Cichlid fishes as a model to understand normal and clinical craniofacial variation.

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Dev Biol. Author manuscript; available in PMC 2017 July 15. Published in final edited form as: Dev Biol. 2016 July 15; 415(2): 338–346. doi:10.1016/j.ydbio.2015.12.018.

Cichlid fishes as a model to understand normal and clinical craniofacial variation Kara E. Powder1,* and R. Craig Albertson1,* 1Department

of Biology, University of Massachusetts, Amherst, MA 01003, USA.

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We have made great strides towards understanding the etiology of craniofacial disorders, especially for ‘simple’ Mendelian traits. However, the facial skeleton is a complex trait, and the full spectrum of genetic, developmental, and environmental factors that contribute to its final geometry remain unresolved. Forward genetic screens are constrained with respect to complex traits due to the types of genes and alleles commonly identified, developmental pleiotropy, and limited information about the impact of environmental interactions. Here, we discuss how studies in an evolutionary model – African cichlid fishes – can complement traditional approaches to understand the genetic and developmental origins of complex shape. Cichlids exhibit an unparalleled range of natural craniofacial morphologies that model normal human variation, and in certain instance mimic human facial dysmorphologies. Moreover, the evolutionary history and genomic architecture of cichlids make them an ideal system to identify the genetic basis of these phenotypes via quantitative trait loci (QTL) mapping and population genomics. Given the molecular conservation of developmental genes and pathways, insights from cichlids are applicable to human facial variation and disease. We review recent work in this system, which has identified lbh as a novel regulator of neural crest cell migration, determined the Wnt and Hedgehog pathways mediate species-specific bone morphologies, and examined how plastic responses to diet modulate adult facial shapes. These studies have not only revealed new roles for existing pathways in craniofacial development, but have identified new genes and mechanisms involved in shaping the craniofacial skeleton. In all, we suggest that combining work in traditional laboratory and evolutionary models offers significant potential to provide a more complete and comprehensive picture of the myriad factors that are involved in the development of complex traits.

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Graphical abstract

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Corresponding Authors: Department of Biology, University of Massachusetts Amherst, 221 Morrill Science Center South, 611 North Pleasant Street, Amherst, MA 01003, Tel: 413-545-2865, Fax: 413-545-3243, K.E.P.: [email protected], R.C.A.: [email protected]. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Powder and Albertson

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Author Manuscript Keywords craniofacial; cichlids; complex trait; morphological variation; evolutionary mutant

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Craniofacial development and disease: progress and challenges

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Over 70% of all birth defects are associated with craniofacial malformations (Hall 2009). Although significant advances have been made in understanding the etiology of many Mendelian craniofacial disorders (e.g., Treacher Collins Syndrome (Kadakia, et al. 2014), Apert Syndrome (Wilkie, et al. 1995), and Crouzon Syndrome (Reardon, et al. 1994)), much less is known about the factors that contribute to complex diseases (e.g. non-syndromic cleft lip and/or palate) and normal facial variation, which result from the cumulative effects of many alleles and their interactions with the environment (Fish, et al. 2014; Glazier, et al. 2002; Hallgrimsson, et al. 2009; Hallgrimsson, et al. 2014; Hirschhorn and Daly 2005; Hochheiser, et al. 2011). Even for monogenetic diseases in which the causative genes are known we still lack a comprehensive picture of the genetic, cellular, and environmental interactions that contribute to the severity of the disease (e.g., the impact of genetic background (Dixon and Dixon 2004)). The National Institute of Dental and Craniofacial Research (NIDCR) initiative FaceBase, a consortium aimed at advancing research in facial development and disease, states that “much research is needed to achieve a molecular and cellular understanding of the mechanisms by which genes and gene products interact to generate complex phenotypes.” Thus, a significant challenge in craniofacial biology remains to uncover the genomic and developmental mechanisms that underlie the production of subtle and complex patterns of variation in craniofacial shape.

The limitations of induced mutations

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Much of our knowledge of craniofacial development has been acquired from induced mutations and loss-of-function experiments in a small handful of model organisms, particularly Mus musculus (mouse), Gallus gallus (chicken), Xenopus laevis (African clawed frog), and Danio rerio (zebrafish). These studies have provided critical insights into the basis of early developmental patterning events and the etiology of craniofacial diseases, particularly “simple” Mendelian disorders. However, traditional forward genetics screens and the use of knockout mutants are not without limitations. We propose that embracing the natural variation present in “evolutionary mutant” models (Albertson, et al. 2009), including cichlid fishes, can overcome some of these limitations and complement our current knowledge of the genetic and developmental basis of normal and extreme, clinical

Dev Biol. Author manuscript; available in PMC 2017 July 15.


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craniofacial variation. The crux of the argument is that all forward genetic analyses are, by definition, based on phenotype, and natural systems provide a vast reservoir of phenotypic variation. An understanding of this natural variation will supplement findings about phenotypes that have been artificially generated through mutagenesis. The limitations of traditional approaches and the complementary nature of evolutionary models are discussed in greater detail below. Screens commonly miss non-essential genes and subtle mutations

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Classic forward genetic approaches screen for abnormal phenotypes in populations of mutagenized animals. These screens typically focus on early and often lethal phenotypes, and are well suited to identify genes that are essential for a particular function. They have a bias towards certain types of genes, such as those that regulate a critical developmental switch or act as integrators of multiple pathways. Many genes are routinely missed by such an approach, including those that have redundant function, act as a genetic modifier, or contribute to variation in a process but are not essential for trait development. While specialized (e.g., “enhancer”) screens (Kile and Hilton 2005; Patton and Zon 2001) can uncover some of these factors, these are labor intensive and require base knowledge or assumptions about gene action. In all, it is becoming increasingly appreciated (e.g., (Bolker 2012)) that new approaches and new models are needed to identify the genes that may have been missed by classic forward genetic screens.

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In addition to disproportionally targeting genes with early essential functions, screens also unequally identify certain types of alleles and mutations. Upwards of 75% of mutant alleles identified in standard laboratory screens are in coding regions and result in severe disruption or complete loss of gene function (Nguyen and Xu 2008). This is perhaps unsurprising, as severe genetic lesions are likely to have more prominent phenotypic defects that are easier to identify by researchers, and speaks to the power and efficiency of forward genetic screens. However, complex traits such as normal facial variation and clinical conditions like nonsyndromic cleft lip and/or palate predominantly do not result from null alleles with large effects, but rather from a compilation of small effects from many genes that act at multiple developmental stages or confer susceptibility to environmental effects (Fish, et al. 2014; Glazier, et al. 2002; Hallgrimsson, et al. 2009; Hallgrimsson, et al. 2014; Hirschhorn and Daly 2005; Hochheiser, et al. 2011). In accordance with this, the overwhelming majority (>80%) of variants implicated in complex traits and diseases by genome wide association studies (GWAS) are predicted to be in non-coding regions (Hindorff, et al. 2009; Khandelwal, et al. 2013; Manolio 2009). Further, genes with essential roles in early development are likely to face strong stabilizing selection, and thus may not contribute to normal patterns of variation. For instance, Shh is critical for proper facial morphogenesis (Belloni, et al. 1996; Chiang, et al. 1996; Hu and Helms 1999; Jeong, et al. 2004; Wada, et al. 2005; Young, et al. 2010). While subtle modulation of this pathway can produce a dosedependent phenotypic continuum during embryonic development, the effect is non-linear such that the range of “normal” variation is quite narrow and even slight changes in Shh levels can result in major malformations such as clefting in adults (Young, et al. 2010). This experiment may explain why this gene has yet to be identified in studies of normal facial variation (Boehringer, et al. 2011; Liu, et al. 2012; Paternoster, et al. 2012; Sherwood, et al.



