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Hallgrimsson, B.

Publications and source records attributed to Hallgrimsson, B..

At least 19 recordsLinked to original sources

Heterochronic Uncoupling of Brain and Face Morphogenesis Drives Premature Fusion in Ciliary Transition Zone Mutants

Normal facial development is highly coordinated with embryonic brain expansion, suggesting the forebrain acts as a physical scaffold dictating the spatial timing of facial prominence apposition and fusion. To test this idea, we compared B9d1 ciliary transition zone mutants, which exhibit altered Hedgehog signaling and premature facial fusion, to a normal murine developmental morphospace. At e11.5, mutant brains are significantly reduced in size, yet intrinsic facial prominence size remains largely normal. Projecting e11.5 and e12.5 mutants into the normal morphospace reveals a severe heterochronic uncoupling: the delayed, narrowed neurocranium mechanically forces normal-sized facial prominences into premature convergence. These results indicate that when brain growth slows, facial prominences initiate contact earlier in restricted spatial bounds. Conversely, this model predicts that an accelerated, expanded brain may act as a physical wedge, increasing the likelihood of cleft lip. By mathematically modeling these structural dependencies, we propose that palatogenesis operates on a continuous phenotypic spectrum, where premature fusion and cleft lip represent alternative physical outcomes conditioned on the underlying brain developmental trajectory.

developmental biology↗

Navigating the window: structural bottlenecks in avian craniofacial integration revealed by the ontogenetic patterning of shape variance

Background: Successful palatal morphogenesis requires the precise spatiotemporal choreography of independent facial prominences. Our previous macroevolutionary analyses identified a convergence in amniote facial growth at primary palatal fusion, associated with reduced shape variability. We hypothesize that this constraint operates within individual species, representing a shared structural bottleneck where brain growth acts as a critical morphogenetic co-factor. To test this idea, we analyzed high-resolution 3D micro-CT images of embryonic chickens (Gallus gallus, N=217) spanning primary palatogenesis. Utilizing 3D geometric morphometrics (3DGM), we quantified a continuous "developmental morphospace" integrating the face and brain. Results: Facial shape follows a highly nonlinear developmental trajectory. Using a continuous sliding-window analysis, we demonstrate that local morphological disparity undergoes a significant system-wide collapse coinciding with primary palatal fusion. Partial Least Squares (PLS) confirms this morphospace pivot is tightly coordinated with neurocranial development. Post-fusion, the modules uncouple: facial allometry switches from convergent to divergent projecting growth, while the brain undergoes spatial encapsulation, subsequently flatlining its morphological disparity. Conclusions: Craniofacial morphogenesis can be described in terms of a tightly regulated biphasic developmental hourglass. The physical tethering of facial prominences creates a brief structurally constrained "shape window" essential for successful fusion. Deviations from this bottleneck, whether driven by altered prominence trajectories, increased local variance, or disruptions to the underlying forebrain landscape, push embryos into unoccupied morphospace, providing a unified mechanical and predictive framework for the spatiotemporal origins of non-syndromic cleft lip.

developmental biology↗

Cephalo-pelvic covariation and sexual dimorphism are disrupted in hybrid mice: implications for the human obstetrical dilemma

Cephalo-pelvic disproportion in humans has traditionally been interpreted through the obstetrical dilemma framework, assuming a trade-off between bipedal locomotion and childbirth. However, cephalo-pelvic covariation and pelvic sexual dimorphism might be common adaptations to parturition among mammals. We use a controlled hybridization model in mice to test whether cephalo-pelvic covariation and pelvic sexual dimorphism are population-specific, genetically structured, and sensitive to hybridization. We analyzed skull-pelvis variation and covariation, as well as sexual dimorphism of pelvic morphology across four divergent wild-derived mouse strains and their hybrids. Hybridization induced consistent cranial and pelvic size enlargement. Females exhibited significant cephalo-pelvic shape covariation, characterized by an association between rounder, wider birth canals and larger neurocrania, consistent with functional integration under obstetric selection. Hybrids showed disrupted size covariation, increased pelvis shape variance, and reduced cephalo-pelvic integration. Pelvic sexual dimorphism was systematically reduced in hybrids. Cephalo-pelvic covariation and pelvic sexual dimorphism are not exclusive to bipedal or encephalized species. They likely reflect widespread selection on birth canal morphology in mammals and have a complex genetic basis sensitive to hybridization. These findings weaken a human-exclusive interpretation of the obstetrical dilemma and highlight genetic introgression as an understudied factor shaping cephalo-pelvic integration and disproportion risk in mammals, including humans.

