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Gleeson D, Sethi D, Platte R, Burvill J, Barrett D, Akhtar S, Bruntraeger M, Bottomley J, Mouse Genetics Project S, Bussell J, Ryder E. High-throughput genotyping of high-homology mutant mouse strains by next-generation sequencing. Methods 2021; 191:78-86. [PMID: 33096238 PMCID: PMC8205115 DOI: 10.1016/j.ymeth.2020.10.011] [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: 07/25/2020] [Revised: 09/25/2020] [Accepted: 10/18/2020] [Indexed: 11/05/2022] Open
Abstract
Genotyping of knockout alleles in mice is commonly performed by end-point PCR or gene-specific/universal cassette qPCR. Both have advantages and limitations in terms of assay design and interpretation of results. As an alternative method for high-throughput genotyping, we investigated next generation sequencing (NGS) of PCR amplicons, with a focus on CRISPR-mediated exon deletions where antibiotic selection markers are not present. By multiplexing the wild type and mutant-specific PCR reactions, the genotype can be called by the relative sequence counts of each product. The system is highly scalable and can be applied to a variety of different allele types, including those produced by the International Mouse Phenotyping Consortium and associated projects. One potential challenge with any assay design is locating unique areas of the genome, especially when working with gene families or regions of high homology. These can result in misleading or ambiguous genotypes for either qPCR or end-point assays. Here, we show that genotyping by NGS can negate these issues by simple, automated filtering of undesired sequences. Analysis and genotype calls can also be fully automated, using FASTQ or FASTA input files and an in-house Perl script and SQL database.
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Affiliation(s)
- Diane Gleeson
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Debarati Sethi
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Radka Platte
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Jonathan Burvill
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Daniel Barrett
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Shaheen Akhtar
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Michaela Bruntraeger
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Joanna Bottomley
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | | | - James Bussell
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Edward Ryder
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK.
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2
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Haselimashhadi H, Mason JC, Mallon AM, Smedley D, Meehan TF, Parkinson H. OpenStats: A robust and scalable software package for reproducible analysis of high-throughput phenotypic data. PLoS One 2020; 15:e0242933. [PMID: 33378393 PMCID: PMC7773254 DOI: 10.1371/journal.pone.0242933] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2020] [Accepted: 11/12/2020] [Indexed: 11/19/2022] Open
Abstract
Reproducibility in the statistical analyses of data from high-throughput phenotyping screens requires a robust and reliable analysis foundation that allows modelling of different possible statistical scenarios. Regular challenges are scalability and extensibility of the analysis software. In this manuscript, we describe OpenStats, a freely available software package that addresses these challenges. We show the performance of the software in a high-throughput phenomic pipeline in the International Mouse Phenotyping Consortium (IMPC) and compare the agreement of the results with the most similar implementation in the literature. OpenStats has significant improvements in speed and scalability compared to existing software packages including a 13-fold improvement in computational time to the current production analysis pipeline in the IMPC. Reduced complexity also promotes FAIR data analysis by providing transparency and benefiting other groups in reproducing and re-usability of the statistical methods and results. OpenStats is freely available under a Creative Commons license at www.bioconductor.org/packages/OpenStats.
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Affiliation(s)
- Hamed Haselimashhadi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Jeremy C. Mason
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Ann-Marie Mallon
- MRC Harwell Institute, Harwell Campus, Oxfordshire, United kingdom
| | | | - Terrence F. Meehan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Helen Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
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3
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von Kortzfleisch VT, Karp NA, Palme R, Kaiser S, Sachser N, Richter SH. Improving reproducibility in animal research by splitting the study population into several 'mini-experiments'. Sci Rep 2020; 10:16579. [PMID: 33024165 PMCID: PMC7538440 DOI: 10.1038/s41598-020-73503-4] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 09/11/2020] [Indexed: 01/16/2023] Open
Abstract
In light of the hotly discussed 'reproducibility crisis', a rethinking of current methodologies appears essential. Implementing multi-laboratory designs has been shown to enhance the external validity and hence the reproducibility of findings from animal research. We here aimed at proposing a new experimental strategy that transfers this logic into a single-laboratory setting. We systematically introduced heterogeneity into our study population by splitting an experiment into several 'mini-experiments' spread over different time points a few weeks apart. We hypothesised to observe improved reproducibility in such a 'mini-experiment' design in comparison to a conventionally standardised design, according to which all animals are tested at one specific point in time. By comparing both designs across independent replicates, we could indeed show that the use of such a 'mini-experiment' design improved the reproducibility and accurate detection of exemplary treatment effects (behavioural and physiological differences between four mouse strains) in about half of all investigated strain comparisons. Thus, we successfully implemented and empirically validated an easy-to-handle strategy to tackle poor reproducibility in single-laboratory studies. Since other experiments within different life science disciplines share the main characteristics with the investigation reported here, these studies are likely to also benefit from this approach.
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Affiliation(s)
- Vanessa Tabea von Kortzfleisch
- Department of Behavioural Biology, University of Münster, Badestraße 13, Münster, Germany.
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany.
| | - Natasha A Karp
- Data Sciences and Quantitative Biology, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK
| | - Rupert Palme
- Department of Biomedical Sciences, University of Veterinary Medicine, Vienna, Austria
| | - Sylvia Kaiser
- Department of Behavioural Biology, University of Münster, Badestraße 13, Münster, Germany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
| | - Norbert Sachser
- Department of Behavioural Biology, University of Münster, Badestraße 13, Münster, Germany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
| | - S Helene Richter
- Department of Behavioural Biology, University of Münster, Badestraße 13, Münster, Germany.
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany.
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4
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Hobson L, Bains RS, Greenaway S, Wells S, Nolan PM. Phenotyping in Mice Using Continuous Home Cage Monitoring and Ultrasonic Vocalization Recordings. ACTA ACUST UNITED AC 2020; 10:e80. [PMID: 32813317 DOI: 10.1002/cpmo.80] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Over the last century, the study of mouse behavior has uncovered insights into brain molecular mechanisms while revealing potential causes of many neurological disorders. To this end, researchers have widely exploited the use of mutant strains, including those generated in mutagenesis screens and those produced using increasingly sophisticated genome engineering technologies. It is now relatively easy to access mouse models carrying alleles that faithfully recapitulate changes found in human patients or bearing variants of genes that provide data on those genes' functions. Concurrent with these developments has been an appreciation of the limitations of some current testing platforms, especially those monitoring complex behaviors. Out-of-cage observational testing is useful in describing overt persistent phenotypes but risks missing sporadic or intermittent events. Furthermore, measuring the progression of a phenotype, potentially over many months, can be difficult while relying on assays that may be susceptible to changes in the testing environment. In recent years, there has also been increasing awareness that measurement of behaviors in isolation can be limiting, given that mice attempt to hide behavioral cues of vulnerability. To overcome these limitations, laboratory animal science is capitalizing on progress in data capture and processing expertise. Moreover, as additional recording modes become commonplace, ultrasonic vocalization recording is an appealing focus, as mice use vocalizations in various social contexts. Using video and audio technologies, we record the voluntary, unprovoked behaviors and vocalizations of mice in social groups. Adoption of these approaches is undoubtedly set to increase, as they capture the round-the-clock behavior of mouse strains. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Continuous recording of home cage activity using the Home Cage Analyzer (HCA) system Support Protocol: Subcutaneous insertion of a radio frequency identification microchip in the inguinal area Basic Protocol 2: Continuous recording of mouse ultrasonic vocalizations in the home cage.
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Affiliation(s)
- Liane Hobson
- Medical Research Council Harwell Institute, Harwell, Oxfordshire, United Kingdom
| | - Rasneer S Bains
- Medical Research Council Harwell Institute, Harwell, Oxfordshire, United Kingdom
| | - Simon Greenaway
- Medical Research Council Harwell Institute, Harwell, Oxfordshire, United Kingdom
| | - Sara Wells
- Medical Research Council Harwell Institute, Harwell, Oxfordshire, United Kingdom
| | - Patrick M Nolan
- Medical Research Council Harwell Institute, Harwell, Oxfordshire, United Kingdom
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5
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Marenne G, Hendricks AE, Perdikari A, Bounds R, Payne F, Keogh JM, Lelliott CJ, Henning E, Pathan S, Ashford S, Bochukova EG, Mistry V, Daly A, Hayward C, Wareham NJ, O'Rahilly S, Langenberg C, Wheeler E, Zeggini E, Farooqi IS, Barroso I. Exome Sequencing Identifies Genes and Gene Sets Contributing to Severe Childhood Obesity, Linking PHIP Variants to Repressed POMC Transcription. Cell Metab 2020; 31:1107-1119.e12. [PMID: 32492392 PMCID: PMC7267775 DOI: 10.1016/j.cmet.2020.05.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 03/06/2020] [Accepted: 05/09/2020] [Indexed: 12/12/2022]
Abstract
Obesity is genetically heterogeneous with monogenic and complex polygenic forms. Using exome and targeted sequencing in 2,737 severely obese cases and 6,704 controls, we identified three genes (PHIP, DGKI, and ZMYM4) with an excess burden of very rare predicted deleterious variants in cases. In cells, we found that nuclear PHIP (pleckstrin homology domain interacting protein) directly enhances transcription of pro-opiomelanocortin (POMC), a neuropeptide that suppresses appetite. Obesity-associated PHIP variants repressed POMC transcription. Our demonstration that PHIP is involved in human energy homeostasis through transcriptional regulation of central melanocortin signaling has potential diagnostic and therapeutic implications for patients with obesity and developmental delay. Additionally, we found an excess burden of predicted deleterious variants involving genes nearest to loci from obesity genome-wide association studies. Genes and gene sets influencing obesity with variable penetrance provide compelling evidence for a continuum of causality in the genetic architecture of obesity, and explain some of its missing heritability.
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Affiliation(s)
- Gaëlle Marenne
- Wellcome Sanger Institute, Cambridge, UK; Inserm, Univ Brest, EFS, UMR 1078, GGB, 29200 Brest, France
| | - Audrey E Hendricks
- Wellcome Sanger Institute, Cambridge, UK; Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO, USA
| | - Aliki Perdikari
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Rebecca Bounds
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | | | - Julia M Keogh
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | | | - Elana Henning
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Saad Pathan
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Sofie Ashford
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Elena G Bochukova
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Vanisha Mistry
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Allan Daly
- Wellcome Sanger Institute, Cambridge, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK; Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Nicholas J Wareham
- University of Cambridge MRC Epidemiology Unit, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Stephen O'Rahilly
- MRC Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Claudia Langenberg
- University of Cambridge MRC Epidemiology Unit, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Eleanor Wheeler
- Wellcome Sanger Institute, Cambridge, UK; University of Cambridge MRC Epidemiology Unit, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Eleftheria Zeggini
- Wellcome Sanger Institute, Cambridge, UK; Institute of Translational Genomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - I Sadaf Farooqi
- University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK.
| | - Inês Barroso
- Wellcome Sanger Institute, Cambridge, UK; University of Cambridge MRC Epidemiology Unit, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK.
