Linking Psychiatric Genetics to Cell-Type Specific Enhancer Function

项目摘要 全基因组关联研究（GWAS）提供了强有力的统计证据， 变异增加疾病风险。然而，迄今为止，大多数GWAS确定的风险变体， 包括那些精神疾病，不影响蛋白质编码序列，而是映射到非编码序列 DNA.单独的GWAS对这些变异增加风险的机制几乎没有直接的了解。 人们普遍认为，许多影响远距离作用的转录增强子的功能，但 人类基因组中非编码功能序列的历史性注释不足， 诠释挑战在过去的十年里，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： 大规模地识别基因组中的增强子。例如，我们的团队使用了来自小鼠的ChIP-seq， 人脑组织，以鉴定发育活性脑增强剂的初始集合。此外如 作为ENCODE联盟的成员，我们生成了第一个绘制大脑的高分辨率时间序列 染色质景观贯穿小鼠产前发育。这些资源，沿着着互补 来自NIH资助的联盟的数据，现在可以帮助解释GWAS结果。这里我们 我建议弥合目前非编码GWAS发现和机械理解之间的差距 精神疾病的病因学我们将结合广泛的现有表观基因组资源， 尖端的小鼠工程和单细胞分辨率转录组分析， 了解增强子变异如何导致精神疾病风险。具体而言，我们将：1）执行 精神疾病GWAS结果和表观基因组学预测的脑增强剂的综合分析， 鉴定携带疾病相关变体的调控序列，并将它们按功能优先级排序， 2）使用高通量小鼠转基因测定来体内验证预测的增强子， 确定它们活跃的确切大脑区域，3）使用转基因单细胞RNA测序 小鼠以确定脑增强子发挥功能的确切细胞类型，以及4）在体内使用这些细胞类型 功能基因组方法，以揭示疾病相关的序列变异是否以及如何影响 每个增强子的细胞类型特异性活性。作为精神疾病队列的全基因组测序 继续取得进展，我们还将评估这些研究的变体。结合起来，我们的工作将揭示 非编码疾病相关变体如何改变体内增强子功能，将非编码GWAS发现与 特定的细胞类型，并提供了一组独特的良好表征的增强子，可用于标记 离散的神经元细胞群体用于进一步的下游表征。结果将大大 提高我们对非编码序列变化如何导致精神疾病的机械理解， 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.