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Gómez-Pascual A, Glikman DM, Ng HX, Tomkins JE, Lu L, Xu Y, Ashbrook DG, Kaczorowski C, Kempermann G, Killmar J, Mozhui K, Aebersold R, Williams EG, Williams RW, Overall RW, Jucker M, de Bakker DEM. Polyglucosan body density in the aged mouse hippocampus is controlled by a novel modifier locus on chromosome 1. bioRxiv 2023:2023.11.22.567373. [PMID: 38045339 PMCID: PMC10690248 DOI: 10.1101/2023.11.22.567373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Aging can be associated with the accumulation of hypobranched glycogen molecules (polyglucosan bodies, PGBs), particularly in astrocytes of the hippocampus. While PGBs have a detrimental effect on cognition in diseases such as adult polyglucosan body disease and Lafora disease, the underlying mechanism and clinical relevance of age-related PGB accumulation remains unknown. Here, we have investigated the genetic basis and functional impact of age-related PGB accumulation in 32 fully sequenced BXD-type strains of mice which exhibit a 400-fold variation in PGB burden in 16-18 month old females. We mapped a major locus controlling PGB density in the hippocampus to chromosome 1 at 72-75 Mb (linkage of 4.9 -logP), which we defined as the Pgb1 locus. To identify potentially causal gene variants within Pgb1, we generated extensive hippocampal transcriptome datasets and identified two strong candidate genes for which mRNA correlates with PGB density-Smarcal1 and Usp37. In addition, both Smarcal1 and Usp37 contain non-synonymous allele variations likely to impact protein function. A phenome-wide association analysis highlighted a trans-regulatory effect of the Pgb1 locus on expression of Hp1bp3, a gene known to play a role in age-related changes in learning and memory. To investigate the potential impact of PGBs on cognition, we performed conditioned fear memory testing on strains displaying varying degrees of PGB burden, and a phenome-wide association scan of ~12,000 traits. Importantly, we did not find any evidence suggesting a negative impact of PGB burden on cognitive capacity. Taken together, we have identified a major modifier locus controlling PGB burden in the hippocampus and shed light on the genetic architecture and clinical relevance of this strikingly heterogeneous hippocampal phenotype.
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Affiliation(s)
- A Gómez-Pascual
- Department of Information and Communications Engineering, University of Murcia, Murcia, Spain
| | - D M Glikman
- University of Vienna, Vienna, Austria
- Department of Neuronal Cell Biology, Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - H X Ng
- Department of Cognitive Science University of California, San Diego, USA
| | - J E Tomkins
- Centre for Misfolding Diseases, Department of Chemistry, University of Cambridge, Cambridge, UK
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, 20815
| | - L Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Center, Memphis, TN, USA
| | - Y Xu
- Department of Cellular Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - D G Ashbrook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Center, Memphis, TN, USA
| | | | - G Kempermann
- German Center for Neurodegenerative Diseases (DZNE), Dresden, Germany
| | - J Killmar
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Center, Memphis, TN, USA
| | - K Mozhui
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Center, Memphis, TN, USA
- Department of Preventive Medicine, College of Medicine, University of Tennessee Health Center, Memphis, TN, USA
| | - R Aebersold
- Department of Biology, Institute of Molecular Systems Biology, ETH Zurich. Zurich, Switzerland
| | - E G Williams
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Center, Memphis, TN, USA
| | - R W Overall
- Humboldt University of Berlin, Berlin, Germany
| | - M Jucker
- Department of Cellular Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - D E M de Bakker
- Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
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Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Author Correction: Universal DNA methylation age across mammalian tissues. Nat Aging 2023; 3:1462. [PMID: 37674040 PMCID: PMC10645586 DOI: 10.1038/s43587-023-00499-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Affiliation(s)
- A T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - Z Fei
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, Riverside, CA, USA
| | - A Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - T R Robeck
- Zoological SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - J A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - R Lowe
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - Q Yan
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - J Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - H Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - V A Acosta-Rodriguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - D M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - J Almunia
- Loro Parque Fundacion, Puerto de la Cruz, Spain
| | - A Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - R Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C S Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - G Banks
- School of Science and Technology, Clifton Campus, Nottingham Trent University, Nottingham, UK
| | - K Belov
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - N C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - P Black
- Busch Gardens Tampa, Tampa, FL, USA
| | - D T Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
- Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - E K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - C E Breeze
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - R T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - G G Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - A Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - J M Cavin
- Gulf World, Dolphin Company, Panama City Beach, FL, USA
| | - L Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - I Chatzistamou
- Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - H Chen
- Department of Pharmacology, Addiction Science and Toxicology, the University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - P Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - O W Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S M Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - L N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - M L Cossette
- Department of Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - J Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - J DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S DiRocco
- SeaWorld of Florida, Orlando, FL, USA
| | - C Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | | | - C K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - S Emmrich
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E Erbay
- Altos Labs, San Francisco, CA, USA
| | - C Erlacher-Reid
- SeaWorld of Florida, Orlando, FL, USA
- SeaWorld Orlando, Orlando, FL, USA
| | - C G Faulkes
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - S H Ferguson
- Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - C J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - J M Gaillard
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - E Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - L Gerber
- Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - V N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - R G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - M J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - C B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - E N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - M B Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - D W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - M Haulena
- Vancouver Aquarium, Vancouver, British Columbia, Canada
| | - K Herrick
- SeaWorld of California, San Diego, CA, USA
| | - A N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - C J Hogg
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - T A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - T Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
- Division of Genetics and Metabolism, Oishei Children's Hospital, Buffalo, NY, USA
| | | | - A J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - G Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - O Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | - H Katcher
- Yuvan Research, Mountain View, CA, USA
| | | | - V Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - H Kiaris
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M S Kobor
- Edwin S.H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - P Kordowitzki
- Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences, Olsztyn, Poland
- Institute for Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | - W R Koski
- LGL Limited, King City, Ontario, Canada
| | - M Krützen
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
| | - S B Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Larison
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Center for Tropical Research, Institute for the Environment and Sustainability, UCLA, Los Angeles, CA, USA
| | - S G Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - J F Lemaitre
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - A J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - X Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - D T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - T J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - N Macoretta
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - D Maddox
- White Oak Conservation, Yulee, FL, USA
| | - C O Matkin
- North Gulf Oceanic Society, Homer, AK, USA
| | - J A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - J Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - J J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - G A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - K Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - J Munshi-South
- Louis Calder Center-Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - A Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M Nagy
- Museum fur Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - P Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - P W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - N B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Niehrs
- Institute of Molecular Biology, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - J K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - P O'Tierney Ginn
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - D T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Division of Regulatory Genomics and Cancer Evolution, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - A G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - S Osborn
- SeaWorld of Texas, San Antonio, TX, USA
| | - E A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - K M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - K C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - M Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - K J Peters
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
| | - A B Pedersen
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - J L Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - D W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - G M Pinho
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - J R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
| | - P Reddy
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - B Rey
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - B R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - J Robbins
- Center for Coastal Studies, Provincetown, MA, USA
| | | | - J Russell
- SeaWorld of California, San Diego, CA, USA
| | - E Rydkina
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - L L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - A B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - K M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - D Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | - T Schmitt
- SeaWorld of California, San Diego, CA, USA
| | | | - L B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - K E Sears
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - A W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - A Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - A B A Shafer
- Department of Forensic Science, Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - D Shanmuganayagam
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - K Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - I Sinha
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - R G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - E Soltanmaohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | | | - L Staggs
- SeaWorld of Florida, Orlando, FL, USA
| | | | - K J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - D T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | - V J Sugrue
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - B Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - J S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Takasugi
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E C Teeling
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - M J Thompson
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Van Bonn
- John G. Shedd Aquarium, Chicago, IL, USA
| | - S C Vernes
- School of Biology, the University of St Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - D Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - H V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M C Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - N Wang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R K Wayne
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - G S Wilkinson
- Department of Biology, University of Maryland, College Park, MD, USA
| | - C K Williams
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - X W Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M Yao
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - B G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - B Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Zhang
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - P Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, USA
| | - Y Zhao
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - W Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Zimmermann
- Department of Mathematics and Technology, University of Applied Sciences Koblenz, Koblenz, Germany
| | - J Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - K Raj
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - S Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
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3
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Lu AT, Fei Z, Haghani A, Robeck TR, Zoller JA, Li CZ, Lowe R, Yan Q, Zhang J, Vu H, Ablaeva J, Acosta-Rodriguez VA, Adams DM, Almunia J, Aloysius A, Ardehali R, Arneson A, Baker CS, Banks G, Belov K, Bennett NC, Black P, Blumstein DT, Bors EK, Breeze CE, Brooke RT, Brown JL, Carter GG, Caulton A, Cavin JM, Chakrabarti L, Chatzistamou I, Chen H, Cheng K, Chiavellini P, Choi OW, Clarke SM, Cooper LN, Cossette ML, Day J, DeYoung J, DiRocco S, Dold C, Ehmke EE, Emmons CK, Emmrich S, Erbay E, Erlacher-Reid C, Faulkes CG, Ferguson SH, Finno CJ, Flower JE, Gaillard JM, Garde E, Gerber L, Gladyshev VN, Gorbunova V, Goya RG, Grant MJ, Green CB, Hales EN, Hanson MB, Hart DW, Haulena M, Herrick K, Hogan AN, Hogg CJ, Hore TA, Huang T, Izpisua Belmonte JC, Jasinska AJ, Jones G, Jourdain E, Kashpur O, Katcher H, Katsumata E, Kaza V, Kiaris H, Kobor MS, Kordowitzki P, Koski WR, Krützen M, Kwon SB, Larison B, Lee SG, Lehmann M, Lemaitre JF, Levine AJ, Li C, Li X, Lim AR, Lin DTS, Lindemann DM, Little TJ, Macoretta N, Maddox D, Matkin CO, Mattison JA, McClure M, Mergl J, Meudt JJ, Montano GA, Mozhui K, Munshi-South J, Naderi A, Nagy M, Narayan P, Nathanielsz PW, Nguyen NB, Niehrs C, O'Brien JK, O'Tierney Ginn P, Odom DT, Ophir AG, Osborn S, Ostrander EA, Parsons KM, Paul KC, Pellegrini M, Peters KJ, Pedersen AB, Petersen JL, Pietersen DW, Pinho GM, Plassais J, Poganik JR, Prado NA, Reddy P, Rey B, Ritz BR, Robbins J, Rodriguez M, Russell J, Rydkina E, Sailer LL, Salmon AB, Sanghavi A, Schachtschneider KM, Schmitt D, Schmitt T, Schomacher L, Schook LB, Sears KE, Seifert AW, Seluanov A, Shafer ABA, Shanmuganayagam D, Shindyapina AV, Simmons M, Singh K, Sinha I, Slone J, Snell RG, Soltanmaohammadi E, Spangler ML, Spriggs MC, Staggs L, Stedman N, Steinman KJ, Stewart DT, Sugrue VJ, Szladovits B, Takahashi JS, Takasugi M, Teeling EC, Thompson MJ, Van Bonn B, Vernes SC, Villar D, Vinters HV, Wallingford MC, Wang N, Wayne RK, Wilkinson GS, Williams CK, Williams RW, Yang XW, Yao M, Young BG, Zhang B, Zhang Z, Zhao P, Zhao Y, Zhou W, Zimmermann J, Ernst J, Raj K, Horvath S. Universal DNA methylation age across mammalian tissues. Nat Aging 2023; 3:1144-1166. [PMID: 37563227 PMCID: PMC10501909 DOI: 10.1038/s43587-023-00462-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 06/21/2023] [Indexed: 08/12/2023]
Abstract
Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.
