151
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Shaw ND, Brand H, Kupchinsky ZA, Bengani H, Plummer L, Jones TI, Erdin S, Williamson KA, Rainger J, Stortchevoi A, Samocha K, Currall BB, Dunican DS, Collins RL, Willer JR, Lek A, Lek M, Nassan M, Pereira S, Kammin T, Lucente D, Silva A, Seabra CM, Chiang C, An Y, Ansari M, Rainger JK, Joss S, Smith JC, Lippincott MF, Singh SS, Patel N, Jing JW, Law JR, Ferraro N, Verloes A, Rauch A, Steindl K, Zweier M, Scheer I, Sato D, Okamoto N, Jacobsen C, Tryggestad J, Chernausek S, Schimmenti LA, Brasseur B, Cesaretti C, García-Ortiz JE, Buitrago TP, Silva OP, Hoffman JD, Mühlbauer W, Ruprecht KW, Loeys BL, Shino M, Kaindl AM, Cho CH, Morton CC, Meehan RR, van Heyningen V, Liao EC, Balasubramanian R, Hall JE, Seminara SB, Macarthur D, Moore SA, Yoshiura KI, Gusella JF, Marsh JA, Graham JM, Lin AE, Katsanis N, Jones PL, Crowley WF, Davis EE, FitzPatrick DR, Talkowski ME. SMCHD1 mutations associated with a rare muscular dystrophy can also cause isolated arhinia and Bosma arhinia microphthalmia syndrome. Nat Genet 2017; 49:238-248. [PMID: 28067909 PMCID: PMC5473428 DOI: 10.1038/ng.3743] [Citation(s) in RCA: 104] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Accepted: 11/16/2016] [Indexed: 12/14/2022]
Abstract
Arhinia, or absence of the nose, is a rare malformation of unknown etiology that is often accompanied by ocular and reproductive defects. Sequencing of 40 people with arhinia revealed that 84% of probands harbor a missense mutation localized to a constrained region of SMCHD1 encompassing the ATPase domain. SMCHD1 mutations cause facioscapulohumeral muscular dystrophy type 2 (FSHD2) via a trans-acting loss-of-function epigenetic mechanism. We discovered shared mutations and comparable DNA hypomethylation patterning between these distinct disorders. CRISPR/Cas9-mediated alteration of smchd1 in zebrafish yielded arhinia-relevant phenotypes. Transcriptome and protein analyses in arhinia probands and controls showed no differences in SMCHD1 mRNA or protein abundance but revealed regulatory changes in genes and pathways associated with craniofacial patterning. Mutations in SMCHD1 thus contribute to distinct phenotypic spectra, from craniofacial malformation and reproductive disorders to muscular dystrophy, which we speculate to be consistent with oligogenic mechanisms resulting in pleiotropic outcomes.
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Affiliation(s)
- Natalie D Shaw
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Harrison Brand
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Zachary A Kupchinsky
- Center for Human Disease Modeling, Duke University Medical Center, Durham, North Carolina, USA
| | - Hemant Bengani
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - Lacey Plummer
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Takako I Jones
- Department of Cell and Developmental Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Serkan Erdin
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Kathleen A Williamson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - Joe Rainger
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - Alexei Stortchevoi
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Kaitlin Samocha
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Benjamin B Currall
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Donncha S Dunican
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - Ryan L Collins
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Bioinformatics and Integrative Genomics, Division of Medical Sciences, Harvard Medical School, Boston, Massachusetts, USA
| | - Jason R Willer
- Center for Human Disease Modeling, Duke University Medical Center, Durham, North Carolina, USA
| | - Angela Lek
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - Monkol Lek
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Malik Nassan
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | - Shahrin Pereira
- Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Tammy Kammin
- Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Diane Lucente
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Alexandra Silva
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Catarina M Seabra
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
- GABBA Program, University of Porto, Porto, Portugal
| | - Colby Chiang
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Yu An
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Morad Ansari
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - Jacqueline K Rainger
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - Shelagh Joss
- West of Scotland Genetics Service, South Glasgow University Hospitals, Glasgow, UK
| | - Jill Clayton Smith
- Faculty of Medical and Human Sciences, Institute of Human Development, Manchester Centre for Genomic Medicine, University of Manchester, Manchester Academic Health Science Centre (MAHSC), Manchester, UK
| | - Margaret F Lippincott
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Sylvia S Singh
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Nirav Patel
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jenny W Jing
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jennifer R Law
- Division of Pediatric Endocrinology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nalton Ferraro
- Department of Oral and Maxillofacial Surgery, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Alain Verloes
- Department of Genetics, Robert Debré Hospital, Paris, France
| | - Anita Rauch
- Institute of Medical Genetics and Radiz-Rare Disease Initiative Zurich, Clinical Research Priority Program for Rare Diseases, University of Zurich, Schlieren-Zurich, Switzerland
| | - Katharina Steindl
- Institute of Medical Genetics and Radiz-Rare Disease Initiative Zurich, Clinical Research Priority Program for Rare Diseases, University of Zurich, Schlieren-Zurich, Switzerland
| | - Markus Zweier
- Institute of Medical Genetics and Radiz-Rare Disease Initiative Zurich, Clinical Research Priority Program for Rare Diseases, University of Zurich, Schlieren-Zurich, Switzerland
| | - Ianina Scheer
- Department of Diagnostic Imaging, Children's Hospital, Zurich, Switzerland
| | - Daisuke Sato
- Department of Pediatrics, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Nobuhiko Okamoto
- Department of Medical Genetics, Osaka Medical Center and Research Institute for Maternal and Child Health, Osaka, Japan
| | - Christina Jacobsen
- Division of Endocrinology and Genetics, Boston Children's Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jeanie Tryggestad
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Steven Chernausek
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Lisa A Schimmenti
- Departments of Otorhinolaryngology and Clinical Genomics, Mayo Clinic, Rochester, Minnesota, USA
| | - Benjamin Brasseur
- DeWitt Daughtry Family Department of Surgery, University of Miami Leonard M. Miller School of Medicine, Miami, Florida, USA
| | - Claudia Cesaretti
- Medical Genetics Unit, Fondazione IRCCS Cà Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | - Jose E García-Ortiz
- División de Genética, Centro de Investigación Biomédica de Occidente, Instituto Mexicano del Seguro Social, Guadalajara, Mexico
| | | | | | - Jodi D Hoffman
- Divisions of Genetics and Maternal Fetal Medicine, Tufts Medical Center, Boston, Massachusetts, USA
| | - Wolfgang Mühlbauer
- Department of Plastic and Aesthetic Surgery, ATOS Klinik, Munich, Germany
| | - Klaus W Ruprecht
- Department of Ophthalmology, University Hospital of the Saarland, Homburg, Germany
| | - Bart L Loeys
- Center for Medical Genetics, University of Antwerp and Antwerp University Hospital, Antwerp, Belgium
| | - Masato Shino
- Department of Otolaryngology and Head and Neck Surgery, Gunma University Graduate School of Medicine, Gunma, Japan
| | - Angela M Kaindl
- Biology and Neurobiology, Charité-University Medicine Berlin and Berlin Institute of Health, Berlin, Germany
| | - Chie-Hee Cho
- Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital of Bern, Bern, Switzerland
| | - Cynthia C Morton
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Obstetrics, Gynecology and Reproductive Biology, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Richard R Meehan
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - Veronica van Heyningen
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - Eric C Liao
- Center for Regenerative Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Division of Plastic and Reconstructive Surgery, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Stem Cell Institute, Cambridge, Massachusetts, USA
| | - Ravikumar Balasubramanian
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Janet E Hall
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Stephanie B Seminara
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Daniel Macarthur
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Steven A Moore
- Department of Pathology, University of Iowa Carver College of Medicine, Iowa City, Iowa, USA
| | - Koh-Ichiro Yoshiura
- Department of Human Genetics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
| | - James F Gusella
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA
| | - Joseph A Marsh
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - John M Graham
- Department of Pediatrics, Cedars Sinai Medical Center, Los Angeles, California, USA
| | - Angela E Lin
- Medical Genetics, MassGeneral Hospital for Children and Harvard Medical School, Boston, Massachusetts, USA
| | - Nicholas Katsanis
- Center for Human Disease Modeling, Duke University Medical Center, Durham, North Carolina, USA
| | - Peter L Jones
- Department of Cell and Developmental Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - William F Crowley
- Harvard Reproductive Endocrine Sciences Center and NICHD Center of Excellence in Translational Research in Fertility and Infertility, Reproductive Endocrine Unit of the Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Erica E Davis
- Center for Human Disease Modeling, Duke University Medical Center, Durham, North Carolina, USA
| | - David R FitzPatrick
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh Western General Hospital, Edinburgh, UK
| | - Michael E Talkowski
- Molecular Neurogenetics Unit and Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Center for Mendelian Genomics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
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152
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Smoly I, Shemesh N, Ziv-Ukelson M, Ben-Zvi A, Yeger-Lotem E. An Asymmetrically Balanced Organization of Kinases versus Phosphatases across Eukaryotes Determines Their Distinct Impacts. PLoS Comput Biol 2017; 13:e1005221. [PMID: 28135269 PMCID: PMC5279721 DOI: 10.1371/journal.pcbi.1005221] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Accepted: 10/24/2016] [Indexed: 12/22/2022] Open
Abstract
Protein phosphorylation underlies cellular response pathways across eukaryotes and is governed by the opposing actions of phosphorylating kinases and de-phosphorylating phosphatases. While kinases and phosphatases have been extensively studied, their organization and the mechanisms by which they balance each other are not well understood. To address these questions we performed quantitative analyses of large-scale 'omics' datasets from yeast, fly, plant, mouse and human. We uncovered an asymmetric balance of a previously-hidden scale: Each organism contained many different kinase genes, and these were balanced by a small set of highly abundant phosphatase proteins. Kinases were much more responsive to perturbations at the gene and protein levels. In addition, kinases had diverse scales of phenotypic impact when manipulated. Phosphatases, in contrast, were stable, highly robust and flatly organized, with rather uniform impact downstream. We validated aspects of this organization experimentally in nematode, and supported additional aspects by theoretic analysis of the dynamics of protein phosphorylation. Our analyses explain the empirical bias in the protein phosphorylation field toward characterization and therapeutic targeting of kinases at the expense of phosphatases. We show quantitatively and broadly that this is not only a historical bias, but stems from wide-ranging differences in their organization and impact. The asymmetric balance between these opposing regulators of protein phosphorylation is also common to opposing regulators of two other post-translational modification systems, suggesting its fundamental value. Protein phosphorylation is a reversible modification that underlies cellular responses to stimuli across organisms. Historically, the study of protein phosphorylation concentrated on the role of kinases, which introduce the phosphate, at the expense of phosphatases, which remove it. Many kinases have been associated with specific phenotypes and considered attractive drug targets, while phosphatases remained far less characterized. It has been unclear whether this discrepancy is due to historical biases or reflects real systemic differences between these enzymes. By analyzing large-scale ‘omics’ datasets across genes, transcripts, proteins, interactions, and organisms, we uncovered an asymmetric architecture of kinases versus phosphatases that balances between them, determines their distinct impact patterns, and affects their therapeutic potential. This architecture is conserved from yeast to human and is partially shared by two other protein modification systems, suggesting it is a general feature of these systems.
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Affiliation(s)
- Ilan Smoly
- Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Netta Shemesh
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Michal Ziv-Ukelson
- Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Anat Ben-Zvi
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- Department of Life Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Esti Yeger-Lotem
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- * E-mail:
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153
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Ishikawa A. Identification of a Putative Quantitative Trait Gene for Resistance to Obesity in Mice Using Transcriptome Analysis and Causal Inference Tests. PLoS One 2017; 12:e0170652. [PMID: 28114323 PMCID: PMC5256930 DOI: 10.1371/journal.pone.0170652] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Accepted: 01/09/2017] [Indexed: 11/19/2022] Open
Abstract
It is still challenging to identify causal genes governing obesity. Pbwg1.5, a quantitative trait locus (QTL) for resistance to obesity, was previously discovered from wild Mus musculus castaneus mice and was fine-mapped to a 2.1-Mb genomic region of mouse chromosome 2, where no known gene with an effect on white adipose tissue (WAT) has been reported. The aim of this study was to identify a strong candidate gene for Pbwg1.5 by an integration approach of transcriptome analysis (RNA-sequencing followed by real-time PCR analysis) and the causal inference test (CIT), a statistical method to infer causal relationships between diplotypes, gene expression and trait values. Body weight, body composition and biochemical traits were measured in F2 mice obtained from an intercross between the C57BL/6JJcl strain and a congenic strain carrying Pbwg1.5 on the C57BL/6JJcl background. The F2 mice showed significant diplotype differences in 12 traits including body weight, WAT weight and serum cholesterol/triglyceride levels. The transcriptome analysis revealed that Ly75, Pla2r1, Fap and Gca genes were differentially expressed in the liver and that Fap, Ifih1 and Grb14 were differentially expressed in WAT. However, CITs indicated statistical evidence that only the liver Ly75 gene mediated between genotype and WAT. Ly75 expression was negatively associated with WAT weight. The results suggested that Ly75 is a putative quantitative trait gene for the obesity-resistant Pbwg1.5 QTL discovered from the wild M. m. castaneus mouse. The finding provides a novel insight into a better understanding of the genetic basis for prevention of obesity.
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Affiliation(s)
- Akira Ishikawa
- Laboratory of Animal Genetics, Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, Aichi, Japan
- * E-mail:
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154
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Junge A, Refsgaard JC, Garde C, Pan X, Santos A, Alkan F, Anthon C, von Mering C, Workman CT, Jensen LJ, Gorodkin J. RAIN: RNA-protein Association and Interaction Networks. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2017; 2017:baw167. [PMID: 28077569 PMCID: PMC5225963 DOI: 10.1093/database/baw167] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Revised: 11/18/2016] [Accepted: 12/05/2016] [Indexed: 12/11/2022]
Abstract
Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) as well. However, integration of ncRNAs into protein association networks is challenging due to data heterogeneity. Here, we present a database of ncRNA-RNA and ncRNA-protein interactions and its integration with the STRING database of protein-protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data, interaction predictions and automatic literature mining. RAIN uses an integrative scoring scheme to assign a confidence score to each interaction. We demonstrate that RAIN outperforms the underlying microRNA-target predictions in inferring ncRNA interactions. RAIN can be operated through an easily accessible web interface and all interaction data can be downloaded.Database URL: http://rth.dk/resources/rain.
