Quantitative Modeling for Chromatin Regulation of Gene Expression in Cancer

癌症基因表达染色质调控的定量模型

• 批准号: 9763334
• 负责人: Chongzhi Zang
• 金额: $ 19.24万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2019-09-02
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9763334
• 关键词: ATAC-seq; Algorithms; Bayesian Analysis; Binding; Binding Sites; Bioinformatics; Biological Process; Cancer Biology; Cells; ChIP-seq; Chromatin; Chromatin Modeling; Chromatin Structure; Communities; Complement; Computer Simulation; Computing Methodologies; DNase I hypersensitive sites sequencing; Data; Data Analyses; Databases; Deoxyribonucleases; Development; Disease; Distal; EZH2 gene; Elements; Enhancers; Epigenetic Process; Event; Gene Expression; Gene Expression Regulation; Genes; Genetic Enhancer Element; Genome; Genomics; Goals; Histones; Human; Knowledge; Laboratories; Malignant Neoplasms; Methodological Studies; Methodology; Methods; Modeling; Molecular; Mutate; Neurofibrosarcoma; Nucleotides; Oncogenic; Pattern; Pharmacotherapy; Play; Proteins; Publishing; Regulation; Regulator Genes; Regulatory Element; Research; Research Training; Resolution; Role; Signal Transduction; System; Techniques; Transcriptional Regulation; base; cancer cell; cancer therapy; career; castration resistant prostate cancer; cell type; computer framework; data resource; epigenetic regulation; experience; genomic data; genomic profiles; histone modification; insight; interest; knock-down; new therapeutic target; next generation sequencing; novel; novel therapeutics; precision oncology; predictive modeling; programs; prostate cancer cell; public health relevance; transcription factor; tumor progression; tumorigenesis; user friendly software

PROJECT SUMMARY Chromatin plays an essential role in transcriptional regulation. Chromatin-related genes are frequently mutated in cancers. Dissecting the functions of chromatin in gene regulation is important for understanding the molecular mechanisms of oncogenesis and tumor progression. As an experienced computational biologist with expertise on ChIP-seq bioinformatics and epigenetics, my research has focused on developing computational methodologies for high-throughput genomic data analysis and computational modeling on chromatin regulation of gene expression. With more independent research training in cancer biology, I will develop my research program on computational cancer epigenetics and develop an independent academic career. Recent studies have demonstrated the feasibility of targeting chromatin regulators for active open regions in the genome as novel therapeutics for cancer treatment. However, the context-specific substrates of chromatin regulators and the mechanisms underlying how chromatin regulates gene expression are largely unclear.. With the advent of next-generation sequencing based high-throughput genomic techniques including ChIP-seq, DNase-seq, and ATAC-seq, a large amount of for genomic profiling data became available, making it possible to systematically decipher the gene regulatory mechanisms with an integrative computational approach. The objective of this project is to develop novel quantitative and computational methodologies for studying epigenetic gene regulation and the functions of chromatin regulators in cancer. Specifically, we propose to develop integrative computational methods that leverage the abundant public ChIP-seq, DNase-seq, and ATAC-seq data for predicting functional regulatory elements and TFs. First (Aim 1), we will develop a method that predicts the functional enhancer elements and associated TFs given any gene set using public histone mark ChIP-seq data across multiple cell types. Second (Aim 2), we will develop a quantitative model to identify the nucleotide-resolution chromatin accessibility dynamics from paired-end DNase-seq or ATAC-seq data with correction of intrinsic biases in the data. Finally (Aim 3), we will integrate publicly available DNase- seq, ATAC-seq, and ChIP-seq data in a comprehensive database and systematically characterize the functions of chromatin regulators with a focus on EZH2 in a few cancer systems, including castration-resistant prostate cancer (CRPC) cells, and malignant peripheral nerve sheath tumors (MPNSTs). These computational methods complement existing bioinformatics methodologies and will have broad applications in the study of cancer epigenetics and gene regulation. The proposed research will fill the knowledge gap between oncogenic drivers and downstream gene expression program, and could provide mechanistic support for development of novel targeted therapeutics for cancer precision medicine.

项目概要 染色质在转录调控中起着重要作用。染色质相关基因经常发生突变 在癌症中。剖析染色质在基因调控中的功能对于理解染色质非常重要 肿瘤发生和肿瘤进展的分子机制。作为一名经验丰富的计算生物学家 我拥有 ChIP-seq 生物信息学和表观遗传学方面的专业知识，我的研究重点是开发计算 高通量基因组数据分析和染色质调控计算建模的方法 的基因表达。通过更多的癌症生物学独立研究培训，我将发展我的研究 计算癌症表观遗传学项目并发展独立的学术生涯。 最近的研究证明了针对活跃开放区域的染色质调节因子的可行性 基因组作为癌症治疗的新疗法。然而，染色质的上下文特异性底物 调节因子和染色质如何调节基因表达的机制在很大程度上尚不清楚。 基于下一代测序的高通量基因组技术（包括 ChIP-seq）的出现， DNase-seq、ATAC-seq等大量基因组分析数据的出现，使得基因组分析成为可能 通过综合计算方法系统地破译基因调控机制。 该项目的目标是开发新的定量和计算方法来研究 表观遗传基因调控和染色质调控因子在癌症中的功能。具体来说，我们建议 开发综合计算方法，利用丰富的公共 ChIP-seq、DNase-seq、 用于预测功能调控元件和转录因子的 ATAC-seq 数据。首先（目标 1），我们将开发 一种使用公共方法预测给定任何基因集的功能增强子元件和相关转录因子的方法 组蛋白标记多种细胞类型的 ChIP-seq 数据。其次（目标 2），我们将开发一个定量模型 从配对末端 DNase-seq 或 ATAC-seq 中识别核苷酸分辨率染色质可及性动态 修正了数据中固有偏差的数据。最后（目标 3），我们将集成公开可用的 DNase- seq、ATAC-seq 和 ChIP-seq 数据存储在综合数据库中，并系统地表征 染色质调节因子在一些癌症系统（包括去势抵抗性癌症）中的功能，重点是 EZH2 前列腺癌（CRPC）细胞和恶性周围神经鞘瘤（MPNST）。这些计算 方法补充了现有的生物信息学方法，并将在研究中具有广泛的应用 癌症表观遗传学和基因调控。拟议的研究将填补致癌物之间的知识空白 驱动程序和下游基因表达程序，并可以为开发提供机制支持 癌症精准医学的新型靶向疗法。