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Green RM, Lo Vercio LD, Dauter A, Barretto EC, Devine J, Vidal-García M, Marchini M, Robertson S, Zhao X, Mahika A, Shakir MB, Guo S, Boughner JC, Dean W, Lander AD, Marcucio RS, Forkert ND, Hallgrímsson B. Quantifying the relationship between cell proliferation and morphology during development of the face. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.12.540515. [PMID: 37214859 PMCID: PMC10197725 DOI: 10.1101/2023.05.12.540515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Morphogenesis requires highly coordinated, complex interactions between cellular processes: proliferation, migration, and apoptosis, along with physical tissue interactions. How these cellular and tissue dynamics drive morphogenesis remains elusive. Three dimensional (3D) microscopic imaging poses great promise, and generates elegant images. However, generating even moderate through-put quantified images is challenging for many reasons. As a result, the association between morphogenesis and cellular processes in 3D developing tissues has not been fully explored. To address this critical gap, we have developed an imaging and image analysis pipeline to enable 3D quantification of cellular dynamics along with 3D morphology for the same individual embryo. Specifically, we focus on how 3D distribution of proliferation relates to morphogenesis during mouse facial development. Our method involves imaging with light-sheet microscopy, automated segmentation of cells and tissues using machine learning-based tools, and quantification of external morphology via geometric morphometrics. Applying this framework, we show that changes in proliferation are tightly correlated to changes in morphology over the course of facial morphogenesis. These analyses illustrate the potential of this pipeline to investigate mechanistic relationships between cellular dynamics and morphogenesis during embryonic development.
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Affiliation(s)
- Rebecca M Green
- Department of Oral and Craniofacial Sciences, Center for Craniofacial and Dental Genetics, University of Pittsburgh, Pittsburgh, PA, United States
| | - Lucas D Lo Vercio
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, University of Calgary, Calgary, AB, Canada
| | - Andreas Dauter
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, University of Calgary, Calgary, AB, Canada
| | - Elizabeth C Barretto
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, University of Calgary, Calgary, AB, Canada
| | - Jay Devine
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, University of Calgary, Calgary, AB, Canada
| | - Marta Vidal-García
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, University of Calgary, Calgary, AB, Canada
| | | | - Samuel Robertson
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | - Xiang Zhao
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | - Anandita Mahika
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, University of Calgary, Calgary, AB, Canada
| | - M Bilal Shakir
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, University of Calgary, Calgary, AB, Canada
| | - Sienna Guo
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, University of Calgary, Calgary, AB, Canada
| | - Julia C Boughner
- Department of Anatomy, Physiology and Pharmacology, College of Medicine, University of Saskatchewan, Saskatoon, SK, Canada
| | - Wendy Dean
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | - Arthur D Lander
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, United States
| | - Ralph S Marcucio
- Department of Orthopaedic Surgery, University of California San Francisco, San Francisco, CA, United States
| | - Nils D Forkert
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
| | - Benedikt Hallgrímsson
- Department of Cell Biology & Anatomy, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- McCaig Bone and Joint Institute, University of Calgary, Calgary, AB, Canada
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2
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Sutrisno AA, Katano W, Kawamura H, Tajika Y, Koshiba-Takeuchi K. Combined method of whole mount and block-face imaging: Acquisition of 3D data of gene expression pattern from conventional in situ hybridization. Dev Growth Differ 2023; 65:56-64. [PMID: 36450660 DOI: 10.1111/dgd.12827] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/29/2022] [Accepted: 11/20/2022] [Indexed: 12/02/2022]
Abstract
Visualization of spatiotemporal expression of a gene of interest is a fundamental technique for analyzing the involvements of genes in organ development. In situ hybridization (ISH) is one of the most popular methods for visualizing gene expression. When conventional ISH is performed on sections or whole-mount specimens, the gene expression pattern is represented in 2-dimensional (2D) microscopic images or in the surface view of the specimen. To obtain 3-dimensional (3D) data of gene expression from conventional ISH, the "serial section method" has traditionally been employed. However, this method requires an extensive amount of time and labor because it requires researchers to collect a tremendous number of sections, label all sections by ISH, and image them before 3D reconstruction. Here, we proposed a rapid and low-cost 3D imaging method that can create 3D gene expression patterns from conventional ISH-labeled specimens. Our method consists of a combination of whole-mount ISH and Correlative Microscopy and Blockface imaging (CoMBI). The whole-mount ISH-labeled specimens were sliced using a microtome or cryostat, and all block-faces were imaged and used to reconstruct 3D images by CoMBI. The 3D data acquired using our method showed sufficient quality to analyze the morphology and gene expression patterns in the developing mouse heart. In addition, 2D microscopic images of the sections can be obtained when needed. Correlating 2D microscopic images and 3D data can help annotate gene expression patterns and understand the anatomy of developing organs. These results indicated that our method can be useful in the field of developmental biology.
