Leveraging Descriptor Learning and Functional Map-based Shape Matching for Automatic Landmark Acquisition.

Geometric morphometrics is widely employed across the biological sciences for the quantification of morphological traits. However, the scalability of these methods to large datasets is hampered by the requisite placement of landmarks, which can be laborious and time consuming if done manually. Additionally, the selected landmarks embody a particular hypothesis regarding the critical geometry pertinent to the biological inquiry at hand. Modifying this hypothesis lacks flexibility, necessitating the acquisition of an entirely new set of landmarks on the entire dataset to reflect any theoretical adjustments. In our research, we investigate the precision and accuracy of landmarks derived from the comprehensive set of functional correspondences acquired through the functional map framework of geometry processing. We use a deep functional map network to learn shape descriptors that effectively yield functional map-based and point-to-point correspondences between the specimens in our dataset. We then interrogate these maps to identify corresponding landmarks given manually placed landmarks from the entire dataset. We assess our method by automating the landmarking process on a dataset comprising mandibles from various rodent species, comparing its efficacy against MALPACA, a cutting-edge technique for automatic landmark placement. Compared to MALPACA, our model is notably faster and maintains competitive accuracy. The Root Mean Square Error (RMSE) analysis reveals that while MALPACA generally exhibits the lowest RMSE, our models perform comparably, especially with smaller training datasets, suggesting strong generalizability. Visual evaluations confirm the precision of our landmark placements, with deviations remaining within an acceptable range. These findings underscore the potential of unsupervised learning models in anatomical landmark placement, providing a viable and efficient alternative to traditional methods.

An Open-Source Photogrammetry Workflow for Reconstructing 3D Models.

Acquiring accurate 3D biological models efficiently and economically is important for morphological data collection and analysis in organismal biology. In recent years, structure-from-motion (SFM) photogrammetry has become increasingly popular in biological research due to its flexibility and being relatively low cost. SFM photogrammetry registers 2D images for reconstructing camera positions as the basis for 3D modeling and texturing. However, most studies of organismal biology still relied on commercial software to reconstruct the 3D model from photographs, which impeded the adoption of this workflow in our field due the blocking issues such as cost and affordability. Also, prior investigations in photogrammetry did not sufficiently assess the geometric accuracy of the models reconstructed. Consequently, this study has two goals. First, we presented an affordable and highly flexible SFM photogrammetry pipeline based on the open-source package OpenDroneMap (ODM) and its user interface WebODM. Second, we assessed the geometric accuracy of the photogrammetric models acquired from the ODM pipeline by comparing them to the models acquired via microCT scanning, the de facto method to image skeleton. Our sample comprised 15 Aplodontia rufa (mountain beaver) skulls. Using models derived from microCT scans of the samples as reference, our results showed that the geometry of the models derived from ODM was sufficiently accurate for gross metric and morphometric analysis as the measurement errors are usually around or below 2%, and morphometric analysis captured consistent patterns of shape variations in both modalities. However, subtle but distinct differences between the photogrammetric and microCT-derived 3D models could affect the landmark placement, which in return affected the downstream shape analysis, especially when the variance within a sample is relatively small. At the minimum, we strongly advise not combining 3D models derived from these two modalities for geometric morphometric analysis. Our findings can be indictive of similar issues in other SFM photogrammetry tools since the underlying pipelines are similar. We recommend that users run a pilot test of geometric accuracy before using photogrammetric models for morphometric analysis. For the research community, we provide detailed guidance on using our pipeline for building 3D models from photographs.

Examining craniofacial variation among crispant and mutant zebrafish models of human skeletal diseases.

