A landmark-free morphometrics pipeline for high-resolution phenotyping: application to a mouse model of Down syndrome

Assessing the application of landmark-free morphometrics to macroevolutionary analyses

The study of phenotypic evolution has been transformed in recent decades by methods allowing precise quantification of anatomical shape, in particular 3D geometric morphometrics. While this effectiveness of geometric morphometrics has been demonstrated by thousands of studies, it generally requires manual or semi-automated landmarking, which is time-consuming, susceptible to operator bias, and limits comparisons across morphologically disparate taxa. Emerging automated methods, particularly landmark-free techniques, offer potential solutions, but these approaches have thus far been primarily applied to closely related forms. In this study, we explore the utility of automated, landmark-free approaches for macroevolutionary analyses. We compare an application of Large Deformation Diffeomorphic Metric Mapping (LDDMM) known as Deterministic Atlas Analysis (DAA) with a high-density geometric morphometric approach, using a dataset of 322 mammals spanning 180 families. Initially, challenges arose from using mixed modalities (computed tomography (CT) and surface scans), which we addressed by standardising the data by using Poisson surface reconstruction that creates watertight, closed surfaces for all specimens. After standardisation, we observed a significant improvement in the correspondence between patterns of shape variation measured using manual landmarking and DAA, although differences emerged, especially for Primates and Cetacea. We further evaluated the downstream effects of these differences on macroevolutionary analyses, finding that both methods produced comparable but varying estimates of phylogenetic signal, morphological disparity and evolutionary rates. Our findings highlight the potential of landmark-free approaches like DAA for large scale studies across disparate taxa, owing to their enhanced efficiency. However, they also reveal several challenges that should be addressed before these methods can be widely adopted. In this context, we outline these issues, propose solutions based on existing literature, and identify potential avenues for further research. We argue that by incorporating these improvements, the application of landmark-free analyses could be expanded, thereby enhancing the scope of morphometric studies and enabling the analysis of larger and more diverse datasets.

Personalized Joint Replacement: Landmark-Free Morphometric Analysis of Distal Radii

Background: Fractures of the distal radius are common, particularly among young men and elderly women, often leading to painful wrist arthritis, especially if the joint surface has been affected. Traditional treatments of the wrist, such as full or partial wrist fusion, limit movement, and common wrist prostheses have high complication rates. Regenerative medicine and 3D bioprinting offer the potential for personalized joint replacements. Methods: This study evaluates using the contralateral radius as a template for creating customized distal radius prostheses. Bilateral CT scans of healthy wrists were analyzed to assess the shape and symmetry of the distal radius using a landmark-free morphometric method. Instead of comparing defined landmarks, the entire surface of the radius is analyzed employing dense point- and deformation-based morphometry to detect subtle morphological differences, providing an unbiased and more accurate comparison of the overall deformations in the distal radii. Results: results show strong intraindividual symmetry in joint surfaces. Interindividual comparisons revealed significant morphological variations, particularly gender-specific differences. Conclusions: These findings support the use of the contralateral radius as a template for the replaced side. At the same time, the interindividual results endorse the approach of pursuing personalized prostheses as the optimal replacement for distal joint surfaces. The increasing improvement of 3D-printed prostheses promises new methods for better outcomes in distal radius arthrosis after intraarticular fractures. Further research into clinical applications and biocompatible 3D printing materials is recommended.

