1Department of Anthropology, Pennsylvania State University, 2Center for Functional Anatomy and Evolution, Johns Hopkins University School of Medicine, 3Department of Genetics and Genomic Sciences, Mt. Sinai School of Medicine, 4Department of Pathology & Anatomical Sciences, University of Missouri School of Medicine, 5Center for Quantitative Imaging, Pennsylvania State University
Friday 4:00-4:15, Galleria South
A variety of traits have emerged or, conversely been lost during primate evolution. The development of facial prognathism, a complex trait that varies between primate species, results from the interaction of soft tissue composites and the facial skeleton. Evolutionary changes in facial prognathism do not result from independent changes in individual tissues, but from coordinated changes in developmental interactions among diversified cells and tissues. Identifying the gene networks underlying such traits in evolutionary lineages is difficult, if not impossible, even when rich fossil records exist. Identifying candidate genes and developmental dynamics for these traits in laboratory organisms poses a less challenging problem.
Midfacial hypoplasia is a diagnostic character of hundreds of human diseases and transgenic mice carrying the orthologue of some causative human mutations are available. We use data from µCT and µMR images and histological sections to characterize phenotypic variation of the midface in mice carrying different mutations of fibroblast growth factor receptor 2 and 3 genes (Fgfr2 and Fgfr3). Each mouse model shows generalized midfacial hypoplasia, but facial bones, soft tissue structures, and facial sutures are affected differentially depending upon the exact mutation expressed. Analyses of these mouse models shed light on various developmental changes that might lead to an evolutionary reduction in facial prognathism. Although Fgfr2 and Fgfr3 may not be “the” genes “for” facial prognathism in primate evolution, understanding their impact on facial development and the networks in which they function can generate predictions about suites of traits that evolve together due to shared genetic causes
This work was supported in part by a grant from the National Institute Dental and Craniofacial Research to JTR (R01-DE018500, R01-DE18500-S1,S2). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute Dental and Craniofacial Research or the National Institutes of Health.