Genetic diseases affecting the skeletal system present with a wide range of symptoms that make diagnosis and treatment difficult. Genome-wide association and sequencing studies have identified genes linked to human skeletal diseases. Gene editing of zebrafish models allows researchers to further examine the link between genotype and phenotype, with the long-term goal of improving diagnosis and treatment. While current automated tools enable rapid and in-depth phenotyping of the axial skeleton, characterizing the effects of mutations on the craniofacial skeleton has been more challenging. The objective of this study was to evaluate a semi-automated screening tool can be used to quantify craniofacial variations in zebrafish models using four genes that have been associated with human skeletal diseases (meox1, plod2, sost, and wnt16) as test cases. We used traditional landmarks to ground truth our dataset and pseudolandmarks to quantify variation across the 3D cranial skeleton between the groups (somatic crispant, germline mutant, and control fish). The proposed pipeline identified variation between the crispant or mutant fish and control fish for four genes. Variation in phenotypes parallel human craniofacial symptoms for two of the four genes tested. This study demonstrates the potential as well as the limitations of our pipeline as a screening tool to examine multi-dimensional phenotypes associated with the zebrafish craniofacial skeleton.

Deep learning enabled multi-organ segmentation of mouse embryos.

The International Mouse Phenotyping Consortium (IMPC) has generated a large repository of three-dimensional (3D) imaging data from mouse embryos, providing a rich resource for investigating phenotype/genotype interactions. While the data is freely available, the computing resources and human effort required to segment these images for analysis of individual structures can create a significant hurdle for research. In this paper, we present an open source, deep learning-enabled tool, Mouse Embryo Multi-Organ Segmentation (MEMOS), that estimates a segmentation of 50 anatomical structures with a support for manually reviewing, editing, and analyzing the estimated segmentation in a single application. MEMOS is implemented as an extension on the 3D Slicer platform and is designed to be accessible to researchers without coding experience. We validate the performance of MEMOS-generated segmentations through comparison to state-of-the-art atlas-based segmentation and quantification of previously reported anatomical abnormalities in a Cbx4 knockout strain. This article has an associated First Person interview with the first author of the paper.

Automated landmarking via multiple templates.

Manually collecting landmarks for quantifying complex morphological phenotypes can be laborious and subject to intra and interobserver errors. However, most automated landmarking methods for efficiency and consistency fall short of landmarking highly variable samples due to the bias introduced by the use of a single template. We introduce a fast and open source automated landmarking pipeline (MALPACA) that utilizes multiple templates for accommodating large-scale variations. We also introduce a K-means method of choosing the templates that can be used in conjunction with MALPACA, when no prior information for selecting templates is available. Our results confirm that MALPACA significantly outperforms single-template methods in landmarking both single and multi-species samples. K-means based template selection can also avoid choosing the worst set of templates when compared to random template selection. We further offer an example of post-hoc quality check for each individual template for further refinement. In summary, MALPACA is an efficient and reproducible method that can accommodate large morphological variability, such as those commonly found in evolutionary studies. To support the research community, we have developed open-source and user-friendly software tools for performing K-means multi-templates selection and MALPACA.

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.

Automated atlas-based segmentation for skull base surgical planning.

PURPOSE: Computational surgical planning tools could help develop novel skull base surgical approaches that improve safety and patient outcomes. This defines a need for automated skull base segmentation to improve the usability of surgical planning software. The objective of this work was to design and validate an algorithm for atlas-based automated segmentation of skull base structures in individual image sets for skull base surgical planning. METHODS: Advanced Normalization Tools software was used to construct a synthetic CT template from 6 subjects, and skull base structures were manually segmented to create a reference atlas. Landmark registration followed by Elastix deformable registration was applied to the template to register it to each of the 30 trusted reference image sets. Dice coefficient, average Hausdorff distance, and clinical usability scoring were used to compare the atlas segmentations to those of the trusted reference image sets. RESULTS: The mean for average Hausdorff distance for all structures was less than 2 mm (mean for 95th percentile Hausdorff distance was less than 5 mm). For structures greater than 2.5 mL in volume, the average Dice coefficient was 0.73 (range 0.59-0.82), and for structures less than 2.5 mL in volume the Dice coefficient was less than 0.7. The usability scoring survey was completed by three experts, and all structures met the criteria for acceptable effort except for the foramen spinosum, rotundum, and carotid artery, which required more than minor corrections. CONCLUSION: Currently available open-source algorithms, such as the Elastix deformable algorithm, can be used for automated atlas-based segmentation of skull base structures with acceptable clinical accuracy and minimal corrections with the use of the proposed atlas. The first publicly available CT template and anterior skull base segmentation atlas being released (available at this link: http://hdl.handle.net/1773/46259 ) with this paper will allow for general use of automated atlas-based segmentation of the skull base.