evolutionary biology↗

The craniofacial shape of modern humans embodies genomic signatures of evolution, diversity, and clinical conditions

Human craniofacial morphology is a hallmark of our species diversity and evolutionary history, shaped by adaptation, introgression, and global dispersal. Cranial globularization and chin emergence are well-documented morphological transformations whose genetic basis remains poorly understood, whereas Neandertal introgression is primarily documented through genomic evidence. How these evolutionary phenomena relate to craniofacial variation in present-day humans remains largely unresolved. Here, we leverage 3D craniofacial data from over 50,000 UK Biobank participants and employ a multivariate, multiscale genome-wide association approach to define axes of variation aligned with inter-population allele frequency shifts, evolutionary processes, and clinical conditions. We identify continuous craniofacial trends within our cohort that mirror global patterns of genetic diversity, indicating that facial differences between human populations arise at the phenotypic axes already present within a single population. We further demonstrate that modern human-derived alleles underlie the origins of the human chin by reducing midfacial projection relative to other hominins and reveal the persistent effects of Neandertal introgression on craniofacial diversity today. We also model genetically informed endophenotypes for orofacial clefts, obstructive sleep apnoea, and myopia. These findings provide insights into our species evolutionary history and endophenotypes of clinical conditions and establish a framework for contextualizing craniofacial diversity into biologically meaningful axes of variation relevant to diverse scientific disciplines.

genetics↗

Downstream branches of receptor tyrosine kinase signaling act interdependently to shape the face

BackgroundPreviously 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. ResultsSmall 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. ConclusionsSince 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. Bullet pointsInhibiting three downstream effectors of receptor tyrosine kinase (RTK) signaling (MEK1/2, PLCy, and PI3K) in the frontonasal process of chicken embryos caused similar mild truncation of growth. Combining all three inhibitors had a slightly stronger effect on truncation. Individual inhibitors did not have specific effects on cellular proliferation, apoptosis, or cellular orientation. The downstream branches of RTK signaling likely have shared interdependent effects on cellular activities that contribute to morphogenesis.

developmental biology↗

Mapping genes for human face shape: exploration of univariate phenotyping strategies

Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits. Author SummaryAdvancements linking variation in the human genome to phenotypes have rapidly evolved in recent decades and have revealed that most human traits are influenced by genetic variants to at least some degree. While many traits, such as stature, are straightforward to acquire and investigate, the multivariate and multipartite nature of facial shape makes quantification more challenging. In this study, we compared the impact of different facial phenotyping approaches on gene mapping outcomes. Our findings suggest that the choice of facial phenotyping method has an impact on apparent trait heritability and the ability to detect genetic association signals. These results offer valuable insights into the importance of phenotyping in genetic investigations, especially when dealing with highly complex morphological traits.

genetics↗

Syndrome-informed phenotyping identifies a polygenic background for achondroplasia-like facial variation in the general population

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.

genetics↗

Classifying high-dimensional phenotypes with ensemble learning

O_LIClassification 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. C_LIO_LIWe 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. C_LIO_LIWe 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 R2 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. C_LIO_LILearning-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. C_LI

bioinformatics↗

Quantifying the relationship between cell proliferation and morphology during development of the face

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.

developmental biology↗

Precise modulation of transcription factor levels reveals drivers of dosage sensitivity