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Affiliation(s)
- A T Lu
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - Z Fei
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Statistics, University of California, Riverside, Riverside, CA, USA
| | - A Haghani
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - T R Robeck
- Zoological SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - J A Zoller
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Z Li
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - R Lowe
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - Q Yan
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
| | - J Zhang
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - H Vu
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - J Ablaeva
- Department of Biology, University of Rochester, Rochester, NY, USA
| | - V A Acosta-Rodriguez
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - D M Adams
- Department of Biology, University of Maryland, College Park, MD, USA
| | - J Almunia
- Loro Parque Fundacion, Puerto de la Cruz, Spain
| | - A Aloysius
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - R Ardehali
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A Arneson
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - C S Baker
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - G Banks
- School of Science and Technology, Clifton Campus, Nottingham Trent University, Nottingham, UK
| | - K Belov
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - N C Bennett
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - P Black
- Busch Gardens Tampa, Tampa, FL, USA
| | - D T Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, CA, USA
- Rocky Mountain Biological Laboratory, Crested Butte, CO, USA
| | - E K Bors
- Marine Mammal Institute, Oregon State University, Newport, OR, USA
| | - C E Breeze
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - R T Brooke
- Epigenetic Clock Development Foundation, Los Angeles, CA, USA
| | - J L Brown
- Center for Species Survival, Smithsonian Conservation Biology Institute, Front Royal, VA, USA
| | - G G Carter
- Department of Evolution, Ecology and Organismal Biology, The Ohio State University, Columbus, OH, USA
| | - A Caulton
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
- Department of Biochemistry, University of Otago, Dunedin, New Zealand
| | - J M Cavin
- Gulf World, Dolphin Company, Panama City Beach, FL, USA
| | - L Chakrabarti
- School of Veterinary Medicine and Science, University of Nottingham, Nottingham, UK
| | - I Chatzistamou
- Department of Pathology, Microbiology and Immunology, School of Medicine, University of South Carolina, Columbia, SC, USA
| | - H Chen
- Department of Pharmacology, Addiction Science and Toxicology, the University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Cheng
- Medical Informatics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - P Chiavellini
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - O W Choi
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S M Clarke
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - L N Cooper
- Department of Anatomy and Neurobiology, Northeast Ohio Medical University, Rootstown, OH, USA
| | - M L Cossette
- Department of Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - J Day
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - J DeYoung
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - S DiRocco
- SeaWorld of Florida, Orlando, FL, USA
| | - C Dold
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | | | - C K Emmons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - S Emmrich
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E Erbay
- Altos Labs, San Francisco, CA, USA
| | - C Erlacher-Reid
- SeaWorld of Florida, Orlando, FL, USA
- SeaWorld Orlando, Orlando, FL, USA
| | - C G Faulkes
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - S H Ferguson
- Fisheries and Oceans Canada, Freshwater Institute, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - C J Finno
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | | | - J M Gaillard
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - E Garde
- Greenland Institute of Natural Resources, Nuuk, Greenland
| | - L Gerber
- Evolution and Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, New South Wales, Australia
| | - V N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - V Gorbunova
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - R G Goya
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - M J Grant
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - C B Green
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - E N Hales
- Department of Population Health and Reproduction, University of California, Davis School of Veterinary Medicine, Davis, CA, USA
| | - M B Hanson
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - D W Hart
- Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - M Haulena
- Vancouver Aquarium, Vancouver, British Columbia, Canada
| | - K Herrick
- SeaWorld of California, San Diego, CA, USA
| | - A N Hogan
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - C J Hogg
- School of Life and Environmental Sciences, the University of Sydney, Sydney, New South Wales, Australia
| | - T A Hore
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - T Huang
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
- Division of Genetics and Metabolism, Oishei Children's Hospital, Buffalo, NY, USA
| | | | - A J Jasinska
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - G Jones
- School of Biological Sciences, University of Bristol, Bristol, UK
| | | | - O Kashpur
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
| | - H Katcher
- Yuvan Research, Mountain View, CA, USA
| | | | - V Kaza
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
| | - H Kiaris
- Peromyscus Genetic Stock Center, University of South Carolina, Columbia, SC, USA
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M S Kobor
- Edwin S.H. Leong Healthy Aging Program, Centre for Molecular Medicine and Therapeutics, University of British Columbia, Vancouver, British Columbia, Canada
| | - P Kordowitzki
- Institute of Animal Reproduction and Food Research of the Polish Academy of Sciences, Olsztyn, Poland
- Institute for Veterinary Medicine, Nicolaus Copernicus University, Torun, Poland
| | - W R Koski
- LGL Limited, King City, Ontario, Canada
| | - M Krützen
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
| | - S B Kwon
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Larison
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Center for Tropical Research, Institute for the Environment and Sustainability, UCLA, Los Angeles, CA, USA
| | - S G Lee
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - M Lehmann
- Biochemistry Research Institute of La Plata, Histology and Pathology, School of Medicine, University of La Plata, La Plata, Argentina
| | - J F Lemaitre
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - A J Levine
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Li
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - X Li
- Technology Center for Genomics and Bioinformatics, Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - A R Lim
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - D T S Lin
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - T J Little
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - N Macoretta
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - D Maddox
- White Oak Conservation, Yulee, FL, USA
| | - C O Matkin
- North Gulf Oceanic Society, Homer, AK, USA
| | - J A Mattison
- Translational Gerontology Branch, National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | | | - J Mergl
- Marineland of Canada, Niagara Falls, Ontario, Canada
| | - J J Meudt
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - G A Montano
- Zoological Operations, SeaWorld Parks and Entertainment, Orlando, FL, USA
| | - K Mozhui
- Department of Preventive Medicine, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - J Munshi-South
- Louis Calder Center-Biological Field Station, Department of Biological Sciences, Fordham University, Armonk, NY, USA
| | - A Naderi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M Nagy
- Museum fur Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany
| | - P Narayan
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - P W Nathanielsz
- Texas Pregnancy and Life-course Health Center, Southwest National Primate Research Center, San Antonio, TX, USA
- Department of Animal Science, College of Agriculture and Natural Resources, Laramie, WY, USA
| | - N B Nguyen
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - C Niehrs
- Institute of Molecular Biology, Mainz, Germany
- Division of Molecular Embryology, DKFZ-ZMBH Alliance, Heidelberg, Germany
| | - J K O'Brien
- Taronga Institute of Science and Learning, Taronga Conservation Society Australia, Mosman, New South Wales, Australia
| | - P O'Tierney Ginn
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Department of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - D T Odom
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
- Division of Regulatory Genomics and Cancer Evolution, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - A G Ophir
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - S Osborn
- SeaWorld of Texas, San Antonio, TX, USA
| | - E A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - K M Parsons
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Seattle, WA, USA
| | - K C Paul
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - M Pellegrini
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - K J Peters
- Evolutionary Genetics Group, Department of Evolutionary Anthropology, University of Zurich, Zurich, Switzerland
- School of Earth, Atmospheric and Life Sciences, University of Wollongong, Wollongong, Australia
| | - A B Pedersen
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
| | - J L Petersen
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | - D W Pietersen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Hatfield, South Africa
| | - G M Pinho
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Plassais
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - J R Poganik
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Prado
- Department of Biology, College of Arts and Science, Adelphi University, Garden City, NY, USA
| | - P Reddy
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA
- Salk Institute for Biological Studies, La Jolla, CA, USA
| | - B Rey
- Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive, Villeurbanne, France
| | - B R Ritz
- Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Environmental Health Sciences, UCLA Fielding School of Public Health, Los Angeles, CA, USA
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - J Robbins
- Center for Coastal Studies, Provincetown, MA, USA
| | | | - J Russell
- SeaWorld of California, San Diego, CA, USA
| | - E Rydkina
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - L L Sailer
- Department of Psychology, Cornell University, Ithaca, NY, USA
| | - A B Salmon