Comparing semi-landmarking approaches for analyzing three-dimensional cranial morphology.

OBJECTIVES: Increased use of three-dimensional (3D) imaging data has led to a need for methods capable of capturing rich shape descriptions. Semi-landmarks have been demonstrated to increase shape information but placement in 3D can be time consuming, computationally expensive, or may introduce artifacts. This study implements and compares three strategies to more densely sample a 3D image surface. MATERIALS AND METHODS: Three dense sampling strategies: patch, patch-thin-plate spline (TPS), and pseudo-landmark sampling, are implemented to analyze skulls from three species of great apes. To evaluate the shape information added by each strategy, the semi or pseudo-landmarks are used to estimate a transform between an individual and the population average template. The average mean root squared error between the transformed mesh and the template is used to quantify the success of the transform. RESULTS: The landmark sets generated by each method result in estimates of the template that on average were comparable or exceeded the accuracy of using manual landmarks alone. The patch method demonstrates the most sensitivity to noise and missing data, resulting in outliers with large deviations in the mean shape estimates. Patch-TPS and pseudo-landmarking provide more robust performance in the presence of noise and variability in the dataset. CONCLUSIONS: Each landmarking strategy was capable of producing shape estimations of the population average templates that were generally comparable to manual landmarks alone while greatly increasing the density of the shape information. This study highlights the potential trade-offs between correspondence of the semi-landmark points, consistent point spacing, sample coverage, repeatability, and computational time.

ALPACA: A fast and accurate computer vision approach for automated landmarking of three-dimensional biological structures.

Landmark-based geometric morphometrics has emerged as an essential discipline for the quantitative analysis of size and shape in ecology and evolution. With the ever-increasing density of digitized landmarks, the possible development of a fully automated method of landmark placement has attracted considerable attention. Despite the recent progress in image registration techniques, which could provide a pathway to automation, three-dimensional (3D) morphometric data are still mainly gathered by trained experts. For the most part, the large infrastructure requirements necessary to perform image-based registration, together with its system specificity and its overall speed, have prevented its wide dissemination.Here, we propose and implement a general and lightweight point cloud-based approach to automatically collect high-dimensional landmark data in 3D surfaces (Automated Landmarking through Point cloud Alignment and Correspondence Analysis). Our framework possesses several advantages compared with image-based approaches. First, it presents comparable landmarking accuracy, despite relying on a single, random reference specimen and much sparser sampling of the structure's surface. Second, it can be efficiently run on consumer-grade personal computers. Finally, it is general and can be applied at the intraspecific level to any biological structure of interest, regardless of whether anatomical atlases are available.Our validation procedures indicate that the method can recover intraspecific patterns of morphological variation that are largely comparable to those obtained by manual digitization, indicating that the use of an automated landmarking approach should not result in different conclusions regarding the nature of multivariate patterns of morphological variation.The proposed point cloud-based approach has the potential to increase the scale and reproducibility of morphometrics research. To allow ALPACA to be used out-of-the-box by users with no prior programming experience, we implemented it as a SlicerMorph module. SlicerMorph is an extension that enables geometric morphometrics data collection and 3D specimen analysis within the open-source 3D Slicer biomedical visualization ecosystem. We expect that convenient access to this platform will make ALPACA broadly applicable within ecology and evolution.

