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Wolff’s law of trajectorial orientation proposes that trabecular struts align with the orientation of dominant compressive loads within a joint. Although widely considered in skeletal biology, Wolff’s law has never been experimentally tested while controlling for ontogenetic stage, activity level, and species differences, all factors that may affect trabecular bone growth. Here we report an experimental test of Wolff’s law using a within-species design in age-matched subjects experiencing physiologically normal levels of bone strain. Two age-matched groups of juvenile guinea fowl Numida meleagris ran on a treadmill set at either 0° (Level group) or 20° (Incline group), for 10·min per day over a 45-day treatment period. Birds running on the 20° inclined treadmill used more-flexed knees than those in the Level group at midstance (the point of peak ground reaction force). This difference in joint posture enabled us to test the sensitivity of trabecular alignment to altered load orientation in the knee. Using a new radon transform-based method for measuring trabecular orientation, our analysis shows that the fine trabecular bone in the distal femur has a high degree of correspondence between changes in joint angle and trabecular orientation. The sensitivity of this response supports the prediction that trabecular bone adapts dynamically to the orientation of peak compressive forces., Anthropology

Abstract Background Clefts of the lip (CL), the palate (CP), or both (CLP) are the most common orofacial congenital malformations found among live births, accounting for 65% of all head and neck anomalies. The frequency and pattern of orofacial clefts in different parts of the world and among different human groups varies widely. Generally, populations of Asian or Native American origin have the highest prevalence, while Caucasian populations show intermediate prevalence and African populations the lowest. To date, little is known regarding the epidemiology and pattern of orofacial clefts in Tanzania. Methods A retrospective descriptive study was conducted at Bugando Medical Centre to identify all children with orofacial clefts that attended or were treated during a period of five years. Cleft lip and/or palate records were obtained from patient files in the Hospital's Departments of Surgery, Paediatrics and medical records. Age at presentation, sex, region of origin, type and laterality of the cleft were recorded. In addition, presence of associated congenital anomalies or syndromes was recorded. Results A total of 240 orofacial cleft cases were seen during this period. Isolated cleft lip was the most common cleft type followed closely by cleft lip and palate (CLP). This is a departure from the pattern of clefting reported for Caucasian and Asian populations, where CLP or isolated cleft palate is the most common type. The distribution of clefts by side showed a statistically significant preponderance of the left side (43.7%) (χ2 = 92.4, p < 0.001), followed by the right (28.8%) and bilateral sides (18.3%). Patients with isolated cleft palate presented at very early age (mean age 1.00 years, SE 0.56). Associated congenital anomalies were observed in 2.8% of all patients with orofacial clefts, and included neural tube defects, Talipes and persistent ductus arteriosus. Conclusions Unilateral orofacial clefts were significantly more common than bilateral clefts; with the left side being the most common affected side. Most of the other findings did not show marked differences with orofacial cleft distributions in other African populations.

Abstract Background Using 3D generic models to statistically analyze trends in biological structure changes is an important tool in morphometrics research. Therefore, 3D generic models built for a range of populations are in high demand. However, due to the complexity of biological structures and the limited views of them that medical images can offer, it is still an exceptionally difficult task to quickly and accurately create 3D generic models (a model is a 3D graphical representation of a biological structure) based on medical image stacks (a stack is an ordered collection of 2D images). We show that the creation of a generic model that captures spatial information exploitable in statistical analyses is facilitated by coupling our generalized segmentation method to existing automatic image registration algorithms. Methods The method of creating generic 3D models consists of the following processing steps: (i) scanning subjects to obtain image stacks; (ii) creating individual 3D models from the stacks; (iii) interactively extracting sub-volume by cutting each model to generate the sub-model of interest; (iv) creating image stacks that contain only the information pertaining to the sub-models; (v) iteratively registering the corresponding new 2D image stacks; (vi) averaging the newly created sub-models based on intensity to produce the generic model from all the individual sub-models. Results After several registration procedures are applied to the image stacks, we can create averaged image stacks with sharp boundaries. The averaged 3D model created from those image stacks is very close to the average representation of the population. The image registration time varies depending on the image size and the desired accuracy of the registration. Both volumetric data and surface model for the generic 3D model are created at the final step. Conclusions Our method is very flexible and easy to use such that anyone can use image stacks to create models and retrieve a sub-region from it at their ease. Java-based implementation allows our method to be used on various visualization systems including personal computers, workstations, computers equipped with stereo displays, and even virtual reality rooms such as the CAVE Automated Virtual Environment. The technique allows biologists to build generic 3D models of their interest quickly and accurately.

