# Transcriptome and Network Analysis of Cleft Palate

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2020 · $797,772

## Abstract

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 advance...

## Key facts

- **NIH application ID:** 9877508
- **Project number:** 1R01DE029322-01
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Ethylin Wang Jabs
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $797,772
- **Award type:** 1
- **Project period:** 2020-01-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9877508

## Citation

> US National Institutes of Health, RePORTER application 9877508, Transcriptome and Network Analysis of Cleft Palate (1R01DE029322-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9877508. Licensed CC0.

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