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Hedgehog signaling patterns the oral-aboral axis of the mandibular arch.

Jingyue Xu | Han Liu | Yu Lan | Mike Adam | David E Clouthier | Steven Potter | Rulang Jiang
eLife | 2019

Development of vertebrate jaws involves patterning neural crest-derived mesenchyme cells into distinct subpopulations along the proximal-distal and oral-aboral axes. Although the molecular mechanisms patterning the proximal-distal axis have been well studied, little is known regarding the mechanisms patterning the oral-aboral axis. Using unbiased single-cell RNA-seq analysis followed by in situ analysis of gene expression profiles, we show that Shh and Bmp4 signaling pathways are activated in a complementary pattern along the oral-aboral axis in mouse embryonic mandibular arch. Tissue-specific inactivation of hedgehog signaling in neural crest-derived mandibular mesenchyme led to expansion of BMP signaling activity to throughout the oral-aboral axis of the distal mandibular arch and subsequently duplication of dentary bone in the oral side of the mandible at the expense of tongue formation. Further studies indicate that hedgehog signaling acts through the Foxf1/2 transcription factors to specify the oral fate and pattern the oral-aboral axis of the mandibular mesenchyme.

Pubmed ID: 30638444

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Associated grants

  • Agency: NIDCR NIH HHS, United States
    Id: R01 DE027046
  • Agency: NIH HHS, United States
    Id: R01 DE027046
  • Agency: Shriners Hospitals for Children, International
    Id: #85900
  • Agency: Shriners Hospitals for Children, International
    Id: Grant #85900

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BEAM (tool)

RRID:SCR_007258

Software application that treats the disease-associated markers and their interactions via a bayesian partitioning model and computes, via Markov chain Monte Carlo, the posterior probability that each marker set is associated with the disease. (entry from Genetic Analysis Software)

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Seurat (tool)

RRID:SCR_016341

Software as R package designed for QC, analysis, and exploration of single cell RNA-seq data. Enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data.

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