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Affiliation(s)
- Alexander Junge
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Copenhagen,, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark.,Department of Veterinary Clinical and Animal Sciences, University of Copenhagen, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark
| | - Jan C Refsgaard
- Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Building: 06-2-26, Blegdamsvej 3B, DK-2200 Copenhagen N, Denmark
| | - Christian Garde
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Copenhagen,, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark.,Center for Biological Sequence Analysis, Technical University of Denmark, Kemitorvet, Building 208, DK-2800 Lyngby, Denmark
| | - Xiaoyong Pan
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Copenhagen,, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark.,Department of Veterinary Clinical and Animal Sciences, University of Copenhagen, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark.,Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Building: 06-2-26, Blegdamsvej 3B, DK-2200 Copenhagen N, Denmark
| | - Alberto Santos
- Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Building: 06-2-26, Blegdamsvej 3B, DK-2200 Copenhagen N, Denmark
| | - Ferhat Alkan
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Copenhagen,, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark.,Department of Veterinary Clinical and Animal Sciences, University of Copenhagen, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark
| | - Christian Anthon
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Copenhagen,, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark.,Department of Veterinary Clinical and Animal Sciences, University of Copenhagen, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark
| | - Christian von Mering
- Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Christopher T Workman
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Copenhagen,, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark.,Center for Biological Sequence Analysis, Technical University of Denmark, Kemitorvet, Building 208, DK-2800 Lyngby, Denmark
| | - Lars Juhl Jensen
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Copenhagen,, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark.,Disease Systems Biology Program, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Building: 06-2-26, Blegdamsvej 3B, DK-2200 Copenhagen N, Denmark
| | - Jan Gorodkin
- Center for Non-coding RNA in Technology and Health, University of Copenhagen, Copenhagen,, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark.,Department of Veterinary Clinical and Animal Sciences, University of Copenhagen, Groennegaardsvej 3, DK-1870 Frederiksberg C, Denmark
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155
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Multiplex shRNA Screening of Germ Cell Development by in Vivo Transfection of Mouse Testis. G3-GENES GENOMES GENETICS 2017; 7:247-255. [PMID: 27856695 PMCID: PMC5217113 DOI: 10.1534/g3.116.036087] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Spermatozoa are one of the few mammalian cell types that cannot be fully derived in vitro, severely limiting the application of modern genomic techniques to study germ cell biology. The current gold standard approach of characterizing single-gene knockout mice is slow as generation of each mutant line can take 6–9 months. Here, we describe an in vivo approach to rapid functional screening of germline genes based on a new nonsurgical, nonviral in vivo transfection method to deliver nucleic acids into testicular germ cells. By coupling multiplex transfection of short hairpin RNA (shRNA) constructs with pooled amplicon sequencing as a readout, we were able to screen many genes for spermatogenesis function in a quick and inexpensive experiment. We transfected nine mouse testes with a pilot pool of RNA interference (RNAi) against well-characterized genes to show that this system is highly reproducible and accurate. With a false negative rate of 18% and a false positive rate of 12%, this method has similar performance as other RNAi screens in the well-described Drosophila model system. In a separate experiment, we screened 26 uncharacterized genes computationally predicted to be essential for spermatogenesis and found numerous candidates for follow-up studies. Finally, as a control experiment, we performed a long-term selection screen in neuronal N2a cells, sampling shRNA frequencies at five sequential time points. By characterizing the effect of both libraries on N2a cells, we show that our screening results from testis are tissue-specific. Our calculations indicate that the current implementation of this approach could be used to screen thousands of protein-coding genes simultaneously in a single mouse testis. The experimental protocols and analysis scripts provided will enable other groups to use this procedure to study diverse aspects of germ cell biology ranging from epigenetics to cell physiology. This approach also has great promise as an applied tool for validating diagnoses made from medical genome sequencing, or designing synthetic biological sequences that can act as potent and highly specific male contraceptives.
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156
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Eppig JT, Smith CL, Blake JA, Ringwald M, Kadin JA, Richardson JE, Bult CJ. Mouse Genome Informatics (MGI): Resources for Mining Mouse Genetic, Genomic, and Biological Data in Support of Primary and Translational Research. Methods Mol Biol 2017; 1488:47-73. [PMID: 27933520 DOI: 10.1007/978-1-4939-6427-7_3] [Citation(s) in RCA: 62] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The Mouse Genome Informatics (MGI), resource ( www.informatics.jax.org ) has existed for over 25 years, and over this time its data content, informatics infrastructure, and user interfaces and tools have undergone dramatic changes (Eppig et al., Mamm Genome 26:272-284, 2015). Change has been driven by scientific methodological advances, rapid improvements in computational software, growth in computer hardware capacity, and the ongoing collaborative nature of the mouse genomics community in building resources and sharing data. Here we present an overview of the current data content of MGI, describe its general organization, and provide examples using simple and complex searches, and tools for mining and retrieving sets of data.
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Affiliation(s)
- Janan T Eppig
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA.
| | - Cynthia L Smith
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA
| | - Judith A Blake
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA
| | - Martin Ringwald
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA
| | - James A Kadin
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA
| | | | - Carol J Bult
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA
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157
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Heat Shock Proteins and Maternal Contribution to Oogenesis and Early Embryogenesis. ADVANCES IN ANATOMY, EMBRYOLOGY, AND CELL BIOLOGY 2017; 222:1-27. [PMID: 28389748 DOI: 10.1007/978-3-319-51409-3_1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Early embryos develop from fertilized eggs using materials that are stored during oocyte growth and which can be defined as maternal contribution (molecules, factors, or determinants). Several heat shock proteins (HSPs) and the heat shock transcriptional factor (HSF) are part of the maternal contribution that is critical for successful embryogenesis and reproduction. A maternal role for heat shock-related genes was mainly demonstrated in genetic experimental organisms (e.g., fly, nematode, mouse). Nowadays, an increasing number of "omics" data are produced from a large panel of organisms implementing a catalog of maternal and/or embryonic HSPs and HSFs. However, for most of them, it remains to better understand their potential roles in this context. Existing and future genome-wide screens mainly set up to create loss-of-function are likely to improve this situation. This chapter will discuss available data from various experimental organisms following the developmental steps from egg production to early embryogenesis.
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158
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Ruffier M, Kähäri A, Komorowska M, Keenan S, Laird M, Longden I, Proctor G, Searle S, Staines D, Taylor K, Vullo A, Yates A, Zerbino D, Flicek P. Ensembl core software resources: storage and programmatic access for DNA sequence and genome annotation. Database (Oxford) 2017; 2017:3074789. [PMID: 28365736 PMCID: PMC5467575 DOI: 10.1093/database/bax020] [Citation(s) in RCA: 35] [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: 10/28/2016] [Revised: 02/07/2017] [Accepted: 02/20/2017] [Indexed: 01/09/2023]
Abstract
The Ensembl software resources are a stable infrastructure to store, access and manipulate genome assemblies and their functional annotations. The Ensembl 'Core' database and Application Programming Interface (API) was our first major piece of software infrastructure and remains at the centre of all of our genome resources. Since its initial design more than fifteen years ago, the number of publicly available genomic, transcriptomic and proteomic datasets has grown enormously, accelerated by continuous advances in DNA-sequencing technology. Initially intended to provide annotation for the reference human genome, we have extended our framework to support the genomes of all species as well as richer assembly models. Cross-referenced links to other informatics resources facilitate searching our database with a variety of popular identifiers such as UniProt and RefSeq. Our comprehensive and robust framework storing a large diversity of genome annotations in one location serves as a platform for other groups to generate and maintain their own tailored annotation. We welcome reuse and contributions: our databases and APIs are publicly available, all of our source code is released with a permissive Apache v2.0 licence at http://github.com/Ensembl and we have an active developer mailing list ( http://www.ensembl.org/info/about/contact/index.html ). Database URL http://www.ensembl.org.
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Affiliation(s)
- Magali Ruffier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Andreas Kähäri
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Monika Komorowska
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Stephen Keenan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Matthew Laird
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ian Longden
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Glenn Proctor
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Steve Searle
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Daniel Staines
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Kieron Taylor
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Alessandro Vullo
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Andrew Yates
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Daniel Zerbino
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
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159
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Abstract
Many publicly available data repositories and resources have been developed to support protein-related information management, data-driven hypothesis generation, and biological knowledge discovery. To help researchers quickly find the appropriate protein-related informatics resources, we present a comprehensive review (with categorization and description) of major protein bioinformatics databases in this chapter. We also discuss the challenges and opportunities for developing next-generation protein bioinformatics databases and resources to support data integration and data analytics in the Big Data era.
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Affiliation(s)
- Chuming Chen
- Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, 19711, USA.
| | - Hongzhan Huang
- Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, 19711, USA
| | - Cathy H Wu
- Center for Bioinformatics and Computational Biology, Department of Computer and Information Sciences, University of Delaware, Newark, DE, 19711, USA
- Protein Information Resource, Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, Washington, DC, 20007, USA
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160
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Global Analysis of Protein Expression of Inner Ear Hair Cells. J Neurosci 2016; 37:1320-1339. [PMID: 28039372 DOI: 10.1523/jneurosci.2267-16.2016] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2016] [Revised: 11/29/2016] [Accepted: 12/19/2016] [Indexed: 11/21/2022] Open
Abstract
The mammalian inner ear (IE) subserves auditory and vestibular sensations via highly specialized cells and proteins. Sensory receptor hair cells (HCs) are necessary for transducing mechanical inputs and stimulating sensory neurons by using a host of known and as yet unknown protein machinery. To understand the protein composition of these unique postmitotic cells, in which irreversible protein degradation or damage can lead to impaired hearing and balance, we analyzed IE samples by tandem mass spectrometry to generate an unbiased, shotgun-proteomics view of protein identities and abundances. By using Pou4f3/eGFP-transgenic mice in which HCs express GFP driven by Pou4f3, we FACS purified a population of HCs to analyze and compare the HC proteome with other IE subproteomes from sensory epithelia and whole IE. We show that the mammalian HC proteome comprises hundreds of uniquely or highly expressed proteins. Our global proteomic analysis of purified HCs extends the existing HC transcriptome, revealing previously undetected gene products and isoform-specific protein expression. Comparison of our proteomic data with mouse and human databases of genetic auditory/vestibular impairments confirms the critical role of the HC proteome for normal IE function, providing a cell-specific pool of candidates for novel, important HC genes. Several proteins identified exclusively in HCs by proteomics and verified by immunohistochemistry map to human genetic deafness loci, potentially representing new deafness genes. SIGNIFICANCE STATEMENT Hearing and balance rely on specialized sensory hair cells (HCs) in the inner ear (IE) to convey information about sound, acceleration, and orientation to the brain. Genetically and environmentally induced perturbations to HC proteins can result in deafness and severe imbalance. We used transgenic mice with GFP-expressing HCs, coupled with FACS sorting and tandem mass spectrometry, to define the most complete HC and IE proteome to date. We show that hundreds of proteins are uniquely identified or enriched in HCs, extending previous gene expression analyses to reveal novel HC proteins and isoforms. Importantly, deafness-linked proteins were significantly enriched in HCs, suggesting that this in-depth proteomic analysis of IE sensory cells may hold potential for deafness gene discovery.
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161
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Munkacsi AB, Hammond N, Schneider RT, Senanayake DS, Higaki K, Lagutin K, Bloor SJ, Ory DS, Maue RA, Chen FW, Hernandez-Ono A, Dahlson N, Repa JJ, Ginsberg HN, Ioannou YA, Sturley SL. Normalization of Hepatic Homeostasis in the Npc1nmf164 Mouse Model of Niemann-Pick Type C Disease Treated with the Histone Deacetylase Inhibitor Vorinostat. J Biol Chem 2016; 292:4395-4410. [PMID: 28031458 DOI: 10.1074/jbc.m116.770578] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Revised: 12/21/2016] [Indexed: 12/31/2022] Open
Abstract
Niemann-Pick type C (NP-C) disease is a fatal genetic lipidosis for which there is no Food and Drug Administration (FDA)-approved therapy. Vorinostat, an FDA-approved inhibitor of histone deacetylases, ameliorates lysosomal lipid accumulation in cultured NP-C patient fibroblasts. To assess the therapeutic potential of histone deacetylase inhibition, we pursued these in vitro observations in two murine models of NP-C disease. Npc1nmf164 mice, which express a missense mutation in the Npc1 gene, were treated intraperitoneally, from weaning, with the maximum tolerated dose of vorinostat (150 mg/kg, 5 days/week). Disease progression was measured via gene expression, liver function and pathology, serum and tissue lipid levels, body weight, and life span. Transcriptome analyses of treated livers indicated multiple changes consistent with reversal of liver dysfunction that typifies NP-C disease. Significant improvements in liver pathology and function were achieved by this treatment regimen; however, NPC1 protein maturation and levels, disease progression, weight loss, and animal morbidity were not detectably altered. Vorinostat concentrations were >200 μm in the plasma compartment of treated animals but were almost 100-fold lower in brain tissue. Apolipoprotein B metabolism and the expression of key components of lipid homeostasis in primary hepatocytes from null (Npc1-/-) and missense (Npc1nmf164 ) mutant mice were altered by vorinostat treatment, consistent with a response by these cells independent of the status of the Npc1 locus. These results suggest that HDAC inhibitors have utility to treat visceral NP-C disease. However, it is clear that improved blood-brain barrier penetration will be required to alleviate the neurological symptoms of human NP-C disease.
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Affiliation(s)
- Andrew B Munkacsi
- From the School of Biological Sciences and .,Centre for Biodiscovery, Victoria University of Wellington, Wellington 6012, New Zealand
| | | | | | | | - Katsumi Higaki
- the Division of Functional Genomics, Research Center for Bioscience and Technology, Tottori University, Yonago 683-8503, Japan
| | | | | | - Daniel S Ory
- the Department of Medicine, Washington University School of Medicine, St. Louis, Missouri 63110
| | - Robert A Maue
- the Department of Physiology and Neurobiology and the Department of Biochemistry, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire 03755
| | - Fannie W Chen
- the Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, New York 10029
| | | | - Nicole Dahlson
- the Departments of Physiology and Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas 75390, and
| | - Joyce J Repa
- the Departments of Physiology and Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas 75390, and
| | | | - Yiannis A Ioannou
- the Department of Genetics and Genomic Sciences, Mount Sinai School of Medicine, New York, New York 10029
| | - Stephen L Sturley
- the Department of Genetics and Development, Columbia University Medical Center, New York, New York 10032
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162
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Accelerating Adverse Outcome Pathway Development Using Publicly Available Data Sources. Curr Environ Health Rep 2016; 3:53-63. [PMID: 26809562 DOI: 10.1007/s40572-016-0079-y] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
The adverse outcome pathway (AOP) concept links molecular perturbations with organism and population-level outcomes to support high-throughput toxicity (HTT) testing. International efforts are underway to define AOPs and store the information supporting these AOPs in a central knowledge base; however, this process is currently labor-intensive and time-consuming. Publicly available data sources provide a wealth of information that could be used to define computationally predicted AOPs (cpAOPs), which could serve as a basis for creating expert-derived AOPs in a much more efficient way. Computational tools for mining large datasets provide the means for extracting and organizing the information captured in these public data sources. Using cpAOPs as a starting point for expert-derived AOPs should accelerate AOP development. Coupling this with tools to coordinate and facilitate the expert development efforts will increase the number and quality of AOPs produced, which should play a key role in advancing the adoption of HTT testing, thereby reducing the use of animals in toxicity testing and greatly increasing the number of chemicals that can be tested.
