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Yuan M, Goovaerts S, Vanneste M, Matthews H, Hoskens H, Richmond S, Klein OD, Spritz RA, Hallgrimsson B, Walsh S, Shriver MD, Shaffer JR, Weinberg SM, Peeters H, Claes P. Mapping genes for human face shape: exploration of univariate phenotyping strategies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597731. [PMID: 38895298 PMCID: PMC11185724 DOI: 10.1101/2024.06.06.597731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits. Author Summary Advancements linking variation in the human genome to phenotypes have rapidly evolved in recent decades and have revealed that most human traits are influenced by genetic variants to at least some degree. While many traits, such as stature, are straightforward to acquire and investigate, the multivariate and multipartite nature of facial shape makes quantification more challenging. In this study, we compared the impact of different facial phenotyping approaches on gene mapping outcomes. Our findings suggest that the choice of facial phenotyping method has an impact on apparent trait heritability and the ability to detect genetic association signals. These results offer valuable insights into the importance of phenotyping in genetic investigations, especially when dealing with highly complex morphological traits.
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Nagawa K, Inoue K, Hara Y, Shimizu H, Tsuchihashi S, Matsuura K, Kozawa E, Sugita N, Niitsu M. Three-dimensional magnetic resonance imaging-based statistical shape analysis and machine learning-based prediction of patellofemoral instability. Sci Rep 2024; 14:11390. [PMID: 38762569 PMCID: PMC11102474 DOI: 10.1038/s41598-024-62143-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 05/14/2024] [Indexed: 05/20/2024] Open
Abstract
This study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. Twenty (19 patients) and 31 MRI scans (30 patients) of femurs with PFI and normal femurs, respectively, were used. Bone and cartilage segmentation of the distal femurs was performed and subsequently converted into 3D reconstructed models. The pointwise distance map showed anterior elevation of the trochlea, particularly at the central floor of the proximal trochlea, in the PFI models compared with the normal models. Principal component analysis examined shape variations in the PFI group, and several principal components exhibited shape variations in the trochlear floor and intercondylar width. Multivariate analysis showed that these shape components were significantly correlated with the PFI/non-PFI distinction after adjusting for age and sex. Our ML-based prediction model for PFI achieved a strong predictive performance with an accuracy of 0.909 ± 0.015, and an area under the curve of 0.939 ± 0.009 when using a support vector machine with a linear kernel. This study demonstrated that 3D MRI-based SSA can realistically visualize statistical results on surface models and may facilitate the understanding of complex shape features.
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Affiliation(s)
- Keita Nagawa
- Department of Radiology, Saitama Medical University, 38 Morohongou, Moroyama-Machi, Iruma-Gun, Saitama, Japan.
| | - Kaiji Inoue
- Department of Radiology, Saitama Medical University, 38 Morohongou, Moroyama-Machi, Iruma-Gun, Saitama, Japan.
| | - Yuki Hara
- Department of Radiology, Saitama Medical University, 38 Morohongou, Moroyama-Machi, Iruma-Gun, Saitama, Japan
| | - Hirokazu Shimizu
- Department of Radiology, Saitama Medical University, 38 Morohongou, Moroyama-Machi, Iruma-Gun, Saitama, Japan
| | - Saki Tsuchihashi
- Department of Radiology, Saitama Medical University, 38 Morohongou, Moroyama-Machi, Iruma-Gun, Saitama, Japan
| | - Koichiro Matsuura
- Department of Radiology, Saitama Medical University, 38 Morohongou, Moroyama-Machi, Iruma-Gun, Saitama, Japan
| | - Eito Kozawa
- Department of Radiology, Saitama Medical University, 38 Morohongou, Moroyama-Machi, Iruma-Gun, Saitama, Japan
| | - Naoki Sugita
- Department of Orthopedics, Saitama Medical University, 38 Morohongou, Moroyama-Machi, Iruma-Gun, Saitama, Japan
| | - Mamoru Niitsu
- Department of Radiology, Saitama Medical University, 38 Morohongou, Moroyama-Machi, Iruma-Gun, Saitama, Japan
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Imirzian N, Püffel F, Roces F, Labonte D. Large deformation diffeomorphic mapping of 3D shape variation reveals two distinct mandible and head capsule morphs in Atta vollenweideri leaf-cutter worker ants. Ecol Evol 2024; 14:e11236. [PMID: 38633523 PMCID: PMC11021802 DOI: 10.1002/ece3.11236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 02/21/2024] [Accepted: 03/15/2024] [Indexed: 04/19/2024] Open
Abstract
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.