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6
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Kollmus H, Fuchs H, Lengger C, Haselimashhadi H, Bogue MA, Östereicher MA, Horsch M, Adler T, Aguilar-Pimentel JA, Amarie OV, Becker L, Beckers J, Calzada-Wack J, Garrett L, Hans W, Hölter SM, Klein-Rodewald T, Maier H, Mayer-Kuckuk P, Miller G, Moreth K, Neff F, Rathkolb B, Rácz I, Rozman J, Spielmann N, Treise I, Busch D, Graw J, Klopstock T, Wolf E, Wurst W, Yildirim AÖ, Mason J, Torres A, Balling R, Mehaan T, Gailus-Durner V, Schughart K, Hrabě de Angelis M. A comprehensive and comparative phenotypic analysis of the collaborative founder strains identifies new and known phenotypes. Mamm Genome 2020; 31:30-48. [PMID: 32060626 PMCID: PMC7060152 DOI: 10.1007/s00335-020-09827-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 01/31/2020] [Indexed: 01/21/2023]
Abstract
The collaborative cross (CC) is a large panel of mouse-inbred lines derived from eight founder strains (NOD/ShiLtJ, NZO/HILtJ, A/J, C57BL/6J, 129S1/SvImJ, CAST/EiJ, PWK/PhJ, and WSB/EiJ). Here, we performed a comprehensive and comparative phenotyping screening to identify phenotypic differences and similarities between the eight founder strains. In total, more than 300 parameters including allergy, behavior, cardiovascular, clinical blood chemistry, dysmorphology, bone and cartilage, energy metabolism, eye and vision, immunology, lung function, neurology, nociception, and pathology were analyzed; in most traits from sixteen females and sixteen males. We identified over 270 parameters that were significantly different between strains. This study highlights the value of the founder and CC strains for phenotype-genotype associations of many genetic traits that are highly relevant to human diseases. All data described here are publicly available from the mouse phenome database for analyses and downloads.
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Affiliation(s)
- Heike Kollmus
- Department of Infection Genetics, Helmholtz Centre for Infection Research, Inhoffenstr.7, 38124, Braunschweig, Germany
| | - Helmut Fuchs
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Christoph Lengger
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Hamed Haselimashhadi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | | | - Manuela A Östereicher
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Marion Horsch
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Thure Adler
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Juan Antonio Aguilar-Pimentel
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Oana Veronica Amarie
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Lore Becker
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Johannes Beckers
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Chair of Experimental Genetics, School of Life Science Weihenstephan, Technische Universität München, Alte Akademie 8, 85354, Freising, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Julia Calzada-Wack
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Lillian Garrett
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Wolfgang Hans
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Sabine M Hölter
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Tanja Klein-Rodewald
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Holger Maier
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Philipp Mayer-Kuckuk
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Gregor Miller
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Kristin Moreth
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Frauke Neff
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Birgit Rathkolb
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Institute of Molecular Animal Breeding and Biotechnology, Gene Center, Ludwig-Maximilians-University München, Feodor-Lynen Str. 25, 81377, Munich, Germany
| | - Ildikó Rácz
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Clinic of Neurodegenerative Diseases and Gerontopsychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Jan Rozman
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Nadine Spielmann
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Irina Treise
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Dirk Busch
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München, Trogerstrasse 30, 81675, Munich, Germany
| | - Jochen Graw
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Thomas Klopstock
- Department of Neurology, Friedrich-Baur-Institute, Klinikum Der Ludwig-Maximilians-Universität München, Ziemssenstr. 1a, 80336, Munich, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) Site Munich, Feodor-Lynen-Str. 17, 81377, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Feodor-Lynen-Str. 17, 81377, Munich, Germany
| | - Eckhard Wolf
- Institute of Molecular Animal Breeding and Biotechnology, Gene Center, Ludwig-Maximilians-University München, Feodor-Lynen Str. 25, 81377, Munich, Germany
| | - Wolfgang Wurst
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) Site Munich, Feodor-Lynen-Str. 17, 81377, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Feodor-Lynen-Str. 17, 81377, Munich, Germany
- Chair of Developmental Genetics, Technische Universität München-Weihenstephan, C/O Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Ali Önder Yildirim
- Institute of Lung Biology and Disease, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- German Center for Lung Research, Marburg, Germany
| | - Jeremy Mason
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Arturo Torres
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Rudi Balling
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg, Luxembourg
| | - Terry Mehaan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Valerie Gailus-Durner
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
| | - Klaus Schughart
- Department of Infection Genetics, Helmholtz Centre for Infection Research, Inhoffenstr.7, 38124, Braunschweig, Germany.
- University of Veterinary Medicine Hannover, Hanover, Germany.
- University of Tennessee Health Science Center, Memphis, TN, USA.
| | - Martin Hrabě de Angelis
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Chair of Experimental Genetics, School of Life Science Weihenstephan, Technische Universität München, Alte Akademie 8, 85354, Freising, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
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7
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Abeler-Dörner L, Laing AG, Lorenc A, Ushakov DS, Clare S, Speak AO, Duque-Correa MA, White JK, Ramirez-Solis R, Saran N, Bull KR, Morón B, Iwasaki J, Barton PR, Caetano S, Hng KI, Cambridge E, Forman S, Crockford TL, Griffiths M, Kane L, Harcourt K, Brandt C, Notley G, Babalola KO, Warren J, Mason JC, Meeniga A, Karp NA, Melvin D, Cawthorne E, Weinrick B, Rahim A, Drissler S, Meskas J, Yue A, Lux M, Song-Zhao GX, Chan A, Ballesteros Reviriego C, Abeler J, Wilson H, Przemska-Kosicka A, Edmans M, Strevens N, Pasztorek M, Meehan TF, Powrie F, Brinkman R, Dougan G, Jacobs W, Lloyd CM, Cornall RJ, Maloy KJ, Grencis RK, Griffiths GM, Adams DJ, Hayday AC. High-throughput phenotyping reveals expansive genetic and structural underpinnings of immune variation. Nat Immunol 2020; 21:86-100. [PMID: 31844327 PMCID: PMC7338221 DOI: 10.1038/s41590-019-0549-0] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Accepted: 10/29/2019] [Indexed: 01/28/2023]
Abstract
By developing a high-density murine immunophenotyping platform compatible with high-throughput genetic screening, we have established profound contributions of genetics and structure to immune variation (http://www.immunophenotype.org). Specifically, high-throughput phenotyping of 530 unique mouse gene knockouts identified 140 monogenic 'hits', of which most had no previous immunologic association. Furthermore, hits were collectively enriched in genes for which humans show poor tolerance to loss of function. The immunophenotyping platform also exposed dense correlation networks linking immune parameters with each other and with specific physiologic traits. Such linkages limit freedom of movement for individual immune parameters, thereby imposing genetically regulated 'immunologic structures', the integrity of which was associated with immunocompetence. Hence, we provide an expanded genetic resource and structural perspective for understanding and monitoring immune variation in health and disease.
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Affiliation(s)
| | - Adam G Laing
- Department of Immunobiology, King's College London, London, UK
- The Francis Crick Institute, London, UK
| | - Anna Lorenc
- Department of Immunobiology, King's College London, London, UK
- The Francis Crick Institute, London, UK
| | - Dmitry S Ushakov
- Department of Immunobiology, King's College London, London, UK
- The Francis Crick Institute, London, UK
| | | | | | | | | | | | - Namita Saran
- Department of Immunobiology, King's College London, London, UK
| | | | - Belén Morón
- Sir William Dunn School of Pathology, University of Oxford, Oxford, UK
| | - Jua Iwasaki
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Philippa R Barton
- Cambridge Institute of Medical Research, University of Cambridge, Cambridge, UK
| | - Susana Caetano
- Department of Immunobiology, King's College London, London, UK
- Wellcome Sanger Institute, Hinxton, UK
| | - Keng I Hng
- Department of Immunobiology, King's College London, London, UK
| | | | - Simon Forman
- Lydia Becker Institute of Immunology and Inflammation, Wellcome Trust Centre for Cell Matrix Research, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | | | | | | | | | | | | | - Kolawole O Babalola
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
| | - Jonathan Warren
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
| | - Jeremy C Mason
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
| | - Amrutha Meeniga
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
| | - Natasha A Karp
- Data Sciences & Quantitative Biology, Discovery Sciences, R&D Biopharmaceuticals, AstraZeneca, Cambridge, UK
| | | | | | - Brian Weinrick
- Department of Microbiology and Immunology, Department of Molecular Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Albina Rahim
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - Sibyl Drissler
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - Justin Meskas
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - Alice Yue
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - Markus Lux
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, Canada
| | | | - Anna Chan
- Department of Immunobiology, King's College London, London, UK
| | | | | | | | | | - Matthew Edmans
- MRC Human Immunology Unit, University of Oxford, Oxford, UK
| | | | - Markus Pasztorek
- Department of Immunobiology, King's College London, London, UK
- Department of Biomedical Science, University of Applied Sciences FH Campus Wien, Vienna, Austria
| | - Terrence F Meehan
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, UK
| | - Fiona Powrie
- The Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
| | - Ryan Brinkman
- Terry Fox Laboratory, British Columbia Cancer Agency, Vancouver, BC, Canada
- Department of Bioinformatics, University of British Columbia, Vancouver, BC, Canada
| | | | - William Jacobs
- Department of Microbiology and Immunology, Department of Molecular Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Clare M Lloyd
- National Heart and Lung Institute, Imperial College London, London, UK
| | | | - Kevin J Maloy
- Institute of Infection, Immunity & Inflammation, University of Glasgow, Glasgow, UK
| | - Richard K Grencis
- Lydia Becker Institute of Immunology and Inflammation, Wellcome Trust Centre for Cell Matrix Research, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Gillian M Griffiths
- Cambridge Institute of Medical Research, University of Cambridge, Cambridge, UK
| | | | - Adrian C Hayday
- Department of Immunobiology, King's College London, London, UK.
- The Francis Crick Institute, London, UK.
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8
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Abstract
Purinergic signaling involves extracellular purines and pyrimidines acting upon specific cell surface purinoceptors classified into the P1, P2X, and P2Y families for nucleosides and nucleotides. This widespread signaling mechanism is active in all major tissues and influences a range of functions in health and disease. Orthologs to all but one of the human purinoceptors have been found in mouse, making this laboratory animal a useful model to study their function. Indeed, analyses of purinoceptors via knock-in or knockout approaches to produce gain or loss of function phenotypes have revealed several important therapeutic targets. None of the homozygous purinoceptor knockouts proved to be developmentally lethal, which suggest that either these receptors are not involved in key developmental processes or that the large number of receptors in each family allowed for functional compensation. Different models for the same purinoceptor often show compatible phenotypes but there have been examples of significant discrepancies. These revealed unexpected differences in the structure of human and mouse genes and emphasized the importance of the genetic background of different mouse strains. In this chapter, we provide an overview of the current knowledge and new trends in the modifications of purinoceptor genes in vivo. We discuss the resulting phenotypes, their applications and relative merits and limitations of mouse models available to study purinoceptor subtypes.