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2011). As pointed out by Hallgrimsson and colleagues (Hallgrimsson, et al. 2014), it is quite possible (and even likely) that genes not identified by embryonic mutagenesis screens are contributing to the majority of normal facial variation in humans. Developmental pleiotropy limits the assessment of later developmental stages

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Mutagenesis screens are also constrained by developmental pleiotropy, wherein a single gene acts in multiple tissues and/or at multiple developmental stages. Defects at the earliest stage in which the gene has an essential function (e.g. neural crest cell migration) often preclude examination of phenotypes at later developmental stages (e.g. chondrogenesis and facial growth). This problem can be circumvented using conditional knockouts or targeted activation of alleles (Campbell, et al. 2012; Chan, et al. 2007; Patton and Zon 2001), but this requires prior knowledge about the gene of interest. Pleiotropy is a critical concern for facial development, as defects in neural crest cell specification and migration have a higher likelihood of being lethal (Hall 2009), and thus may be less applicable to normal human variation than alterations in later developmental stages such as osteogenesis. In order to understand the etiology of complex traits that manifest later in development, there is a need to supplement traditional approaches with those that specifically address later developmental stages, including adults (Albertson and Yelick 2004). Gene x environment (GxE) interactions account for variation in both Mendelian diseases and complex traits


Genetic screens and genome-wide association studies (GWAS) have identified hundreds of loci that are associated with complex human traits and diseases. However, for most complex traits, these cumulatively have only been able to account for a small percentage of the heritability of phenotypes. Sources of such “missing heritability” are thought to be genetic modifiers (GxG or epistasis) and environmental interactions (GxE) (Eichler, et al. 2010; Gibson 2010; Manolio, et al. 2009). Even for “simple” monogenetic disorders (e.g. cystic fibrosis), we are only beginning to understand the genetic modifiers and environmental interactions that impact disease severity and penetrance (Nadeau 2001); in this way Mendelian phenotypes can act as complex traits (Dipple and McCabe 2000). In addition, the influence of the genetic, cellular, and external environment can have significant impacts on craniofacial development. For instance, sex hormones have drastic effects on embryonic facial patterning (Cohen, et al. 2014), juvenile development (Fujita, et al. 2004; Marquez Hernandez, et al. 2011; Verdonck, et al. 1998), and bone remodeling at juvenile and adult stages (Frenkel, et al. 2010; Nicks, et al. 2010). The hardness of diet can also have a significant impact on craniofacial geometry (Genbrugge, et al. 2011; Parsons, et al. 2014; Swiderski and Zelditch 2013). The role of such sex-specific and GxE interactions represent a long-standing gap in our knowledge of the etiology and pathophysiology of complex diseases that are unlikely to be answered with traditional mutagenesis screens.



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Harnessing natural variation in evolutionary mutants to understand complex traits Nature as a potent “mutagenizing” force While Charles Darwin and other 19th century biologist embraced the astounding natural diversity of living things, the 20th century became the era of model organisms such as the fly and mouse (Davis 2004). Technological advances in genome sequencing and molecular techniques have enabled modern biologists to once again turn to natural variation in nonmodel organisms (discussed in (Albertson, et al. 2009; Bolker 2012; Mahar 2009; Schartl 2014)), spurring on the current “golden age” of comparative and evolutionary genetics (Nadeau and Jiggins 2010). We argue that these advances also open up opportunities to use evolutionary systems to better understand the human condition.


Nature is a source of vast biodiversity, which has accumulated over millions of years as populations are continually challenged by natural (and sexual) selection. For craniofacial structures, trophic adaptations have resulted in morphologies exquisitely matched to feeding niches. Sometimes these phenotypes are extreme and/or discontinuous (i.e., may be considered a phenotypic novelty), such as the snout of an anteater or the cranio-dental skeleton of toothed whales. Alternatively, adaptive radiations can produce extensive continuous variation in craniofacial form. Textbook examples of this continuous variation include Darwin’s finches (Grant 1986; Grant and Grant 2014) and African cichlids (Kocher 2004). Because the mutations that underlie these adaptive phenotypes are part of a well integrated genetic architecture (i.e., they are not deleterious), such systems offer great potential to reveal new insights into the genes and mechanisms that underlie this important trait. Moreover, given that changes in gene regulation are the primary source of both the development of complex traits in humans (Hindorff, et al. 2009; Hirschhorn and Daly 2005; Khandelwal, et al. 2013; Korstanje and Paigen 2002; Manolio 2009) and morphological evolution (Carroll, et al. 2005; Jacob 1977; King and Wilson 1975; Stern 2000; Wray 2007), the study of natural variants should more accurately reflect the number, effect, mode of action, interaction, and environmental sensitivity of genes that underlie complex traits compared to induced mutagenesis screens. Craniofacial development is conserved among vertebrates

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During facial development, neural crest cells (NCCs) must coordinate a complex pattern of molecular and cellular signals from the ectoderm and the endoderm to properly induce, specify, migrate, proliferate, and differentiate into the bones and cartilages of the face (reviewed in (Brugmann, et al. 2006; Santagati and Rijli 2003; Sauka-Spengler and BronnerFraser 2008)). Alterations in any of these processes can produce clinical malformations or variation on which natural selection can act. One of the major biological findings of the late 20th century was that all multicellular animals share a conserved set of genes and circuits that govern development (Carroll, et al. 2005). Craniofacial development is no exception; despite dramatic differences in adult structures, the molecular and morphogenetic processes that mediate NCC and craniofacial development are highly conserved among vertebrates (Knight and Schilling 2006; Medeiros



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and Crump 2012; Schilling 1997). In other words, homology occurs at multiple levels, spanning adult skeletal elements, cellular mechanisms such as migration and fusion, and genes (Shubin, et al. 2009; Wagner 2014). This “deep homology” (Shubin, et al. 2009) allows insights into human facial development from non-mammalian systems, including both traditional models (e.g. zebrafish and chicken) and evolutionary models (e.g. cichlids). For example, mammalian and fish palates have distinct morphologies and are comprised of non-homologous elements (Dougherty, et al. 2013; Murray and Schutte 2004; Swartz, et al. 2011). Despite this, their development requires the action of homologous cell- and tissuelevel processes including migration of cranial neural crest cells, as well as the coordinated outgrowth and fusion of multiple processes and structures (Dougherty, et al. 2013; Murray and Schutte 2004). Further, homologous genes regulate these cellular mechanisms. For instance, loss of irf6 or the microRNA Mirn140 and Pdgf signaling network results in conspicuous orofacial clefting in both humans and zebrafish (Dougherty, et al. 2013; Eberhart, et al. 2008; Kondo, et al. 2002; Li, et al. 2010; Rattanasopha, et al. 2012). These insights confirm the deep homology of the vertebrate skull. While the component parts may vary across taxa, the underlying genetic and developmental logic that assemble these structures are highly conserved. This and other findings (see (Albertson, et al. 2009)) support the idea that a common set of genes may underlie adaptive diversification in the wild and facial dysmorphologies in the clinic. Therefore, insights gleaned from studies in evolutionary models are directly relevant to human development and possibility even disease. In fact, as we illustrate below, the same extreme phenotypic state could even be considered a disease in one species/lineage and an adaptation in a second lineage (Fig. 1).

The evolutionary history of cichlids makes them an ideal system to study Author Manuscript

the genetic basis of craniofacial variation Cichlids (family: Cichlidae) are tropical freshwater fish that have undergone an extraordinary adaptive radiation in terms of the pace, number of species, and degree of morphological diversity (Fryer and Iles 1972; Kocher 2004; Salzburger and Meyer 2004). In all, cichlids account for about 8% of all fish species (Kuraku and Meyer 2008), making them one of the most species-rich vertebrate families (Salzburger and Meyer 2004). Their main radiation (~2000 endemic species) occurred in the East African rift lakes, namely Lakes Malawi, Tanganyika, and Victoria. Within Lake Malawi alone, there are upwards of 1000 species that have evolved within ~1-2 million years (Kornfield and Smith 2000; Salzburger and Meyer 2004; Sturmbauer, et al. 2001; Turner, et al. 2001), with speciation events having occurred as recently as 1,000 years ago (Won, et al. 2005).

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Cichlids demonstrate unparalleled craniofacial variation, analogous to normal and clinical variation in humans A hallmark of cichlid radiations is their incredible diversity in behavior, color, body shape, and, critical for this synopsis, facial morphologies (Fig. 1). Cichlids encompass an extensive variety of trophic strategies, including algae grazing, snail crushing, sand sifting, egg predation, scale eating, and piscivorous hunting, and each of these is associated with different morphological and functional demands (Fryer and Iles 1972; Konings 2001; Kornfield and Smith 2000) (Fig. 1). Despite this wide range of phenotypes, the primary axis



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of facial variation among all African cichlids distinguishes two generalized feeding strategies – biters and suckers (Cooper, et al. 2010). Fish with stout faces, small eyes, tricuspid teeth, and short, downturned jaws are adapted to bite, pick, or scrape attached algae or crush hard mollusks. On the other hand, fish with elongated faces, larger eyes, unicuspid or bicuspid teeth, and longer, isognathus jaws have adapted to suction other fish, small invertebrates, or algae from the water column (Albertson, et al. 2005; Cooper, et al. 2010; Konings 2001; Streelman and Albertson 2006). Notably, cichlid craniofacial variation has evolved along this same axis independently in the three African Great Lakes (Lakes Malawi, Tanganyika, and Victoria) (Cooper, et al. 2010; Fryer and Iles 1972). Despite their independent evolution over markedly different time scales, cichlids from each lake demonstrate remarkable convergence in craniofacial morphologies (Albertson, et al. 2003a; Cooper, et al. 2010; Fryer and Iles 1972). These “experimental replicates” provide a powerful opportunity to determine whether convergent morphologies result from alterations of the same genes and pathways, or whether there are multiple genetic and cellular mechanisms that result in similar phenotypes. Not only is this an important question in evolutionary theory, but such insights into genetic architecture would also provide a better understanding of which aspects of craniofacial anatomy are developmentally plastic and which are inflexible (i.e. canalized).

