Arabidopsis 2010: Genomics Approaches to Finding Transcriptional Networks

转录因子网络是植物和其他生物协调基因表达的适当激活和时间安排的遗传蓝图。破译转录网络的第一步是确定所有基因在细胞类型分辨率下的表达模式。为了实现这一目标，该研究项目将开发一种新的基因组学方法，包括从转基因株系中分离细胞，在转基因株系中，荧光蛋白被用作细胞特异性标记。然后，分类后的细胞群体将被用作与微阵列杂交的RNA的来源。该项目的重点是在拟南芥根中表达的基因，这是一个易于处理的模型，因为它的简单和高度组织的结构。所讨论的基因网络将主要是那些涉及DNA结合转录因子的网络。这些基因的调节区将与荧光蛋白融合，以确定这些序列赋予组织特异性表达的能力。此外，还将进行相同DNA结合因子的翻译融合，从而能够分析影响蛋白质定位的转录后事件。将开发生物信息学工具，根据多种数据来源优化表达模式。这些分析工具将通过杜克大学本菲实验室网站(http://www.biology.duke.edu/benfeylab/at2010.html)的链接提供。所有转录因子及其根细胞类型特定表达谱的列表将在本网站的定期更新中提供。因此，这项研究将确定大量基因的特定表达结构域，这是确定基因功能的重要第一步。这项研究还将为新出现的分析工具提供输入，这些工具可以根据详细的表达模式破译基因调控的控制。这将有助于确定转录因子如何影响其他基因转录的功能。为了利用基因功能发现的力量，找到更好地控制基因表达的方法是至关重要的。基因表达的靶向修饰很可能是改善植物性能的最重要途径之一。这项研究将确定大量具有高度特异性表达模式的基因，其特定的调控代码将在许多植物研究和改良领域发挥重要作用。关于许多基因在何时何地表达的详细信息以及控制它们表达的蛋白质将有助于推进对所有植物如何控制其生长和发育的理解。该项目的另一个重要部分将是培训下一代科学家，将计算方法融入植物生物学。研究生和本科生将积极参与研究。杜克大学和纽约大学拥有非常多样化的学生群体，少数族裔和女性学生的代表性很好。PIs还将积极参与外展工作，如为当地高中教师提供的方案。

Transcription factor networks are the genetic blueprint by which plants and other organisms orchestrate the proper activation and timing of gene expression. A first step in deciphering transcriptional networks is to determine the expression pattern of all genes at cell-type resolution. To accomplish this goal, this research project will develop a new genomics approach, which involves sorting cells from transgenic lines in which a fluorescent protein is used as a cell-specific marker. The sorted cell populations will then be used as a source of RNA that is hybridized to microarrays. The project focuses on genes expressed in the Arabidopsis root, which is a tractable model because of its simple and highly organized structure. The gene networks in question will be primarily those that involve DNA-binding transcription factors. The regulatory regions of these genes will be fused to fluorescent proteins to determine the ability of these sequences to confer tissue-specific expression. In addition, translational fusions of the same DNA binding factors will be made, enabling an analysis of post-transcriptional events that affect protein localization. Bioinformatics tools will be developed that refine expression patterns based on multiple sources of data. These analysis tools will be made available through links at the Benfey lab website (http://www.biology.duke.edu/benfeylab/at2010.html) at Duke University. The list of all transcription factors with their root cell-type specific expression profiles will be made available in regular updates of this site. Thus, the research will determine the specific expression domains of a vast number of genes, which is an important first step in determining gene function. The research will also provide the input for emerging analysis tools that can decipher the controls of gene regulation based on detailed expression patterns. This will help establish the function of transcription factors in terms of how they affect the transcription of other genes. To harness the power of gene function discoveries, it is critical to find ways to gain greater control over the expression of genes. Targeted modification of gene expression is likely to be one of the most important ways to improve plant performance. This research will identify a large number of genes with highly specific expression patterns whose specific regulatory "code" will be of significant use in many areas of plant research and improvement. The detailed information on where and when many genes are expressed and the proteins that control their expression will help advance the understanding of how all plants control their growth and development. Another important part of the project will be to train the next generation of scientists to integrate computational approaches into plant biology. Graduate and undergraduate students will participate actively in the research. Duke and NYU have very diverse student populations with excellent representation of minority and women students. The PIs also will participate actively in outreach efforts such as programs for local high school teachers.