1
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Murphy P, Armit C, Hill B, Venkataraman S, Frankel P, Baldock RA, Davidson DR. Integrated analysis of Wnt signalling system component gene expression. Development 2022; 149:276001. [PMID: 35831952 PMCID: PMC9481969 DOI: 10.1242/dev.200312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 07/06/2022] [Indexed: 11/20/2022]
Abstract
Wnt signalling controls patterning and differentiation across many tissues and organs of the developing embryo through temporally and spatially restricted expression of multi-gene families encoding ligands, receptors, pathway modulators and intracellular components. Here, we report an integrated analysis of key genes in the 3D space of the mouse embryo across multiple stages of development. We applied a method for 3D/3D image transformation to map all gene expression patterns to a single reference embryo for each stage, providing both visual analysis and volumetric mapping allowing computational methods to interrogate the combined expression patterns. We identify territories where multiple Wnt and Fzd genes are co-expressed and cross-compare all patterns, including all seven Wnt paralogous gene pairs. The comprehensive analysis revealed regions in the embryo where no Wnt or Fzd gene expression is detected, and where single Wnt genes are uniquely expressed. This work provides insight into a previously unappreciated level of organisation of expression patterns, as well as presenting a resource that can be utilised further by the research community for whole-system analysis. Summary: A systematic analysis of integrated expression patterns of Wnt signalling pathway component-encoding genes and canonical pathway read-out, spatially mapped in 3D to mouse embryo models identifies co-expression territories.
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Affiliation(s)
- Paula Murphy
- School of Natural Sciences, Department of Zoology, Trinity College Dublin, The University of Dublin 1 , Dublin 2 , Ireland
| | - Chris Armit
- Institute of Cancer and Genetics, University of Edinburgh 2 MRC Human Genetics Unit , , Crewe Road, Edinburgh EH4 2XU , UK
| | - Bill Hill
- Institute of Cancer and Genetics, University of Edinburgh 2 MRC Human Genetics Unit , , Crewe Road, Edinburgh EH4 2XU , UK
| | - Shanmugasundaram Venkataraman
- Institute of Cancer and Genetics, University of Edinburgh 2 MRC Human Genetics Unit , , Crewe Road, Edinburgh EH4 2XU , UK
| | - Patrick Frankel
- School of Natural Sciences, Department of Zoology, Trinity College Dublin, The University of Dublin 1 , Dublin 2 , Ireland
| | - Richard A. Baldock
- Institute of Cancer and Genetics, University of Edinburgh 2 MRC Human Genetics Unit , , Crewe Road, Edinburgh EH4 2XU , UK
| | - Duncan R. Davidson
- Institute of Cancer and Genetics, University of Edinburgh 2 MRC Human Genetics Unit , , Crewe Road, Edinburgh EH4 2XU , UK
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2
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Abstract
The increasingly multidisciplinary nature of scientific research necessitates a need for Open Data repositories that can archive data in support of publications in scientific journals. Recognising this need, even before GigaScience launched in 2012, GigaDB was already in place and taking data for a year before (making it 11 this year). Since GigaDB launched, there has been a consistent growth in this resource in terms of data volume, data discoverability and data re-use. In this commentary, we provide a retrospective of key changes over the last decade, and the role of Data Curation in enhancing the user experience. Furthermore we explore a much needed emphasis on enabling researchers to interact with and explore datasets prior to data download.
