Novel statistical tools for cell line specific epigenetic analysis

用于细胞系特异性表观遗传分析的新型统计工具

• 批准号: 8825711
• 负责人: Wenxuan Zhong
• 金额: $ 34.85万
• 依托单位: UNIVERSITY OF GEORGIA
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-15 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8825711
• 关键词: Aberrant DNA Methylation; Affect; Algorithms; Alzheimer' s Disease; Angelman Syndrome; Autoimmune Diseases; Cell Line; Chronic Lymphocytic Leukemia; Communities; Complex; Computer software; DNA Methylation; Data; Data Analyses; Development; Diabetes Mellitus; Dimensions; Disease; Epigenetic Process; Funding; Gene Expression; Gene Expression Profiling; Gene Expression Regulation; Genes; Genetic Transcription; Genomics; Goals; Grant; Heart Diseases; Human; Intervention; Lead; Malignant Neoplasms; Methylation; Modeling; Modification; Nucleotides; Pattern; Prader-Willi Syndrome; Procedures; Process; Property; Regulation; Research; Role; Sensitivity and Specificity; Solutions; Specificity; Statistical Methods; Statistical Models; Techniques; Technology; Testing; Theoretical Studies; Transcriptional Regulation; Weight; age related; analytical method; base; cell type; computerized tools; design; flexibility; genetic regulatory protein; genome wide association study; genome-wide; high throughput analysis; human disease; improved; next generation sequencing; novel; public health relevance; theories; tool; transcription factor; transcriptome sequencing; user-friendly

DESCRIPTION (provided by applicant): Gene transcription is a complex and tightly regulated process. Accumulating evidence has indicated that it was concertedly regulated by regulatory proteins, mainly transcription factors (TF), and epigenetic modifications. The role of TFs in the regulation of gene transcription has been extensively studied, but much less understood is the role of epigenetic modification. DNA methylation has been newly discovered as key controller in gene transcription too. Aberrant DNA methylation changes can cause a number of human diseases such as developmental diseases (ICF syndrome, Prader-Willi and Angelman syndromes etc), aging related diseases (i.e. Alzheimer's disease), heart disease, diabetes, and autoimmune diseases. Moreover, large amount of evidence implicated that DNA methylation is a key player in cancer development. The overarching goal of this project is to develop a set of novel statistical tools to identify the differentially expressed DNA methylation patterns and understand the roles of DNA methylation in gene transcriptional regulation. In particular, we intends to achieve three scientific goals: 1) improving the sensitivity and specificity in identifyng the single nucleotide based DNA methylation change; 2) bridging the research gap in DNA methylation analysis and gene expression analysis by using the sufficient dimension reduction model; 3) developing a new statistical framework to overcome the grand challenges in epigenetic analysis and build the mathematical underpinning. With the rapid development of next generation sequencing technique in the past decades, where large amount of epigenetic and genomic data are routinely collected, processed and stored, we believe our efforts will not only extend our understanding of the regulatory mechanism in gene transcription but also lead to (1) fundamental advances in DNA methylation analysis, (2) development and refinement of technology for the rapid and continuous identification of gene regulation related DNA methylation cites, (3) prototyping of the epigenetic chip for human intervention of certain disease.

描述（由申请人提供）：基因转录是一个复杂且受到严格调控的过程。越来越多的证据表明，它受到调节蛋白（主要是转录因子（TF））和表观遗传修饰的协同调节。转录因子在基因转录调控中的作用已被广泛研究，但对表观遗传修饰的作用知之甚少。 DNA 甲基化也被新发现为基因转录的关键控制者。 DNA甲基化异常变化可引起多种人类疾病，如发育性疾病（ICF综合征、普瑞德威利综合征和天使综合征等）、衰老相关疾病（如阿尔茨海默病）、心脏病、糖尿病和自身免疫性疾病。此外，大量证据表明 DNA 甲基化是癌症发展的关键因素。该项目的总体目标是开发一套新颖的统计工具来识别差异表达的 DNA 甲基化模式并了解 DNA 甲基化在基因转录调控中的作用。具体来说，我们打算实现三个科学目标：1）提高识别基于单核苷酸的DNA甲基化变化的灵敏度和特异性； 2）利用充分降维模型弥补DNA甲基化分析和基因表达分析的研究空白； 3）开发一个新的统计框架，以克服表观遗传分析中的巨大挑战并建立数学基础。随着过去几十年二代测序技术的快速发展，大量的表观遗传和基因组数据被常规收集、处理和存储，我们相信我们的努力不仅会扩展我们对基因转录调控机制的理解，而且会引领我们的研究方向。 (1) DNA 甲基化分析的根本性进展，(2) 快速、连续识别基因调控相关 DNA 甲基化位点的技术的开发和完善，(3) 用于人类干预某些疾病的表观遗传芯片的原型设计。