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163
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Manta AK, Papadopoulou D, Polyzos AP, Fragopoulou AF, Skouroliakou AS, Thanos D, Stravopodis DJ, Margaritis LH. Mobile-phone radiation-induced perturbation of gene-expression profiling, redox equilibrium and sporadic-apoptosis control in the ovary of Drosophila melanogaster. Fly (Austin) 2016; 11:75-95. [PMID: 27960592 DOI: 10.1080/19336934.2016.1270487] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
The daily use by people of wireless communication devices has increased exponentially in the last decade, begetting concerns regarding its potential health hazards. Drosophila melanogaster four days-old adult female flies were exposed for 30 min to radiation emitted by a commercial mobile phone at a SAR of 0.15 W/kg and a SAE of 270 J/kg. ROS levels and apoptotic follicles were assayed in parallel with a genome-wide microarrays analysis. ROS cellular contents were found to increase by 1.6-fold (x), immediately after the end of exposure, in follicles of pre-choriogenic stages (germarium - stage 10), while sporadically generated apoptotic follicles (germarium 2b and stages 7-9) presented with an averaged 2x upregulation in their sub-population mass, 4 h after fly's irradiation with mobile device. Microarray analysis revealed 168 genes being differentially expressed, 2 h post-exposure, in response to radiofrequency (RF) electromagnetic field-radiation exposure (≥1.25x, P < 0.05) and associated with multiple and critical biological processes, such as basic metabolism and cellular subroutines related to stress response and apoptotic death. Exposure of adult flies to mobile-phone radiation for 30 min has an immediate impact on ROS production in animal's ovary, which seems to cause a global, systemic and non-targeted transcriptional reprogramming of gene expression, 2 h post-exposure, being finally followed by induction of apoptosis 4 h after the end of exposure. Conclusively, this unique type of pulsed radiation, mainly being derived from daily used mobile phones, seems capable of mobilizing critical cytopathic mechanisms, and altering fundamental genetic programs and networks in D. melanogaster.
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Affiliation(s)
- Areti K Manta
- a Section of Cell Biology and Biophysics, Department of Biology , National and Kapodistrian University of Athens , Athens , Greece
| | - Deppie Papadopoulou
- b Basic Research Center , Biomedical Research Foundation of the Academy of Athens , Athens , Greece
| | - Alexander P Polyzos
- b Basic Research Center , Biomedical Research Foundation of the Academy of Athens , Athens , Greece
| | - Adamantia F Fragopoulou
- a Section of Cell Biology and Biophysics, Department of Biology , National and Kapodistrian University of Athens , Athens , Greece
| | - Aikaterini S Skouroliakou
- c Department of Energy Technology Engineering , Technological Educational Institute of Athens , Athens , Greece
| | - Dimitris Thanos
- b Basic Research Center , Biomedical Research Foundation of the Academy of Athens , Athens , Greece
| | - Dimitrios J Stravopodis
- a Section of Cell Biology and Biophysics, Department of Biology , National and Kapodistrian University of Athens , Athens , Greece
| | - Lukas H Margaritis
- a Section of Cell Biology and Biophysics, Department of Biology , National and Kapodistrian University of Athens , Athens , Greece
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164
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Shaw DR. Searching the Mouse Genome Informatics (MGI) Resources for Information on Mouse Biology from Genotype to Phenotype. ACTA ACUST UNITED AC 2016; 56:1.7.1-1.7.16. [PMID: 27930808 DOI: 10.1002/cpbi.18] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
The Mouse Genome Informatics (MGI) resource provides the research community with access to information on the genetics, genomics, and biology of the laboratory mouse. Core data in MGI include gene characterization and function, phenotype and disease model descriptions, DNA and protein sequence data, gene expression data, vertebrate homologies, SNPs, mapping data, and links to other bioinformatics databases. Semantic integration is supported through the use of standardized nomenclature, and through the use of controlled vocabularies such as the mouse Anatomical Dictionary, the Mammalian Phenotype Ontology, and the Gene Ontologies. MGI extracts and organizes data from primary literature. MGI data are shared with and widely displayed from other bioinformatics resources. The database is updated weekly with curated annotations, and regularly adds new datasets and features. This unit provides a guide to using the MGI bioinformatics resource. © 2016 by John Wiley & Sons, Inc.
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Affiliation(s)
- David R Shaw
- MGI User Support, The Jackson Laboratory, Bar Harbor, Maine
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165
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Adam S, Melguizo Sanchis D, El-Kamah G, Samarasinghe S, Alharthi S, Armstrong L, Lako M. Concise Review: Getting to the Core of Inherited Bone Marrow Failures. Stem Cells 2016; 35:284-298. [PMID: 27870251 PMCID: PMC5299470 DOI: 10.1002/stem.2543] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2016] [Revised: 10/15/2016] [Accepted: 10/28/2016] [Indexed: 12/20/2022]
Abstract
Bone marrow failure syndromes (BMFS) are a group of disorders with complex pathophysiology characterized by a common phenotype of peripheral cytopenia and/or hypoplastic bone marrow. Understanding genetic factors contributing to the pathophysiology of BMFS has enabled the identification of causative genes and development of diagnostic tests. To date more than 40 mutations in genes involved in maintenance of genomic stability, DNA repair, ribosome and telomere biology have been identified. In addition, pathophysiological studies have provided insights into several biological pathways leading to the characterization of genotype/phenotype correlations as well as the development of diagnostic approaches and management strategies. Recent developments in bone marrow transplant techniques and the choice of conditioning regimens have helped improve transplant outcomes. However, current morbidity and mortality remain unacceptable underlining the need for further research in this area. Studies in mice have largely been unable to mimic disease phenotype in humans due to difficulties in fully replicating the human mutations and the differences between mouse and human cells with regard to telomere length regulation, processing of reactive oxygen species and lifespan. Recent advances in induced pluripotency have provided novel insights into disease pathogenesis and have generated excellent platforms for identifying signaling pathways and functional mapping of haplo‐insufficient genes involved in large‐scale chromosomal deletions–associated disorders. In this review, we have summarized the current state of knowledge in the field of BMFS with specific focus on modeling the inherited forms and how to best utilize these models for the development of targeted therapies. Stem Cells2017;35:284–298
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Affiliation(s)
- Soheir Adam
- Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA.,Hematology Department, Medical School, King Abdulaziz University, Jeddah, KSA
| | | | - Ghada El-Kamah
- Division of Human Genetics & Genome Research, National Research Center, Cairo, Egypt
| | - Sujith Samarasinghe
- Department of Hematology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Sameer Alharthi
- Princess Al Jawhara Al-Brahim Center of Excellence in Research of Hereditary Disorders, King Abdulaziz University, KSA
| | - Lyle Armstrong
- Institute of Genetic Medicine, Newcastle University, United Kingdom
| | - Majlinda Lako
- Institute of Genetic Medicine, Newcastle University, United Kingdom
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166
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Chen Y, Xu R. Drug repurposing for glioblastoma based on molecular subtypes. J Biomed Inform 2016; 64:131-138. [PMID: 27697594 PMCID: PMC6146394 DOI: 10.1016/j.jbi.2016.09.019] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Revised: 08/23/2016] [Accepted: 09/27/2016] [Indexed: 01/12/2023]
Abstract
A recent multi-platform analysis by The Cancer Genome Atlas identified four distinct molecular subtypes for glioblastoma (GBM) and demonstrated that the subtypes correlate with clinical phenotypes and treatment responses. In this study, we developed a computational drug repurposing approach to predict GBM drugs based on the molecular subtypes. Our approach leverages the genomic signature for each GBM subtype, and integrates the human cancer genomics with mouse phenotype data to identify the opportunity of reusing the FDA-approved agents to treat specific GBM subtypes. Specifically, we first constructed the phenotype profile for each GBM subtype using their genomic signatures. For each approved drug, we also constructed a phenotype profile using the drug target genes. Then we developed an algorithm to match and prioritize drugs based on their phenotypic similarities to the GBM subtypes. Our approach is highly generalizable for other disorders if provided with a list of disorder-specific genes. We first evaluated the approach in predicting drugs for the whole GBM. For a combined set of approved, potential and off-label GBM drugs, we achieved a median rank of 9.3%, which is significantly higher (p
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Affiliation(s)
- Yang Chen
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, United States
| | - Rong Xu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, United States.
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167
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Rudolph JD, de Graauw M, van de Water B, Geiger T, Sharan R. Elucidation of Signaling Pathways from Large-Scale Phosphoproteomic Data Using Protein Interaction Networks. Cell Syst 2016; 3:585-593.e3. [DOI: 10.1016/j.cels.2016.11.005] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Revised: 08/24/2016] [Accepted: 11/09/2016] [Indexed: 01/01/2023]
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168
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Kernohan KD, McBride A, Xi Y, Martin N, Schwartzentruber J, Dyment DA, Majewski J, Blaser S, Boycott KM, Chitayat D. Loss of the arginine methyltranserase PRMT7 causes syndromic intellectual disability with microcephaly and brachydactyly. Clin Genet 2016; 91:708-716. [PMID: 27718516 DOI: 10.1111/cge.12884] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Revised: 09/30/2016] [Accepted: 09/30/2016] [Indexed: 01/09/2023]
Abstract
Post-translational protein modifications exponentially expand the functional complement of proteins encoded by the human genome. One such modification is the covalent addition of a methyl group to arginine or lysine residues, which is used to regulate a substantial proportion of the proteome. Arginine and lysine methylation are catalyzed by protein arginine methyltransferase (PRMTs) and protein lysine methyltransferase proteins (PKMTs), respectively; each methyltransferase has a specific set of target substrates. Here, we report a male with severe intellectual disability, facial dysmorphism, microcephaly, short stature, brachydactyly, cryptorchidism and seizures who was found to have a homozygous 15,309 bp deletion encompassing the transcription start site of PRMT7, which we confirmed is functionally a null allele. We show that the patient's cells have decreased levels of protein arginine methylation, and that affected proteins include the essential histones, H2B and H4. Finally, we demonstrate that patient cells have altered Wnt signaling, which may have contributed to the skeletal abnormalities. Our findings confirm the recent disease association of PRMT7, expand the phenotypic manifestations of this disorder and provide insight into the molecular pathogenesis of this new condition.
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Affiliation(s)
- K D Kernohan
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
| | - A McBride
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
| | - Y Xi
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
| | - N Martin
- The Prenatal Diagnosis and Medical Genetics Program, Department of Obstetrics and Gynecology, Mount Sinai Hospital, University of Toronto, Toronto, Canada
| | - J Schwartzentruber
- Genome Quebec Innovation Centre, McGill University, Montreal, Canada.,Department of Human Genetics, McGill University, Montreal, Canada
| | - D A Dyment
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada.,Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - J Majewski
- Genome Quebec Innovation Centre, McGill University, Montreal, Canada.,Department of Human Genetics, McGill University, Montreal, Canada
| | - S Blaser
- Department of Diagnostic Imaging, Hospital for Sick Children, University of Toronto, Toronto, Canada
| | -
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada
| | - K M Boycott
- Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Canada.,Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - D Chitayat
- The Prenatal Diagnosis and Medical Genetics Program, Department of Obstetrics and Gynecology, Mount Sinai Hospital, University of Toronto, Toronto, Canada.,Department of Pediatrics, Division of Clinical and Metabolic Genetics, Hospital for Sick Children, University of Toronto, Toronto, Canada
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169
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Snijders AM, Langley SA, Kim YM, Brislawn CJ, Noecker C, Zink EM, Fansler SJ, Casey CP, Miller DR, Huang Y, Karpen GH, Celniker SE, Brown JB, Borenstein E, Jansson JK, Metz TO, Mao JH. Influence of early life exposure, host genetics and diet on the mouse gut microbiome and metabolome. Nat Microbiol 2016; 2:16221. [PMID: 27892936 DOI: 10.1038/nmicrobiol.2016.221] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2016] [Accepted: 10/07/2016] [Indexed: 12/22/2022]
Abstract
Although the gut microbiome plays important roles in host physiology, health and disease1, we lack understanding of the complex interplay between host genetics and early life environment on the microbial and metabolic composition of the gut. We used the genetically diverse Collaborative Cross mouse system2 to discover that early life history impacts the microbiome composition, whereas dietary changes have only a moderate effect. By contrast, the gut metabolome was shaped mostly by diet, with specific non-dietary metabolites explained by microbial metabolism. Quantitative trait analysis identified mouse genetic trait loci (QTL) that impact the abundances of specific microbes. Human orthologues of genes in the mouse QTL are implicated in gastrointestinal cancer. Additionally, genes located in mouse QTL for Lactobacillales abundance are implicated in arthritis, rheumatic disease and diabetes. Furthermore, Lactobacillales abundance was predictive of higher host T-helper cell counts, suggesting an important link between Lactobacillales and host adaptive immunity.
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Affiliation(s)
- Antoine M Snijders
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Sasha A Langley
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Young-Mo Kim
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Colin J Brislawn
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Cecilia Noecker
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA
| | - Erika M Zink
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Sarah J Fansler
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Cameron P Casey
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Darla R Miller
- Systems Genetics Core Facility, Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Yurong Huang
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Gary H Karpen
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA.,Department of Molecular and Cell Biology, University of California, Berkeley, California 94720, USA
| | - Susan E Celniker
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - James B Brown
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Elhanan Borenstein
- Department of Genome Sciences, University of Washington, Seattle, Washington 98105, USA.,Department of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, USA.,Santa Fe Institute, Santa Fe, New Mexico 87501, USA
| | - Janet K Jansson
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Thomas O Metz
- Earth and Biological Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - Jian-Hua Mao
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
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170
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Katsube T, Wang B, Tanaka K, Ninomiya Y, Varès G, Kawagoshi T, Shiomi N, Kubota Y, Liu Q, Morita A, Nakajima T, Nenoi M. Effects of chronic restraint-induced stress on radiation-induced chromosomal aberrations in mouse splenocytes. MUTATION RESEARCH-GENETIC TOXICOLOGY AND ENVIRONMENTAL MUTAGENESIS 2016; 813:18-26. [PMID: 28010925 DOI: 10.1016/j.mrgentox.2016.11.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2016] [Revised: 10/25/2016] [Accepted: 11/21/2016] [Indexed: 12/16/2022]
Abstract
Both ionizing radiation (IR) and psychological stress (PS) cause detrimental effects on humans. A recent study showed that chronic restraint-induced PS (CRIPS) diminished the functions of Trp53 and enhanced radiocarcinogenesis in Trp53-heterozygous (Trp53+/-) mice. These findings had a marked impact on the academic field as well as the general public, particularly among residents living in areas radioactively contaminated by nuclear accidents. In an attempt to elucidate the modifying effects of CRIPS on radiation-induced health consequences in Trp53 wild-type (Trp53+/+) animals, investigations involving multidisciplinary analyses were performed. We herein demonstrated that CRIPS induced changes in the frequency of IR-induced chromosomal aberrations (CAs) in splenocytes. Five-week-old male Trp53+/+ C57BL/6J mice were restrained for 6h per day for 28 consecutive days, and total body irradiation (TBI) at a dose of 4Gy was performed on the 8th day. Metaphase chromosome spreads prepared from splenocytes at the end of the 28-day restraint regimen were painted with fluorescence in situ hybridization (FISH) probes for chromosomes 1, 2, and 3. The results obtained showed that CRIPS alone did not induce CAs, while TBI caused significant increases in CAs, mostly translocations. Translocations appeared at a lower frequency in mice exposed to TBI plus CRIPS than in those exposed to TBI alone. No significant differences were observed in the frequencies of the other types of CAs (insertions, dicentrics, and fragments) visualized with FISH between these experimental groups (TBI+CRIPS vs. TBI). These results suggest that CRIPS does not appear to synergize with the clastogenicity of IR.
