Genetic architecture of trait variance in craniofacial morphology.

The genetic architecture of trait variance has long been of interest in genetics and evolution. One of the earliest attempts to understand this architecture was presented in Lerner's Genetic Homeostasis (1954). Lerner proposed that heterozygotes should be better able to tolerate environmental perturbations because of functional differences between the alleles at a given locus, with each allele optimal for slightly different environments. This greater robustness to environmental variance, he argued, would result in smaller trait variance for heterozygotes. The evidence for Lerner's hypothesis has been inconclusive. To address this question using modern genomic methods, we mapped loci associated with differences in trait variance (vQTL) on 1,101 individuals from the F34 of an advanced intercross between LG/J and SM/J mice. We also mapped epistatic interactions for these vQTL in order to understand the influence of epistasis for the architecture of trait variance. We did not find evidence supporting Lerner's hypothesis, that heterozygotes tend to have smaller trait variances than homozygotes. We further show that the effects of most mapped loci on trait variance are produced by epistasis affecting trait means and that those epistatic effects account for about a half of the differences in genotypic-specific trait variances. Finally, we propose a model where the different interactions between the additive and dominance effects of the vQTL and their epistatic partners can explain Lerner's original observations but can also be extended to include other conditions where heterozygotes are not the least variable genotype.

Palatal segment contributions to midfacial growth in three inbred mouse strains.

Following facial prominence fusion, anterior-posterior (A-P) elongation of the palate is a critical aspect of palatogenesis and integrated midfacial elongation. Reciprocal epithelial-mesenchymal interactions drive secondary palate elongation and periodic signaling center formation within the rugae growth zone (RGZ). However, the relationship between RGZ dynamics and the morphogenetic behavior of underlying palatal bone mesenchymal precursors has remained enigmatic. Our results indicate that cellular activity at the RGZ simultaneously drives rugae formation and elongation of the maxillary bone primordium within the anterior secondary palate, which more than doubles in length prior to palatal shelf fusion. The first formed palatal ruga, found just posterior to the RGZ, represents a consistent morphological boundary between anterior and posterior secondary palate bone precursors, being found at the future maxillary-palatine suture. These results suggest a model where changes in RGZ-driven A-P growth of the anterior secondary palate may produce interspecies and intraspecies differences in facial prognathism and differences in the proportional contribution of palatal segment-associated bones to total palate length. An ontogenetic comparison of three inbred mouse strains indicated that while RGZ-driven growth of the anterior secondary palate is critical for early midfacial outgrowth, subtle strain-specific bony contributions to adult palate length are not present until after this initial palatal growth period. This multifaceted illustration of normal midfacial growth dynamics confirms a one-to-one relationship between palatal segments and upper jaw bones during the earliest stages of palatal growth, which may serve as the basis for evolutionary change in upper jaw morphology. Additionally, identified mouse strain-specific differences in palatal segment elongation provide a useful foundation for understanding the impact of background genetic effects on facial morphogenesis.

MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses.

Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase ( www.facebase.org , https://doi.org/10.25550/3-HXMC ) and GitHub ( https://github.com/jaydevine/MusMorph ).

The genetic basis of neurocranial size and shape across varied lab mouse populations.

Brain and skull tissues interact through molecular signalling and mechanical forces during head development, leading to a strong correlation between the neurocranium and the external brain surface. Therefore, when brain tissue is unavailable, neurocranial endocasts are often used to approximate brain size and shape. Evolutionary changes in brain morphology may have resulted in secondary changes to neurocranial morphology, but the developmental and genetic processes underlying this relationship are not well understood. Using automated phenotyping methods, we quantified the genetic basis of endocast variation across large genetically varied populations of laboratory mice in two ways: (1) to determine the contributions of various genetic factors to neurocranial form and (2) to help clarify whether a neurocranial variation is based on genetic variation that primarily impacts bone development or on genetic variation that primarily impacts brain development, leading to secondary changes in bone morphology. Our results indicate that endocast size is highly heritable and is primarily determined by additive genetic factors. In addition, a non-additive inbreeding effect led to founder strains with lower neurocranial size, but relatively large brains compared to skull size; suggesting stronger canalization of brain size and/or a general allometric effect. Within an outbred sample of mice, we identified a locus on mouse chromosome 1 that is significantly associated with variation in several positively correlated endocast size measures. Because the protein-coding genes at this locus have been previously associated with brain development and not with bone development, we propose that genetic variation at this locus leads primarily to variation in brain volume that secondarily leads to changes in neurocranial globularity. We identify a strain-specific missense mutation within Akt3 that is a strong causal candidate for this genetic effect. Whilst it is not appropriate to generalize our hypothesis for this single locus to all other loci that also contribute to the complex trait of neurocranial skull morphology, our results further reveal the genetic basis of neurocranial variation and highlight the importance of the mechanical influence of brain growth in determining skull morphology.