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Affiliation(s)
| | - Wataru Katano
- Graduate School of Life Sciences, Toyo University, Gunma, Japan
| | - Hayata Kawamura
- Graduate School of Life Sciences, Toyo University, Gunma, Japan
| | - Yuki Tajika
- Graduate School of Medicine, Gunma University, Maebashi, Gunma, Japan
| | - Kazuko Koshiba-Takeuchi
- Faculty of Life Sciences, Department of Applied Biosciences, Toyo University, Gunma, Japan.,Graduate School of Life Sciences, Toyo University, Gunma, Japan
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3
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Dalmasso G, Musy M, Niksic M, Robert-Moreno A, Badía-Careaga C, Sanz-Ezquerro JJ, Sharpe J. 4D reconstruction of murine developmental trajectories using spherical harmonics. Dev Cell 2022; 57:2140-2150.e5. [PMID: 36055247 PMCID: PMC9481268 DOI: 10.1016/j.devcel.2022.08.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 05/02/2022] [Accepted: 08/11/2022] [Indexed: 11/30/2022]
Abstract
Normal organogenesis cannot be recapitulated in vitro for mammalian organs, unlike in species including Drosophila and zebrafish. Available 3D data in the form of ex vivo images only provide discrete snapshots of the development of an organ morphology. Here, we propose a computer-based approach to recreate its continuous evolution in time and space from a set of 3D volumetric images. Our method is based on the remapping of shape data into the space of the coefficients of a spherical harmonics expansion where a smooth interpolation over time is simpler. We tested our approach on mouse limb buds and embryonic hearts. A key advantage of this method is that the resulting 4D trajectory can take advantage of all the available data while also being able to interpolate well through time intervals for which there are little or no data. This allows for a quantitative, data-driven 4D description of mouse limb morphogenesis. Computer-based method recreating a 3D plus time evolution of a set of volumetric images Technique based on the interpolation of the coefficients of spherical harmonics Data-driven quantitative 4D description of limb and heart morphogenesis Quantitatively reliable baseline description of organ development
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Affiliation(s)
- Giovanni Dalmasso
- European Molecular Biology Laboratory (EMBL-Barcelona), 08003 Barcelona, Spain.
| | - Marco Musy
- European Molecular Biology Laboratory (EMBL-Barcelona), 08003 Barcelona, Spain
| | - Martina Niksic
- Centre for Genomic Regulation (CRG), 08003 Barcelona, Spain
| | | | | | - Juan Jose Sanz-Ezquerro
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), 28029 Madrid, Spain; Centro Nacional de Biotecnologia (CSIC Madrid), 28049 Madrid, Spain
| | - James Sharpe
- European Molecular Biology Laboratory (EMBL-Barcelona), 08003 Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain.
