Systematic Identification and Phenotypic Characterization of causal genetic variants in Rare Disease-Associated Birth Defects

项目摘要 尽管在一个实施例中实施全外显子组测序（WES）和全基因组测序（WGS）， 临床环境极大地促进了出生缺陷相关遗传变异的鉴定， 导致先天性缺陷的特定变异仍然是一个重大挑战。更具体地说，大多数变体 在临床测序中检测到的基因发生在以前与疾病无关的基因中或在 缺乏可预测功能后果的基因组。增强阐明因果变异的能力 有望改善患者的生活质量，在某些情况下， 否则会错过的治疗干预。在这项提案中，我们利用我们研究所无与伦比的 儿科遗传数据库，以指导可扩展的基于细胞的系统的开发， 通过在动物和患者来源的类器官模型中进行表型验证，将系统地识别遗传 在我们未确诊的罕见病患者人群中，这些变异是导致先天性缺陷的原因。我们将 (Aim 1）与我们患者中最常见的先天性缺陷相关的功能丧失变体目录 在相关的类器官模型中进行基因组规模的CRISPR筛选，以区分携带变异的 在发育中发挥作用的基因，并验证斑马鱼基因丢失的表型后果 模型同时，我们将（目标2）目录非编码变异（即内含子，推定的顺式调控）相关 与普遍存在的先天性缺陷，开发一套大规模平行的基因组检测，能够分析 非编码遗传变异的大规模调控影响，并干扰候选变异的表达- 相关基因在斑马鱼模型，以确定表型的后果。最后，我们将（目标3） 生成患者源性类器官模型，利用精确的基因组工程结合单细胞 患者源性类器官中的转录组学，以验证特定变体在先天性缺陷中的因果作用， 并使用患者源性的空间转录组学表征变异对发育的影响。 类器官作为替代物。我们预计，本提案中概述的工作将建立一个实验性的 该框架可用于识别导致各种先天性疾病的遗传变异， 缺陷

Project Summary Although the implementation of whole exome sequencing (WES) and whole genome sequencing (WGS) in a clinical setting has greatly facilitated the identification of birth defect-associated genetic variants, distinguishing the specific variants that cause congenital defects remains a major challenge. More specifically, most variants detected in clinical sequencing occur in genes not previously associated with disease or in noncoding regions of the genome that lack predictable functional consequences. Enhancing the ability to illuminate causal variants holds the promise of improving the quality of life for patients and in some cases may provide a window for therapeutic intervention that would otherwise be missed. In this proposal we leverage our institute’s unparalleled pediatric genetic data repository to guide the development of scalable cell-based systems that, when coupled with phenotypic validation in both animal and patient-derived organoid models, will systematically identify genetic variants that are responsible for congenital defects in our undiagnosed rare disease patient population. We will (Aim 1) catalog loss-of-function variants associated with the most prevalent congenital defects in our patient population, perform genome-scale CRISPR screens in relevant organoid models to distinguish variant-harboring genes that play a role in development, and validate the phenotypic consequences of gene loss in a zebrafish model. In parallel, we will (Aim 2) catalog noncoding variants (i.e. intronic, putative cis-regulatory) associated with prevalent congenital defects, develop a suite of massively parallel genomic assays capable of profiling the regulatory impact of noncoding genetic variants at scale, and perturb the expression of candidate variant- associated genes in a zebrafish model to determine the phenotypic consequences. Finally, we will (Aim 3) generate patient-derived organoid models, utilize precision genome engineering in combination with single-cell transcriptomics in patient-derived organoids to validate the causal role of specific variants in congenital defects, and characterize the impact of variants on development using spatial transcriptomics in patient-derived organoids as a proxy. We anticipate that the work outlined in this proposal will establish an experimental framework that can be deployed to identify genetic variants that are responsible for a wide variety of congenital defects.