Transcriptional regulation displays extensive robustness, but human genetics indicate sensitivity to transcription factor (TF) dosage. Reconciling such observations requires quantitative studies of TF dosage effects at trait-relevant ranges, which are lacking to date. TFs play central roles in both normal-range and disease-associated variation in facial morphology; we therefore developed an approach to precisely modulate TF levels in human facial progenitors and applied it to SOX9, a TF associated with craniofacial variation and disease (Pierre Robin Sequence, PRS). We found that 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 predict gene expression responses. Sensitive REs and genes underlie the vulnerability of chondrogenesis and PRS-like craniofacial shape variation to SOX9 dosage perturbation. We propose that such REs and genes drive the sensitivity of specific phenotypes to TF dosage, while buffering of other genes leads to robust, nonlinear dosage-to-phenotype relationships.

genetics↗

Fgf8 dosage regulates jaw shape and symmetry through pharyngeal-cardiac tissue relationships

BackgroundAsymmetries in craniofacial anomalies are commonly observed. With respect to 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. ResultsDevelopmental 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 an early disruption to Meckels cartilage, which is discontinuous and appears as two separate condensations in Fgf8 mutants. All skeletal elements associated with the proximal condensation are dysmorphic in the mutants, which is exemplified by a malformed and mis-oriented malleus. At later stages, Fgf8 mutants exhibit syngnathia, which falls into 2 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-individual variation. ConclusionsWe hypothesize that these asymmetries are linked to asymmetries in heart development resulting in higher levels of Fgf8 on the right side of the face during development, which may buffer the right side to mild developmental perturbations. This mutant mouse is a good model for future investigations of mechanisms underlying human syngnathia and facial asymmetry.

developmental biology↗

Bite force performance from wild derived mice has undetectable heritability despite having heritable morphological components.

Fitness-related traits tend to have low heritabilities. Conversely, morphology tends to be highly heritable. Yet, many fitness-related performance traits such as running speed or bite force depend critically on morphology. Craniofacial morphology correlates with bite performance in several groups including rodents. However, within species, this relationship is less clear, and the genetics of performance, morphology and function are rarely analyzed in combination. Here, we use a half-sib design in outbred wild-derived Mus musculus to study the morphology-bite force relationship and determine whether there is additive genetic (co-)variance for these traits. Results suggest that bite force has undetectable additive genetic variance and heritability in this sample, while morphological traits related mechanically to bite force exhibit varying levels of heritability. The most heritable traits include the length of the mandible which relates to bite force. Despite its correlation with morphology, realized bite force was not heritable, which suggests it is less responsive to selection in comparison to its morphological determinants. We explain this paradox with a non-additive, many-to-one mapping hypothesis of heritable change in complex traits. We furthermore propose that performance traits could evolve if pleiotropic relationships among the determining traits are modified.

evolutionary biology↗

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, doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph).

genetics↗

HDAC9 structural variants disrupting TWIST1 transcriptional regulation lead to craniofacial and limb malformations

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 HDAC9 sequence. Based on SVs within the HDAC9-TWIST1 locus, we defined the 3 HDAC9 sequence (~500Kb) as a critical TWIST1 regulatory region, encompassing craniofacial TWIST1 enhancers and CTCF sites. Deletions of either Twist1 enhancers (eTw5-7{Delta}/{Delta}) or Ctcf site (Ctcf{Delta}/{Delta}) within the Hdac9 protein-coding sequence in mice 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 region 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 (Hdac9INV/+) 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 elucidated essential components of TWIST1 transcriptional machinery that reside within the HDAC9 sequence, suggesting that SVs, encompassing protein-coding sequence, such as HDAC9, 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, such as TWIST1.

genomics↗

Segmentation of Tissues and Proliferating Cells in Light-Sheet Microscopy Images using Convolutional Neural Networks

