Transcriptome and Network Analysis of Cleft Palate

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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.