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Craniofacial variation among most cichlid species is continuous between alternate short versus long face morphologies, and in this way analogous to “normal” facial variation among human populations (Fig. 1). However, certain species have evolved extreme morphologies adapted to specialized feeding methods. In these instances, craniofacial morphologies between cichlid lineages are more discontinuous, mimicking pathological variation in the human facial skeleton such as micrognathia, midface hypoplasia, and facial asymmetries (Fig. 1, (Albertson, et al. 2009)). As with human dysmorphologies, craniofacial differences among cichlids can be detected as early as NCC migration (Albertson and Kocher 2006; Powder, et al. 2014), with additional shape differences accumulating into larval and juvenile stages (Parsons, et al. 2014; Powder, et al. 2015). Cichlids are thus an ideal evolutionary system to study the genetic and developmental origins of both subtle and extreme facial variation due to their (1) extensive morphological variation, (2) mimicking of variation found in humans, and (3) similarities to mammals at the molecular and tissue level. The genomic architecture of Lake Malawi cichlids is ideal for association and QTL mapping studies

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Despite their remarkable phenotypic diversity, cichlids exhibit a relatively high degree of genomic homogeneity due to their rapid evolution (~1-2 million years for Lake Malawi (Sturmbauer, et al. 2001)) and ongoing hybridization. Five complete cichlid genomes are now available (Brawand, et al. 2014), and among the major insights from this work is that approximately half of the polymorphisms identified among species (which shared a common ancestor ~10 million years ago) exhibit incomplete lineage sorting. In other words, a significant proportion of ancestral polymorphisms are still segregating between species via genetic recombination and hybridization (Brawand, et al. 2014; Loh, et al. 2013). The result is a young species flock characterized by relatively low levels of nucleotide diversity (i.e. lower than that between different laboratory strains of zebrafish, (Loh, et al. 2008)) and high



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levels of shared polymorphisms. Notably, these properties mean that genetic/genomic comparisons between cichlid species (or genera) are analogous to those between human populations.

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A combination of high phenotypic variation and low genotypic variation make cichlids an ideal system for population genomics. Specifically, given the high degree of shared polymorphisms (Brawand, et al. 2014; Loh, et al. 2013), global genetic differentiation is low among Lake Malawi cichlids (average FST ≈ 0.2 (Loh, et al. 2008)). Thus outlier loci that exhibit signatures of divergence (e.g. high FST values) are de facto candidates for trait differences between species or genera. Essentially, neutral polymorphisms have not had time to become fixed between species, which means that outlier loci are likely to exist because they mediate a phenotype that is under divergent selection. For instance, a SNP near the neural patterning gene irx1 was found to exhibit an outlier FST value in a genome-wide comparison between cichlid lineages that have distinct brain morphologies (Loh, et al. 2008). This observation suggested that irx1 might mediate differences in brain development between these fishes. Subsequent functional studies supported this hypothesis by showing that differential expression of irx1 is associated with changes in brain patterning that result in differences in the relative size of the telencephalon versus the thalamus in cichlids (Sylvester, et al. 2010).

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With accumulating genomic resources it is now relatively easy to identify divergent loci among cichlids, however linking these loci to a specific trait is not always straightforward because species/lineages usually differ with respect to multiple traits. Pedigree mapping of quantitative traits (e.g., QTL mapping) is a better method with which to link variation in genotype with variation in a specific phenotype. Given their recent divergence, most Lake Malawi cichlid species (and many genera) produce fertile hybrids, enabling the generation of large pedigrees for QTL mapping (e.g. craniofacial traits in (Albertson, et al. 2003b; Albertson, et al. 2005; Cooper, et al. 2011; Hu and Albertson 2014; Parsons, et al. 2012; Parsons, et al. 2015; Stewart and Albertson 2010; Streelman and Albertson 2006)). A key limitation of QTL mapping however is that the identification of causative genes and/or polymorphisms for a QTL can be challenging and expensive due the time and labor involved in generating sufficient numbers of recombinant animals for fine mapping. Thus, population genomics can efficiently identify divergent loci that are under selection, but cannot link genotype to a specific phenotype. Alternatively, QTL mapping can statistically associate genetic intervals to specific phenotypes, but often lacks the resolution to pinpoint specific causative genes and nucleotides.

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Recently, investigators have begun to address these methodological limitations by combining both population genomics and QTL mapping into a single experiment, thereby leveraging the advantages while mitigating the disadvantages of each approach (Albertson, et al. 2014; Barrett and Hoekstra 2011; Parsons and Albertson 2013). For example, we previously used this approach to implicate pax3a in cichlid coloration (Albertson, et al. 2014). We first used QTL mapping to associate a 28cM region with levels of red/yellow pigmentation. This region corresponds to approximately 11Mb of physical sequence and contains ~315 genes, making it daunting to identify candidate genes. Population genomic analysis of this region identified 366 genetic polymorphisms between cichlid species that also differ with respect to



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pigmentation. However, of these, just 17 exhibited high levels of differentiation between the species, suggesting they may be driving the phenotypic differences. One was in the 5′UTR of pax3a, which has been previously associated with specification of pigment cells (Minchin and Hughes 2008). This example demonstrates how population genomic analysis, which takes advantage of recombination in the wild, can be used to effectively narrow the list of candidate genes that underlie a QTL.

Cichlid studies can complement traditional approaches in model organisms


Given their morphological diversity and genomic architecture, cichlids offer a powerful evolutionary system to complement traditional approaches in model organisms such as Mus musculus and Gallus gallus. With the vast number of genetic tools available in laboratory models (e.g., genome editing), the validation of candidate genes identified in cichlids may require experiments in model systems. That said, functional validation of candidate genes (or at least pathways) can also be performed in the cichlid system. The choice of whether to examine the mechanism of gene action within cichlids themselves or within traditional model organisms is dependent on the particulars of the candidate gene or pathway. Cichlids are readily susceptible to pharmacological manipulations through addition of small molecules to their water (Bloomquist, et al. 2015; Fraser, et al. 2008; Fraser, et al. 2013; Hu and Albertson 2014; Parsons and Albertson 2013; Parsons, et al. 2014; Powder, et al. 2015; Roberts, et al. 2011; Sylvester, et al. 2010; Sylvester, et al. 2013). These chemicals have varying degrees of target specificity (i.e. may antagonize the entire Wnt pathway versus a specific ligand), though, and result in embryo-wide changes in gene expression. For candidates that do not have pharmacological agents or require increased specificity, mechanism of gene action can be determined using the battery of experimental methods available in model organisms such as zebrafish and Xenopus, including transgenics, injections (morpholinos and/or overexpression), and transplantations (Albertson, et al. 2005; Powder, et al. 2014). There is also much promise for bringing such experiments from traditional model organisms into the cichlid system. For instance, cichlids are amenable to transgenesis (Fujimura and Kocher 2011; Juntti, et al. 2013), and CRISPR/Cas9-mediated genome editing (Sternberg and Doudna 2015) is a powerful new tool that has shown great promise in non-model organisms, including cichlids (Li, et al. 2014). Below we briefly illustrate how cichlids, in conjunction with such mechanistic analyses, have yielded novel insights into craniofacial development. Lbh is a novel regulator of neural crest cell migration

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Neurocristopathies (Bolande 1974) are syndromes resulting from abnormal neural crest cell (NCC) development, commonly NCC migration or proliferation (Hall 2009). Given the wide variety of NCC derivatives (Hall 2009; Santagati and Rijli 2003; Sauka-Spengler and Bronner-Fraser 2008), neurocristopathies often present with a suite of defects in craniofacial, neural, otic, cardiac, and pigment structures or tissues. We recently identified a novel regulator of neural crest cell development in cichlids. We started with a QTL on linkage group 19 that contributed to variation in the relative length of the mandible (Albertson, et al. 2005; Cooper, et al. 2011). Notably, one of the cichlid species used to



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generate this cross exhibits an extremely short jaw (“evolved micrognathia”) (Fig. 1, far left). Using population genomics, we were able to narrow this region and identify limb bud and heart homolog (lbh) as a candidate gene (Powder, et al. 2014). Lbh is a largely uncharacterized putative transcriptional regulator (Ai, et al. 2008) expressed during vertebrate limb and heart development (Briegel and Joyner 2001), but previously not known to regulate facial development.