Opportunities and Challenges in Applying AI to Evolutionary Morphology

Artificial intelligence (AI) is poised to revolutionize many aspects of science, including the study of evolutionary morphology. While classical AI methods such as principal component analysis and cluster analysis have been commonplace in the study of evolutionary morphology for decades, recent years have seen increasing application of deep learning to ecology and evolutionary biology. As digitized specimen databases become increasingly prevalent and openly available, AI is offering vast new potential to circumvent long-standing barriers to rapid, big data analysis of phenotypes. Here, we review the current state of AI methods available for the study of evolutionary morphology, which are most developed in the area of data acquisition and processing. We introduce the main available AI techniques, categorizing them into 3 stages based on their order of appearance: (1) machine learning, (2) deep learning, and (3) the most recent advancements in large-scale models and multimodal learning. Next, we present case studies of existing approaches using AI for evolutionary morphology, including image capture and segmentation, feature recognition, morphometrics, and phylogenetics. We then discuss the prospectus for near-term advances in specific areas of inquiry within this field, including the potential of new AI methods that have not yet been applied to the study of morphological evolution. In particular, we note key areas where AI remains underutilized and could be used to enhance studies of evolutionary morphology. This combination of current methods and potential developments has the capacity to transform the evolutionary analysis of the organismal phenotype into evolutionary phenomics, leading to an era of "big data" that aligns the study of phenotypes with genomics and other areas of bioinformatics.

How many specimens make a sufficient training set for automated three-dimensional feature extraction?

Deep learning has emerged as a robust tool for automating feature extraction from three-dimensional images, offering an efficient alternative to labour-intensive and potentially biased manual image segmentation methods. However, there has been limited exploration into the optimal training set sizes, including assessing whether artficial expansion by data augmentation can achieve consistent results in less time and how consistent these benefits are across different types of traits. In this study, we manually segmented 50 planktonic foraminifera specimens from the genus Menardella to determine the minimum number of training images required to produce accurate volumetric and shape data from internal and external structures. The results reveal unsurprisingly that deep learning models improve with a larger number of training images with eight specimens being required to achieve 95% accuracy. Furthermore, data augmentation can enhance network accuracy by up to 8.0%. Notably, predicting both volumetric and shape measurements for the internal structure poses a greater challenge compared with the external structure, owing to low contrast differences between different materials and increased geometric complexity. These results provide novel insight into optimal training set sizes for precise image segmentation of diverse traits and highlight the potential of data augmentation for enhancing multivariate feature extraction from three-dimensional images.

Large deformation diffeomorphic mapping of 3D shape variation reveals two distinct mandible and head capsule morphs in Atta vollenweideri leaf-cutter worker ants

Ants are crucial ecosystem engineers, and their ecological success is facilitated by a division of labour among sterile "workers". In some ant lineages, workers have undergone further morphological differentiation, resulting in differences in body size, shape, or both. Distinguishing between changes in size and shape is not trivial. Traditional approaches based on allometry reduce complex 3D shapes into simple linear, areal, or volume metrics; modern approaches using geometric morphometrics typically rely on landmarks, introducing observer bias and a trade-off between effort and accuracy. Here, we use a landmark-free method based on large deformation diffeomorphic metric mapping (LDDMM) to assess the co-variation of size and 3D shape in the mandibles and head capsules of Atta vollenweideri leaf-cutter ants, a species exhibiting extreme worker size-variation. Body mass varied by more than two orders of magnitude, but a shape atlas created via LDDMM on μ-CT-derived 3D mesh files revealed only two distinct head capsule and mandibles shapes-one for the minims (body mass < 1 mg) and one for all other workers. We discuss the functional significance of the identified 3D shape variation, and its implications for the evolution of extreme polymorphism in Atta.

Investigating brain alterations in the Dp1Tyb mouse model of Down syndrome

Down syndrome (DS) is one of the most common birth defects and the most prevalent genetic form of intellectual disability. DS arises from trisomy of chromosome 21, but its molecular and pathological consequences are not fully understood. In this study, we compared Dp1Tyb mice, a DS model, against their wild-type (WT) littermates of both sexes to investigate the impact of DS-related genetic abnormalities on the brain phenotype. We performed in vivo whole brain magnetic resonance imaging (MRI) and hippocampal 1H magnetic resonance spectroscopy (MRS) on the animals at 3 months of age. Subsequently, ex vivo MRI scans and histological analyses were conducted post-mortem. Our findings unveiled the following neuroanatomical and biochemical alterations in the Dp1Tyb brains: a smaller surface area and a rounder shape compared to WT brains, with DS males also presenting smaller global brain volume compared with the counterpart WT. Regional volumetric analysis revealed significant changes in 26 out of 72 examined brain regions, including the medial prefrontal cortex and dorsal hippocampus. These alterations were consistently observed in both in vivo and ex vivo imaging data. Additionally, high-resolution ex vivo imaging enabled us to investigate cerebellar layers and hippocampal sub-regions, revealing selective areas of decrease and remodelling in these structures. An analysis of hippocampal metabolites revealed an elevation in glutamine and the glutamine/glutamate ratio in the Dp1Tyb mice compared to controls, suggesting a possible imbalance in the excitation/inhibition ratio. This was accompanied by the decreased levels of taurine. Histological analysis revealed fewer neurons in the hippocampal CA3 and DG layers, along with an increase in astrocytes and microglia. These findings recapitulate multiple neuroanatomical and biochemical features associated with DS, enriching our understanding of the potential connection between chromosome 21 trisomy and the resultant phenotype.

