Deconstructing Reciprocal Genomic Disorders by Integration of Genome Engineering and Cellular Modeling

人类基因组研究的一个重要目标是识别和表征遗传贡献者 神经发育性疾病我们基因组特定片段的反复缺失和重复 已经成为在表现出异常的患者中发现的一些最常见的突变， 神经发育总的来说，这些基因组的丢失和获得解释了约5-10%的自闭症谱系障碍， 精神分裂症和智力残疾。尽管人们对这些重排及其相关的 疾病，相互基因组疾病（RGDs），相对较少的研究已经解决了他们的功能 在分子水平上的后果。该项目将利用基因组编辑技术生成一系列 与同基因背景相比具有感兴趣的缺失或重复的细胞系。RNA测序将 作为一个平台，以研究全球变化的基因表达所造成的每一个重排， 体外神经元分化的过程。首先，我将建立，区分和表征细胞 十个RGD的模型来描述和比较在转录水平上缺失和重复的转录结果， 10个基因组间隔（Aim 1）。其次，我将开发一种并行基因组工程的方法，并将其应用于 获得具有改变剂量的较小片段和四个RGD区域内的单个基因的细胞系（Aim 2）。 第三，我将区分和表征具有这些较小重排的细胞系，以确定遗传驱动因素 在四种相应的RGD中观察到潜在的失调（目标3）。这项研究将提供一个 最常见的RGD重排的转录效应的详细评估和比较。的 平行的基因组编辑策略将免费提供给科学界，让研究人员 以产生数百或数千个仅在特定的感兴趣的突变上不同的等基因细胞系。 最后，遗传驱动分析有望在神经发育疾病的病因学中发现新的基因。 总的来说，通过提高我们对RGDs的分子理解，这项研究将为开发有效的 有针对性的治疗

An important goal of human genomic research is the identification and characterization of genetic contributors to neurodevelopmental disease. Recurrent deletions and duplications of specific segments of our genome have emerged as some of the most common mutations identified in patients showing abnormal neurodevelopment. Collectively, these genomic losses and gains explain ~5-10% of autism spectrum disorder, schizophrenia, and intellectual disability. Despite intense interest in these rearrangements and their associated diseases, reciprocal genomic disorders (RGDs), relatively few studies have addressed their functional consequences at the molecular level. This project will leverage genome editing technology to generate a series of cell lines with deletions or duplications of interest against an isogenic background. RNA sequencing will then serve as a platform to investigate global changes in gene expression resulting from each rearrangement over the course of in vitro neuronal differentiation. First, I will establish, differentiate, and characterize cellular models for ten RGDs to describe and compare the transcriptional consequences of deletion and duplication at ten genomic intervals (Aim 1). Second, I will develop a method for parallel genome engineering and apply it to obtain cell lines with altered dosage of smaller segments and single genes within four RGD regions (Aim 2). Third, I will differentiate and characterize cell lines with these smaller rearrangements to identify genetic drivers underlying dysregulation observed in the four corresponding RGDs (Aim 3). This research will provide a detailed assessment and comparison of transcriptional effects of the most common RGD rearrangements. The parallel genome editing strategy will be made freely available to the scientific community, allowing researchers to generate hundreds or thousands of isogenic cell lines differing only by specified mutations of interest. Finally, genetic driver analyses promise to implicate new genes in the etiology of neurodevelopmental disease. Overall, by enhancing our molecular understanding of RGDs, this study will inform efforts to develop effective targeted treatments.