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Affiliation(s)
- Chris Armit
- GigaScience Press, BGI Hong Kong Tech Co Ltd., 26F A Kings Wing Place 2, 1 On Kwan Street, Shek Mun, Sha Tin, NT, Hong Kong SAR
| | - Mary Ann Tuli
- GigaScience Press, BGI Hong Kong Tech Co Ltd., 26F A Kings Wing Place 2, 1 On Kwan Street, Shek Mun, Sha Tin, NT, Hong Kong SAR
| | - Christopher I Hunter
- GigaScience Press, BGI Hong Kong Tech Co Ltd., 26F A Kings Wing Place 2, 1 On Kwan Street, Shek Mun, Sha Tin, NT, Hong Kong SAR
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3
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Lindström NO, Sealfon R, Chen X, Parvez RK, Ransick A, De Sena Brandine G, Guo J, Hill B, Tran T, Kim AD, Zhou J, Tadych A, Watters A, Wong A, Lovero E, Grubbs BH, Thornton ME, McMahon JA, Smith AD, Ruffins SW, Armit C, Troyanskaya OG, McMahon AP. Spatial transcriptional mapping of the human nephrogenic program. Dev Cell 2021; 56:2381-2398.e6. [PMID: 34428401 DOI: 10.1016/j.devcel.2021.07.017] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 05/06/2021] [Accepted: 07/27/2021] [Indexed: 12/11/2022]
Abstract
Congenital abnormalities of the kidney and urinary tract are among the most common birth defects, affecting 3% of newborns. The human kidney forms around a million nephrons from a pool of nephron progenitors over a 30-week period of development. To establish a framework for human nephrogenesis, we spatially resolved a stereotypical process by which equipotent nephron progenitors generate a nephron anlage, then applied data-driven approaches to construct three-dimensional protein maps on anatomical models of the nephrogenic program. Single-cell RNA sequencing identified progenitor states, which were spatially mapped to the nephron anatomy, enabling the generation of functional gene networks predicting interactions within and between nephron cell types. Network mining identified known developmental disease genes and predicted targets of interest. The spatially resolved nephrogenic program made available through the Human Nephrogenesis Atlas (https://sckidney.flatironinstitute.org/) will facilitate an understanding of kidney development and disease and enhance efforts to generate new kidney structures.
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Affiliation(s)
- Nils O Lindström
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
| | - Rachel Sealfon
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Xi Chen
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Riana K Parvez
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andrew Ransick
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Guilherme De Sena Brandine
- Molecular and Computational Biology, Division of Biological Sciences, University of Southern, Los Angeles, CA 90089, USA
| | - Jinjin Guo
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Bill Hill
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Tracy Tran
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Albert D Kim
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jian Zhou
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Alicja Tadych
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Aaron Watters
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Aaron Wong
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Elizabeth Lovero
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Brendan H Grubbs
- Maternal Fetal Medicine Division, Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Matthew E Thornton
- Maternal Fetal Medicine Division, Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jill A McMahon
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andrew D Smith
- Molecular and Computational Biology, Division of Biological Sciences, University of Southern, Los Angeles, CA 90089, USA
| | - Seth W Ruffins
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Chris Armit
- MRC Human Genetics Unit, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK; BGI Hong Kong, 26/F, Kings Wing Plaza 2, 1 On Kwan Street, Shek Mun, NT, Hong Kong
| | - Olga G Troyanskaya
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA; Department of Computer Science, Princeton University, Princeton, NJ, USA.
| | - Andrew P McMahon
- Department of Stem Cell Biology and Regenerative Medicine, Broad-CIRM Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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Horner NR, Venkataraman S, Armit C, Casero R, Brown JM, Wong MD, van Eede MC, Henkelman RM, Johnson S, Teboul L, Wells S, Brown SD, Westerberg H, Mallon AM. LAMA: automated image analysis for the developmental phenotyping of mouse embryos. Development 2021; 148:dev192955. [PMID: 33574040 PMCID: PMC8015254 DOI: 10.1242/dev.192955] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 12/21/2020] [Indexed: 11/20/2022]
Abstract
Advanced 3D imaging modalities, such as micro-computed tomography (micro-CT), have been incorporated into the high-throughput embryo pipeline of the International Mouse Phenotyping Consortium (IMPC). This project generates large volumes of raw data that cannot be immediately exploited without significant resources of personnel and expertise. Thus, rapid automated annotation is crucial to ensure that 3D imaging data can be integrated with other multi-dimensional phenotyping data. We present an automated computational mouse embryo phenotyping pipeline that harnesses the large amount of wild-type control data available in the IMPC embryo pipeline in order to address issues of low mutant sample number as well as incomplete penetrance and variable expressivity. We also investigate the effect of developmental substage on automated phenotyping results. Designed primarily for developmental biologists, our software performs image pre-processing, registration, statistical analysis and segmentation of embryo images. We also present a novel anatomical E14.5 embryo atlas average and, using it with LAMA, show that we can uncover known and novel dysmorphology from two IMPC knockout lines.
