Analytic tools to examine high-resolution and genome-scale DNA methylation data

用于检查高分辨率和基因组规模 DNA 甲基化数据的分析工具

• 批准号: 7770107
• 负责人: Andrew David Smith
• 金额: $ 38.67万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7770107
• 关键词: Accounting; Address; Algorithms; Attention; Binding; Binding Sites; Biological; Cancer cell line; Cells; Characteristics; Chromosomes; Clinical; Clinical Markers; Communities; Complement; Complex; Computational algorithm; Computer Simulation; Computing Methodologies; DNA; DNA Methylation; DNA Methylation Regulation; Data; Data Set; Dependency; Development; Family; Foundations; Frequencies; Gene Expression; Generations; Genes; Genome; Genomics; Goals; Hematopoietic; Histology; Human Development; Individual; Knowledge; Malignant Neoplasms; Medical; Methods; Methylation; Modeling; Modification; Molecular; Outcome; Pattern; Play; Principal Investigator; Probability; Property; Psyche structure; Regulation; Research; Research Personnel; Resolution; Role; Sampling; Site; Statistical Methods; Statistical Models; Techniques; Technology; Testing; Trees; Variant; analytical method; base; bisulfite; cancer genome; cell type; clinical application; computer framework; cost; design; epigenomics; improved; novel; predictive modeling; programs; promoter; public health relevance; research study; tool; transcription factor; tumor; tumor progression

DESCRIPTION (provided by applicant): DNA methylation plays a critical role in regulating lineage specification and restriction of potency during mammalian development; aberrant patterns of DNA methylation are generally observed in cancers. Second-generation sequencing of bisulfite treated DNA is enabling DNA methylation to be examined in greater detail, and recently demonstrated array-based capture technique allow ultra-deep bisulfite sequencing in selected genomic regions. This project develops algorithmic and statistical methods required to formulate and test specific hypotheses about DNA methylation based on data from these novel experimental technologies. A family of statistical models will be designed to characterize features of DNA methylation in a cell or sample, and algorithms will be designed for associated computational tasks of model fitting, probability calculations and feature identification. The methods will be validated through application to novel, ultra-deep bisulfite sequencing data; specific hypotheses about the regulation of DNA methylation and how methylation regulates gene expression will be tested simultaneously. Specific methylation datasets related to development and cancer will be produced. Computational methods will be developed for identifying clonal features of methylation profiles in cells, for predicting developmental relationships between cells, and for resolving information about the complexity and histology of tumor samples. Efficient and robust implementations of the methods will be developed and released for public use. The proposed research will provide increased analytical capability to complement emerging experimental technology for investigating DNA methylation. This will enable researchers, particularly those studying human development and cancers, to ask and answer more precise questions about the functions of DNA methylation. Moreover, this technology will assist in identifying the most effective methylation-based markers for clinical outcomes associated with cancers. PUBLIC HEALTH RELEVANCE: The proposed research will produce analytic technology to complement emerging experimental technology in analyzing DNA methylation patterns. DNA methylation is involved in regulating human development, and aberrant methylation patterns are a general characteristic of cancer genomes. By providing increased capacity for analyzing methylation data, this project will assist researchers elucidate the role and mechanisms of DNA methylation in cancer and development.

描述（由申请人提供）：DNA甲基化在哺乳动物发育过程中调节谱系规范和效力限制中发挥着关键作用； DNA 甲基化的异常模式通常在癌症中观察到。对亚硫酸氢盐处理的 DNA 进行第二代测序能够更详细地检查 DNA 甲基化，最近展示的基于阵列的捕获技术允许在选定的基因组区域进行超深亚硫酸氢盐测序。该项目开发了基于这些新颖实验技术的数据制定和测试有关 DNA 甲基化的特定假设所需的算法和统计方法。将设计一系列统计模型来表征细胞或样本中 DNA 甲基化的特征，并为模型拟合、概率计算和特征识别等相关计算任务设计算法。这些方法将通过应用于新型超深亚硫酸氢盐测序数据进行验证；关于DNA甲基化调节以及甲基化如何调节基因表达的具体假设将同时进行测试。将生成与发育和癌症相关的特定甲基化数据集。将开发计算方法来识别细胞中甲基化谱的克隆特征，预测细胞之间的发育关系，以及解析有关肿瘤样本的复杂性和组织学的信息。这些方法的高效、稳健的实施将被开发并发布以供公众使用。拟议的研究将提供增强的分析能力，以补充研究 DNA 甲基化的新兴实验技术。这将使研究人员，特别是那些研究人类发育和癌症的研究人员，能够提出并回答有关 DNA 甲基化功能的更精确的问题。此外，该技术将有助于识别与癌症相关的临床结果的最有效的基于甲基化的标记物。 公共健康相关性：拟议的研究将产生分析技术，以补充分析 DNA 甲基化模式的新兴实验技术。 DNA 甲基化参与调节人类发育，异常甲基化模式是癌症基因组的普遍特征。通过提高甲基化数据分析能力，该项目将帮助研究人员阐明 DNA 甲基化在癌症和发育中的作用和机制。