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Affiliation(s)
| | | | - Flavio Roces
- Department of Behavioural Physiology and SociobiologyBiocenter, University of WürzburgWürzburgGermany
| | - David Labonte
- Department of BioengineeringImperial College LondonLondonUK
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Richbourg HA, Vidal-García M, Brakora KA, Devine J, Takenaka R, Young NM, Gong SG, Neves A, Hallgrímsson B, Marcucio RS. Dosage-dependent effects of FGFR2 W290R mutation on craniofacial shape and cellular dynamics of the basicranial synchondroses. Anat Rec (Hoboken) 2024:10.1002/ar.25398. [PMID: 38409943 PMCID: PMC11345876 DOI: 10.1002/ar.25398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 12/31/2023] [Accepted: 01/17/2024] [Indexed: 02/28/2024]
Abstract
Craniosynostosis is a common yet complex birth defect, characterized by premature fusion of the cranial sutures that can be syndromic or nonsyndromic. With over 180 syndromic associations, reaching genetic diagnoses and understanding variations in underlying cellular mechanisms remains a challenge. Variants of FGFR2 are highly associated with craniosynostosis and warrant further investigation. Using the missense mutation FGFR2W290R , an effective mouse model of Crouzon syndrome, craniofacial features were analyzed using geometric morphometrics across developmental time (E10.5-adulthood, n = 665 total). Given the interrelationship between the cranial vault and basicranium in craniosynostosis patients, the basicranium and synchondroses were analyzed in perinates. Embryonic time points showed minimal significant shape differences. However, hetero- and homozygous mutant perinates and adults showed significant differences in shape and size of the cranial vault, face, and basicranium, which were associated with cranial doming and shortening of the basicranium and skull. Although there were also significant shape and size differences associated with the basicranial bones and clear reductions in basicranial ossification in cleared whole-mount samples, there were no significant alterations in chondrocyte cell shape, size, or orientation along the spheno-occipital synchondrosis. Finally, shape differences in the cranial vault and basicranium were interrelated at perinatal stages. These results point toward the possibility that facial shape phenotypes in craniosynostosis may result in part from pleiotropic effects of the causative mutations rather than only from the secondary consequences of the sutural defects, indicating a novel direction of research that may shed light on the etiology of the broad changes in craniofacial morphology observed in craniosynostosis syndromes.
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Affiliation(s)
- Heather A. Richbourg
- Department of Orthopedic Surgery; University of California, San Francisco; San Francisco, CA, 94110, USA
| | - Marta Vidal-García
- Alberta Children’s Hospital Research Institute, University of Calgary, 28 Oki Dr NW, Calgary, AB, T3B 6A8, Canada
- The McCaig Institute for Bone and Joint Health, University of Calgary, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada
- Department of Cell Biology and Anatomy, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, AB, T2N 4N1, Canada
| | - Katherine A. Brakora
- Department of Neuroscience and Experimental Therapeutics, Texas A&M University School of Medicine, Bryan, TX 77807, USA
| | - Jay Devine
- Alberta Children’s Hospital Research Institute, University of Calgary, 28 Oki Dr NW, Calgary, AB, T3B 6A8, Canada
- The McCaig Institute for Bone and Joint Health, University of Calgary, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada
- Department of Cell Biology and Anatomy, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, AB, T2N 4N1, Canada
| | - Risa Takenaka
- Department of Orthopedic Surgery; University of California, San Francisco; San Francisco, CA, 94110, USA
- Molecular and Cellular Biology, University of Washington, Seattle, WA, 98195, USA
| | - Nathan M. Young
- Department of Orthopedic Surgery; University of California, San Francisco; San Francisco, CA, 94110, USA
| | - Siew-Ging Gong
- Faculty of Dentistry, University of Toronto, Toronto, Ontario, M5G 1G6, Canada
| | - Amanda Neves
- The McCaig Institute for Bone and Joint Health, University of Calgary, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada
- Department of Cell Biology and Anatomy, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, AB, T2N 4N1, Canada
- DeepSurfaceAI, 1039 17 Avenue Southwest Calgary AB T2T 0B1, Canada
| | - Benedikt Hallgrímsson
- Alberta Children’s Hospital Research Institute, University of Calgary, 28 Oki Dr NW, Calgary, AB, T3B 6A8, Canada
- The McCaig Institute for Bone and Joint Health, University of Calgary, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada
- Department of Cell Biology and Anatomy, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, AB, T2N 4N1, Canada
| | - Ralph S. Marcucio
- Department of Orthopedic Surgery; University of California, San Francisco; San Francisco, CA, 94110, USA
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Devine J, Kurki HK, Epp JR, Gonzalez PN, Claes P, Hallgrímsson B. Classifying high-dimensional phenotypes with ensemble learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.29.542750. [PMID: 37398168 PMCID: PMC10312448 DOI: 10.1101/2023.05.29.542750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Classification is a fundamental task in biology used to assign members to a class. While linear discriminant functions have long been effective, advances in phenotypic data collection are yielding increasingly high-dimensional datasets with more classes, unequal class covariances, and non-linear distributions. Numerous studies have deployed machine learning techniques to classify such distributions, but they are often restricted to a particular organism, a limited set of algorithms, and/or a specific classification task. In addition, the utility of ensemble learning or the strategic combination of models has not been fully explored.We performed a meta-analysis of 33 algorithms across 20 datasets containing over 20,000 high-dimensional shape phenotypes using an ensemble learning framework. Both binary (e.g., sex, environment) and multi-class (e.g., species, genotype, population) classification tasks were considered. The ensemble workflow contains functions for preprocessing, training individual learners and ensembles, and model evaluation. We evaluated algorithm performance within and among datasets. Furthermore, we quantified the extent to which various dataset and phenotypic properties impact performance.We found that discriminant analysis variants and neural networks were the most accurate base learners on average. However, their performance varied substantially between datasets. Ensemble models achieved the highest performance on average, both within and among datasets, increasing average accuracy by up to 3% over the top base learner. Higher class R2 values, mean class shape distances, and between- vs. within-class variances were positively associated with performance, whereas higher class covariance distances were negatively associated. Class balance and total sample size were not predictive.Learning-based classification is a complex task driven by many hyperparameters. We demonstrate that selecting and optimizing an algorithm based on the results of another study is a flawed strategy. Ensemble models instead offer a flexible approach that is data agnostic and exceptionally accurate. By assessing the impact of various dataset and phenotypic properties on classification performance, we also offer potential explanations for variation in performance. Researchers interested in maximizing performance stand to benefit from the simplicity and effectiveness of our approach made accessible via the R package pheble.
