Defining an Integrated Signaling Network That Patterns the Craniofacial Skeleton

定义一个模拟颅面骨骼的集成信号网络

基本信息

批准号：
8750599
负责人：
David E. Clouthier
金额：
$ 67.12万
依托单位：
UNIVERSITY OF COLORADO DENVER
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-07-01 至 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8750599
关键词：
Address Affect Alagille Syndrome Automobile Driving Bone Morphogenetic Proteins Branchial arch structure Buffers Candidate Disease Gene Cleft Palate Collection Competence Complex Computer Analysis Computer Simulation Congenital Abnormality Data Databases Defect Development Disease Dorsal Embryo Endothelin-1 Enhancers Ensure Etiology Event Face Feedback Fishes Gene Expression Gene Mutation Gene Targeting Genes Genetic Genetic Enhancer Element Goals High-Throughput RNA Sequencing Human Interdisciplinary Study Jaw Mediating Micrognathism Mining Modeling Molecular Profiling Morphogenesis Mus Mutate Noise Notch Signaling Pathway Outcome Pathway interactions Pattern Phenotype Play Positioning Attribute Regulator Genes Regulatory Element Resistance Role Shapes Signal Pathway Signal Transduction Silicon Skeletal Development Skeleton Structural Congenital Anomalies Syndrome System Testing Time To specify Transgenic Mice Transgenic Organisms Work Zebrafish base clinically relevant craniofacial gene function genetic analysis improved in vivo in vivo imaging malformation mathematical model mouse model mutant notch protein novel progenitor programs public health relevance response simulation skeletal spatiotemporal three dimensional structure tool transcriptome sequencing

项目摘要

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.

描述（由申请人提供）：许多颅面骨架来自咽弓，3D结构，随着时间的推移，形状表达和基因表达的复杂变化。但是，尚未在体内对拱形早期基因表达谱进行详细分析。没有这样的信息，就无法预测基因表达变化将如何影响随后的骨骼发育。我们的实验室已广泛研究了拱形中的内皮素1（EDN1），骨形态发生蛋白（BMP），Wnt和Jag/Notch信号通路，因为这四个途径模拟了面部骨骼的背腹侧（D-V）轴。我们已经表明，EDN1和BMP信号传导最初促进腹侧表达的基因，然后将拱形细分为单独的D-V亚域。我们的初步数据表明，Wnt信号控制能力对EDN1/BMP做出响应，并且这三个途径与JAG/Notch信号相反。由这四个信号调节的路径是高度动态的，其中包含多个反馈回路和串扰，这些反馈环和串扰会产生可抵抗扰动的强大系统。通过在所有四个信号中的小鼠和斑马鱼突变体的集合中，我们处于一个独特的位置，可以详细地评估跨物种的基因表达的保护，以进行计算建模。我们的目标是使用这些模型在这些信号的遗传扰动后观察到的硅面部缺陷中预测。我们的双物种方法将确定新的候选基因，并生成与人类颅面遗传学相关的模型。为了解决这些目标，我们将追求两个具体目标。在AIM 1中，我们假设，尽管EDN1，BMP，WNT和JAG/NOTCH信号对于在沿D-V轴拱形中建立骨骼祖细胞的初始身份至关重要，但它们每个都起着独特的作用。我们将通过使用高通量RNA测序来解决这一假设，以定义所有四种途径的突变体中基因表达的早期变化。这些早期响应曲线（ERP）将用于产生模型，以整合突变体的基因表达变化，以了解每个因子的独特作用和信号之间的串扰。在AIM 2中，我们假设增强器的“核心”集负责每个信号的ERP，其中一些信号介导了信号通路内或反馈之间的串扰，并彼此绝缘途径。我们将通过隔离AIM 1中鉴定的基因并在两只小鼠中测试其活动来解决这一问题和斑马鱼。这些将被整合到我们的数学模型中，以了解增强子灵敏度以及如何调节基因表达边界的清晰度。我们的长期目标是为颅面基因调节网络建立一个综合模型，该网络可以在可获得新数据的情况下进行修改。