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Affiliation(s)
- Takanori Katsube
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, 263-8555, Japan.
| | - Bing Wang
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, 263-8555, Japan.
| | - Kaoru Tanaka
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, 263-8555, Japan.
| | - Yasuharu Ninomiya
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, 263-8555, Japan.
| | - Guillaume Varès
- Advanced Medical Instrumentation Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, 904-0495, Japan.
| | - Taiki Kawagoshi
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, 263-8555, Japan.
| | - Naoko Shiomi
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, 263-8555, Japan.
| | - Yoshihisa Kubota
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, 263-8555, Japan.
| | - Qiang Liu
- Institute of Radiation Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300192, PR China.
| | - Akinori Morita
- Department of Biomedical Science and Technology, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, 770-8503, Japan.
| | - Tetsuo Nakajima
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, 263-8555, Japan.
| | - Mitsuru Nenoi
- National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, 263-8555, Japan.
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171
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Towards Functional Annotation of the Preimplantation Transcriptome: An RNAi Screen in Mammalian Embryos. Sci Rep 2016; 6:37396. [PMID: 27869233 PMCID: PMC5116644 DOI: 10.1038/srep37396] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2016] [Accepted: 10/27/2016] [Indexed: 12/19/2022] Open
Abstract
With readily available transcriptome-wide data, understanding the role of each expressed gene is an essential next step. Although RNAi technologies allow for genome-wide screens in cell culture, these approaches cannot replace strategies for discovery in the embryo. Here we present, for the first time, a knockdown screen in mouse preimplantation embryos. Early mammalian development encompasses dynamic cellular, molecular and epigenetic events that are largely conserved from mouse to man. We assayed 712 genes for requirements during preimplantation. We identified 59 genes required for successful development or outgrowth and implantation. We have characterized each phenotype and revealed cellular, molecular, and lineage specific defects following knockdown of transcript. Induced network analyses demonstrate this as a valid approach to identify networks of genes that play important roles during preimplantation. Our approach provides a robust and efficient strategy towards identification of novel phenotypes during mouse preimplantation and facilitates functional annotation of the mammalian transcriptome.
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172
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173
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Roberts JH, Liu F, Karnuta JM, Fitzgerald MC. Discovery of Age-Related Protein Folding Stability Differences in the Mouse Brain Proteome. J Proteome Res 2016; 15:4731-4741. [PMID: 27806573 DOI: 10.1021/acs.jproteome.6b00927] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Described here is the application of thermodynamic stability measurements to study age-related differences in the folding and stability of proteins in a rodent model of aging. Thermodynamic stability profiles were generated for 809 proteins in brain cell lysates from mice, aged 6 (n = 7) and 18 months (n = 9) using the Stability of Proteins from Rates of Oxidation (SPROX) technique. The biological variability of the protein stability measurements was low and within the experimental error of SPROX. A total of 83 protein hits were detected with age-related stability differences in the brain samples. Remarkably, the large majority of the brain protein hits were destabilized in the old mice, and the hits were enriched in proteins that have slow turnover rates (p < 0.07). Furthermore, 70% of the hits have been previously linked to aging or age-related diseases. These results help validate the use of thermodynamic stability measurements to capture relevant age-related proteomic changes and establish a new biophysical link between these proteins and aging.
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Affiliation(s)
- Julia H Roberts
- Department of Chemistry, Duke University , Durham, North Carolina 27708, United States
| | - Fang Liu
- Department of Chemistry, Duke University , Durham, North Carolina 27708, United States
| | - Jaret M Karnuta
- Department of Chemistry, Duke University , Durham, North Carolina 27708, United States
| | - Michael C Fitzgerald
- Department of Chemistry, Duke University , Durham, North Carolina 27708, United States
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174
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Gundersen GW, Jagodnik KM, Woodland H, Fernandez NF, Sani K, Dohlman AB, Ung PMU, Monteiro CD, Schlessinger A, Ma'ayan A. GEN3VA: aggregation and analysis of gene expression signatures from related studies. BMC Bioinformatics 2016; 17:461. [PMID: 27846806 PMCID: PMC5111283 DOI: 10.1186/s12859-016-1321-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Accepted: 11/04/2016] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Genome-wide gene expression profiling of mammalian cells is becoming a staple of many published biomedical and biological research studies. Such data is deposited into data repositories such as the Gene Expression Omnibus (GEO) for potential reuse. However, these repositories currently do not provide simple interfaces to systematically analyze collections of related studies. RESULTS Here we present GENE Expression and Enrichment Vector Analyzer (GEN3VA), a web-based system that enables the integrative analysis of aggregated collections of tagged gene expression signatures identified and extracted from GEO. Each tagged collection of signatures is presented in a report that consists of heatmaps of the differentially expressed genes; principal component analysis of all signatures; enrichment analysis with several gene set libraries across all signatures, which we term enrichment vector analysis; and global mapping of small molecules that are predicted to reverse or mimic each signature in the aggregate. We demonstrate how GEN3VA can be used to identify common molecular mechanisms of aging by analyzing tagged signatures from 244 studies that compared young vs. old tissues in mammalian systems. In a second case study, we collected 86 signatures from treatment of human cells with dexamethasone, a glucocorticoid receptor (GR) agonist. Our analysis confirms consensus GR target genes and predicts potential drug mimickers. CONCLUSIONS GEN3VA can be used to identify, aggregate, and analyze themed collections of gene expression signatures from diverse but related studies. Such integrative analyses can be used to address concerns about data reproducibility, confirm results across labs, and discover new collective knowledge by data reuse. GEN3VA is an open-source web-based system that is freely available at: http://amp.pharm.mssm.edu/gen3va .
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Affiliation(s)
- Gregory W Gundersen
- Department of Pharmacological Sciences, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA.,Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Kathleen M Jagodnik
- Fluid Physics and Transport Processes Branch, NASA Glenn Research Center, 21000 Brookpark Rd, Cleveland, OH, 44135, USA.,Center for Space Medicine, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX, 77030, USA
| | - Holly Woodland
- , Daylesford, The Fairway, Weybridge, Surrey, KT13 0RZ, UK
| | - Nicholas F Fernandez
- Department of Pharmacological Sciences, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA.,Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Kevin Sani
- Department of Pharmacological Sciences, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA.,Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Anders B Dohlman
- Department of Pharmacological Sciences, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA.,Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Peter Man-Un Ung
- Department of Pharmacological Sciences, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Caroline D Monteiro
- Department of Pharmacological Sciences, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA.,Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Avner Schlessinger
- Department of Pharmacological Sciences, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA
| | - Avi Ma'ayan
- Department of Pharmacological Sciences, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA. .,Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, Box 1603, New York, NY, 10029, USA.
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175
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Genome Sequencing of Chromosome 1 Substitution Lines Derived from Chinese Wild Mice Revealed a Unique Resource for Genetic Studies of Complex Traits. G3-GENES GENOMES GENETICS 2016; 6:3571-3580. [PMID: 27605517 PMCID: PMC5100856 DOI: 10.1534/g3.116.033902] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Mouse resources such as Collaborative Cross, outbred stocks, Hybrid Mouse Diversity Panel, and chromosome substitution strains have been instrumental to many progresses in the studies of complex traits genetics. We have established a population of chromosome 1 (Chr 1) substitution lines (C1SLs) in which donor chromosomes were derived from Chinese wild mice. Genome sequencing of 18 lines of this population showed that Chr 1 had been replaced by the donor chromosome. About 4.5 million unique single nucleotide polymorphisms and indels were discovered on Chr 1, of which 1.3 million were novel. Compared with sequenced classical inbred strains, Chr 1 of each C1SL had fivefold more variants, and more loss of function and potentially regulatory variants. Further haplotype analysis showed that the donor chromosome accumulated more historical recombination events, with the largest haplotype block being only 100 kb, and about 57% of the blocks were <1 kb. Subspecies origin analysis showed that these chromosomes had a mosaic genome structure that dominantly originated from Mus musculus musculus and M. m. castaneus subspecies, except for the C57BL/6J-Chr1KM line from M. m. domesticus. In addition, phenotyping four of these lines on blood biochemistry suggested that there were substantial phenotypic variations among our lines, especially line C57BL/6J-Chr1HZ and donor strain C57BL/6J. Further gene ontology enrichment revealed that the differentially expressed genes among liver-expressed genes between C57BL/6J and C57BL/6J-Chr1HZ were enriched in lipid metabolism biological processes. All these characteristics enable C1SLs to be a unique resource for identifying and fine mapping quantitative trait loci on mouse Chr 1, and carrying out systems genetics studies of complex traits.
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176
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Yan H, Fei N, Wu G, Zhang C, Zhao L, Zhang M. Regulated Inflammation and Lipid Metabolism in Colon mRNA Expressions of Obese Germfree Mice Responding to Enterobacter cloacae B29 Combined with the High Fat Diet. Front Microbiol 2016; 7:1786. [PMID: 27877172 PMCID: PMC5099522 DOI: 10.3389/fmicb.2016.01786] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Accepted: 10/24/2016] [Indexed: 01/07/2023] Open
Abstract
Increased evidences have demonstrated that gut microbiota targeted diet intervention can alleviate obesity and related metabolic disorders. The underlying mechanism of interactions among diet, microbiota, and host still remains unclear. Enterobacter cloacae B29, an endotoxin-producing strain dominated in the gut of a morbidly obese volunteer (weight 174.8 kg, BMI 58.8 kg m-2) was isolated and transplanted to germfree mice (inoculated 1010 cells of B29 per day for 1 week). Using deep mRNA sequencing technology, we compared different gene expression profiles in the colon samples of the germfree mice treated with/without B29 and/or high fat diet (HFD) for 16 weeks and identified 279 differential expressed genes in total, including up-regulated genes Apoa4 (fold change, 2.77), Ido1 (2.66), Cyp4a10 (7.01), and down-regulated genes Cyp2e1 (0.11), Cyp26b1 (0.34), Akr1b7 (0.42), Adipoq (0.36), Cyp1a1 (0.11), Apoa1 (0.44), Npc1l1 (0.37), Tff2 (0.13), Apoc1 (0.30), Ctla2a (0.34), Mttp (0.49), Lpl (0.48). Fifty-nine GO biological processes and five KEGG pathways, particularly the peroxisome proliferator-activated receptors signaling pathway, were significantly enriched in response to HFD+B29, which were mainly relevant to inflammation and the metabolism of lipid, lipoprotein, and sterols. These functional changes were consistent with the developed obesity, insulin-resistance, and aggravated inflammatory conditions of the HFD+B29 mice. This work provides insight into the gene expression changes in response to HFD+B29, helping to understand the mechanism of the interactions among HFD, B29 and the germfree mice.
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Affiliation(s)
- Huiying Yan
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University Shanghai, China
| | - Na Fei
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University Shanghai, China
| | - Guojun Wu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University Shanghai, China
| | - Chenhong Zhang
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University Shanghai, China
| | - Liping Zhao
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University Shanghai, China
| | - Menghui Zhang
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic and Developmental Sciences, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University Shanghai, China
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177
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Shu L, Zhao Y, Kurt Z, Byars SG, Tukiainen T, Kettunen J, Orozco LD, Pellegrini M, Lusis AJ, Ripatti S, Zhang B, Inouye M, Mäkinen VP, Yang X. Mergeomics: multidimensional data integration to identify pathogenic perturbations to biological systems. BMC Genomics 2016; 17:874. [PMID: 27814671 PMCID: PMC5097440 DOI: 10.1186/s12864-016-3198-9] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 10/25/2016] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Complex diseases are characterized by multiple subtle perturbations to biological processes. New omics platforms can detect these perturbations, but translating the diverse molecular and statistical information into testable mechanistic hypotheses is challenging. Therefore, we set out to create a public tool that integrates these data across multiple datasets, platforms, study designs and species in order to detect the most promising targets for further mechanistic studies. RESULTS We developed Mergeomics, a computational pipeline consisting of independent modules that 1) leverage multi-omics association data to identify biological processes that are perturbed in disease, and 2) overlay the disease-associated processes onto molecular interaction networks to pinpoint hubs as potential key regulators. Unlike existing tools that are mostly dedicated to specific data type or settings, the Mergeomics pipeline accepts and integrates datasets across platforms, data types and species. We optimized and evaluated the performance of Mergeomics using simulation and multiple independent datasets, and benchmarked the results against alternative methods. We also demonstrate the versatility of Mergeomics in two case studies that include genome-wide, epigenome-wide and transcriptome-wide datasets from human and mouse studies of total cholesterol and fasting glucose. In both cases, the Mergeomics pipeline provided statistical and contextual evidence to prioritize further investigations in the wet lab. The software implementation of Mergeomics is freely available as a Bioconductor R package. CONCLUSION Mergeomics is a flexible and robust computational pipeline for multidimensional data integration. It outperforms existing tools, and is easily applicable to datasets from different studies, species and omics data types for the study of complex traits.
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Affiliation(s)
- Le Shu
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Yuqi Zhao
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Zeyneb Kurt
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sean Geoffrey Byars
- Center for Systems Genomics, University of Melbourne, Melbourne, Australia.,School of BioSciences, University of Melbourne, Melbourne, Australia
| | | | | | - Luz D Orozco
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Aldons J Lusis
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Bin Zhang
- Department of Genetics and Genomics Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael Inouye
- Center for Systems Genomics, University of Melbourne, Melbourne, Australia.,School of BioSciences, University of Melbourne, Melbourne, Australia.,Department of Pathology, University of Melbourne, Melbourne, Australia
| | - Ville-Petteri Mäkinen
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA. .,South Australian Health and Medical Research Institute, Adelaide, Australia. .,School of Biological Sciences, University of Adelaide, Adelaide, Australia. .,Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.
| | - Xia Yang
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, USA. .,Insitute for Quantitative and Computational Biosciences, University of California, Los Angeles, Los Angeles, CA, USA.
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178
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Reutter H, Hilger AC, Hildebrandt F, Ludwig M. Underlying genetic factors of the VATER/VACTERL association with special emphasis on the "Renal" phenotype. Pediatr Nephrol 2016; 31:2025-33. [PMID: 26857713 PMCID: PMC5207487 DOI: 10.1007/s00467-016-3335-3] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Revised: 01/14/2016] [Accepted: 01/15/2016] [Indexed: 12/18/2022]
Abstract
The acronym VATER/VACTERL association (OMIM #192350) refers to the rare non-random co-occurrence of the following component features (CFs): vertebral defects (V), anorectal malformations (A), cardiac defects (C), tracheoesophageal fistula with or without esophageal atresia (TE), renal malformations (R), and limb defects (L). According to epidemiological studies, the majority of patients with VATER/VACTERL association present with a "Renal" phenotype comprising a large spectrum of congenital renal anomalies. This finding is supported by evidence linking all of the human disease genes for the VATER/VACTERL association identified to date, namely, FGF8, FOXF1, HOXD13, LPP, TRAP1, and ZIC3, with renal malformations. Here we review these genotype-phenotype correlations and suggest that the elucidation of the genetic causes of the VATER/VACTERL association will ultimately provide insights into the genetic causes of the complete spectrum of congenital renal anomalies per se.