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Affiliation(s)
- Robin M H Rumney
- School of Pharmacy and Biomedical Sciences, University of Portsmouth, Portsmouth, UK
| | - Dariusz C Górecki
- School of Pharmacy and Biomedical Sciences, University of Portsmouth, Portsmouth, UK.
- Military Institute of Hygiene and Epidemiology, Warsaw, Poland.
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9
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Keller MP, Rabaglia ME, Schueler KL, Stapleton DS, Gatti DM, Vincent M, Mitok KA, Wang Z, Ishimura T, Simonett SP, Emfinger CH, Das R, Beck T, Kendziorski C, Broman KW, Yandell BS, Churchill GA, Attie AD. Gene loci associated with insulin secretion in islets from non-diabetic mice. J Clin Invest 2019; 129:4419-4432. [PMID: 31343992 DOI: 10.1172/jci129143] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Genetic susceptibility to type 2 diabetes is primarily due to β-cell dysfunction. However, a genetic study to directly interrogate β-cell function ex vivo has never been previously performed. We isolated 233,447 islets from 483 Diversity Outbred (DO) mice maintained on a Western-style diet, and measured insulin secretion in response to a variety of secretagogues. Insulin secretion from DO islets ranged >1,000-fold even though none of the mice were diabetic. The insulin secretory response to each secretagogue had a unique genetic architecture; some of the loci were specific for one condition, whereas others overlapped. Human loci that are syntenic to many of the insulin secretion QTL from mouse are associated with diabetes-related SNPs in human genome-wide association studies. We report on three genes, Ptpn18, Hunk and Zfp148, where the phenotype predictions from the genetic screen were fulfilled in our studies of transgenic mouse models. These three genes encode a non-receptor type protein tyrosine phosphatase, a serine/threonine protein kinase, and a Krϋppel-type zinc-finger transcription factor, respectively. Our results demonstrate that genetic variation in insulin secretion that can lead to type 2 diabetes is discoverable in non-diabetic individuals.
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Affiliation(s)
- Mark P Keller
- University of Wisconsin-Madison, Biochemistry Department, Madison, Wisconsin, USA
| | - Mary E Rabaglia
- University of Wisconsin-Madison, Biochemistry Department, Madison, Wisconsin, USA
| | - Kathryn L Schueler
- University of Wisconsin-Madison, Biochemistry Department, Madison, Wisconsin, USA
| | - Donnie S Stapleton
- University of Wisconsin-Madison, Biochemistry Department, Madison, Wisconsin, USA
| | | | | | - Kelly A Mitok
- University of Wisconsin-Madison, Biochemistry Department, Madison, Wisconsin, USA
| | - Ziyue Wang
- University of Wisconsin-Madison, Department of Biostatistics and Medical Informatics, Madison, Wisconsin, USA
| | | | - Shane P Simonett
- University of Wisconsin-Madison, Biochemistry Department, Madison, Wisconsin, USA
| | | | - Rahul Das
- University of Wisconsin-Madison, Biochemistry Department, Madison, Wisconsin, USA
| | - Tim Beck
- Department of Genetics and Genome Biology, University of Leicester, Leicester, United Kingdom
| | - Christina Kendziorski
- University of Wisconsin-Madison, Department of Biostatistics and Medical Informatics, Madison, Wisconsin, USA
| | - Karl W Broman
- University of Wisconsin-Madison, Department of Biostatistics and Medical Informatics, Madison, Wisconsin, USA
| | - Brian S Yandell
- University of Wisconsin-Madison, Department of Horticulture, Madison, Wisconsin, USA
| | | | - Alan D Attie
- University of Wisconsin-Madison, Biochemistry Department, Madison, Wisconsin, USA
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10
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Ingham NJ, Pearson SA, Vancollie VE, Rook V, Lewis MA, Chen J, Buniello A, Martelletti E, Preite L, Lam CC, Weiss FD, Powis Z, Suwannarat P, Lelliott CJ, Dawson SJ, White JK, Steel KP. Mouse screen reveals multiple new genes underlying mouse and human hearing loss. PLoS Biol 2019; 17:e3000194. [PMID: 30973865 PMCID: PMC6459510 DOI: 10.1371/journal.pbio.3000194] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 03/07/2019] [Indexed: 11/23/2022] Open
Abstract
Adult-onset hearing loss is very common, but we know little about the underlying molecular pathogenesis impeding the development of therapies. We took a genetic approach to identify new molecules involved in hearing loss by screening a large cohort of newly generated mouse mutants using a sensitive electrophysiological test, the auditory brainstem response (ABR). We review here the findings from this screen. Thirty-eight unexpected genes associated with raised thresholds were detected from our unbiased sample of 1,211 genes tested, suggesting extreme genetic heterogeneity. A wide range of auditory pathophysiologies was found, and some mutant lines showed normal development followed by deterioration of responses, revealing new molecular pathways involved in progressive hearing loss. Several of the genes were associated with the range of hearing thresholds in the human population and one, SPNS2, was involved in childhood deafness. The new pathways required for maintenance of hearing discovered by this screen present new therapeutic opportunities. This study uses an electrophysiological screen of over a thousand new mutant mouse lines to identify 38 new genes underlying deafness, some associated with human hearing function, revealing a wide range of molecular and pathological mechanisms. Progressive hearing loss with age is extremely common in the population, leading to difficulties in understanding speech, increased social isolation, and associated depression. We know it has a significant heritability, but so far we know very little about the molecular pathways leading to hearing loss, hampering the development of treatments. Here, we describe a large-scale screen of 1,211 new targeted mouse mutant lines, resulting in the identification of 38 genes underlying hearing loss that were not previously suspected of involvement in hearing. Some of these genes reveal molecular pathways that may be useful targets for drug development. Our further analysis of the genes identified and the varied pathological mechanisms within the ear resulting from the mutations suggests that hearing loss is an extremely heterogeneous disorder and may have as many as 1,000 genes involved.
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Affiliation(s)
- Neil J. Ingham
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | | | | | - Victoria Rook
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Morag A. Lewis
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Jing Chen
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Annalisa Buniello
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Elisa Martelletti
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Lorenzo Preite
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Chi Chung Lam
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Felix D. Weiss
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Zӧe Powis
- Department of Emerging Genetics Medicine, Ambry Genetics, Aliso Viejo, California, United States of America
| | - Pim Suwannarat
- Mid-Atlantic Permanente Medical Group, Rockville, Maryland, United States of America
| | | | - Sally J. Dawson
- UCL Ear Institute, University College London, London, United Kingdom
| | | | - Karen P. Steel
- Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Wolfson Centre for Age-Related Diseases, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- * E-mail:
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11
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Balmus G, Larrieu D, Barros AC, Collins C, Abrudan M, Demir M, Geisler NJ, Lelliott CJ, White JK, Karp NA, Atkinson J, Kirton A, Jacobsen M, Clift D, Rodriguez R, Adams DJ, Jackson SP. Targeting of NAT10 enhances healthspan in a mouse model of human accelerated aging syndrome. Nat Commun 2018; 9:1700. [PMID: 29703891 PMCID: PMC5923383 DOI: 10.1038/s41467-018-03770-3] [Citation(s) in RCA: 96] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Accepted: 03/12/2018] [Indexed: 02/02/2023] Open
Abstract
Hutchinson-Gilford Progeria Syndrome (HGPS) is a rare, but devastating genetic disease characterized by segmental premature aging, with cardiovascular disease being the main cause of death. Cells from HGPS patients accumulate progerin, a permanently farnesylated, toxic form of Lamin A, disrupting the nuclear shape and chromatin organization, leading to DNA-damage accumulation and senescence. Therapeutic approaches targeting farnesylation or aiming to reduce progerin levels have provided only partial health improvements. Recently, we identified Remodelin, a small-molecule agent that leads to amelioration of HGPS cellular defects through inhibition of the enzyme N-acetyltransferase 10 (NAT10). Here, we show the preclinical data demonstrating that targeting NAT10 in vivo, either via chemical inhibition or genetic depletion, significantly enhances the healthspan in a Lmna G609G HGPS mouse model. Collectively, the data provided here highlights NAT10 as a potential therapeutic target for HGPS.
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Affiliation(s)
- Gabriel Balmus
- The Wellcome Trust/Cancer Research UK Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QN, UK
- The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Delphine Larrieu
- The Wellcome Trust/Cancer Research UK Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QN, UK.
- Department of Clinical Biochemistry, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, CB2 0XY, UK.
| | - Ana C Barros
- The Wellcome Trust/Cancer Research UK Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QN, UK
- The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Casey Collins
- The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Monica Abrudan
- The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Mukerrem Demir
- The Wellcome Trust/Cancer Research UK Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QN, UK
| | - Nicola J Geisler
- The Wellcome Trust/Cancer Research UK Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QN, UK
- The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | | | | | - Natasha A Karp
- The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
- Discovery Sciences, IMED Biotech Unit, AstraZeneca, Cambridge, CB4 0WG, UK
| | - James Atkinson
- Drug Safety and Metabolism, IMED Biotech Unit, AstraZeneca, Cambridge, CB2 23AT, UK
| | - Andrea Kirton
- The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Matt Jacobsen
- Drug Safety and Metabolism, IMED Biotech Unit, AstraZeneca, Cambridge, CB2 23AT, UK
| | - Dean Clift
- Laboratory of Molecular Biology, Cambridge, CB2 OQH, UK
| | - Raphael Rodriguez
- Institut Curie, PSL Research University, Paris Cedex 05, France
- CNRS UMR3666, 75005, Paris, France
- INSERM U1143, 75005, Paris, France
| | - David J Adams
- The Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
| | - Stephen P Jackson
- The Wellcome Trust/Cancer Research UK Gurdon Institute and Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QN, UK.