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Affiliation(s)
- Jay Devine
- Department of Cell Biology and Anatomy, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 4N1, CANADA
| | - Helen K. Kurki
- Department of Anthropology, University of Victoria, 3800 Finnerty Rd, Victoria, BC V8P 5C2, CANADA
| | - Jonathan R. Epp
- Department of Cell Biology and Anatomy, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 4N1, CANADA
| | - Paula N. Gonzalez
- Institute for Studies in Neuroscience and Complex Systems (ENyS) CONICET, Universidad Nacional de La Plata, Av. Calchaquí 5402, Florencio Varela, Buenos Aires, ARGENTINA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, 3000 Leuven, BELGIUM
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, 3000 Leuven, BELGIUM
| | - Benedikt Hallgrímsson
- Department of Cell Biology and Anatomy, Cumming School of Medicine, University of Calgary, 3330 Hospital Dr NW, Calgary, AB T2N 4N1, CANADA
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de Gier W. Phylomorphometrics reveal ecomorphological convergence in pea crab carapace shapes (Brachyura, Pinnotheridae). Ecol Evol 2023; 13:e9744. [PMID: 36694551 PMCID: PMC9842789 DOI: 10.1002/ece3.9744] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 12/23/2022] [Accepted: 12/30/2022] [Indexed: 01/19/2023] Open
Abstract
Most members of the speciose pea crab family (Decapoda: Brachyura: Pinnotheridae) are characterized by their symbioses with marine invertebrates in various host phyla. The ecology of pea crabs is, however, understudied, and the degree of host dependency of most species is still unclear. With the exception of one lineage of ectosymbiotic echinoid-associated crabs, species within the subfamily Pinnotherinae are endosymbionts, living within the body cavities of mollusks, ascidians, echinoderms, and brachiopods. By contrast, most members of the two other subfamilies are considered to have an ectosymbiotic lifestyle, sharing burrows and tubes with various types of worms and burrowing crustaceans (inquilism). The body shapes within the family are extremely variable, mainly in the width and length of the carapace. The variation of carapace shapes in the family, focusing on pinnotherines, is mapped using landmark-based morphometrics. Mean carapace shapes of species groups (based on their host preference) are statistically compared. In addition, a phylomorphometric approach is used to study three different convergence events (across subfamilies; between three genera; and within one genus), and link these events with the associated hosts.
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Affiliation(s)
- Werner de Gier
- Naturalis Biodiversity CenterLeidenThe Netherlands
- Groningen Institute for Evolutionary Life SciencesUniversity of GroningenGroningenThe Netherlands
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7
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Zhang C, Porto A, Rolfe S, Kocatulum A, Maga AM. Automated landmarking via multiple templates. PLoS One 2022; 17:e0278035. [PMID: 36454982 PMCID: PMC9714854 DOI: 10.1371/journal.pone.0278035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 11/08/2022] [Indexed: 12/02/2022] Open
Abstract
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.