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Affiliation(s)
- Neil R Horner
- Medical Research Council Harwell Institute, Harwell OX11 0RD, UK
| | - Shanmugasundaram Venkataraman
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine (IGMM), University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Chris Armit
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine (IGMM), University of Edinburgh, Edinburgh EH4 2XU, UK
- BGI Hong Kong, 26/F, Kings Wing Plaza 2, 1 On Kwan Street, Shek Mun, New Territories, Hong Kong
| | - Ramón Casero
- Medical Research Council Harwell Institute, Harwell OX11 0RD, UK
| | - James M Brown
- School of Computer Science, University of Lincoln, Lincoln LN6 7TS
| | - Michael D Wong
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, Ontario M5T 3H7, Canada
| | - Matthijs C van Eede
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, Ontario M5T 3H7, Canada
| | - R Mark Henkelman
- Mouse Imaging Centre, Hospital for Sick Children, Toronto, Ontario M5T 3H7, Canada
| | - Sara Johnson
- Medical Research Council Harwell Institute, Harwell OX11 0RD, UK
| | - Lydia Teboul
- Medical Research Council Harwell Institute, Harwell OX11 0RD, UK
| | - Sara Wells
- Medical Research Council Harwell Institute, Harwell OX11 0RD, UK
| | - Steve D Brown
- Medical Research Council Harwell Institute, Harwell OX11 0RD, UK
| | | | - Ann-Marie Mallon
- Medical Research Council Harwell Institute, Harwell OX11 0RD, UK
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5
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Xiao SZ, Armit C, Edmunds S, Goodman L, Li P, Tuli MA, Hunter CI. Increased interactivity and improvements to the GigaScience database, GigaDB. Database (Oxford) 2019; 2019:5314010. [PMID: 30753480 PMCID: PMC6376146 DOI: 10.1093/database/baz016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 01/10/2019] [Accepted: 01/19/2019] [Indexed: 11/16/2022]
Abstract
With a large increase in the volume and type of data archived in GigaScience Database (GigaDB) since its launch in 2011, we have studied the metrics and user patterns to assess the important aspects needed to best suit current and future use. This has led to new front-end developments and enhanced interactivity and functionality that greatly improve user experience. In this article, we present an overview of the current practices including the Biocurational role of the GigaDB staff, the broad usage metrics of GigaDB datasets and an update on how the GigaDB platform has been overhauled and enhanced to improve the stability and functionality of the codebase. Finally, we report on future directions for the GigaDB resource.
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6
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Abstract
“The Atlas of Mouse Development” by Kaufman is a classic paper atlas that is the de facto standard for the definition of mouse embryo anatomy in the context of standard histological images. We have redigitized the original haematoxylin and eosin–stained tissue sections used for the book at high resolution and transferred the hand-drawn annotations to digital form. We have augmented the annotations with standard ontological assignments (EMAPA anatomy) and made the data freely available via an online viewer (eHistology) and from the University of Edinburgh DataShare archive. The dataset captures and preserves the definitive anatomical knowledge of the original atlas, provides a core image set for deeper community annotation and teaching, and delivers a unique high-quality set of high-resolution histological images through mammalian development for manual and automated analysis.