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12
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André V, Gau C, Scheideler A, Aguilar-Pimentel JA, Amarie OV, Becker L, Garrett L, Hans W, Hölter SM, Janik D, Moreth K, Neff F, Östereicher M, Racz I, Rathkolb B, Rozman J, Bekeredjian R, Graw J, Klingenspor M, Klopstock T, Ollert M, Schmidt-Weber C, Wolf E, Wurst W, Gailus-Durner V, Brielmeier M, Fuchs H, Hrabé de Angelis M. Laboratory mouse housing conditions can be improved using common environmental enrichment without compromising data. PLoS Biol 2018; 16:e2005019. [PMID: 29659570 PMCID: PMC5922977 DOI: 10.1371/journal.pbio.2005019] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Revised: 04/27/2018] [Accepted: 03/09/2018] [Indexed: 01/03/2023] Open
Abstract
Animal welfare requires the adequate housing of animals to ensure health and well-being. The application of environmental enrichment is a way to improve the well-being of laboratory animals. However, it is important to know whether these enrichment items can be incorporated in experimental mouse husbandry without creating a divide between past and future experimental results. Previous small-scale studies have been inconsistent throughout the literature, and it is not yet completely understood whether and how enrichment might endanger comparability of results of scientific experiments. Here, we measured the effect on means and variability of 164 physiological parameters in 3 conditions: with nesting material with or without a shelter, comparing these 2 conditions to a “barren” regime without any enrichments. We studied a total of 360 mice from each of 2 mouse strains (C57BL/6NTac and DBA/2NCrl) and both sexes for each of the 3 conditions. Our study indicates that enrichment affects the mean values of some of the 164 parameters with no consistent effects on variability. However, the influence of enrichment appears negligible compared to the effects of other influencing factors. Therefore, nesting material and shelters may be used to improve animal welfare without impairment of experimental outcome or loss of comparability to previous data collected under barren housing conditions. Adequate housing of laboratory animals is essential to guarantee their well-being. From a scientific perspective, physically and mentally healthy animals also contribute to increased validity and reproducibility of experimental results. The choice of nesting material or shelter type, referred to as environmental enrichment, may influence how laboratory animals perform species-specific behaviors. Consequently, changes in these nesting and shelter materials could influence scientific results by, for example, increasing variability in measured characteristics. Whether studies using different environmental enrichment materials can be compared is currently questioned. Our study shows that simple, species-specific environmental enrichment in the form of nesting material alone or in combination with a shelter did not consistently increase variability of physiological parameters in mice. Differences in parameter average values appeared to be of minor biological relevance when compared to the effects of other environmental factors. These simple environmental enrichment devices may therefore be applied to improve the housing environment of laboratory mice without compromising data validity or comparability.
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Affiliation(s)
- Viola André
- Research Unit Comparative Medicine, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- * E-mail:
| | - Christine Gau
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Angelika Scheideler
- Research Unit Comparative Medicine, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Juan A. Aguilar-Pimentel
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Oana V. Amarie
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lore Becker
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lillian Garrett
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Wolfgang Hans
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Sabine M. Hölter
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Dirk Janik
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Pathology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Kristin Moreth
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Frauke Neff
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Pathology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Manuela Östereicher
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Ildiko Racz
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Molecular Psychiatry, University of Bonn, Bonn, Germany
| | - Birgit Rathkolb
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Molecular Animal Breeding and Biotechnology, Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Jan Rozman
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Raffi Bekeredjian
- Department of Cardiology, University of Heidelberg, Heidelberg, Germany
| | - Jochen Graw
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Martin Klingenspor
- Molecular Nutritional Medicine, Else Kröner-Fresenius Center, Technische Universität München, Freising-Weihenstephan, Germany
- ZIEL—Center for Nutrition and Food Sciences, Technische Universität München, Freising, Germany
| | - Thomas Klopstock
- Department of Neurology, Friedrich-Baur-Institute, Klinikum der Ludwig-Maximilians-Universität München, Munich, Germany
- Deutsches Institut für Neurodegenerative Erkrankungen (DZNE), Site Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Markus Ollert
- Department of Dermatology and Allergy Center, Odense Research Center for Anaphylaxis (ORCA), Odense University hospital, University of Southern Denmark, Odense C, Denmark
- Department of Infection and Immunity, Luxembourg Institute of Health (LIH), Esch-sur-Alzette, Luxembourg
| | - Carsten Schmidt-Weber
- Center of Allergy & Environment (ZAUM), Technische Universität München and Helmholtz Zentrum München, Munich, Germany and Member of the German Center for Lung Research (DZL), Gießen, Germany
| | - Eckhard Wolf
- Institute of Molecular Animal Breeding and Biotechnology, Gene Center, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Wolfgang Wurst
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Deutsches Institut für Neurodegenerative Erkrankungen (DZNE), Site Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Munich, Germany
- Technische Universität München, Freising-Weihenstephan, Chair of Developmental Genetics, c/o Helmholtz Zentrum München, Neuherberg, Germany
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Valérie Gailus-Durner
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Markus Brielmeier
- Research Unit Comparative Medicine, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Helmut Fuchs
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Martin Hrabé de Angelis
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- Chair of Experimental Genetics, School of Life Science Weihenstephan, Technische Universität München, Freising, Germany
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13
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Watson RA, Gates AS, Wynn EH, Calvert FE, Girousse A, Lelliott CJ, Barroso I. Lyplal1 is dispensable for normal fat deposition in mice. Dis Model Mech 2017; 10:1481-1488. [PMID: 29084768 PMCID: PMC5769613 DOI: 10.1242/dmm.031864] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2017] [Accepted: 10/17/2017] [Indexed: 12/13/2022] Open
Abstract
Genome-wide association studies (GWAS) have detected association between variants in or near the Lysophospholipase-like 1 (LYPLAL1) locus and metabolic traits, including central obesity, fatty liver and waist-to-hip ratio. LYPLAL1 is also known to be upregulated in the adipose tissue of obese patients. However, the physiological role of LYPLAL1 is not understood. To investigate the function of Lyplal1 in vivo we investigated the phenotype of the Lyplal1tm1a(KOMP)Wtsi homozygous mouse. Body composition was unaltered in Lyplal1 knockout mice as assessed by dual-energy X-ray absorptiometry (DEXA) scanning, both on normal chow and on a high-fat diet. Adipose tissue distribution between visceral and subcutaneous fat depots was unaltered, with no change in adipocyte cell size. The response to both insulin and glucose dosing was normal in Lyplal1tm1a(KOMP)Wtsi homozygous mice, with normal fasting blood glucose concentrations. RNAseq analysis of liver, muscle and adipose tissue confirmed that Lyplal1 expression was ablated with minimal additional changes in gene expression. These results suggest that Lyplal1 is dispensable for normal mouse metabolic physiology and that despite having been maintained through evolution Lyplal1 is not an essential gene, suggesting possible functional redundancy. Further studies will be required to clarify its physiological role.
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Affiliation(s)
- Rachel A Watson
- Human Genetics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Amy S Gates
- Human Genetics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK.,Department of Medical Genetics, Cambridge Institute for Medical Research, Medical Genetics, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0XY, UK
| | - Elizabeth H Wynn
- Human Genetics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Fiona E Calvert
- Human Genetics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Amandine Girousse
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK.,Université de Toulouse, Inserm U1031, CHU Rangueil, Batiment L1, BP 84225, 31 432 Toulouse, France
| | - Christopher J Lelliott
- Human Genetics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Inês Barroso
- Human Genetics, Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK .,Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK
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14
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A high-throughput in vivo screening method in the mouse for identifying regulators of metastatic colonization. Nat Protoc 2017; 12:2465-2477. [PMID: 29095442 DOI: 10.1038/nprot.2017.118] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
We describe a sensitive, robust, high-throughput method for quantifying the ability of metastatic tumor cells to colonize a secondary organ. Metastasis is the leading cause of death in cancer patients, and successful colonization of the secondary organ is the rate-limiting step in the metastatic process; thus, experimental methods that can be used to interrogate the key factors required for this critical step are of great importance. The experimental metastasis assay we detail here includes tail-vein injection of cancer cells into the mouse and determination of the resulting secondary organ colonization, primarily in the lung, 10 d post dosing. This assay can be used to investigate factors that regulate metastatic colonization both at the tumor-cell-intrinsic level (via manipulation of the tumor cells before injection) and at the tumor-cell-extrinsic level (such as the tissue microenvironment, via the use of genetically modified (GM) mice or agents such as antibodies or drugs). Using this method, we have robustly screened more than 950 GM mouse lines to identify novel microenvironmental regulators of metastatic colonization. The experimental details discussed here include choosing of appropriate cell numbers, handling of the cells, selection of recipient animals and injection techniques. Furthermore, we discuss key experimental design considerations, including the choice of the method used to determine metastatic burden and statistical analysis of the results, as well as provide troubleshooting tips and identification of factors that contribute to experimental variability.
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15
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WD40-repeat 47, a microtubule-associated protein, is essential for brain development and autophagy. Proc Natl Acad Sci U S A 2017; 114:E9308-E9317. [PMID: 29078390 DOI: 10.1073/pnas.1713625114] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
The family of WD40-repeat (WDR) proteins is one of the largest in eukaryotes, but little is known about their function in brain development. Among 26 WDR genes assessed, we found 7 displaying a major impact in neuronal morphology when inactivated in mice. Remarkably, all seven genes showed corpus callosum defects, including thicker (Atg16l1, Coro1c, Dmxl2, and Herc1), thinner (Kif21b and Wdr89), or absent corpus callosum (Wdr47), revealing a common role for WDR genes in brain connectivity. We focused on the poorly studied WDR47 protein sharing structural homology with LIS1, which causes lissencephaly. In a dosage-dependent manner, mice lacking Wdr47 showed lethality, extensive fiber defects, microcephaly, thinner cortices, and sensory motor gating abnormalities. We showed that WDR47 shares functional characteristics with LIS1 and participates in key microtubule-mediated processes, including neural stem cell proliferation, radial migration, and growth cone dynamics. In absence of WDR47, the exhaustion of late cortical progenitors and the consequent decrease of neurogenesis together with the impaired survival of late-born neurons are likely yielding to the worsening of the microcephaly phenotype postnatally. Interestingly, the WDR47-specific C-terminal to LisH (CTLH) domain was associated with functions in autophagy described in mammals. Silencing WDR47 in hypothalamic GT1-7 neuronal cells and yeast models independently recapitulated these findings, showing conserved mechanisms. Finally, our data identified superior cervical ganglion-10 (SCG10) as an interacting partner of WDR47. Taken together, these results provide a starting point for studying the implications of WDR proteins in neuronal regulation of microtubules and autophagy.