Background and ObjectiveA variety of genetic mutations are known to affect cell proliferation and apoptosis during organism development, leading to structural birth defects such as facial clefting. Yet, the mechanisms how these alterations influence the development of the face remain unclear. Cell proliferation and its relation to shape variation can be studied in high detail using Light-Sheet Microscopy (LSM) imaging across a range of developmental time points. However, the large number of LSM images captured at cellular resolution precludes manual analysis. Thus, the aim of this work was to develop and evaluate automatic methods to segment tissues and proliferating cells in these images in an accurate and efficient way. MethodsWe developed, trained, and evaluated convolutional neural networks (CNNs) for segmenting tissues, cells, and specifically proliferating cells in LSM datasets. We compared the automatically extracted tissue and cell annotations to corresponding manual segmentations for three specific applications: (i) tissue segmentation (neural ectoderm and mesenchyme) in nuclear-stained LSM images, (ii) cell segmentation in nuclear-stained LSM images, and (iii) segmentation of proliferating cells in Phospho-Histone H3 (PHH3)-stained LSM images. ResultsThe automatic CNN-based tissue segmentation method achieved a macro-average F-score of 0.84 compared to a macro-average F-score of 0.89 comparing corresponding manual segmentations from two observers. The automatic cell segmentation method in nuclear-stained LSM images achieved an F-score of 0.57, while comparing the manual segmentations resulted in an F-score of 0.39. Finally, the automatic segmentation method of proliferating cells in the PHH3-stained LSM datasets achieved an F-score of 0.56 for the automated method, while comparing the manual segmentations resulted in an F-score of 0.45. ConclusionsThe proposed automatic CNN-based framework for tissue and cell segmentation leads to results comparable to the inter-observer agreement, accelerating the LSM image analysis. The trained CNN models can also be applied for shape or morphological analysis of embryos, and more generally in other areas of cell biology.

bioinformatics↗

Genome-wide Copy Number Variations in a Large Cohort of Bantu African Children

BackgroundCopy number variations (CNVs) account for a substantial proportion of inter-individual genomic variation. However, a majority of genomic variation studies have focused on single-nucleotide variations (SNVs), with limited genome-wide analysis of CNVs in large cohorts, especially in populations that are under-represented in genetic studies including people of African descent. ResultsIn this study, we carried out a genome-wide analysis in > 3400 healthy Bantu Africans from Tanzania using high density (> 2.5 million probes) genotyping arrays. We identified over 400000 CNVs larger than 1 kilobase (kb), for an average of 120 CNVs (SE = 2.57) per individual. We detected 866 large CNVs ([≥] 300 kb), some of which overlapped genomic regions previously associated with multiple congenital anomaly syndromes, including Prader-Willi/Angelman syndrome (Type1) and 22q11.2 deletion syndrome. Furthermore, several of the common CNVs seen in our cohort ([≥] 5%) overlap genes previously associated with developmental disorders. ConclusionThese findings may help refine the phenotypic outcomes and penetrance of variations affecting genes and genomic regions previously implicated in diseases. Our study provides one of the largest datasets of CNVs from individuals of African ancestry, enabling improved clinical evaluation and disease association of CNVs observed in research and clinical studies in African populations.

genomics↗

Shapes and Genescapes: Mapping Multivariate Phenotype-Biological Process Associations for Craniofacial Shape

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 = 1,145 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 (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 which 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.

genomics↗

Selection for increased tibia length in mice alters skull shape through parallel changes in developmental mechanisms

Bones in the vertebrate cranial base and limb skeleton grow by endochondral ossification, under the control of growth plates. Mechanisms of endochondral ossification are conserved across growth plates, which increases covariation in size and shape among bones, and in turn may lead to correlated changes in skeletal traits not under direct selection. We used micro-CT and geometric morphometrics to characterize shape changes in the cranium of the Longshanks mouse, which was selectively bred for longer tibiae. We show that Longshanks skulls became longer, flatter, and narrower in a stepwise process. Moreover, we show that these morphological changes likely resulted from developmental changes in the growth plates of the Longshanks cranial base, mirroring changes observed in its tibia. Thus, indirect and non-adaptive morphological changes can occur due to developmental overlap among distant skeletal elements, with important implications for interpreting the evolutionary history of vertebrate skeletal form.

evolutionary biology↗