Functional Dissection of CNVs in Neurodevelopmental Traits

神经发育特征中 CNV 的功能剖析

• 批准号: 10107962
• 负责人: Erica Ellen Davis
• 金额: $ 19.13万
• 依托单位: LURIE CHILDREN'S HOSPITAL OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-15 至 2021-09-19
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10107962
• 关键词: Functional; Dissection; CNVs; Neurodevelopmental; Traits

 DESCRIPTION (provided by applicant): Despite major advances in genomic technologies, the integration of genetic data with clinical management remains challenging. This problem is particularly poignant for copy number variants (CNVs), lesions that typically perturb the dosage of dozens of genes and, as recent data have revealed, are major contributors to genetic disorders, most notably neurodevelopmental traits. Recent advances that afford superior resolution in the detection of genomic lesions have accelerated the discovery of CNVs in patients; however, with the exception of rare cases with point mutations of discrete genes within a CNV, the transition from CNV detection to assigning phenotypic contribution of specific genes remains largely intractable. We have taken an orthogonal approach to the problem, grounded on two key observations: a) that some CNVs associated with neurodevelopmental traits exhibit quantitative anatomical phenotypic surrogates; and b) that some CNVs manifest in reciprocal relationships (deletions and duplications of the same or overlapping genomic segment) with either similar or mirroring clinical phenotypes. Grounded on these observations, we have performed systematic overexpression and suppression studies in zebrafish embryos and have identified KCTD13 and CHD1L as the primary drivers of the neuroanatomical phenotypes associated with the 16p11.2 and 1q21.1 CNVs respectively, results that have been substantiated by the subsequent identification of rare atypical de novo deletions in these two genes in patients with autism spectrum disorders (ASD). Here we propose to develop further our tools to systematically dissect other reciprocal CNVs associated with neurocognitive traits. Under a series of filters that select for number of protein encoding genes, and mandate tractable anatomical features that can be recapitulated in zebrafish embryos, we will focus initially on 12 CNVs and assay in vivo the possible contribution of each gene contained within these lesions. Additionally, we will ask whether concomitant dosage misregulation of the primary CNV driver locus and each additional gene within the CNV might influence the expressivity of relevant anatomical, quantitative phenotypes. For the resulting group of candidate or contributing CNV driver genes, we will ask whether these genes a) are also involved in atypical, rare deletions identified by high resolution array comparative genomic hybridization (aCGH) datasets generated from cohorts with an enrichment of neurocognitive phenotypes; and b) bear point mutations in ASD exomes that will be functionally tested using a zebrafish model to assay pathogenicity and direction of effect. Finally, we will ask whether testing of all alleles detected for each transcript in cases and controls might reveal a mutational burden at these loci that is invisible by statistical means alone. Together, these data will identify a number of genes that drive neurocognitive effects in humans and provide an efficient platform for the systematic dissection of CNVs discovered in patient exomes and genomes.

 描述（由适用提供）：尽管基因组技术取得了重大进展，但遗传数据与临床管理的整合仍然受到挑战。对于拷贝数变异（CNV），通常会干扰数十个基因的剂量的病变特别令人发指，正如最近的数据所表明的那样，是遗传疾病的主要因素，最著名的是神经发育特征。最近在检测基因组病变方面提供了卓越分辨率的进展加速了患者中CNV的发现。但是，除了CNV内离散基因的点突变的罕见病例外，从CNV检测到分配特定基因的表型贡献的过渡仍然很棘手。我们已经针对该问题采取了正交方法，基于两个关键观察：a）一些与神经发育特征相关的CNV暴露了定量解剖表型替代物； b）某些CNV与相似或镜像临床表型的相互关系（删除和重复或重叠的基因组段）中表现出来。基于这些观察，我们在斑马鱼胚胎中进行了系统的过表达和抑制研究，并确定KCTD13和CHD1L是神经解剖表型的主要驱动因素，分别与16p11.2和1q21.1 CNV相关的自身识别的结果分别鉴定出了这些遗传，这些结果已证实了这些遗传，这些遗传已被证明了这些遗传的遗传。频谱障碍（ASD）。在这里，我们建议开发进一步的工具，以系统地剖析与神经认知性状相关的其他相互CNV。在一系列滤镜中，可以选择蛋白质编码基因的数量，并要求可以在斑马鱼胚胎中概括的可拖动解剖特征，我们最初将重点放在12个CNV上，并在体内分析这些病变中每个基因的可能贡献。此外，我们将询问原发性CNV驱动器基因座和CNV中的每个其他基因的同时剂量不调节是否可能影响相关解剖学，定量表型的表现。对于最终的候选者或贡献CNV驱动基因的组，我们将询问这些基因是否也参与了非典型，罕见的缺失，这是由高分辨率阵列比较基因组杂交（ACGH）数据集所鉴定的，该数据集由具有富集神经认知表型的同类人群产生。 b）ASD外显子体中的熊点突变将在功能上使用斑马鱼模型进行功能测试，以测定致病性和效果方向。最后，我们将询问是否检测到所有等位基因的测试 对于每个成绩单，在情况和对照组中可能会揭示这些基因座的突变烧伤，仅统计手段就看不见。总之，这些数据将确定许多驱动人类神经认知效应的基因，并为患者外部和基因组中发现的CNV的系统解剖提供有效的平台。