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Affiliation(s)
- Heiko Reutter
- Institute of Human Genetics, University of Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany. .,Department of Neonatology and Pediatric Intensive Care, Children's Hospital-University of Bonn, Bonn, Germany.
| | - Alina C Hilger
- Institute of Human Genetics, University of Bonn, Sigmund-Freud-Str. 25, 53127, Bonn, Germany
| | - Friedhelm Hildebrandt
- Department of Medicine, Boston Children's Hospital-Harvard Medical School, Boston, MA, USA
| | - Michael Ludwig
- Department of Clinical Chemistry and Clinical Pharmacology, University of Bonn, Bonn, Germany
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179
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Tao J, Xu E, Zhao Y, Singh S, Li X, Couchy G, Chen X, Zucman-Rossi J, Chikina M, Monga SPS. Modeling a human hepatocellular carcinoma subset in mice through coexpression of met and point-mutant β-catenin. Hepatology 2016; 64:1587-1605. [PMID: 27097116 PMCID: PMC5073058 DOI: 10.1002/hep.28601] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Revised: 03/18/2016] [Accepted: 04/13/2016] [Indexed: 12/24/2022]
Abstract
UNLABELLED Hepatocellular cancer (HCC) remains a significant therapeutic challenge due to its poorly understood molecular basis. In the current study, we investigated two independent cohorts of 249 and 194 HCC cases for any combinatorial molecular aberrations. Specifically we assessed for simultaneous HMET expression or hMet activation and catenin β1 gene (CTNNB1) mutations to address any concomitant Met and Wnt signaling. To investigate cooperation in tumorigenesis, we coexpressed hMet and β-catenin point mutants (S33Y or S45Y) in hepatocytes using sleeping beauty transposon/transposase and hydrodynamic tail vein injection and characterized tumors for growth, signaling, gene signatures, and similarity to human HCC. Missense mutations in exon 3 of CTNNB1 were identified in subsets of HCC patients. Irrespective of amino acid affected, all exon 3 mutations induced similar changes in gene expression. Concomitant HMET overexpression or hMet activation and CTNNB1 mutations were evident in 9%-12.5% of HCCs. Coexpression of hMet and mutant-β-catenin led to notable HCC in mice. Tumors showed active Wnt and hMet signaling with evidence of glutamine synthetase and cyclin D1 positivity and mitogen-activated protein kinase/extracellular signal-regulated kinase, AKT/Ras/mammalian target of rapamycin activation. Introduction of dominant-negative T-cell factor 4 prevented tumorigenesis. The gene expression of mouse tumors in hMet-mutant β-catenin showed high correlation, with subsets of human HCC displaying concomitant hMet activation signature and CTNNB1 mutations. CONCLUSION We have identified cooperation of hMet and β-catenin activation in a subset of HCC patients and modeled this human disease in mice with a significant transcriptomic intersection; this model will provide novel insight into the biology of this tumor and allow us to evaluate novel therapies as a step toward precision medicine. (Hepatology 2016;64:1587-1605).
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Affiliation(s)
- Junyan Tao
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Emily Xu
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yifei Zhao
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sucha Singh
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Xiaolei Li
- Department of Bioengineering and Therapeutic Sciences, University California, San Francisco, CA,Department of Hepatobiliary Surgery, Xijing Hospital, The Fourth Military Medical University, Xi'an, Shaanxi, P.R. China
| | - Gabrielle Couchy
- Inserm, UMR-1162, Génomique fonctionnelle des Tumeurs solides, Equipe Labellisée Ligue Contre le Cancer, Paris, F-75010 France,Université Paris Descartes, Labex Immuno-Oncology, Sorbonne Paris Cité, F-75010 Paris, France,Université Paris 13, Sorbonne Paris Cité, UFR SMBH, F-93000 Bobigny, France,Université Paris Diderot, IUH, F-75010 Paris
| | - Xin Chen
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, P.R. China,Department of Bioengineering and Therapeutic Sciences, University California, San Francisco, CA,Liver Center, University California, San Francisco, CA
| | - Jessica Zucman-Rossi
- Inserm, UMR-1162, Génomique fonctionnelle des Tumeurs solides, Equipe Labellisée Ligue Contre le Cancer, Paris, F-75010 France,Université Paris Descartes, Labex Immuno-Oncology, Sorbonne Paris Cité, F-75010 Paris, France,Université Paris 13, Sorbonne Paris Cité, UFR SMBH, F-93000 Bobigny, France,Université Paris Diderot, IUH, F-75010 Paris
| | - Maria Chikina
- Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Satdarshan P. S. Monga
- Department of Pathology, University of Pittsburgh, Pittsburgh, PA, USA, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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180
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Gu Y, Liu Y, Cao S, Huang X, Zuo Z, Yu S, Deng J, Ding C, Yuan M, Shen L, Wu R, Wen Y, Ren Z, Zhao Q, Peng G, Zhong Z, Wang C, Ma X. Suppressive subtractive hybridization reveals different gene expression between high and low virulence strains of Cladosporium cladosporioides. Microb Pathog 2016; 100:276-284. [PMID: 27744104 DOI: 10.1016/j.micpath.2016.10.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Revised: 08/05/2016] [Accepted: 10/10/2016] [Indexed: 11/29/2022]
Abstract
Cladosporium cladosporioides is a ubiquitous fungus, causing infections in plants, humans, and animals. Suppression subtractive hybridization (SSH) and quantitative real-time PCR (qRT-PCR) were used in this study to identify differences in gene expression between two C. cladosporioides strains, the highly virulent Z20 strain and the lowly virulent Zt strain. A total of 61 unigenes from the forward library and 42 from the reverse library were identified. Gene ontology (GO) analysis showed that these genes were involved in various biological processes, cellular components and molecular functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the unigenes in the forward library corresponded to 5 different pathways and the reverse library unigenes were involved in 3 different pathways. The qRT-PCR results indicated that expressions of APL1, GUD1, CSE1, SPBC3E7.04c and MFS were significantly different between Z20 and Zt strains, while genes encoding the senescence-associated proteins, pse1, nup107, mip1, pex2, icl1 and α/β hydrolase exhibited no significant differences between the two strains. In addition, we found that 5 unigenes encoding mip1, chk1, icl1, α/β hydrolase and β-glucosidase may be associated with pathogenicity. One unigene (MFS) may be related to the resistance to 14 α-demethylase inhibitor fungicides, and 5 unigenes (PEX2, NUP107, PSE1, APL1, and SPBC3E7.04c) may be related to either low spore yield or earlier aging of the Zt strain. Our study may help better understand the molecular mechanism of C. cladosporioides infection, and therefore improve the treatment and prevention of C. cladosporioides induced diseases.
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Affiliation(s)
- Yu Gu
- College of Life Sciences, Sichuan Agricultural University, Ya'an, 625014, China
| | - Yanfang Liu
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Sanjie Cao
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Xiaobo Huang
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Zhicai Zuo
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Shumin Yu
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Junliang Deng
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Chunbang Ding
- College of Life Sciences, Sichuan Agricultural University, Ya'an, 625014, China
| | - Ming Yuan
- College of Life Sciences, Sichuan Agricultural University, Ya'an, 625014, China
| | - Liuhong Shen
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Rui Wu
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Yiping Wen
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Zhihua Ren
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Qin Zhao
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Guangneng Peng
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Zhijun Zhong
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China
| | - Chengdong Wang
- China Conservation and Research Center for the Giant Panda, Ya'an, 625000, China.
| | - Xiaoping Ma
- Key Laboratory of Animal Disease and Human Health of Sichuan Province, College of Veterinary Medicine Sichuan Agricultural University, Chengdu, 611130, China.
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181
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Relevance of mouse models of cardiac fibrosis and hypertrophy in cardiac research. Mol Cell Biochem 2016; 424:123-145. [PMID: 27766529 DOI: 10.1007/s11010-016-2849-0] [Citation(s) in RCA: 67] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 10/14/2016] [Indexed: 01/15/2023]
Abstract
Heart disease causing cardiac cell death due to ischemia-reperfusion injury is a major cause of morbidity and mortality in the United States. Coronary heart disease and cardiomyopathies are the major cause for congestive heart failure, and thrombosis of the coronary arteries is the most common cause of myocardial infarction. Cardiac injury is followed by post-injury cardiac remodeling or fibrosis. Cardiac fibrosis is characterized by net accumulation of extracellular matrix proteins in the cardiac interstitium and results in both systolic and diastolic dysfunctions. It has been suggested by both experimental and clinical evidence that fibrotic changes in the heart are reversible. Hence, it is vital to understand the mechanism involved in the initiation, progression, and resolution of cardiac fibrosis to design anti-fibrotic treatment modalities. Animal models are of great importance for cardiovascular research studies. With the developing research field, the choice of selecting an animal model for the proposed research study is crucial for its outcome and translational purpose. Compared to large animal models for cardiac research, the mouse model is preferred by many investigators because of genetic manipulations and easier handling. This critical review is focused to provide insight to young researchers about the various mouse models, advantages and disadvantages, and their use in research pertaining to cardiac fibrosis and hypertrophy.
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182
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Piñero J, Bravo À, Queralt-Rosinach N, Gutiérrez-Sacristán A, Deu-Pons J, Centeno E, García-García J, Sanz F, Furlong LI. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res 2016; 45:D833-D839. [PMID: 27924018 PMCID: PMC5210640 DOI: 10.1093/nar/gkw943] [Citation(s) in RCA: 1485] [Impact Index Per Article: 185.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 09/29/2016] [Accepted: 10/18/2016] [Indexed: 12/12/2022] Open
Abstract
The information about the genetic basis of human diseases lies at the heart of precision medicine and drug discovery. However, to realize its full potential to support these goals, several problems, such as fragmentation, heterogeneity, availability and different conceptualization of the data must be overcome. To provide the community with a resource free of these hurdles, we have developed DisGeNET (http://www.disgenet.org), one of the largest available collections of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models and the scientific literature. DisGeNET data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, scripts in several programming languages and an R package. DisGeNET is a versatile platform that can be used for different research purposes including the investigation of the molecular underpinnings of specific human diseases and their comorbidities, the analysis of the properties of disease genes, the generation of hypothesis on drug therapeutic action and drug adverse effects, the validation of computationally predicted disease genes and the evaluation of text-mining methods performance.
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Affiliation(s)
- Janet Piñero
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Àlex Bravo
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Núria Queralt-Rosinach
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Alba Gutiérrez-Sacristán
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Jordi Deu-Pons
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Emilio Centeno
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Javier García-García
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Ferran Sanz
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
| | - Laura I Furlong
- Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), Department of Experimental and Health Sciences (DCEXS), Universitat Pompeu Fabra (UPF), C/Dr Aiguader 88, E-08003 Barcelona, Spain
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183
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Chen W, Xia X, Song N, Wang Y, Zhu H, Deng W, Kong Q, Pan X, Qin C. Cross-Species Analysis of Gene Expression and Function in Prefrontal Cortex, Hippocampus and Striatum. PLoS One 2016; 11:e0164295. [PMID: 27716781 PMCID: PMC5055290 DOI: 10.1371/journal.pone.0164295] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2016] [Accepted: 09/22/2016] [Indexed: 01/08/2023] Open
Abstract
Background Mouse has been extensively used as a tool for investigating the onset and development of human neurological disorders. As a first step to construct a transgenic mouse model of human brain lesions, it is of fundamental importance to clarify the similarity and divergence of genetic background between non-diseased human and mouse brain tissues. Methods We systematically compared, based on large scale integrated microarray data, the transcriptomes of three anatomically distinct brain regions; prefrontal cortex (PFC), hippocampus (HIP) and striatum (STR), across human and mouse. The widely used DAVID web server was used to decipher the biological functions of the highly expressed genes that were identified using a previously reported approach. Venn analysis was used to depict the overlapping ratios of the notably enriched biological process (BP) terms (one-tailed Fisher’s exact test and Benjamini correction; adjusted p < 0.01) between two brain tissues. GOSemSim, an R package, was selected to perform GO semantic similarity analysis. Next, we adjusted signal intensities of orthologous genes by the total signals in all samples within species, and used one minus Pearson’s correlation coefficient to assess the expression distance. Hierarchical clustering and principal component analysis (PCA) were selected for expression pattern analysis. Lineage specific expressed orthologous genes were identified by comparison of the most extreme sub-datasets across species and further verified using reverse transcription PCR (RT-PCR) and quantitative real-time PCR (qRT-PCR). Results We found that the number of the significantly enriched BP terms of the highly expressed genes in human brain regions is larger than that in mouse corresponding brain regions. The mainly involved BP terms in human brain tissues associated with protein-membrane targeting and selenium metabolism are species-specific. The overlapping ratios of all the significantly enriched BP terms between any two brain tissues across species are lower than that within species, but the pairwise semantic similarities are very high between any two brain tissues from either human or mouse. Hierarchical clustering analysis shows the biological functions of the highly expressed genes in brain tissues are more consistent within species than interspecies; whereas it shows the expression patterns of orthologous genes are evidently conserved between human and mouse equivalent brain tissues. In addition, we identified four orthologous genes (COX5B, WIF1, SLC4A10 and PLA2G7) that are species-specific, which have been widely studied and confirmed to be closely linked with neuro- physiological and pathological functions. Conclusion Our study highlights the similarities and divergences in gene function and expression between human and mouse corresponding brain regions, including PFC, HIP and STR.