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Using loss-of-function analyses in zebrafish and Xenopus, we demonstrated that lbh is necessary in neural crest cells for proper migration (Powder, et al. 2014). Severe depletion of Lbh resulted in dramatic inhibition of migration and complete loss of NCC-derived facial structures, resulting in lethality. Cichlids with alternate short and long jaw morphologies have distinct SNPs around lbh, including a non-synonymous R>Q mutation in the evolutionarily derived fish with a short mandible. We showed that this single amino acid change resulted in discrete shifts in neural crest cell migration patterns. Whereas the “long jaw” variant causes more NCCs to migrate to the mandibular arch, the “short jaw” form results in fewer NCCs migrating anteriorly; this depletion of the anterior pool of NCCs may result in the diminished mandible derived from this population of cells. Even though lbh plays a critical role in NCC migration and contributes to quantitative variation in craniofacial structures, this gene had not been previously identified in traditional screens for craniofacial regulators, perhaps because severe abrogation of Lbh results in lethality (Powder, et al. 2014). Wnt and Hedgehog pathways regulate species-specific bone development


Contrary to our extensive understanding of how early developmental events and genetic mechanisms regulate neural crest cell induction, migration, and patterning (Brugmann, et al. 2006; Santagati and Rijli 2003; Sauka-Spengler and Bronner-Fraser 2008), comparatively little is known about the mechanisms that determine the shape of bones. One challenge to understanding skeletal morphologies is the re-deployment of signaling pathways during multiple stages of development. For example, the Wnt signaling network plays successive critical roles during NCC induction (reviewed in (Sauka-Spengler and Bronner-Fraser 2008)), proliferation and outgrowth of facial mesenchyme (Brugmann, et al. 2007; Brugmann, et al. 2010), fusion of facial prominences (Lan, et al. 2006; Song, et al. 2009), and osteogenesis (reviewed in (Hartmann 2006; Long 2012)). Likewise, the Hedgehog developmental pathway is necessary for NCC survival (Ahlgren and Bronner-Fraser 1999; Billmyre and Klingensmith 2015), facial patterning and outgrowth at multiple stages (Cordero, et al. 2004; Heyne, et al. 2015; Hu, et al. 2003; Jeong, et al. 2004), and chondrogenesis and osteogenesis (Mo, et al. 1997; Wada, et al. 2005; Yang, et al. 2015). This developmental pleiotropy, the iterative usage of a common pathway in multiple tissues or stages, can limit the assessment of later developmental events. For example, conditional loss of a central mediator of Wnt signaling, β-catenin, in neural crest cells results in early loss of these cells (Brault, et al. 2001), precluding assessment of how changes in expression levels, timing, and pattern can result in quantitative differences in bone shape. Recently work has combined QTL mapping, population genomics, and experimental manipulations in cichlids to associate the Hedgehog and Wnt pathways with subtle,



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quantitative variation in bone shape (Hu and Albertson 2014; Loh, et al. 2008; Parsons, et al. 2014; Roberts, et al. 2011). In one study, we mapped QTL for the shape of the interopercle bone and length of the retroarticular process of the mandible to the same genetic interval (Hu and Albertson 2014; Roberts, et al. 2011). Population genomics identified a SNP in this region that is highly divergent in cichlids with alternate morphologies, and resides upstream of the Hedgehog receptor ptch1. The evolutionarily derived ptch1 allele is associated with decreased expression levels of this gene and thus decreased bone deposition, ultimately resulting in a shorter retroarticular process and narrower interopercle bone. These shape changes have important functional consequences, wherein the derived allele confers decreased bite forces but faster jaw movements to fish that eat by suctioning food from the water column (Hu and Albertson 2014; Roberts, et al. 2011). Population genomics also identified a highly divergent SNP in β-catenin between cichlids with alternate craniofacial shapes (Loh, et al. 2008). This SNP is associated with increased levels of Wnt signaling and accelerated rates of bone deposition in the cichlid face (Parsons, et al. 2014). The accelerated bone development prevents outgrowth of the preorbital region, effectively locking into place an early larval phenotype (i.e., paedomorphosis) (Parsons, et al. 2014; Powder, et al. 2015). This ultimately results in a steeper craniofacial slope more resistant to strong bite forces in an animal that eats by shearing algae off of rocks (Cooper, et al. 2011; Parsons, et al. 2014). These studies illustrate how common developmental pathways, often studied at early developmental stages, are iteratively deployed over extended periods of development to produce complex morphologies. Plasticity: remodeling and GxE interactions

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A critical, but under-studied, aspect of craniofacial biology is the extent to which the environment can influence the genotype-phenotype (G-P) map and thus determine how the craniofacial skeleton develops and evolves. “Environment” is a broad term that could refer to either an organism’s internal or external environment. The internal environment includes such factors as endocrine signaling and the biophysical interactions among cells or tissues. The external environment is the physical (or physiological) conditions in which the organism develops, including light, temperature, and mechanical stresses. Both types of environments will act to filter the set of genetic variants that contribute to phenotypic variation (Jamniczky, et al. 2010). Environmental effects cannot be accounted for in GWAS experiments and are thought to be an important source of the “missing” heritability in complex traits, including the craniofacial skeleton (Eichler, et al. 2010; Gibson 2010; Manolio, et al. 2009).

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In the interest of space we limit our discussion to the external forces that influence the shape of the craniofacial skeleton, mainly foraging environment that can impose distinct kinematic demands on the feeding apparatus. Bone is a dynamic tissue that can sense and respond to its mechanical environment (reviewed in (Alaqeel, et al. 2006; Nguyen and Jacobs 2013; Papachroni, et al. 2009; Robling and Turner 2009)). Consistent with this, genes that participate in bone cell development and matrix deposition were found to be up or down regulated during remodeling of the cichlid pharyngeal jaw in response to diet changes (Gunter, et al. 2013; Schneider, et al. 2014). However, despite an emerging understanding of plasticity at the transcript level, we lack a comprehensive picture of the genetic architecture of this important trait. For instance, how many genes contribute to a plastic response? Do



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different sets of genes underlie trait development in different environments? Or is plasticity regulated by the same genes acting across environments but in which alleles are differentially sensitive to environmental conditions? Genetic mapping experiments performed in different environments can help to address these outstanding questions (e.g., (Kuttner, et al. 2014)), and we have recently performed such studies in cichlids (Parsons, et al., in preparation). Specifically, F3 hybrid families were split and reared for 6 months in alternate foraging environments that imposed distinct kinematic demands on the feeding apparatus, but were otherwise nutritionally identical. The mapping results demonstrate that the foraging environment strongly influences the G-P map. Of 22 identified QTL for a variety of traits, only 1 was significant in both environments; in other words, distinct loci regulate the response to distinct environments. This observation suggests that cryptic genetic variation, a pool of genetic variation that does not result in phenotypic variation under “normal” conditions (Gibson and Dworkin 2004; Paaby and Rockman 2014), is prominent for the craniofacial skeleton. We further detected instances of allele sensitivity to foraging conditions in that one haplotype showed a plastic response while the alternate haplotype did not (Parsons, et al., in preparation). While much work is needed to determine the mechanistic basis of such GxE interactions, studies like this confirm that the foraging environment is a potent force that can influence how genetic variation translates to morphology. Given differences in food items between distinct human populations (e.g., hunter-gatherer to agrarian transitions in early humans as well as modern geographical differences in diet), these results are directly relative to human craniofacial biology. More generally, they support a shift to an eco-devo approach (Abouheif, et al. 2014; Gilbert and Epel 2008), wherein the environment is explicitly incorporated into genetic mapping and developmental studies.

Author Manuscript

Conclusions Despite our extensive knowledge of early craniofacial patterning, we are relatively ignorant of the genetic, cellular, and environmental mechanisms that combine over extended periods of development to produce “normal” variation in humans, and underlie many complex craniofacial malformations. We propose that studying natural variation in non-model animals will be an effective and fruitful approach to determine the types of genes, mutations, and environmental influences that ultimately result in the extraordinary range of human faces. The “evolutionary mutant” cichlid system is ideal for this approach, given their unparalleled array of facial variation and powerful genetic tools. Experiments described here complement traditional approaches, and will advance our understanding of the genomic and developmental origins of complex morphologies.

Author Manuscript

Acknowledgements This work was supported by NSF Career IOS-1054909 (RCA) and NIH/NIDCR 1F32DE023707 (KEP).