A landmark-free analysis of the pelvic girdle in Sulawesi ricefishes (Adrianichthyidae): How 2D and 3D geometric morphometrics can complement each other in the analysis of a complex structure

Geometric morphometrics (GM) enable the quantification of morphological variation on various scales. Recent technical advances allow analyzing complex three-dimensional shapes also in cases where landmark-based approaches are not appropriate. Pelvic girdle bones (basipterygia) of Sulawesi ricefishes are 3D structures that challenge traditional morphometrics. We hypothesize that the pelvic girdle of ricefishes experienced sex-biased selection pressures in species where females provide brood care by carrying fertilized eggs supported by elongated pelvic fins ("pelvic brooding"). We test this by comparing pelvic bone shapes of both sexes in species exhibiting pelvic brooding and the more common reproductive strategy "transfer brooding," by using landmark-free 2D and 3D GM, as well as qualitative shape descriptions. Both landmark-free approaches revealed significant interspecific pelvic bone variation in the lateral process, medial facing side of the pelvic bone, and overall external and internal wing shape. Within pelvic brooders, the three analyzed species are clearly distinct, while pelvic bones of the genus Adrianichthys are more similar to transfer brooding Oryzias. Female pelvic brooding Oryzias exhibit prominent, medially pointing tips extending from the internal wing and basipterygial plate that are reduced or absent in conspecific males, Adrianichthys and transfer brooding Oryzias, supporting our hypothesis that selection pressures affecting pelvic girdle shape are sex-biased in Sulawesi ricefishes. Furthermore, both sexes of pelvic brooding Oryzias have overall larger pelvic bones than other investigated ricefishes. Based on these differences, we characterized two reproductive strategy- and sex-dependent pelvic girdle types for Sulawesi ricefishes. Morphological differences between the investigated pelvic brooding genera Adrianichthys and Oryzias provide additional evidence for two independent origins of pelvic brooding. Overall, our findings add to a better understanding on traits related to pelvic brooding in ricefishes and provide a basis for upcoming studies on pelvic girdle function and morphology.

Beak morphometry and morphogenesis across avian radiations

Adaptive avian radiations associated with the diversification of bird beaks into a multitude of forms enabling different functions are exemplified by Darwin's finches and Hawaiian honeycreepers. To elucidate the nature of these radiations, we quantified beak shape and skull shape using a variety of geometric measures that allowed us to collapse the variability of beak shape into a minimal set of geometric parameters. Furthermore, we find that just two measures of beak shape-the ratio of the width to length and the normalized sharpening rate (increase in the transverse beak curvature near the tip relative to that at the base of the beak)-are strongly correlated with diet. Finally, by considering how transverse sections to the beak centreline evolve with distance from the tip, we show that a simple geometry-driven growth law termed 'modified mean curvature flow' captures the beak shapes of Darwin's finches and Hawaiian honeycreepers. A surprising consequence of the simple growth law is that beak shapes that are not allowed based on the developmental programme of the beak are also not observed in nature, suggesting a link between evolutionary morphology and development in terms of growth-driven developmental constraints.