- The Sam and Ann Barshop Institute for Longevity and Aging Studies and Department of Molecular Medicine, UT Health San Antonio and the Geriatric Research Education and Clinical Center, South Texas Veterans Healthcare System, San Antonio, TX, USA
| | | | - K M Schachtschneider
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Biochemistry and Molecular Genetics, University of Illinois at Chicago, Chicago, IL, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - D Schmitt
- College of Agriculture, Missouri State University, Springfield, MO, USA
| | - T Schmitt
- SeaWorld of California, San Diego, CA, USA
| | | | - L B Schook
- Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA
- Department of Animal Sciences, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - K E Sears
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - A W Seifert
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - A Seluanov
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - A B A Shafer
- Department of Forensic Science, Environmental and Life Sciences, Trent University, Peterborough, Ontario, Canada
| | - D Shanmuganayagam
- Biomedical and Genomic Research Group, Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI, USA
- Department of Surgery, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - A V Shindyapina
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - K Singh
- Shobhaben Pratapbhai Patel School of Pharmacy and Technology Management, SVKM'S NMIMS University, Mumbai, India
| | - I Sinha
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - J Slone
- Division of Human Genetics, Department of Pediatrics, University at Buffalo, Buffalo, NY, USA
| | - R G Snell
- Applied Translational Genetics Group, School of Biological Sciences, Centre for Brain Research, the University of Auckland, Auckland, New Zealand
| | - E Soltanmaohammadi
- Department of Drug Discovery and Biomedical Sciences, College of Pharmacy, University of South Carolina, Columbia, SC, USA
| | - M L Spangler
- Department of Animal Science, University of Nebraska, Lincoln, NE, USA
| | | | - L Staggs
- SeaWorld of Florida, Orlando, FL, USA
| | | | - K J Steinman
- Species Preservation Laboratory, SeaWorld San Diego, San Diego, CA, USA
| | - D T Stewart
- Biology Department, Acadia University, Wolfville, Nova Scotia, Canada
| | - V J Sugrue
- Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - B Szladovits
- Department of Pathobiology and Population Sciences, Royal Veterinary College, Hatfield, UK
| | - J S Takahashi
- Department of Neuroscience, Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Howard Hughes Medical Institute, Department of Neuroscience, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - M Takasugi
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - E C Teeling
- School of Biology and Environmental Science, University College Dublin, Dublin, Ireland
| | - M J Thompson
- Department of Molecular Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - B Van Bonn
- John G. Shedd Aquarium, Chicago, IL, USA
| | - S C Vernes
- School of Biology, the University of St Andrews, Fife, UK
- Neurogenetics of Vocal Communication Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands
| | - D Villar
- Blizard Institute, Faculty of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - H V Vinters
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M C Wallingford
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, USA
- Division of Obstetrics and Gynecology, Tufts University School of Medicine, Boston, MA, USA
| | - N Wang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - R K Wayne
- Department of Ecology and Evolutionary Biology, UCLA, Los Angeles, CA, USA
| | - G S Wilkinson
- Department of Biology, University of Maryland, College Park, MD, USA
| | - C K Williams
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, College of Medicine, Memphis, TN, USA
| | - X W Yang
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - M Yao
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - B G Young
- Fisheries and Oceans Canada, Winnipeg, Manitoba, Canada
| | - B Zhang
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Z Zhang
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - P Zhao
- Division of Cardiology, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, CA, USA
| | - Y Zhao
- Departments of Biology and Medicine, University of Rochester, Rochester, NY, USA
| | - W Zhou
- Center for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Zimmermann
- Department of Mathematics and Technology, University of Applied Sciences Koblenz, Koblenz, Germany
| | - J Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | - K Raj
- Altos Labs, Cambridge Institute of Science, Cambridge, UK
| | - S Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Altos Labs, San Diego Institute of Science, San Diego, CA, USA.
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA, USA.
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4
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Ashbrook DG, Mulligan MK, Williams RW. Post-genomic behavioral genetics: From revolution to routine. Genes Brain Behav 2018; 17:e12441. [PMID: 29193773 PMCID: PMC5876106 DOI: 10.1111/gbb.12441] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 11/02/2017] [Accepted: 11/20/2017] [Indexed: 12/16/2022]
Abstract
What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www. RESEARCH va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.
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Affiliation(s)
- D G Ashbrook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, College of Medicine, Memphis, Tennessee
| | - M K Mulligan
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, College of Medicine, Memphis, Tennessee
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, College of Medicine, Memphis, Tennessee
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5
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Delprato A, Bonheur B, Algéo MP, Murillo A, Dhawan E, Lu L, Williams RW, Crusio WE. A quantitative trait locus on chromosome 1 modulates intermale aggression in mice. Genes Brain Behav 2018; 17:e12469. [PMID: 29457871 DOI: 10.1111/gbb.12469] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Revised: 01/30/2018] [Accepted: 02/15/2018] [Indexed: 12/28/2022]
Abstract
Aggression between male conspecifics is a complex social behavior that is likely modulated by multiple gene variants. In this study, the BXD recombinant inbred mouse strains (RIS) were used to map quantitative trait loci (QTLs) underlying behaviors associated with intermale aggression. Four hundred and fifty-seven males from 55 strains (including the parentals) were observed at an age of 13 ± 1 week in a resident-intruder test following 10 days of isolation. Attack latency was measured directly within a 10-minute time period and the test was repeated 24 hours later. The variables we analyzed were the proportion of attacking males in a given strain as well as the attack latency (on days 1 and 2, and both days combined). On day 1, 29% of males attacked, and this increased to 37% on day 2. Large strain differences were obtained for all measures of aggression, indicating substantial heritability (intraclass correlations 0.10-0.18). We identified a significant QTL on chromosome (Chr) 1 and suggestive QTLs on mouse Chrs 1 and 12 for both attack and latency variables. The significant Chr 1 locus maps to a gene-sparse region between 82 and 88.5 Mb with the C57BL/6J allele increasing aggression and explaining about 18% of the variance. The most likely candidate gene modulating this trait is Htr2b which encodes the serotonin 2B receptor and has been implicated in aggressive and impulsive behavior in mice, humans and other species.
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Affiliation(s)
- A Delprato
- Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287, University of Bordeaux, Pessac Cedex, France.,CNRS, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287, Pessac Cedex, France.,BioScience Project, Wakefield, Massachusetts
| | - B Bonheur
- Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287, University of Bordeaux, Pessac Cedex, France.,CNRS, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287, Pessac Cedex, France
| | - M-P Algéo
- Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287, University of Bordeaux, Pessac Cedex, France.,CNRS, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287, Pessac Cedex, France
| | - A Murillo
- BioScience Project, Wakefield, Massachusetts
| | - E Dhawan
- BioScience Project, Wakefield, Massachusetts
| | - L Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, Memphis, Tennessee
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, Memphis, Tennessee
| | - W E Crusio
- Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287, University of Bordeaux, Pessac Cedex, France.,CNRS, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, UMR 5287, Pessac Cedex, France
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6
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Breeze J, Patel J, Dover MS, Williams RW. Success rates and complications of autologous onlay bone grafts and sinus lifts in patients with congenital hypodontia and after trauma. Br J Oral Maxillofac Surg 2017; 55:830-833. [PMID: 28869085 DOI: 10.1016/j.bjoms.2017.08.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Accepted: 08/02/2017] [Indexed: 10/19/2022]
Abstract
Autogenous bone remains the gold standard for augmentation of the alveolar ridge in congenital hypodontia and appreciable post-traumatic deformity. This generally reflects the volume of material required for such defects and the osteogenic potential of the grafts. Morbidity at the donor site and success rates may lead to autogenous grafts being superseded by xenografts or alloplastic materials in the future, but we know of little evidence to confirm this. All patients having augmentation of the alveolar ridge or sinus lift to enable subsequent placement of implants between 01 January 2009 and 31 December 2016 were identified from a prospectively-gathered database held at the Queen Elizabeth Hospital, Birmingham. Morbidity was recorded, with overall success defined as a graft that enabled subsequent placement of an implant. During this period the following grafts: calvarial (n=4), iliac crest (n=4), and ramus (n=149) were recorded, as well as 53 sinus lifts. Sinus lift augmentation with BioOss® had the highest success rate (51/53). Calvarial and iliac crest grafts had higher failure rates (2/4 and 3/4, respectively) than those from the mandibular ramus (6/149, 4%). Fifteen of 149 (10%) ramus grafts resulted in transient anaesthesia of the inferior alveolar nerve but no patients developed any permanent morbidity at the donor or recipient sites. Ramus grafts are a predictable method of bone augmentation with only transient morbidity at the donor site. Higher failure rates for extraoral grafts probably reflect their use in more challenging cases when more bone is required. Bilateral ramus grafts are an alternative to extraoral grafts and may be supplemented by bovine-derived particulate grafts with no appreciable increase in complications.
