Modeling the Dynamics of Genome-Scale Data Across Trees

跨树基因组规模数据的动态建模

基本信息

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
项目类别：
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

项目摘要

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：人类基因组编码具有数百个组织和数万亿个细胞的创造性污染的发育程序。对于大多数人体组织而言，这些因素对调节RNA表达的作用在调节RNA表达方面的作用很少，并且对过程的讨论可能会导致出生缺陷，癌症和其他疾病的进展。基因组关系，组蛋白的修饰和TF结合可促成数百个细胞环境。需要在开发谱系中开发的分析工具。细胞哪些基因组区域受这些修饰的影响是某些不同的谱系，可以开发，测试和验证具有较少的血细胞区分的详细表征。 DNA甲基化和组蛋白的修饰现在是特定癌症的标志，鉴于正确的数据，该框架可能会为更好地了解此类生物标志物的生物基础。