The COVID-19 pandemic demonstrated the need for respiratory protection against airborne pathogens. Respirator options for children are limited, and existing designs do not consider differences in facial shape or size. We created a dataset of children's facial images from three cohorts, then used geometric morphometric analyses of dense and sparse facial landmark representations to quantify age, sex and ancestry-related variation in shape. We found facial shape and size in children vary significantly with age from ages 2 to 18, particularly in dimensions relevant to respirator design. Sex differences are small throughout most of the age range of our sample. Ancestry is associated with significant facial shape variation in dimensions that may affect respirator fit. We offer guidance on how to our results can be used for the appropriate design of devices such as respirators for pediatric populations. We also highlight the need to consider ancestry-related variation in facial morphology to promote equitable, inclusive products., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Background –: Previously we found that increasing fibroblast growth factor (FGF) signaling in the neural crest cells within the frontonasal process (FNP) of the chicken embryo caused dysmorphology that was correlated with reduced proliferation, disrupted cellular orientation, and lower MAPK activation but no change in PLCy and PI3K activation. This suggests RTK signaling may drive craniofacial morphogenesis through specific downstream effectors that affect cellular activities. In this study we inhibited three downstream branches of RTK signaling to determine their role in regulating cellular activities and how these changes affect morphogenesis of the FNP., Results –: Small molecule inhibitors of MEK1/2, PI3K, and PLCy were delivered individually and in tandem to the right FNP of chicken embryos. All treatments caused asymmetric proximodistal truncation on the treated side and a mild expansion on the untreated side compared to DMSO control treated FNPs. Inhibiting each pathway caused similar decreased proliferation and disrupted cellular orientation, but did not affect apoptosis., Conclusions –: Since RTK signaling is a ubiquitous and tightly regulated biochemical system we conclude that the downstream pathways are robust to developmental perturbation through redundant signaling systems.

Human craniofacial shape is highly variable yet highly heritable with numerous genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the general population. We compare three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores reveals a polygenic basis for facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples, both human and mouse, shows craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing insights into the genetic intersection of complex traits and Mendelian disorders., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

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., Competing Interests: Conflicts of interest The authors declare no conflict of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Genetics Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Craniosynostosis is a common yet complex birth defect, characterized by premature fusion of the cranial sutures that can be syndromic or nonsyndromic. With over 180 syndromic associations, reaching genetic diagnoses and understanding variations in underlying cellular mechanisms remains a challenge. Variants of FGFR2 are highly associated with craniosynostosis and warrant further investigation. Using the missense mutation FGFR2 W290R , an effective mouse model of Crouzon syndrome, craniofacial features were analyzed using geometric morphometrics across developmental time (E10.5-adulthood, n = 665 total). Given the interrelationship between the cranial vault and basicranium in craniosynostosis patients, the basicranium and synchondroses were analyzed in perinates. Embryonic time points showed minimal significant shape differences. However, hetero- and homozygous mutant perinates and adults showed significant differences in shape and size of the cranial vault, face, and basicranium, which were associated with cranial doming and shortening of the basicranium and skull. Although there were also significant shape and size differences associated with the basicranial bones and clear reductions in basicranial ossification in cleared whole-mount samples, there were no significant alterations in chondrocyte cell shape, size, or orientation along the spheno-occipital synchondrosis. Finally, shape differences in the cranial vault and basicranium were interrelated at perinatal stages. These results point toward the possibility that facial shape phenotypes in craniosynostosis may result in part from pleiotropic effects of the causative mutations rather than only from the secondary consequences of the sutural defects, indicating a novel direction of research that may shed light on the etiology of the broad changes in craniofacial morphology observed in craniosynostosis syndromes., (© 2024 The Authors. The Anatomical Record published by Wiley Periodicals LLC on behalf of American Association for Anatomy.)

