Temporal Single Cell RNAseq to Identify Genes and Pathways Affected by 15q11.2 Duplication in Autism iPSC-Derived Differentiating Cortical Neurons

项目摘要 我们的目标是建立一个分化皮层神经元祖细胞的单细胞RNAseq数据库 本发明提供了用于神经细胞移植的来源于患者特异性诱导多能干细胞（iPSC）的NPC和神经元。 发育性疾病（NDDs）。该数据库还将包括关于分化、形态、形成 和功能的突触，注释的分析结果，并将支持最先进的 单细胞RNAseq生物信息学工具。我们将提供所有这些，以及相应的NPC， 神经元作为研究试剂，作为支持该领域NDD学术研究和药物发现的工具。 在2002年出生的儿童中，每68个中就有一个被诊断患有自闭症谱系障碍（ASD），这是一种公共卫生疾病。 在美国优先。ASD的遗传易感性被认为是通过改变 神经元发育，部分通过改变基因表达来证明。患者特异性诱导多能 干细胞（iPSC）已被证明通过神经原性免疫反应再现特定的疾病表型。 可以作为有效的疾病模型。因此，单细胞RNAseq沿着可及的和可被识别的RNA分子， 将ASD特异性iPSC分化为神经祖细胞和神经元亚型的受控过程可以 为ASD发病机制和生物标志物的时间和多谱系维度提供见解， 诊断、进展和治疗发现。 15q11.2的拷贝数变异（CNVS）是神经系统疾病的一个突出风险因素，包括 自闭症，癫痫，精神分裂症。15 q11-q13重复/三重复代表了最常见的 ASD患者（高达3%）。复制和微缺失都可能导致相同的疾病， 这表明该区域在正常神经功能中的重要性，以及研究其影响的必要性。 重复和删除，以便充分了解机制。 I期利用来自ASD患者的四个15q11.2重复iPSC系和两个对照iPSC系： 目的1：表征ASD和对照iPSC衍生的神经元的神经分化。分化iPSC 分为皮层NPC、谷氨酸能和GABA能亚型。通过以下方式确定ASD线路中的缺陷 突触的形态学研究和结构分析。 目的2：在9个细胞中生成区分NPC和神经元亚型的单细胞RNAseq数据集。 分化过程中的时间点。 目标3：进行生物信息学分析。重建神经元的分子动力学 分化实验条件包括采样频率和细胞数。识别， 验证15q11.2复制对神经元分化和功能影响的分子特征。 第二阶段：利用这里建立的实验条件，从 将携带不同基因突变的多个ASD iPSC系纳入数据库;建立数据库 结构和用户界面，并寻求确定异常分化和功能发展所造成的 ASD突变以及在多种疾病中常见和差异影响的基因和途径， ASD突变。我们将投入资源，用我们自己的发现和那些 以增强其对订户的效用。

PROJECT SUMMARY We aim to establish a single-cell RNAseq database of differentiating cortical neuronal progenitors (NPCs) and neurons derived from patient-specific induced pluripotent stem cells (iPSCs) for neuro- developmental diseases (NDDs). The database will also include data on differentiation, morphology, formation and functionality of synapses, annotations of analytical findings, and will be supported by the most advanced single-cell RNAseq bioinformatics tools. We will provide all this, together with corresponding NPCs and neurons for research reagents, as tool to support academic research and drug discovery for NDDs in the field. One in 68 children born in 2002 are diagnosed with Autism Spectrum Disorder (ASD), a public health priority in the US. Genetic predispositions in ASD are thought to contribute to the primary pathology by altering neuronal development, evidenced partly by altered gene expressions. Patient-specific induced pluripotent stem cells (iPSCs) have been shown to recapitulate specific disease phenotypes through the neurogenic process and can serve as effective disease models. Hence, single-cell RNAseq along the accessible and controlled process of differentiating ASD-specific iPSCs into neural progenitors and subtypes of neurons can provide insights into the temporal and multi-lineage dimensions of ASD pathogenesis and biomarkers for diagnostics, progression, and therapeutics discovery. Copy-number variants (CNVS) at 15q11.2 is a prominent risk factor for neurological disorders including ASD, epilepsy, and schizophrenia. 15q11-q13 duplication/triplication represent the most common CNVs in patients with ASD (up to 3%). Duplications and microdeletions can both lead to the same disorders, suggesting the importance of this region in normal neurological functions and the necessity to study the impact of both duplications and deletions for a full understanding of the mechanisms. Phase I utilizes four 15q11.2 duplication iPSC lines from ASD patients and two control iPSC lines to: Aim 1: Characterize neural differentiation of ASD and control iPSC-derived neurons. Differentiate iPSCs into cortical NPCs, glutamatergic, and GABAergic subtypes. Identify deficits in ASD lines through morphological studies and structural analyses of synapses. Aim 2: Generate single-cell RNAseq datasets of differentiating NPCs and neuronal subtypes at nine time points during differentiation. Aim 3: Perform bioinformatics analyses. Reconstitute the molecular dynamics underlying neuronal differentiation. Validate experimental conditions including sampling frequency and number of cells. Identify, validate molecular signatures underlying 15q11.2 duplication’s impact on neuronal differentiation and functions. Phase II: utilize the experimental conditions established here to generate single-cell RNAseq datasets from multiple ASD iPSC lines that harbor different genetic mutations to be included in the database; build database structure and user interface, and seek to identify aberrant differentiation and functional development caused by ASD mutations as well as genes and pathways that are commonly and differentially affected across multiple ASD mutations. We will devote resources to annotate the database with our own findings and those that are published by peers to enhance its utility to subscribers.