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16
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Systematic heterogenization for better reproducibility in animal experimentation. Lab Anim (NY) 2017; 46:343-349. [DOI: 10.1038/laban.1330] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2017] [Accepted: 05/15/2017] [Indexed: 11/09/2022]
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17
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Meehan TF, Conte N, West DB, Jacobsen JO, Mason J, Warren J, Chen CK, Tudose I, Relac M, Matthews P, Karp N, Santos L, Fiegel T, Ring N, Westerberg H, Greenaway S, Sneddon D, Morgan H, Codner GF, Stewart ME, Brown J, Horner N, Haendel M, Washington N, Mungall CJ, Reynolds CL, Gallegos J, Gailus-Durner V, Sorg T, Pavlovic G, Bower LR, Moore M, Morse I, Gao X, Tocchini-Valentini GP, Obata Y, Cho SY, Seong JK, Seavitt J, Beaudet AL, Dickinson ME, Herault Y, Wurst W, de Angelis MH, Lloyd KK, Flenniken AM, Nutter LMJ, Newbigging S, McKerlie C, Justice MJ, Murray SA, Svenson KL, Braun RE, White JK, Bradley A, Flicek P, Wells S, Skarnes WC, Adams DJ, Parkinson H, Mallon AM, Brown SD, Smedley D. Disease model discovery from 3,328 gene knockouts by The International Mouse Phenotyping Consortium. Nat Genet 2017; 49:1231-1238. [PMID: 28650483 PMCID: PMC5546242 DOI: 10.1038/ng.3901] [Citation(s) in RCA: 163] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2016] [Accepted: 05/25/2017] [Indexed: 12/12/2022]
Abstract
Although next-generation sequencing has revolutionized the ability to associate variants with human diseases, diagnostic rates and development of new therapies are still limited by a lack of knowledge of the functions and pathobiological mechanisms of most genes. To address this challenge, the International Mouse Phenotyping Consortium is creating a genome- and phenome-wide catalog of gene function by characterizing new knockout-mouse strains across diverse biological systems through a broad set of standardized phenotyping tests. All mice will be readily available to the biomedical community. Analyzing the first 3,328 genes identified models for 360 diseases, including the first models, to our knowledge, for type C Bernard-Soulier, Bardet-Biedl-5 and Gordon Holmes syndromes. 90% of our phenotype annotations were novel, providing functional evidence for 1,092 genes and candidates in genetically uncharacterized diseases including arrhythmogenic right ventricular dysplasia 3. Finally, we describe our role in variant functional validation with The 100,000 Genomes Project and others.
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Affiliation(s)
- Terrence F. Meehan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Nathalie Conte
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - David B. West
- Children’s Hospital Oakland Research Institute, Oakland, California 94609, USA
| | - Julius O. Jacobsen
- William Harvey Research Institute, Queen Mary University of London, London, E1 4NS, UK
| | - Jeremy Mason
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jonathan Warren
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Chao-Kung Chen
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ilinca Tudose
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Mike Relac
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Peter Matthews
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Natasha Karp
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Luis Santos
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Tanja Fiegel
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Natalie Ring
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Henrik Westerberg
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Simon Greenaway
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Duncan Sneddon
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Hugh Morgan
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Gemma F Codner
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Michelle E Stewart
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - James Brown
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Neil Horner
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | | | - Melissa Haendel
- Department of Medical Informatics and Clinical Epidemiology and OHSU Library, Oregon Health & Science University, Portland, OR, 97239, USA
| | - Nicole Washington
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Christopher J. Mungall
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Corey L Reynolds
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Juan Gallegos
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Valerie Gailus-Durner
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Experimental Genetics, Neuherberg 85764, Germany
| | - Tania Sorg
- CELPHEDIA, PHENOMIN, Institut Clinique de la Souris (ICS), 1 rue Laurent Fries, F-67404 Illkirch-Graffenstaden, France
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg, Illkirch, France
- Centre National de la Recherche Scientifique, UMR7104, Illkirch, France
- Institut National de la Santé et de la Recherche Médicale, U964, Illkirch, France
| | - Guillaume Pavlovic
- CELPHEDIA, PHENOMIN, Institut Clinique de la Souris (ICS), 1 rue Laurent Fries, F-67404 Illkirch-Graffenstaden, France
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg, Illkirch, France
- Centre National de la Recherche Scientifique, UMR7104, Illkirch, France
- Institut National de la Santé et de la Recherche Médicale, U964, Illkirch, France
| | - Lynette R Bower
- Mouse Biology Program, University of California, Davis, California 95618, USA
| | - Mark Moore
- IMPC, San Anselmo, California 94960, USA
| | - Iva Morse
- Charles River Laboratories, Wilmington, Massachusetts 01887, USA
| | - Xiang Gao
- SKL of Pharmaceutical Biotechnology and Model Animal Research Center, Collaborative Innovation Center for Genetics and Development, Nanjing Biomedical Research Institute, Nanjing University, Nanjing 210061, China
| | - Glauco P Tocchini-Valentini
- Monterotondo Mouse Clinic, Italian National Research Council (CNR), Institute of Cell Biology and Neurobiology, Monterotondo Scalo I-00015, Italy
| | - Yuichi Obata
- RIKEN BioResource Center, Tsukuba, Ibaraki 305-0074, Japan
| | - Soo Young Cho
- Korea Mouse Phenotyping Center, 08826, Republic of Korea
- National Cancer Center, Goyang, Gyeonggi, 10408, Republic of Korea
| | - Je Kyung Seong
- Korea Mouse Phenotyping Center, 08826, Republic of Korea
- Research Institute for Veterinary Science, Seoul National University, Republic of Korea
| | - John Seavitt
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Arthur L. Beaudet
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Mary E. Dickinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA
| | - Yann Herault
- CELPHEDIA, PHENOMIN, Institut Clinique de la Souris (ICS), 1 rue Laurent Fries, F-67404 Illkirch-Graffenstaden, France
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg, Illkirch, France
- Centre National de la Recherche Scientifique, UMR7104, Illkirch, France
- Institut National de la Santé et de la Recherche Médicale, U964, Illkirch, France
| | - Wolfgang Wurst
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Experimental Genetics, Neuherberg 85764, Germany
| | - Martin Hrabe de Angelis
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Experimental Genetics, Neuherberg 85764, Germany
| | - K.C. Kent Lloyd
- Mouse Biology Program, University of California, Davis, California 95618, USA
| | - Ann M Flenniken
- The Centre for Phenogenomics, Toronto, Ontario M5T 3H7, Canada
| | | | | | - Colin McKerlie
- The Centre for Phenogenomics, Toronto, Ontario M5T 3H7, Canada
| | - Monica J. Justice
- Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Ontario M5T 3H7, Canada
| | | | | | | | - Jacqueline K. White
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Allan Bradley
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Sara Wells
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - William C. Skarnes
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - David J. Adams
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Helen Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ann-Marie Mallon
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Steve D.M. Brown
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK
| | - Damian Smedley
- William Harvey Research Institute, Queen Mary University of London, London, E1 4NS, UK
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18
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Karp NA, Mason J, Beaudet AL, Benjamini Y, Bower L, Braun RE, Brown SDM, Chesler EJ, Dickinson ME, Flenniken AM, Fuchs H, Angelis MHD, Gao X, Guo S, Greenaway S, Heller R, Herault Y, Justice MJ, Kurbatova N, Lelliott CJ, Lloyd KCK, Mallon AM, Mank JE, Masuya H, McKerlie C, Meehan TF, Mott RF, Murray SA, Parkinson H, Ramirez-Solis R, Santos L, Seavitt JR, Smedley D, Sorg T, Speak AO, Steel KP, Svenson KL, Wakana S, West D, Wells S, Westerberg H, Yaacoby S, White JK. Prevalence of sexual dimorphism in mammalian phenotypic traits. Nat Commun 2017. [PMID: 28650954 PMCID: PMC5490203 DOI: 10.1038/ncomms15475] [Citation(s) in RCA: 162] [Impact Index Per Article: 23.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
The role of sex in biomedical studies has often been overlooked, despite evidence of sexually dimorphic effects in some biological studies. Here, we used high-throughput phenotype data from 14,250 wildtype and 40,192 mutant mice (representing 2,186 knockout lines), analysed for up to 234 traits, and found a large proportion of mammalian traits both in wildtype and mutants are influenced by sex. This result has implications for interpreting disease phenotypes in animal models and humans. Systemic dissection of sexually dimorphic phenotypes in mice is lacking. Here, Karp and the International Mouse Phenotype Consortium show that approximately 10% of qualitative traits and 56% of quantitative traits in mice as measured in laboratory setting are sexually dimorphic.