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Affiliation(s)
- Wei Chen
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) & Comparative Medicine Centre, Peking Union Medical Collage (PUMC), Beijing, P.R. China
| | - Xiayu Xia
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) & Comparative Medicine Centre, Peking Union Medical Collage (PUMC), Beijing, P.R. China
| | - Nan Song
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) & Comparative Medicine Centre, Peking Union Medical Collage (PUMC), Beijing, P.R. China
| | - Ying Wang
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) & Comparative Medicine Centre, Peking Union Medical Collage (PUMC), Beijing, P.R. China
| | - Hua Zhu
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) & Comparative Medicine Centre, Peking Union Medical Collage (PUMC), Beijing, P.R. China
| | - Wei Deng
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) & Comparative Medicine Centre, Peking Union Medical Collage (PUMC), Beijing, P.R. China
| | - Qi Kong
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) & Comparative Medicine Centre, Peking Union Medical Collage (PUMC), Beijing, P.R. China
| | - Xianmin Pan
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) & Comparative Medicine Centre, Peking Union Medical Collage (PUMC), Beijing, P.R. China
- Ministry of Education, The Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing, P.R. China
| | - Chuan Qin
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) & Comparative Medicine Centre, Peking Union Medical Collage (PUMC), Beijing, P.R. China
- * E-mail:
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184
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Dickel DE, Barozzi I, Zhu Y, Fukuda-Yuzawa Y, Osterwalder M, Mannion BJ, May D, Spurrell CH, Plajzer-Frick I, Pickle CS, Lee E, Garvin TH, Kato M, Akiyama JA, Afzal V, Lee AY, Gorkin DU, Ren B, Rubin EM, Visel A, Pennacchio LA. Genome-wide compendium and functional assessment of in vivo heart enhancers. Nat Commun 2016; 7:12923. [PMID: 27703156 PMCID: PMC5059478 DOI: 10.1038/ncomms12923] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2016] [Accepted: 08/16/2016] [Indexed: 12/04/2022] Open
Abstract
Whole-genome sequencing is identifying growing numbers of non-coding variants in human disease studies, but the lack of accurate functional annotations prevents their interpretation. We describe the genome-wide landscape of distant-acting enhancers active in the developing and adult human heart, an organ whose impairment is a predominant cause of mortality and morbidity. Using integrative analysis of >35 epigenomic data sets from mouse and human pre- and postnatal hearts we created a comprehensive reference of >80,000 putative human heart enhancers. To illustrate the importance of enhancers in the regulation of genes involved in heart disease, we deleted the mouse orthologs of two human enhancers near cardiac myosin genes. In both cases, we observe in vivo expression changes and cardiac phenotypes consistent with human heart disease. Our study provides a comprehensive catalogue of human heart enhancers for use in clinical whole-genome sequencing studies and highlights the importance of enhancers for cardiac function. Identification of non-coding variants has outstripped our ability to annotate and interpret them. Dickel et al. present a compendium of over 80,000 putative human heart enhancers and demonstrate that two conserved enhancers are required for proper cardiac function in mice.
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Affiliation(s)
- Diane E Dickel
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Iros Barozzi
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Yiwen Zhu
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Yoko Fukuda-Yuzawa
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Marco Osterwalder
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Brandon J Mannion
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Dalit May
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Cailyn H Spurrell
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Ingrid Plajzer-Frick
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Catherine S Pickle
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Elizabeth Lee
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Tyler H Garvin
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Momoe Kato
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Jennifer A Akiyama
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Veena Afzal
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA
| | - Ah Young Lee
- Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - David U Gorkin
- Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA.,Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, California 92093, USA
| | - Edward M Rubin
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA.,U.S. Department of Energy Joint Genome Institute, Walnut Creek, California 94598, USA
| | - Axel Visel
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA.,U.S. Department of Energy Joint Genome Institute, Walnut Creek, California 94598, USA.,School of Natural Sciences, University of California, Merced, Merced, California 95343, USA
| | - Len A Pennacchio
- Functional Genomics Department, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA.,U.S. Department of Energy Joint Genome Institute, Walnut Creek, California 94598, USA
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185
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Abstract
We report on the sequencing of 10,545 human genomes at 30×-40× coverage with an emphasis on quality metrics and novel variant and sequence discovery. We find that 84% of an individual human genome can be sequenced confidently. This high-confidence region includes 91.5% of exon sequence and 95.2% of known pathogenic variant positions. We present the distribution of over 150 million single-nucleotide variants in the coding and noncoding genome. Each newly sequenced genome contributes an average of 8,579 novel variants. In addition, each genome carries on average 0.7 Mb of sequence that is not found in the main build of the hg38 reference genome. The density of this catalog of variation allowed us to construct high-resolution profiles that define genomic sites that are highly intolerant of genetic variation. These results indicate that the data generated by deep genome sequencing is of the quality necessary for clinical use.
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186
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Jing J, Pattaro C, Hoppmann A, Okada Y, Fox CS, Köttgen A. Combination of mouse models and genomewide association studies highlights novel genes associated with human kidney function. Kidney Int 2016; 90:764-73. [DOI: 10.1016/j.kint.2016.04.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Revised: 03/20/2016] [Accepted: 04/07/2016] [Indexed: 12/31/2022]
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187
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Ainsbury EA, Barnard S, Bright S, Dalke C, Jarrin M, Kunze S, Tanner R, Dynlacht JR, Quinlan RA, Graw J, Kadhim M, Hamada N. Ionizing radiation induced cataracts: Recent biological and mechanistic developments and perspectives for future research. MUTATION RESEARCH-REVIEWS IN MUTATION RESEARCH 2016; 770:238-261. [DOI: 10.1016/j.mrrev.2016.07.010] [Citation(s) in RCA: 90] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Revised: 07/27/2016] [Accepted: 07/28/2016] [Indexed: 02/06/2023]
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188
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Liu Z, Fang H, Slikker W, Tong W. Potential Reuse of Oncology Drugs in the Treatment of Rare Diseases. Trends Pharmacol Sci 2016; 37:843-857. [DOI: 10.1016/j.tips.2016.06.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Revised: 06/27/2016] [Accepted: 06/30/2016] [Indexed: 12/23/2022]
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189
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Dickinson ME, Flenniken AM, Ji X, Teboul L, Wong MD, White JK, Meehan TF, Weninger WJ, Westerberg H, Adissu H, Baker CN, Bower L, Brown JM, Caddle LB, Chiani F, Clary D, Cleak J, Daly MJ, Denegre JM, Doe B, Dolan ME, Edie SM, Fuchs H, Gailus-Durner V, Galli A, Gambadoro A, Gallegos J, Guo S, Horner NR, Hsu CW, Johnson SJ, Kalaga S, Keith LC, Lanoue L, Lawson TN, Lek M, Mark M, Marschall S, Mason J, McElwee ML, Newbigging S, Nutter LM, Peterson KA, Ramirez-Solis R, Rowland DJ, Ryder E, Samocha KE, Seavitt JR, Selloum M, Szoke-Kovacs Z, Tamura M, Trainor AG, Tudose I, Wakana S, Warren J, Wendling O, West DB, Wong L, Yoshiki A, MacArthur DG, Tocchini-Valentini GP, Gao X, Flicek P, Bradley A, Skarnes WC, Justice MJ, Parkinson HE, Moore M, Wells S, Braun RE, Svenson KL, de Angelis MH, Herault Y, Mohun T, Mallon AM, Henkelman RM, Brown SD, Adams DJ, Lloyd KK, McKerlie C, Beaudet AL, Bucan M, Murray SA. High-throughput discovery of novel developmental phenotypes. Nature 2016; 537:508-514. [PMID: 27626380 PMCID: PMC5295821 DOI: 10.1038/nature19356] [Citation(s) in RCA: 799] [Impact Index Per Article: 99.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Accepted: 08/10/2016] [Indexed: 12/29/2022]
Abstract
Approximately one-third of all mammalian genes are essential for life. Phenotypes resulting from knockouts of these genes in mice have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5,000 knockout mouse lines, here we identify 410 lethal genes during the production of the first 1,751 unique gene knockouts. Using a standardized phenotyping platform that incorporates high-resolution 3D imaging, we identify phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts.
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Affiliation(s)
- Mary E. Dickinson
- Department of Molecular Physiology and Biophysics, Houston, Texas, USA
| | - Ann M. Flenniken
- The Centre for Phenogenomics, Toronto, Ontario, Canada
- Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Xiao Ji
- Genomics and Computational Biology Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA 19104
| | - Lydia Teboul
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | - Michael D. Wong
- The Centre for Phenogenomics, Toronto, Ontario, Canada
- Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jacqueline K. White
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Terrence F. Meehan
- European Molecular Biology Laboratory- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Wolfgang J. Weninger
- Centre for Anatomy and Cell Biology, Medical University of Vienna, Vienna, Austria
| | - Henrik Westerberg
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | - Hibret Adissu
- The Centre for Phenogenomics, Toronto, Ontario, Canada
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - Lynette Bower
- Mouse Biology Program, University of California, Davis
| | - James M. Brown
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | | | - Francesco Chiani
- Monterotondo Mouse Clinic, Italian National Research Council (CNR), Institute of Cell Biology and Neurobiology, Monterotondo Scalo, Itally
| | - Dave Clary
- Mouse Biology Program, University of California, Davis
| | - James Cleak
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | - Mark J. Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston MA, USA
- Program in Medical and Population Genetics, Broad Institute MIT and Harvard, Cambridge, MA, USA
| | | | - Brendan Doe
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | | | | | - Helmut Fuchs
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Experimental Genetics and German Mouse Clinic, Neuherberg, Germany
| | - Valerie Gailus-Durner
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Experimental Genetics and German Mouse Clinic, Neuherberg, Germany
| | - Antonella Galli
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Alessia Gambadoro
- Monterotondo Mouse Clinic, Italian National Research Council (CNR), Institute of Cell Biology and Neurobiology, Monterotondo Scalo, Itally
| | - Juan Gallegos
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Shiying Guo
- SKL of Pharmaceutical Biotechnology and Model Animal Research Center, Collaborative Innovation Center for Genetics and Development, Nanjing Biomedical Research Institute, Nanjing University, China
| | - Neil R. Horner
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | - Chih-wei Hsu
- Department of Molecular Physiology and Biophysics, Houston, Texas, USA
| | - Sara J. Johnson
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | - Sowmya Kalaga
- Department of Molecular Physiology and Biophysics, Houston, Texas, USA
| | - Lance C. Keith
- Department of Molecular Physiology and Biophysics, Houston, Texas, USA
| | - Louise Lanoue
- Mouse Biology Program, University of California, Davis
| | - Thomas N. Lawson
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | - Monkol Lek
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston MA, USA
- Program in Medical and Population Genetics, Broad Institute MIT and Harvard, Cambridge, MA, USA
| | - Manuel Mark
- Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris (ICS), et Institut de Génétique Biologie Moléculaire et Cellulaire (IGBMC) CNRS, INSERM, University of Strasbourg, Illkirch-Graffenstaden, France
| | - Susan Marschall
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Experimental Genetics and German Mouse Clinic, Neuherberg, Germany
| | - Jeremy Mason
- European Molecular Biology Laboratory- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | | | - Susan Newbigging
- The Centre for Phenogenomics, Toronto, Ontario, Canada
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Lauryl M.J. Nutter
- The Centre for Phenogenomics, Toronto, Ontario, Canada
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - Ramiro Ramirez-Solis
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | | | - Edward Ryder
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Kaitlin E. Samocha
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston MA, USA
- Program in Medical and Population Genetics, Broad Institute MIT and Harvard, Cambridge, MA, USA
| | - John R. Seavitt
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Mohammed Selloum
- Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris (ICS), et Institut de Génétique Biologie Moléculaire et Cellulaire (IGBMC) CNRS, INSERM, University of Strasbourg, Illkirch-Graffenstaden, France
| | - Zsombor Szoke-Kovacs
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | | | | | - Ilinca Tudose
- European Molecular Biology Laboratory- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | | | - Jonathan Warren
- European Molecular Biology Laboratory- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Olivia Wendling
- Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris (ICS), et Institut de Génétique Biologie Moléculaire et Cellulaire (IGBMC) CNRS, INSERM, University of Strasbourg, Illkirch-Graffenstaden, France
| | - David B. West
- Children’s Hospital Oakland Research Institute, Oakland, CA 94609
| | - Leeyean Wong
- Department of Molecular Physiology and Biophysics, Houston, Texas, USA
| | | | | | - Daniel G. MacArthur
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston MA, USA
- Program in Medical and Population Genetics, Broad Institute MIT and Harvard, Cambridge, MA, USA
| | - Glauco P. Tocchini-Valentini
- Monterotondo Mouse Clinic, Italian National Research Council (CNR), Institute of Cell Biology and Neurobiology, Monterotondo Scalo, Itally
| | - Xiang Gao
- SKL of Pharmaceutical Biotechnology and Model Animal Research Center, Collaborative Innovation Center for Genetics and Development, Nanjing Biomedical Research Institute, Nanjing University, China
| | - Paul Flicek
- European Molecular Biology Laboratory- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Allan Bradley
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - William C. Skarnes
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Monica J. Justice
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Helen E. Parkinson
- European Molecular Biology Laboratory- European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | | | - Sara Wells
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | | | | | - Martin Hrabe de Angelis
- Helmholtz Zentrum München, German Research Center for Environmental Health, Institute of Experimental Genetics and German Mouse Clinic, Neuherberg, Germany
- Chair of Experimental Genetics, School of Life Science Weihenstephan, Technische Universität München, Freising
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - Yann Herault
- Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris (ICS), et Institut de Génétique Biologie Moléculaire et Cellulaire (IGBMC) CNRS, INSERM, University of Strasbourg, Illkirch-Graffenstaden, France
| | - Tim Mohun
- The Francis Crick Institute Mill Hill Laboratory, The Ridgeway, Mill Hill, London, UK
| | - Ann-Marie Mallon
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | - R. Mark Henkelman
- The Centre for Phenogenomics, Toronto, Ontario, Canada
- Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Steve D.M. Brown
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Harwell, Oxfordshire, UK
| | - David J. Adams
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | | | - Colin McKerlie
- The Centre for Phenogenomics, Toronto, Ontario, Canada
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Arthur L. Beaudet
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Maja Bucan
- Departments of Genetics and Psychiatry, Perlman School of Medicine, University of Pennsylvania, Philadelphia PA 19104
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190
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Sorte HS, Osnes LT, Fevang B, Aukrust P, Erichsen HC, Backe PH, Abrahamsen TG, Kittang OB, Øverland T, Jhangiani SN, Muzny DM, Vigeland MD, Samarakoon P, Gambin T, Akdemir ZHC, Gibbs RA, Rødningen OK, Lyle R, Lupski JR, Stray-Pedersen A. A potential founder variant in CARMIL2/RLTPR in three Norwegian families with warts, molluscum contagiosum, and T-cell dysfunction. Mol Genet Genomic Med 2016; 4:604-616. [PMID: 27896283 PMCID: PMC5118205 DOI: 10.1002/mgg3.237] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Accepted: 07/22/2016] [Indexed: 12/30/2022] Open
Abstract
Background Four patients from three Norwegian families presented with a common skin phenotype of warts, molluscum contagiosum, and dermatitis since early childhood, and various other immunological features. Warts are a common manifestation of human papilloma virus (HPV), but when they are overwhelming, disseminated and/or persistent, and presenting together with other immunological features, a primary immunodeficiency disease (PIDD) may be suspected. Methods and results The four patients were exome sequenced as part of a larger study for detecting genetic causes of primary immunodeficiencies. No disease‐causing variants were identified in known primary immunodeficiency genes or in other disease‐related OMIM genes. However, the same homozygous missense variant in CARMIL2 (also known as RLTPR) was identified in all four patients. In each family, the variant was located within a narrow region of homozygosity, representing a potential region of autozygosity. CARMIL2 is a protein of undetermined function. A role in T‐cell activation has been suggested and the mouse protein homolog (Rltpr) is essential for costimulation of T‐cell activation via CD28, and for the development of regulatory T cells. Immunophenotyping demonstrated reduced regulatory, CD4+ memory, and CD4+ follicular T cells in all four patients. In addition, they all seem to have a deficiency in IFNγ ‐synthesis in CD4+ T cells and NK cells. Conclusions We report a novel primary immunodeficiency, and a differential molecular diagnosis to CXCR4‐,DOCK8‐,GATA2‐,MAGT1‐,MCM4‐,STK4‐,RHOH‐,TMC6‐, and TMC8‐related diseases. The specific variant may represent a Norwegian founder variant segregating on a population‐specific haplotype.