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Affiliation(s)
- Chi Zhang
- Center for Development Biology and Regenerative Medicine, Seattle Children’s Research Institute, Seattle, Washington, United States of America
| | - Arthur Porto
- Department of Biological Sciences, Louisiana State University, Baton Rouge, Louisiana, United States of America
- Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana, United States of America
| | - Sara Rolfe
- Center for Development Biology and Regenerative Medicine, Seattle Children’s Research Institute, Seattle, Washington, United States of America
- Friday Harbor Laboratories, University of Washington, San Juan Island, Washington, United States of America
| | - Altan Kocatulum
- Alfred University, Alfred, New York, United States of America
| | - A. Murat Maga
- Center for Development Biology and Regenerative Medicine, Seattle Children’s Research Institute, Seattle, Washington, United States of America
- Division of Craniofacial Medicine, Department of Pediatrics, University of Washington, Seattle, Washington, United States of America
- * E-mail:
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8
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Percival CJ, Devine J, Hassan CR, Vidal‐Garcia M, O'Connor‐Coates CJ, Zaffarini E, Roseman C, Katz D, Hallgrimsson B. The genetic basis of neurocranial size and shape across varied lab mouse populations. J Anat 2022; 241:211-229. [PMID: 35357006 PMCID: PMC9296060 DOI: 10.1111/joa.13657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 02/11/2022] [Accepted: 03/08/2022] [Indexed: 11/26/2022] Open
Abstract
Brain and skull tissues interact through molecular signalling and mechanical forces during head development, leading to a strong correlation between the neurocranium and the external brain surface. Therefore, when brain tissue is unavailable, neurocranial endocasts are often used to approximate brain size and shape. Evolutionary changes in brain morphology may have resulted in secondary changes to neurocranial morphology, but the developmental and genetic processes underlying this relationship are not well understood. Using automated phenotyping methods, we quantified the genetic basis of endocast variation across large genetically varied populations of laboratory mice in two ways: (1) to determine the contributions of various genetic factors to neurocranial form and (2) to help clarify whether a neurocranial variation is based on genetic variation that primarily impacts bone development or on genetic variation that primarily impacts brain development, leading to secondary changes in bone morphology. Our results indicate that endocast size is highly heritable and is primarily determined by additive genetic factors. In addition, a non-additive inbreeding effect led to founder strains with lower neurocranial size, but relatively large brains compared to skull size; suggesting stronger canalization of brain size and/or a general allometric effect. Within an outbred sample of mice, we identified a locus on mouse chromosome 1 that is significantly associated with variation in several positively correlated endocast size measures. Because the protein-coding genes at this locus have been previously associated with brain development and not with bone development, we propose that genetic variation at this locus leads primarily to variation in brain volume that secondarily leads to changes in neurocranial globularity. We identify a strain-specific missense mutation within Akt3 that is a strong causal candidate for this genetic effect. Whilst it is not appropriate to generalize our hypothesis for this single locus to all other loci that also contribute to the complex trait of neurocranial skull morphology, our results further reveal the genetic basis of neurocranial variation and highlight the importance of the mechanical influence of brain growth in determining skull morphology.
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Affiliation(s)
| | - Jay Devine
- Cell Biology and AnatomyUniversity of Calgary Cumming School of MedicineCalgaryCanada
| | | | - Marta Vidal‐Garcia
- Cell Biology and AnatomyUniversity of Calgary Cumming School of MedicineCalgaryCanada
| | | | - Eva Zaffarini
- Cell Biology and AnatomyUniversity of Calgary Cumming School of MedicineCalgaryCanada
| | - Charles Roseman
- Department of Evolution, Ecology, and BehaviorUniversity of IllinoisUrbanaIllinoisUSA
| | - David Katz
- Cell Biology and AnatomyUniversity of Calgary Cumming School of MedicineCalgaryCanada
| | - Benedikt Hallgrimsson
- Cell Biology and Anatomy, Alberta Children's Hospital Research Institute, Cumming School of MedicineUniversity of CalgaryCalgaryCanada
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Mitteroecker P, Schaefer K. Thirty years of geometric morphometrics: Achievements, challenges, and the ongoing quest for biological meaningfulness. AMERICAN JOURNAL OF BIOLOGICAL ANTHROPOLOGY 2022; 178 Suppl 74:181-210. [PMID: 36790612 PMCID: PMC9545184 DOI: 10.1002/ajpa.24531] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 03/28/2022] [Accepted: 04/17/2022] [Indexed: 12/30/2022]
Abstract
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).
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Affiliation(s)
- Philipp Mitteroecker
- Department of Evolutionary Biology, Unit for Theoretical BiologyUniversity of ViennaViennaAustria
| | - Katrin Schaefer
- Department of Evolutionary AnthropologyUniversity of ViennaViennaAustria,Human Evolution and Archaeological Sciences (HEAS)University of ViennaViennaAustria
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10
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Hirsch N, Dahan I, D'haene E, Avni M, Vergult S, Vidal-García M, Magini P, Graziano C, Severi G, Bonora E, Nardone AM, Brancati F, Fernández-Jaén A, Rory OJ, Hallgrímsson B, Birnbaum RY. HDAC9 structural variants disrupting TWIST1 transcriptional regulation lead to craniofacial and limb malformations. Genome Res 2022; 32:1242-1253. [PMID: 35710300 PMCID: PMC9341515 DOI: 10.1101/gr.276196.121] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 06/02/2022] [Indexed: 11/25/2022]
Abstract
Structural variants (SVs) can affect protein-coding sequences as well as gene regulatory elements. However, SVs disrupting protein-coding sequences that also function as cis-regulatory elements remain largely uncharacterized. Here, we show that craniosynostosis patients with SVs containing the histone deacetylase 9 (HDAC9) protein-coding sequence are associated with disruption of TWIST1 regulatory elements that reside within the HDAC9 sequence. Based on SVs within the HDAC9-TWIST1 locus, we defined the 3'-HDAC9 sequence as a critical TWIST1 regulatory region, encompassing craniofacial TWIST1 enhancers and CTCF sites. Deletions of either Twist1 enhancers (eTw5-7Δ/Δ) or CTCF site (CTCF-5Δ/Δ) within the Hdac9 protein-coding sequence led to decreased Twist1 expression and altered anterior/posterior limb expression patterns of SHH pathway genes. This decreased Twist1 expression results in a smaller sized and asymmetric skull and polydactyly that resembles Twist1+/- mouse phenotype. Chromatin conformation analysis revealed that the Twist1 promoter interacts with Hdac9 sequences that encompass Twist1 enhancers and a CTCF site, and that interactions depended on the presence of both regulatory regions. Finally, a large inversion of the entire Hdac9 sequence (Hdac9 INV/+) in mice that does not disrupt Hdac9 expression but repositions Twist1 regulatory elements showed decreased Twist1 expression and led to a craniosynostosis-like phenotype and polydactyly. Thus, our study elucidates essential components of TWIST1 transcriptional machinery that reside within the HDAC9 sequence. It suggests that SVs encompassing protein-coding sequences could lead to a phenotype that is not attributed to its protein function but rather to a disruption of the transcriptional regulation of a nearby gene.
