. The outcomes of these studies will (1) significantly enhance our understanding of the architecture of retinal cell type-specific regulatory networks, (2) reveal the molecular pathology underlying IRD, (3) establish a highly valuable, publicly-available data set of cis-regulatory elements relevant to retinal degenerative diseases as a resource for retinal disease research, (4) improve mutation detection in patients, and (5) facilitate discovery and development of novel therapies for IRD. We have assembled a multidisciplinary team of outstanding investigators with expertise in epigenetics (Ren), genome sciences (Frazer) and IRD genetics and disease modeling (Ayyagari) who are well positioned to complete this ambitious project.