Gene Expression Core

发育转录网络的输入是胚胎每个细胞核中转录因子蛋白质随时间的差异浓度。输出是每个细胞核中靶基因的转录水平。对染色的胚胎进行简单的目视检查以揭示基因表达模式，结果显示许多基因的表达水平以高度复杂的空间和时间方式在细胞与细胞之间存在差异（例如，程序概述[1]中的图4）。因此，为了能够对转录因子的组合如何协调以产生这种复杂的输出模式进行建模，必须在具有细胞分辨率的3D中定量因子蛋白和靶mRNA的表达。为此，我们开发了基于 方法，如下所述，提供了第一个描述的形态和定量基因表达的完整胚胎与细胞分辨率在计算上可分析的格式，一个虚拟胚胎[2-5]。 项目2将产生数百个转基因果蝇品系，其中在转录因子识别位点中携带点突变的CRM被放置在近端启动子/报告基因构建体的上游。很可能（并且对于测试我们的模型是非常期望的），这些突变中的大多数将导致1-3个转录因子的占用率的适度（几倍）变化以及伴随的表达的部分的定量变化。 由CRM驱动的模式。为了能够测量这些转录变化，有必要使用我们的图像分析管道来定量由这些CRM的原始和突变形式驱动的报告基因表达的空间和时间模式。我们将在这个目标中这样做。

The inputs for developmental transcription networks are the differential concentrations of transcription factor proteins in each nucleus of the embryo over time. The outputs are the levels of transcription of target genes in each nucleus. Simple visual inspection of embryos stained to reveal gene expression patterns shows that many genes' expression levels differ from cell to cell in a highly complex spatial and temporal manner (e.g. Fig. 4 in the Program Overview [1]). Therefore, to be able to model how combinations of transcription factors coordinate to produce such complex output patterns, it is essential to quantitate factor protein and target mRNA expression in 3D with cellular resolution. To this end, we have developed image analysis based methods, described below, that provided the first description of morphology and quantitative gene expression of a complete embryo with cellular resolution in a computationally analyzable format, a VirtualEmbryo [2-5]. Project 2 will generate hundreds of transgenic fly lines in which CRMs bearing point mutations in transcription factor recognition sites are placed upstream of a proximal promoter/reporter gene construct. It is likely (and highly desirable for testing our models) that most of these mutations will lead to modest (several fold) changes in occupancy of 1-3 transcription factors and concomitant quantitative changes in parts of the expression patterns driven by the CRMs. To be able to measure these transcription changes, it will be necessary to use our image analysis pipeline to quantitate the spatial and temporal patterns of reporter gene expression driven by both the original and the mutated forms of these CRMs. We will do this in this Aim.