Massively parallel characterization of psychiatric disease associated regulatory elements in defined cell types

项目总结/摘要 神经元发育异常可导致多种精神疾病。突变破坏蛋白 编码基因已被发现导致这些疾病中的一些，但他们中的大量仍然存在 未破案件各种分子和临床数据表明，基因调控序列的突变可能 是导致这些疾病的主要因素然而，只有少数因果调节突变被发现， 约会这主要是因为功能性调控元件难以识别，特别是在混合细胞中， 例如，大脑发育。此外，这些元素很难在功能上表征， 在这些细胞类型中的高通量方式。为了应对这些挑战，我们建议使用新的单细胞 基因组技术沿着人类原代细胞中的大规模平行报告基因测定（MPRA）， 类器官，以表征成千上万的大脑发育相关的基因，调控元件和途径。 首先，使用跨多个皮质区域的单细胞RNA-seq（scRNA-seq）和ATAC-seq（sci-ATAC-seq）， 在三个发展阶段，我们将产生一个全面的人类大脑皮层下区域的发展， 参与人类大脑发育的基因、调节元件和网络地图（目标1）。接下来我们就 使用类似的技术（scRNA-seq和sci-ATAC-seq）对来自 诱导多能干细胞（iPSC）。我们将比较类器官细胞的调控程序， 在正常的人类大脑发育过程中。为了评估关键转录因子参与的作用， 精神疾病的基因调控途径在发育中的大脑，我们将使用基因组编辑的 相同的遗传背景，在相关的关键转录因子中产生杂合功能丧失突变 在精神疾病中的作用，并评估其对基因表达（scRNA-seq）和基因调控（sci- ATAC-seq）（目的2）。最后，我们将对超过37，500个候选增强子和核苷酸进行功能表征。 使用基于慢病毒的MPRA（lentiMPRA）在从 人类原代细胞和类器官。这些序列中的几个也将在缺乏关键基因的类器官中进行测定。 目的2中缺失的转录因子，以测试这些基因对调节活性的重要性，并鉴定 与调节变体的相互作用（目标3）。所有目标的数据将用于建立基因预测模型， 表达和增强子活性作为调控序列的函数，其将用于设计lentiMPRA 库并使用初始库的结果迭代地改进模型。结合我们的项目将使用切割- scRNA-seq、sci-ATAC-seq和MPRA等边缘技术与先进的计算分析相结合 显著增加功能特征的人类大脑发育调节的数量， 元素以及它们的活性如何在疾病相关突变的存在下变化，以阐明 精神疾病的遗传基础

Project Summary / Abstract Abnormal neuronal development can lead to a wide array of psychiatric disorders. Mutations disrupting protein coding genes have been found to cause some of these disorders but a large number of them still remain unsolved. A variety of molecular and clinical data suggests that mutations in gene regulatory sequences could be a major contributor to these disorders. However, only a few causal regulatory mutations have been found to date. This is primarily because functional regulatory elements are difficult to identify, particularly in mixed cell populations such as the developing brain. In addition, these elements are difficult to functionally characterize in a high-throughput manner in these cell types. To address these challenges, we propose to use novel single-cell genomic technologies along with massively parallel reporter assays (MPRAs) in human primary cells and organoids to characterize thousands of brain development associated genes, regulatory elements and pathways. First, using single cell RNA-seq (scRNA-seq) and ATAC-seq (sci-ATAC-seq) across multiple cortical areas and subcortical regions of developing human brain at three development stages, we will generate a comprehensive map of genes, regulatory elements and networks involved in human brain development (Aim 1). Next, we will use similar techniques (scRNA-seq and sci-ATAC-seq) on human cerebral organoid cultures derived from induced pluripotent stem cells (iPSCs). We will compare regulatory programs in organoid cells to cells present during normal human brain development. To assess the contribution of key transcription factors involved in psychiatric disorders to gene regulatory pathways in the developing brain, we will use genome editing on the same genetic background to create heterozygous loss-of-function mutations in key transcription factors involved in psychiatric disorders and assess their effects on gene expression (scRNA-seq) and gene regulation (sci- ATAC-seq) (Aim 2). Finally, we will functionally characterize over 37,500 candidate enhancers and nucleotide variants within them using a lentiviral-based MPRA (lentiMPRA) in disease-relevant cell types purified from human primary cells and organoids. Several of these sequences will also be assayed in organoids lacking key transcription factors deleted in Aim 2 to test the importance of these genes to regulatory activity and to identify interactions with regulatory variants (Aim 3). Data from all aims will be used to build predictive models of gene expression and enhancer activity as a function of regulatory sequences, which will be used to design lentiMPRA libraries and iteratively improve models using results from initial libraries. Combined our project will use cutting- edge techniques such as scRNA-seq, sci-ATAC-seq and MPRA coupled with advanced computational analyses to significantly increase the number of functionally characterized human brain developmental regulatory elements and how their activity changes in the presence of disease associated mutations to shed light on the genetic basis for psychiatric disorders.