Developing Informatics Technologies to Model Cancer Gene Regulation

项目摘要/摘要 全基因组研究表明，包括转录因子在内的反式作用因子、染色质 调节因子和其他染色质相关因子在癌症中经常发生突变，重申了这种异常 基因调控是肿瘤发生的关键机制。这些反式作用因子调节的方式 对全基因组基础上的转录知之甚少，促使越来越多的芯片序列和 DNase-SEQ实验定位全基因组转录因子结合(Cstrome)和染色质状态 (表观基因组)。通过对CHIP-SEQ和CHIP-SEQ的分析，获得了新的和重要的生物学见解 DNASE-SEQ数据与其他已发布的芯片-SEQ和DNASE-SEQ数据集的集成以及表达式 配置文件。然而，大多数癌症生物学家发现环磷酰胺和环磷酰胺的计算数据分析和整合 表观基因组数据是此类研究的主要瓶颈，因为缺乏信息学专业知识和 基础设施。这项建议的目标是发展信息学技术，以改善 芯片序列和DNA序列数据的获取、分析、集成和再利用，以便 实验癌症生物学家建立癌症转录和表观遗传基因调控模型 研究。 具体地说，我们建议开发信息学技术来解决以下三个关键方面 表观基因组和基因组数据分析。首先，我们将实施自动化数据收集的软件， 加工和质量控制，支持各种类型的未发布和公共芯片-seq和 要分析的DNase-seq数据，并将其转换为便于使用的统计数据和格式 综合分析。其次，我们将开发系统，允许基因表达数据 用蛋白质组和表观基因组数据进行解释，以阐明调控机制。第三，我们 将开发工具来快速准确地识别信息丰富的公共数据集并进行推断 调节和相互作用的组合规则。最后，我们将发展基础设施和 接口来托管在前三个目标中开发的算法和工具，并提供 实验癌症生物学家具有灵活和直观的用户体验。我们将设计我们的 易于与补充软件系统和数据库交互的软件。该软件 在这个提议中开发的将是免费开放源码的，我们将与我们的 协作者和用户改进其功能和用户界面。

Project Summary / Abstract Genome-wide studies have demonstrated that trans-acting factors, including transcription factors, chromatin regulators and other chromatin-associated factors, are frequently mutated in cancer, reaffirming that aberrant gene regulation is a key mechanism in oncogenesis. The way in which these trans-acting factors regulate transcription on a genome-wide basis is poorly understood, motiving ever increasing number of ChIP-seq and DNase-seq experiments to map genome-wide transcription factor binding (cistrome) and chromatin status (epigenome). Novel and significant biological insights have been gained through the analysis of ChIP-seq and DNase-seq data integrated with other published ChIP-seq and DNase-seq data sets as well as expression profiles. Most cancer biologists, however, find computational data analysis and integration of cistrome and epigenome data to be the major bottleneck of such studies due to the lack of informatics expertise and infrastructure. The objective of this proposal is to develop the informatics technologies to improve the acquisition, analysis, integration and reuse of ChIP-seq and DNase-seq data so as to allow experimental cancer biologists to model transcriptional and epigenetic gene regulation in cancer research. Specifically, we propose to develop informatics technologies to address three critical aspects of epigenome and cistrome data analysis. First, we will implement software to automate data collection, processing and quality control, enabling diverse types of unpublished and public ChIP-seq and DNase-seq data to be analyzed and converted into statistics and formats that can be readily used for integrative analysis. Second, we will develop systems to allow gene expression data to be interpreted with cistrome and epigenome data in order to elucidate regulatory mechanisms. Third, we will develop tools to quickly and accurately identify informative public datasets and to infer combinatorial rules of regulation and interactions. Finally, we will develop the infrastructure and interface to host the algorithms and tools developed in the first three aims, and provide the experimental cancer biologists with a flexible and intuitive user experience. We will design our software to interact easily with complementary software systems and databases. The software developed in this proposal will be freely available open-source, and we will work with our collaborators and users to improve its functions and user interface.