High-throughput modeling of autism risk genes using zebrafish

使用斑马鱼进行自闭症风险基因的高通量建模

• 批准号: 10121604
• 负责人: DANIEL H GESCHWIND
• 金额: $ 81.18万
• 依托单位: CALIFORNIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10121604
• 关键词: Address; Animal Model; Autopsy; Behavior; Behavioral; Behavioral Model; Biological Assay; Biological Models; Brain; Cells; Communities; Data; Development; Disease; Disease model; Drug Screening; Gene Expression; Genes; Genetic; Goals; Human; Image; Individual; Inherited; Lead; Literature; Methods; Missense Mutation; Modeling; Molecular; Mutation; Neurons; Orthologous Gene; Pathway Analysis; Pathway interactions; Pharmacology; Phenotype; Proteins; Publishing; RNA Splicing; Reagent; Reporting; Resources; Risk; Role; Seizures; Signal Transduction; Sleep; Sleep disturbances; Social Behavior; Spliced Genes; Startle Reaction; System; Testing; Time; Tissue-Specific Gene Expression; Translating; Variant; Vertebrates; Zebrafish; autism spectrum disorder; base; behavior test; behavioral phenotyping; brain behavior; cohort; comorbidity; cost; cost effectiveness; de novo mutation; disorder risk; experimental study; gene function; genetic risk factor; genetic testing; genome sequencing; genome wide association study; genome-wide; habituation; high throughput analysis; high throughput screening; high-throughput drug screening; imaging approach; improved; in vivo; molecular phenotype; mutant; neurodevelopment; novel; novel therapeutics; null mutation; relative effectiveness; risk variant; screening; social; transcriptomics; whole genome

Autism spectrum disorder (ASD) is caused by both environmental and genetic factors, with the genetic contribution estimated at 60-80%. Dozens of genes that increase risk for ASD have been identified, most based on de novo mutations, but these mutations are predicted to account for only 15-20% of ASD cases. Thus, the majority of the genetic contribution to ASD is predicted to result from common and rare inherited variation, but few such genes have been identified. Recently, using whole genome sequencing, we reported genome wide evidence for >60 ASD risk genes, 26 of them novel for ASD, with signals derived from inherited and de novo protein truncating or missense mutations. The functions of most of these genes are unknown, so a crucial and necessary next step is to explore their impact on neurodevelopment and neuronal function using a model organism. The current pace of translating genetic risk factors into phenotypes, mechanisms and therapies is limited in part by inefficiencies with in vivo mammalian model systems, which makes them impractical for creating and behaviorally testing large numbers of mutant lines. Here, we leverage the zebrafish, which occupies a unique niche as a vertebrate model with features amenable to both in vivo screening and mechanistic understanding, including ex utero development, transparency, small size, rapid development, a conserved yet relatively simple vertebrate brain, behaviors relevant to ASD, and cost-effectiveness relative to mammalian models. While the zebrafish cannot recapitulate ASD and has limitations for modeling a human disorder, an emerging literature supports the notion that it is a useful model to study the functions of genes that contribute to ASD risk. Rather than assess ASD-risk genes one at a time, we will accelerate progress towards mechanistic understanding via high-throughput assays and analyses. In Specific Aim 1 we will generate null mutations in the zebrafish orthologs of 24 high confidence, novel, genome-wide significant ASD risk genes, and systematically test each mutant for neurodevelopmental, behavioral, neuronal network, and transcriptomic phenotypes. In Specific Aim 2, we will use transcriptomic analyses, at the whole brain and single cell levels, to integrate ASD risk genes into functional networks, and test for convergence across genes and species, including ASD post mortem brain. We will also test for functional associations among behavioral phenotypes that are often co-morbid in ASD, such as disrupted sleep and social behavioral deficits. In Specific Aim 3 we will perform mechanistic studies to understand how mutation of specific ASD-risk genes leads to phenotypes. This project will efficiently and cost-effectively create and characterize vertebrate animal models for a large number of novel ASD risk genes. These animal models will be a valuable resource for the community, particularly for large-scale in vivo drug screens to identify new therapies for ASD.

自闭症谱系障碍（ASD）是由环境和遗传因素引起的，遗传因素 估计占60- 80%。已经确定了数十种增加ASD风险的基因，其中大部分基于 新生突变，但预计这些突变仅占ASD病例的15-20%。因此 预测ASD的大部分遗传贡献来自常见和罕见的遗传变异，但是 很少有这样的基因被鉴定出来。最近，利用全基因组测序， 有证据表明有超过60个ASD风险基因，其中26个是ASD的新基因，其信号来自遗传和新生 蛋白质截短或错义突变。这些基因中的大多数的功能是未知的，所以一个关键的， 必要的下一步是使用模型探索它们对神经发育和神经元功能的影响 有机体目前将遗传风险因素转化为表型、机制和治疗方法的速度是 部分受限于体内哺乳动物模型系统的效率低下，这使得它们对于创建 并对大量突变株系进行行为测试。在这里，我们利用斑马鱼，它占据了独特的 小生境作为具有适合于体内筛选和机理理解的特征的脊椎动物模型， 包括子宫外发育、透明、体积小、发育快、保守但相对简单， 脊椎动物大脑，与ASD相关的行为，以及相对于哺乳动物模型的成本效益。而 斑马鱼不能重现ASD，并且在模拟人类疾病方面存在局限性， 支持这是一个有用的模型来研究导致ASD风险的基因功能的观点。而 而不是一次评估一个ASD风险基因，我们将通过以下方式加速对机制的理解 高通量测定和分析。在特定目标1中，我们将在斑马鱼直系同源物中产生无效突变。 24个高置信度，新的，全基因组显著ASD风险基因，并系统地测试每个突变体， 神经发育、行为、神经元网络和转录组表型。在第二阶段，我们将 在全脑和单细胞水平上使用转录组学分析，将ASD风险基因整合到功能基因组中。 网络，并测试跨基因和物种的趋同性，包括ASD死后大脑。我们还将 测试行为表型之间的功能关联，这些行为表型通常在ASD中共病，例如破坏 睡眠和社会行为缺陷。在具体目标3中，我们将进行机制研究，以了解如何 特定ASD风险基因的突变导致表型。该项目将有效和具有成本效益地创造 并表征大量新型ASD风险基因的脊椎动物模型。这些动物模型 将是社区的宝贵资源，特别是用于大规模体内药物筛选以识别新的 ASD的治疗方法