Defining an Integrated Signaling Network That Patterns the Craniofacial Skeleton

描述（由申请人提供）：大部分颅面骨骼来自咽弓，3D结构，随着时间的推移，形状和基因表达发生复杂变化。然而，对弓的早期基因表达谱的详细分析尚未在体内进行。没有这些信息，就不可能预测基因表达的变化将如何影响随后的骨骼发育。我们的实验室广泛研究了弓中的内皮素1 （Edn1）、骨形态发生蛋白（Bmp）、Wnt和Jag/Notch信号通路，因为这四个通路是面部骨骼背腹轴（D-V）的模式。我们已经表明，Edn1和Bmp信号最初促进腹侧表达基因，随后将弓细分为单独的D-V亚结构域。我们的初步数据表明Wnt信号控制对Edn1/Bmp的反应能力，而这三种信号通路与Jag/Notch信号通路相反。由这四个信号调节的通路是高度动态的，包含多个反馈回路和串扰，从而创建一个抗扰动的鲁棒系统。通过收集小鼠和斑马鱼的所有四种信号突变体，我们处于一个独特的位置，可以评估物种间基因表达的守恒，并提供足够的细节来进行计算建模。我们的目标是使用这些模型来预测在这些信号的遗传扰动后观察到的硅面缺陷。我们的双物种方法将识别新的候选基因，并产生与人类颅面遗传学临床相关的模型。为了实现这些目标，我们将追求两个具体目标。在Aim 1中，我们假设Edn1、Bmp、Wnt和Jag/Notch信号都对沿D-V轴的弓建立骨骼祖细胞的初始身份至关重要，但它们各自发挥不同的作用。我们将通过使用高通量RNA测序来确定所有四种途径突变体中基因表达的早期变化来解决这一假设。这些早期反应谱（ERPs）将用于建立整合突变体基因表达变化的模型，以了解每个因子的独特作用和信号之间的串扰。在Aim 2中，我们假设“核心”增强子组负责每个信号的ERP，其中一些增强子介导信号通路内的串扰或反馈，以及相互隔离的通路。我们将通过分离Aim 1中鉴定的基因的增强子并在两只小鼠中测试其活性来解决这个问题

DESCRIPTION (provided by applicant): Much of the craniofacial skeleton arises from the pharyngeal arches, 3D structures that undergo complex changes in shape and gene expression over time. However, detailed analyses of early gene expression profiles in the arches have not been performed in vivo. Without such information, it is impossible to predict how gene expression changes will affect subsequent skeletal development. Our labs have extensively studied the endothelin1 (Edn1), bone morphogenetic protein (Bmp), Wnt and Jag/Notch signaling pathways in the arches, as these four pathways pattern the dorsal-ventral (D-V) axis of the facial skeleton. We have shown that Edn1 and Bmp signaling initially promote ventrally- expressed genes and later subdivide the arches into separate D-V sub-domains. Our preliminary data suggest that Wnt signaling controls competence to respond to Edn1/Bmp and that these three pathways are opposed by Jag/Notch signaling. The pathways regulated by these four signals are highly dynamic, containing multiple feedback loops and crosstalk that create a robust system resistant to perturbation. With a collection of mouse and zebrafish mutants in all four signals, we are in a unique position to assess conservation of gene expression across species in sufficient detail for computational modeling. Our goal is to use these models to predict in silicon facial defects observed following genetic perturbations of these signals. Our dual-species approach will identify new candidate genes and generate models that are clinically relevant to human craniofacial genetics. To address these goals we will pursue two specific aims. In Aim 1, we hypothesize that while Edn1, Bmp, Wnt and Jag/Notch signaling are all critical for establishing the initial identities of skeletal progenitor in the arches along the D-V axis, they each play distinct roles. We will address this hypothesis by using high-throughput RNA sequencing to define early changes in gene expression in mutants of all four pathways. These Early Response Profiles (ERPs) will be used to produce models that integrate gene expression changes across mutants to understand both the unique roles of each factor and crosstalk between signals. In Aim 2 we hypothesize that "core" sets of enhancers are responsible for the ERP for each signal, some of which mediate crosstalk between or feedback within a signaling pathway, as well as insulating pathways from one another. We will address this by isolating enhancers for genes identified in Aim 1 and testing their activities in both mice and zebrafish. These will be incorporated into our mathematical models to understand enhancer sensitivity and how this regulates sharpness of gene expression boundaries. Our long-term goal is to build a comprehensive model for a craniofacial gene regulatory network that can be amended as new data are available.