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.

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.

Morphological simulation tests the limits on phenotype discovery in 3D image analysis.

In the past few decades, advances in 3D imaging have created new opportunities for reverse genetic screens. Rapidly growing datasets of 3D images of genetic knockouts require high-throughput, automated computational approaches for identifying and characterizing new phenotypes. However, exploratory, discovery-oriented image analysis pipelines used to discover these phenotypes can be difficult to validate because, by their nature, the expected outcome is not known a priori . Introducing known morphological variation through simulation can help distinguish between real phenotypic differences and random variation; elucidate the effects of sample size; and test the sensitivity and reproducibility of morphometric analyses. Here we present a novel approach for 3D morphological simulation that uses open-source, open-access tools available in 3D Slicer, SlicerMorph, and Advanced Normalization Tools in R (ANTsR). While we focus on diffusible-iodine contrast-enhanced micro-CT (diceCT) images, this approach can be used on any volumetric image. We then use our simulated datasets to test whether tensor-based morphometry (TBM) can recover our introduced differences; to test how effect size and sample size affect detectability; and to determine the reproducibility of our results. In our approach to morphological simulation, we first generate a simulated deformation based on a reference image and then propagate this deformation to subjects using inverse transforms obtained from the registration of subjects to the reference. This produces a new dataset with a shifted population mean while retaining individual variability because each sample deforms more or less based on how different or similar it is from the reference. TBM is a widely-used technique that statistically compares local volume differences associated with local deformations. Our results showed that TBM recovered our introduced morphological differences, but that detectability was dependent on the effect size, the sample size, and the region of interest (ROI) included in the analysis. Detectability of subtle phenotypes can be improved both by increasing the sample size and by limiting analyses to specific body regions. However, it is not always feasible to increase sample sizes in screens of essential genes. Therefore, methodical use of ROIs is a promising way to increase the power of TBM to detect subtle phenotypes. Generating known morphological variation through simulation has broad applicability in developmental, evolutionary, and biomedical morphometrics and is a useful way to distinguish between a failure to detect morphological difference and a true lack of morphological difference. Morphological simulation can also be applied to AI-based supervised learning to augment datasets and overcome dataset limitations.

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.