References Abouheif E, Fave MJ, Ibarraran-Viniegra AS, Lesoway MP, Rafiqi AM, Rajakumar R. Eco-evo-devo: the time has come. Adv Exp Med Biol. 2014; 781:107–25. [PubMed: 24277297]



Page 13

Author Manuscript Author Manuscript Author Manuscript Author Manuscript

Abzhanov A, Protas M, Grant BR, Grant PR, Tabin CJ. Bmp4 and morphological variation of beaks in Darwin's finches. Science. 2004; 305(5689):1462–5. [PubMed: 15353802] Ahlgren SC, Bronner-Fraser M. Inhibition of sonic hedgehog signaling in vivo results in craniofacial neural crest cell death. Curr Biol. 1999; 9(22):1304–14. [PubMed: 10574760] Ai J, Wang Y, Tan K, Deng Y, Luo N, Yuan W, Wang Z, Li Y, Wang Y, Mo X. A human homolog of mouse Lbh gene, hLBH, expresses in heart and activates SRE and AP-1 mediated MAPK signaling pathway. Mol Biol Rep. 2008; 35(2):179–187. [PubMed: 17390236] Alaqeel SM, Hinton RJ, Opperman LA. Cellular response to force application at craniofacial sutures. Orthod Craniofac Res. 2006; 9(3):111–22. [PubMed: 16918675] Albertson RC, Cresko WA, Detrich H 3rd, Postlethwait JH. Evolutionary mutant models for human disease. Trends Genet. 2009; 25(2):74–81. [PubMed: 19108930] Albertson RC, Kocher TD. Genetic and developmental basis of cichlid trophic diversity. Heredity (Edinb). 2006; 97(3):211–21. [PubMed: 16835594] Albertson RC, Powder KE, Hu Y, Coyle KP, Roberts RB, Parsons KJ. Genetic basis of continuous variation in the levels and modular inheritance of pigmentation in cichlid fishes. Mol Ecol. 2014; 23(21):5135–50. [PubMed: 25156298] Albertson RC, Streelman JT, Kocher TD. Directional selection has shaped the oral jaws of Lake Malawi cichlid fishes. Proc Natl Acad Sci U S A. 2003a; 100(9):5252–7. [PubMed: 12704237] Albertson RC, Streelman JT, Kocher TD. Genetic basis of adaptive shape differences in the cichlid head. J Hered. 2003b; 94(4):291–301. [PubMed: 12920100] Albertson RC, Streelman JT, Kocher TD, Yelick PC. Integration and evolution of the cichlid mandible: the molecular basis of alternate feeding strategies. Proc Natl Acad Sci U S A. 2005; 102(45): 16287–92. [PubMed: 16251275] Albertson RC, Yelick PC. Morphogenesis of the jaw: development beyond the embryo. Methods Cell Biol. 2004; 76:437–54. [PubMed: 15602886] Barrett RD, Hoekstra HE. Molecular spandrels: tests of adaptation at the genetic level. Nat Rev Genet. 2011; 12(11):767–80. [PubMed: 22005986] Belloni E, Muenke M, Roessler E, Traverso G, Siegel-Bartelt J, Frumkin A, Mitchell HF, Donis-Keller H, Helms C, Hing AV. Identification of Sonic hedgehog as a candidate gene responsible for holoprosencephaly. Nat Genet. 1996; 14(3):353–6. [PubMed: 8896571] Billmyre KK, Klingensmith J. Sonic hedgehog from pharyngeal arch 1 epithelium is necessary for early mandibular arch cell survival and later cartilage condensation differentiation. Dev Dyn. 2015; 244(4):564–76. [PubMed: 25626636] Bloomquist RF, Parnell NF, Phillips KA, Fowler TE, Yu TY, Sharpe PT, Streelman JT. Coevolutionary patterning of teeth and taste buds. Proc Natl Acad Sci U S A. 2015; 112(44):E5954–62. [PubMed: 26483492] Boehringer S, van der Lijn F, Liu F, Gunther M, Sinigerova S, Nowak S, Ludwig KU, Herberz R, Klein S, Hofman A. Genetic determination of human facial morphology: links between cleft-lips and normal variation. Eur J Hum Genet. 2011; 19(11):1192–7. [PubMed: 21694738] Bolande RP. The neurocristopathies: A unifying concept of disease arising in neural crest maldevelopment. Human Pathology. 1974; 5(4):409–429. Bolker J. Model organisms: There's more to life than rats and flies. Nature. 2012; 491(7422):31–3. [PubMed: 23128209] Brault V, Moore R, Kutsch S, Ishibashi M, Rowitch DH, McMahon AP, Sommer L, Boussadia O, Kemler R. Inactivation of the beta-catenin gene by Wnt1-Cre-mediated deletion results in dramatic brain malformation and failure of craniofacial development. Development. 2001; 128(8):1253–64. [PubMed: 11262227] Brawand D, Wagner CE, Li YI, Malinsky M, Keller I, Fan S, Simakov O, Ng AY, Lim ZW, Bezault E. The genomic substrate for adaptive radiation in African cichlid fish. Nature. 2014; 513(7518):375– 81. [PubMed: 25186727] Briegel K, Joyner A. Identification and characterization of Lbh, a novel conserved nuclear protein expressed during early limb and heart development. Dev Biol. 2001; 233(2):291–304. [PubMed: 11336496]



Page 14


Brugmann SA, Goodnough LH, Gregorieff A, Leucht P, ten Berge D, Fuerer C, Clevers H, Nusse R, Helms JA. Wnt signaling mediates regional specification in the vertebrate face. Development. 2007; 134(18):3283–95. [PubMed: 17699607] Brugmann SA, Powder KE, Young NM, Goodnough LH, Hahn SM, James AW, Helms JA, Lovett M. Comparative gene expression analysis of avian embryonic facial structures reveals new candidates for human craniofacial disorders. Hum Mol Genet. 2010; 19(5):920–30. [PubMed: 20015954] Brugmann SA, Tapadia MD, Helms JA. The molecular origins of species-specific facial pattern. Curr Top Dev Biol. 2006; 73:1–42. [PubMed: 16782454] Campbell LJ, Willoughby JJ, Jensen AM. Two types of Tet-On transgenic lines for doxycyclineinducible gene expression in zebrafish rod photoreceptors and a gateway-based tet-on toolkit. PLoS ONE. 2012; 7(12):e51270. [PubMed: 23251476] Carroll, SB.; Grenier, JK.; Weatherbee, SD. From DNA to Diversity: Molecular Genetics and the Evolution of Animal Design. 2nd. Blackwell: 2005. Chan W, Costantino N, Li R, Lee SC, Su Q, Melvin D, Court DL, Liu P. A recombineering based approach for high-throughput conditional knockout targeting vector construction. Nucleic Acids Res. 2007; 35(8):e64. [PubMed: 17426124] Chiang C, Litingtung Y, Lee E, Young KE, Corden JL, Westphal H, Beachy PA. Cyclopia and defective axial patterning in mice lacking Sonic hedgehog gene function. Nature. 1996; 383(6599): 407–13. [PubMed: 8837770] Cohen SP, LaChappelle AR, Walker BS, Lassiter CS. Modulation of estrogen causes disruption of craniofacial chondrogenesis in Danio rerio. Aquat Toxicol. 2014; 152:113–20. [PubMed: 24747083] Cooper WJ, Parsons K, McIntyre A, Kern B, McGee-Moore A, Albertson RC. Bentho-pelagic divergence of cichlid feeding architecture was prodigious and consistent during multiple adaptive radiations within African rift-lakes. PLoS One. 2010; 5(3):e9551. [PubMed: 20221400] Cooper WJ, Wernle J, Mann K, Albertson RC. Functional and Genetic Integration in the Skulls of Lake Malawi Cichlids. Evolutionary Biology. 2011; 38(3):316–334. Cordero D, Marcucio R, Hu D, Gaffield W, Tapadia M, Helms JA. Temporal perturbations in sonic hedgehog signaling elicit the spectrum of holoprosencephaly phenotypes. J Clin Invest. 2004; 114(4):485–94. [PubMed: 15314685] Davis RH. The age of model organisms. Nat Rev Genet. 2004; 5(1):69–76. [PubMed: 14708017] Dipple KM, McCabe ER. Phenotypes of patients with “simple” Mendelian disorders are complex traits: thresholds, modifiers, and systems dynamics. Am J Hum Genet. 2000; 66(6):1729–35. [PubMed: 10793008] Dixon J, Dixon MJ. Genetic background has a major effect on the penetrance and severity of craniofacial defects in mice heterozygous for the gene encoding the nucleolar protein Treacle. Dev Dyn. 2004; 229(4):907–14. [PubMed: 15042714] Dougherty M, Kamel G, Grimaldi M, Gfrerer L, Shubinets V, Ethier R, Hickey G, Cornell RA, Liao EC. Distinct requirements for wnt9a and irf6 in extension and integration mechanisms during zebrafish palate morphogenesis. Development. 2013; 140(1):76–81. [PubMed: 23154410] Eberhart JK, He X, Swartz ME, Yan YL, Song H, Boling TC, Kunerth AK, Walker MB, Kimmel CB, Postlethwait JH. MicroRNA Mirn140 modulates Pdgf signaling during palatogenesis. Nat Genet. 2008; 40(3):290–8. [PubMed: 18264099] Eichler EE, Flint J, Gibson G, Kong A, Leal SM, Moore JH, Nadeau JH. Missing heritability and strategies for finding the underlying causes of complex disease. Nat Rev Genet. 2010; 11(6):446– 50. [PubMed: 20479774] Fish JL, Sklar RS, Woronowicz KC, Schneider RA. Multiple developmental mechanisms regulate species-specific jaw size. Development. 2014; 141(3):674–84. [PubMed: 24449843] Fraser GJ, Bloomquist RF, Streelman JT. A periodic pattern generator for dental diversity. BMC Biol. 2008; 6:32. [PubMed: 18625062] Fraser GJ, Bloomquist RF, Streelman JT. Common developmental pathways link tooth shape to regeneration. Dev Biol. 2013; 377(2):399–414. [PubMed: 23422830] Frenkel B, Hong A, Baniwal SK, Coetzee GA, Ohlsson C, Khalid O, Gabet Y. Regulation of adult bone turnover by sex steroids. J Cell Physiol. 2010; 224(2):305–10. [PubMed: 20432458] Dev Biol. Author manuscript; available in PMC 2017 July 15.


