Modeling the Dynamics of Genome-Scale Data Across Trees

跨树基因组规模数据的动态建模

• 批准号: 9117563
• 负责人: John Anthony Capra
• 金额: $ 34.98万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9117563
• 关键词: Accounting; Address; Adoption; Age; Algorithmic Software; Algorithms; Big Data; Binding; Biochemical; Biological; Biological Assay; Biological Markers; Blood; Blood Cells; Cancer Biology; Cell Differentiation process; Cells; Cereals; ChIP-seq; Collection; Communities; Complex; Computer software; Computing Methodologies; Congenital Abnormality; Crete; DNA Methylation; DNA Modification Process; Data; Data Set; Dependency; Development; Developmental Biology; Diagnostic; Disease; Ensure; Epigenetic Process; Event; Exhibits; Formulation; Gene Expression; Genes; Genetic Transcription; Genome; Genomic Segment; Genomics; Goals; Human Genome; Individual; Knowledge; Lead; Link; Maintenance; Malignant Neoplasms; Markov Chains; Methodology; Methods; Modeling; Modification; Molecular; Molecular Evolution; Organ; Organism; Pattern; Phylogenetic Analysis; Play; Process; Production; Recording of previous events; Regulation; Regulator Genes; Regulatory Element; Research; Research Personnel; Signal Transduction; Staging; Statistical Methods; Statistical Models; Stem cells; Structure; Techniques; Technology; Testing; Time; Tissues; Trees; Tweens; Ursidae Family; Validation; Work; base; biochemical model; cell type; chromatin modification; developmental disease; discrete data; genome-wide; genomic data; histone modification; human tissue; open source; programs; public health relevance; sound; spatiotemporal; tool; transcription factor; transcriptome sequencing; tumor

 DESCRIPTION (provided by applicant): The human genome encodes the developmental programs that result in the creation and maintenance of a complex organism with hundreds of tissues and trillions of cells. Precise, cell type specific control of gene expression is crucial t these processes. Transcription factor (TF) binding, DNA methylation, and histone modifications at gene regulatory elements play key roles in regulating RNA expression. However, the interplay be- tween these factors is poorly understood for most human tissues, and disruption of these processes can cause birth defects, cancer, and other disease. Recent advances in experimental technology have resulted in the production of thousands of genome- wide profiles of DNA methylation, histone modifications, and TF binding across hundreds of cellular contexts. These data hold the promise of revealing the dynamic genomic changes that drive proper development, but sound statistical and computational methods for integrating and testing hypotheses about these large, complex, and highly interdependent data are needed. Different cellular contexts are related through their differentiation histories, and the goal of this projectis to develop analysis tools that leverage these dependencies be- tween developmentally related cell types. This will facilitate the identification of significant changes in DNA and chromatin modifications within developing lineages, and it will highlight when and how these modifications impact gene expression. The approaches developed in this project will enable researchers to address the following biomedically important questions: Which DNA and chromatin modifications drive different transitions in a cellular differentiation? Which genomic regions are influenced by these modifications? What genes are influenced by these dynamic regulatory modifications in different lineages? Software will be developed, tested, and validated on several recent detailed characterizations of blood cell differentiation. This work will provide the developmental and cancer biology communities with open-source tools for characterizing the genomic basis of normal and abnormal development. In addition, with erroneous patterns of DNA methylation and histone modification now being used as diagnostic hallmarks for specific cancers, given the right data, this framework may open up avenues towards a better understanding of the biological underpinnings of such biomarkers.

 描述（由申请人提供）：人类基因组编码发育程序，导致具有数百个组织和数万亿个细胞的复杂生物体的产生和维持。对基因表达进行精确的细胞类型特异性控制对这些过程至关重要。转录因子（TF）结合，DNA甲基化和组蛋白修饰的基因调控元件在调节RNA表达中发挥关键作用。然而，对于大多数人体组织，这些因素之间的相互作用知之甚少，这些过程的破坏可能导致出生缺陷，癌症和其他疾病。 实验技术的最新进展已经产生了数千个全基因组范围的DNA甲基化、组蛋白修饰和TF结合谱，这些谱跨越了数百种细胞环境。这些数据有望揭示驱动正常发育的动态基因组变化，但需要合理的统计和计算方法来整合和测试这些大型，复杂和高度相互依赖的数据的假设。不同的细胞环境通过它们的分化历史而相互关联，并且该项目的目标是开发利用发育相关细胞类型之间的这些依赖性的分析工具。这将有助于识别发育谱系中DNA和染色质修饰的显著变化，并将突出显示这些修饰何时以及如何影响基因表达。 该项目开发的方法将使研究人员能够解决以下生物医学上重要的问题：哪些DNA和染色质修饰驱动细胞分化中的不同转变？哪些基因组区域受到这些修饰的影响？在不同的谱系中，哪些基因受到这些动态调节修饰的影响？ 软件将被开发，测试和验证的几个最近的详细表征血细胞分化。这项工作将为发育和癌症生物学社区提供开源工具，用于表征正常和异常发育的基因组基础。此外，由于DNA甲基化和组蛋白修饰的错误模式现在被用作特定癌症的诊断标志，如果有正确的数据，这个框架可能会为更好地理解这些生物标志物的生物学基础开辟道路。