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Affiliation(s)
- Hanne S Sorte
- Department of Medical Genetics Oslo University Hospital and University of Oslo Oslo Norway
| | - Liv T Osnes
- Department of Immunology Oslo University Hospital Oslo Norway
| | - Børre Fevang
- Institute of Clinical MedicineUniversity of OsloOsloNorway; Section of Clinical Immunology and Infectious DiseasesOslo University HospitalOsloNorway; Research Institute of Internal MedicineOslo University HospitalOsloNorway
| | - Pål Aukrust
- Institute of Clinical MedicineUniversity of OsloOsloNorway; Section of Clinical Immunology and Infectious DiseasesOslo University HospitalOsloNorway; Research Institute of Internal MedicineOslo University HospitalOsloNorway
| | - Hans C Erichsen
- Department of Pediatrics Oslo University Hospital Oslo Norway
| | - Paul H Backe
- Department of Medical BiochemistryInstitute of Clinical MedicineUniversity of OsloOsloNorway; Department of MicrobiologyOslo University HospitalOsloNorway
| | - Tore G Abrahamsen
- Institute of Clinical MedicineUniversity of OsloOsloNorway; Department of PediatricsOslo University HospitalOsloNorway
| | - Ole B Kittang
- Department of Pediatrics Sørlandet Hospital Kristiansand Norway
| | | | | | - Donna M Muzny
- Human Genome Sequencing Center of Baylor College of Medicine Houston Texas
| | - Magnus D Vigeland
- Department of Medical Genetics Oslo University Hospital and University of Oslo Oslo Norway
| | - Pubudu Samarakoon
- Department of Medical Genetics Oslo University Hospital and University of Oslo Oslo Norway
| | - Tomasz Gambin
- Institute of computer scienceWarsaw University of TechnologyWarsawPoland; Baylor-Hopkins Center for Mendelian Genomics (BHCMG) of the Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexas
| | - Zeynep H C Akdemir
- Baylor-Hopkins Center for Mendelian Genomics (BHCMG) of the Department of Molecular and Human Genetics Baylor College of Medicine Houston Texas
| | - Richard A Gibbs
- Baylor-Hopkins Center for Mendelian Genomics (BHCMG) of the Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexas; Human Genome Sequencing Center of Baylor College of MedicineHoustonTexas; Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexas
| | - Olaug K Rødningen
- Department of Medical Genetics Oslo University Hospital and University of Oslo Oslo Norway
| | - Robert Lyle
- Department of Medical Genetics Oslo University Hospital and University of Oslo Oslo Norway
| | - James R Lupski
- Baylor-Hopkins Center for Mendelian Genomics (BHCMG) of the Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexas; Human Genome Sequencing Center of Baylor College of MedicineHoustonTexas; Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexas; Department of PediatricsBaylor College of Medicine, and Texas Children's HospitalHoustonTexas
| | - Asbjørg Stray-Pedersen
- Baylor-Hopkins Center for Mendelian Genomics (BHCMG) of the Department of Molecular and Human GeneticsBaylor College of MedicineHoustonTexas; Norwegian National Unit for Newborn ScreeningDivision of Children and Adolescent MedicineOslo University HospitalOsloNorway
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191
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Mak CCY, Chow PC, Liu APY, Chan KYK, Chu YWY, Mok GTK, Leung GKC, Yeung KS, Chau AKT, Lowther C, Scherer SW, Marshall CR, Bassett AS, Chung BHY. De novo large rare copy-number variations contribute to conotruncal heart disease in Chinese patients. NPJ Genom Med 2016; 1:16033. [PMID: 29263819 PMCID: PMC5685312 DOI: 10.1038/npjgenmed.2016.33] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Revised: 08/02/2016] [Accepted: 08/05/2016] [Indexed: 01/05/2023] Open
Abstract
Conotruncal heart anomalies (CTDs) are particularly prevalent congenital heart diseases (CHD) in Hong Kong. We surveyed large (>500 kb), rare (<1% frequency in controls) copy-number variations (CNVs) in Chinese patients with CTDs to identify potentially disease-causing variations. Adults who tested negative for 22q11.2 deletions were recruited from the adult CHD clinic in Hong Kong. Using a stringent calling criteria, high-confidence CNV calls were obtained, and a large control set comprising 3,987 Caucasian and 1,945 Singapore Chinese subjects was used to identify rare CNVs. Ten large rare CNVs were identified, and 3 in 108 individuals were confirmed to harbour de novo CNVs. All three patients were syndromic with a more complex phenotype, and each of these CNVs overlapped regions likely to be important in CHD. One was a 611 kb deletion at 17p13.3, telomeric to the Miller-Dieker syndrome (MDS) critical region, overlapping the NXN gene. Another was a 5 Mb deletion at 13q33.3, within a previously described critical region for CHD. A third CNV, previously unreported, was a large duplication at 2q22.3 overlapping the ZEB2 gene. The commonly reported 1q21.1 recurrent duplication was not observed in this Chinese cohort. We provide detailed phenotypic and genotypic descriptions of large rare genic CNVs that may represent CHD loci in the East Asian population. Larger samples of Chinese origin will be required to determine whether the genome-wide distribution differs from that found in predominantly European CHD cohorts.
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Affiliation(s)
- Christopher C Y Mak
- Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Pak Cheong Chow
- Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Anthony P Y Liu
- Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Kelvin Y K Chan
- Department of Obstetrics and Gynecology, Queen Mary Hospital, Hong Kong, China
| | - Yoyo W Y Chu
- Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Gary T K Mok
- Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Gordon K C Leung
- Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Kit San Yeung
- Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Adolphus K T Chau
- Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Chelsea Lowther
- The Clinical Genetics Research Program at The Centre for Addiction and Mental Health, The Dalglish Family 22q Clinic at The University Health Network, and The Department of Psychiatry at The University of Toronto, Toronto, ON, Canada
| | - Stephen W Scherer
- The Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Christian R Marshall
- The Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Anne S Bassett
- The Clinical Genetics Research Program at The Centre for Addiction and Mental Health, The Dalglish Family 22q Clinic at The University Health Network, and The Department of Psychiatry at The University of Toronto, Toronto, ON, Canada
| | - Brian H Y Chung
- Department of Paediatrics & Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
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192
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Thangaraju K, Király R, Mótyán JA, Ambrus VA, Fuxreiter M, Fésüs L. Computational analyses of the effect of novel amino acid clusters of human transglutaminase 2 on its structure and function. Amino Acids 2016; 49:605-614. [DOI: 10.1007/s00726-016-2330-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Accepted: 09/08/2016] [Indexed: 02/01/2023]
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193
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Hoppmann AS, Schlosser P, Backofen R, Lausch E, Köttgen A. GenToS: Use of Orthologous Gene Information to Prioritize Signals from Human GWAS. PLoS One 2016; 11:e0162466. [PMID: 27612175 PMCID: PMC5017755 DOI: 10.1371/journal.pone.0162466] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Accepted: 08/23/2016] [Indexed: 11/18/2022] Open
Abstract
Genome-wide association studies (GWAS) evaluate associations between genetic variants and a trait or disease of interest free of prior biological hypotheses. GWAS require stringent correction for multiple testing, with genome-wide significance typically defined as association p-value <5*10-8. This study presents a new tool that uses external information about genes to prioritize SNP associations (GenToS). For a given list of candidate genes, GenToS calculates an appropriate statistical significance threshold and then searches for trait-associated variants in summary statistics from human GWAS. It thereby allows for identifying trait-associated genetic variants that do not meet genome-wide significance. The program additionally tests for enrichment of significant candidate gene associations in the human GWAS data compared to the number expected by chance. As proof of principle, this report used external information from a comprehensive resource of genetically manipulated and systematically phenotyped mice. Based on selected murine phenotypes for which human GWAS data for corresponding traits were publicly available, several candidate gene input lists were derived. Using GenToS for the investigation of candidate genes underlying murine skeletal phenotypes in data from a large human discovery GWAS meta-analysis of bone mineral density resulted in the identification of significantly associated variants in 29 genes. Index variants in 28 of these loci were subsequently replicated in an independent GWAS replication step, highlighting that they are true positive associations. One signal, COL11A1, has not been discovered through GWAS so far and represents a novel human candidate gene for altered bone mineral density. The number of observed genes that contained significant SNP associations in human GWAS based on murine candidate gene input lists was much greater than the number expected by chance across several complex human traits (enrichment p-value as low as 10-10). GenToS can be used with any candidate gene list, any GWAS summary file, runs on a desktop computer and is freely available.
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Affiliation(s)
- Anselm S. Hoppmann
- Dept. of Pediatric Genetics, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Division of Genetic Epidemiology, Institute for Medical Biometry and Statistics, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Pascal Schlosser
- Institute for Medical Biometry and Statistics, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Rolf Backofen
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany
| | - Ekkehart Lausch
- Dept. of Pediatric Genetics, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Anna Köttgen
- Division of Genetic Epidemiology, Institute for Medical Biometry and Statistics, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- * E-mail:
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194
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Prunotto A, Stevenson BJ, Berthonneche C, Schüpfer F, Beckmann JS, Maurer F, Bergmann S. RNAseq analysis of heart tissue from mice treated with atenolol and isoproterenol reveals a reciprocal transcriptional response. BMC Genomics 2016; 17:717. [PMID: 27604219 PMCID: PMC5015234 DOI: 10.1186/s12864-016-3059-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2016] [Accepted: 09/01/2016] [Indexed: 01/17/2023] Open
Abstract
Background The transcriptional response to many widely used drugs and its modulation by genetic variability is poorly understood. Here we present an analysis of RNAseq profiles from heart tissue of 18 inbred mouse strains treated with the β-blocker atenolol (ATE) and the β-agonist isoproterenol (ISO). Results Differential expression analyses revealed a large set of genes responding to ISO (n = 1770 at FDR = 0.0001) and a comparatively small one responding to ATE (n = 23 at FDR = 0.0001). At a less stringent definition of differential expression, the transcriptional responses to these two antagonistic drugs are reciprocal for many genes, with an overall anti-correlation of r = −0.3. This trend is also observed at the level of most individual strains even though the power to detect differential expression is significantly reduced. The inversely expressed gene sets are enriched with genes annotated for heart-related functions. Modular analysis revealed gene sets that exhibit coherent transcription profiles across some strains and/or treatments. Correlations between these modules and a broad spectrum of cardiovascular traits are stronger than expected by chance. This provides evidence for the overall importance of transcriptional regulation for these organismal responses and explicits links between co-expressed genes and the traits they are associated with. Gene set enrichment analysis of differentially expressed groups of genes pointed to pathways related to heart development and functionality. Conclusions Our study provides new insights into the transcriptional response of the heart to perturbations of the β-adrenergic system, implicating several new genes that had not been associated to this system previously. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3059-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Andrea Prunotto
- Department of Medical Genetics, University of Lausanne, Rue du Bugnon 27, 1011, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | - Corinne Berthonneche
- Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Rue du Bugnon 27, 1011, Lausanne, Switzerland
| | - Fanny Schüpfer
- Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Rue du Bugnon 27, 1011, Lausanne, Switzerland
| | - Jacques S Beckmann
- Department of Medical Genetics, University of Lausanne, Rue du Bugnon 27, 1011, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Rue du Bugnon 27, 1011, Lausanne, Switzerland
| | - Fabienne Maurer
- Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Rue du Bugnon 27, 1011, Lausanne, Switzerland.
| | - Sven Bergmann
- Department of Medical Genetics, University of Lausanne, Rue du Bugnon 27, 1011, Lausanne, Switzerland. .,Swiss Institute of Bioinformatics, Lausanne, Switzerland. .,Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa.
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195
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Reiding KR, Hipgrave Ederveen AL, Rombouts Y, Wuhrer M. Murine Plasma N-Glycosylation Traits Associated with Sex and Strain. J Proteome Res 2016; 15:3489-3499. [PMID: 27546880 DOI: 10.1021/acs.jproteome.6b00071] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Glycosylation is an abundant and important protein modification with large influence on the properties and interactions of glycoconjugates. Human plasma N-glycosylation has been the subject of frequent investigation, revealing strong associations with physiological and pathological conditions. Less well-characterized is the plasma N-glycosylation of the mouse, the most commonly used animal model for studying human diseases, particularly with regard to differences between strains and sexes. For this reason, we used MALDI-TOF(/TOF)-MS(/MS) assisted by linkage-specific derivatization of the sialic acids to comparatively analyze the plasma N-glycosylation of both male and female mice originating from BALB/c, CD57BL/6, CD-1, and Swiss Webster strains. The combined use of this analytical method and the recently developed data processing software named MassyTools allowed the relative quantification of the N-glycan species within plasma, the distinction between α2,3- and α2,6-linked N-glycolylneuraminic acids (due to respective lactonization and ethyl esterification), the detection of sialic acid O-acetylation, as well as the characterization of branching sialylation (Neu5Gcα2,3-Hex-[Neu5Gcα2,6-]HexNAc). When analyzing the glycosylation according to mouse sex, we found that female mice present a considerably higher degree of core fucosylation (2-4-fold depending on the strain), galactosylation, α2,6-linked sialylation, and larger high-mannose type glycan species compared with their male counterparts. Male mice, on the contrary, showed on average higher α2,3-linked sialylation, branching sialylation, and putative bisection. These differences together with sialic acid acetylation proved to be strain-specific as well. Interestingly, the outbred strains CD-1 and Swiss Webster displayed considerably larger interindividual variation than inbred strains BALB/c and CD57BL/6, suggesting a strong hereditable component of the observed plasma N-glycome.