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Affiliation(s)
- J Breeze
- Queen Elizabeth Hospital Birmingham, Mindelsohn Way, Edgbaston, Birmingham B15 2GW.
| | - J Patel
- Queen Elizabeth Hospital Birmingham, Mindelsohn Way, Edgbaston, Birmingham B15 2GW
| | - M S Dover
- Queen Elizabeth Hospital Birmingham, Mindelsohn Way, Edgbaston, Birmingham B15 2GW
| | - R W Williams
- Queen Elizabeth Hospital Birmingham, Mindelsohn Way, Edgbaston, Birmingham B15 2GW
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7
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Delprato A, Algéo MP, Bonheur B, Bubier JA, Lu L, Williams RW, Chesler EJ, Crusio WE. QTL and systems genetics analysis of mouse grooming and behavioral responses to novelty in an open field. Genes Brain Behav 2017; 16:790-799. [PMID: 28544613 DOI: 10.1111/gbb.12392] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 05/11/2017] [Accepted: 05/11/2017] [Indexed: 02/04/2023]
Abstract
The open field is a classic test used to assess exploratory behavior, anxiety and locomotor activity in rodents. Here, we mapped quantitative trait loci (QTLs) underlying behaviors displayed in an open field, using a panel of 53 BXD recombinant inbred mouse strains with deep replication (10 per strain and sex). The use of these strains permits the integration and comparison of data obtained in different laboratories, and also offers the possibility to study trait covariance by exploiting powerful bioinformatics tools and resources. We quantified behavioral traits during 20-min test sessions including (1) percent time spent and distance traveled near the wall (thigmotaxis), (2) leaning against the wall, (3) rearing, (4) jumping, (5) grooming duration, (6) grooming frequency, (7) locomotion and (8) defecation. All traits exhibit moderate heritability making them amenable to genetic analysis. We identified a significant QTL on chromosome M.m. 4 at approximately 104 Mb that modulates grooming duration in both males and females (likelihood ratio statistic values of approximately 18, explaining 25% and 14% of the variance, respectively) and a suggestive QTL modulating locomotion that maps to the same locus. Bioinformatic analysis indicates Disabled 1 (Dab1, a key protein in the reelin signaling pathway) as a particularly strong candidate gene modulating these behaviors. We also found 2 highly suggestive QTLs for a sex by strain interaction for grooming duration on chromosomes 13 and 17. In addition, we identified a pairwise epistatic interaction between loci on chromosomes 12 at 36-37 Mb and 14 at 34-36 Mb that influences rearing frequency in males.
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Affiliation(s)
- A Delprato
- Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, University of Bordeaux, Pessac, France.,Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, CNRS, Pessac, France.,BioScience Project, Wakefield, MA, USA
| | - M-P Algéo
- Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, University of Bordeaux, Pessac, France.,Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, CNRS, Pessac, France
| | - B Bonheur
- Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, University of Bordeaux, Pessac, France.,Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, CNRS, Pessac, France
| | - J A Bubier
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - L Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, Memphis, TN, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, Memphis, TN, USA
| | | | - W E Crusio
- Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, University of Bordeaux, Pessac, France.,Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, CNRS, Pessac, France
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8
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Delprato A, Bonheur B, Algéo MP, Rosay P, Lu L, Williams RW, Crusio WE. Systems genetic analysis of hippocampal neuroanatomy and spatial learning in mice. Genes Brain Behav 2015; 14:591-606. [PMID: 26449520 DOI: 10.1111/gbb.12259] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Revised: 09/20/2015] [Accepted: 10/06/2015] [Indexed: 12/23/2022]
Abstract
Variation in hippocampal neuroanatomy correlates well with spatial learning ability in mice. Here, we have studied both hippocampal neuroanatomy and behavior in 53 isogenic BXD recombinant strains derived from C57BL/6J and DBA/2J parents. A combination of experimental, neuroinformatic and systems genetics methods was used to test the genetic bases of variation and covariation among traits. Data were collected on seven hippocampal subregions in CA3 and CA4 after testing spatial memory in an eight-arm radial maze task. Quantitative trait loci were identified for hippocampal structure, including the areas of the intra- and infrapyramidal mossy fibers (IIPMFs), stratum radiatum and stratum pyramidale, and for a spatial learning parameter, error rate. We identified multiple loci and gene variants linked to either structural differences or behavior. Gpc4 and Tenm2 are strong candidate genes that may modulate IIPMF areas. Analysis of gene expression networks and trait correlations highlight several processes influencing morphometrical variation and spatial learning.
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Affiliation(s)
- A Delprato
- University of Bordeaux, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France.,CNRS, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France.,BioScience Project, Wakefield, MA, USA
| | - B Bonheur
- University of Bordeaux, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France.,CNRS, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France
| | - M-P Algéo
- University of Bordeaux, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France.,CNRS, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France
| | - P Rosay
- University of Bordeaux, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France.,CNRS, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France
| | - L Lu
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, Memphis, TN, USA
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, Memphis, TN, USA
| | - W E Crusio
- University of Bordeaux, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France.,CNRS, Institut de Neurosciences Cognitives et Intégratives d'Aquitaine, Pessac, France
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9
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Ye R, Carneiro AMD, Airey D, Sanders-Bush E, Williams RW, Lu L, Wang J, Zhang B, Blakely RD. Evaluation of heritable determinants of blood and brain serotonin homeostasis using recombinant inbred mice. Genes Brain Behav 2013; 13:247-60. [PMID: 24102824 DOI: 10.1111/gbb.12092] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2013] [Revised: 10/01/2013] [Accepted: 10/01/2013] [Indexed: 12/31/2022]
Abstract
The biogenic amine serotonin (5-HT, 5-hydroxytryptamine) exerts powerful, modulatory control over multiple physiological functions in the brain and periphery, ranging from mood and appetite to vasoconstriction and gastrointestinal motility. In order to gain insight into shared and distinct molecular and phenotypic networks linked to variations in 5-HT homeostasis, we capitalized on the stable genetic variation present in recombinant inbred mouse strains. This family of strains, all derived from crosses between C57BL/6J and DBA/2J (BXD) parents, represents a unique, community resource with approximately 40 years of assembled phenotype data that can be exploited to explore and test causal relationships in silico. We determined levels of 5-HT and 5-hydroxyindoleacetic acid from whole blood, midbrain and thalamus/hypothalamus (diencephalon) of 38 BXD lines and both sexes. All 5-HT measures proved highly heritable in each region, although both gender and region significantly impacted between-strain correlations. Our studies identified both expected and novel biochemical, anatomical and behavioral phenotypes linked to 5-HT traits, as well as distinct quantitative trait loci. Analyses of these loci nominate a group of genes likely to contribute to gender- and region-specific capacities for 5-HT signaling. Analysis of midbrain mRNA variations across strains revealed overlapping gene expression networks linked to 5-HT synthesis and metabolism. Altogether, our studies provide a rich profile of genomic, molecular and phenotypic networks that can be queried for novel relationships contributing risk for disorders linked to perturbed 5-HT signaling.
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Affiliation(s)
- R Ye
- Department of Pharmacology, Vanderbilt University School of Medicine, Nashville
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10
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Huang Y, Wang L, Bennett B, Williams RW, Wang YJ, Gu WK, Jiao Y. Potential role of Atp5g3 in epigenetic regulation of alcohol preference or obesity from a mouse genomic perspective. Genet Mol Res 2013; 12:3662-74. [PMID: 24085430 DOI: 10.4238/2013.september.18.1] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
The mitochondrial ATP synthase, subunit c, isoform 3 gene (Atp5g3) encodes subunit 9, the subunit of the multisubunit enzyme that catalyzes ATP synthesis during oxidative phosphorylation in mitochondria. According to the Ensembl database, Atp5g3 in mice is located on chromosome 2 between 73746504 and 73749383 bp, within the genomic regions of two sets of quantitative trait loci - alcohol preference and body weight. Both of those traits are more influenced by epigenetic factors than many other traits are. Using currently available phenotype and gene expression profiles from the GeneNetwork database, we obtained correlations between Atp5g3 and alcoholism- and obesity-relevant phenotypes. The correlation in expression levels between Atp5g3 and each of its 12 partner genes in the molecular interaction are different in various tissues and genes. Transcriptome mapping indicated that Atp5g3 is differentially regulated in the hippocampus, cerebellum, and liver. Owing to a lack of known polymorphisms of Atp5g3 among three relevant mouse strains, C57BL/6J (B6), DBA/2J (D2), and BALB/ cJ, the molecular mechanism for the connection between Atp5g3 and alcoholism and body weight requires further investigation.