Craniofacial phenotyping is critical for both syndrome delineation and diagnosis because craniofacial abnormalities occur in 30% of characterized genetic syndromes. Clinical reports, textbooks, and available software tools typically provide two-dimensional, static images and illustrations of the characteristic phenotypes of genetic syndromes. In this work, we provide an interactive web application that provides three-dimensional, dynamic visualizations for the characteristic craniofacial effects of 95 syndromes. Users can visualize syndrome facial appearance estimates quantified from data and easily compare craniofacial phenotypes of different syndromes. Our application also provides a map of morphological similarity between a target syndrome and other syndromes. Finally, users can upload 3D facial scans of individuals and compare them to our syndrome atlas estimates. In summary, we provide an interactive reference for the craniofacial phenotypes of syndromes that allows for precise, individual-specific comparisons of dysmorphology., Competing Interests: Declaration of interests J.D.A., D.C.K., T.C., and J.H.M.P. are employees of DeepSurfaceAI, a company that uses 3D facial imaging and analysis to develop software that aids plastic craniofacial surgery. J.D.A., J.J.B., D.C.K., N.D.F., and B.H. have a financial stake in this company. DeepSurfaceAI is not currently engaged in the use of facial imaging for syndrome diagnosis and has no immediate plans to do so., (Copyright © 2023 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Human craniofacial shape is highly variable yet highly heritable with genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the normal population. We compared three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores revealed a polygenic basis for normal facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples showed craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing new insights into the genetic intersection of complex traits and Mendelian disorders.

Human genetic syndromes are often challenging to diagnose clinically. Facial phenotype is a key diagnostic indicator for hundreds of genetic syndromes and computer-assisted facial phenotyping is a promising approach to assist diagnosis. Most previous approaches to automated face-based syndrome diagnosis have analyzed different datasets of either 2D images or surface mesh-based 3D facial representations, making direct comparisons of performance challenging. In this work, we developed a set of subject-matched 2D and 3D facial representations, which we then analyzed with the aim of comparing the performance of 2D and 3D image-based approaches to computer-assisted syndrome diagnosis. This work represents the most comprehensive subject-matched analyses to date on this topic. In our analyses of 1907 subject faces representing 43 different genetic syndromes, 3D surface-based syndrome classification models significantly outperformed 2D image-based models trained and evaluated on the same subject faces. These results suggest that the clinical adoption of 3D facial scanning technology and continued collection of syndromic 3D facial scan data may substantially improve face-based syndrome diagnosis., (© 2023. The Author(s), under exclusive licence to European Society of Human Genetics.)

Facial recognition technology (FRT) has been adopted as a precision medicine tool. The medical genetics field highlights both the clinical potential and privacy risks of this technology, putting the discipline at the forefront of a new digital privacy debate. Investigating how geneticists perceive the privacy concerns surrounding FRT can help shape the evolution and regulation of the field, and provide lessons for medicine and research more broadly. Five hundred and sixty-two genetics clinicians and researchers were approached to fill out a survey, 105 responded, and 80% of these completed. The survey consisted of 48 questions covering demographics, relationship to new technologies, views on privacy, views on FRT, and views on regulation. Genetics professionals generally placed a high value on privacy, although specific views differed, were context-specific, and covaried with demographic factors. Most respondents (88%) agreed that privacy is a basic human right, but only 37% placed greater weight on it than other values such as freedom of speech. Most respondents (80%) supported FRT use in genetics, but not necessarily for broader clinical use. A sizeable percentage (39%) were unaware of FRT's lower accuracy rates in marginalized communities and of the mental health effects of privacy violations (62%), but most (76% and 75%, respectively) expressed concern when informed. Overall, women and those who self-identified as politically progressive were more concerned about the lower accuracy rates in marginalized groups (88% vs. 64% and 83% vs. 63%, respectively). Younger geneticists were more wary than older geneticists about using FRT in genetics (28% compared to 56% "strongly" supported such use). There was an overall preference for more regulation, but respondents had low confidence in governments' or technology companies' ability to accomplish this. Privacy views are nuanced and context-dependent. Support for privacy was high but not absolute, and clear deficits existed in awareness of crucial FRT-related discrimination potential and mental health impacts. Education and professional guidelines may help to evolve views and practices within the field., (© 2023 Wiley Periodicals LLC.)

Adaptive evolution may be influenced by canalization, the buffering of developmental processes from environmental and genetic perturbations, but how this occurs is poorly understood. Here, we explore how gene expression variability evolves in diverging and hybridizing populations, by focusing on the Arctic charr (Salvelinus alpinus) of Thingvallavatn, a classic case of divergence between feeding habitats. We report distinct profiles of gene expression variance for both coding RNAs and microRNAs between the offspring of two contrasting morphs (benthic/limnetic) and their hybrids reared in common conditions and sampled at two key points of cranial development. Gene expression variance in the hybrids is substantially affected by maternal effects, and many genes show biased expression variance toward the limnetic morph. This suggests that canalization, as inferred by gene expression variance, can rapidly diverge in sympatry through multiple gene pathways, which are associated with dominance patterns possibly biasing evolutionary trajectories and mitigating the effects of hybridization on adaptive evolution., (© 2023. Springer Nature Limited.)