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Affiliation(s)
- Natasha A Karp
- Mouse Informatics Group, The Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK.,Quantitative Biology, AstraZeneca, Unit 310, Cambridge Science Park, Cambridge CB4 0WG, UK
| | - Jeremy Mason
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Arthur L Beaudet
- Human and Molecular Genetics, Baylor College of Medicine, 1 Baylor Plaza, Houston, Texas 77030, USA
| | - Yoav Benjamini
- Department of Statistics and O.R. School of Mathematical Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Lynette Bower
- Mouse Biology Program, University of California, 2795 Second Street, Suite 400, Davis, California 95618, USA
| | - Robert E Braun
- The Jackson Laboratory, 600 Main Street, Bar Harbor, Maine 04609, USA
| | | | - Elissa J Chesler
- The Jackson Laboratory, 600 Main Street, Bar Harbor, Maine 04609, USA
| | - Mary E Dickinson
- Molecular Physiology and Biophysics, Baylor College of Medicine, 1 Baylor Plaza, Houston, Texas 77030, USA
| | - Ann M Flenniken
- The Centre for Phenogenomics, 25 Orde Street, Toronto, Ontario, Canada M5T 3H7
| | - Helmut Fuchs
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg 85764, Germany
| | - Martin Hrabe de Angelis
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, Ingolstädter Landstraße 1, Neuherberg 85764, Germany.,School of Life Science Weihenstephan, Technische Universität München, Alte Akademie 8, Freising 85354, Germany.,German Center for Diabetes Research (DZD), Ingostädter Landstr. 1, Neuherberg 85764, Germany
| | - Xiang Gao
- Model Animal Research Center, Nanjing University, 12 Xuefu Road, Pukou, Nanjing, Jiangsu 210061, China
| | - Shiying Guo
- Model Animal Research Center, Nanjing University, 12 Xuefu Road, Pukou, Nanjing, Jiangsu 210061, China
| | | | - Ruth Heller
- Department of Statistics and O.R. School of Mathematical Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Yann Herault
- CELPHEDIA, PHENOMIN, Institut Clinique de la Souris, 1 Rue Laurent Fries, Illkirch 67404, France.,Institut de Génétique et de Biologie Moléculaire et Cellulaire, 1 Rue Laurent Fries, Illkirch 67404, France.,Centre National de la Recherche Scientifique, UMR7104, 1 rue Laurent Fries, Illkirch 67404, France.,Institut National de la Santé et de la Recherche Médicale, U964, 1 rue Laurent Fries, Illkirch 67404, France.,Université de Strasbourg, 1 rue Laurent Fries, Illkirch 67404, France
| | - Monica J Justice
- The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, Canada M5G 1X8
| | - Natalja Kurbatova
- Department of Statistics and O.R. School of Mathematical Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Christopher J Lelliott
- Mouse Genetics Project, The Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - K C Kent Lloyd
- Mouse Biology Program, University of California, 2795 Second Street, Suite 400, Davis, California 95618, USA
| | | | - Judith E Mank
- Department of Genetics, Evolution &Environment, University College London, Gower Street, London WC1E 6BT, UK
| | - Hiroshi Masuya
- BioResource Center, RIKEN, 3-1-1 Koyadai, Tsukuba, Ibaraki 305-0074, Japan
| | - Colin McKerlie
- The Centre for Phenogenomics, 25 Orde Street, Toronto, Ontario, Canada M5T 3H7.,The Hospital for Sick Children, 686 Bay Street, Toronto, Ontario, Canada M5G 0A4
| | - Terrence F Meehan
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Richard F Mott
- Genetics Institute, University College London, Gower Street, London WC1E 6BT, UK
| | - Stephen A Murray
- The Jackson Laboratory, 600 Main Street, Bar Harbor, Maine 04609, USA
| | - Helen Parkinson
- European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ramiro Ramirez-Solis
- Mouse Genetics Project, The Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Luis Santos
- MRC Harwell Institute, Harwell Campus, Harwell OX11 0RD, UK
| | - John R Seavitt
- Human and Molecular Genetics, Baylor College of Medicine, 1 Baylor Plaza, Houston, Texas 77030, USA
| | - Damian Smedley
- Clinical Pharmacology, Queen Mary University of London, Gower Street, London WC1E 6BT, UK
| | - Tania Sorg
- CELPHEDIA, PHENOMIN, Institut Clinique de la Souris, 1 Rue Laurent Fries, Illkirch 67404, France.,Institut de Génétique et de Biologie Moléculaire et Cellulaire, 1 Rue Laurent Fries, Illkirch 67404, France.,Centre National de la Recherche Scientifique, UMR7104, 1 rue Laurent Fries, Illkirch 67404, France.,Institut National de la Santé et de la Recherche Médicale, U964, 1 rue Laurent Fries, Illkirch 67404, France.,Université de Strasbourg, 1 rue Laurent Fries, Illkirch 67404, France
| | - Anneliese O Speak
- Mouse Genetics Project, The Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
| | - Karen P Steel
- Mouse Genetics Project, The Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK.,Wolfson Centre for Age-Related Diseases, King's College London, Wolfson Wing, Hodgkin Building, Guys Campus, London SE1 1UL, UK
| | - Karen L Svenson
- The Jackson Laboratory, 600 Main Street, Bar Harbor, Maine 04609, USA
| | | | - Shigeharu Wakana
- BioResource Center, RIKEN, 3-1-1 Koyadai, Tsukuba, Ibaraki 305-0074, Japan
| | - David West
- Children's Hospital Oakland Research Institute, 5700 Martin Luther King Jr Way, Oakland, California 94609, USA
| | - Sara Wells
- MRC Harwell Institute, Harwell Campus, Harwell OX11 0RD, UK
| | | | - Shay Yaacoby
- Department of Statistics and O.R. School of Mathematical Sciences, Tel Aviv University, Tel Aviv 69978, Israel
| | - Jacqueline K White
- The Jackson Laboratory, 600 Main Street, Bar Harbor, Maine 04609, USA.,Mouse Genetics Project, The Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1SA, UK
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19
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Ingvorsen C, Karp NA, Lelliott CJ. The role of sex and body weight on the metabolic effects of high-fat diet in C57BL/6N mice. Nutr Diabetes 2017; 7:e261. [PMID: 28394359 PMCID: PMC5436097 DOI: 10.1038/nutd.2017.6] [Citation(s) in RCA: 66] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 01/11/2017] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Metabolic disorders are commonly investigated using knockout and transgenic mouse models on the C57BL/6N genetic background due to its genetic susceptibility to the deleterious metabolic effects of high-fat diet (HFD). There is growing awareness of the need to consider sex in disease progression, but limited attention has been paid to sexual dimorphism in mouse models and its impact in metabolic phenotypes. We assessed the effect of HFD and the impact of sex on metabolic variables in this strain. METHODS We generated a reference data set encompassing glucose tolerance, body composition and plasma chemistry data from 586 C57BL/6N mice fed a standard chow and 733 fed a HFD collected as part of a high-throughput phenotyping pipeline. Linear mixed model regression analysis was used in a dual analysis to assess the effect of HFD as an absolute change in phenotype, but also as a relative change accounting for the potential confounding effect of body weight. RESULTS HFD had a significant impact on all variables tested with an average absolute effect size of 29%. For the majority of variables (78%), the treatment effect was modified by sex and this was dominated by male-specific or a male stronger effect. On average, there was a 13.2% difference in the effect size between the male and female mice for sexually dimorphic variables. HFD led to a significant body weight phenotype (24% increase), which acts as a confounding effect on the other analysed variables. For 79% of the variables, body weight was found to be a significant source of variation, but even after accounting for this confounding effect, similar HFD-induced phenotypic changes were found to when not accounting for weight. CONCLUSION HFD and sex are powerful modifiers of metabolic parameters in C57BL/6N mice. We also demonstrate the value of considering body size as a covariate to obtain a richer understanding of metabolic phenotypes.
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Affiliation(s)
- C Ingvorsen
- Mouse Pipelines, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK
- University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Robinson Way, Cambridge, UK
| | - N A Karp
- Mouse Informatics Group, Wellcome Trust Sanger Institute, Cambridge, UK
| | - C J Lelliott
- Mouse Pipelines, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK
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van de Lagemaat LN, Stanford LE, Pettit CM, Strathdee DJ, Strathdee KE, Elsegood KA, Fricker DG, Croning MDR, Komiyama NH, Grant SGN. Standardized experiments in mutant mice reveal behavioural similarity on 129S5 and C57BL/6J backgrounds. GENES BRAIN AND BEHAVIOR 2017; 16:409-418. [DOI: 10.1111/gbb.12364] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2016] [Revised: 09/12/2016] [Accepted: 11/21/2016] [Indexed: 01/27/2023]
Affiliation(s)
- L. N. van de Lagemaat
- Centre for Clinical Brain Sciences, Chancellor's Building; University of Edinburgh; Edinburgh UK
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
| | - L. E. Stanford
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
| | - C. M. Pettit
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
| | - D. J. Strathdee
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
- Transgenic Technology Division; CRUK Beatson Institute; Glasgow UK
| | - K. E. Strathdee
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
| | - K. A. Elsegood
- Centre for Clinical Brain Sciences, Chancellor's Building; University of Edinburgh; Edinburgh UK
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
| | - D. G. Fricker
- Centre for Clinical Brain Sciences, Chancellor's Building; University of Edinburgh; Edinburgh UK
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
| | - M. D. R. Croning
- Centre for Clinical Brain Sciences, Chancellor's Building; University of Edinburgh; Edinburgh UK
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
| | - N. H. Komiyama
- Centre for Clinical Brain Sciences, Chancellor's Building; University of Edinburgh; Edinburgh UK
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
| | - S. G. N. Grant
- Centre for Clinical Brain Sciences, Chancellor's Building; University of Edinburgh; Edinburgh UK
- Genes to Cognition Programme; Wellcome Trust Sanger Institute; Cambridge UK
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Improving the Identification of Phenotypic Abnormalities and Sexual Dimorphism in Mice When Studying Rare Event Categorical Characteristics. Genetics 2016; 205:491-501. [PMID: 27932544 PMCID: PMC5289831 DOI: 10.1534/genetics.116.195388] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 11/11/2016] [Indexed: 11/19/2022] Open
Abstract
Biological research frequently involves the study of phenotyping data. Many of these studies focus on rare event categorical data, and functional genomics studies typically study the presence or absence of an abnormal phenotype. With the growing interest in the role of sex, there is a need to assess the phenotype for sexual dimorphism. The identification of abnormal phenotypes for downstream research is challenged by the small sample size, the rare event nature, and the multiple testing problem, as many variables are monitored simultaneously. Here, we develop a statistical pipeline to assess statistical and biological significance while managing the multiple testing problem. We propose a two-step pipeline to initially assess for a treatment effect, in our case example genotype, and then test for an interaction with sex. We compare multiple statistical methods and use simulations to investigate the control of the type-one error rate and power. To maximize the power while addressing the multiple testing issue, we implement filters to remove data sets where the hypotheses to be tested cannot achieve significance. A motivating case study utilizing a large scale high-throughput mouse phenotyping data set from the Wellcome Trust Sanger Institute Mouse Genetics Project, where the treatment is a gene ablation, demonstrates the benefits of the new pipeline on the downstream biological calls.
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Novoselova TV, Larder R, Rimmington D, Lelliott C, Wynn EH, Gorrigan RJ, Tate PH, Guasti L, O'Rahilly S, Clark AJL, Logan DW, Coll AP, Chan LF. Loss of Mrap2 is associated with Sim1 deficiency and increased circulating cholesterol. J Endocrinol 2016; 230:13-26. [PMID: 27106110 PMCID: PMC5064762 DOI: 10.1530/joe-16-0057] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Accepted: 04/21/2016] [Indexed: 11/08/2022]
Abstract
Melanocortin receptor accessory protein 2 (MRAP2) is a transmembrane accessory protein predominantly expressed in the brain. Both global and brain-specific deletion of Mrap2 in mice results in severe obesity. Loss-of-function MRAP2 mutations have also been associated with obesity in humans. Although MRAP2 has been shown to interact with MC4R, a G protein-coupled receptor with an established role in energy homeostasis, appetite regulation and lipid metabolism, the mechanisms through which loss of MRAP2 causes obesity remains uncertain. In this study, we used two independently derived lines of Mrap2 deficient mice (Mrap2(tm1a/tm1a)) to further study the role of Mrap2 in the regulation of energy balance and peripheral lipid metabolism. Mrap2(tm1a/tm1a) mice have a significant increase in body weight, with increased fat and lean mass, but without detectable changes in food intake or energy expenditure. Transcriptomic analysis showed significantly decreased expression of Sim1, Trh, Oxt and Crh within the hypothalamic paraventricular nucleus of Mrap2(tm1a/tm1a) mice. Circulating levels of both high-density lipoprotein and low-density lipoprotein were significantly increased in Mrap2 deficient mice. Taken together, these data corroborate the role of MRAP2 in metabolic regulation and indicate that, at least in part, this may be due to defective central melanocortin signalling.