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Affiliation(s)
- Y Huang
- Department of Orthopaedic Surgery and BME-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN, USA
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11
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Jellen LC, Lu L, Wang X, Unger EL, Earley CJ, Allen RP, Williams RW, Jones BC. Iron deficiency alters expression of dopamine-related genes in the ventral midbrain in mice. Neuroscience 2013; 252:13-23. [PMID: 23911809 DOI: 10.1016/j.neuroscience.2013.07.058] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2013] [Revised: 07/24/2013] [Accepted: 07/24/2013] [Indexed: 12/01/2022]
Abstract
A clear link exists between iron deficiency (ID) and nigrostriatal dopamine malfunction. This link appears to play an important role in at least restless legs syndrome (RLS) if not several other neurological diseases. Yet, the underlying mechanisms remain unclear. The effects of ID on gene expression in the brain have not been studied extensively. Here, to better understand how exactly ID alters dopamine functioning, we investigated the effects of ID on gene expression in the brain, seeking to identify any potential transcription-based mechanisms. We used six strains of recombinant inbred mice (BXD type) known to differ in susceptibility to ID in the brain. Upon weaning, we subjected mice from each strain to either an iron-deficient or iron-adequate diet. After 100 days of dietary treatment, we measured the effects of ID on gene expression in the ventral midbrain, a region containing the substantia nigra. The substantia nigra is the base of the nigrostriatal dopamine pathway and a region particularly affected by iron loss in RLS. We screened for ID-induced changes in expression, including changes in that of both iron-regulating and dopamine-related genes. Results revealed a number of expression changes occurring in ID, with large strain-dependent differences in the genes involved and number of expression changes occurring. In terms of dopamine-related genes, results revealed ID-induced expression changes in three genes with direct ties to nigrostriatal dopamine functioning, two of which have never before been implicated in an iron-dopamine pathway. These were stromal cell-derived factor 1 (Cxcl12, or SDF-1), a ferritin regulator and potent dopamine neuromodulator, and hemoglobin, beta adult chain 1 (Hbb-b1), a gene recently shown to play a functional role in dopaminergic neurons. The extent of up-regulation of these genes varied by strain. This work not only demonstrates a wide genetic variation in the transcriptional response to ID in the brain, but also reveals two novel biochemical pathways by which iron may potentially alter dopamine function.
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Affiliation(s)
- L C Jellen
- Neuroscience Institute, The Pennsylvania State University, University Park, PA, USA
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12
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Hernandez-Medrano JH, Williams RW, van Drunen Littel-van den Hurk S, Peters AR, Hannant D, Campbell BK, Webb R. Early postnatal immunisation against gonadotrophin-releasing hormone induces a high but differential immune response in heifer calves. Res Vet Sci 2013; 95:472-9. [PMID: 23778305 DOI: 10.1016/j.rvsc.2013.05.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2013] [Revised: 05/21/2013] [Accepted: 05/26/2013] [Indexed: 10/26/2022]
Abstract
The aim of this study was to evaluate endocrinological and immunological effects of early postnatal immunisation against gonadotrophin-releasing hormone (GnRH) in heifer calves, as similar treatment in sheep provokes long-term immunocastration. Heifer calves were injected with either a construct of GnRH - bovine herpes virus 1 glycoprotein D (BHV1 gD; n=9) or saline (n=9) at 2, 6 and 13.5 weeks of age. Antibody (GnRH and carrier) and endocrine responses to immunisation were measured twice monthly (FSH and progesterone) or during intensive sampling regimes (LH). Early postnatal immunisation against GnRH induced a high, but variable, antibody response against both GnRH and carrier. Based on antibody responses, animals were divided into high-titre (HT, n=5) and low-titre (LT, n=4). Occurring mainly in HT, a further peak in anti-GnRH antibodies, stimulated independently of the carrier, was observed at 23 weeks of age, with antibody titres ≥ 10% binding for ≈ 9 weeks post-peak. Conversely immunisation had only temporary, reversible effects on reproductive function, not affecting age at puberty. We hypothesise that the newly generated antibody measured 10 weeks after the final immunisation resulted from antigenic stimulation and immunological memory cell activation to an endogenous GnRH release. This outcome offers an opportunity for further manipulation of reproductive function based on modulation of GnRH secretion and activity where long-term immunological memory may contribute to durable endocrine effects.
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Affiliation(s)
- J H Hernandez-Medrano
- Division of Animal Sciences, School of Biosciences, Sutton Bonington Campus, The University of Nottingham, Loughborough LE12 5RD, United Kingdom.
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13
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Rosen GD, Azoulay NG, Griffin EG, Newbury A, Koganti L, Fujisaki N, Takahashi E, Grant PE, Truong DT, Fitch RH, Lu L, Williams RW. Bilateral subcortical heterotopia with partial callosal agenesis in a mouse mutant. ACTA ACUST UNITED AC 2012; 23:859-72. [PMID: 22455839 DOI: 10.1093/cercor/bhs080] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Cognition and behavior depend on the precise placement and interconnection of complex ensembles of neurons in cerebral cortex. Mutations that disrupt migration of immature neurons from the ventricular zone to the cortical plate have provided major insight into mechanisms of brain development and disease. We have discovered a new and highly penetrant spontaneous mutation that leads to large nodular bilateral subcortical heterotopias with partial callosal agenesis. The mutant phenotype was first detected in a colony of fully inbred BXD29 mice already known to harbor a mutation in Tlr4. Neurons confined to the heterotopias are mainly born in midgestation to late gestation and would normally have migrated into layers 2-4 of overlying neocortex. Callosal cross-sectional area and fiber number are reduced up to 50% compared with coisogenic wildtype BXD29 substrain controls. Mutants have a pronounced and highly selective defect in rapid auditory processing. The segregation pattern of the mutant phenotype is most consistent with a two-locus autosomal recessive model, and selective genotyping definitively rules out the Tlr4 mutation as a cause. The discovery of a novel mutation with strong pleiotropic anatomical and behavioral effects provides an important new resource for dissecting molecular mechanisms and functional consequences of errors of neuronal migration.
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Affiliation(s)
- G D Rosen
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA.
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14
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Hernandez-Medrano JH, Williams RW, Peters AR, Hannant D, Campbell BK, Webb R. Neonatal immunisation against a novel gonadotrophin-releasing hormone construct delays the onset of gonadal growth and puberty in bull calves. Reprod Fertil Dev 2012; 24:973-82. [DOI: 10.1071/rd11210] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2011] [Accepted: 02/03/2012] [Indexed: 11/23/2022] Open
Abstract
The aim of the present study was to investigate the effect of the neonatal immunisation of bull calves against a novel gonadotrophin-releasing hormone (GnRH) construct, comprised of GnRH coupled to the glycoprotein D subunit of the bovine herpes virus-1 (GnRH–BHV1 gD), on endocrine status, reproductive organ development and carcass quality. Eighteen bull calves received either GnRH construct (n = 9) or saline (control; n = 9) at 2, 6 and 13.5 weeks of age. Blood samples were taken to determine antibody titres against GnRH, FSH and testosterone (T) concentrations and LH pulse characteristics, with testicular circumference monitored monthly. Immunisation reduced LH pulse amplitude (P < 0.05) and T concentrations (P < 0.05), particularly at the peak in anti-GnRH titres after the second booster at 16 weeks of age (P < 0.001), but not when titres fell. Despite antibody titres decreasing after 16 weeks, immunisation reduced testicular size between 16 to 57 weeks of age (P < 0.05), provoking an 8-week delay in puberty onset, defined as testicular circumference ≥14 cm. In conclusion, neonatal immunisation induced a significant immune response against GnRH, provoking a temporary endocrine disturbance that had a long-term effect on testicular development, delaying the onset of puberty. These results support the hypothesis that a developmental window exists during testicular development, such that disturbance of the endocrine drive to the gonads during this period results in a longer-term impairment of gonadal function.
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15
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Wang X, Mozhui K, Li Z, Mulligan MK, Ingels JF, Zhou X, Hori RT, Chen H, Cook MN, Williams RW, Lu L. A promoter polymorphism in the Per3 gene is associated with alcohol and stress response. Transl Psychiatry 2012; 2:e73. [PMID: 22832735 PMCID: PMC3309544 DOI: 10.1038/tp.2011.71] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
The period homolog genes Per1, Per2 and Per3 are important components of the circadian clock system. In addition to their role in maintaining circadian rhythm, these genes have been linked to mood disorders, stress response and vulnerability to addiction and alcoholism. In this study, we combined high-resolution sequence analysis and quantitative trait locus (QTL) mapping of gene expression and behavioral traits to identify Per3 as a compelling candidate for the interaction between circadian rhythm, alcohol and stress response. In the BXD family of mouse strains, sequence variants in Per3 have marked effects on steady-state mRNA and protein levels. As a result, the transcript maps as a cis-acting expression QTL (eQTL). We found that an insertion/deletion (indel) variant in a putative stress response element in the promoter region of Per3 causes local control of transcript abundance. This indel results in differences in protein binding affinities between the two alleles through the Nrf2 transcriptional activator. Variation in Per3 is also associated with downstream differences in the expression of genes involved in circadian rhythm, alcohol, stress response and schizophrenia. We found that the Per3 locus is linked to stress/anxiety traits, and that the basal expression of Per3 is also correlated with several anxiety and addiction-related phenotypes. Treatment with alcohol results in increased expression of Per3 in the hippocampus, and this effect interacts with acute restraint stress. Our data provide strong evidence that variation in the Per3 transcript is causally associated with and also responsive to stress and alcohol.
