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

通过基因组工程和细胞建模的整合解构相互的基因组疾病

基本信息

批准号：
9470125
负责人：
Alexander Nuttle
金额：
$ 5.72万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-09-19 至 2019-09-18
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9470125
关键词：
16p11.2 Accounting Address Architecture Attention deficit hyperactivity disorder Autistic Disorder Biological Bipolar Disorder Cell Culture Techniques Cell Line Cell model Cells Chromosomes Clinical Clustered Regularly Interspaced Short Palindromic Repeats Communities Copy Number Polymorphism Curiosities DNA Sequence Rearrangement Disease Disease model Engineering Environment Etiology Frequencies Gene Expression Gene Expression Profile Genes Genetic Genetic Predisposition to Disease Genetic Transcription Genetic Variation Genome Genome engineering Genomic Segment Genomics Global Change Goals Human Human Genetics In Vitro Individual Intellectual functioning disability Light Link Meiosis Methods Modeling Molecular Molecular Profiling Morbidity - disease rate Mutation Nature Neurodevelopmental Disorder Neuronal Differentiation Neurons Neurosciences Overlapping Genes Pathogenesis Pathogenicity Pathway Analysis Pathway interactions Patients Phenotype Process Recording of previous events Recurrence Research Research Personnel Risk Rosa Schizophrenia Series Specific qualifier value Symptoms Syndrome Technology Time Training Translating Work autism spectrum disorder disease phenotype dosage experimental study functional genomics genome editing homologous recombination induced pluripotent stem cell insight interest large scale production microdeletion nerve stem cell neurodevelopment neuropsychiatric disorder novel novel strategies post-doctoral training recombinase-mediated cassette exchange research and development stem cells synthetic biology therapeutic development transcriptome transcriptome sequencing transcriptomics

项目摘要

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.

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至神经发育疾病。我们基因组特定片段的反复删除和重复已成为在表现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，这些基因组损失和增益解释了约 5-10% 的自闭症谱系障碍，精神分裂症和智力障碍。尽管人们对这些重新排列及其相关的兴趣浓厚疾病，相互基因组疾病（RGD），相对较少的研究涉及其功能分子水平上的后果。该项目将利用基因组编辑技术生成一系列在同基因背景下具有感兴趣的缺失或重复的细胞系。然后RNA测序将作为一个平台来研究每次重排导致的基因表达的全球变化体外神经元分化过程。首先，我将建立、区分和表征细胞十个 RGD 模型来描述和比较删除和重复的转录后果十个基因组区间（目标 1）。其次，我将开发一种平行基因组工程方法并将其应用于获得四个 RGD 区域内较小片段和单基因剂量发生变化的细胞系（目标 2）。第三，我将通过这些较小的重排来区分和表征细胞系，以识别遗传驱动因素在四个相应的 RGD 中观察到潜在的失调（目标 3）。这项研究将提供最常见 RGD 重排的转录效应的详细评估和比较。这平行基因组编辑策略将免费提供给科学界，使研究人员能够产生数百或数千个仅因特定的感兴趣突变而不同的同基因细胞系。最后，遗传驱动分析有望将新基因与神经发育疾病的病因学联系起来。总的来说，通过增强我们对 RGD 的分子理解，这项研究将为开发有效的 RGD 的努力提供信息。有针对性的治疗。