O-fucosylation of thrombospondin type 1 repeats is essential for ECM remodeling and signaling during bone development.

Many extracellular matrix (ECM) associated proteins that influence ECM properties have Thrombospondin type 1 repeats (TSRs) which are modified with O-linked fucose. The O-fucose is added in the endoplasmic reticulum to folded TSRs by the enzyme Protein O-fucosyltransferase-2 (POFUT2) and is proposed to promote efficient trafficking of substrates. The importance of this modification for function of TSR-proteins is underscored by the early embryonic lethality of mouse embryos lacking Pofut2. To overcome early lethality and investigate the impact of the Pofut2 knockout on the secretion of POFUT2 substrates and on extracellular matrix properties in vivo, we deleted Pofut2 in the developing limb mesenchyme using Prrx1-Cre recombinase. Loss of Pofut2 in the limb mesenchyme caused significant shortening of the limbs, long bones and tendons and stiff joint resembling the musculoskeletal dysplasias in human and in mice with mutations in ADAMTS or ADAMTSL proteins. Limb shortening was evident at embryonic day 14.5 where loss of O-fucosylation led to an accumulation of fibrillin 2 (FBN2), decreased BMP and IHH signaling, and increased TGF-ß signaling. Consistent with these changes we saw a decrease in the size of the hypertrophic zone with lower levels of Collagen-X. Unexpectedly, we observed minimal effects of the Pofut2 knockout on secretion of two POFUT2 substrates, CCN2 or ADAMTS17, in the developing bone. In contrast, CCN2 and two other POFUT2 substrates important for bone development, ADAMTS6 and 10, showed a decrease in secretion from POFUT2-null HEK293T cells in vitro. These combined results suggest that the impact of the Pofut2 mutation is cell-type specific. In addition, these observations raise the possibility that the O-fucose modification on TSRs extends beyond promoting efficient trafficking of POFUT2 substrates and has the potential to influence their function in the extracellular environment.

Investigating the effects of compound paralogous EPHB receptor mutations on mouse facial development.

BACKGROUND: Variation in facial shape may arise from the combinatorial or overlapping actions of paralogous genes. Given its many members, and overlapping expression and functions, the EPH receptor family is a compelling candidate source of craniofacial morphological variation. We performed a detailed morphometric analysis of an allelic series of E14.5 Ephb1-3 receptor mutants to determine the effect of each paralogous receptor gene on craniofacial morphology. RESULTS: We found that Ephb1, Ephb2, and Ephb3 genotypes significantly influenced facial shape, but Ephb1 effects were weaker than Ephb2 and Ephb3 effects. Ephb2-/- and Ephb3-/- mutations affected similar aspects of facial morphology, but Ephb3-/- mutants had additional facial shape effects. Craniofacial differences across the allelic series were largely consistent with predicted additive genetic effects. However, we identified a potentially important nonadditive effect where Ephb1 mutants displayed different morphologies depending on the combination of other Ephb paralogs present, where Ephb1+/- , Ephb1-/- , and Ephb1-/- ; Ephb3-/- mutants exhibited a consistent deviation from their predicted facial shapes. CONCLUSIONS: This study provides a detailed assessment of the effects of Ephb receptor gene paralogs on E14.5 mouse facial morphology and demonstrates how the loss of specific receptors contributes to facial dysmorphology.

Facial shape and allometry quantitative trait locus intervals in the Diversity Outbred mouse are enriched for known skeletal and facial development genes.