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Affiliation(s)
- Naama Hirsch
- Department of Life Sciences, Faculty of Natural Sciences, The Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
- Center of Evolutionary Genomics and Medicine, The Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
| | - Idit Dahan
- Department of Life Sciences, Faculty of Natural Sciences, The Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
- Center of Evolutionary Genomics and Medicine, The Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
| | - Eva D'haene
- Center for Medical Genetics, Ghent University, 9000, Ghent, Belgium
| | - Matan Avni
- Department of Life Sciences, Faculty of Natural Sciences, The Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
- Center of Evolutionary Genomics and Medicine, The Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
| | - Sarah Vergult
- Center for Medical Genetics, Ghent University, 9000, Ghent, Belgium
| | - Marta Vidal-García
- Department of Cell Biology and Anatomy, Alberta Children's Hospital Research Institute, University of Calgary, T2N 1N4, Calgary, Alberta, Canada
| | - Pamela Magini
- U.O. Genetica Medica, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138, Bologna, Italy
| | - Claudio Graziano
- U.O. Genetica Medica, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138, Bologna, Italy
| | - Giulia Severi
- U.O. Genetica Medica, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138, Bologna, Italy
| | - Elena Bonora
- U.O. Genetica Medica, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138, Bologna, Italy
- Department of Medical and Surgical Sciences, University of Bologna, 40126, Bologna, Italy
| | - Anna Maria Nardone
- Medical Genetics Unit, Policlinico Tor Vergata University Hospital, 00133, Rome, Italy
| | - Francesco Brancati
- Department of Life, Health and Environmental Sciences, University of L'Aquila, 67100, L'Aquila, Italy
- Human Functional Genomics Laboratory, San Raffaele Pisana, 00167, Rome, Italy
| | - Alberto Fernández-Jaén
- Department of Pediatrics and Neurology, Hospital Universitario Quirónsalud, School of Medicine, Universidad Europea de Madrid, 28223, Madrid, Spain
| | - Olson J Rory
- Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Benedikt Hallgrímsson
- Department of Cell Biology and Anatomy, Alberta Children's Hospital Research Institute, University of Calgary, T2N 1N4, Calgary, Alberta, Canada
| | - Ramon Y Birnbaum
- Department of Life Sciences, Faculty of Natural Sciences, The Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
- Center of Evolutionary Genomics and Medicine, The Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel
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11
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MusMorph, a database of standardized mouse morphology data for morphometric meta-analyses. Sci Data 2022; 9:230. [PMID: 35614082 PMCID: PMC9133120 DOI: 10.1038/s41597-022-01338-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 04/13/2022] [Indexed: 11/08/2022] Open
Abstract
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 ).
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12
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Savriama Y, Tautz D. Testing the accuracy of 3D automatic landmarking via genome-wide association studies. G3 (BETHESDA, MD.) 2022; 12:jkab443. [PMID: 35100368 PMCID: PMC9210295 DOI: 10.1093/g3journal/jkab443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 12/16/2021] [Indexed: 11/13/2022]
Abstract
Various advances in 3D automatic phenotyping and landmark-based geometric morphometric methods have been made. While it is generally accepted that automatic landmarking compromises the capture of the biological variation, no studies have directly tested the actual impact of such landmarking approaches in analyses requiring a large number of specimens and for which the precision of phenotyping is crucial to extract an actual biological signal adequately. Here, we use a recently developed 3D atlas-based automatic landmarking method to test its accuracy in detecting QTLs associated with craniofacial development of the house mouse skull and lower jaws for a large number of specimens (circa 700) that were previously phenotyped via a semiautomatic landmarking method complemented with manual adjustment. We compare both landmarking methods with univariate and multivariate mapping of the skull and the lower jaws. We find that most significant SNPs and QTLs are not recovered based on the data derived from the automatic landmarking method. Our results thus confirm the notion that information is lost in the automated landmarking procedure although somewhat dependent on the analyzed structure. The automatic method seems to capture certain types of structures slightly better, such as lower jaws whose shape is almost entirely summarized by its outline and could be assimilated as a 2D flat object. By contrast, the more apparent 3D features exhibited by a structure such as the skull are not adequately captured by the automatic method. We conclude that using 3D atlas-based automatic landmarking methods requires careful consideration of the experimental question.