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Affiliation(s)
- Richard A Baldock
- MRC Human Genetics Unit, Institute of Genomic and Molecular Medicine, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Chris Armit
- MRC Human Genetics Unit, Institute of Genomic and Molecular Medicine, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
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7
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Armit C, Richardson L, Venkataraman S, Graham L, Burton N, Hill B, Yang Y, Baldock RA. eMouseAtlas: An atlas-based resource for understanding mammalian embryogenesis. Dev Biol 2017; 423:1-11. [PMID: 28161522 PMCID: PMC5442644 DOI: 10.1016/j.ydbio.2017.01.023] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Revised: 01/31/2017] [Accepted: 01/31/2017] [Indexed: 11/23/2022]
Abstract
The eMouseAtlas resource is an online database of 3D digital models of mouse development, an ontology of mouse embryo anatomy and a gene-expression database with about 30K spatially mapped gene-expression patterns. It is closely linked with the MGI/GXD database at the Jackson Laboratory and holds links to almost all available image-based gene-expression data for the mouse embryo. In this resource article we describe the novel web-based tools we have developed for 3D visualisation of embryo anatomy and gene expression. We show how mapping of gene expression data onto spatial models delivers a framework for capturing gene expression that enhances our understanding of development, and we review the exploratory tools utilised by the EMAGE gene expression database as a means of defining co-expression of in situ hybridisation, immunohistochemistry, and lacZ-omic expression patterns. We report on recent developments of the eHistology atlas and our use of web-services to support embedding of the online 'The Atlas of Mouse Development' in the context of other resources such as the DMDD mouse phenotype database. In addition, we discuss new developments including a cellular-resolution placental atlas, third-party atlas models, clonal analysis data and a new interactive eLearning resource for developmental processes.
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Affiliation(s)
- Chris Armit
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Lorna Richardson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Shanmugasundaram Venkataraman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Liz Graham
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Nicholas Burton
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Bill Hill
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Yiya Yang
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
| | - Richard A Baldock
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Crewe Road, EH4 2XU, UK
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8
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Armit C, Hill B, Venkataraman S, McLeod K, Burger A, Baldock R. The 'straight mouse': defining anatomical axes in 3D embryo models. Database (Oxford) 2017; 2017:3066360. [PMID: 28365728 PMCID: PMC5467569 DOI: 10.1093/database/bax010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Accepted: 01/27/2017] [Indexed: 11/25/2022]
Abstract
A primary objective of the eMouseAtlas Project is to enable 3D spatial mapping of whole embryo gene expression data to capture complex 3D patterns for indexing, visualization, cross-comparison and analysis. For this we have developed a spatio-temporal framework based on 3D models of embryos at different stages of development coupled with an anatomical ontology. Here we introduce a method of defining coordinate axes that correspond to the anatomical or biologically relevant anterior–posterior (A–P), dorsal–ventral (D–V) and left–right (L–R) directions. These enable more sophisticated query and analysis of the data with biologically relevant associations, and provide novel data visualizations that can reveal patterns that are otherwise difficult to detect in the standard 3D coordinate space. These anatomical coordinates are defined using the concept of a ‘straight mouse-embryo’ within which the anatomical coordinates are Cartesian. The straight embryo model has been mapped via a complex non-linear transform onto the standard embryo model. We explore the utility of this anatomical coordinate system in elucidating the spatial relationship of spatially mapped embryonic ‘Fibroblast growth factor’ gene expression patterns, and we discuss the importance of this technology in summarizing complex multimodal mouse embryo image data from gene expression and anatomy studies. Database URL:www.emouseatlas.org
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Affiliation(s)
- Chris Armit
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh College of Medicine and Veterinary Medicine, Edinburgh, Scotland EH4 2XU, UK and
| | - Bill Hill
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh College of Medicine and Veterinary Medicine, Edinburgh, Scotland EH4 2XU, UK and
| | - S Venkataraman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh College of Medicine and Veterinary Medicine, Edinburgh, Scotland EH4 2XU, UK and
| | - Kenneth McLeod
- Department of Computer Science, Heriot-Watt University, Edinburgh, Scotland EH14 4AS, UK
| | - Albert Burger
- Department of Computer Science, Heriot-Watt University, Edinburgh, Scotland EH14 4AS, UK
| | - Richard Baldock
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh College of Medicine and Veterinary Medicine, Edinburgh, Scotland EH4 2XU, UK and
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Abstract
The International Mouse Phenotyping Consortium (IMPC) is a major international effort to explore the effects of knocking out 20,000 genes in the mouse. A new study by White and colleagues, published in the current issue of Disease Models & Mechanisms, demonstrates the usefulness of lacZ in situ reporter expression patterns in extending our understanding of genotype-phenotype relationships as part of the IMPC high-throughput screen. In situ gene expression profiling is invaluable for evaluating compartment-specific gene expression patterns, and these enrich our understanding of the role of genes in a great number of biological processes in multiple organ systems. Furthermore, the complexity of gene expression patterns informs our understanding of how genes influence lethality. This Editorial aims to highlight ways in which the lacZ expression profiles can impact on biomedical research by uncovering as-yet-unknown genotype-phenotype relationships, and through predicting the role of genes in health and disease.
