Systems Biology Analysis of Human Erythropoiesis
Systems Biology Analysis of Human Erythropoiesis
批准号:
9294127
负责人:
STUART H ORKIN
金额:
$67.58万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-01 至 2019-05-31
关键词:
AdultAllelesAreaAutomobile DrivingBindingBioinformaticsBiological ModelsBiological ProcessBiologyCell Differentiation processCell MaintenanceChromatinCollaborationsComputer AnalysisComputer SimulationComputing MethodologiesDataData SetDevelopmentDevelopmental GeneDevelopmental ProcessDiseaseDistalEnhancersErythrocytesErythroidErythroid Progenitor CellsErythropoiesisGene ExpressionGene Expression RegulationGenerationsGenesGenetic Enhancer ElementGenetic TranscriptionGenomicsGenotypeHematological DiseaseHumanInvestigationLifeLinkMammalsMediatingMethodsModelingMolecularMolecular GeneticsOrganOxygenPlayProcessProductionRegulationRegulator GenesRegulatory ElementResearchRoleSpecificitySystemSystems BiologyTissuesVariantVertebratesWorkcell typecofactorcombinatorialcostepigenomicsexperienceexperimental studyfetalgenetic variantgenome wide association studygenome-widegenomic datahuman datahuman subjectimprovedinsightnetwork modelsprogramspublic health relevanceresponsetraittranscription factortranscriptometranscriptomics
中文摘要
描述(由申请人提供):红细胞生成是脊椎动物的一个基本过程,长期以来一直是发育调控分子研究的范例。已经确定的是,少数转录因子,也称为主调控因子,在维持细胞身份和/或调节细胞分化过程中起着至关重要的作用。然而,目前还不完全清楚它们是如何相互结合或各种辅助因素起作用的,特别是在不同的发育阶段。由于哺乳动物中至少有一千种转录调节因子,因此可能的组合数量是天文数字。单独使用实验方法来剖析这种复杂性仍然是一项艰巨的任务,因为它需要高昂的成本和劳动力。为了克服这一挑战,我们提出了一种由经验丰富的实验和计算生物学家组成的团队进行的系统生物学方法。以人类原代红前体细胞为模型系统,我们将通过基因组、表观基因组和转录组分析生成广泛的实验数据,开发数据整合和预测计算方法,并通过破坏正常的调节活动来扰乱系统。我们的初步工作已经确定了成人和胎儿红细胞前体之间重要的调控网络差异,并表明主调控因子和辅助因子之间的协作通过作用于增强子元件在驱动发育阶段特异性转录变化中起重要作用。这将通过关注以下具体目标来扩展:(1)通过整合基因组和表观基因组数据类型来预测和验证人类原发性红系前体发育阶段特异性基因调控网络;(2)利用分子和遗传学实验对基因调控网络进行扰动,并进一步整合这些信息来完善我们的网络模型;(3)描述遗传变异对染色质状态、基因表达和红系性状的影响。最后,我们的研究结果将极大地扩展我们目前对组合控制机制的理解,以建立细胞类型和发育阶段特异性,并为红系性状相关的遗传变异提供功能见解。
英文摘要
DESCRIPTION (provided by applicant): Erythropoiesis is a fundamental process in vertebrate animals and has long served as a paradigm for molecular investigations of developmental regulation. It has been well established that a small number of transcription factors, also known as master regulators, play an essential role in the maintenance of cell-identity and/or regulate the cell differentiation process. However, it is not fully elucidated how they work in combination with each other or various cofactors, particularly at different developmental stages. Since there are at least a thousand transcriptional regulators in mammals, the number of possible combinations is astronomical. Using experimental methods alone to dissect such complexity remains a daunting task as it demands prohibitively high cost and labor. To overcome this challenge, we propose a systems biology approach to be carried out by a team of experienced experimental and computational biologists. Using human primary erythroid precursor cells as the model system, we will generate extensive experimental data by genomic, epigenomic, and transcriptomic profiling, develop data-integrative and predictive computational methods, and perturb the systems by disrupting the normal regulatory activities. Our preliminary work has identified important regulatory network differences between adult and fetal erythroid precursors and suggested that collaboration between master regulators and cofactors plays an important role in driving developmental stage-specific transcriptional changes through acting upon enhancer elements. This will be extended by focusing on the following specific aims: (1) Predict and validate the developmental stage-specific gene regulatory networks in human primary erythroid precursors by integrating genomic and epigenomic data-types; (2) Perturb the gene regulatory networks using molecular and genetic experiments and further integrate such information to refine our network model; (3) Characterize the role of genetic variants influencing chromatin state, gene expression, and erythroid traits. In the end our results will greatly expand our current mechanistic understanding of combinatorial control in establishing cell-type and developmental stage-specificity and provide functional insights into erythroid trait- associated genetic variants.
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