The biology of how faces are built and come to differ from one another is complex. Discovering normal variants that contribute to differences in facial morphology is one key to untangling this complexity, with important implications for medicine and evolutionary biology. This study maps quantitative trait loci (QTL) for skeletal facial shape using Diversity Outbred (DO) mice. The DO is a randomly outcrossed population with high heterozygosity that captures the allelic diversity of eight inbred mouse lines from three subspecies. The study uses a sample of 1147 DO animals (the largest sample yet employed for a shape QTL study in mouse), each characterized by 22 three-dimensional landmarks, 56,885 autosomal and X-chromosome markers, and sex and age classifiers. We identified 37 facial shape QTL across 20 shape principal components (PCs) using a mixed effects regression that accounts for kinship among observations. The QTL include some previously identified intervals as well as new regions that expand the list of potential targets for future experimental study. Three QTL characterized shape associations with size (allometry). Median support interval size was 3.5 Mb. Narrowing additional analysis to QTL for the five largest magnitude shape PCs, we found significant overrepresentation of genes with known roles in growth, skeletal and facial development, and sensory organ development. For most intervals, one or more of these genes lies within 0.25 Mb of the QTL's peak. QTL effect sizes were small, with none explaining more than 0.5% of facial shape variation. Thus, our results are consistent with a model of facial diversity that is influenced by key genes in skeletal and facial development and, simultaneously, is highly polygenic.

Aberrant cell segregation in the craniofacial primordium and the emergence of facial dysmorphology in craniofrontonasal syndrome.

Craniofrontonasal syndrome (CFNS) is a rare X-linked disorder characterized by craniofacial, skeletal, and neurological anomalies and is caused by mutations in EFNB1. Heterozygous females are more severely affected by CFNS than hemizygous males, a phenomenon called cellular interference that results from EPHRIN-B1 mosaicism. In Efnb1 heterozygous mice, mosaicism for EPHRIN-B1 results in cell sorting and more severe phenotypes than Efnb1 hemizygous males, but how craniofacial dysmorphology arises from cell segregation is unknown and CFNS etiology therefore remains poorly understood. Here, we couple geometric morphometric techniques with temporal and spatial interrogation of embryonic cell segregation in mouse mutant models to elucidate mechanisms underlying CFNS pathogenesis. By generating EPHRIN-B1 mosaicism at different developmental timepoints and in specific cell populations, we find that EPHRIN-B1 regulates cell segregation independently in early neural development and later in craniofacial development, correlating with the emergence of quantitative differences in face shape. Whereas specific craniofacial shape changes are qualitatively similar in Efnb1 heterozygous and hemizygous mutant embryos, heterozygous embryos are quantitatively more severely affected, indicating that Efnb1 mosaicism exacerbates loss of function phenotypes rather than having a neomorphic effect. Notably, neural tissue-specific disruption of Efnb1 does not appear to contribute to CFNS craniofacial dysmorphology, but its disruption within neural crest cell-derived mesenchyme results in phenotypes very similar to widespread loss. EPHRIN-B1 can bind and signal with EPHB1, EPHB2, and EPHB3 receptor tyrosine kinases, but the signaling partner(s) relevant to CFNS are unknown. Geometric morphometric analysis of an allelic series of Ephb1; Ephb2; Ephb3 mutant embryos indicates that EPHB2 and EPHB3 are key receptors mediating Efnb1 hemizygous-like phenotypes, but the complete loss of EPHB1-3 does not fully recapitulate the severity of CFNS-like Efnb1 heterozygosity. Finally, by generating Efnb1+/Δ; Ephb1; Ephb2; Ephb3 quadruple knockout mice, we determine how modulating cumulative receptor activity influences cell segregation in craniofacial development and find that while EPHB2 and EPHB3 play an important role in craniofacial cell segregation, EPHB1 is more important for cell segregation in the brain; surprisingly, complete loss of EPHB1-EPHB3 does not completely abrogate cell segregation. Together, these data advance our understanding of the etiology and signaling interactions underlying CFNS dysmorphology.

A Registration and Deep Learning Approach to Automated Landmark Detection for Geometric Morphometrics.

Geometric morphometrics is the statistical analysis of landmark-based shape variation and its covariation with other variables. Over the past two decades, the gold standard of landmark data acquisition has been manual detection by a single observer. This approach has proven accurate and reliable in small-scale investigations. However, big data initiatives are increasingly common in biology and morphometrics. This requires fast, automated, and standardized data collection. We combine techniques from image registration, geometric morphometrics, and deep learning to automate and optimize anatomical landmark detection. We test our method on high-resolution, micro-computed tomography images of adult mouse skulls. To ensure generalizability, we use a morphologically diverse sample and implement fundamentally different deformable registration algorithms. Compared to landmarks derived from conventional image registration workflows, our optimized landmark data show up to a 39.1% reduction in average coordinate error and a 36.7% reduction in total distribution error. In addition, our landmark optimization produces estimates of the sample mean shape and variance-covariance structure that are statistically indistinguishable from expert manual estimates. For biological imaging datasets and morphometric research questions, our approach can eliminate the time and subjectivity of manual landmark detection whilst retaining the biological integrity of these expert annotations.

