Determining how noisy gene expression controls stochastic fate choices during development

在开发过程中指定细胞命运通常被认为是一个高度可重复性的过程，由以下驱动 细胞谱系和信号传递。细胞多样性也可以由固有的分子噪声(即可变性)引起 在随机细胞命运指定期间的基因表达，其中细胞在两个或更多个之间随机选择 命运。与谱系和信号机制相比，人们对噪音如何影响基因表达知之甚少。 在发展过程中决定命运。 该项目旨在解决果蝇视觉系统中随机细胞命运的指定 黑猩猩。苍蝇眼包含一个简单的、随机的、二元的命运选择。眼睛是由两个随机拼接而成的 检测颜色的光感受器亚型，由不同的光检测视紫红质蛋白的表达定义。 这种二元决定由转录因子无刺(SS)控制，它以随机的形式表达 R7光感受器亚群(65%)。无刺基因(Ss)的随机表达受 两个增强子元素(“早期”和“晚期”增强子)在整个发育过程中的时间方式，以及一个 转录抑制因子，Klu。Ss的早期表达是有噪声的，导致基因水平的变异性。 前体R7细胞间的表达。通过操纵DNA元件(增强剂和消音器)和KLU 转录因子，ss的表达强度可以在早期进行调节。值得注意的是，早期的这些操纵 在终末分化的R7细胞中，SS的表达引起SS开/关比的变化。基于这些 发现，假设在R7祖细胞中不同水平的ss表达(即早期)设置 在终末分化的R7细胞中开/关的表达频率(即晚期)。该项目旨在解决 促进早期ss表达的可变性以及这种可变性的后果。 基因表达噪声的一个主要来源来自转录过程。抄写是 与生俱来的随机性，以突发的形式出现，在不同的基因和 细胞。三色RNA荧光原位杂交将用于监测单个细胞的转录 确定Klu和不同的DNA元件如何控制固定组织中早期ss表达的变异(目的 1)。为了从机制上理解转录如何影响早期表达的可变性，这个项目 目的通过使用MS2/MCP系统和实时成像来可视化早期ss的表达(目标1)。最后，一个链接 早期表达和最终细胞命运之间的关系将通过实时监测内源性ss的表达来实现 从前体细胞阶段到终末分化的时间(目标2)。该项目将在 约翰霍普金斯大学，小罗伯特·J·约翰斯顿的实验室。申请者将接受额外的培训。 普林斯顿大学和巴斯德研究所的合作者(托马斯·格雷戈博士)。这个项目的成果 将阐明在视网膜发育过程中控制ss表达的机制，特别是如何 在后生动物发育过程中，分子可变性驱动细胞命运的随机决定

Cell fate specification during development is often thought of as a highly reproducible process driven by cell lineage and signaling. Cellular diversity can also arise from the inherent molecular noise (i.e. variability) in gene expression during stochastic cell fate specification, where a cell randomly chooses between two or more fates. Compared to lineage and signaling mechanisms, very little is known about how noise in gene expression drives fate decisions during development. This project aims to address stochastic cell fate specification in the visual system of Drosophila melanogaster. The fly eye contains a simple, stochastic, binary fate choice. The eye is a random mosaic of two color-detecting photoreceptor subtypes, defined by expression of different light-detecting Rhodopsin proteins. This binary decision is controlled by the transcription factor Spineless (Ss), which is expressed in a random subset (65%) of R7 photoreceptors. Stochastic expression of the gene spineless (ss) is controlled in a temporal manner throughout development by two enhancer elements (“early” and “late” enhancers), and a transcriptional repressor, Klu. Early expression of ss is noisy, producing variability in the levels of gene expression between precursor R7 cells. By manipulating DNA elements (enhancers and silencers) and the Klu transcription factor, the strength of ss expression early can be tuned. Remarkably, these manipulations of early expression cause changes in the on/off ratio of Ss in terminally differentiated R7 cells. Based on these findings, it is hypothesized that variable levels of ss expression amongst R7 progenitors (i.e. early) sets the on/off expression frequency in terminally differentiated R7 cells (i.e. late). This project aims to address what promotes early ss expression variability as well as the consequences of this variability. A major source of gene expression noise arises from the process of transcription. Transcription is inherently stochastic, and occurs in bursts that vary in amplitude, frequency, and duration between genes and cells. Three-color RNA fluorescence in situ hybridization will be used to monitor transcription in individual cells to determine how Klu and different DNA elements control variation in in early ss expression in fixed tissue (Aim 1). To gain a mechanistic understanding of how transcriptional affects early expression variability, this project aims to visualize early ss expression by using the MS2/MCP system and live imaging (Aim 1). Finally, a link between early expression and terminal cell fate will be made by monitoring endogenous ss expression in real time from the precursor cell stage through terminal differentiation (Aim 2). This project will be carried out at Johns Hopkins University in the lab of Robert J. Johnston Jr. The applicant will receive additional training from collaborators at Princeton University and the Institut Pasteur (Dr. Thomas Gregor). The results of this project will elucidate the mechanisms controlling expression of ss during retina development, in particular, how molecular variability drives a stochastic cell fate decision during metazoan development