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Affiliation(s)
- X Wang
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - K Mozhui
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Z Li
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - M K Mulligan
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - J F Ingels
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - X Zhou
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - R T Hori
- Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, TN, USA
| | - H Chen
- Department of Pharmacology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - M N Cook
- Department of Psychology, University of Memphis, Memphis, TN, USA
| | - R W Williams
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - L Lu
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN, USA,Jiangsu Ley Laboratory of Neuroregeneration, Nantong University, Nantong, China,Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, 855 Monroe Avenue, Memphis, TN 38163, USA. E-mail:
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Rapoport B, Williams RW, Chen CR, McLachlan SM. Immunoglobulin heavy chain variable region genes contribute to the induction of thyroid-stimulating antibodies in recombinant inbred mice. Genes Immun 2010; 11:254-63. [PMID: 20407472 PMCID: PMC4108286 DOI: 10.1038/gene.2010.8] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Graves' hyperthyroidism is an autoimmune disease occurring spontaneously in humans and caused by autoantibodies that stimulate the thyrotropin receptor. In mice, inducing Graves'-like hyperthyroidism requires in vivo expression of the thyrotropin receptor using plasmid or adenovirus vectors. However, mice with different genetic backgrounds vary markedly in their susceptibility to induced hyperthyroidism. Further, in some strains major disparities exist between the induction of hyperthyroidism and detection of thyroid-stimulating antibodies. To break tolerance, virtually all Graves' mouse models involve immunization with human thyrotropin-receptor DNA and the standard thyroid-stimulating antibody bioassay uses cells expressing the human thyrotropin receptor. We hypothesized, and now report, that disparities between hyperthyroidism and thyroid-stimulating antibody bioactivity are explained, at least in part, by differential antibody recognition of the human vs the mouse thyrotropin receptor. The genetic basis for these species differences was explored using genotyped, recombinant-inbred mouse strains. We report that loci in the immunoglobulin heavy chain variable region as well as in the major histocompatibility complex region contribute in a strain-specific manner to the development of antibodies specific for the human or the mouse thyrotropin receptor. The novel finding of a role for immunoglobulin heavy chain variable region gene involvement in thyroid-stimulating antibody epitopic specificity provides potential insight into genetic susceptibility in human Graves' disease.
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Affiliation(s)
- B Rapoport
- Cedars-Sinai Research Institute and UCLA School of Medicine, Los Angeles, CA 90048, USA
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Williams RW, Dunker AK, Peticolas WL. A NEW METHOD FOR DETERMINING PROTEIN SECONDARY STRUCTURE BY LASER RAMAN SPECTROSCOPY APPLIED TO fd PHAGE. Biophys J 2010; 32:232-4. [PMID: 19431366 DOI: 10.1016/s0006-3495(80)84944-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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Yager P, Chang EL, Williams RW, Dalziel AW. The secondary structure of acetylcholine receptor reconstituted in a single lipid component as determined by Raman spectroscopy. Biophys J 2010; 45:26-8. [PMID: 19431551 DOI: 10.1016/s0006-3495(84)84095-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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Gadhia K, Rehman K, Williams RW, Sharp I. Traumatic pseudolipoma: herniation of buccal fat pad, a report of two cases. Int J Oral Maxillofac Surg 2009; 38:694-6. [PMID: 19179045 DOI: 10.1016/j.ijom.2008.12.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2008] [Revised: 07/05/2008] [Accepted: 12/22/2008] [Indexed: 12/16/2022]
Abstract
Traumatic pseudolipoma is a term used to describe intra-oral herniation of the buccal fat pad. A tear of the buccinator muscle and buccal mucosa allows the buccal fat pad to extrude into the oral cavity. Initially, the lesion can suggest a more sinister cause, but a history of trauma, an absence of mass before the accident, anatomical site and fatty appearance should suggest a diagnosis of traumatic herniation of buccal fat pad. This injury is rare, but two cases presented to the authors' hospital over a period of 3 months.
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Affiliation(s)
- K Gadhia
- Birmingham Children's Hospital, Birmingham, United Kingdom.
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Martinelli RE, Hamilton TF, Williams RW, Kehl SR. Separation of uranium and plutonium isotopes for measurement by multi collector inductively coupled plasma mass spectroscopy. J Radioanal Nucl Chem 2009. [DOI: 10.1007/s10967-009-0150-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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Abstract
The mammalian genome contains a large layer of hidden biological information. High-throughput methods have provided new insights into the regulatory networks that orchestrate the "when, where and how" of gene expression, revealing a complex interplay between proteins, regulatory RNAs, and chemical and structural alterations of the genome itself. Naturally occurring antisense transcription has been considered as an important feature in creating transcriptional and hence cellular and organismal complexity. Here, we review the current understanding of the extent, functions and significance of antisense transcription. We critically discuss results from genome-wide studies and documented examples of individual antisense transcripts. So far, the regulatory potential of gene overlaps has been demonstrated only in a few selected cases of experimentally characterized antisense transcripts. Facing the large-scale antisense transcription observed in eukaryotic genomes, it still remains an open challenge to distinguish transcriptional noise from biological function of gene overlapping patterns.
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Affiliation(s)
- T Beiter
- Molecular Biology Lab, Medical Clinic, Department of Sports Medicine, University of Tuebingen, Wilhelmstr. 31, 72074 Tuebingen, Germany.
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Badea A, Johnson GA, Williams RW. Genetic dissection of the mouse brain using high-field magnetic resonance microscopy. Neuroimage 2009; 45:1067-79. [PMID: 19349225 DOI: 10.1016/j.neuroimage.2009.01.021] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2008] [Revised: 12/05/2008] [Accepted: 01/12/2009] [Indexed: 10/21/2022] Open
Abstract
Magnetic resonance (MR) imaging has demonstrated that variation in brain structure is associated with differences in behavior and disease state. However, it has rarely been practical to prospectively test causal models that link anatomical and functional differences in humans. In the present study we have combined classical mouse genetics with high-field MR to systematically explore and test such structure-functional relations across multiple brain regions. We segmented 33 regions in two parental strains-C57BL/6J (B) and DBA/2J (D)-and in nine BXD recombinant inbred strains. All strains have been studied extensively for more than 20 years using a battery of genetic, functional, anatomical, and behavioral assays. We compared levels of variation within and between strains and sexes, by region, and by system. Average within-strain variation had a coefficient of variation (CV) of 1.6% for the whole brain; while the CV ranged from 2.3 to 3.6% for olfactory bulbs, cortex and cerebellum, and up to approximately 18% for septum and laterodorsal thalamic nucleus. Variation among strain averages ranged from 6.7% for cerebellum, 7.6% for whole brain, 9.0% for cortex, up to approximately 26% for the ventricles, laterodorsal thalamic nucleus, and the interpeduncular nucleus. Heritabilities averaged 0.60+/-0.18. Sex differences were not significant with the possible (and unexpected) exception of the pons ( approximately 20% larger in males). A correlation matrix of regional volumes revealed high correlations among functionally related parts of the CNS (e.g., components of the limbic system), and several high correlations between regions that are not anatomically connected, but that may nonetheless be functionally or genetically coupled.
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Affiliation(s)
- A Badea
- Center for In Vivo Microscopy, Box 3302 Duke University Medical Center, Durham, NC 27710, USA
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Rosen GD, Pung CJ, Owens CB, Caplow J, Kim H, Mozhui K, Lu L, Williams RW. Genetic modulation of striatal volume by loci on Chrs 6 and 17 in BXD recombinant inbred mice. Genes Brain Behav 2009; 8:296-308. [PMID: 19191878 DOI: 10.1111/j.1601-183x.2009.00473.x] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Natural variation in the absolute and relative size of different parts of the human brain is substantial, with a range that often exceeds a factor of 2. Much of this variation is generated by the cumulative effects of sets of unknown gene variants that modulate the proliferation, growth and death of neurons and glial cells. Discovering and testing the functions of these genes should contribute significantly to our understanding of differences in brain development, behavior and disease susceptibility. We have exploited a large population of genetically well-characterized strains of mice (BXD recombinant inbred strains) to map gene variants that influence the volume of the dorsal striatum (caudate-putamen without nucleus accumbens). We used unbiased methods to estimate volumes bilaterally in a sex-balanced sample taken from the Mouse Brain Library (www.mbl.org). We generated a matched microarray data set to efficiently evaluate candidate genes (www.genenetwork.org). As in humans, volume of the striatum is highly heritable, with greater than twofold differences among strains. We mapped a locus that modulates striatal volume on chromosome (Chr) 6 at 88 +/- 5 Mb. We also uncovered an epistatic interaction between loci on Chr 6 and Chr 17 that modulates striatal volume. Using bioinformatic tools and the corresponding expression database, we have identified positional candidates in these quantitative trait locus intervals.
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Affiliation(s)
- G D Rosen
- Division of Behavioral Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA.
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Mulligan MK, Ponomarev I, Boehm SL, Owen JA, Levin PS, Berman AE, Blednov YA, Crabbe JC, Williams RW, Miles MF, Bergeson SE. Alcohol trait and transcriptional genomic analysis of C57BL/6 substrains. Genes, Brain and Behavior 2008; 7:677-89. [DOI: 10.1111/j.1601-183x.2008.00405.x] [Citation(s) in RCA: 63] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Boschma SP, Williams RW. Using morphological traits to identify persistent lucernes for dryland agriculture in NSW, Australia. ACTA ACUST UNITED AC 2008. [DOI: 10.1071/ar06206] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
This paper reports on several studies conducted to better understand the variability between lucerne cultivars and lines, and use this to predict persistence in dryland grazing pastures in eastern Australia. Morphological traits of 20 cultivars/lines were measured in irrigated and dryland spaced plant experiments. Studies were also conducted to describe variation among lucernes in their utilisation of starch and responses to water deficit, pests and diseases. Multiple regression analyses were used to develop simple models where the measured traits could be used to predict persistence of lucerne lines in dryland evaluation experiments.