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4
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A diffusion MRI-based spatiotemporal continuum of the embryonic mouse brain for probing gene-neuroanatomy connections. Proc Natl Acad Sci U S A 2022; 119:2111869119. [PMID: 35165149 PMCID: PMC8851557 DOI: 10.1073/pnas.2111869119] [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] [Accepted: 12/07/2021] [Indexed: 11/18/2022] Open
Abstract
We established an ultra high-resolution diffusion MRI atlas of the embryonic mouse brains from E10.5 to E15.5, which characterizes the continuous changes of brain morphology and microstructures at mesoscopic scale. By integrating gene-expression data into the spatiotemporal continuum, we can navigate the evolving landscape of gene expression and neuroanatomy across both spatial and temporal dimensions to visualize their interactions in normal and abnormal embryonic brain development. We also identified regional clusters with distinct developmental trajectories and identified gene-expression profiles that matched to these regional domains. The diffusion MRI–based continuum of the embryonic brain and the computational techniques presented in this study offer a valuable tool for systematic study of the genetic control of brain development. The embryonic mouse brain undergoes drastic changes in establishing basic anatomical compartments and laying out major axonal connections of the developing brain. Correlating anatomical changes with gene-expression patterns is an essential step toward understanding the mechanisms regulating brain development. Traditionally, this is done in a cross-sectional manner, but the dynamic nature of development calls for probing gene–neuroanatomy interactions in a combined spatiotemporal domain. Here, we present a four-dimensional (4D) spatiotemporal continuum of the embryonic mouse brain from E10.5 to E15.5 reconstructed from diffusion magnetic resonance microscopy (dMRM) data. This study achieved unprecedented high-definition dMRM at 30- to 35-µm isotropic resolution, and together with computational neuroanatomy techniques, we revealed both morphological and microscopic changes in the developing brain. We transformed selected gene-expression data to this continuum and correlated them with the dMRM-based neuroanatomical changes in embryonic brains. Within the continuum, we identified distinct developmental modes comprising regional clusters that shared developmental trajectories and similar gene-expression profiles. Our results demonstrate how this 4D continuum can be used to examine spatiotemporal gene–neuroanatomical interactions by connecting upstream genetic events with anatomical changes that emerge later in development. This approach would be useful for large-scale analysis of the cooperative roles of key genes in shaping the developing brain.
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5
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Klatzow J, Dalmasso G, Martínez-Abadías N, Sharpe J, Uhlmann V. μMatch: 3D Shape Correspondence for Biological Image Data. FRONTIERS IN COMPUTER SCIENCE 2022. [DOI: 10.3389/fcomp.2022.777615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Modern microscopy technologies allow imaging biological objects in 3D over a wide range of spatial and temporal scales, opening the way for a quantitative assessment of morphology. However, establishing a correspondence between objects to be compared, a first necessary step of most shape analysis workflows, remains challenging for soft-tissue objects without striking features allowing them to be landmarked. To address this issue, we introduce the μMatch 3D shape correspondence pipeline. μMatch implements a state-of-the-art correspondence algorithm initially developed for computer graphics and packages it in a streamlined pipeline including tools to carry out all steps from input data pre-processing to classical shape analysis routines. Importantly, μMatch does not require any landmarks on the object surface and establishes correspondence in a fully automated manner. Our open-source method is implemented in Python and can be used to process collections of objects described as triangular meshes. We quantitatively assess the validity of μMatch relying on a well-known benchmark dataset and further demonstrate its reliability by reproducing published results previously obtained through manual landmarking.
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6
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Wang S, Larina IV, Larin KV. Label-free optical imaging in developmental biology [Invited]. BIOMEDICAL OPTICS EXPRESS 2020; 11:2017-2040. [PMID: 32341864 PMCID: PMC7173889 DOI: 10.1364/boe.381359] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 01/30/2020] [Accepted: 02/25/2020] [Indexed: 05/03/2023]
Abstract
Application of optical imaging in developmental biology marks an exciting frontier in biomedical optics. Optical resolution and imaging depth allow for investigation of growing embryos at subcellular, cellular, and whole organism levels, while the complexity and variety of embryonic processes set multiple challenges stimulating the development of various live dynamic embryonic imaging approaches. Among other optical methods, label-free optical techniques attract an increasing interest as they allow investigation of developmental mechanisms without application of exogenous markers or fluorescent reporters. There has been a boost in development of label-free optical imaging techniques for studying embryonic development in animal models over the last decade, which revealed new information about early development and created new areas for investigation. Here, we review the recent progress in label-free optical embryonic imaging, discuss specific applications, and comment on future developments at the interface of photonics, engineering, and developmental biology.
