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

罕见病相关出生缺陷因果遗传变异的系统鉴定和表型特征

• 批准号: 10563687
• 负责人: Scott T Younger
• 金额: $ 64.11万
• 依托单位: CHILDREN'S MERCY HOSP (KANSAS CITY, MO)
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-21 至 2027-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10563687
• 关键词: Acceleration; Address; Animal Model; Animals; Biological Assay; CRISPR screen; Catalogs; Cells; Childhood; Clinical; Clustered Regularly Interspaced Short Palindromic Repeats; Congenital Abnormality; Coupled; Defect; Detection; Development; Diagnosis; Disease; Embryo; Engineering; Gene Expression; Genes; Genetic; Genome; Genome engineering; Genomics; Goals; Lead; Methods; Modeling; Organoids; Patient Selection; Patients; Peripheral Blood Mononuclear Cell; Phenotype; Process; Property; Proxy; Quality of life; RNA Splicing; Rare Diseases; Regulatory Element; Reporter; Reporter Genes; Resources; Role; Sampling; Series; Spliced Genes; System; Technology; Therapeutic Intervention; Translating; Untranslated RNA; Validation; Variant; Work; Zebrafish; causal variant; clinical phenotype; clinical sequencing; data repository; disease phenotype; exome sequencing; genetic variant; genome editing; genome sequencing; genome-wide; improved; induced pluripotent stem cell; innovation; loss of function; loss of function mutation; novel; patient population; patient subsets; programs; rare variant; repository; screening; transcriptomics; variant detection; whole genome

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.

项目摘要 尽管全外显子组测序(WES)和全基因组测序(WGS)在 临床环境极大地促进了出生缺陷相关遗传变异的识别，区分 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发生在以前与疾病无关的基因中或在 缺乏可预测的功能后果的基因组。增强解释因果变量的能力 承诺改善患者的生活质量，在某些情况下可能提供一个窗口 否则就会错过的治疗性干预。在这项提案中，我们利用我们研究所无与伦比的 儿科遗传数据库用于指导可扩展细胞系统的开发，当耦合时 通过在动物和患者衍生的器官模型中进行表型验证，将系统地识别基因 导致我们未被诊断的罕见疾病患者群体中先天性缺陷的变异。我们会 (目标1)与我们患者中最常见的先天性缺陷相关的功能丧失变异 群体，在相关的器官模型中进行基因组规模的CRISPR筛查，以区分含有变异的 在发育中起作用的基因，并验证斑马鱼基因缺失的表型后果 模特。同时，我们将(目标2)分类相关的非编码变体(即内含子，推定为顺式调控) 对于普遍存在的先天性缺陷，开发一套大规模平行的基因组分析方法，能够分析 大规模非编码遗传变异的调控影响，并扰乱候选变异的表达- 斑马鱼模型中的相关基因以确定表型后果。最后，我们将(目标3) 生成患者衍生的器官模型，利用精密基因组工程与单细胞相结合 在患者衍生的器官中进行转录切分以验证特定变异在先天性缺陷中的因果作用， 并利用空间转录组分析了变异对发育的影响。 作为代理人的有机化合物。我们预计，这项提案中概述的工作将建立一个试验性的 一个框架，可用于识别导致各种先天性心脏病的遗传变异 缺陷。