Classification is a fundamental task in biology used to assign members to a class. While linear discriminant functions have long been effective, advances in phenotypic data collection are yielding increasingly high-dimensional datasets with more classes, unequal class covariances, and non-linear distributions. Numerous studies have deployed machine learning techniques to classify such distributions, but they are often restricted to a particular organism, a limited set of algorithms, and/or a specific classification task. In addition, the utility of ensemble learning or the strategic combination of models has not been fully explored.We performed a meta-analysis of 33 algorithms across 20 datasets containing over 20,000 high-dimensional shape phenotypes using an ensemble learning framework. Both binary (e.g., sex, environment) and multi-class (e.g., species, genotype, population) classification tasks were considered. The ensemble workflow contains functions for preprocessing, training individual learners and ensembles, and model evaluation. We evaluated algorithm performance within and among datasets. Furthermore, we quantified the extent to which various dataset and phenotypic properties impact performance.We found that discriminant analysis variants and neural networks were the most accurate base learners on average. However, their performance varied substantially between datasets. Ensemble models achieved the highest performance on average, both within and among datasets, increasing average accuracy by up to 3% over the top base learner. Higher class R 2 values, mean class shape distances, and between- vs. within-class variances were positively associated with performance, whereas higher class covariance distances were negatively associated. Class balance and total sample size were not predictive.Learning-based classification is a complex task driven by many hyperparameters. We demonstrate that selecting and optimizing an algorithm based on the results of another study is a flawed strategy. Ensemble models instead offer a flexible approach that is data agnostic and exceptionally accurate. By assessing the impact of various dataset and phenotypic properties on classification performance, we also offer potential explanations for variation in performance. Researchers interested in maximizing performance stand to benefit from the simplicity and effectiveness of our approach made accessible via the R package pheble ., Competing Interests: Conflict of Interest Statement The authors have no conflicts of interest to declare.

Neuroimages are a valuable tool for studying brain morphology in experiments using animal models. Magnetic resonance imaging (MRI) has become the standard method for soft tissues, although its low spatial resolution poses some limits for small animals. Here, we describe a protocol for obtaining high-resolution three-dimensional (3D) information on mouse neonate brains and skulls using micro-computed tomography (micro-CT). The protocol includes those steps needed to dissect the samples, stain and scan the brain, and obtain morphometric measurements of the whole organ and regions of interest (ROIs). Image analysis includes the segmentation of structures and the digitization of point coordinates. In sum, this work shows that the combination of micro-CT and Lugol's solution as a contrast agent is a suitable alternative for imaging the perinatal brains of small animals. This imaging workflow has applications in developmental biology, biomedicine, and other sciences interested in assessing the effect of diverse genetic and environmental factors on brain development.

Morphogenesis requires highly coordinated, complex interactions between cellular processes: proliferation, migration, and apoptosis, along with physical tissue interactions. How these cellular and tissue dynamics drive morphogenesis remains elusive. Three dimensional (3D) microscopic imaging poses great promise, and generates elegant images. However, generating even moderate through-put quantified images is challenging for many reasons. As a result, the association between morphogenesis and cellular processes in 3D developing tissues has not been fully explored. To address this critical gap, we have developed an imaging and image analysis pipeline to enable 3D quantification of cellular dynamics along with 3D morphology for the same individual embryo. Specifically, we focus on how 3D distribution of proliferation relates to morphogenesis during mouse facial development. Our method involves imaging with light-sheet microscopy, automated segmentation of cells and tissues using machine learning-based tools, and quantification of external morphology via geometric morphometrics. Applying this framework, we show that changes in proliferation are tightly correlated to changes in morphology over the course of facial morphogenesis. These analyses illustrate the potential of this pipeline to investigate mechanistic relationships between cellular dynamics and morphogenesis during embryonic development., Competing Interests: Competing interests The authors declare no competing or financial interests.