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Affiliation(s)
- Shang Wang
- Department of Biomedical Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ 07030, USA
| | - Irina V. Larina
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Kirill V. Larin
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
- Department of Biomedical Engineering, University of Houston, 3605 Cullen Boulevard, Houston, TX 77204, USA
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7
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Felice RN, Watanabe A, Cuff AR, Noirault E, Pol D, Witmer LM, Norell MA, O'Connor PM, Goswami A. Evolutionary Integration and Modularity in the Archosaur Cranium. Integr Comp Biol 2019; 59:371-382. [PMID: 31120528 DOI: 10.1093/icb/icz052] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
Complex structures, like the vertebrate skull, are composed of numerous elements or traits that must develop and evolve in a coordinated manner to achieve multiple functions. The strength of association among phenotypic traits (i.e., integration), and their organization into highly-correlated, semi-independent subunits termed modules, is a result of the pleiotropic and genetic correlations that generate traits. As such, patterns of integration and modularity are thought to be key factors constraining or facilitating the evolution of phenotypic disparity by influencing the patterns of variation upon which selection can act. It is often hypothesized that selection can reshape patterns of integration, parceling single structures into multiple modules or merging ancestrally semi-independent traits into a strongly correlated unit. However, evolutionary shifts in patterns of trait integration are seldom assessed in a unified quantitative framework. Here, we quantify patterns of evolutionary integration among regions of the archosaur skull to investigate whether patterns of cranial integration are conserved or variable across this diverse group. Using high-dimensional geometric morphometric data from 3D surface scans and computed tomography scans of modern birds (n = 352), fossil non-avian dinosaurs (n = 27), and modern and fossil mesoeucrocodylians (n = 38), we demonstrate that some aspects of cranial integration are conserved across these taxonomic groups, despite their major differences in cranial form, function, and development. All three groups are highly modular and consistently exhibit high integration within the occipital region. However, there are also substantial divergences in correlation patterns. Birds uniquely exhibit high correlation between the pterygoid and quadrate, components of the cranial kinesis apparatus, whereas the non-avian dinosaur quadrate is more closely associated with the jugal and quadratojugal. Mesoeucrocodylians exhibit a slightly more integrated facial skeleton overall than the other grades. Overall, patterns of trait integration are shown to be stable among archosaurs, which is surprising given the cranial diversity exhibited by the clade. At the same time, evolutionary innovations such as cranial kinesis that reorganize the structure and function of complex traits can result in modifications of trait correlations and modularity.
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Affiliation(s)
- Ryan N Felice
- Centre for Integrative Anatomy, Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK.,Life Sciences Department, Vertebrates Division, Natural History Museum, London, SW7 5BD, UK
| | - Akinobu Watanabe
- Life Sciences Department, Vertebrates Division, Natural History Museum, London, SW7 5BD, UK.,Department of Anatomy, New York Institute of Technology College of Osteopathic Medicine, Old Westbury, NY 11568, USA.,Division of Paleontology, American Museum of Natural History, New York, NY 10024, USA
| | - Andrew R Cuff
- Structure and Motion Laboratory, Department of Comparative Biomedical Sciences, Royal Veterinary College, Hawkshead Lane, North Mymms, Hertfordshire, AL9 7TA, UK
| | - Eve Noirault
- Life Sciences Department, Vertebrates Division, Natural History Museum, London, SW7 5BD, UK
| | - Diego Pol
- CONICET. Museo Paleontológico Egidio Feruglio, Av. Fontana 140, Trelew, Chubut, U9100GYO, Argentina
| | - Lawrence M Witmer
- Department of Biomedical Sciences, Ohio University Heritage College of Osteopathic Medicine, Athens, OH, USA
| | - Mark A Norell
- Division of Paleontology, American Museum of Natural History, New York, NY 10024, USA
| | - Patrick M O'Connor
- Department of Biomedical Sciences, Ohio University Heritage College of Osteopathic Medicine, Athens, OH, USA.,Ohio Center for Ecology and Evolutionary Studies, Ohio University, Athens, OH, USA
| | - Anjali Goswami
- Life Sciences Department, Vertebrates Division, Natural History Museum, London, SW7 5BD, UK.,Department of Genetics, Evolution, and Environment, University College London, London, WC1E 6BT, UK