Assessing craniofacial growth and form without landmarks: A new automatic approach based on spectral methods

We present a novel method for the morphometric analysis of series of 3D shapes, and demonstrate its relevance for the detection and quantification of two craniofacial anomalies: trigonocephaly and metopic ridges, using CT-scans of young children. Our approach is fully automatic, and does not rely on manual landmark placement and annotations. Our approach furthermore allows to differentiate shape classes, enabling successful differential diagnosis between trigonocephaly and metopic ridges, two related conditions characterized by triangular foreheads. These results were obtained using recent developments in automatic nonrigid 3D shape correspondence methods and specifically spectral approaches based on the functional map framework. Our method can capture local changes in geometric structure, in contrast to methods based, for instance, on global shape descriptors. As such, our approach allows to perform automatic shape classification and provides visual feedback on shape regions associated with different classes of deformations. The flexibility and generality of our approach paves the way for the application of spectral methods in quantitative medicine.

Pervasive cortical and white matter anomalies in a mouse model for CHARGE syndrome

CHARGE (Coloboma of the eye, Heart defects, Atresia of the choanae, Retardation of growth, Genital anomalies and Ear abnormalities) syndrome is a disorder caused by mutations in the gene encoding CHD7, an ATP dependent chromatin remodelling factor, and is characterised by a diverse array of congenital anomalies. These include a range of neuroanatomical comorbidities which likely underlie the varied neurodevelopmental disorders associated with CHARGE syndrome, which include intellectual disability, motor coordination deficits, executive dysfunction, and autism spectrum disorder. Cranial imaging studies are challenging in CHARGE syndrome patients, but high-throughput magnetic resonance imaging (MRI) techniques in mouse models allow for the unbiased identification of neuroanatomical defects. Here, we present a comprehensive neuroanatomical survey of a Chd7 haploinsufficient mouse model of CHARGE syndrome. Our study uncovered widespread brain hypoplasia and reductions in white matter volume across the brain. The severity of hypoplasia appeared more pronounced in posterior areas of the neocortex compared to anterior regions. We also perform the first assessment of white matter tract integrity in this model through diffusion tensor imaging (DTI) to assess the potential functional consequences of widespread reductions in myelin, which suggested the presence of white matter integrity defects. To determine if white matter alterations correspond to cellular changes, we quantified oligodendrocyte lineage cells in the postnatal corpus callosum, uncovering reduced numbers of mature oligodendrocytes. Together, these results present a range of promising avenues of focus for future cranial imaging studies in CHARGE syndrome patients.

Hypochondroplasia gain-of-function mutation in FGFR3 causes defective bone mineralization in mice

Hypochondroplasia (HCH) is a mild dwarfism caused by missense mutations in fibroblast growth factor receptor 3 (FGFR3), with the majority of cases resulting from a heterozygous p.Asn540Lys gain-of-function mutation. Here, we report the generation and characterization of the first mouse model (Fgfr3Asn534Lys/+) of HCH to our knowledge. Fgfr3Asn534Lys/+ mice exhibited progressive dwarfism and impairment of the synchondroses of the cranial base, resulting in defective formation of the foramen magnum. The appendicular and axial skeletons were both severely affected and we demonstrated an important role of FGFR3 in regulation of cortical and trabecular bone structure. Trabecular bone mineral density (BMD) of long bones and vertebral bodies was decreased, but cortical BMD increased with age in both tibiae and femurs. These results demonstrate that bones in Fgfr3Asn534Lys/+ mice, due to FGFR3 activation, exhibit some characteristics of osteoporosis. The present findings emphasize the detrimental effect of gain-of-function mutations in the Fgfr3 gene on long bone modeling during both developmental and aging processes, with potential implications for the management of elderly patients with hypochondroplasia and osteoporosis.

An automated landmark method to describe geometric changes in the human mandible during growth

OBJECTIVE

The principal aim of this study was to assess an automatic landmarking approach to human mandibles based on the atlas method. The secondary aim was to identify the areas of greatest variation in the mandibles of middle-aged to older adults.