A feasibility study of OCT for anatomical and vascular phenotyping of mouse embryo.

The embryo phenotyping of genetic murine model is invaluable when investigating functions of genes underlying embryonic development and birth defect. Although traditional imaging technologies such as ultrasound are very useful for evaluating phenotype of murine embryos, the use of advanced techniques for phenotyping is desirable to obtain more information from genetic research. This letter tests the feasibility of optical coherence tomography (OCT) as a high-throughput phenotyping tool for murine embryos. Three-dimensional OCT imaging is performed for live and cleared mouse embryos in the late developmental stage (embryonic day 17.5). By using a dynamic focusing method and OCT angiography (OCTA) approach, our OCT imaging of the embryo exhibits rapid and clean visualization of organ structures deeper than 5 mm and complex microvasculature of perfused blood vessels in the murine embryonic body. This demonstration suggests that OCT imaging can be useful for comprehensively assessing embryo anatomy and angiography of genetically engineered mice.

Cranial growth in isolated sagittal craniosynostosis compared with normal growth in the first 6 months of age.

Sagittal craniosynostosis (SCS), the most common type of premature perinatal cranial suture fusion, results in abnormal head shape that requires extensive surgery to correct. It is important to find objective and repeatable measures of severity and surgical outcome to examine the effect of timing and technique on different SCS surgeries. The purpose of this study was to develop statistical models of infant (0-6 months old) skull growth in both normative and SCS subjects (prior to surgery). Our goal was to apply these models to the assessment of differences between these two groups in overall post-natal growth patterns and sutural growth rates as a first step to develop methods for predictive models of surgical outcome. We identified 81 patients with isolated, non-syndromic SCS from Seattle Children's Craniofacial Center patient database who had a preoperative CT exam before the age of 6 months. As a control group, we identified 117 CT exams without any craniofacial abnormalities or bone fractures in the same age group. We first created population-level templates from the CT images of the SCS and normal groups. All CT images from both groups, as well as the canonical templates of both cohorts, were annotated with anatomical landmarks, which were used in a growth model that predicted the locations of these landmarks at a given age based on each population. Using the template images and the landmark positions predicted by the growth models, we created 3D meshes for each week of age up to 6 months for both populations. To analyze the growth patterns at the suture sites, we annotated both templates with additional semi-landmarks equally spaced along the metopic, coronal, sagittal and lambdoidal cranial sutures. By transferring these semi-landmarks to meshes produced from the growth model, we measured the displacement of the bone borders and suture closure rates. We found that the growth at the metopic and coronal sutures were more rapid in the SCS cohort than in the normal cohort. The antero-posterior displacement of the semi-landmarks also indicated a more rapid growth in the sagittal plane in the SCS model than in the normal model. Statistical templates and geometric morphometrics are promising tools for understanding the growth patterns in normal and synostotic populations and to produce objective and reproducible measurements of severity and outcome. Our study is the first of its kind to quantify the bone growth for the first 6 months of life in both normal and sagittal synostosis patients.

Geometric morphometrics reveal altered corpus callosum shape in pyridoxine-dependent epilepsy.

OBJECTIVE: To evaluate the features and maturational changes in overall callosal shape in patients with pyridoxine-dependent epilepsy (PDE). METHODS: Measurements were conducted through landmark-based geometric morphometrics applied on cerebral MRIs of patients with PDE and age-matched control subjects. The outline of the corpus callosum was manually traced in the midsagittal plane. Three hundred semi-landmarks along the outline were collected and underwent statistical generalized Procrustes analysis. An allometric regression was applied to evaluate the callosal shape due to growth over time. RESULTS: Thirty-eight patients with PDE and 38 age- and sex-matched control subjects were included. Mean age at the time of the MRI in the patient group was 9.3 years (median 6.3 years, range 0.01-48 years). Significant differences (p < 0.01) in the mean callosal shape between patients and controls were found. The allometric regression model revealed significant shape variations (p < 0.01) between the 2 study groups across the developmental course after controlling for the effect of callosal size on shape. This latter effect turned out to be significant as well (p < 0.001). CONCLUSIONS: Patients with PDE show an altered callosal shape and variations in callosal ontogeny, which are likely secondary to the underlying genetic defect with abnormal function of antiquitin, the product of the ALDH7A1 gene.