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Affiliation(s)
- T V Novoselova
- Centre for EndocrinologyQueen Mary University of London, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Charterhouse Square, London, UK
| | - R Larder
- University of Cambridge Metabolic Research LaboratoriesMRC Metabolic Disease Unit, Wellcome Trust-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge, UK
| | - D Rimmington
- University of Cambridge Metabolic Research LaboratoriesMRC Metabolic Disease Unit, Wellcome Trust-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge, UK
| | - C Lelliott
- Wellcome Trust Sanger InstituteWellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - E H Wynn
- Wellcome Trust Sanger InstituteWellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - R J Gorrigan
- Centre for EndocrinologyQueen Mary University of London, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Charterhouse Square, London, UK
| | - P H Tate
- Wellcome Trust Sanger InstituteWellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - L Guasti
- Centre for EndocrinologyQueen Mary University of London, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Charterhouse Square, London, UK
| | - S O'Rahilly
- University of Cambridge Metabolic Research LaboratoriesMRC Metabolic Disease Unit, Wellcome Trust-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge, UK
| | - A J L Clark
- Centre for EndocrinologyQueen Mary University of London, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Charterhouse Square, London, UK
| | - D W Logan
- Wellcome Trust Sanger InstituteWellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - A P Coll
- University of Cambridge Metabolic Research LaboratoriesMRC Metabolic Disease Unit, Wellcome Trust-MRC Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, Addenbrooke's Hospital, Cambridge, UK
| | - L F Chan
- Centre for EndocrinologyQueen Mary University of London, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Charterhouse Square, London, UK
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Oellrich A, Meehan TF, Parkinson H, Sarntivijai S, White JK, Karp NA. Reporting phenotypes in mouse models when considering body size as a potential confounder. J Biomed Semantics 2016; 7:2. [PMID: 26865945 PMCID: PMC4748495 DOI: 10.1186/s13326-016-0050-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2015] [Accepted: 02/02/2016] [Indexed: 01/09/2023] Open
Abstract
Genotype-phenotype studies aim to identify causative relationships between genes and phenotypes. The International Mouse Phenotyping Consortium is a high throughput phenotyping program whose goal is to collect phenotype data for a knockout mouse strain of every protein coding gene. The scale of the project requires an automatic analysis pipeline to detect abnormal phenotypes, and disseminate the resulting gene-phenotype annotation data into public resources. A body weight phenotype is a common result of knockout studies. As body weight correlates with many other biological traits, this challenges the interpretation of related gene-phenotype associations. Co-correlation can lead to gene-phenotype associations that are potentially misleading. Here we use statistical modelling to account for body weight as a potential confounder to assess the impact. We find that there is a considerable impact on previously established gene-phenotype associations due to an increase in sensitivity as well as the confounding effect. We investigated the existing ontologies to represent this phenotypic information and we explored ways to ontologically represent the results of the influence of confounders on gene-phenotype associations. With the scale of data being disseminated within the high throughput programs and the range of downstream studies that utilise these data, it is critical to consider how we improve the quality of the disseminated data and provide a robust ontological representation.
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Affiliation(s)
- Anika Oellrich
- />Mouse Informatics Group, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire UK
- />Social Genetic & Developmental Psychiatry, King’s College London, London, UK
| | - Terrence F. Meehan
- />Samples, Phenotypes and Ontologies, European Molecular Biology Laboratory—European Bioinformatics Institute, Hinxton, Cambridge UK
| | - Helen Parkinson
- />Samples, Phenotypes and Ontologies, European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK
| | - Sirarat Sarntivijai
- />Samples, Phenotypes and Ontologies, European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK
- />The Centre for Therapeutic Target Validation, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD UK
| | - Jacqueline K. White
- />Mouse Genetics Project, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire UK
| | - Natasha A. Karp
- />Mouse Informatics Group, Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire UK
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Discovery of four recessive developmental disorders using probabilistic genotype and phenotype matching among 4,125 families. Nat Genet 2015; 47:1363-9. [PMID: 26437029 PMCID: PMC5988033 DOI: 10.1038/ng.3410] [Citation(s) in RCA: 112] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Accepted: 08/31/2015] [Indexed: 12/29/2022]
Abstract
Discovery of most autosomal recessive disease genes has involved analysis of large, often consanguineous, multiplex families or small cohorts of unrelated individuals with a well-defined clinical condition. Discovery of novel dominant causes of rare, genetically heterogenous developmental disorders has been revolutionized by exome analysis of large cohorts of phenotypically diverse parent-offspring trios 1,2. Here we analysed 4,125 families with diverse, rare, genetically heterogeneous developmental disorders and identified four novel autosomal recessive disorders. These four disorders were identified by integrating Mendelian filtering (identifying probands with rare biallelic putatively damaging variants in the same gene) with statistical assessments of (i) the likelihood of sampling the observed genotypes from the general population, and (ii) the phenotypic similarity of patients with the same recessive candidate gene. This new paradigm promises to catalyse discovery of novel recessive disorders, especially those with less consistent or nonspecific clinical presentations, and those caused predominantly by compound heterozygous genotypes.
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PhenStat: A Tool Kit for Standardized Analysis of High Throughput Phenotypic Data. PLoS One 2015; 10:e0131274. [PMID: 26147094 PMCID: PMC4493137 DOI: 10.1371/journal.pone.0131274] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 05/06/2015] [Indexed: 12/31/2022] Open
Abstract
The lack of reproducibility with animal phenotyping experiments is a growing concern among the biomedical community. One contributing factor is the inadequate description of statistical analysis methods that prevents researchers from replicating results even when the original data are provided. Here we present PhenStat – a freely available R package that provides a variety of statistical methods for the identification of phenotypic associations. The methods have been developed for high throughput phenotyping pipelines implemented across various experimental designs with an emphasis on managing temporal variation. PhenStat is targeted to two user groups: small-scale users who wish to interact and test data from large resources and large-scale users who require an automated statistical analysis pipeline. The software provides guidance to the user for selecting appropriate analysis methods based on the dataset and is designed to allow for additions and modifications as needed. The package was tested on mouse and rat data and is used by the International Mouse Phenotyping Consortium (IMPC). By providing raw data and the version of PhenStat used, resources like the IMPC give users the ability to replicate and explore results within their own computing environment.
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Abstract
The Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines were developed to address the lack of reproducibility in biomedical animal studies and improve the communication of research findings. While intended to guide the preparation of peer-reviewed manuscripts, the principles of transparent reporting are also fundamental for in vivo databases. Here, we describe the benefits and challenges of applying the guidelines for the International Mouse Phenotyping Consortium (IMPC), whose goal is to produce and phenotype 20,000 knockout mouse strains in a reproducible manner across ten research centres. In addition to ensuring the transparency and reproducibility of the IMPC, the solutions to the challenges of applying the ARRIVE guidelines in the context of IMPC will provide a resource to help guide similar initiatives in the future. Transparent reporting is key to ensuring reproducibility of animal research. This article examines the challenges of applying the ARRIVE guidelines to a large-scale, collaborative, in vivo research initiative—the International Mouse Phenotyping Consortium.
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Balmus G, Karp NA, Ng BL, Jackson SP, Adams DJ, McIntyre RE. A high-throughput in vivo micronucleus assay for genome instability screening in mice. Nat Protoc 2015; 10:205-15. [PMID: 25551665 PMCID: PMC4806852 DOI: 10.1038/nprot.2015.010] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
We describe a sensitive, robust, high-throughput method for quantifying the formation of micronuclei, markers of genome instability, in mouse erythrocytes. Micronuclei are whole chromosomes or chromosome segments that have been separated from the nucleus. Other methods of detection rely on labor-intensive, microscopy-based techniques. Here we describe a 2-d, 96-well plate-based flow cytometric method of micronucleus scoring that is simple enough for a research technician experienced in flow cytometry to perform. The assay detects low levels of genome instability that cannot be readily identified by classic phenotyping, using 25 μl of blood. By using this assay, we have screened >10,000 blood samples and discovered novel genes that contribute to vertebrate genome maintenance, as well as novel disease models and mechanisms of genome instability disorders. We discuss experimental design considerations, including statistical power calculation, we provide troubleshooting tips and we discuss factors that contribute to a false-positive increase in the number of micronucleated red blood cells and to experimental variability.
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Affiliation(s)
- Gabriel Balmus
- The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QN, UK
- Maintenance of Genome Stability; The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Natasha A Karp
- Mouse Genetics Project; The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Bee Ling Ng
- Cytometry Core Facility; The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Stephen P Jackson
- The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Tennis Court Road, Cambridge, CB2 1QN, UK
- Maintenance of Genome Stability; The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - David J Adams
- Experimental Cancer Genetics; The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Rebecca E McIntyre
- Experimental Cancer Genetics; The Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
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Karp NA, Speak AO, White JK, Adams DJ, Hrabé de Angelis M, Hérault Y, Mott RF. Impact of temporal variation on design and analysis of mouse knockout phenotyping studies. PLoS One 2014; 9:e111239. [PMID: 25343444 PMCID: PMC4208881 DOI: 10.1371/journal.pone.0111239] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2014] [Accepted: 09/18/2014] [Indexed: 12/12/2022] Open
Abstract
A significant challenge facing high-throughput phenotyping of in-vivo knockout mice is ensuring phenotype calls are robust and reliable. Central to this problem is selecting an appropriate statistical analysis that models both the experimental design (the workflow and the way control mice are selected for comparison with knockout animals) and the sources of variation. Recently we proposed a mixed model suitable for small batch-oriented studies, where controls are not phenotyped concurrently with mutants. Here we evaluate this method both for its sensitivity to detect phenotypic effects and to control false positives, across a range of workflows used at mouse phenotyping centers. We found the sensitivity and control of false positives depend on the workflow. We show that the phenotypes in control mice fluctuate unexpectedly between batches and this can cause the false positive rate of phenotype calls to be inflated when only a small number of batches are tested, when the effect of knockout becomes confounded with temporal fluctuations in control mice. This effect was observed in both behavioural and physiological assays. Based on this analysis, we recommend two approaches (workflow and accompanying control strategy) and associated analyses, which would be robust, for use in high-throughput phenotyping pipelines. Our results show the importance in modelling all sources of variability in high-throughput phenotyping studies.