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Affiliation(s)
- Chris Armit
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
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10
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Richardson L, Graham L, Moss J, Burton N, Roochun Y, Armit C, Baldock RA. Developing the eHistology Atlas. Database (Oxford) 2015; 2015:bav105. [PMID: 26500249 PMCID: PMC4618478 DOI: 10.1093/database/bav105] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Revised: 09/17/2015] [Accepted: 09/30/2015] [Indexed: 01/03/2023]
Abstract
The eMouseAtlas project has undertaken to generate a new resource providing access to high-resolution colour images of the slides used in the renowned textbook 'The Atlas of Mouse Development' by Matthew H. Kaufman. The original histology slides were digitized, and the associated anatomy annotations captured for display in the new resource. These annotations were assigned to objects in the standard reference anatomy ontology, allowing the eHistology resource to be linked to other data resources including the Edinburgh Mouse Atlas Gene-Expression database (EMAGE) an the Mouse Genome Informatics (MGI) gene-expression database (GXD). The provision of the eHistology Atlas resource was assisted greatly by the expertise of the eMouseAtlas project in delivering large image datasets within a web environment, using IIP3D technology. This technology also permits future extensions to the resource through the addition of further layers of data and annotations to the resource. Database URL: www.emouseatlas.org/emap/eHistology/index.php.
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Affiliation(s)
- Lorna Richardson
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Liz Graham
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Julie Moss
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Nick Burton
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Yogmatee Roochun
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Chris Armit
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
| | - Richard A Baldock
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, UK
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Abstract
A significant proportion of developmental biology data is presented in the form of images at morphologically diverse stages of development. The curation of these datasets presents different challenges to that of sequence/text-based data. Towards this end, the eMouseAtlas project created a digital atlas of mouse embryo development as a means of understanding developmental anatomy and exploring the relationship between genes and development in a spatial context. Using the morphological staging system pioneered by Karl Theiler, the project has generated 3D models of post-implantation mouse development and used them as a spatial framework for the delineation of anatomical components and for archiving in situ gene expression data in the EMAGE database. This has allowed us to develop a unique online resource for mouse developmental biology. We describe here the underlying structure of the resource, as well as some of the tools that have been developed to allow users to mine the curated image data. These tools include our IIP3D/X3DOM viewer that allows 3D visualisation of anatomy and/or gene expression in the context of a web browser, and the eHistology resource that extends this functionality to allow visualisation of high-resolution cellular level images of histology sections. Furthermore, we review some of the informatics aspects of eMouseAtlas to provide a deeper insight into the use of the atlas and gene expression database.
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Affiliation(s)
- Chris Armit
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland
| | - Lorna Richardson
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland
| | - Bill Hill
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland
| | - Yiya Yang
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland
| | - Richard A Baldock
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Edinburgh, Scotland.