DESIGN

Our sample consisted of 160 mandibles from computed tomography scans of 80 men and 80 women aged between 40 and 79 years. Eleven anatomical landmarks were placed manually on mandibles. The automated landmarking through point cloud alignment and correspondence (ALPACA) method implemented in 3D Slicer was used to automatically place landmarks to all meshes. Euclidean distances, normalized centroid size, and Procrustes ANOVA were calculated for both methods. A pseudo-landmarks approach was followed using ALPACA to identify areas of changes among our sample.

RESULTS

The ALPACA method showed significant differences in Euclidean distances for all landmarks compared to the manual method. A mean Euclidean distance of 1.7 mm was found for the ALPACA method and 0.99 mm for the manual method. Both methods found that sex, age, and size had a significant effect on mandibular shape. The greatest variations were observed in the condyle, ramus, and symphysis regions.

CONCLUSION

The results obtained using the ALPACA method are acceptable and promising. This approach can automatically place landmarks with an average accuracy of less than 2 mm, which may be sufficient in most anthropometric analyses. In the light of our results, however, odontological application such as occlusal analysis is not recommended.

Craniofacial dysmorphology in Down syndrome is caused by increased dosage of Dyrk1a and at least three other genes

Down syndrome (DS), trisomy of human chromosome 21 (Hsa21), occurs in 1 in 800 live births and is the most common human aneuploidy. DS results in multiple phenotypes, including craniofacial dysmorphology, which is characterised by midfacial hypoplasia, brachycephaly and micrognathia. The genetic and developmental causes of this are poorly understood. Using morphometric analysis of the Dp1Tyb mouse model of DS and an associated mouse genetic mapping panel, we demonstrate that four Hsa21-orthologous regions of mouse chromosome 16 contain dosage-sensitive genes that cause the DS craniofacial phenotype, and identify one of these causative genes as Dyrk1a. We show that the earliest and most severe defects in Dp1Tyb skulls are in bones of neural crest (NC) origin, and that mineralisation of the Dp1Tyb skull base synchondroses is aberrant. Furthermore, we show that increased dosage of Dyrk1a results in decreased NC cell proliferation and a decrease in size and cellularity of the NC-derived frontal bone primordia. Thus, DS craniofacial dysmorphology is caused by an increased dosage of Dyrk1a and at least three other genes.

A Comparison of Semilandmarking Approaches in the Analysis of Size and Shape

Often, few landmarks can be reliably identified in analyses of form variation and covariation. Thus, ‘semilandmarking’ algorithms have increasingly been applied to surfaces and curves. However, the locations of semilandmarks depend on the investigator’s choice of algorithm and their density. In consequence, to the extent that different semilandmarking approaches and densities result in different locations of semilandmarks, they can be expected to yield different results concerning patterns of variation and co-variation. The extent of such differences due to methodology is, as yet, unclear and often ignored. In this study, the performance of three landmark-driven semilandmarking approaches is assessed, using two different surface mesh datasets (ape crania and human heads) with different degrees of variation and complexity, by comparing the results of morphometric analyses. These approaches produce different semilandmark locations, which, in turn, lead to differences in statistical results, although the non-rigid semilandmarking approaches are consistent. Morphometric analyses using semilandmarks must be interpreted with due caution, recognising that error is inevitable and that results are approximations. Further work is needed to investigate the effects of using different landmark and semilandmark templates and to understand the limitations and advantages of different semilandmarking approaches.

Morphometric analysis of the size-adjusted linear dimensions of the skull landmarks revealed craniofacial dysmorphology in Mid1-cKO mice

BACKGROUND

The early craniofacial development is a highly coordinated process involving neural crest cell migration, proliferation, epithelial apoptosis, and epithelial-mesenchymal transition (EMT). Both genetic defects and environmental factors can affect these processes and result in orofacial clefts. Mutations in MID1 gene cause X-linked Opitz Syndrome (OS), which is a congenital malformation characterized by craniofacial defects including cleft lip/palate (CLP). Previous studies demonstrated impaired neurological structure and function in Mid1 knockout mice, while no CLP was observed. However, given the highly variable severities of the facial manifestations observed in OS patients within the same family carrying identical genetic defects, subtle craniofacial malformations in Mid1 knockout mice could be overlooked in these studies. Therefore, we propose that a detailed morphometric analysis should be necessary to reveal mild craniofacial dysmorphologies that reflect the similar developmental defects seen in OS patients.