Mapping genetic variants for cranial vault shape in humans.

The shape of the cranial vault, a region comprising interlocking flat bones surrounding the cerebral cortex, varies considerably in humans. Strongly influenced by brain size and shape, cranial vault morphology has both clinical and evolutionary relevance. However, little is known about the genetic basis of normal vault shape in humans. We performed a genome-wide association study (GWAS) on three vault measures (maximum cranial width [MCW], maximum cranial length [MCL], and cephalic index [CI]) in a sample of 4419 healthy individuals of European ancestry. All measures were adjusted by sex, age, and body size, then tested for association with genetic variants spanning the genome. GWAS results for the two cohorts were combined via meta-analysis. Significant associations were observed at two loci: 15p11.2 (lead SNP rs2924767, p = 2.107 × 10-8) for MCW and 17q11.2 (lead SNP rs72841279, p = 5.29 × 10-9) for MCL. Additionally, 32 suggestive loci (p < 5x10-6) were observed. Several candidate genes were located in these loci, such as NLK, MEF2A, SOX9 and SOX11. Genome-wide linkage analysis of cranial vault shape in mice (N = 433) was performed to follow-up the associated candidate loci identified in the human GWAS. Two loci, 17q11.2 (c11.loc44 in mice) and 17q25.1 (c11.loc74 in mice), associated with cranial vault size in humans, were also linked with cranial vault size in mice (LOD scores: 3.37 and 3.79 respectively). These results provide further insight into genetic pathways and mechanisms underlying normal variation in human craniofacial morphology.

Genetic mapping of molar size relations identifies inhibitory locus for third molars in mice.

Molar size in Mammals shows considerable disparity and exhibits variation similar to that predicted by the Inhibitory Cascade model. The importance of such developmental systems in favoring evolutionary trajectories is also underlined by the fact that this model can predict macroevolutionary patterns. Using backcross mice, we mapped QTL for molar sizes controlling for their sequential development. Genetic controls for upper and lower molars appear somewhat similar, and regions containing genes implied in dental defects drive this variation. We mapped three relationship QTLs (rQTL) modifying the control of the mesial molars on the focal third molar. These regions overlap Shh, Sostdc1, and Fst genes, which have pervasive roles in development and should be buffered against new variation. It has theoretically been shown that rQTL produces new variation channeled in the direction of adaptive changes. Our results provide evidence that evolutionary/disease patterns of tooth size variation could result from such a non-random generating process.

Correction: Skeleton of an unusual, cat-sized marsupial relative (Metatheria: Marsupialiformes) from the middle Eocene (Lutetian: 44-43 million years ago) of Turkey.

[This corrects the article DOI: 10.1371/journal.pone.0181712.].

Skeleton of an unusual, cat-sized marsupial relative (Metatheria: Marsupialiformes) from the middle Eocene (Lutetian: 44-43 million years ago) of Turkey.