ADAMTS9 and ADAMTS20 are differentially affected by loss of B3GLCT in mouse model of Peters plus syndrome.

Peters plus syndrome (MIM #261540 PTRPLS), characterized by defects in eye development, prominent forehead, hypertelorism, short stature and brachydactyly, is caused by mutations in the ß3-glucosyltransferase (B3GLCT) gene. Protein O-fucosyltransferase 2 (POFUT2) and B3GLCT work sequentially to add an O-linked glucose ß1-3fucose disaccharide to properly folded thrombospondin type 1 repeats (TSRs). Forty-nine proteins are predicted to be modified by POFUT2, and nearly half are members of the ADAMTS superfamily. Previous studies suggested that O-linked fucose is essential for folding and secretion of POFUT2-modified proteins and that B3GLCT-mediated extension to the disaccharide is essential for only a subset of targets. To test this hypothesis and gain insight into the origin of PTRPLS developmental defects, we developed and characterized two mouse B3glct knockout alleles. Using these models, we tested the role of B3GLCT in enabling function of ADAMTS9 and ADAMTS20, two highly conserved targets whose functions are well characterized in mouse development. The mouse B3glct mutants developed craniofacial and skeletal abnormalities comparable to PTRPLS. In addition, we observed highly penetrant hydrocephalus, white spotting and soft tissue syndactyly. We provide strong genetic and biochemical evidence that hydrocephalus and white spotting in B3glct mutants resulted from loss of ADAMTS20, eye abnormalities from partial reduction of ADAMTS9 and cleft palate from loss of ADAMTS20 and partially reduced ADAMTS9 function. Combined, these results provide compelling evidence that ADAMTS9 and ADAMTS20 were differentially sensitive to B3GLCT inactivation and suggest that the developmental defects in PTRPLS result from disruption of a subset of highly sensitive POFUT2/B3GLCT targets such as ADAMTS20.

Hybridization in human evolution: Insights from other organisms.

During the late Pleistocene, isolated lineages of hominins exchanged genes thus influencing genomic variation in humans in both the past and present. However, the dynamics of this genetic exchange and associated phenotypic consequences through time remain poorly understood. Gene exchange across divergent lineages can result in myriad outcomes arising from these dynamics and the environmental conditions under which it occurs. Here we draw from our collective research across various organisms, illustrating some of the ways in which gene exchange can structure genomic/phenotypic diversity within/among species. We present a range of examples relevant to questions about the evolution of hominins. These examples are not meant to be exhaustive, but rather illustrative of the diverse evolutionary causes/consequences of hybridization, highlighting potential drivers of human evolution in the context of hybridization including: influences on adaptive evolution, climate change, developmental systems, sex-differences in behavior, Haldane's rule and the large X-effect, and transgressive phenotypic variation.

The effect of automated landmark identification on morphometric analyses.

Morphometric analysis of anatomical landmarks allows researchers to identify specific morphological differences between natural populations or experimental groups, but manually identifying landmarks is time-consuming. We compare manually and automatically generated adult mouse skull landmarks and subsequent morphometric analyses to elucidate how switching from manual to automated landmarking will impact morphometric analysis results for large mouse (Mus musculus) samples (n = 1205) that represent a wide range of 'normal' phenotypic variation (62 genotypes). Other studies have suggested that the use of automated landmarking methods is feasible, but this study is the first to compare the utility of current automated approaches to manual landmarking for a large dataset that allows the quantification of intra- and inter-strain variation. With this unique sample, we investigated how switching to a non-linear image registration-based automated landmarking method impacts estimated differences in genotype mean shape and shape variance-covariance structure. In addition, we tested whether an initial registration of specimen images to genotype-specific averages improves automatic landmark identification accuracy. Our results indicated that automated landmark placement was significantly different than manual landmark placement but that estimated skull shape covariation was correlated across methods. The addition of a preliminary genotype-specific registration step as part of a two-level procedure did not substantially improve on the accuracy of one-level automatic landmark placement. The landmarks with the lowest automatic landmark accuracy are found in locations with poor image registration alignment. The most serious outliers within morphometric analysis of automated landmarks displayed instances of stochastic image registration error that are likely representative of errors common when applying image registration methods to micro-computed tomography datasets that were initially collected with manual landmarking in mind. Additional efforts during specimen preparation and image acquisition can help reduce the number of registration errors and improve registration results. A reduction in skull shape variance estimates were noted for automated landmarking methods compared with manual landmarking. This partially reflects an underestimation of more extreme genotype shapes and loss of biological signal, but largely represents the fact that automated methods do not suffer from intra-observer landmarking error. For appropriate samples and research questions, our image registration-based automated landmarking method can eliminate the time required for manual landmarking and have a similar power to identify shape differences between inbred mouse genotypes.