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Affiliation(s)
- Yoland Savriama
- Department Evolutionary Genetics, Max-Planck Institute for Evolutionary Biology, 24306 Plön, Germany
| | - Diethard Tautz
- Department Evolutionary Genetics, Max-Planck Institute for Evolutionary Biology, 24306 Plön, Germany
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13
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Porto A, Rolfe S, Maga AM. ALPACA: A fast and accurate computer vision approach for automated landmarking of three-dimensional biological structures. Methods Ecol Evol 2021; 12:2129-2144. [PMID: 35874971 PMCID: PMC9291522 DOI: 10.1111/2041-210x.13689] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2021] [Indexed: 11/27/2022]
Abstract
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.
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Affiliation(s)
- Arthur Porto
- Department of Biological SciencesLouisiana State UniversityBaton RougeLAUSA
- Center for Computation and TechnologyLouisiana State UniversityBaton RougeLAUSA
| | - Sara Rolfe
- Friday Harbor LaboratoriesUniversity of WashingtonSan Juan IslandWAUSA
- Center for Development Biology and Regenerative MedicineSeattle Children's Research InstituteSeattleWAUSA
| | - A. Murat Maga
- Center for Development Biology and Regenerative MedicineSeattle Children's Research InstituteSeattleWAUSA
- Division of Craniofacial MedicineDepartment of PediatricsUniversity of WashingtonSeattleWAUSA
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14
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Wittner C, Borowski M, Pirl L, Kastner J, Schrempf A, Schäfer U, Trieb K, Senck S. Thickness accuracy of virtually designed patient-specific implants for large neurocranial defects. J Anat 2021; 239:755-770. [PMID: 34086982 PMCID: PMC8450480 DOI: 10.1111/joa.13465] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 04/27/2021] [Accepted: 05/12/2021] [Indexed: 12/15/2022] Open
Abstract
The combination of computer‐aided design (CAD) techniques based on computed tomography (CT) data to generate patient‐specific implants is in use for decades. However, persisting disadvantages are complicated design procedures and rigid reconstruction protocols, for example, for tailored implants mimicking the patient‐specific thickness distribution of missing cranial bone. In this study we used two different approaches, CAD‐ versus thin‐plate spline (TPS)‐based implants, to reconstruct extensive unilateral and bilateral cranial defects in three clinical cases. We used CT data of three complete human crania that were virtually damaged according to the missing regions in the clinical cases. In total, we carried out 132 virtual reconstructions and quantified accuracy from the original to the generated implant and deviations in the resulting implant thickness as root‐mean‐square error (RMSE). Reconstructions using TPS showed an RMSE of 0.08–0.18 mm in relation to geometric accuracy. CAD‐based implants showed an RMSE of 0.50–1.25 mm. RMSE in relation to implant thickness was between 0.63 and 0.70 mm (TPS) while values for CAD‐based implants were significantly higher (0.63–1.67 mm). While both approaches provide implants showing a high accuracy, the TPS‐based approach additionally provides implants that accurately reproduce the patient‐specific thickness distribution of the affected cranial region.
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Affiliation(s)
- Claudia Wittner
- Research Group Computed Tomography, University of Applied Sciences Upper Austria, Wels, Austria
| | - Markus Borowski
- Institut für Röntgendiagnostik und Nuklearmedizin, Städtisches Klinikum Braunschweig GmbH, Braunschweig, Germany
| | - Lukas Pirl
- Institut für Röntgendiagnostik und Nuklearmedizin, Städtisches Klinikum Braunschweig GmbH, Braunschweig, Germany
| | - Johann Kastner
- Research Group Computed Tomography, University of Applied Sciences Upper Austria, Wels, Austria
| | - Andreas Schrempf
- Research Group for Surgical Simulators Linz, University of Applied Sciences Upper Austria, Linz, Austria
| | - Ute Schäfer
- Forschungseinheit Experimentelle Neurotraumatologie, Medizinische Universität Graz, Graz, Austria
| | - Klemens Trieb
- Research Group Computed Tomography, University of Applied Sciences Upper Austria, Wels, Austria.,Department of Orthopedic and Trauma Surgery, Paracelsus Medical University Salzburg, Salzburg, Austria
| | - Sascha Senck
- Research Group Computed Tomography, University of Applied Sciences Upper Austria, Wels, Austria
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15
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Unger CM, Devine J, Hallgrímsson B, Rolian C. Selection for increased tibia length in mice alters skull shape through parallel changes in developmental mechanisms. eLife 2021; 10:e67612. [PMID: 33899741 PMCID: PMC8118654 DOI: 10.7554/elife.67612] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 04/23/2021] [Indexed: 12/18/2022] Open
Abstract
Bones in the vertebrate cranial base and limb skeleton grow by endochondral ossification, under the control of growth plates. Mechanisms of endochondral ossification are conserved across growth plates, which increases covariation in size and shape among bones, and in turn may lead to correlated changes in skeletal traits not under direct selection. We used micro-CT and geometric morphometrics to characterize shape changes in the cranium of the Longshanks mouse, which was selectively bred for longer tibiae. We show that Longshanks skulls became longer, flatter, and narrower in a stepwise process. Moreover, we show that these morphological changes likely resulted from developmental changes in the growth plates of the Longshanks cranial base, mirroring changes observed in its tibia. Thus, indirect and non-adaptive morphological changes can occur due to developmental overlap among distant skeletal elements, with important implications for interpreting the evolutionary history of vertebrate skeletal form.