We describe a near-complete, three-dimensionally preserved skeleton of a metatherian (relative of modern marsupials) from the middle Eocene (Lutetian: 44-43 million years ago) Lülük member of the Uzunçarsidere Formation, central Turkey. With an estimated body mass of 3-4 kg, about the size of a domestic cat (Felis catus) or spotted quoll (Dasyurus maculatus), it is an order of magnitude larger than the largest fossil metatherians previously known from the Cenozoic of the northern hemisphere. This new taxon is characterised by large, broad third premolars that probably represent adaptations for hard object feeding (durophagy), and its craniodental morphology suggests the capacity to generate high bite forces. Qualitative and quantitative functional analyses of its postcranial skeleton indicate that it was probably scansorial and relatively agile, perhaps broadly similar in locomotor mode to the spotted quoll, but with a greater capacity for climbing and grasping. Bayesian phylogenetic analysis of a total evidence dataset comprising 259 morphological characters and 9kb of DNA sequence data from five nuclear protein-coding genes, using both undated and "tip-and-node dating" approaches, place the new taxon outside the marsupial crown-clade, but within the clade Marsupialiformes. It demonstrates that at least one metatherian lineage evolved to occupy the small-medium, meso- or hypo-carnivore niche in the northern hemisphere during the early Cenozoic, at a time when there were numerous eutherians (placentals and their fossil relatives) filling similar niches. However, the known mammal fauna from Uzunçarsidere Formation appears highly endemic, and geological evidence suggests that this region of Turkey was an island for at least part of the early Cenozoic, and so the new taxon may have evolved in isolation from potential eutherian competitors. Nevertheless, the new taxon reveals previously unsuspected ecomorphological disparity among northern hemisphere metatherians during the first half of the Cenozoic.

A population level atlas of Mus musculus craniofacial skeleton and automated image-based shape analysis.

Laboratory mice are staples for evo/devo and genetics studies. Inbred strains provide a uniform genetic background to manipulate and understand gene-environment interactions, while their crosses have been instrumental in studies of genetic architecture, integration and modularity, and mapping of complex biological traits. Recently, there have been multiple large-scale studies of laboratory mice to further our understanding of the developmental basis, evolution, and genetic control of shape variation in the craniofacial skeleton (i.e. skull and mandible). These experiments typically use micro-computed tomography (micro-CT) to capture the craniofacial phenotype in 3D and rely on manually annotated anatomical landmarks to conduct statistical shape analysis. Although the common choice for imaging modality and phenotyping provides the potential for collaborative research for even larger studies with more statistical power, the investigator (or lab-specific) nature of the data collection hampers these efforts. Investigators are rightly concerned that subtle differences in how anatomical landmarks were recorded will create systematic bias between studies that will eventually influence scientific findings. Even if researchers are willing to repeat landmark annotation on a combined dataset, different lab practices and software choices may create obstacles for standardization beyond the underlying imaging data. Here, we propose a freely available analysis system that could assist in the standardization of micro-CT studies in the mouse. Our proposal uses best practices developed in biomedical imaging and takes advantage of existing open-source software and imaging formats. Our first contribution is the creation of a synthetic template for the adult mouse craniofacial skeleton from 25 inbred strains and five F1 crosses that are widely used in biological research. The template contains a fully segmented cranium, left and right hemi-mandibles, endocranial space, and the first few cervical vertebrae. We have been using this template in our lab to segment and isolate cranial structures in an automated fashion from a mixed population of mice, including craniofacial mutants, aged 4-12.5 weeks. As a secondary contribution, we demonstrate an application of nearly automated shape analysis, using symmetric diffeomorphic image registration. This approach, which we call diGPA, closely approximates the popular generalized Procrustes analysis (GPA) but negates the collection of anatomical landmarks. We achieve our goals by using the open-source advanced normalization tools (ANT) image quantification library, as well as its associated R library (ANTsR) for statistical image analysis. Finally, we make a plea to investigators to commit to using open imaging standards and software in their labs to the extent possible to increase the potential for data exchange and improve the reproducibility of findings. Future work will incorporate more anatomical detail (such as individual cranial bones, turbinals, dentition, middle ear ossicles) and more diversity into the template.

Mutations in CRADD Result in Reduced Caspase-2-Mediated Neuronal Apoptosis and Cause Megalencephaly with a Rare Lissencephaly Variant.

