Tools for annotating mutations in the 3D cancer genome

用于注释 3D 癌症基因组突变的工具

基本信息

批准号：
9899958
负责人：
Kai Tan
金额：
$ 32.15万
依托单位：
CHILDREN'S HOSP OF PHILADELPHIA
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-04-19 至 2023-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9899958
关键词：
3-Dimensional Affect Architecture Area Benchmarking Cancer Etiology Chromatin Collaborations Communication Communities Computer software Computing Methodologies DNA Data Databases Disease Enhancers Gaussian model Genetic Enhancer Element Genetic Transcription Genome Genomics Goals Informatics Investigation Letters Malignant Neoplasms Methods Modeling Mutation Mutation Analysis Oncogene Deregulation Performance Point Mutation Regulator Genes Research Research Personnel Role Seminal Standardization Structure Structure-Activity Relationship Technology Tissues Transact Untranslated RNA Variant base bioinformatics tool cancer cell cancer genome cancer type causal variant cell type data integration epigenomics genome database genome sequencing innovation insertion/deletion mutation insight programs promoter repository tool transcriptomics tumor tumorigenesis

项目摘要

Project Summary Genome sequencing has revealed thousands of mutations associated with various types of cancer. The vast majority of the identified variants are noncoding. A number of seminal studies have revealed that noncoding mutations can disrupt 3D genome architecture and cause cancer. To accelerate discovery in this emerging area of investigation, bioinformatics tools for integrative analysis of mutation and 3D genome organization data is critically needed. In this project, we will develop a suite of bioinformatics tools to predict the hierarchy of 3D genome organization and use such information to interpret and identify causal noncoding mutations. In aim 1, we will develop a method for identifying mutations that disrupt chromatin domain and subdomain boundaries in cancers. In aim 2, we will use disease-relevant enhancer- promoter network for prioritizing mutations that disrupt enhancer function. In aim 3, we will develop a 3D cancer genome database for curating, querying and visualizing chromatin interaction data together with transcriptomic, epigenomic, and mutation data.

项目概要基因组测序揭示了与各种类型相关的数千个突变癌症。绝大多数已识别的变体都是非编码的。一些开创性研究表明非编码突变可以破坏 3D 基因组建筑并导致癌症。加速这一新兴领域的发现用于突变和 3D 基因组综合分析的调查、生物信息学工具迫切需要组织数据。在这个项目中，我们将开发一套预测 3D 基因组组织层次结构并使用此类工具的生物信息学工具解释和识别因果非编码突变的信息。在目标 1 中，我们将开发一种方法来识别破坏染色质结构域的突变癌症的子域边界。在目标 2 中，我们将使用与疾病相关的增强剂—— 启动子网络，用于优先考虑破坏增强子功能的突变。在目标 3 中，我们将开发用于管理、查询和可视化的 3D 癌症基因组数据库染色质相互作用数据以及转录组、表观基因组和突变数据。