Transcriptome and Network Analysis of Cleft Palate

腭裂的转录组和网络分析

• 批准号: 10314049
• 负责人: Ethylin Wang Jabs
• 金额: $ 76.04万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10314049
• 关键词: Adhesions; Affect; Age; Anterior; Binding; Biological; Biomechanics; CRISPR/Cas technology; Cells; Cleft Palate; Clinical; Complex; Computational Biology; Congenital Abnormality; Critical Pathways; Data; Data Set; Defect; Development; Developmental Biology; Diagnosis; Disease; Embryo; Epithelial; Etiology; Event; FGFR2 gene; Fibroblast Growth Factor; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Genetic; Genetic Transcription; Genotype; Goals; Growth; Human; Immunohistochemistry; In Situ Hybridization; Individual; Internet; Intervention; Intuition; Knock-in; Knockout Mice; Libraries; Light; Link; Literature; Maps; Maxilla; Medial; Mediating; Medical; Mesenchymal; Mesenchyme; Methods; Modeling; Molecular; Morphogenesis; Morphology; Movement; Mus; Mutant Strains Mice; Mutation; Operative Surgical Procedures; Organ Culture Techniques; Outcome; Palate; Pathologic; Pathway Analysis; Pathway interactions; Pattern; Population; Prevention; Process; Property; Psychosocial Assessment and Care; RNA; RNA Splicing; Resolution; Role; SHH gene; Series; Signal Pathway; Signal Transduction; Structural Congenital Anomalies; Structure; System; Systems Biology; Technology; Tissue-Specific Gene Expression; Tissues; Validation; Wild Type Mouse; Work; advanced system; base; cell type; craniofacial; differential expression; gene discovery; human model; in silico; in vivo; innovation; insight; mouse model; multiple omics; mutant; mutant mouse model; network models; novel; null mutation; oral cleft; orofacial cleft; palatal shelves; palatogenesis; prevent; psychosocial; simulation; single cell sequencing; single-cell RNA sequencing; tool; transcription factor; transcriptome; transcriptome sequencing; transcriptomics

ABSTRACT Cleft palate is one of the most common structural birth defects. Surgical correction and medical and psychosocial care impose significant personal and societal burdens. Increased understanding of the etiology of cleft palate potentially will lead to improvements in diagnosis and treatment. Palatogenesis is enormously complex. Paired palatal shelves first extend vertically from the maxillary processes and must grow sufficiently so that upon horizontal elevation their medial edges come into contact. Epithelia covering the medial shelves disintegrate, allowing their fusion. Key processes involved include epithelial/mesenchymal interactions and transitions. Studies in humans and mice have identified at least 429 genes associated with oral clefting. Reductionist scientific approaches have provided detail about individual genes and pathways in palatogenesis, but the intuitive models generated are not sufficient to represent the enormous complexity of the process. We will employ transcriptome and network analyses to understand how biological components work together to produce system- wide outcomes of epithelial differentiation and adhesion, mesenchymal biomechanical properties affecting remodeling and shelf elevation, and anterior/posterior regionalization of epithelia and mesenchyme. These processes require the integration of multiple cross-regulating signaling pathways. Fibroblast growth factor (FGF) and sonic hedgehog (SHH) are two such pathways, and their information is integrated with other pathways by the transcription factor p63. We will generate bulk and single-cell RNA-seq libraries from the palatal shelves of wild type mice to discover gene coexpression and regulatory networks, and specific cell populations involved in normal palatogenesis. For bulk RNA-seq libraries we will separate anterior and posterior epithelial and mesenchymal compartments allowing region-specific analysis of transcriptional changes. We will use the same approach for four mutant mouse lines, exploiting these gene perturbations to identify key driver genes and interacting pathways within these networks. We will study two activating FGFR2 mutations that exert their differential effects from the epithelium or the mesenchyme (S252W or C342Y) and null mutations of SHH and p63, expressed in the epithelium. Complementary bulk and single-cell RNA-seq libraries will identify differential gene expression and novel key components and pathways critical to palatogenesis. We will use these datasets, in conjunction with publicly available palate-related datasets to build high-resolution, multiscale molecular networks that will be used to develop predictive, mechanistic models of palatogenesis. Novel molecular networks and key regulators identified through the multiscale network modeling approach will be validated by in situ hybridization, immunohistochemistry, palatal organ cultures, and mouse models. Our innovative approach to generating comprehensive datasets, using advanced systems biology technologies, and building multiscale network models of normal and abnormal palatogenesis will have a large impact on the clinical, craniofacial, -omics, and developmental biology fields.

抽象的 口感是最常见的结构出生缺陷之一。手术矫正以及医疗和社会心理 护理施加巨大的个人和社会负担。对left裂病因的了解增加了 有可能导致诊断和治疗的改善。古质发生非常复杂。配对 帕拉塔尔架子首先从上颌过程垂直延伸，必须足够生长，以便在 水平海拔其内侧边缘接触。覆盖内侧架子的上皮分解， 允许他们的融合。涉及的关键过程包括上皮/间质相互作用和过渡。 在人类和小鼠中的研究已经鉴定出至少429个与口服裂口相关的基因。还原主义者 科学方法提供了有关古质发生中各个基因和途径的细节，但是直观 生成的模型不足以表示过程的巨大复杂性。我们将雇用 转录组和网络分析，以了解生物成分如何共同生产系统 - 上皮分化和粘附的广泛结果，间质生物力学特性影响 上皮和间质的重塑和架子抬高以及前/后区域化。这些 过程需要集成多个交叉调节信号通路。成纤维细胞生长因子（FGF） 和声音刺猬（SHH）就是两个这样的途径，它们的信息与其他途径集成在一起 转录因子p63。我们将从帕拉塔尔的货架上产生散装和单细胞RNA-seq库 野生型小鼠发现基因共表达和调节网络，以及参与的特定细胞种群 正常的古质发生。对于散装RNA-seq库，我们将分离前后上皮和 间充质室允许针对转录变化的区域特定分析。我们将使用相同的 四个突变小鼠系的方法，利用这些基因扰动来识别关键驱动基因和 这些网络中的交互途径。我们将研究两个激活的FGFR2突变 上皮或间质（S252W或C342Y）和SHH和无效突变的差异作用 p63，在上皮中表达。互补的散装和单细胞RNA-seq库将识别差异 基因表达和新型关键成分和对古氏生成至关重要的途径。我们将使用这些数据集， 结合公开可用的味觉相关数据集，以构建高分辨率，多尺分子 将用于开发古质发生的预测机械模型的网络。新颖的分子网络 以及通过多尺度网络建模方法确定的关键调节器将由Intu验证 杂交，免疫组织化学，pa骨器官培养物和小鼠模型。我们的创新方法 使用高级系统生物学技术生成综合数据集并建造多尺度 正常和异常古质发生的网络模型将对临床，颅面，颅面有很大影响 - 组和发展生物学领域。