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12
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Berry RL, Ozdemir DD, Aronow B, Lindström NO, Dudnakova T, Thornburn A, Perry P, Baldock R, Armit C, Joshi A, Jeanpierre C, Shan J, Vainio S, Baily J, Brownstein D, Davies J, Hastie ND, Hohenstein P. Deducing the stage of origin of Wilms' tumours from a developmental series of Wt1-mutant mice. Development 2015. [DOI: 10.1242/dev.129239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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13
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Abstract
The Atlas of Mouse Development by Professor Mathew Kaufman is an essential text for understanding mouse developmental anatomy. This definitive and authoritative atlas is still in production and is essential for any biologist working with the mouse embryo, although the last revision dates back to 1994. Here, we announce the eHistology online resource that provides free access to high-resolution colour images digitized from the original histological sections (www.emouseatlas.org/emap/eHistology/index.php) used by Kaufman for the Atlas. The images are provided with the original annotations and plate numbering of the paper atlas and enable viewing the material to cellular resolution.
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Affiliation(s)
- Elizabeth Graham
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Julie Moss
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Nick Burton
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | | | - Chris Armit
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Lorna Richardson
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Richard Baldock
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
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14
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Abstract
There was an error published in Development 142, 1909-1911. Author Yogmatee Roochun was omitted. The corrected author list appears above. The authors apologise to readers for this mistake.
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Affiliation(s)
- Elizabeth Graham
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Julie Moss
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Nick Burton
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Yogmatee Roochun
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Chris Armit
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Lorna Richardson
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Richard Baldock
- MRC Human Genetics Unit, IGMM, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
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Berry RL, Ozdemir DD, Aronow B, Lindström NO, Dudnakova T, Thornburn A, Perry P, Baldock R, Armit C, Joshi A, Jeanpierre C, Shan J, Vainio S, Baily J, Brownstein D, Davies J, Hastie ND, Hohenstein P. Deducing the stage of origin of Wilms' tumours from a developmental series of Wt1-mutant mice. Dis Model Mech 2015; 8:903-17. [PMID: 26035382 PMCID: PMC4527280 DOI: 10.1242/dmm.018523] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2014] [Accepted: 05/07/2015] [Indexed: 12/28/2022] Open
Abstract
Wilms' tumours, paediatric kidney cancers, are the archetypal example of tumours caused through the disruption of normal development. The genetically best-defined subgroup of Wilms' tumours is the group caused by biallelic loss of the WT1 tumour suppressor gene. Here, we describe a developmental series of mouse models with conditional loss of Wt1 in different stages of nephron development before and after the mesenchymal-to-epithelial transition (MET). We demonstrate that Wt1 is essential for normal development at all kidney developmental stages under study. Comparison of genome-wide expression data from the mutant mouse models with human tumour material of mutant or wild-type WT1 datasets identified the stage of origin of human WT1-mutant tumours, and emphasizes fundamental differences between the two human tumour groups due to different developmental stages of origin. Summary: The comparison of different nephron-specific Wt1-knockout mouse models identifies the stage of origin of human WT1-mutant Wilms' tumours.
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Affiliation(s)
- Rachel L Berry
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Derya D Ozdemir
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Bruce Aronow
- Department of Biomedical Informatics and Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Nils O Lindström
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Tatiana Dudnakova
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Anna Thornburn
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Paul Perry
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Richard Baldock
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Chris Armit
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Anagha Joshi
- The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
| | - Cécile Jeanpierre
- INSERM, UMR 1163, Laboratory of Inherited Kidney Diseases, Paris 75015, France Paris Descartes - Sorbonne Paris Cité University, Imagine Institute, Paris 75015, France
| | - Jingdong Shan
- Biocenter Oulu, InfoTech Oulu, Faculty of Biochemistry and Molecular Medicine, Aapistie 5A, University of Oulu, PO Box 5000, Oulu 90014, Finland
| | - Seppo Vainio
- Biocenter Oulu, InfoTech Oulu, Faculty of Biochemistry and Molecular Medicine, Aapistie 5A, University of Oulu, PO Box 5000, Oulu 90014, Finland
| | - James Baily
- Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK
| | - David Brownstein