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Affiliation(s)
- Karli R Reiding
- Leiden University Medical Center , Center for Proteomics and Metabolomics, Leiden 2333ZA, The Netherlands
| | - Agnes L Hipgrave Ederveen
- Leiden University Medical Center , Center for Proteomics and Metabolomics, Leiden 2333ZA, The Netherlands
| | - Yoann Rombouts
- Leiden University Medical Center , Center for Proteomics and Metabolomics, Leiden 2333ZA, The Netherlands.,Institut de Pharmacologie et de Biologie Structurale, Université de Toulouse, CNRS, UPS, Toulouse 31077, France
| | - Manfred Wuhrer
- Leiden University Medical Center , Center for Proteomics and Metabolomics, Leiden 2333ZA, The Netherlands
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196
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Naldaiz-Gastesi N, Goicoechea M, Alonso-Martín S, Aiastui A, López-Mayorga M, García-Belda P, Lacalle J, San José C, Araúzo-Bravo MJ, Trouilh L, Anton-Leberre V, Herrero D, Matheu A, Bernad A, García-Verdugo JM, Carvajal JJ, Relaix F, Lopez de Munain A, García-Parra P, Izeta A. Identification and Characterization of the Dermal Panniculus Carnosus Muscle Stem Cells. Stem Cell Reports 2016; 7:411-424. [PMID: 27594590 PMCID: PMC5032673 DOI: 10.1016/j.stemcr.2016.08.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Revised: 08/01/2016] [Accepted: 08/01/2016] [Indexed: 01/05/2023] Open
Abstract
The dermal Panniculus carnosus (PC) muscle is important for wound contraction in lower mammals and represents an interesting model of muscle regeneration due to its high cell turnover. The resident satellite cells (the bona fide muscle stem cells) remain poorly characterized. Here we analyzed PC satellite cells with regard to developmental origin and purported function. Lineage tracing shows that they originate in Myf5+, Pax3/Pax7+ cell populations. Skin and muscle wounding increased PC myofiber turnover, with the satellite cell progeny being involved in muscle regeneration but with no detectable contribution to the wound-bed myofibroblasts. Since hematopoietic stem cells fuse to PC myofibers in the absence of injury, we also studied the contribution of bone marrow-derived cells to the PC satellite cell compartment, demonstrating that cells of donor origin are capable of repopulating the PC muscle stem cell niche after irradiation and bone marrow transplantation but may not fully acquire the relevant myogenic commitment. PC satellite cells originate from Myf5+, Pax3/Pax7+ cell lineages Skin and muscle wounding increase PC myofiber turnover Donor bone marrow cells repopulate the PC satellite niche after BMT Dermis-derived myogenesis originates from the PC satellite cell population
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Affiliation(s)
- Neia Naldaiz-Gastesi
- Tissue Engineering Laboratory, Bioengineering Area, Instituto Biodonostia, San Sebastián 20014, Spain; Neuroscience Area, Instituto Biodonostia, San Sebastián 20014, Spain; CIBERNED, Instituto de Salud Carlos III, Madrid 28029, Spain
| | - María Goicoechea
- Neuroscience Area, Instituto Biodonostia, San Sebastián 20014, Spain; CIBERNED, Instituto de Salud Carlos III, Madrid 28029, Spain
| | - Sonia Alonso-Martín
- INSERM U955-E10, Université Paris Est, Faculté de Médicine, IMRB U955-E10, Creteil 94000, France
| | - Ana Aiastui
- Neuroscience Area, Instituto Biodonostia, San Sebastián 20014, Spain; CIBERNED, Instituto de Salud Carlos III, Madrid 28029, Spain
| | - Macarena López-Mayorga
- Molecular Embryology Team, Centro Andaluz de Biología del Desarrollo, Sevilla 41013, Spain
| | - Paula García-Belda
- CIBERNED, Instituto de Salud Carlos III, Madrid 28029, Spain; Laboratorio de Neurobiología Comparada, Instituto Cavanilles, Universidad de Valencia, Valencia 46980, Spain
| | - Jaione Lacalle
- Tissue Engineering Laboratory, Bioengineering Area, Instituto Biodonostia, San Sebastián 20014, Spain; Neuroscience Area, Instituto Biodonostia, San Sebastián 20014, Spain; Faculty of Medicine and Nursing, UPV-EHU, San Sebastián 20014, Spain
| | - Carlos San José
- Animal Facility and Experimental Surgery, Instituto Biodonostia, San Sebastián 20014, Spain
| | - Marcos J Araúzo-Bravo
- Computational Biology and Systems Biomedicine, Instituto Biodonostia, San Sebastián 20014, Spain; IKERBASQUE, Basque Foundation for Science, Bilbao 48013, Spain
| | - Lidwine Trouilh
- INSA, UPS, INP, LISBP, Université de Toulouse, 31077 Toulouse, France; INRA, UMR792, Ingénierie des Systèmes Biologiques et des Procédés, 31400 Toulouse, France; CNRS, UMR5504, 31400 Toulouse, France
| | - Véronique Anton-Leberre
- INSA, UPS, INP, LISBP, Université de Toulouse, 31077 Toulouse, France; INRA, UMR792, Ingénierie des Systèmes Biologiques et des Procédés, 31400 Toulouse, France; CNRS, UMR5504, 31400 Toulouse, France
| | - Diego Herrero
- Immunology and Oncology Department, Spanish National Center for Biotechnology (CNB-CSIC), Madrid 28049, Spain
| | - Ander Matheu
- IKERBASQUE, Basque Foundation for Science, Bilbao 48013, Spain; Cellular Oncology Group, Oncology Area, Instituto Biodonostia, San Sebastián 20014, Spain
| | - Antonio Bernad
- Immunology and Oncology Department, Spanish National Center for Biotechnology (CNB-CSIC), Madrid 28049, Spain
| | - José Manuel García-Verdugo
- CIBERNED, Instituto de Salud Carlos III, Madrid 28029, Spain; Laboratorio de Neurobiología Comparada, Instituto Cavanilles, Universidad de Valencia, Valencia 46980, Spain
| | - Jaime J Carvajal
- Molecular Embryology Team, Centro Andaluz de Biología del Desarrollo, Sevilla 41013, Spain
| | - Frédéric Relaix
- INSERM U955-E10, Université Paris Est, Faculté de Médicine, IMRB U955-E10, Creteil 94000, France
| | - Adolfo Lopez de Munain
- Neuroscience Area, Instituto Biodonostia, San Sebastián 20014, Spain; CIBERNED, Instituto de Salud Carlos III, Madrid 28029, Spain; Faculty of Medicine and Nursing, Department of Neurosciences, UPV-EHU, San Sebastián 20014, Spain; Department of Neurology, Hospital Universitario Donostia, San Sebastián 20014, Spain
| | - Patricia García-Parra
- Tissue Engineering Laboratory, Bioengineering Area, Instituto Biodonostia, San Sebastián 20014, Spain; Neuroscience Area, Instituto Biodonostia, San Sebastián 20014, Spain; CIBERNED, Instituto de Salud Carlos III, Madrid 28029, Spain.
| | - Ander Izeta
- Tissue Engineering Laboratory, Bioengineering Area, Instituto Biodonostia, San Sebastián 20014, Spain; Department of Biomedical Engineering, School of Engineering, Tecnun-University of Navarra, San Sebastián 20009, Spain.
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197
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Donahoe PK, Longoni M, High FA. Polygenic Causes of Congenital Diaphragmatic Hernia Produce Common Lung Pathologies. THE AMERICAN JOURNAL OF PATHOLOGY 2016; 186:2532-43. [PMID: 27565037 DOI: 10.1016/j.ajpath.2016.07.006] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2016] [Revised: 06/20/2016] [Accepted: 07/13/2016] [Indexed: 12/12/2022]
Abstract
Congenital diaphragmatic hernia (CDH) is one of the most common and lethal congenital anomalies, and significant evidence is available in support of a genetic contribution to its etiology, including single-gene knockout mice associated with diaphragmatic defects, rare monogenetic disorders in humans, familial aggregation, and association of CDH with chromosomal abnormalities. Structural lung defects in the form of lung hypoplasia are almost invariably seen in patients with CDH and frequently in animal models of this condition. Better understanding of the mechanisms of pulmonary defects in CDH has the potential for creating targeted therapies, particularly in postnatal stages, when therapeutics can have maximum clinical impact on the surviving cohorts. Successful treatment of CDH is dependent on the integration of human genomic and genetic data with developmental expression profiling, mouse knockouts, and gene network and pathway modeling, which have generated a large number of candidate genes and pathways for follow-up studies. In particular, defective alveolarization appears to be a common and potentially actionable phenotype in both patients and animal models.
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Affiliation(s)
- Patricia K Donahoe
- Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, Massachusetts; Department of Surgery, Harvard Medical School, Boston, Massachusetts; Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts.
| | - Mauro Longoni
- Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, Massachusetts; Department of Surgery, Harvard Medical School, Boston, Massachusetts
| | - Frances A High
- Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, Massachusetts; Department of Surgery, Harvard Medical School, Boston, Massachusetts; Department of Pediatrics, Massachusetts General Hospital, Boston, Massachusetts; Department of Surgery, Boston Children's Hospital, Boston, Massachusetts
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198
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Fluck J, Madan S, Ansari S, Kodamullil AT, Karki R, Rastegar-Mojarad M, Catlett NL, Hayes W, Szostak J, Hoeng J, Peitsch M. Training and evaluation corpora for the extraction of causal relationships encoded in biological expression language (BEL). DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2016; 2016:baw113. [PMID: 27554092 PMCID: PMC4995071 DOI: 10.1093/database/baw113] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2015] [Accepted: 07/07/2016] [Indexed: 01/21/2023]
Abstract
Success in extracting biological relationships is mainly dependent on the complexity of the task as well as the availability of high-quality training data. Here, we describe the new corpora in the systems biology modeling language BEL for training and testing biological relationship extraction systems that we prepared for the BioCreative V BEL track. BEL was designed to capture relationships not only between proteins or chemicals, but also complex events such as biological processes or disease states. A BEL nanopub is the smallest unit of information and represents a biological relationship with its provenance. In BEL relationships (called BEL statements), the entities are normalized to defined namespaces mainly derived from public repositories, such as sequence databases, MeSH or publicly available ontologies. In the BEL nanopubs, the BEL statements are associated with citation information and supportive evidence such as a text excerpt. To enable the training of extraction tools, we prepared BEL resources and made them available to the community. We selected a subset of these resources focusing on a reduced set of namespaces, namely, human and mouse genes, ChEBI chemicals, MeSH diseases and GO biological processes, as well as relationship types ‘increases’ and ‘decreases’. The published training corpus contains 11 000 BEL statements from over 6000 supportive text excerpts. For method evaluation, we selected and re-annotated two smaller subcorpora containing 100 text excerpts. For this re-annotation, the inter-annotator agreement was measured by the BEL track evaluation environment and resulted in a maximal F-score of 91.18% for full statement agreement. In addition, for a set of 100 BEL statements, we do not only provide the gold standard expert annotations, but also text excerpts pre-selected by two automated systems. Those text excerpts were evaluated and manually annotated as true or false supportive in the course of the BioCreative V BEL track task. Database URL:http://wiki.openbel.org/display/BIOC/Datasets
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Affiliation(s)
- Juliane Fluck
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, Sankt Augustin, Germany
| | - Sumit Madan
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, Sankt Augustin, Germany
| | - Sam Ansari
- Philip Morris International R&D, Philip Morris Products S.A, Quai Jeanrenaud 5, Neuchâtel, 2000, Switzerland
| | - Alpha T Kodamullil
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, Sankt Augustin, Germany
| | - Reagon Karki
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, Sankt Augustin, Germany
| | | | | | - William Hayes
- Selventa, One Alewife Center, Cambridge, MA 02140, USA
| | - Justyna Szostak
- Philip Morris International R&D, Philip Morris Products S.A, Quai Jeanrenaud 5, Neuchâtel, 2000, Switzerland
| | - Julia Hoeng
- Philip Morris International R&D, Philip Morris Products S.A, Quai Jeanrenaud 5, Neuchâtel, 2000, Switzerland
| | - Manuel Peitsch
- Philip Morris International R&D, Philip Morris Products S.A, Quai Jeanrenaud 5, Neuchâtel, 2000, Switzerland
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199
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Chen Y, Gao Z, Wang B, Xu R. Towards precision medicine-based therapies for glioblastoma: interrogating human disease genomics and mouse phenotypes. BMC Genomics 2016; 17 Suppl 7:516. [PMID: 27557118 PMCID: PMC5001238 DOI: 10.1186/s12864-016-2908-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Glioblastoma (GBM) is the most common and aggressive brain tumors. It has poor prognosis even with optimal radio- and chemo-therapies. Since GBM is highly heterogeneous, drugs that target on specific molecular profiles of individual tumors may achieve maximized efficacy. Currently, the Cancer Genome Atlas (TCGA) projects have identified hundreds of GBM-associated genes. We develop a drug repositioning approach combining disease genomics and mouse phenotype data towards predicting targeted therapies for GBM. METHODS We first identified disease specific mouse phenotypes using the most recently discovered GBM genes. Then we systematically searched all FDA-approved drugs for candidates that share similar mouse phenotype profiles with GBM. We evaluated the ranks for approved and novel GBM drugs, and compared with an existing approach, which also use the mouse phenotype data but not the disease genomics data. RESULTS We achieved significantly higher ranks for the approved and novel GBM drugs than the earlier approach. For all positive examples of GBM drugs, we achieved a median rank of 9.2 45.6 of the top predictions have been demonstrated effective in inhibiting the growth of human GBM cells. CONCLUSION We developed a computational drug repositioning approach based on both genomic and phenotypic data. Our approach prioritized existing GBM drugs and outperformed a recent approach. Overall, our approach shows potential in discovering new targeted therapies for GBM.
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Affiliation(s)
- Yang Chen
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA
| | - Zhen Gao
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA
| | - Bingcheng Wang
- Department of Pharmacology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Rong Xu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA.
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200
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Puig-Oliveras A, Revilla M, Castelló A, Fernández AI, Folch JM, Ballester M. Expression-based GWAS identifies variants, gene interactions and key regulators affecting intramuscular fatty acid content and composition in porcine meat. Sci Rep 2016; 6:31803. [PMID: 27666082 PMCID: PMC4989154 DOI: 10.1038/srep31803] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2016] [Accepted: 07/26/2016] [Indexed: 12/20/2022] Open
Abstract
The aim of this work is to better understand the genetic mechanisms determining two complex traits affecting porcine meat quality: intramuscular fat (IMF) content and its fatty acid (FA) composition. With this purpose, expression Genome-Wide Association Study (eGWAS) of 45 lipid-related genes associated with meat quality traits in swine muscle (Longissimus dorsi) of 114 Iberian × Landrace backcross animals was performed. The eGWAS identified 241 SNPs associated with 11 genes: ACSM5, CROT, FABP3, FOS, HIF1AN, IGF2, MGLL, NCOA1, PIK3R1, PLA2G12A and PPARA. Three expression Quantitative Trait Loci (eQTLs) for IGF2, ACSM5 and MGLL were identified, showing cis-acting effects, whereas 16 eQTLs had trans regulatory effects. A polymorphism in the ACSM5 promoter region associated with its expression was identified. In addition, strong candidate genes regulating ACSM5, FOS, PPARA, PIK3R1, PLA2G12A and HIF1AN gene expression were also seen. Notably, the analysis highlighted the NR3C1 transcription factor as a strong candidate gene involved in the regulation of the 45 genes analysed. Finally, the IGF2, MGLL, MC2R, ARHGAP6, and NR3C1 genes were identified as potential regulators co-localizing within QTLs for fatness and growth traits in the IBMAP population. The results obtained increase our knowledge in the functional regulatory mechanisms involved in these complex traits.
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Affiliation(s)
- Anna Puig-Oliveras
- Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Spain.,Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), 08193 Bellaterra, Spain
| | - Manuel Revilla
- Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Spain.,Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), 08193 Bellaterra, Spain
| | - Anna Castelló
- Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Spain.,Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), 08193 Bellaterra, Spain
| | - Ana I Fernández
- Departamento de Genética Animal, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), 28040 Madrid, Spain
| | - Josep M Folch
- Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Spain.,Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), 08193 Bellaterra, Spain
| | - Maria Ballester
- Departament de Ciència Animal i dels Aliments, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Spain.,Plant and Animal Genomics, Centre de Recerca en Agrigenòmica (CRAG), 08193 Bellaterra, Spain.,Departament de Genètica i Millora Animal, Institut de Recerca i Tecnologia Agroalimentàries (IRTA), Torre Marimon, 08140 Caldes de Montbui, Spain
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