Page 15


Fryer, G.; Iles, TD. The Cichlid Fishes of the Great Lakes of Africa: Their Biology and Evolution. T.F.H. Publications; 1972. Fujimura K, Kocher TD. Tol2-mediated transgenesis in tilapia (Oreochromis niloticus). Aquaculture. 2011; 319(3-4):342–346. [PubMed: 21938082] Fujita T, Ohtani J, Shigekawa M, Kawata T, Kaku M, Kohno S, Tsutsui K, Tenjo K, Motokawa M, Tohma Y. Effects of sex hormone disturbances on craniofacial growth in newborn mice. J Dent Res. 2004; 83(3):250–4. [PubMed: 14981129] Genbrugge A, Heyde AS, Adriaens D, Boone M, Van Hoorebeke L, Dirckx J, Aerts P, Podos J, Herrel A. Ontogeny of the cranial skeleton in a Darwin's finch (Geospiza fortis). J Anat. 2011; 219(2): 115–31. [PubMed: 21599660] Gibson G. Hints of hidden heritability in GWAS. Nat Genet. 2010; 42(7):558–60. [PubMed: 20581876] Gibson G, Dworkin I. Uncovering cryptic genetic variation. Nat Rev Genet. 2004; 5(9):681–90. [PubMed: 15372091] Gilbert, SF.; Epel, D. Ecological Developmental Biology: Integrating Epigenetics, Medicine, and Evolution. Sinauer Associates; Sunderland, MA: 2008. Glazier AM, Nadeau JH, Aitman TJ. Finding genes that underlie complex traits. Science. 2002; 298(5602):2345–9. [PubMed: 12493905] Grant, PR. Ecology and Evolution of Darwin's Finches. Princeton University Press; 1986. Grant, PR.; Grant, BR. 40 Years of Evolution: Darwin's Finches on Daphne Major Island. Princeton University Press; 2014. Gunter HM, Fan S, Xiong F, Franchini P, Fruciano C, Meyer A. Shaping development through mechanical strain: the transcriptional basis of diet-induced phenotypic plasticity in a cichlid fish. Mol Ecol. 2013; 22(17):4516–31. [PubMed: 23952004] Hall, BK. The Neural Crest and Neural Crest Cells in Vertebrate Development and Evolution. Springer; 2009. Hallgrimsson B, Jamniczky H, Young NM, Rolian C, Parsons TE, Boughner JC, Marcucio RS. Deciphering the Palimpsest: Studying the Relationship Between Morphological Integration and Phenotypic Covariation. Evol Biol. 2009; 36(4):355–376. [PubMed: 23293400] Hallgrimsson B, Mio W, Marcucio RS, Spritz R. Let's Face It-Complex Traits Are Just Not That Simple. PLoS Genet. 2014; 10(11):e1004724. [PubMed: 25375250] Hartmann C. A Wnt canon orchestrating osteoblastogenesis. Trends Cell Biol. 2006; 16(3):151–8. [PubMed: 16466918] Heyne GW, Melberg CG, Doroodchi P, Parins KF, Kietzman HW, Everson JL, Ansen-Wilson LJ, Lipinski RJ. Definition of critical periods for Hedgehog pathway antagonist-induced holoprosencephaly, cleft lip, and cleft palate. PLoS One. 2015; 10(3):e0120517. [PubMed: 25793997] Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, Manolio TA. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A. 2009; 106(23):9362–7. [PubMed: 19474294] Hirschhorn JN, Daly MJ. Genome-wide association studies for common diseases and complex traits. Nat Rev Genet. 2005; 6(2):95–108. [PubMed: 15716906] Hochheiser H, Aronow BJ, Artinger K, Beaty TH, Brinkley JF, Chai Y, Clouthier D, Cunningham ML, Dixon M, Donahue LR. The FaceBase Consortium: a comprehensive program to facilitate craniofacial research. Dev Biol. 2011; 355(2):175–82. [PubMed: 21458441] Hu D, Helms JA. The role of sonic hedgehog in normal and abnormal craniofacial morphogenesis. Development. 1999; 126(21):4873–84. [PubMed: 10518503] Hu D, Marcucio RS, Helms JA. A zone of frontonasal ectoderm regulates patterning and growth in the face. Development. 2003; 130(9):1749–58. [PubMed: 12642481] Hu Y, Albertson RC. Hedgehog signaling mediates adaptive variation in a dynamic functional system in the cichlid feeding apparatus. Proc Natl Acad Sci U S A. 2014; 111(23):8530–4. [PubMed: 24912175] Jacob F. Evolution and tinkering. Science. 1977; 196(4295):1161–6. [PubMed: 860134]



Page 16


Jamniczky HA, Boughner JC, Rolian C, Gonzalez PN, Powell CD, Schmidt EJ, Parsons TE, Bookstein FL, Hallgrimsson B. Rediscovering Waddington in the post-genomic age: Operationalising Waddington's epigenetics reveals new ways to investigate the generation and modulation of phenotypic variation. Bioessays. 2010; 32(7):553–8. [PubMed: 20544734] Jeong J, Mao J, Tenzen T, Kottmann AH, McMahon AP. Hedgehog signaling in the neural crest cells regulates the patterning and growth of facial primordia. Genes Dev. 2004; 18(8):937–51. [PubMed: 15107405] Juntti SA, Hu CK, Fernald RD. Tol2-mediated generation of a transgenic haplochromine cichlid, Astatotilapia burtoni. PLoS One. 2013; 8(10):e77647. [PubMed: 24204902] Kadakia S, Helman SN, Badhey AK, Saman M, Ducic Y. Treacher Collins Syndrome: the genetics of a craniofacial disease. Int J Pediatr Otorhinolaryngol. 2014; 78(6):893–8. [PubMed: 24690222] Khandelwal KD, van Bokhoven H, Roscioli T, Carels CE, Zhou H. Genomic approaches for studying craniofacial disorders. Am J Med Genet C Semin Med Genet. 2013; 163C(4):218–31. [PubMed: 24142857] Kile BT, Hilton DJ. The art and design of genetic screens: mouse. Nat Rev Genet. 2005; 6(7):557–67. [PubMed: 15951745] King MC, Wilson AC. Evolution at two levels in humans and chimpanzees. Science. 1975; 188(4184): 107–16. [PubMed: 1090005] Knight RD, Schilling TF. Cranial neural crest and development of the head skeleton. Adv Exp Med Biol. 2006; 589:120–33. [PubMed: 17076278] Kocher TD. Adaptive evolution and explosive speciation: the cichlid fish model. Nat Rev Genet. 2004; 5(4):288–98. [PubMed: 15131652] Kondo S, Schutte BC, Richardson RJ, Bjork BC, Knight AS, Watanabe Y, Howard E, de Lima RL, Daack-Hirsch S, Sander A. Mutations in IRF6 cause Van der Woude and popliteal pterygium syndromes. Nat Genet. 2002; 32(2):285–9. [PubMed: 12219090] Konings, A. Malawi cichlids in their natural habitat. Cichlid Press; El Paso, TX: 2001. Kornfield I, Smith PF. African Cichlid Fishes: Model Systems for Evolutionary Biology. Annual Review of Ecology and Systematics. 2000; 31:163–196. Korstanje R, Paigen B. From QTL to gene: the harvest begins. Nat Genet. 2002; 31(3):235–6. [PubMed: 12089518] Kuraku S, Meyer A. Genomic analysis of cichlid fish 'natural mutants'. Curr Opin Genet Dev. 2008; 18(6):551–8. [PubMed: 19095433] Kuttner E, Parsons KJ, Easton AA, Skulason S, Danzmann RG, Ferguson MM. Hidden genetic variation evolves with ecological specialization: the genetic basis of phenotypic plasticity in Arctic charr ecomorphs. Evol Dev. 2014; 16(4):247–57. [PubMed: 24920458] Lan Y, Ryan RC, Zhang Z, Bullard SA, Bush JO, Maltby KM, Lidral AC, Jiang R. Expression of Wnt9b and activation of canonical Wnt signaling during midfacial morphogenesis in mice. Dev Dyn. 2006; 235(5):1448–54. [PubMed: 16496313] Li L, Meng T, Jia Z, Zhu G, Shi B. Single nucleotide polymorphism associated with nonsyndromic cleft palate influences the processing of miR-140. Am J Med Genet A. 2010; 152A(4):856–62. [PubMed: 20358594] Li M, Yang H, Zhao J, Fang L, Shi H, Li M, Sun Y, Zhang X, Jiang D, Zhou L. Efficient and heritable gene targeting in tilapia by CRISPR/Cas9. Genetics. 2014; 197(2):591–9. [PubMed: 24709635] Liu F, van der Lijn F, Schurmann C, Zhu G, Chakravarty MM, Hysi PG, Wollstein A, Lao O, de Bruijne M, Ikram MA. A genome-wide association study identifies five loci influencing facial morphology in Europeans. PLoS Genet. 2012; 8(9):e1002932. [PubMed: 23028347] Liu W, Sun X, Braut A, Mishina Y, Behringer RR, Mina M, Martin JF. Distinct functions for Bmp signaling in lip and palate fusion in mice. Development. 2005; 132(6):1453–61. [PubMed: 15716346] Loh YH, Bezault E, Muenzel FM, Roberts RB, Swofford R, Barluenga M, Kidd CE, Howe AE, Di Palma F, Lindblad-Toh K. Origins of shared genetic variation in African cichlids. Mol Biol Evol. 2013; 30(4):906–17. [PubMed: 23275489]