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Affiliation(s)
- Natasha A. Karp
- Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, United Kingdom
- * E-mail:
| | - Anneliese O. Speak
- Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, United Kingdom
| | | | - David J. Adams
- Wellcome Trust Sanger Institute, Hinxton, Cambridgeshire, United Kingdom
| | - Martin Hrabé de Angelis
- German Mouse Clinic - Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany
- Experimental Genetics, Technische Universität München, Freising-Weihenstephan, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Yann Hérault
- Institut Clinique de la Souris, Université de Strasbourg, Illkirch, France
| | - Richard F. Mott
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, United Kingdom
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Oellrich A, Jacobsen J, Papatheodorou I, Smedley D. Using association rule mining to determine promising secondary phenotyping hypotheses. ACTA ACUST UNITED AC 2014; 30:i52-59. [PMID: 24932005 PMCID: PMC4059059 DOI: 10.1093/bioinformatics/btu260] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
MOTIVATION Large-scale phenotyping projects such as the Sanger Mouse Genetics project are ongoing efforts to help identify the influences of genes and their modification on phenotypes. Gene-phenotype relations are crucial to the improvement of our understanding of human heritable diseases as well as the development of drugs. However, given that there are ∼: 20 000 genes in higher vertebrate genomes and the experimental verification of gene-phenotype relations requires a lot of resources, methods are needed that determine good candidates for testing. RESULTS In this study, we applied an association rule mining approach to the identification of promising secondary phenotype candidates. The predictions rely on a large gene-phenotype annotation set that is used to find occurrence patterns of phenotypes. Applying an association rule mining approach, we could identify 1967 secondary phenotype hypotheses that cover 244 genes and 136 phenotypes. Using two automated and one manual evaluation strategies, we demonstrate that the secondary phenotype candidates possess biological relevance to the genes they are predicted for. From the results we conclude that the predicted secondary phenotypes constitute good candidates to be experimentally tested and confirmed. AVAILABILITY The secondary phenotype candidates can be browsed through at http://www.sanger.ac.uk/resources/databases/phenodigm/gene/secondaryphenotype/list. CONTACT ao5@sanger.ac.uk or ds5@sanger.ac.uk SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Anika Oellrich
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB1 10SA, UK
| | - Julius Jacobsen
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB1 10SA, UK
| | - Irene Papatheodorou
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB1 10SA, UK
| | | | - Damian Smedley
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB1 10SA, UK
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Salsbury G, Cambridge EL, McIntyre Z, Arends MJ, Karp NA, Isherwood C, Shannon C, Hooks Y, Ramirez-Solis R, Adams DJ, White JK, Speak AO. Disruption of the potassium channel regulatory subunit KCNE2 causes iron-deficient anemia. Exp Hematol 2014; 42:1053-8.e1. [PMID: 25127743 PMCID: PMC4271779 DOI: 10.1016/j.exphem.2014.07.269] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2014] [Revised: 07/04/2014] [Accepted: 07/08/2014] [Indexed: 12/21/2022]
Abstract
Iron homeostasis is a dynamic process that is tightly controlled to balance iron uptake, storage, and export. Reduction of dietary iron from the ferric to the ferrous form is required for uptake by solute carrier family 11 (proton-coupled divalent metal ion transporters), member 2 (Slc11a2) into the enterocytes. Both processes are proton dependent and have led to the suggestion of the importance of acidic gastric pH for the absorption of dietary iron. Potassium voltage-gated channel subfamily E, member 2 (KCNE2), in combination with potassium voltage-gated channel, KQT-like subfamily, member 1 (KCNQ1), form a gastric potassium channel essential for gastric acidification. Deficiency of either Kcne2 or Kcnq1 results in achlorhydia, gastric hyperplasia, and neoplasia, but the impact on iron absorption has not, to our knowledge, been investigated. Here we report that Kcne2-deficient mice, in addition to the previously reported phenotypes, also present with iron-deficient anemia. Interestingly, impaired function of KCNQ1 results in iron-deficient anemia in Jervell and Lange-Nielsen syndrome patients. We speculate that impaired function of KCNE2 could result in the same clinical phenotype.
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Affiliation(s)
- Grace Salsbury
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Emma L Cambridge
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Zoe McIntyre
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Mark J Arends
- University of Edinburgh Division of Pathology, Institute of Genetics & Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Natasha A Karp
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Christopher Isherwood
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Carl Shannon
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Yvette Hooks
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | | | - Ramiro Ramirez-Solis
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - David J Adams
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Jacqueline K White
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Anneliese O Speak
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, United Kingdom.
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Evaluation of growth patterns and body composition in C57Bl/6J mice using dual energy X-ray absorptiometry. BIOMED RESEARCH INTERNATIONAL 2014; 2014:253067. [PMID: 25110666 PMCID: PMC4119710 DOI: 10.1155/2014/253067] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2014] [Revised: 05/29/2014] [Accepted: 06/16/2014] [Indexed: 11/17/2022]
Abstract
The normal growth pattern of female C57BL/6J mice, from 5 to 30 weeks of age, has been investigated in a longitudinal study. Weight, body surface area (BS), and body mass index (BMI) were evaluated in forty mice. Lean mass and fat mass, bone mineral content (BMC), and bone mineral density (BMD) were monitored by dual energy X-ray absorptiometry (DEXA). Weight and BS increased linearly (16.15 ± 0.64-27.64 ± 1.42 g; 51.13 ± 0.74-79.57 ± 2.15 cm(2), P < 0.01), more markedly from 5 to 9 weeks of age (P < 0.001). BMD showed a peak at 17 weeks (0.0548 ± 0.0011 g/cm(2) ∗ m, P < 0.01). Lean mass showed an evident gain at 9 (15.8 ± 0.8 g, P < 0.001) and 25 weeks (20.5 ± 0.3 g, P < 0.01), like fat mass from 13 to 17 weeks (2.0 ± 0.4-3.6 ± 0.7 g, P < 0.01). BMI and lean mass index (LMI) reached the highest value at 21 weeks (3.57 ± 0.02-0.284 ± 0.010 g/cm(2), resp.), like fat mass index (FMI) at 17 weeks (0.057 ± 0.009 g/cm(2)) (P < 0.01). BMI, weight, and BS showed a moderate positive correlation (0.45-0.85) with lean mass from 5 to 21 weeks. Mixed linear models provided a good prediction for lean mass, fat mass, and BMD. This study may represent a baseline reference for a future comparison of wild-type C57BL/6J mice with models of altered growth.
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Adissu HA, Estabel J, Sunter D, Tuck E, Hooks Y, Carragher DM, Clarke K, Karp NA, Newbigging S, Jones N, Morikawa L, White JK, McKerlie C. Histopathology reveals correlative and unique phenotypes in a high-throughput mouse phenotyping screen. Dis Model Mech 2014; 7:515-24. [PMID: 24652767 PMCID: PMC4007403 DOI: 10.1242/dmm.015263] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
The Mouse Genetics Project (MGP) at the Wellcome Trust Sanger Institute aims to generate and phenotype over 800 genetically modified mouse lines over the next 5 years to gain a better understanding of mammalian gene function and provide an invaluable resource to the scientific community for follow-up studies. Phenotyping includes the generation of a standardized biobank of paraffin-embedded tissues for each mouse line, but histopathology is not routinely performed. In collaboration with the Pathology Core of the Centre for Modeling Human Disease (CMHD) we report the utility of histopathology in a high-throughput primary phenotyping screen. Histopathology was assessed in an unbiased selection of 50 mouse lines with (n=30) or without (n=20) clinical phenotypes detected by the standard MGP primary phenotyping screen. Our findings revealed that histopathology added correlating morphological data in 19 of 30 lines (63.3%) in which the primary screen detected a phenotype. In addition, seven of the 50 lines (14%) presented significant histopathology findings that were not associated with or predicted by the standard primary screen. Three of these seven lines had no clinical phenotype detected by the standard primary screen. Incidental and strain-associated background lesions were present in all mutant lines with good concordance to wild-type controls. These findings demonstrate the complementary and unique contribution of histopathology to high-throughput primary phenotyping of mutant mice.
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Affiliation(s)
- Hibret A Adissu
- Centre for Modeling Human Disease, Toronto Centre for Phenogenomics, 25 Orde Street, Toronto, ON M5T 3H7, Canada
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Koscielny G, Yaikhom G, Iyer V, Meehan TF, Morgan H, Atienza-Herrero J, Blake A, Chen CK, Easty R, Di Fenza A, Fiegel T, Grifiths M, Horne A, Karp NA, Kurbatova N, Mason JC, Matthews P, Oakley DJ, Qazi A, Regnart J, Retha A, Santos LA, Sneddon DJ, Warren J, Westerberg H, Wilson RJ, Melvin DG, Smedley D, Brown SDM, Flicek P, Skarnes WC, Mallon AM, Parkinson H. The International Mouse Phenotyping Consortium Web Portal, a unified point of access for knockout mice and related phenotyping data. Nucleic Acids Res 2014; 42:D802-9. [PMID: 24194600 PMCID: PMC3964955 DOI: 10.1093/nar/gkt977] [Citation(s) in RCA: 206] [Impact Index Per Article: 20.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2013] [Revised: 09/20/2013] [Accepted: 10/01/2013] [Indexed: 12/21/2022] Open
Abstract
The International Mouse Phenotyping Consortium (IMPC) web portal (http://www.mousephenotype.org) provides the biomedical community with a unified point of access to mutant mice and rich collection of related emerging and existing mouse phenotype data. IMPC mouse clinics worldwide follow rigorous highly structured and standardized protocols for the experimentation, collection and dissemination of data. Dedicated 'data wranglers' work with each phenotyping center to collate data and perform quality control of data. An automated statistical analysis pipeline has been developed to identify knockout strains with a significant change in the phenotype parameters. Annotation with biomedical ontologies allows biologists and clinicians to easily find mouse strains with phenotypic traits relevant to their research. Data integration with other resources will provide insights into mammalian gene function and human disease. As phenotype data become available for every gene in the mouse, the IMPC web portal will become an invaluable tool for researchers studying the genetic contributions of genes to human diseases.
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Affiliation(s)
- Gautier Koscielny
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Gagarine Yaikhom
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Vivek Iyer
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Terrence F. Meehan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Hugh Morgan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Julian Atienza-Herrero
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Andrew Blake
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Chao-Kung Chen
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Richard Easty
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Armida Di Fenza
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Tanja Fiegel
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Mark Grifiths
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Alan Horne
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Natasha A. Karp
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Natalja Kurbatova
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Jeremy C. Mason
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Peter Matthews
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Darren J. Oakley
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Asfand Qazi
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Jack Regnart
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Ahmad Retha
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Luis A. Santos
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Duncan J. Sneddon
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Jonathan Warren
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Henrik Westerberg
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Robert J. Wilson
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - David G. Melvin
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Damian Smedley
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Steve D. M. Brown
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - William C. Skarnes
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Ann-Marie Mallon
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Helen Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire OX11 0RD, UK and Mouse Informatics Group, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
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Hoehndorf R, Hancock JM, Hardy NW, Mallon AM, Schofield PN, Gkoutos GV. Analyzing gene expression data in mice with the Neuro Behavior Ontology. Mamm Genome 2013; 25:32-40. [PMID: 24177753 DOI: 10.1007/s00335-013-9481-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2013] [Accepted: 09/02/2013] [Indexed: 12/13/2022]
Abstract
We have applied the Neuro Behavior Ontology (NBO), an ontology for the annotation of behavioral gene functions and behavioral phenotypes, to the annotation of more than 1,000 genes in the mouse that are known to play a role in behavior. These annotations can be explored by researchers interested in genes involved in particular behaviors and used computationally to provide insights into the behavioral phenotypes resulting from differences in gene expression. We developed the OntoFUNC tool and have applied it to enrichment analyses over the NBO to provide high-level behavioral interpretations of gene expression datasets. The resulting increase in the number of gene annotations facilitates the identification of behavioral or neurologic processes by assisting the formulation of hypotheses about the relationships between gene, processes, and phenotypic manifestations resulting from behavioral observations.
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Affiliation(s)
- Robert Hoehndorf
- Department of Computer Science, University of Aberystwyth, Old College, King Street, Aberystwyth, SY23 2AX, UK,
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