RESULTS

In this research, morphometric study of the P0 male Mid1-cKO mice were performed using Procrustes superimposition as well as EMDA analysis of the size-adjusted three-dimensional coordinates of 105 skull landmarks, which were collected on the bone surface reconstructed using microcomputed tomographic images. Our results revealed the craniofacial deformation such as the increased dimension of the frontal and nasal bone in Mid1-cKO mice, in line with the most prominent facial features such as hypertelorism, prominent forehead, broad and/or high nasal bridge seen in OS patients.

CONCLUSION

 While been extensively used in evolutionary biology and anthropology in the last decades, geometric morphometric analysis was much less used in developmental biology. Given the high interspecies variances in facial anatomy, the work presented in this research suggested the advantages of morphometric analysis in characterizing animal models of craniofacial developmental defects to reveal phenotypic variations and the underlining pathogenesis.

Automated morphological phenotyping using learned shape descriptors and functional maps: A novel approach to geometric morphometrics

The methods of geometric morphometrics are commonly used to quantify morphology in a broad range of biological sciences. The application of these methods to large datasets is constrained by manual landmark placement limiting the number of landmarks and introducing observer bias. To move the field forward, we need to automate morphological phenotyping in ways that capture comprehensive representations of morphological variation with minimal observer bias. Here, we present Morphological Variation Quantifier (morphVQ), a shape analysis pipeline for quantifying, analyzing, and exploring shape variation in the functional domain. morphVQ uses descriptor learning to estimate the functional correspondence between whole triangular meshes in lieu of landmark configurations. With functional maps between pairs of specimens in a dataset we can analyze and explore shape variation. morphVQ uses Consistent ZoomOut refinement to improve these functional maps and produce a new representation of shape variation, area-based and conformal (angular) latent shape space differences (LSSDs). We compare this new representation of shape variation to shape variables obtained via manual digitization and auto3DGM, an existing approach to automated morphological phenotyping. We find that LSSDs compare favorably to modern 3DGM and auto3DGM while being more computationally efficient. By characterizing whole surfaces, our method incorporates more morphological detail in shape analysis. We can classify known biological groupings, such as Genus affiliation with comparable accuracy. The shape spaces produced by our method are similar to those produced by modern 3DGM and to auto3DGM, and distinctiveness functions derived from LSSDs show us how shape variation differs between groups. morphVQ can capture shape in an automated fashion while avoiding the limitations of manually digitized landmarks, and thus represents a novel and computationally efficient addition to the geometric morphometrics toolkit.

Green Tea Catechins Modulate Skeletal Development with Effects Dependent on Dose, Time, and Structure in a down Syndrome Mouse Model

Altered skeletal development in Down syndrome (DS) results in a brachycephalic skull, flattened face, shorter mandibular ramus, shorter limbs, and reduced bone mineral density (BMD). Our previous study showed that low doses of green tea extract enriched in epigallocatechin-3-gallate (GTE-EGCG), administered continuously from embryonic day 9 to postnatal day 29, reduced facial dysmorphologies in the Ts65Dn (TS) mouse model of DS, but high doses could exacerbate them. Here, we extended the analyses to other skeletal structures and systematically evaluated the effects of high and low doses of GTE-EGCG treatment over postnatal development in wild-type (WT) and TS mice using in vivo µCT and geometric morphometrics. TS mice developed shorter and wider faces, skulls, and mandibles, together with shorter and narrower humerus and scapula, and reduced BMD dynamically over time. Besides facial morphology, GTE-EGCG did not rescue any other skeletal phenotype in TS treated mice. In WT mice, GTE-EGCG significantly altered the shape of the skull and mandible, reduced the length and width of the long bones, and lowered the BMD. The disparate effects of GTE-EGCG depended on the dose, developmental timepoint, and anatomical structure analyzed, emphasizing the complex nature of DS and the need to further investigate the simultaneous effects of GTE-EGCG supplementation.