Transcriptional regulation exhibits extensive robustness, but human genetics indicates sensitivity to transcription factor (TF) dosage. Reconciling such observations requires quantitative studies of TF dosage effects at trait-relevant ranges, largely lacking so far. TFs play central roles in both normal-range and disease-associated variation in craniofacial morphology; we therefore developed an approach to precisely modulate TF levels in human facial progenitor cells and applied it to SOX9, a TF associated with craniofacial variation and disease (Pierre Robin sequence (PRS)). Most SOX9-dependent regulatory elements (REs) are buffered against small decreases in SOX9 dosage, but REs directly and primarily regulated by SOX9 show heightened sensitivity to SOX9 dosage; these RE responses partially predict gene expression responses. Sensitive REs and genes preferentially affect functional chondrogenesis and PRS-like craniofacial shape variation. We propose that such REs and genes underlie the sensitivity of specific phenotypes to TF dosage, while buffering of other genes leads to robust, nonlinear dosage-to-phenotype relationships., (© 2023. The Author(s).)

Many genetic syndromes are associated with distinctive facial features. Several computer-assisted methods have been proposed that make use of facial features for syndrome diagnosis. Training supervised classifiers, the most common approach for this purpose, requires large, comprehensive, and difficult to collect databases of syndromic facial images. In this work, we use unsupervised, normalizing flow-based manifold and density estimation models trained entirely on unaffected subjects to detect syndromic 3D faces as statistical outliers. Furthermore, we demonstrate a general, user-friendly, gradient-based interpretability mechanism that enables clinicians and patients to understand model inferences. 3D facial surface scans of 2471 unaffected subjects and 1629 syndromic subjects representing 262 different genetic syndromes were used to train and evaluate the models. The flow-based models outperformed unsupervised comparison methods, with the best model achieving an ROC-AUC of 86.3% on a challenging, age and sex diverse data set. In addition to highlighting the viability of outlier-based syndrome screening tools, our methods generalize and extend previously proposed outlier scores for 3D face-based syndrome detection, resulting in improved performance for unsupervised syndrome detection., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Gender-affirming facial surgery (GFS) is pursued by transgender individuals who desire facial features that better reflect their gender identity. Currently, there are a few objective guidelines to justify and facilitate effective surgical decision making. Objective: To quantify the effect of sex on adult facial size and shape through an analysis of three-dimensional (3D) facial surface images. Materials and Methods: Facial measurements were obtained by registering an atlas facial surface to 3D surface scans of 545 males and 1028 females older than 20 years of age. The differences between male and female faces were analyzed and visualized for a set of predefined surgically relevant facial regions. Results: On average, male faces are 7.3% larger than female faces (Cohen's D  = 2.17). Sex is associated with significant facial shape differences ( p  < 0.0001) in the entire face as well as in each sub-region considered in this study. The facial regions in which sex has the largest effect on shape are the brow, jaw, nose, and cheek. Conclusions: These findings provide biologic data-driven anatomic guidance and justification for GFS, particularly forehead contouring cranioplasty, mandible and chin alterations, rhinoplasty, and cheek modifications.

Background: Asymmetries in craniofacial anomalies are commonly observed. In the facial skeleton, the left side is more commonly and/or severely affected than the right. Such asymmetries complicate treatment options. Mechanisms underlying variation in disease severity between individuals as well as within individuals (asymmetries) are still relatively unknown., Results: Developmental reductions in fibroblast growth factor 8 (Fgf8) have a dosage dependent effect on jaw size, shape, and symmetry. Further, Fgf8 mutants have directionally asymmetric jaws with the left side being more affected than the right. Defects in lower jaw development begin with disruption to Meckel's cartilage, which is discontinuous. All skeletal elements associated with the proximal condensation are dysmorphic, exemplified by a malformed and misoriented malleus. At later stages, Fgf8 mutants exhibit syngnathia, which falls into two broad categories: bony fusion of the maxillary and mandibular alveolar ridges and zygomatico-mandibular fusion. All of these morphological defects exhibit both inter- and intra-specimen variation., Conclusions: We hypothesize that these asymmetries are linked to heart development resulting in higher levels of Fgf8 on the right side of the face, which may buffer the right side to developmental perturbations. This mouse model may facilitate future investigations of mechanisms underlying human syngnathia and facial asymmetry., (© 2022 The Authors. Developmental Dynamics published by Wiley Periodicals LLC on behalf of American Association for Anatomy.)

