Linking Psychiatric Genetics to Cell-Type Specific Enhancer Function

项目总结 全基因组关联研究(GWAS)提供了强有力的统计证据将个体序列联系起来 疾病风险增加的变种。然而，到目前为止，GWAS确定的大多数风险变种， 包括精神障碍的那些，不会影响蛋白质编码序列，而是映射到非编码序列 DNA仅凭GWAs并不能直接洞察这些变异导致风险增加的机制。 人们普遍认为，许多基因都会影响远距离作用的转录增强子的功能，但 历史上对人类基因组中非编码功能序列的糟糕注释使它们的 口译具有挑战性。在过去的十年里，我们的实验室和其他实验室在以下方面取得了实质性进展 大规模识别基因组中的增强子。例如，我们的团队使用了MICE和 人脑组织，以确定最初收集的发育活性脑增强剂。此外，由于 ENCODE联盟的成员们，我们生成了第一个描绘大脑的高分辨率时间序列 小鼠出生前发育过程中的染色质景观。这些资源，以及互补的 来自美国国立卫生研究院资助的财团的数据现在可以用来帮助解释GWAs的结果。在这里我们 建议弥合非编码的全球气候分析结果和机械性理解之间的当前差距 精神障碍病因学。我们将结合大量现有的表观基因组资源来 尖端的小鼠工程和单细胞分辨率转录组分析 了解增强子变异是如何增加精神疾病风险的。具体来说，我们将：1)执行 一项对精神障碍的GWA结果和表观预测的脑增强剂的综合分析 识别含有疾病相关变体的调控序列，并对它们进行功能优先排序 验证，2)使用高通量小鼠转基因试验来验证体内预测的增强子和 确定它们活动的确切大脑区域，3)使用转基因的单细胞RNA测序 小鼠确定大脑增强剂发挥作用的确切细胞类型(S)，并在体内使用这些细胞 用功能基因组学方法揭示疾病相关序列变异是否以及如何影响 细胞类型-每个增强子的特定活性。作为精神疾病队列的全基因组测序 为了继续取得进展，我们还将评估这些研究的变种。结合起来，我们的工作将揭示 非编码疾病相关变异体如何改变体内增强子功能，将非编码GWAS的发现与 特定的细胞类型，并提供一个独特的具有良好特性的增强剂小组，可用于标记 离散的神经细胞群体，用于进一步的下游表征。其结果将大大提高 提高我们对非编码序列变化如何导致精神疾病的机械性理解 为潜在的下游疗法提供切入点。

PROJECT SUMMARY Genome-wide association studies (GWAS) provide robust statistical evidence linking individual sequence variants to increased risk of disease. However, the majority of GWAS-identified risk variants identified to date, including those for psychiatric disorders, do not affect protein-coding sequence but instead map to noncoding DNA. GWAS alone yield little direct insight into the mechanisms by which these variants confer increased risk. It is widely assumed that many affect the function of distant-acting transcriptional enhancers, but the historically poor annotation of noncoding functional sequences in the human genome has rendered their interpretation challenging. Over the past decade, our lab and others made substantial progress toward identifying enhancers in the genome at scale. For example, our group has used ChIP-seq from mouse and human brain tissues to identify initial collections of developmentally active brain enhancers. Furthermore, as members of the ENCODE consortium, we generated the first high-resolution time series mapping the brain chromatin landscape throughout mouse prenatal development. These resources, along with complementary data from NIH-funded consortia, are now available to aid in the interpretation of GWAS results. Here we propose to bridge the current gap between noncoding GWAS findings and mechanistic understanding of psychiatric disorder etiology. We will couple extensive pre-existing epigenomic resources to cutting-edge mouse engineering and single cell-resolution transcriptome analyses in order to understand how enhancer variants contribute to psychiatric disease risk. Specifically we will: 1) Perform an integrative analysis of psychiatric disorder GWAS results and epigenomically predicted brain enhancers to identify regulatory sequences that harbor disease-associated variants and prioritize them for functional validation, 2) Use high-throughput mouse transgenic assays to validate predicted enhancers in vivo and determine the exact brain regions in which they are active, 3) Use single cell RNA-sequencing of transgenic mice to determine the exact cell type(s) in which a brain enhancer functions, and 4) Use these in vivo functional genomic methods to uncover whether and how disease-associated sequence variants impact the cell type-specific activity of each enhancer. As whole genome sequencing of psychiatric disease cohorts continues to progress, we will also assess variants from those studies. In combination, our work will uncover how noncoding disease-associated variants alter enhancer function in vivo, link noncoding GWAS findings to specific cell types, and provide a unique panel of well-characterized enhancers that can be used to label discrete neuronal cell populations for further downstream characterization. The results will substantially improve our mechanistic understanding of how noncoding sequence changes contribute to mental illness and provide entry points for potential downstream therapies.