Page 17


Loh YH, Katz L, Mims M, Kocher TD, Yi SV, Streelman JT. Comparative analysis reveals signatures of differentiation amid genomic polymorphism in Lake Malawi cichlids. Genome Biol. 2008; 8(7):R113. [PubMed: 18616806] Long F. Building strong bones: molecular regulation of the osteoblast lineage. Nat Rev Mol Cell Biol. 2012; 13(1):27–38. [PubMed: 22189423] Mahar B. Evolution: Biology's next top model? Nature. 2009; 458:695–698. [PubMed: 19360058] Manolio TA. Cohort studies and the genetics of complex disease. Nat Genet. 2009; 41(1):5–6. [PubMed: 19112455] Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, McCarthy MI, Ramos EM, Cardon LR, Chakravarti A. Finding the missing heritability of complex diseases. Nature. 2009; 461(7265):747–53. [PubMed: 19812666] Marquez Hernandez RA, Ohtani J, Fujita T, Sunagawa H, Ishikawa E, Tsubamoto N, Kawata T, Kaku M, Motokawa M, Tanne K. Mandibular and femoral growth alteration after sex hormone disruption in growing mice. Orthod Craniofac Res. 2011; 14(2):63–9. [PubMed: 21457455] Medeiros DM, Crump JG. New perspectives on pharyngeal dorsoventral patterning in development and evolution of the vertebrate jaw. Dev Biol. 2012; 371(2):121–35. [PubMed: 22960284] Minchin JE, Hughes SM. Sequential actions of Pax3 and Pax7 drive xanthophore development in zebrafish neural crest. Dev Biol. 2008; 317(2):508–22. [PubMed: 18417109] Mo R, Freer AM, Zinyk DL, Crackower MA, Michaud J, Heng HH, Chik KW, Shi XM, Tsui LC, Cheng SH. Specific and redundant functions of Gli2 and Gli3 zinc finger genes in skeletal patterning and development. Development. 1997; 124(1):113–23. [PubMed: 9006072] Murray JC, Schutte BC. Cleft palate: players, pathways, and pursuits. J Clin Invest. 2004; 113(12): 1676–8. [PubMed: 15199400] Nadeau JH. Modifier genes in mice and humans. Nat Rev Genet. 2001; 2(3):165–74. [PubMed: 11256068] Nadeau NJ, Jiggins CD. A golden age for evolutionary genetics? Genomic studies of adaptation in natural populations. Trends Genet. 2010; 26(11):484–92. [PubMed: 20851493] Nguyen AM, Jacobs CR. Emerging role of primary cilia as mechanosensors in osteocytes. Bone. 2013; 54(2):196–204. [PubMed: 23201223] Nguyen D, Xu T. The expanding role of mouse genetics for understanding human biology and disease. Dis Model Mech. 2008; 1(1):56–66. [PubMed: 19048054] Nicks KM, Fowler TW, Gaddy D. Reproductive hormones and bone. Curr Osteoporos Rep. 2010; 8(2): 60–7. [PubMed: 20425612] Paaby AB, Rockman MV. Cryptic genetic variation: evolution's hidden substrate. Nat Rev Genet. 2014; 15(4):247–58. [PubMed: 24614309] Papachroni KK, Karatzas DN, Papavassiliou KA, Basdra EK, Papavassiliou AG. Mechanotransduction in osteoblast regulation and bone disease. Trends Mol Med. 2009; 15(5):208–16. [PubMed: 19362057] Parsons KJ, Albertson RC. Unifying and generalizing the two strands of evo devo. Trends Ecol Evol. 2013; 28(10):584–91. [PubMed: 23876674] Parsons KJ, Marquez E, Albertson RC. Constraint and opportunity: the genetic basis and evolution of modularity in the cichlid mandible. Am Nat. 2012; 179(1):64–78. [PubMed: 22173461] Parsons KJ, Trent Taylor A, Powder KE, Albertson RC. Wnt signalling underlies the evolution of new phenotypes and craniofacial variability in Lake Malawi cichlids. Nat Commun. 2014; 5:3629. [PubMed: 24699776] Parsons KJ, Wang J, Anderson G, Albertson RC. Nested Levels of Adaptive Divergence: The Genetic Basis of Craniofacial Divergence and Ecological Sexual Dimorphism. G3 (Bethesda). 2015; 5(8): 1613–24. [PubMed: 26038365] Paternoster L, Zhurov AI, Toma AM, Kemp JP, St Pourcain B, Timpson NJ, McMahon G, McArdle W, Ring SM, Smith GD. Genome-wide association study of three-dimensional facial morphology identifies a variant in PAX3 associated with nasion position. Am J Hum Genet. 2012; 90(3):478– 85. [PubMed: 22341974]



Page 18


Patton EE, Zon LI. The art and design of genetic screens: zebrafish. Nat Rev Genet. 2001; 2(12):956– 66. [PubMed: 11733748] Powder KE, Cousin H, McLinden GP, Craig Albertson R. A Nonsynonymous Mutation in the Transcriptional Regulator lbh Is Associated with Cichlid Craniofacial Adaptation and Neural Crest Cell Development. Mol Biol Evol. 2014 Powder KE, Milch K, Asselin G, Albertson RC. Constraint and diversification of developmental trajectories in cichlid facial morphologies. Evodevo. 2015; 6:25. [PubMed: 26225206] Rattanasopha S, Tongkobpetch S, Srichomthong C, Siriwan P, Suphapeetiporn K, Shotelersuk V. PDGFRa mutations in humans with isolated cleft palate. Eur J Hum Genet. 2012; 20(10):1058– 62. [PubMed: 22473090] Reardon W, Winter RM, Rutland P, Pulleyn LJ, Jones BM, Malcolm S. Mutations in the fibroblast growth factor receptor 2 gene cause Crouzon syndrome. Nat Genet. 1994; 8(1):98–103. [PubMed: 7987400] Roberts RB, Hu Y, Albertson RC, Kocher TD. Craniofacial divergence and ongoing adaptation via the hedgehog pathway. Proc Natl Acad Sci U S A. 2011; 108(32):13194–13199. [PubMed: 21788496] Robling AG, Turner CH. Mechanical signaling for bone modeling and remodeling. Crit Rev Eukaryot Gene Expr. 2009; 19(4):319–38. [PubMed: 19817708] Salzburger W, Meyer A. The species flocks of East African cichlid fishes: recent advances in molecular phylogenetics and population genetics. Naturwissenschaften. 2004; 91(6):277–90. [PubMed: 15241604] Santagati F, Rijli FM. Cranial neural crest and the building of the vertebrate head. Nat Rev Neurosci. 2003; 4(10):806–18. [PubMed: 14523380] Sauka-Spengler T, Bronner-Fraser M. A gene regulatory network orchestrates neural crest formation. Nat Rev Mol Cell Biol. 2008; 9(7):557–68. [PubMed: 18523435] Schartl M. Beyond the zebrafish: diverse fish species for modeling human disease. Dis Model Mech. 2014; 7(2):181–92. [PubMed: 24271780] Schilling TF. Genetic analysis of craniofacial development in the vertebrate embryo. Bioessays. 1997; 19(6):459–68. [PubMed: 9204763] Schneider RF, Li Y, Meyer A, Gunter HM. Regulatory gene networks that shape the development of adaptive phenotypic plasticity in a cichlid fish. Mol Ecol. 2014; 23(18):4511–26. [PubMed: 25041245] Sherwood RJ, Duren DL, Mahaney MC, Blangero J, Dyer TD, Cole SA, Czerwinski SA, Chumlea WC, Siervogel RM, Choh AC. A genome-wide linkage scan for quantitative trait loci influencing the craniofacial complex in humans (Homo sapiens sapiens). Anat Rec (Hoboken). 2011; 294(4): 664–75. [PubMed: 21328561] Shubin N, Tabin C, Carroll S. Deep homology and the origins of evolutionary novelty. Nature. 2009; 457(7231):818–23. [PubMed: 19212399] Song L, Li Y, Wang K, Wang YZ, Molotkov A, Gao L, Zhao T, Yamagami T, Wang Y, Gan Q. Lrp6mediated canonical Wnt signaling is required for lip formation and fusion. Development. 2009; 136(18):3161–71. [PubMed: 19700620] Stern DL. Evolutionary developmental biology and the problem of variation. Evolution. 2000; 54(4): 1079–91. [PubMed: 11005278] Sternberg SH, Doudna JA. Expanding the Biologist's Toolkit with CRISPR-Cas9. Mol Cell. 2015; 58(4):568–74. [PubMed: 26000842] Stewart TA, Albertson RC. Evolution of a unique predatory feeding apparatus: functional anatomy, development and a genetic locus for jaw laterality in Lake Tanganyika scale-eating cichlids. BMC Biol. 2010; 8:8. [PubMed: 20102595] Streelman JT, Albertson RC. Evolution of novelty in the cichlid dentition. J Exp Zool B Mol Dev Evol. 2006; 306(3):216–26. [PubMed: 16555305] Sturmbauer C, Baric S, Salzburger W, Ruber L, Verheyen E. Lake level fluctuations synchronize genetic divergences of cichlid fishes in African lakes. Mol Biol Evol. 2001; 18(2):144–54. [PubMed: 11158373]