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Affiliation(s)
- Colton M Unger
- Department of Biological Sciences, University of CalgaryCalgaryCanada
- McCaig Institute for Bone and Joint HealthCalgaryCanada
| | - Jay Devine
- Department of Cell Biology and Anatomy, University of CalgaryCalgaryCanada
| | - Benedikt Hallgrímsson
- McCaig Institute for Bone and Joint HealthCalgaryCanada
- Department of Cell Biology and Anatomy, University of CalgaryCalgaryCanada
- Alberta Children's Hospital Research Institute for Child and Maternal Health, University of CalgaryCalgaryCanada
| | - Campbell Rolian
- McCaig Institute for Bone and Joint HealthCalgaryCanada
- Department of Comparative Biology and Experimental Medicine, Faculty of Veterinary Medicine, University of CalgaryCalgaryCanada
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16
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Toussaint N, Redhead Y, Vidal-García M, Lo Vercio L, Liu W, Fisher EMC, Hallgrímsson B, Tybulewicz VLJ, Schnabel JA, Green JBA. A landmark-free morphometrics pipeline for high-resolution phenotyping: application to a mouse model of Down syndrome. Development 2021; 148:dev188631. [PMID: 33712441 PMCID: PMC7969589 DOI: 10.1242/dev.188631] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 02/01/2021] [Indexed: 12/20/2022]
Abstract
Characterising phenotypes often requires quantification of anatomical shape. Quantitative shape comparison (morphometrics) traditionally uses manually located landmarks and is limited by landmark number and operator accuracy. Here, we apply a landmark-free method to characterise the craniofacial skeletal phenotype of the Dp1Tyb mouse model of Down syndrome and a population of the Diversity Outbred (DO) mouse model, comparing it with a landmark-based approach. We identified cranial dysmorphologies in Dp1Tyb mice, especially smaller size and brachycephaly (front-back shortening), homologous to the human phenotype. Shape variation in the DO mice was partly attributable to allometry (size-dependent shape variation) and sexual dimorphism. The landmark-free method performed as well as, or better than, the landmark-based method but was less labour-intensive, required less user training and, uniquely, enabled fine mapping of local differences as planar expansion or shrinkage. Its higher resolution pinpointed reductions in interior mid-snout structures and occipital bones in both the models that were not otherwise apparent. We propose that this landmark-free pipeline could make morphometrics widely accessible beyond its traditional niches in zoology and palaeontology, especially in characterising developmental mutant phenotypes.
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Affiliation(s)
- Nicolas Toussaint
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - Yushi Redhead
- Centre for Craniofacial Biology & Regeneration, King's College London, UK
- The Francis Crick Institute, London NW1 1AT, UK
| | - Marta Vidal-García
- Department of Cell Biology & Anatomy, University of Calgary, Calgary AB T2N 4N1, Canada
| | - Lucas Lo Vercio
- Department of Cell Biology & Anatomy, University of Calgary, Calgary AB T2N 4N1, Canada
| | - Wei Liu
- Department of Cell Biology & Anatomy, University of Calgary, Calgary AB T2N 4N1, Canada
| | - Elizabeth M C Fisher
- Department of Neurodegenerative Disease, Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Benedikt Hallgrímsson
- Department of Cell Biology & Anatomy, University of Calgary, Calgary AB T2N 4N1, Canada
| | - Victor L J Tybulewicz
- The Francis Crick Institute, London NW1 1AT, UK
- Department of Immunology & Inflammation, Imperial College London, London W12 0NN, UK
| | - Julia A Schnabel
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - Jeremy B A Green
- Centre for Craniofacial Biology & Regeneration, King's College London, UK
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17
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Hipsley CA, Aguilar R, Black JR, Hocknull SA. High-throughput microCT scanning of small specimens: preparation, packing, parameters and post-processing. Sci Rep 2020; 10:13863. [PMID: 32807929 PMCID: PMC7431592 DOI: 10.1038/s41598-020-70970-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 08/04/2020] [Indexed: 12/17/2022] Open
Abstract
High-resolution X-ray microcomputed tomography, or microCT (μCT), enables the digital imaging of whole objects in three dimensions. The power of μCT to visualize internal features without disarticulation makes it particularly valuable for the study of museum collections, which house millions of physical specimens documenting the spatio-temporal patterns of life. Despite the potential for comparative analyses, most μCT studies include limited numbers of museum specimens, due to the challenges of digitizing numerous individuals within a project scope. Here we describe a method for high-throughput μCT scanning of hundreds of small (< 2 cm) specimens in a single container, followed by individual labelling and archival storage. We also explore the effects of various packing materials and multiple specimens per capsule to minimize sample movement that can degrade image quality, and hence μCT investment. We demonstrate this protocol on vertebrate fossils from Queensland Museum, Australia, as part of an effort to track community responses to climate change over evolutionary time. This system can be easily modified for other types of wet and dry material amenable to X-ray attenuation, including geological, botanical and zoological samples, providing greater access to large-scale phenotypic data and adding value to global collections.
