High resolution dissection of oncogene enhancer networks via CRISPR screening and live-cell imaging.

通过 CRISPR 筛选和活细胞成像对癌基因增强子网络进行高分辨率解剖。

• 批准号: 10671756
• 负责人: Lei Stanley Qi
• 金额: $ 44.24万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10671756
• 关键词: 3-Dimensional; Architecture; BCL2 gene; Biology; CRISPR interference; CRISPR screen; CRISPR-mediated transcriptional activation; CRISPR/Cas technology; Cancer cell line; Cells; Chromatin; Chromatin Structure; Clustered Regularly Interspaced Short Palindromic Repeats; Color; Complex; DNA; Data; Disease; Dissection; Distant; Elements; Engineering; Enhancers; Exhibits; GATA4 gene; Gene Expression; Gene Expression Regulation; Genes; Genetic Epistasis; Genetic Predisposition to Disease; Genetic Transcription; Genome; Genome engineering; Genomic approach; Growth; Guide RNA; Hela Cells; Human Genome; IRF1 gene; Image; Imaging technology; Individual; K-562; K562 Cells; Leukemic Cell; Libraries; MYC gene; Machine Learning; Malignant Neoplasms; Maps; Mediating; Mediator; Messenger RNA; Methods; Modeling; Myeloid Leukemia; Oncogenes; Pattern; Penetrance; Phase; Physical condensation; Play; Promoter Regions; Proteins; RNA; Regulation; Regulatory Element; Resolution; Role; Single Nucleotide Polymorphism; Stretching; Techniques; Testing; Time; Transcription Coactivator; Translating; Untranslated RNA; Variant; Work; biological systems; cancer cell; cancer risk; cancer type; cell type; clinical risk; computer studies; design; disorder risk; experimental study; gene network; genetic association; genetic variant; genome wide association study; genomic locus; live cell imaging; machine learning model; mammalian genome; promoter; real time monitoring; screening; ultra high resolution; virulence gene

ABSTRACT Non-coding elements comprise 98% of the human genome. The coordination of non-coding regulatory elements in the mammalian genome plays a pivotal role in controlling gene expression. Both experimental and computational studies reveal that pathogenic genes involved in complex diseases, including oncogenes, are regulated by a large number of enhancers, implying the existence of a complex interdependent regulatory network of enhancers in modulating and maintaining expression of these genes. Genome-Wide Association Studies (GWAS) reveal that non-coding regulatory elements, including enhancers, are hotspots for the genetic predisposition to disease. To determine causal relationships between chromatin architecture and gene transcription, perturbation in a biological system is necessary. Recent advances in CRISPR-based genome engineering and live cell imaging technologies have enabled new techniques for ultrahigh resolution interrogation of the function of various genome regulatory elements and how they relate to gene expression. In preliminary studies in our lab, we performed a targeted CRISPR interference (CRISPRi) based screen to study how the 7 MYC enhancers present in K562 cells work together to co-regulate this oncogene. We created a library with >87,000 pairs of gRNAs targeting the MYC enhancers to understand the epistatic network of gene regulation underlying MYC expression. We found that when a subset of enhancer pairs were targeted together, they exhibited a more dramatic than expected reduction in growth rate. We developed a model that divides MYC enhancers into 2 layers that work together with varying degrees of efficiency to co-regulate MYC expression in K562 cells. Here, we seek to expand these preliminary results to examine additional oncogenes and perform these experiments in additional cell types. In addition, we will combine perturbation of oncogene enhancers with CRISPR-based live cell imaging (termed CRISPR LiveFISH), that allows for the dynamic imaging of multiple genomic loci, mRNA, and protein components in living cells. In Aim 1, we will develop an ultrahigh-resolution multiplexed CRISPRi/a tiling screens platform to dissect enhancer interactions of different oncogenes in different cancer cell lines. We will perform multiplexed CRISPRi/CRISPRa screens to inhibit or activate pairs of enhancers with an ultrahigh spatial resolution (~20bp) controlling four oncogenes (MYC, CCND, BCL2, PDE4DIP) in K562 and HeLa cells. In Aim 2, we will characterize the dynamic real-time interactions between transcriptional coactivators, mediators, multiple enhancers, promoters, and RNA transcription during CRISPRi/a-mediated perturbation. We will monitor real-time dynamics of different enhancers, promotors, RNA transcription, and the transcriptional coactivator proteins BRD4, IRF1, and Gata4 using LiveFISH with and without enhancer perturbation. Altogether, we seek to apply new CRISPR technologies developed in our lab to create a model of how oncogene enhancers are dynamically regulated across multiple oncogenes and in multiple types of cancer cells.

摘要 非编码元件占人类基因组的98%。非编码调控元件的协调 在哺乳动物中，基因组在控制基因表达方面起着举足轻重的作用。试验性和 计算研究表明，涉及复杂疾病的致病基因，包括癌基因，是 受大量增强子调控，暗示存在复杂的相互依存的调控 调节和维持这些基因表达的增强子网络。全基因组关联 研究表明，包括增强子在内的非编码调控元件是遗传研究的热点 疾病的易感性。确定染色质结构和基因之间的因果关系 转录，生物系统中的扰动是必要的。基于CRISPR的基因组研究进展 工程技术和活细胞成像技术使超高分辨率审讯的新技术成为可能 各种基因组调控元件的功能以及它们与基因表达的关系。在预赛中 在我们的实验室中，我们进行了基于靶向CRISPR干扰(CRISPRi)的筛查，以研究7 K562细胞中存在的MYC增强子共同作用，共同调节这一癌基因。我们创建了一个库 针对MYC增强子的8.7万对gRNA，以了解基因调控的上位性网络 潜在的MYC表达式。我们发现，当增强子对的子集被一起靶向时，它们 表现出比预期更戏剧性的增长率下降。我们开发了一个模型，将MYC 将增强剂分成两层，以不同程度的效率共同作用，共同调节MYC的表达 K562细胞。在这里，我们寻求扩展这些初步结果以检查更多的癌基因并执行 这些实验是在其他细胞类型上进行的。此外，我们将把癌基因增强剂的扰动与 基于CRISPR的活细胞成像(称为CRISPR LiveFISH)，允许对多个 活细胞中的基因组位置、信使核糖核酸和蛋白质组分。在目标1中，我们将开发一种超高分辨率 多重CRISPRi/a平铺筛选平台剖析不同癌基因在不同肿瘤中的增强子相互作用 癌细胞系。我们将执行多路CRISPRi/CRISPRa筛查来抑制或激活增强子对 以超高空间分辨率(~20BP)控制K562中的四个癌基因(MYC、CCND、BCL2、PDE4DIP) 和HeLa细胞。在目标2中，我们将描述转录之间的动态实时交互作用 CRISPRi/a介导的辅活化子、介体、多个增强子、启动子和RNA转录 微扰。我们将监测不同增强子、启动子、RNA转录和 使用LiveFISH和不加增强子的转录共激活蛋白BRD4、IRF1和GATA4 微扰。总之，我们寻求应用我们实验室开发的新CRISPR技术来创建 癌基因增强子是如何在多种癌基因和多种癌症中动态调节的 细胞。