Academic journal article Genetics

Genetic Analysis of Craniofacial Traits in the Medaka

Academic journal article Genetics

Genetic Analysis of Craniofacial Traits in the Medaka

Article excerpt

ABSTRACT

Family and twin studies suggest that a substantial genetic component underlies individual differences in craniofacial morphology. In the current study, we quantified 444 craniofacial traits in 100 individuals from two inbred medaka (Oryzias latipes) strains, HNI and Hd-rR. Relative distances between defined landmarks were measured in digital images of the medaka head region. A total of 379 traits differed significantly between the two strains, indicating that many craniofacial traits are controlled by genetic factors. Of these, 89 traits were analyzed via interval mapping of 184 F^sub 2^ progeny from an intercross between HNI and Hd-rR. We identified quantitative trait loci for 66 craniofacial traits. The highest logarithm of the odds score was 6.2 for linkage group (LG) 9 and 11. Trait L33, which corresponds to the ratio of head length to head height at eye level, mapped to LG9; trait V15, which corresponds to the ratio of snout length to head width measured behind the eyes, mapped to LG11. Our initial results confirm the potential of the medaka as a model system for the genetic analysis of complex traits such as craniofacial morphology.

CRANIOFACIAL morphology is a complex but interesting trait that reveals individual phenotypic differences within a species as well as morphological divergence among species. Multiple genetic factors and environmental variables account for the large degree of variability in human craniofacial morphology. The heritability of human craniofacial morphology has been thoroughly investigated in twins and families. A genetic component has been reported for 60-90% of craniofacial traits, including facial height, position of the lower jaw, and cranial base dimensions (Savoye et al. 1998; Johannsdottir et al. 2005). Further analysis of human linkages is difficult, due in part to sample heterogeneity, limited sample numbers, and a significant impact of environmental factors on craniofacial phenotypes. To control for these effects, animal models are often used to genetically dissect the developmental pathways that operate in concert to govern multifactorial traits.

Single gene mutation analyses in mice and zebrafish have shown that several common signaling cascades function during vertebrate craniofacial development, highlighting the potential of these animals as models. A loss of Sonic hedgehog (Shh) signaling severely reduces the size of the craniofacial skeleton and produces marked craniofacial defects, including complete or partial cyclopia, in both mice and zebrafish (Brand et al. 1996; Chiang et al. 1996; Chen et al. 2001). These data suggest that Shh signaling is crucial for the development of craniofacial components. Similarly, mouse embryos lacking Endothelin-1 (Et-1) show severe defects in Meckel's cartilage in the mandibular arch and the ventral cartilage in the hyoid arch (Kurihara et al. 1994). The mandibular and hyoid arch ventral cartilages are also affected by mutation of sucker (suc), the zebrafish Et-1 ortholog (Miller et al. 2000). Thus, the craniofacial phenotypes of homozygous mouse Et-1 mutants and zebrafish suc mutants are essentially identical. These findings suggest that the molecular mechanisms underlying craniofacial development are largely conserved in vertebrate species.

Quantitative trait locus (QTL) analysis has been used to successfully identify chromosomal regions affecting the quantitative traits, including obesity, bone density, and cerebellum size (Beamer et al. 1999; Brockmann et al. 2000; Airey et al. 2001). The jaw apparatus, one of the most thoroughly investigated craniofacial components, has recently been analyzed as a quantitative trait, and QTL analysis has identified several genomic regions responsible for the size and shape of the mandible in mice (Klingenberg et al. 2001, 2004; Dohmoto et al. 2002). Furthermore, the shape of the oral jaw in the east African cichlid fish has been analyzed using quantitative genetics, and associated QTL have been identified (Albertson et al. …

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