Transcription networks in C elegans organogenesis

我们的长期目标是破译后生动物系统中控制差异基因表达的机制。差异基因表达是发育过程中的一个主要决定因素，转录调控不当可导致多种疾病。尽管有大量的基因表达数据可用，但人们对在系统水平上调节基因表达的机制知之甚少。每个基因的表达是转录激活和抑制之间的平衡，受多个转录因子(TF)的调控。5%-10%的后生动物基因编码TF。每个转铁蛋白通过与蛋白质伴侣和靶基因DMA结合来调节多个靶基因的表达。多重相互作用的TFS 多个转录因子的协同作用表明，基因的差异表达是复杂的转录调控网络的结果，其中许多转录因子在功能上是相连的。 这项建议的总体目标是定位控制线虫肠道发育的TRN。线虫的肠道发育是理解差异基因表达的一个很好的系统，因为有全基因组的肠道表达数据，而且转录调控在这个组织中起着关键作用。我们将使用高通量酵母单杂交和双杂交系统，通过绘制涉及肠道启动子和转录因子的蛋白质-DNA和蛋白质-蛋白质相互作用图来识别肠道TRN。我们将生成一个数据库，用于数据跟踪、数据分析和公开提供数据。为了验证相互作用，我们将手动和计算将蛋白质相互作用与可用的基因表达和表型数据整合在一起。此外，我们将启动蛋白质的验证 通过实验方法进行相互作用。肠道TRNS的图谱将揭示转录 肠道发育中差异基因表达的机制。由于这是一个保守的生物学程序，这些TRN也可能为哺乳动物的差异基因表达提供洞察力。

Our long-term goal is to decipher the mechanisms that control differential gene expression in metazoan systems. Differential gene expression is a major determinant in development, and misregulation of transcription can lead to numerous diseases. Although vast amounts of gene expression data are available, little is known about the mechanisms that regulate gene expression at a systems level. The expression of each gene is a balance between transcription activation and repression, governed by multiple transcription factors (TFs). Between 5-10% of metazoan genes encode TFs. Each TF regulates the expression of multiple target genes by binding both to protein partners and to target gene DMA. The multiple interactions TFs engage in, and the concerted action of multiple TFs per gene suggests that differential gene expression is the result of intricate transcription regulatory networks (TRNs) in which many TFs are functionally connected. The general aim of this proposal is to map TRNs that control intestinal development in the nematode Caenhorhabditis elegans. C. elegans intestinal development is an excellent system to understand differential gene expression because genome-wide intestinal expression data are available and because transcription regulation plays a pivotal role in this tissue. We will identify intestinal TRNs by mapping protein-DNA and protein-protein interactions involving intestinal promoters and TFs using high-throughput yeast one -and two-hybrid systems. We will generate a database for data tracking, data analysis and to make the data publicly available. To validate interactions, we will manually and computationally integrate protein interactions with available gene expression and phenotypic data. In addition, we will initiate the validation of protein interactions by experimental methods. The mapping of intestinal TRNs will reveal transcriptional mechanisms that underlie differential gene expression in intestinal development. Since this is a conserved biological program, these TRNs may provide insights into mammalian differential gene expression as well.