- Queen's Medical Research Institute, University of Edinburgh, 47 Little France Crescent, Edinburgh, EH16 4TJ, UK
| | - Jamie Davies
- Centre for Integrative Physiology, University of Edinburgh, Hugh Robson Building, 15 George Square, Edinburgh, EH8 9XD, UK
| | - Nicholas D Hastie
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Peter Hohenstein
- MRC Human Genetics Unit, MRC Institute for Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK The Roslin Institute, University of Edinburgh, Easter Bush Campus, Midlothian, EH25 9RG, UK
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16
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Richardson L, Venkataraman S, Stevenson P, Yang Y, Moss J, Graham L, Burton N, Hill B, Rao J, Baldock RA, Armit C. EMAGE mouse embryo spatial gene expression database: 2014 update. Nucleic Acids Res 2013; 42:D835-44. [PMID: 24265223 PMCID: PMC3965061 DOI: 10.1093/nar/gkt1155] [Citation(s) in RCA: 93] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
EMAGE (http://www.emouseatlas.org/emage/) is a freely available database of in situ gene expression patterns that allows users to perform online queries of mouse developmental gene expression. EMAGE is unique in providing both text-based descriptions of gene expression plus spatial maps of gene expression patterns. This mapping allows spatial queries to be accomplished alongside more traditional text-based queries. Here, we describe our recent progress in spatial mapping and data integration. EMAGE has developed a method of spatially mapping 3D embryo images captured using optical projection tomography, and through the use of an IIP3D viewer allows users to view arbitrary sections of raw and mapped 3D image data in the context of a web browser. EMAGE now includes enhancer data, and we have spatially mapped images from a comprehensive screen of transgenic reporter mice that detail the expression of mouse non-coding genomic DNA fragments with enhancer activity. We have integrated the eMouseAtlas anatomical atlas and the EMAGE database so that a user of the atlas can query the EMAGE database easily. In addition, we have extended the atlas framework to enable EMAGE to spatially cross-index EMBRYS whole mount in situ hybridization data. We additionally report on recent developments to the EMAGE web interface, including new query and analysis capabilities.
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Affiliation(s)
- Lorna Richardson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital EH4 2XU, UK
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Armit C. Developmental biology and databases: how to archive, find and query gene expression patterns using the world wide web. Organogenesis 2012; 3:70-3. [PMID: 19279703 DOI: 10.4161/org.3.2.4942] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2007] [Accepted: 08/28/2007] [Indexed: 11/19/2022] Open
Abstract
Systems biology has undergone an explosive growth in recent times. The staggering amount of expression data that can now be obtained from microarray chip analysis and high-throughput in situ screens has lent itself to the creation of large, terabyte-capacity databases in which to house gene expression patterns. Furthermore, innovative methods can be used to interrogate these databases and to link genomic information to functional information of embryonic cells, tissues and organs. These formidable advancements have led to the development of a whole host of online resources that have allowed biologists to probe the mysteries of growth and form with renewed zeal. This review seeks to highlight general features of these databases, and to identify the methods by which expression data can be retrieved.
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Armit C, Venkataraman S, Richardson L, Stevenson P, Moss J, Graham L, Ross A, Yang Y, Burton N, Rao J, Hill B, Rannie D, Wicks M, Davidson D, Baldock R. eMouseAtlas, EMAGE, and the spatial dimension of the transcriptome. Mamm Genome 2012; 23:514-24. [PMID: 22847374 PMCID: PMC3463796 DOI: 10.1007/s00335-012-9407-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2012] [Accepted: 06/22/2012] [Indexed: 01/10/2023]
Abstract
eMouseAtlas (www.emouseatlas.org) is a comprehensive online resource to visualise mouse development and investigate gene expression in the mouse embryo. We have recently deployed a completely redesigned Mouse Anatomy Atlas website (www.emouseatlas.org/emap/ema) that allows users to view 3D embryo reconstructions, delineated anatomy, and high-resolution histological sections. A new feature of the website is the IIP3D web tool that allows a user to view arbitrary sections of 3D embryo reconstructions using a web browser. This feature provides interactive access to very high-volume 3D images via a tiled pan-and-zoom style interface and circumvents the need to download large image files for visualisation. eMouseAtlas additionally includes EMAGE (Edinburgh Mouse Atlas of Gene Expression) (www.emouseatlas.org/emage), a freely available, curated online database of in situ gene expression patterns, where gene expression domains extracted from raw data images are spatially mapped into atlas embryo models. In this way, EMAGE introduces a spatial dimension to transcriptome data and allows exploration of the spatial similarity between gene expression patterns. New features of the EMAGE interface allow complex queries to be built, and users can view and compare multiple gene expression patterns. EMAGE now includes mapping of 3D gene expression domains captured using the imaging technique optical projection tomography. 3D mapping uses WlzWarp, an open-source software tool developed by eMouseAtlas.