The morphological changes of the brain and the skull are highly integrated as a result of shared developmental pathways and different types of interactions between them. Shared developmental trajectories between these two structures might be influenced by genetic and environmental factors. Although the effect of environmental factors on neural and craniofacial traits has been extensively studied, less is known about the specific impact of stressful conditions on the coordinated variation between these structures. Here, we test the effect of early nutrient restriction on morphological correspondence between the brain and the endocast. For this purpose, mice exposed to protein or calorie-protein restriction during gestation and lactation were compared with a control group in which dams were fed standard food ad libitum. High-resolution images were obtained after weaning to describe brain and endocranial morphology. By magnetic resonance imaging (MRI), brain volumes were obtained and endocasts were segmented from skull reconstructions derived from micro-computed tomography (microCT). Brain and endocranial volumes were compared to assess the correspondence in size. Shape changes were analyzed using a set of landmarks and semilandmarks on 3D surfaces. Results indicated that brain volume is relatively less affected by undernutrition during development than endocast volume. Shape covariation between the brain and the endocast was found to be quite singular for protein-restricted animals. Procrustes distances were larger between the brain and the endocast of the same specimens than between brains or endocasts of different animals, which means that the greatest similarity is by type of structure and suggests that the use of the endocast as a direct proxy of the brain at this intraspecific scale could have some limitations. In the same line, patterns of brain shape asymmetry were not directly estimated from endocranial surfaces. In sum, our findings indicate that morphological variation and association between the brain and the endocast is modulated by environmental factors and support the idea that head morphogenesis results from complex processes that are sensitive to the pervasive influence of nutrient intake., (© 2022 Anatomical Society.)

Structural variants (SVs) can affect protein-coding sequences as well as gene regulatory elements. However, SVs disrupting protein-coding sequences that also function as cis -regulatory elements remain largely uncharacterized. Here, we show that craniosynostosis patients with SVs containing the histone deacetylase 9 (HDAC9 ) protein-coding sequence are associated with disruption of TWIST1 regulatory elements that reside within the HDAC9 sequence. Based on SVs within the HDAC9 - TWIST1 locus, we defined the 3'- HDAC9 sequence as a critical TWIST1 regulatory region, encompassing craniofacial TWIST1 enhancers and CTCF sites. Deletions of either Twist1 enhancers (eTw5-7 Δ/Δ ) or CTCF site (CTCF-5 Δ/Δ ) within the Hdac9 protein-coding sequence led to decreased Twist1 expression and altered anterior/posterior limb expression patterns of SHH pathway genes. This decreased Twist1 expression results in a smaller sized and asymmetric skull and polydactyly that resembles Twist1 +/- mouse phenotype. Chromatin conformation analysis revealed that the Twist1 promoter interacts with Hdac9 sequences that encompass Twist1 enhancers and a CTCF site, and that interactions depended on the presence of both regulatory regions. Finally, a large inversion of the entire Hdac9 sequence ( Hdac9 INV/+ ) in mice that does not disrupt Hdac9 expression but repositions Twist1 regulatory elements showed decreased Twist1 expression and led to a craniosynostosis-like phenotype and polydactyly. Thus, our study elucidates essential components of TWIST1 transcriptional machinery that reside within the HDAC9 sequence. It suggests that SVs encompassing protein-coding sequences could lead to a phenotype that is not attributed to its protein function but rather to a disruption of the transcriptional regulation of a nearby gene., (© 2022 Hirsch et al.; Published by Cold Spring Harbor Laboratory Press.)

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 )., (© 2022. The Author(s).)

A variety of genetic mutations affect cell proliferation during organism development, leading to structural birth defects. However, the mechanisms by which these alterations influence the development of the face remain unclear. Cell proliferation and its relation to shape variation can be studied using Light-Sheet Microscopy (LSM) imaging across a range of developmental time points using mouse models. The aim of this work was to develop and evaluate accurate automatic methods based on convolutional neural networks (CNNs) for: (i) tissue segmentation (neural ectoderm and mesenchyme), (ii) cell segmentation in nuclear-stained images, and (iii) segmentation of proliferating cells in phospho-Histone H3 (pHH3)-stained LSM images of mouse embryos. For training and evaluation of the CNN models, 155 to 176 slices from 10 mouse embryo LSM images with corresponding manual segmentations were available depending on the segmentation task. Three U-net CNN models were trained optimizing their loss functions, among other hyper-parameters, depending on the segmentation task. The tissue segmentation achieved a macro-average F-score of 0.84, whereas the inter-observer value was 0.89. The cell segmentation achieved a Dice score of 0.57 and 0.56 for nuclear-stained and pHH3-stained images, respectively, whereas the corresponding inter-observer Dice scores were 0.39 and 0.45, respectively. The proposed pipeline using the U-net CNN architecture can accelerate LSM image analysis and together with the annotated datasets can serve as a reference for comparison of more advanced LSM image segmentation methods in future.