Lissencephaly is a malformation of cortical development typically caused by deficient neuronal migration resulting in cortical thickening and reduced gyration. Here we describe a "thin" lissencephaly (TLIS) variant characterized by megalencephaly, frontal predominant pachygyria, intellectual disability, and seizures. Trio-based whole-exome sequencing and targeted re-sequencing identified recessive mutations of CRADD in six individuals with TLIS from four unrelated families of diverse ethnic backgrounds. CRADD (also known as RAIDD) is a death-domain-containing adaptor protein that oligomerizes with PIDD and caspase-2 to initiate apoptosis. TLIS variants cluster in the CRADD death domain, a platform for interaction with other death-domain-containing proteins including PIDD. Although caspase-2 is expressed in the developing mammalian brain, little is known about its role in cortical development. CRADD/caspase-2 signaling is implicated in neurotrophic factor withdrawal- and amyloid-ß-induced dendritic spine collapse and neuronal apoptosis, suggesting a role in cortical sculpting and plasticity. TLIS-associated CRADD variants do not disrupt interactions with caspase-2 or PIDD in co-immunoprecipitation assays, but still abolish CRADD's ability to activate caspase-2, resulting in reduced neuronal apoptosis in vitro. Homozygous Cradd knockout mice display megalencephaly and seizures without obvious defects in cortical lamination, supporting a role for CRADD/caspase-2 signaling in mammalian brain development. Megalencephaly and lissencephaly associated with defective programmed cell death from loss of CRADD function in humans implicate reduced apoptosis as an important pathophysiological mechanism of cortical malformation. Our data suggest that CRADD/caspase-2 signaling is critical for normal gyration of the developing human neocortex and for normal cognitive ability.

Postnatal Development of the Craniofacial Skeleton in Male C57BL/6J Mice.

C57BL/6J is one of the most commonly used inbred mouse strains in biomedical research, including studies of craniofacial development and teratogenic studies of craniofacial malformation. The current study quantitatively assessed the development of the skull in male C57BL/6J mice by using high-resolution 3D imaging of 55 landmarks from 48 male mice over 10 developmental time points from postnatal day 0 to 90. The growth of the skull plateaued at approximately postnatal day 60, and the shape of the skull did not change markedly thereafter. The amount of asymmetry in the craniofacial skeleton seemed to peak at birth, but considerable variation persisted in all age groups. For C57BL/6J male mice, postnatal day 60 is the earliest time point at which the skull achieves its adult shape and proportions. In addition, C57BL/6J male mice appear to have an inherent susceptibility to craniofacial malformation.

Does 3D Phenotyping Yield Substantial Insights in the Genetics of the Mouse Mandible Shape?

We describe the application of high-resolution 3D microcomputed tomography, together with 3D landmarks and geometric morphometrics, to validate and further improve previous quantitative genetic studies that reported QTL responsible for variation in the mandible shape of laboratory mice using a new backcross between C57BL/6J and A/J inbred strains. Despite the increasing availability of 3D imaging techniques, artificial flattening of the mandible by 2D imaging techniques seems at first an acceptable compromise for large-scale phenotyping protocols, thanks to an abundance of low-cost digital imaging systems such as microscopes or digital cameras. We evaluated the gain of information from considering explicitly this additional third dimension, and also from capturing variation on the bone surface where no precise anatomical landmark can be marked. Multivariate QTL mapping conducted with different landmark configurations (2D vs. 3D; manual vs. semilandmarks) broadly agreed with the findings of previous studies. Significantly more QTL (23) were identified and more precisely mapped when the mandible shape was captured with a large set of semilandmarks coupled with manual landmarks. It appears that finer phenotypic characterization of the mandibular shape with 3D landmarks, along with higher density genotyping, yields better insights into the genetic architecture of mandibular development. Most of the main variation is, nonetheless, preferentially embedded in the natural 2D plane of the hemi-mandible, reinforcing the results of earlier influential investigations.