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Dev Biol. 2017 Jun 1;426(1):97-114. doi: 10.1016/j.ydbio.2017.03.025. Epub 2017 Mar 29.

Systems biology of facial development: contributions of ectoderm and mesenchyme.

Author information

1
Department of Cell and Developmental Biology, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA; Computational Bioscience Program, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA. Electronic address: Joan.hooper@ucdenver.edu.
2
Department of Cell and Developmental Biology, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA; Department of Craniofacial Biology, University of Colorado School of Dental Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA. Electronic address: wgfeng2009@gmail.com.
3
Department of Craniofacial Biology, University of Colorado School of Dental Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA. Electronic address: Hong.Li@ucdenver.edu.
4
Department of Biomedical Research, National Jewish Health, 1400 Jackson Street, Denver, CO 80206, USA. Electronic address: Leachs@njhealth.org.
5
Computational Bioscience Program, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA; Department of Medicine, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA. Electronic address: tzu.phang@ucdenver.edu.
6
Computational Bioscience Program, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA. Electronic address: charlotte.siska@ucdenver.edu.
7
Department of Pediatrics, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA. Electronic address: kenneth.l.jones@ucdenver.edu.
8
Human Medical Genetics and Genomics Program, University of Colorado School of Medicine, 12800 E 17th Avenue, Aurora, CO 80045, USA. Electronic address: Richard.Spritz@ucdenver.edu.
9
Computational Bioscience Program, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA; Department of Pharmacology, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA. Electronic address: Larry.Hunter@ucdenver.edu.
10
Department of Cell and Developmental Biology, University of Colorado School of Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA; Department of Craniofacial Biology, University of Colorado School of Dental Medicine, 12801 E 17th Avenue, Aurora, CO 80045, USA. Electronic address: trevor.williams@ucdenver.edu.

Abstract

The rapid increase in gene-centric biological knowledge coupled with analytic approaches for genomewide data integration provides an opportunity to develop systems-level understanding of facial development. Experimental analyses have demonstrated the importance of signaling between the surface ectoderm and the underlying mesenchyme are coordinating facial patterning. However, current transcriptome data from the developing vertebrate face is dominated by the mesenchymal component, and the contributions of the ectoderm are not easily identified. We have generated transcriptome datasets from critical periods of mouse face formation that enable gene expression to be analyzed with respect to time, prominence, and tissue layer. Notably, by separating the ectoderm and mesenchyme we considerably improved the sensitivity compared to data obtained from whole prominences, with more genes detected over a wider dynamic range. From these data we generated a detailed description of ectoderm-specific developmental programs, including pan-ectodermal programs, prominence- specific programs and their temporal dynamics. The genes and pathways represented in these programs provide mechanistic insights into several aspects of ectodermal development. We also used these data to identify co-expression modules specific to facial development. We then used 14 co-expression modules enriched for genes involved in orofacial clefts to make specific mechanistic predictions about genes involved in tongue specification, in nasal process patterning and in jaw development. Our multidimensional gene expression dataset is a unique resource for systems analysis of the developing face; our co-expression modules are a resource for predicting functions of poorly annotated genes, or for predicting roles for genes that have yet to be studied in the context of facial development; and our analytic approaches provide a paradigm for analysis of other complex developmental programs.

KEYWORDS:

Co-expression modules; Epithelial-mesenchymal interaction; Functional genomics; Orofacial clefts; Transcriptome

PMID:
28363736
PMCID:
PMC5530582
DOI:
10.1016/j.ydbio.2017.03.025
[Indexed for MEDLINE]
Free PMC Article

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