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Author Manuscript Author Manuscript Author Manuscript

Suzuki S, Marazita ML, Cooper ME, Miwa N, Hing A, Jugessur A, Natsume N, Shimozato K, Ohbayashi N, Suzuki Y. Mutations in BMP4 are associated with subepithelial, microform, and overt cleft lip. Am J Hum Genet. 2009; 84(3):406–11. [PubMed: 19249007] Swartz ME, Sheehan-Rooney K, Dixon MJ, Eberhart JK. Examination of a palatogenic gene program in zebrafish. Dev Dyn. 2011; 240(9):2204–20. [PubMed: 22016187] Swiderski DL, Zelditch ML. The complex ontogenetic trajectory of mandibular shape in a laboratory mouse. J Anat. 2013; 223(6):568–80. [PubMed: 24111948] Sylvester JB, Rich CA, Loh YH, van Staaden MJ, Fraser GJ, Streelman JT. Brain diversity evolves via differences in patterning. Proc Natl Acad Sci U S A. 2010; 107(21):9718–23. [PubMed: 20439726] Sylvester JB, Rich CA, Yi C, Peres JN, Houart C, Streelman JT. Competing signals drive telencephalon diversity. Nat Commun. 2013; 4:1745. [PubMed: 23612286] Turner GF, Seehausen O, Knight ME, Allender CJ, Robinson RL. How many species of cichlid fishes are there in African lakes? Mol Ecol. 2001; 10(3):793–806. [PubMed: 11298988] Verdonck A, De Ridder L, Kuhn R, Darras V, Carels C, de Zegher F. Effect of testosterone replacement after neonatal castration on craniofacial growth in rats. Arch Oral Biol. 1998; 43(7):551–7. [PubMed: 9730273] Wada N, Javidan Y, Nelson S, Carney TJ, Kelsh RN, Schilling TF. Hedgehog signaling is required for cranial neural crest morphogenesis and chondrogenesis at the midline in the zebrafish skull. Development. 2005; 132(17):3977–88. [PubMed: 16049113] Wagner, GP. Homology, Genes, and Evolutionary Innovation. Princeton University Press; Princeton, NJ: 2014. Wilkie AO, Slaney SF, Oldridge M, Poole MD, Ashworth GJ, Hockley AD, Hayward RD, David DJ, Pulleyn LJ, Rutland P. Apert syndrome results from localized mutations of FGFR2 and is allelic with Crouzon syndrome. Nat Genet. 1995; 9(2):165–72. [PubMed: 7719344] Won YJ, Sivasundar A, Wang Y, Hey J. On the origin of Lake Malawi cichlid species: a population genetic analysis of divergence. Proc Natl Acad Sci U S A. 2005; 102(Suppl 1):6581–6. [PubMed: 15851665] Wray GA. The evolutionary significance of cis-regulatory mutations. Nat Rev Genet. 2007; 8(3):206– 16. [PubMed: 17304246] Yang J, Andre P, Ye L, Yang YZ. The Hedgehog signalling pathway in bone formation. Int J Oral Sci. 2015; 7(2):73–9. [PubMed: 26023726] Young NM, Chong HJ, Hu D, Hallgrimsson B, Marcucio RS. Quantitative analyses link modulation of sonic hedgehog signaling to continuous variation in facial growth and shape. Development. 2010; 137(20):3405–9. [PubMed: 20826528]

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Highlights •

Mutagenesis screens are limited with respect to the study of complex traits

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“Evolutionary mutant” cichlid fishes mimic normal & clinical human facial variation

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The conservation of facial development makes studies in cichlids broadly relevant

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Efficient identification of genetic basis in cichlids via QTL & population genomics

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Cichlids lend novel insights into neurocristopathies, osteogenesis, and plasticity

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Author Manuscript Figure 1. Cichlids demonstrate extensive craniofacial variation analogous to normal and clinical variation in humans


Comparison of human (top) and cichlid (bottom) facial variation. Most cichlid facial variation is continuous across species adapted to bite or scrape food from the substrate (left), or to suck food from the water column (right). This is similar to the continuous spectrum of “normal” facial variation found among human populations. Notably, some cichlid species have evolved extreme morphologies that mimic pathological variation in humans such as micrognathia (far left) and midface hypoplasia (far right). Cichlid images courtesy of Ad Konings. All cichlids are from Lake Malawi. From left to right, including feeding mode (Konings 2001): Labeotropheus fuelleborni (biting: scraping connected algae), Tropheops sp. ‘taiwan’ (biting: nip/twist of connected algae), Cynotilapia zebroides (suctioning: plankton from water column or combing loose algae), Tyrannochromis nigriventer (suctioning: ambush predator of other fish), Aulonocara rostratum (sonar hunting of invertebrates buried in sand), and Caprichromis orthognathus (head-butts mouth brooding females, then eats released eggs and larvae). Illustrations of human skulls from different populations (from left to right: American Indian, European, and Sub-Saharan African) by Diana Marques, courtesy of the Smithsonian’s National Museum of Natural History.

Author Manuscript Dev Biol. Author manuscript; available in PMC 2017 July 15.

Genetic basis of continuous variation in the levels and modular inheritance of pigmentation in cichlid fishes.

Evolution of genomic structural variation and genomic architecture in the adaptive radiations of African cichlid fishes.

Testing the stages model in the adaptive radiation of cichlid fishes in East African Lake Tanganyika.

Secondary contact seeds phenotypic novelty in cichlid fishes.

Identification of cichlid fishes from Lake Malawi using computer vision.

Isotocin neuronal phenotypes differ among social systems in cichlid fishes.

Teleosts as Model Organisms To Understand Host-Microbe Interactions.

Using zebrafish as the model organism to understand organ regeneration.

Comparative transcriptomics of anal fin pigmentation patterns in cichlid fishes.

Genetic divergence, speciation and morphological stasis in a lineage of African cichlid fishes.

Morphology and efficiency of a specialized foraging behavior, sediment sifting, in neotropical cichlid fishes.

Craniofacial variation in Australasian and Pacific populations.

Zebra Finches As a Model Species to Understand the Roots of Rhythm.

A comparative study of an innate immune response in Lamprologine cichlid fishes.

A compendium of developmental gene expression in Lake Malawi cichlid fishes.

Back to Tanganyika: a case of recent trans-species-flock dispersal in East African haplochromine cichlid fishes.

Body size diversity and frequency distributions of Neotropical cichlid fishes (Cichliformes: Cichlidae: Cichlinae).

Divergent positive selection in rhodopsin from lake and riverine cichlid fishes.

Variation of tectal morphology in teleost fishes.

Using euhalophytes to understand salt tolerance and to develop saline agriculture: Suaeda salsa as a promising model.

Influence of substrate orientation on feeding kinematics and performance of algae-grazing Lake Malawi cichlid fishes.

A century of morphological variation in Cyprinidae fishes.

Phenotypic variation and selective mortality as major drivers of recruitment variability in fishes.

A mixed methods approach to understand variation in lung cancer practice and the role of guidelines.