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Affiliation(s)
- Chris Armit
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU, Scotland, UK.
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Harding SD, Armit C, Armstrong J, Brennan J, Cheng Y, Haggarty B, Houghton D, Lloyd-MacGilp S, Pi X, Roochun Y, Sharghi M, Tindal C, McMahon AP, Gottesman B, Little MH, Georgas K, Aronow BJ, Potter SS, Brunskill EW, Southard-Smith EM, Mendelsohn C, Baldock RA, Davies JA, Davidson D. The GUDMAP database--an online resource for genitourinary research. Development 2011; 138:2845-53. [PMID: 21652655 PMCID: PMC3188593 DOI: 10.1242/dev.063594] [Citation(s) in RCA: 183] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
The GenitoUrinary Development Molecular Anatomy Project (GUDMAP) is an international consortium working to generate gene expression data and transgenic mice. GUDMAP includes data from large-scale in situ hybridisation screens (wholemount and section) and microarray gene expression data of microdissected, laser-captured and FACS-sorted components of the developing mouse genitourinary (GU) system. These expression data are annotated using a high-resolution anatomy ontology specific to the developing murine GU system. GUDMAP data are freely accessible at www.gudmap.org via easy-to-use interfaces. This curated, high-resolution dataset serves as a powerful resource for biologists, clinicians and bioinformaticians interested in the developing urogenital system. This paper gives examples of how the data have been used to address problems in developmental biology and provides a primer for those wishing to use the database in their own research.
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Affiliation(s)
- Simon D Harding
- MRC Human Genetics Unit, Western General Hospital, Edinburgh EH4 2XU, UK.
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Armit C, Brown W, Marshall A, Ritchie C. 215 Predictors of increased physical activity levels following participation in a general practice based intervention. J Sci Med Sport 2005. [DOI: 10.1016/s1440-2440(17)30711-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Armit C, Brown W, Marshall A, Ritchie C. 263 Changes in cardiovascular health, well-being and physical activity: results from a 12-week general practice based intervention. J Sci Med Sport 2005. [DOI: 10.1016/s1440-2440(17)30759-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Abstract
The aim of this study was to examine the reliability and validity of field tests for assessing physical function in mid-aged and young-old people (55-70 y). Tests were selected that required minimal space and equipment and could be implemented in multiple field settings such as a general practitioner's office. Nineteen participants completed 2 field and 1 laboratory testing sessions. Intra-class correlations showed good reliability for the tests of upper body strength (lift and reach, R= .66), lower body strength (sit to stand, R = .80) and functional capacity (Canadian Step Test, R= .92), but not for leg power (single timed chair rise. R = .28). There was also good reliability for the balance test during 3 stances: parallel (94.7% agreement), semi-tandem (73.7%), and tandem (52.6%). Comparison of field test results with objective laboratory measures found good validity for the sit to stand (cf 1RM leg press, Pearson r= .68, p < .05), and for the step test (cf PWC140, r = -.60, p < .001), but not for the lift and reach (cf 1RM bench press, r = .43, p > .05), balance (r = -.13, -.18, .23) and rate of force development tests (r = -.28). It was concluded that the lower body strength and cardiovascular function tests were appropriate for use in field settings with mid-aged and young-old adults.
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Affiliation(s)
- C Ritchie
- School of Human Movement Studies, The University of Queensland, Brisbane, Queensland, Australia
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