Developmental constraint through negative pleiotropy in the zygomatic arch.

BACKGROUND: Previous analysis suggested that the relative contribution of individual bones to regional skull lengths differ between inbred mouse strains. If the negative correlation of adjacent bone lengths is associated with genetic variation in a heterogeneous population, it would be an example of negative pleiotropy, which occurs when a genetic factor leads to opposite effects in two phenotypes. Confirming negative pleiotropy and determining its basis may reveal important information about the maintenance of overall skull integration and developmental constraint on skull morphology. RESULTS: We identified negative correlations between the lengths of the frontal and parietal bones in the midline cranial vault as well as the zygomatic bone and zygomatic process of the maxilla, which contribute to the zygomatic arch. Through gene association mapping of a large heterogeneous population of Diversity Outbred (DO) mice, we identified a quantitative trait locus on chromosome 17 driving the antagonistic contribution of these two zygomatic arch bones to total zygomatic arch length. Candidate genes in this region were identified and real-time PCR of the maxillary processes of DO founder strain embryos indicated differences in the RNA expression levels for two of the candidate genes, Camkmt and Six2. CONCLUSIONS: A genomic region underlying negative pleiotropy of two zygomatic arch bones was identified, which provides a mechanism for antagonism in component bone lengths while constraining overall zygomatic arch length. This type of mechanism may have led to variation in the contribution of individual bones to the zygomatic arch noted across mammals. Given that similar genetic and developmental mechanisms may underlie negative correlations in other parts of the skull, these results provide an important step toward understanding the developmental basis of evolutionary variation and constraint in skull morphology.

Craniomandibular form and body size variation of first generation mouse hybrids: A model for hominin hybridization.

Hybridization occurs in a number of mammalian lineages, including among primate taxa. Analyses of ancient genomes have shown that hybridization between our lineage and other archaic hominins in Eurasia occurred numerous times in the past. However, we still have limited empirical data on what a hybrid skeleton looks like, or how to spot patterns of hybridization among fossils for which there are no genetic data. Here we use experimental mouse models to supplement previous studies of primates. We characterize size and shape variation in the cranium and mandible of three wild-derived inbred mouse strains and their first generation (F1) hybrids. The three parent taxa in our analysis represent lineages that diverged over approximately the same period as the human/Neanderthal/Denisovan lineages and their hybrids are variably successful in the wild. Comparisons of body size, as quantified by long bone measurements, are also presented to determine whether the identified phenotypic effects of hybridization are localized to the cranium or represent overall body size changes. The results indicate that hybrid cranial and mandibular sizes, as well as limb length, exceed that of the parent taxa in all cases. All three F1 hybrid crosses display similar patterns of size and form variation. These results are generally consistent with earlier studies on primates and other mammals, suggesting that the effects of hybridization may be similar across very different scenarios of hybridization, including different levels of hybrid fitness. This paper serves to supplement previous studies aimed at identifying F1 hybrids in the fossil record and to introduce further research that will explore hybrid morphologies using mice as a proxy for better understanding hybridization in the hominin fossil record.

Body size and allometric variation in facial shape in children.

OBJECTIVES: Morphological integration, or the tendency for covariation, is commonly seen in complex traits such as the human face. The effects of growth on shape, or allometry, represent a ubiquitous but poorly understood axis of integration. We address the question of to what extent age and measures of size converge on a single pattern of allometry for human facial shape. METHODS: Our study is based on two large cross-sectional cohorts of children, one from Tanzania and the other from the United States (N = 7,173). We employ 3D facial imaging and geometric morphometrics to relate facial shape to age and anthropometric measures. RESULTS: The two populations differ significantly in facial shape, but the magnitude of this difference is small relative to the variation within each group. Allometric variation for facial shape is similar in both populations, representing a small but significant proportion of total variation in facial shape. Different measures of size are associated with overlapping but statistically distinct aspects of shape variation. Only half of the size-related variation in facial shape can be explained by the first principal component of four size measures and age while the remainder associates distinctly with individual measures. CONCLUSIONS: Allometric variation in the human face is complex and should not be regarded as a singular effect. This finding has important implications for how size is treated in studies of human facial shape and for the developmental basis for allometric variation more generally.