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Flaherty K, Richtsmeier JT. It's about Time: Ossification Center Formation in C57BL/6 Mice from E12⁻E16. J Dev Biol 2018; 6:jdb6040031. [PMID: 30558321 PMCID: PMC6316780 DOI: 10.3390/jdb6040031] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2018] [Revised: 12/11/2018] [Accepted: 12/13/2018] [Indexed: 01/04/2023] Open
Abstract
The establishment of precise, high-resolution temporal sequences for morphogenetic events in laboratory mice remains a vexing issue in developmental biology. Mouse embryos collected at the same period of gestation, even those from the same litter, show wide variation in individual levels of progress along their developmental trajectory. Therefore, age at harvest does not provide sufficient information about developmental progress to serve as the basis for forming samples for the study of rapidly or near-simultaneously occurring events such as the sequence of ossification center formation. Here, we generate two measures of individual developmental progress (developmental age) for a large sample of mouse embryos using crown⁻rump lengths that measures size, and limbstaging ages produced by the embryonic Mouse Ontogenetic Staging System (eMOSS) that measure shape. Using these measures, we establish fine-grained sequences of ossification center appearance for mouse embryos. The two measures of developmental progress generate slightly different sequences of ossification center formation demonstrating that despite their tight correlation throughout the developmental period, size and shape are aspects of form that are at least partially dissociated in development.
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Affiliation(s)
- Kevin Flaherty
- Department of Anthropology, Pennsylvania State University, University Park, PA 16802, USA.
- Department of Biology, Augustana College, Rock Island, IL 61201, USA.
| | - Joan T Richtsmeier
- Department of Anthropology, Pennsylvania State University, University Park, PA 16802, USA.
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9
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Hallgrimsson B, Green RM, Katz DC, Fish JL, Bernier FP, Roseman CC, Young NM, Cheverud JM, Marcucio RS. The developmental-genetics of canalization. Semin Cell Dev Biol 2018; 88:67-79. [PMID: 29782925 DOI: 10.1016/j.semcdb.2018.05.019] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2018] [Revised: 05/16/2018] [Accepted: 05/17/2018] [Indexed: 10/16/2022]
Abstract
Canalization, or robustness to genetic or environmental perturbations, is fundamental to complex organisms. While there is strong evidence for canalization as an evolved property that varies among genotypes, the developmental and genetic mechanisms that produce this phenomenon are very poorly understood. For evolutionary biology, understanding how canalization arises is important because, by modulating the phenotypic variation that arises in response to genetic differences, canalization is a determinant of evolvability. For genetics of disease in humans and for economically important traits in agriculture, this subject is important because canalization is a potentially significant cause of missing heritability that confounds genomic prediction of phenotypes. We review the major lines of thought on the developmental-genetic basis for canalization. These fall into two groups. One proposes specific evolved molecular mechanisms while the other deals with robustness or canalization as a more general feature of development. These explanations for canalization are not mutually exclusive and they overlap in several ways. General explanations for canalization are more likely to involve emergent features of development than specific molecular mechanisms. Disentangling these explanations is also complicated by differences in perspectives between genetics and developmental biology. Understanding canalization at a mechanistic level will require conceptual and methodological approaches that integrate quantitative genetics and developmental biology.
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Affiliation(s)
- Benedikt Hallgrimsson
- Dept. of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada.
| | - Rebecca M Green
- Dept. of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - David C Katz
- Dept. of Cell Biology & Anatomy, Alberta Children's Hospital Research Institute and McCaig Bone and Joint Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Jennifer L Fish
- Dept. of Biological Sciences, University of Massachusetts Lowell, Lowell, MA, 01854, USA
| | - Francois P Bernier
- Dept of Medical Genetics, Alberta Children's Hospital Research Institute Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Charles C Roseman
- Dept. of Animal Biology, University of Illinois Urbana Champaign, Urbana, IL, 61801, USA
| | - Nathan M Young
- Dept. of Orthopaedic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA, 94110, USA
| | - James M Cheverud
- Dept. of Biology, Loyola University Chicago, Chicago, IL, 60660, USA
| | - Ralph S Marcucio
- Dept. of Orthopaedic Surgery, School of Medicine, University of California San Francisco, San Francisco, CA, 94110, USA.
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