Thirty years of geometric morphometrics: Achievements, challenges, and the ongoing quest for biological meaningfulness

The foundations of geometric morphometrics were worked out about 30 years ago and have continually been refined and extended. What has remained as a central thrust and source of debate in the morphometrics community is the shared goal of meaningful biological inference through a tight connection between biological theory, measurement, multivariate biostatistics, and geometry. Here we review the building blocks of modern geometric morphometrics: the representation of organismal geometry by landmarks and semilandmarks, the computation of shape or form variables via superimposition, the visualization of statistical results as actual shapes or forms, the decomposition of shape variation into symmetric and asymmetric components and into different spatial scales, the interpretation of various geometries in shape or form space, and models of the association between shape or form and other variables, such as environmental, genetic, or behavioral data. We focus on recent developments and current methodological challenges, especially those arising from the increasing number of landmarks and semilandmarks, and emphasize the importance of thorough exploratory multivariate analyses rather than single scalar summary statistics. We outline promising directions for further research and for the evaluation of new developments, such as "landmark-free" approaches. To illustrate these methods, we analyze three-dimensional human face shape based on data from the Avon Longitudinal Study of Parents and Children (ALSPAC).

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 ).

Computational anatomy and geometric shape analysis enables analysis of complex craniofacial phenotypes in zebrafish

Due to the complexity of fish skulls, previous attempts to classify craniofacial phenotypes have relied on qualitative features or sparce 2D landmarks. In this work we aim to identify previously unknown 3D craniofacial phenotypes with a semiautomated pipeline in adult zebrafish mutants. We first estimate a synthetic 'normative' zebrafish template using MicroCT scans from a sample pool of wild-type animals using the Advanced Normalization Tools (ANTs). We apply a computational anatomy (CA) approach to quantify the phenotype of zebrafish with disruptions in bmp1a, a gene implicated in later skeletal development and whose human ortholog when disrupted is associated with Osteogenesis Imperfecta. Compared to controls, the bmp1a fish have larger otoliths, larger normalized centroid sizes, and exhibit shape differences concentrated around the operculum, anterior frontal, and posterior parietal bones. Moreover, bmp1a fish differ in the degree of asymmetry. Our CA approach offers a potential pipeline for high-throughput screening of complex fish craniofacial shape to discover novel phenotypes for which traditional landmarks are too sparce to detect. The current pipeline successfully identifies areas of variation in zebrafish mutants, which are an important model system for testing genome to phenome relationships in the study of development, evolution, and human diseases. This article has an associated First Person interview with the first author of the paper.

μMatch: 3D Shape Correspondence for Biological Image Data

Modern microscopy technologies allow imaging biological objects in 3D over a wide range of spatial and temporal scales, opening the way for a quantitative assessment of morphology. However, establishing a correspondence between objects to be compared, a first necessary step of most shape analysis workflows, remains challenging for soft-tissue objects without striking features allowing them to be landmarked. To address this issue, we introduce the μMatch 3D shape correspondence pipeline. μMatch implements a state-of-the-art correspondence algorithm initially developed for computer graphics and packages it in a streamlined pipeline including tools to carry out all steps from input data pre-processing to classical shape analysis routines. Importantly, μMatch does not require any landmarks on the object surface and establishes correspondence in a fully automated manner. Our open-source method is implemented in Python and can be used to process collections of objects described as triangular meshes. We quantitatively assess the validity of μMatch relying on a well-known benchmark dataset and further demonstrate its reliability by reproducing published results previously obtained through manual landmarking.