The Interaction of Genetic Background and Mutational Effects in Regulation of Mouse Craniofacial Shape.

Inbred genetic background significantly influences the expression of phenotypes associated with known genetic perturbations and can underlie variation in disease severity between individuals with the same mutation. However, the effect of epistatic interactions on the development of complex traits, such as craniofacial morphology, is poorly understood. Here, we investigated the effect of three inbred backgrounds (129X1/SvJ, C57BL/6J, and FVB/NJ) on the expression of craniofacial dysmorphology in mice (Mus musculus) with loss of function in three members of the Sprouty family of growth factor negative regulators (Spry1, Spry2, or Spry4) in order to explore the impact of epistatic interactions on skull morphology. We found that the interaction of inbred background and the Sprouty genotype explains as much craniofacial shape variation as the Sprouty genotype alone. The most severely affected genotypes display a relatively short and wide skull, a rounded cranial vault, and a more highly angled inferior profile. Our results suggest that the FVB background is more resilient to Sprouty loss of function than either C57 or 129, and that Spry4 loss is generally less severe than loss of Spry1 or Spry2 While the specific modifier genes responsible for these significant background effects remain unknown, our results highlight the value of intercrossing mice of multiple inbred backgrounds to identify the genes and developmental interactions that modulate the severity of craniofacial dysmorphology. Our quantitative results represent an important first step toward elucidating genetic interactions underlying variation in robustness to known genetic perturbations in mice.

Genetics of murine craniofacial morphology: diallel analysis of the eight founders of the Collaborative Cross.

Using eight inbred founder strains of the mouse Collaborative Cross (CC) project and their reciprocal F1 hybrids, we quantified variation in craniofacial morphology across mouse strains, explored genetic contributions to craniofacial variation that distinguish the founder strains, and tested whether specific or summary measures of craniofacial shape display stronger additive genetic contributions. This study thus provides critical information about phenotypic diversity among CC founder strains and about the genetic contributions to this phenotypic diversity, which is relevant to understanding the basis of variation in standard laboratory strains and natural populations. Craniofacial shape was quantified as a series of size-adjusted linear dimensions (RDs) and by principal components (PC) analysis of morphological landmarks captured from computed tomography images from 62 of the 64 reciprocal crosses of the CC founder strains. We first identified aspects of skull morphology that vary between these phenotypically 'normal' founder strains and that are defining characteristics of these strains. We estimated the contributions of additive and various non-additive genetic factors to phenotypic variation using diallel analyses of a subset of these strongly differing RDs and the first eight PCs of skull shape variation. We find little difference in the genetic contributions to RD measures and PC scores, suggesting fundamental similarities in the magnitude of genetic contributions to both specific and summary measures of craniofacial phenotypes. Our results indicate that there are stronger additive genetic effects associated with defining phenotypic characteristics of specific founder strains, suggesting these distinguishing measures are good candidates for use in genotype-phenotype association studies of CC mice. Our results add significantly to understanding of genotype-phenotype associations in the skull, which serve as a foundation for modeling the origins of medically and evolutionarily relevant variation.

Morphometrics, 3D Imaging, and Craniofacial Development.

Recent studies have shown how volumetric imaging and morphometrics can add significantly to our understanding of morphogenesis, the developmental basis for variation, and the etiology of structural birth defects. On the other hand, the complex questions and diverse imaging data in developmental biology present morphometrics with more complex challenges than applications in virtually any other field. Meeting these challenges is necessary in order to understand the mechanistic basis for variation in complex morphologies. This chapter reviews the methods and theory that enable the application of modern landmark-based morphometrics to developmental biology and craniofacial development, in particular. We discuss the theoretical foundations of morphometrics as applied to development and review the basic approaches to the quantification of morphology. Focusing on geometric morphometrics, we discuss the principal statistical methods for quantifying and comparing morphological variation and covariation structure within and among groups. Finally, we discuss the future directions for morphometrics in developmental biology that will be required for approaches that enable quantitative integration across the genotype-phenotype map.