Similarity in facial characteristics between relatives suggests a strong genetic component underlies facial variation. While there have been numerous studies of the genetics of facial abnormalities and, more recently, single nucleotide polymorphism (SNP) genome-wide association studies (GWASs) of normal facial variation, little is known about the role of genetic structural variation in determining facial shape. In a sample of Bantu African children, we found that only 9% of common copy number variants (CNVs) and 10-kb CNV analysis windows are well tagged by SNPs (r 2 ≥ 0.8), indicating that associations with our internally called CNVs were not captured by previous SNP-based GWASs. Here, we present a GWAS and gene set analysis of the relationship between normal facial variation and CNVs in a sample of Bantu African children. We report the top five regions, which had p values ≤ 9.35 × 10 -6 and find nominal evidence of independent CNV association (p < 0.05) in three regions previously identified in SNP-based GWASs. The CNV region with strongest association (p = 1.16 × 10 -6 , 55 losses and seven gains) contains NFATC1 , which has been linked to facial morphogenesis and Cherubism, a syndrome involving abnormal lower facial development. Genomic loss in the region is associated with smaller average lower facial depth. Importantly, new loci identified here were not identified in a SNP-based GWAS, suggesting that CNVs are likely involved in determining facial shape variation. Given the plethora of SNP-based GWASs, calling CNVs from existing data may be a relatively inexpensive way to aid in the study of complex traits., Competing Interests: F.Y. is now a postdoctoral associate at The Jackson Laboratory. H.Y. is now an employee at Bionano Genomics. J.B.C. has current affiliations with the Programs in Metabolism and Medical & Population Genetics at Broad Institute of Harvard and MIT, the Center for Genomic Medicine at Massachusetts General Hospital, and the Division of Endocrinology and Center for Basic and Translational Obesity Research at Boston Children's Hospital. A.E.H. is on the editorial board for HGG Advances. All other authors declare no competing interests., (© 2021 The Authors.)

Realistic mappings of genes to morphology are inherently multivariate on both sides of the equation. The importance of coordinated gene effects on morphological phenotypes is clear from the intertwining of gene actions in signaling pathways, gene regulatory networks, and developmental processes underlying the development of shape and size. Yet, current approaches tend to focus on identifying and localizing the effects of individual genes and rarely leverage the information content of high-dimensional phenotypes. Here, we explicitly model the joint effects of biologically coherent collections of genes on a multivariate trait - craniofacial shape - in a sample of n = 1145 mice from the Diversity Outbred (DO) experimental line. We use biological process Gene Ontology (GO) annotations to select skeletal and facial development gene sets and solve for the axis of shape variation that maximally covaries with gene set marker variation. We use our process-centered, multivariate genotype-phenotype (process MGP) approach to determine the overall contributions to craniofacial variation of genes involved in relevant processes and how variation in different processes corresponds to multivariate axes of shape variation. Further, we compare the directions of effect in phenotype space of mutations to the primary axis of shape variation associated with broader pathways within which they are thought to function. Finally, we leverage the relationship between mutational and pathway-level effects to predict phenotypic effects beyond craniofacial shape in specific mutants. We also introduce an online application that provides users the means to customize their own process-centered craniofacial shape analyses in the DO. The process-centered approach is generally applicable to any continuously varying phenotype and thus has wide-reaching implications for complex trait genetics., Competing Interests: JA, DK, DR, MV, WL, FA, CR, SM, JC, DG, RM, BH No competing interests declared, (© 2021, Aponte et al.)

Facial morphology is highly variable, both within and among human populations, and a sizable portion of this variation is attributable to genetics. Previous genome scans have revealed more than 100 genetic loci associated with different aspects of normal-range facial variation. Most of these loci have been detected in Europeans, with few studies focusing on other ancestral groups. Consequently, the degree to which facial traits share a common genetic basis across diverse sets of humans remains largely unknown. We therefore investigated the genetic basis of facial morphology in an East African cohort. We applied an open-ended data-driven phenotyping approach to a sample of 2,595 3D facial images collected on Tanzanian children. This approach segments the face into hierarchically arranged, multivariate features that capture the shape variation after adjusting for age, sex, height, weight, facial size and population stratification. Genome scans of these multivariate shape phenotypes revealed significant (p < 2.5 × 10-8) signals at 20 loci, which were enriched for active chromatin elements in human cranial neural crest cells and embryonic craniofacial tissue, consistent with an early developmental origin of the facial variation. Two of these associations were in highly conserved regions showing craniofacial-specific enhancer activity during embryological development (5q31.1 and 12q21.31). Six of the 20 loci surpassed a stricter threshold accounting for multiple phenotypes with study-wide significance (p < 6.25 × 10-10). Cross-population comparisons indicated 10 association signals were shared with Europeans (seven sharing the same associated SNP), and facilitated fine-mapping of causal variants at previously reported loci. Taken together, these results may point to both shared and population-specific components to the genetic architecture of facial variation., Competing Interests: The authors have declared that no competing interests exist.

