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 在控制基因表达中起着关键作用。实验和 计算研究表明，复杂疾病中涉及的致病基因，包括癌基因， 由大量的增强子调控，这意味着存在一个复杂的相互依赖的调控机制。 增强子网络在调节和维持这些基因的表达。全基因组关联 研究（GWAS）表明，非编码调控元件，包括增强子，是遗传调控的热点。 易患病的体质为了确定染色质结构和基因之间的因果关系 转录，在生物系统中的扰动是必要的。基于CRISPR的基因组研究进展 工程学和活细胞成像技术已经使高分辨率询问的新技术成为可能 各种基因组调控元件的功能以及它们如何与基因表达相关。初步 在我们实验室的研究中，我们进行了一项基于靶向CRISPR干扰（CRISPRi）的筛选，以研究7种基因是如何被激活的。 K562细胞中存在的MYC增强子共同调节该癌基因。我们创建了一个图书馆， > 87，000对靶向MYC增强子的gRNA，以了解基因调控的上位性网络 潜在的MYC表达。我们发现，当一个子集的增强子对一起靶向时，它们 显示出比预期更剧烈的增长率下降。我们开发了一个模型， 增强子分成2层，它们以不同程度的效率共同调节MYC表达。 K562细胞。在这里，我们试图扩大这些初步结果，以检查其他癌基因，并执行 这些实验在其他细胞类型。此外，我们将结合癌基因增强子的联合收割机扰动与 基于CRISPR的活细胞成像（称为CRISPR LiveFISH），允许对多种细胞进行动态成像 活细胞中的基因组位点、mRNA和蛋白质组分。在目标1中，我们将开发超高分辨率 多重CRISPRi/a平铺筛选平台，以剖析不同肿瘤细胞中不同癌基因的增强子相互作用， 癌细胞系。我们将进行多重CRISPRi/CRISPRa筛选，以抑制或激活增强子对， 在K562中，空间分辨率约为20 bp，控制四种癌基因（MYC，CCND，BCL 2，PDE 4DIP） HeLa细胞在目标2中，我们将描述转录因子之间的动态实时相互作用， CRISPRi/a介导的转录过程中的共激活子、介导子、多重增强子、启动子和RNA转录 扰动我们将监测不同增强子，启动子，RNA转录和转录的实时动态。 转录辅激活蛋白BRD 4、IRF 1和Gata 4，使用有和没有增强子的LiveFISH 扰动总之，我们寻求应用我们实验室开发的新CRISPR技术来创建一个模型， 癌基因增强子如何在多种癌基因和多种类型的癌症中动态调节 细胞