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中文摘要
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项目1 -基因组的时空结构 总结 分子生物学的一个中心挑战是理解转录调控元件是如何 从基因组中选择,从而指定细胞身份和细胞特异性反应。本课题 将使用系统生物学方法和地图到模型范式来深入了解一般的 负责顺式调节元件的选择和功能的机制, 对病原体的转录反应。这些活动包括以下四个具体目标。一是 将生成一个地图,并使用它来模拟细胞特异性增强子景观的选择。该目的是 基于这样的假设,即谱系决定转录因子的相对简单组合 LDTF在选择大部分细胞特异性增强子中起主导作用。我们将开发和测试 一个机械网络模型,从巨噬细胞结合位点的全基因组预测开始, LDTF及其在预测其他协作转录的全基因组结合位置方面的进展 有助于增强子选择的因素。其次,我们将绘制和建模信号依赖的作用, 转录因子(SDTF)在调节增强子景观。这一目标的基础是假设 功能性增强子的一个基本特征是它被主动转录。为此,我们将扩大 在目标1中开发的用于预测SDTF结合的机制网络模型,以及随后的 脂多糖暴露或腺病毒感染后增强子的转录激活。的 该模型的预测价值将通过SDTF的功能丧失研究和 自然遗传变异的影响。第三,我们将试图预测转录活性作为一个功能, 增强子相互作用我们建议扩展在目标2中实现的机械网络模型,以考虑 在空间共定位的背景下共调节转录起始位点。该模型的这一方面将 通过评估功能丧失突变体和自然遗传变异对增强子的影响进行测试- 启动子相互作用使用Hi-C测定的修改版本,其将测序能力集中在 与启动子的相互作用。最后,我们将绘制和建模3D病毒-宿主基因组相互作用中心 以及决定跨组织和物种感染结果的转录网络。我们 假设病毒基因组靶向并破坏宿主基因组的3D组织和相互作用 以在感染的时间过程中激活不同的病毒和宿主转录程序。拟议 研究将绘制和模拟不同组织内的3D基因组相互作用和转录程序 决定病毒嗜性和复制的类型。这些研究特别令人感兴趣,因为 人腺病毒感染的“早期”程序在小鼠细胞中是完整的,它们的生产性裂解 复制/表达通过知之甚少的机制被“晚期”阻断。分子 对这些机制的理解在概念和实践层面上都非常重要。
英文摘要
PROJECT 1 – SPATIOTEMPORAL ARCHITECTURE OF THE GENOME SUMMARY A central challenge of molecular biology is to understand how transcriptional regulatory elements are selected from the genome thereby specifying cellular identity and cell-specific responses. In this project, we will use systems biology approaches and the maps-to-model paradigm to gain insights into general mechanisms responsible for the selection and function of cis-regulatory elements necessary for transcriptional responses to pathogens. These activities consist of the following four Specific Aims. First, we will generate a map and use this to model the selection of cell-specific enhancer landscapes. This aim is based on the hypothesis that relatively simple combinations of lineage-determining transcription factors (LDTFs) play dominant roles in selecting a large fraction of cell-specific enhancers. We will develop and test a mechanistic network model that begins with genome-wide predictions of binding sites for macrophage LDTFs and progresses to predict the genome-wide binding locations of other collaborating transcription factors that contribute to enhancer selection. Second, we will map and model the role of signal-dependent transcription factors (SDTFs) in regulating the enhancer landscape. This aim is based on the hypothesis that an essential feature of a functional enhancer is that it is actively transcribed. In this aim, we will extend the mechanistic network model developed in Aim 1 to predict binding of SDTFs and subsequent transcriptional activation of enhancers following lipopolysaccharide exposure or adenoviral infection. The predictive value of the model will be tested by loss-of-function studies of the SDTFs and by evaluation of effects of natural genetic variation. Third, we will try to predict transcriptional activity as a function of enhancer interactions. We propose extending the mechanistic network model achieved in Aim 2 to consider co-regulated transcriptional start sites in the context of spatial co-localization. This aspect of the model will be tested by evaluating loss-of-function mutants and the impact of natural genetic variation on enhancer- promoter interactions using a modified version of the Hi-C assay that focuses sequencing power on interactions involving promoters. Finally, we will map and model the 3D virus-host genome interaction hubs and transcriptional networks that determine the outcome of infection across tissues and species. We hypothesize that viral genomes target and subvert the 3D organization and interactions of the host genome to activate different viral and host transcriptional programs in the time course of infection. The proposed studies will map and model 3D genome interactions and transcriptional programs within different tissue types that determine viral tropism and replication. These studies are of particular interest because, while the `early' program of human adenovirus infection is intact in mouse cells, their productive lytic replication/expression is blocked `late' through mechanisms that are poorly understood. A molecular understanding of these mechanisms would be highly significant at both conceptual and practical levels.
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A Cardiovascular-NASH disease nexus: Common Mechanisms and Treatments?
Macrophage-specific targeting of LXRs in CVD and NASH
A Cardiovascular-NASH disease nexus: Common Mechanisms and Treatments?
Macrophage-specific targeting of LXRs in CVD and NASH
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