Although many studies relating stature to foot length have been carried out, the relationship between foot size and body mass remains poorly understood. Here we investigate this relationship in 193 adult and 50 juvenile habitually unshod/minimally shod individuals from five different populations-Machiguenga, Daasanach, Pumé, Hadzabe, and Samoans-varying greatly in body size and shape. Body mass is highly correlated with foot size, and can be predicted from foot area (maximum length × breadth) in the combined sample with an average error of about 10%. However, comparisons among populations indicate that body shape, as represented by the body mass index (BMI), has a significant effect on foot size proportions, with higher BMI samples exhibiting relatively smaller feet. Thus, we also derive equations for estimating body mass from both foot size and BMI, with BMI in footprint samples taken as an average value for a taxon or population, estimated independently from skeletal remains. Techniques are also developed for estimating body mass in juveniles, who have relatively larger feet than adults, and for converting between foot and footprint size. Sample applications are given for five Pliocene through Holocene hominin footprint samples from Laetoli (Australopithecus afarensis), Ileret (probable Homo erectus), Happisburgh (possible Homo antecessor), Le Rozel (archaic Homo sapiens), and Barcin Höyük (H. sapiens). Body mass estimates for Homo footprint samples appear reasonable when compared to skeletal estimates for related samples. However, estimates for the Laetoli footprint sample using the new formulae appear to be too high when compared to skeletal estimates for A. afarensis. Based on the proportions of A.L. 288-1, this is apparently a result of relatively large feet in this taxon. A different method using a ratio between body mass and foot area in A.L. 288-1 provides estimates more concordant with skeletal estimates and should be used for A. afarensis., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Epigenetic and chromatin regulation of craniofacial development remains poorly understood. Ankyrin Repeat Domain 11 ( ANKRD11 ) is a chromatin regulator that has previously been shown to control neural stem cell fates via modulation of histone acetylation. ANKRD11 gene variants, or microdeletions of the 16q24.3 chromosomal region encompassing the ANKRD11 gene, cause KBG syndrome, a rare autosomal dominant congenital disorder with variable neurodevelopmental and craniofacial involvement. Craniofacial abnormalities include a distinct facial gestalt, delayed bone age, tooth abnormalities, delayed fontanelle closure, and frequently cleft or submucosal palate. Despite this, the dramatic phenotype and precise role of ANKRD11 in embryonic craniofacial development remain unexplored. Quantitative analysis of 3D images of KBG syndromic subjects shows an overall reduction in the size of the middle and lower face. Here, we report that mice with heterozygous deletion of Ankrd11 in neural crest cells (Ankrd11 nchet ) display a mild midfacial hypoplasia including reduced midfacial width and a persistent open fontanelle, both of which mirror KBG syndrome patient facial phenotypes. Mice with a homozygous Ankrd11 deletion in neural crest cells (Ankrd11 ncko ) die at birth. They show increased severity of several clinical manifestations described for KBG syndrome, such as cleft palate, retrognathia, midfacial hypoplasia, and reduced calvarial growth. At E14.5, Ankrd11 expression in the craniofacial complex is closely associated with developing bony structures, while expression at birth is markedly decreased. Conditional deletion of Ankrd11 leads to a reduction in ossification of midfacial bones, with several ossification centers failing to expand and/or fuse. Intramembranous bones show features of delayed maturation, with bone remodeling severely curtailed at birth. Palatal shelves remain hypoplastic at all developmental stages, with a local reduction in proliferation at E13.5. Our study identifies Ankrd11 as a critical regulator of intramembranous ossification and palate development and suggests that Ankrd11 nchet and Ankrd11 ncko mice may serve as pre-clinical models for KBG syndrome in humans., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Roth, Baddam, Lin, Vidal-García, Aponte, De Souza, Godziuk, Watson, Footz, Schachter, Egan, Hallgrímsson, Graf and Voronova.)