A TOOLKIT FOR IDENTIFYING CAUSAL VARIANTS IN TRANSCRIPTIONAL ENHANCERS

识别转录增强子因果变异的工具包

• 批准号: 9324326
• 负责人: Kai Tan
• 金额: $ 31.92万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9324326
• 关键词: Address; Affect; Algorithms; Autoimmune Diseases; Autoimmunity; Binding Sites; Biological Assay; Cells; ChIP-seq; Chromatin; Communities; Complex; Computer software; Computing Methodologies; Databases; Disease; Documentation; Enhancers; Etiology; FOXP3 gene; Gene Expression; Gene Expression Regulation; Gene Targeting; Genes; Genetic Transcription; Genetic Variation; Genomics; Genotype; Goals; Human; Human Genome; IL2RA gene; Immune Tolerance; Insulin-Dependent Diabetes Mellitus; Knowledge; Learning; Location; Luciferases; Maintenance; Maps; Methods; Molecular Conformation; Mutation; Outcome; Pattern; Phenotype; Play; Prevention; Quantitative Trait Loci; Regulatory T-Lymphocyte; Reporter; Reporting; Role; Site-Directed Mutagenesis; Supervision; Testing; Tissues; Training; Variant; base; cell type; computer framework; design; diabetes control; disease phenotype; expectation; genetic variant; genome wide association study; genome-wide; histone modification; human disease; immunoregulation; open source; prediction algorithm; promoter; public health relevance; rare variant; screening; transcription factor; user friendly software

DESCRIPTION (provided by applicant): Our long-term goal is to understand the mechanisms by which sequence variations in enhancers affect gene expression. Genome-wide association study (GWAS) and expression quantitative trait loci (eQTL) mapping have revealed thousands of sequence variants that are associated with common diseases and gene expression variations. A large portion of the associated variants is located far away from genes, making them difficult to interpret. Given its abundance and essential role in gene regulation, sequence variants in transcriptional enhancers could be the cause of many phenotypic variations. Currently, identifying such variants remains a challenge because of several hurdles: i) rudimentary annotation of tissue-specific enhancers; ii) lack of strategies to precisely pinpoint the identity and location of transcription factor binding sites (TFBSs) within an enhancer; and iii lack of strategies to assign enhancer targets. By addressing these hurdles, the objective of this project is to design and test a computational framework that enables systematic and rapid screen of enhancer sequence variants that cause complex diseases. As an ultimate test of our approach, we will apply our computational strategy to screen and characterize enhancer variants that are associated with a common autoimmune disease, Type 1 Diabetes. To make the methods developed in this project useful to a much broader community of users, we will develop an open-source software suite and a database dedicated to the analysis and curation of regulatory mutations in enhancers. It is anticipated that the outcomes of this project will have an important positive impact because it promises to significantly accelerate the discovery and systematic documentation of causal genetic variants in the noncoding portion of the human genome.

描述（由申请人提供）：我们的长期目标是了解增强子序列变异影响基因表达的机制。全基因组关联研究 (GWAS) 和表达数量性状位点 (eQTL) 作图揭示了与常见疾病和基因表达变异相关的数千个序列变异。大部分相关变异位于远离基因的位置，使得它们难以解释。鉴于转录增强子的丰富性和在基因调控中的重要作用，转录增强子的序列变异可能是许多表型变异的原因。目前，由于存在几个障碍，识别此类变异仍然是一个挑战：i）组织特异性增强子的基本注释； ii) 缺乏精确定位增强子内转录因子结合位点 (TFBS) 的身份和位置的策略； iii 缺乏分配增强目标的策略。通过解决这些障碍，该项目的目标是设计和测试一个计算框架，能够系统、快速地筛选导致复杂疾病的增强子序列变异。作为对我们方法的最终测试，我们将应用我们的计算策略来筛选和表征与常见自身免疫性疾病 1 型糖尿病相关的增强子变体。为了使该项目中开发的方法对更广泛的用户群体有用，我们将开发一个开源软件套件和一个专门用于分析和管理增强子调控突变的数据库。预计该项目的成果将 重要的积极影响，因为它有望显着加速人类基因组非编码部分中因果遗传变异的发现和系统记录。