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Affiliation(s)
- Christy A Hipsley
- School of BioSciences, University of Melbourne, BioSciences 4, Building 147, Parkville, VIC, 3010, Australia. .,Museums Victoria, GPO Box 666, Melbourne, VIC, 3001, Australia.
| | - Rocio Aguilar
- School of BioSciences, University of Melbourne, BioSciences 4, Building 147, Parkville, VIC, 3010, Australia.,Museums Victoria, GPO Box 666, Melbourne, VIC, 3001, Australia.,School of Biological Sciences, Monash University, Clayton, VIC, Australia
| | - Jay R Black
- School of Earth Sciences, University of Melbourne, Melbourne, VIC, Australia
| | - Scott A Hocknull
- School of BioSciences, University of Melbourne, BioSciences 4, Building 147, Parkville, VIC, 3010, Australia.,Queensland Museum, Geosciences, 122 Gerler Rd., Hendra, QLD, 4011, Australia
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18
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A Registration and Deep Learning Approach to Automated Landmark Detection for Geometric Morphometrics. Evol Biol 2020; 47:246-259. [PMID: 33583965 DOI: 10.1007/s11692-020-09508-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Geometric morphometrics is the statistical analysis of landmark-based shape variation and its covariation with other variables. Over the past two decades, the gold standard of landmark data acquisition has been manual detection by a single observer. This approach has proven accurate and reliable in small-scale investigations. However, big data initiatives are increasingly common in biology and morphometrics. This requires fast, automated, and standardized data collection. We combine techniques from image registration, geometric morphometrics, and deep learning to automate and optimize anatomical landmark detection. We test our method on high-resolution, micro-computed tomography images of adult mouse skulls. To ensure generalizability, we use a morphologically diverse sample and implement fundamentally different deformable registration algorithms. Compared to landmarks derived from conventional image registration workflows, our optimized landmark data show up to a 39.1% reduction in average coordinate error and a 36.7% reduction in total distribution error. In addition, our landmark optimization produces estimates of the sample mean shape and variance-covariance structure that are statistically indistinguishable from expert manual estimates. For biological imaging datasets and morphometric research questions, our approach can eliminate the time and subjectivity of manual landmark detection whilst retaining the biological integrity of these expert annotations.
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19
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The Occasional Perils of Reflection (Across the Midline; in Geometric Morphometrics). Evol Biol 2020. [DOI: 10.1007/s11692-020-09501-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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20
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Modeling the effect of brain growth on cranial bones using finite-element analysis and geometric morphometrics. Surg Radiol Anat 2020; 42:741-748. [PMID: 32266441 DOI: 10.1007/s00276-020-02466-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Accepted: 03/26/2020] [Indexed: 12/13/2022]
Abstract
PURPOSE Brain expansion during ontogeny has been identified as a key factor for explaining the growth pattern of neurocranial bones. However, the dynamics of this relation are only partially understood and a detailed characterization of integrated morphological changes of the brain and the neurocranium along ontogeny is still lacking. The aim of this study was to model the effect of brain growth on cranial bones by means of finite-element analysis (FEA) and geometric morphometric techniques. METHODS First, we described the postnatal changes in brain size and shape by digitizing coordinates of 3D semilandmarks on cranial endocasts, as a proxy of brain, segmented from CT-scans of an ontogenetic sample. Then, two scenarios of brain growth were simulated: one in which brain volume increases with the same magnitude in all directions, and other that includes the information on the relative expansion of brain regions obtained from morphometric analysis. RESULTS Results indicate that in the first model, in which a uniform pressure is applied, the largest displacements were localized in the sutures, especially in the anterior and posterior fontanels, as well as the metopic suture. When information of brain relative growth was introduced into the model, displacements were also concentrated in the lambda region although the values along both sides of the neurocranium (parietal and temporal bones) were larger than under the first scenario. CONCLUSION In sum, we propose a realistic approach to the use of FEA based on morphometric data that offered different results to more simplified models.
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