Mutations in Hcfc1 and Ronin result in an inborn error of cobalamin metabolism and ribosomopathy

Combined methylmalonic acidemia and homocystinuria (cblC) is the most common inborn error of intracellular cobalamin metabolism and due to mutations in Methylmalonic Aciduria type C and Homocystinuria (MMACHC). Recently, mutations in the transcriptional regulators HCFC1 and RONIN (THAP11) were shown to result in cellular phenocopies of cblC. Since HCFC1/RONIN jointly regulate MMACHC, patients with mutations in these factors suffer from reduced MMACHC expression and exhibit a cblC-like disease. However, additional de-regulated genes and the resulting pathophysiology is unknown. Therefore, we have generated mouse models of this disease. In addition to exhibiting loss of Mmachc, metabolic perturbations, and developmental defects previously observed in cblC, we uncovered reduced expression of target genes that encode ribosome protein subunits. We also identified specific phenotypes that we ascribe to deregulation of ribosome biogenesis impacting normal translation during development. These findings identify HCFC1/RONIN as transcriptional regulators of ribosome biogenesis during development and their mutation results in complex syndromes exhibiting aspects of both cblC and ribosomopathies.

Combined methylmalonic acidemia (MMA) and hyperhomocysteinemias are inborn errors of vitamin B12 metabolism, and mutations in the transcriptional regulators HCFC1 and RONIN (THAP11) underlie some forms of these disorders. Here the authors generated mouse models of a human syndrome due to mutations in RONIN (THAP11) and HCFC1, and show that this syndrome is both an inborn error of vitamin B12 metabolism and displays some features of ribosomopathy.

Comprehensive phenotypic analysis of the Dp1Tyb mouse strain reveals a broad range of Down syndrome-related phenotypes

Down syndrome (DS), trisomy 21, results in many complex phenotypes including cognitive deficits, heart defects and craniofacial alterations. Phenotypes arise from an extra copy of human chromosome 21 (Hsa21) genes. However, these dosage-sensitive causative genes remain unknown. Animal models enable identification of genes and pathological mechanisms. The Dp1Tyb mouse model of DS has an extra copy of 63% of Hsa21-orthologous mouse genes. In order to establish whether this model recapitulates DS phenotypes, we comprehensively phenotyped Dp1Tyb mice using 28 tests of different physiological systems and found that 468 out of 1800 parameters were significantly altered. We show that Dp1Tyb mice have wide-ranging DS-like phenotypes, including aberrant erythropoiesis and megakaryopoiesis, reduced bone density, craniofacial changes, altered cardiac function, a pre-diabetic state, and deficits in memory, locomotion, hearing and sleep. Thus, Dp1Tyb mice are an excellent model for investigating complex DS phenotype-genotype relationships for this common disorder.

The Intertwined Evolution and Development of Sutures and Cranial Morphology

Phenotypic variation across mammals is extensive and reflects their ecological diversification into a remarkable range of habitats on every continent and in every ocean. The skull performs many functions to enable each species to thrive within its unique ecological niche, from prey acquisition, feeding, sensory capture (supporting vision and hearing) to brain protection. Diversity of skull function is reflected by its complex and highly variable morphology. Cranial morphology can be quantified using geometric morphometric techniques to offer invaluable insights into evolutionary patterns, ecomorphology, development, taxonomy, and phylogenetics. Therefore, the skull is one of the best suited skeletal elements for developmental and evolutionary analyses. In contrast, less attention is dedicated to the fibrous sutural joints separating the cranial bones. Throughout postnatal craniofacial development, sutures function as sites of bone growth, accommodating expansion of a growing brain. As growth frontiers, cranial sutures are actively responsible for the size and shape of the cranial bones, with overall skull shape being altered by changes to both the level and time period of activity of a given cranial suture. In keeping with this, pathological premature closure of sutures postnatally causes profound misshaping of the skull (craniosynostosis). Beyond this crucial role, sutures also function postnatally to provide locomotive shock absorption, allow joint mobility during feeding, and, in later postnatal stages, suture fusion acts to protect the developed brain. All these sutural functions have a clear impact on overall cranial function, development and morphology, and highlight the importance that patterns of suture development have in shaping the diversity of cranial morphology across taxa. Here we focus on the mammalian cranial system and review the intrinsic relationship between suture development and morphology and cranial shape from an evolutionary developmental biology perspective, with a view to understanding the influence of sutures on evolutionary diversity. Future work integrating suture development into a comparative evolutionary framework will be instrumental to understanding how developmental mechanisms shaping sutures ultimately influence evolutionary diversity.