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.

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.

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.

Analysis of facial skeletal asymmetry during foetal development using µCT imaging.

OBJECTIVES: Asymmetry has been noted in the human craniofacial region in several pathological conditional and growth abnormalities, often with a directional predilection. Physiological asymmetry has also been reported in normal adults and adolescents, with certain regions of the cranioskeleton, such as the mandible, displaying prevalent asymmetry. However, the timing at which such asymmetries arise has not been evaluated. The objectives of this study were to assess the degree of asymmetry in facial bones during the foetal stages of human development. MATERIAL AND METHODS: Twenty-one preserved conceptuses from the Congenital Anomaly Research Center at Kyoto University, between ages 15 and 20 weeks of gestation, were studied using high-resolution µCT imaging. Asymmetry analysis was performed on digitally segmented facial bone pairs, using geometric morphometric (GM) approaches as well as adapted deformation-based asymmetry (DBA) methods. RESULTS: GM analysis revealed that the developing facial bones display statistically significant fluctuating and directional asymmetry. DBA methods suggest that the magnitude of asymmetry in facial bones is low and does not appear to be correlated to the estimate of overall size of conceptus. Additionally, the patterns of asymmetry are highly variable between individual specimens. CONCLUSIONS: The developing foetal facial skeleton displays variable patterns of low magnitude asymmetry. GM and DBA methods offer unique advantages to assess facial asymmetry quantitatively and qualitatively.

Associations Between Genetic Data and Quantitative Assessment of Normal Facial Asymmetry.

Human facial asymmetry is due to a complex interaction of genetic and environmental factors. To identify genetic influences on facial asymmetry, we developed a method for automated scoring that summarizes local morphology features and their spatial distribution. A genome-wide association study using asymmetry scores from two local symmetry features was conducted and significant genetic associations were identified for one asymmetry feature, including genes thought to play a role in craniofacial disorders and development: NFATC1, SOX5, NBAS, and TCF7L1. These results provide evidence that normal variation in facial asymmetry may be impacted by common genetic variants and further motivate the development of automated summaries of complex phenotypes.

A distal 594†bp ECR specifies Hmx1 expression in pinna and lateral facial morphogenesis and is regulated by the Hox-Pbx-Meis complex.

Hmx1 encodes a homeodomain transcription factor expressed in the developing lateral craniofacial mesenchyme, retina and sensory ganglia. Mutation or mis-regulation of Hmx1 underlies malformations of the eye and external ear in multiple species. Deletion or insertional duplication of an evolutionarily conserved region (ECR) downstream of Hmx1 has recently been described in rat and cow, respectively. Here, we demonstrate that the impact of Hmx1 loss is greater than previously appreciated, with a variety of lateral cranioskeletal defects, auriculofacial nerve deficits, and duplication of the caudal region of the external ear. Using a transgenic approach, we demonstrate that a 594 bp sequence encompassing the ECR recapitulates specific aspects of the endogenous Hmx1 lateral facial expression pattern. Moreover, we show that Hoxa2, Meis and Pbx proteins act cooperatively on the ECR, via a core 32 bp sequence, to regulate Hmx1 expression. These studies highlight the conserved role for Hmx1 in BA2-derived tissues and provide an entry point for improved understanding of the causes of the frequent lateral facial birth defects in humans.