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Arabidopsis 2010: Identifying transcriptional networks at cellular resolution

Arabidopsis 2010: Identifying transcriptional networks at cellular resolution
拟南芥 2010:以细胞分辨率识别转录网络
批准号:
0618304
负责人:
Philip Benfey
金额:
$0.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-09-01 至 2010-08-31

项目摘要

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中文摘要
翻译
科学目标:该项目的长期目标是确定当受到不同刺激时,拟南芥在根发育过程中发生的细胞状态。作为定义细胞状态的一种容易处理的方法,当在各种环境条件下生长时,在不同类型的细胞中活跃的转录网络将被识别。为了描述一个一级转录网络,需要三种类型的数据:1)正常实验室条件下和受到外部刺激时细胞类型特定分辨率的转录图谱;2)转录因子在细胞分辨率上的定位知识;3)转录因子靶标的信息。对于第一种技术,将使用一种技术,涉及对荧光标记的细胞群体进行分类,然后对标记细胞的RNA进行微阵列分析。对于第二个,将比较包含驱动荧光报告基因的转录因子的启动子区域的构建体与包含驱动融合到荧光报告基因的转录因子的编码序列的相同启动子区域的构建体的表达模式。对于第三种,酵母单杂交和双杂交方法将与组织特异性转录因子文库一起使用。首先将对在标准实验室条件下生长的植物进行分析。为了确定表达如何受到外界刺激的干扰,植物将系统地受到各种外部刺激以及在细胞类型特定分辨率下确定的对转录图谱的影响。为了确定外部刺激对高空间和时间分辨率表达的影响,将开发一种名为“根阵列”的新技术。来自这些不同方法的结果的组合将提供有关已识别基因功能的信息。这些研究的结果将公布在拟南芥基因表达数据库www.arexdb.org上。广泛的影响:要在植物特性方面实现持续改进,同时将有害的副作用降至最低,将需要对控制植物发育和生理的网络有深入的了解。这项研究将为鉴定根发育过程中活跃的转录网络提供一个高分辨率的数据集。它还将确定与田间植物生长相关的刺激物对根转录网络的影响。这项研究的另一个成果将是详细了解大量植物基因的空间和时间表达模式,以及能够赋予特定表达模式的调控序列。这些在许多植物研究项目中应该具有立竿见影的价值,而且很可能对农学目的也有用。该项目的另一个重要部分将是培训下一代系统生物学植物科学家,该学科集计算、工程和实验方法于一体。博士后研究员、研究生和本科生将在这项研究中接受培训。专业人士亦会积极参与外展工作,例如在杜克大学发展系统生物学课程。该研究计划还将利用目前由Co-Pi Clark指导的生物启发材料和材料系统方面的NSF IGERT计划。IGERT计划的一个重要重点是招募和培训工程和科学领域的女性和代表性不足的少数族裔。与拟南芥2010年目标的关系:研究活动将有助于实现拟南芥2010计划的所有三个主要目标。在正常的实验室条件下提高根表达图谱的分辨率,并针对不同的刺激产生细胞类型特定分辨率的表达图谱,将大大有助于“标杆基因功能”。开发用于顺式元件鉴定和自动图像分析的计算工具,以及开发根阵列,应该提供“全基因组的实验方法和工具,用于分析基因功能和调控。”也许最直接的是,这项研究的目的是确定在根系发育和生理中起作用的转录网络,从而“探索示范网络和系统”。
英文摘要
Scientific Goals: The long-term goal of this project is to define the cellular states that occur during root development in Arabidopsis when subjected to different stimuli. As a tractable approach to defining cellular state, transcriptional networks active in different cell types when grown under a variety of environmental conditions will be identified. To describe a first-order transcriptional network three types of data are needed: 1) transcriptional profiles at cell-type specific resolution under normal lab conditions and when subjected to external stimuli; 2) knowledge of transcription factor localization at cellular resolution and 3) information about the targets of transcription factors. For the first, a technique that involves sorting of fluorescently marked cell populations followed by microarray analysis of the RNA from the marked cells will be used. For the second, comparisons will be made of the expression patterns of constructs containing the promoter regions of transcription factors driving fluorescent reporter genes with constructs containing the same promoter regions driving the coding sequences of transcription factors fused to fluorescent reporter genes. For the third, yeast one-hybrid and two-hybrid methods will be used with libraries of tissue-specific transcription factors. Analyses will initially be performed on plants growing under standard laboratory conditions. To determine how expression is perturbed by external stimuli, plants will be systematically subjected to a variety of external stimuli and the effects on transcriptional profiles determined at cell-type specific resolution. To determine the effect of external stimuli on expression at high spatial and temporal resolution a novel technology called the "RootArray" will be developed. The combination of results, from these different approaches, will provide information concerning the function of the identified genes. Results from these studies will be posted on the Arabidopsis Gene Expression Database, at www.arexdb.org.Broader Impact: To achieve continued improvement in plant traits while minimizing unwanted side effects will require a sophisticated understanding of the networks that control plant development and physiology. This research will provide a high-resolution dataset for the identification of transcriptional networks active during root development. It will also determine the effect on root transcriptional networks of stimuli relevant to plant growth in the field. Another outcome of the research will be detailed knowledge of the spatial and temporal expression patterns of large numbers of plant genes and the regulatory sequences able to confer specific expression patterns. These should be of immediate value in many plant research programs and are likely to be useful for agronomic purposes as well. Another important part of the project will be to train the next generation of plant scientists in Systems Biology, which integrates computational, engineering and experimental approaches. Postdoctoral fellows, graduate and undergraduate students will be trained in this research. The PIs also will participate actively in outreach efforts such as development of a Systems Biology curriculum at Duke. The research program will also leverage the currently funded NSF IGERT program in biologically inspired materials and material systems directed by Co-PI Clark. A significant focus of the IGERT program is placed upon recruitment and training of women and underrepresented minorities in engineering and the sciences.Relevance to Arabidopsis 2010 goals: The research activities will contribute to all three of the primary goals of the Arabidopsis 2010 program. Enhancing the resolution of the root expression map under normal laboratory conditions and producing expression profiles at cell-type specific resolution in response to different stimuli will substantially aid in "Benchmarking Gene Function." Developing computational tools for cis-element identification and automated image analysis as well as developing the RootArray should provide "genome wide experimental approaches and tools for analyzing gene function and regulation." Perhaps most directly, the research has as its aim to identify the transcriptional networks acting in root development and physiology, thus "exploring exemplary networks and systems."
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Collaborative Research: Root Dynamics and Control in Heterogeneous Soft Substrates
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  • 财政年份:
    2019
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EAGER: Determining Interaction Parameters of Roots in Soil
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    1411750
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Arabidopsis 2010: Regulatory Networks Controlling Root Growth and Differentiation
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    1021619
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    Continuing Grant
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  • 依托单位:
Genome-Wide Analysis of Root Traits
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    0820624
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    Continuing Grant
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  • 负责人:
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