Although there was significant variation among cultivars/lines in most measured traits, no single trait reliably predicted persistence of cultivars/lines in dryland evaluation experiments. However, variation in persistence at both sites could be explained by models developed by multiple regression using differences in the mean lengths of the longest stems at 10% flower in summer and winter. Persistent lucernes were those that had relatively long stems in summer and short stems in winter. Water use efficiencies, starch utilisation patterns and resistances to pests and diseases of different lucernes provided some improvement to this simple model, but these improvements were not consistent.
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Aziz RK, Kansal R, Abdeltawab NF, Rowe SL, Su Y, Carrigan D, Nooh MM, Attia RR, Brannen C, Gardner LA, Lu L, Williams RW, Kotb M. Susceptibility to severe Streptococcal sepsis: use of a large set of isogenic mouse lines to study genetic and environmental factors. Genes Immun 2007; 8:404-15. [PMID: 17525705 DOI: 10.1038/sj.gene.6364402] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Variation in responses to pathogens is influenced by exposure history, environment and the host's genetic status. We recently demonstrated that human leukocyte antigen class II allelic differences are a major determinant of the severity of invasive group A streptococcal (GAS) sepsis in humans. While in-depth controlled molecular studies on populations of genetically well-characterized humans are not feasible, it is now possible to exploit genetically diverse panels of recombinant inbred BXD mice to define genetic and environmental risk factors. Our goal in this study was to standardize the model and identify genetic and nongenetic covariates influencing invasive infection outcomes. Despite having common ancestors, the various BXD strains (n strains=33, n individuals=445) showed marked differences in survival. Mice from all strains developed bacteremia but exhibited considerable differences in disease severity, bacterial dissemination and mortality rates. Bacteremia and survival showed the expected negative correlation. Among nongenetic factors, age -- but not sex or weight -- was a significant predictor of survival (P=0.0005). To minimize nongenetic variability, we limited further analyses to mice aged 40-120 days and calculated a corrected relative survival index that reflects the number of days an animal survived post-infection normalized to all significant covariates. Genetic background (strain) was the most significant factor determining susceptibility (P< or =0.0001), thus underscoring the strong effect of host genetic variation in determining susceptibility to severe GAS sepsis. This model offers powerful unbiased forward genetics to map specific quantitative trait loci and networks of pathways modulating the severity of GAS sepsis.
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Affiliation(s)
- R K Aziz
- Department of Microbiology and Immunology, Faculty of Pharmacy, Cairo University, Cairo, Egypt
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Dong H, Martin MV, Colvin J, Ali Z, Wang L, Lu L, Williams RW, Rosen GD, Csernansky JG, Cheverud JM. Quantitative trait loci linked to thalamus and cortex gray matter volumes in BXD recombinant inbred mice. Heredity (Edinb) 2007; 99:62-9. [PMID: 17406662 PMCID: PMC4465230 DOI: 10.1038/sj.hdy.6800965] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
To investigate whether there are separate or shared genetic influences on the development of the thalamus and cerebral cortex, we identified quantitative trait loci (QTLs) for relevant structural volumes in BXD recombinant inbred (RI) strains of mice. In 34 BXD RI strains and two parental strains (C57BL/6J and DBA/2J), we measured the volumes of the entire thalamus and cortex gray matter using point counting and Cavalieri's rule. Heritability was calculated using analysis of variance (ANOVA), and QTL analysis was carried out using WebQTL (http://www.genenetwork.org). The heritability of thalamus volume was 36%, and three suggestive QTLs for thalamus volume were identified on chromosomes 10, 11 and 16. The heritability of cortical gray matter was 43%, and four suggestive QTLs for cortex gray matter volume were identified on chromosomes 2, 8, 16 and 19. The genetic correlation between thalamus and cortex gray matter volumes was 0.64. Also, a single QTL on chromosome 16 (D16Mit100) was identified for thalamus volume, cortex gray matter volume and Morris water maze search-time preference (r=0.71). These results suggest that there are separate and shared genetic influences on the development of the thalamus and cerebral cortex.
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Affiliation(s)
- H Dong
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA.
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Abstract
Since the introduction of the 14-day rule for referrals for cancer in 1999 there has been some suspicion that rates of detection of cancer are low and the number of inappropriate referrals is high. We undertook a prospective study of 150 consecutive patients with oral lesions referred to a department of oral and maxillofacial surgery in a teaching hospital that uses a "two week wait" fast-track referral system for head and neck cancers. The main outcome measures were the number of cancers detected, the age and sex of the patients, the number seen within 2 weeks, by whom, and the final diagnosis. Most patients (n=120, 80%) were referred with oral ulceration. All patients were seen within 2 weeks (mean 6 days). Nine patients (6%) had a diagnosis of malignancy and 17 (11%) had no detectable abnormality. The study confirms what others have shown, that the yield of diagnoses of malignant disease from fast-track referrals is low and the number of non-urgent referrals is high.
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Affiliation(s)
- H V Shah
- Department of Oral and Maxillofacial Surgery, Southmead Hospital, Southmead, Bristol BS10 5NB, UK.
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Hawken RMA, Williams RW, Bridger MWM, Lyons CBA, Jackson SA. Puncture-site metastasis in a radiologically inserted gastrostomy tube: case report and literature review. Cardiovasc Intervent Radiol 2005; 28:377-80. [PMID: 15886946 DOI: 10.1007/s00270-004-0106-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Gastrostomy-site metastases from head and neck cancer have been reported numerous times following endoscopic insertion, with direct implantation being implicated. We present the first reported case of gastrostomy-site metastasis following radiological insertion, and discuss the mechanisms by which this may have occurred. These include: direct implantation, hematogenous dissemination, or the natural shedding of tumor cells into the gastrointestinal tract.
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Affiliation(s)
- R M A Hawken
- Department of ENT Surgery, Derriford Hospital, Plymouth, Devon, UK
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Abstract
MOTIVATION Dissection of the genetics underlying gene expression utilizes techniques from microarray analyses as well as quantitative trait loci (QTL) mapping. Available QLT mapping methods are not tailored for the highly automated analyses required to deal with the thousand of gene transcripts encountered in the mapping of QTL affecting gene expression (sometimes referred to as eQTL). This report focuses on the adaptation of QTL mapping methodology to perform automated mapping of QTL affecting gene expression. RESULTS The analyses of expression data on > 12,000 gene transcripts in BXD recombinant inbred mice found, on average, 629 QTL exceeding the genome-wide 5% threshold. Using additional information on trait repeatabilities and QTL location, 168 of these were classified as 'high confidence' QTL. Current sample sizes of genetical genomics studies make it possible to detect a reasonable number of QTL using simple genetic models, but considerably larger studies are needed to evaluate more complex genetic models. After extensive analyses of real data and additional simulated data (altogether > 300,000 genome scans) we make the following recommendations for detection of QTL for gene expression: (1) For populations with an unbalanced number of replicates on each genotype, weighted least squares should be preferred above ordinary least squares. Weights can be based on repeatability of the trait and the number of replicates. (2) A genome scan based on multiple marker information but analysing only at marker locations is a good approximation to a full interval mapping procedure. (3) Significance testing should be based on empirical genome-wide significance thresholds that are derived for each trait separately. (4) The significant QTL can be separated into high and low confidence QTL using a false discovery rate that incorporates prior information such as transcript repeatabilities and co-localization of gene-transcripts and QTL. (5) Including observations on the founder lines in the QTL analysis should be avoided as it inflates the test statistic and increases the Type I error. (6) To increase the computational efficiency of the study, use of parallel computing is advised. These recommendations are summarized in a possible strategy for mapping of QTL in a least squares framework. AVAILABILITY The software used for this study is available on request from the authors.
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Affiliation(s)
- O Carlborg
- Roslin Institute, Roslin, Midlothian EH25 9 PS, UK
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Mountz JD, Yang P, Wu Q, Zhou J, Tousson A, Fitzgerald A, Allen J, Wang X, Cartner S, Grizzle WE, Yi N, Lu L, Williams RW, Hsu HC. Genetic segregation of spontaneous erosive arthritis and generalized autoimmune disease in the BXD2 recombinant inbred strain of mice. Scand J Immunol 2005; 61:128-38. [PMID: 15683449 DOI: 10.1111/j.0300-9475.2005.01548.x] [Citation(s) in RCA: 50] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The BXD2 strain of mice is one of approximately 80 BXD recombinant inbred (RI) mouse strains derived from an intercross between C57BL/6J (B6) and DBA/2J (D2) strains. We have discovered that adult BXD2 mice spontaneously develop generalized autoimmune disease, including glomerulonephritis (GN), increased serum titres of rheumatoid factor (RF) and anti-DNA antibody, and a spontaneous erosive arthritis characterized by mononuclear cell infiltration, synovial hyperplasia, and bone and cartilage erosion. The features of lupus and arthritis developed by the BXD2 mice segregate in F2 mice generated by crossing BXD2 mice with the parental B6 and D2 strains. Genetic linkage analysis of the serum levels of anti-DNA and RF by using the BXD RI strains shows that the serum titers of anti-DNA and RF were influenced by a genetic locus on mouse chromosome (Chr) 2 near the marker D2Mit412 (78 cm, 163 Mb) and on Chr 4 near D4Mit146 (53.6 cm, 109 Mb), respectively. Both loci are close to the B-cell hyperactivity, lupus or GN susceptibility loci that have been identified previously. The results of our study suggest that the BXD2 strain of mice is a novel model for complex autoimmune disease that will be useful in identifying the mechanisms critical for the immunopathogenesis and genetic segregation of lupus and erosive arthritis.
