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: 8513385
• 负责人: Andrew David Smith
• 金额: $ 38.35万
• 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 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8513385
• 关键词: Accounting; Address; Algorithms; Attention; 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; Investigation; 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; genome annotation; 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.

描述（由申请人提供）：在哺乳动物发育过程中，DNA甲基化在调节谱系规范和效力限制中起关键作用；DNA甲基化的异常模式通常在癌症中观察到。亚硫酸氢盐处理DNA的第二代测序使DNA甲基化能够更详细地进行检查，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度亚硫酸氢盐测序。该项目开发算法和统计方法，以根据这些新实验技术的数据制定和测试关于DNA甲基化的特定假设。将设计一系列统计模型来描述细胞或样品中DNA甲基化的特征，并设计算法用于模型拟合，概率计算和特征识别的相关计算任务。这些方法将通过应用于新的超深亚硫酸盐测序数据进行验证；关于DNA甲基化调控以及甲基化如何调控基因表达的具体假设将同时得到验证。将产生与发育和癌症相关的特定甲基化数据集。计算方法将用于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，以及解决有关肿瘤样本的复杂性和组织学的信息。将开发和发布这些方法的高效和健壮的实现，供公众使用。拟议的研究将提供增加的分析能力，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，能够提出和回答关于DNA甲基化功能的更精确的问题。此外，这项技术将有助于识别与癌症相关的临床结果最有效的甲基化标志物。

项目成果

Using beta-binomial regression for high-precision differential methylation analysis in multifactor whole-genome bisulfite sequencing experiments.

在多因素全基因组亚硫酸盐测序实验中，使用β-二项式回归进行高精度差甲基化分析。

• DOI: 10.1186/1471-2105-15-215
• 发表时间: 2014-06-24
• 期刊: BMC bioinformatics
• 影响因子: 3
• 作者: Dolzhenko E;Smith AD
• 通讯作者: Smith AD

Characterization of universal features of partially methylated domains across tissues and species.

• DOI: 10.1186/s13072-020-00363-7
• 发表时间: 2020-10-02
• 期刊: Epigenetics & chromatin
• 影响因子: 3.9
• 作者: Decato BE;Qu J;Ji X;Wagenblast E;Knott SRV;Hannon GJ;Smith AD
• 通讯作者: Smith AD

MLML: consistent simultaneous estimates of DNA methylation and hydroxymethylation.

• DOI: 10.1093/bioinformatics/btt459
• 发表时间: 2013-10-15
• 期刊: Bioinformatics (Oxford, England)
• 作者: Qu J;Zhou M;Song Q;Hong EE;Smith AD
• 通讯作者: Smith AD

Sperm methylation profiles reveal features of epigenetic inheritance and evolution in primates.

• DOI: 10.1016/j.cell.2011.08.016
• 发表时间: 2011-09-16
• 期刊: Cell
• 影响因子: 64.5
• 作者: Molaro A;Hodges E;Fang F;Song Q;McCombie WR;Hannon GJ;Smith AD
• 通讯作者: Smith AD

DNA methylation dynamics during intestinal stem cell differentiation reveals enhancers driving gene expression in the villus.

• DOI: 10.1186/gb-2013-14-5-r50
• 发表时间: 2013-05-28
• 期刊: Genome biology
• 影响因子: 12.3
• 作者: Kaaij LT;van de Wetering M;Fang F;Decato B;Molaro A;van de Werken HJ;van Es JH;Schuijers J;de Wit E;de Laat W;Hannon GJ;Clevers HC;Smith AD;Ketting RF
• 通讯作者: Ketting RF