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Affiliation(s)
- J D Mountz
- Department of Medicine, Division of Clinical Immunology and Rheumatology, the University of Alabama at Birmingham, AL 35294, USA
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Ponomarev I, Schafer GL, Blednov YA, Williams RW, Iyer VR, Harris RA. Convergent analysis of cDNA and short oligomer microarrays, mouse null mutants and bioinformatics resources to study complex traits. Genes Brain Behav 2005; 3:360-8. [PMID: 15544578 DOI: 10.1111/j.1601-183x.2004.00088.x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Abstract
Gene expression data sets have recently been exploited to study genetic factors that modulate complex traits. However, it has been challenging to establish a direct link between variation in patterns of gene expression and variation in higher order traits such as neuropharmacological responses and patterns of behavior. Here we illustrate an approach that combines gene expression data with new bioinformatics resources to discover genes that potentially modulate behavior. We have exploited three complementary genetic models to obtain convergent evidence that differential expression of a subset of genes and molecular pathways influences ethanol-induced conditioned taste aversion (CTA). As a first step, cDNA microarrays were used to compare gene expression profiles of two null mutant mouse lines with difference in ethanol-induced aversion. Mice lacking a functional copy of G protein-gated potassium channel subunit 2 (Girk2) show a decrease in the aversive effects of ethanol, whereas preproenkephalin (Penk) null mutant mice show the opposite response. We hypothesize that these behavioral differences are generated in part by alterations in expression downstream of the null alleles. We then exploited the WebQTL databases to examine the genetic covariance between mRNA expression levels and measurements of ethanol-induced CTA in BXD recombinant inbred (RI) strains. Finally, we identified a subset of genes and functional groups associated with ethanol-induced CTA in both null mutant lines and BXD RI strains. Collectively, these approaches highlight the phosphatidylinositol signaling pathway and identify several genes including protein kinase C beta isoform and preproenkephalin in regulation of ethanol- induced conditioned taste aversion. Our results point to the increasing potential of the convergent approach and biological databases to investigate genetic mechanisms of complex traits.
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Affiliation(s)
- I Ponomarev
- Waggoner Center for Alcohol and Addiction Research, The University of Texas at Austin, Austin, TX, USA.
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Williams RW, Travess HC, Williams AC. Patients’ experiences after undergoing orthognathic surgery at NHS hospitals in the south west of England. Br J Oral Maxillofac Surg 2004; 42:419-31. [PMID: 15336767 DOI: 10.1016/j.bjoms.2004.05.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/18/2004] [Indexed: 11/18/2022]
Abstract
Patients are being increasingly involved in assessing the quality of care that they receive in the NHS. Our aim was to undertake a retrospective postal survey to evaluate their perception of the delivery of orthognathic surgery in the south west of the United Kingdom (UK) using a patient-centred measure. A total of 327 patients (53% response rate) participated. Although most participants (n = 249, 76%) reported that they were well-informed about what to expect during treatment, many reported that the symptoms of pain, swelling, or difficulty in eating that they experienced immediately post-operatively were worse than expected. A third also reported that it took them longer to recover from the operation than they had anticipated. Patients undergoing orthognathic surgery in the south west of the UK need more specific information about what to expect both immediately post-operatively and at home after discharge.
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Affiliation(s)
- R W Williams
- Division of Child Dental Health, University of Bristol Dental Hospital, Lower Maudlin Street, Bristol BS1 2LY, UK.
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Tan XL, Zhou Y, Cai KF, Shao YX, Zhu SX, Lu L, Williams RW, Gu XS. Identification of QTLs for weight and cross-sectional area on cervical enlargement of spinal cord in mice. Yi Chuan Xue Bao 2004; 31:801-6. [PMID: 15481534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
Two inbred strains of mice, A/J, C57BL/6J and F2 intercross progenies,were used for QTL mapping for weight and cross-sectional area on cervical enlargement of spinal cord in mice. 13 QTLs located on Chromosome 2, 4, 8, 14, 15, 17, 18, 19 and X, respectively, for these two traits were found. Six QTLs were responsible for the cord weight, four for the cross-sectional area and three for both. Among 13 QTLs, three QTLs (P < 0.01) termed SC1 (located near D15Mit158) ,SC2 (DXMit140) and SC3 (DXMit64) accounted for 24%, 19% and 15% of the total variance in weight phenotype, and -3.78, 3.41 and 2.06 mg additive effect, respectively. The P value of other QTLs is between 0.01 and 0.05. SC1 is only one QTL that responsible for both weight and cross-sectional area in three QTLs above. This study revealed the location of major QTLs related size of spinal cord in mice, and may be helpful in fine mapping and ultimate identification of candidate genes.
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Affiliation(s)
- Xiang-Ling Tan
- Key Laboratory of Nerve Regeneration in Jiangsu Province, Nantong Medical College, Nantong 226001 China.
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Hsu HC, Zhang HG, Li L, Yi N, Yang PA, Wu Q, Zhou J, Sun S, Xu X, Yang X, Lu L, Van Zant G, Williams RW, Allison DB, Mountz JD. Age-related thymic involution in C57BL/6J x DBA/2J recombinant-inbred mice maps to mouse chromosomes 9 and 10. Genes Immun 2003; 4:402-10. [PMID: 12944977 DOI: 10.1038/sj.gene.6363982] [Citation(s) in RCA: 44] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
A comprehensive analysis of initial thymus size and involution rate has not been quantitated for different genetic backgrounds of mice, thus genetic linkage analysis of thymic involution has not been possible. Here, we have used a mathematical method to analyze the age-related decline in thymocyte count in C57BL/6 and DBA/2 mice and have observed that thymic involution could be best fit with a negative exponential curve N(t)=beta(0) x exp(-beta(1)t), where t represents the age (day). This regression model was applied to C57BL/6 x DBA/2 (B x D) recombinant inbred strains of mice to identify the genetic loci influencing age-related thymic involution. There was a dramatic genetic effect of B and D alleles on thymocyte count at young age and the age-related thymic involution rate. The strongest quantitative trait loci (QTL) influencing the rate of thymic involution were mapped to mouse chromosome (Chr) 9 (D9Mit20 at 62 cM) and Chr 10 (D10Mit61 at 32 cM). The strongest QTLs influencing the initial thymocyte count were mapped to ChrX (DXMit324 at 26.5 cM) and Chr 3 (D3Mit127 at 70.3 cM). The present study suggests that the initial thymus size and the rate of thymic involution may be influenced by a relatively small number of genetic loci.
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Affiliation(s)
- H-C Hsu
- Department of Medicine, Division of Clinical Immunology and Rheumatology, The University of Alabama at Birmingham, Birmingham, AL, USA
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Abstract
More than ten large-scale mutagenesis projects are now generating hundreds of novel mouse mutants. Projects employ a wide variety of strategies and screens: targeting as much as the whole genome, part of a chromosome or just single genes. In this commentary, we consider the pros and cons of different tactics. We highlight issues of cost, efficiency and defend the impact of this mutagenesis program in an era of sophisticated conditional knockouts and advanced transgenic lines. Given the significant difficulties of adequately phenotyping and mapping randomly generated mutations that cover the whole genome, we tend to favor regional and gene-targeted screens. Whatever the choice of method, whole genome sequence data combined with detailed transcriptome and proteome surveys promise to significantly improve the efficiency with which series of mutations in a large subset of mammalian genes can be generated and cloned.
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Affiliation(s)
- R W Williams
- Center for Genomics and Bioinformatics, University of Tennessee Health Science Center, Madison Avenue, Memphis, TN 38163, USA.
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Peirce JL, Chesler EJ, Williams RW, Lu L. Genetic architecture of the mouse hippocampus: identification of gene loci with selective regional effects. Genes Brain Behav 2003; 2:238-52. [PMID: 12953790 DOI: 10.1034/j.1601-183x.2003.00030.x] [Citation(s) in RCA: 65] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
We recently mapped two quantitative trait loci that have widespread effects on hippocampal architecture in mouse: Hipp1a and Hipp5a. We also noted remarkable strain differences in the relative sizes of different hippocampal regions. Estimated heritable variation for these differences was 42% in hippocampus proper, 40% in dentate gyrus, 31% in granule cell layer and 18% in pyramidal cell layer. Region size varied at least 50% from largest to smallest measurement. Here we have utilized these differences to identify loci with effects on the dentate gyrus, granule cell layer, hippocampus proper and pyramidal cell layer. Our sample consists of C57BL/6J and DBA/2J and 32 BXD recombinant inbred strains. Volumetric data were corrected for shrinkage and for differences in brain weight. We identified significant loci on chromosomes (Chr) 6, 13 and 15, and a significant interaction locus on proximal Chr 11. A suggestive distal Chr 1 locus overlaps with Hipp1a. HipV13a (Chr 13, 42-78Mb) has an additive effect of 0.56 mm3 (12.1%) on dentate gyrus volume, while GrV6a (Chr 6, 29-65 Mb) has additive effects of 0.14 mm3 (16.0%) on the volume of the granule cell layer. HipV13a also interacts with DGVi11a, a locus on proximal Chr 11 that operates exclusively through its epistatic effect on HipV13a and has no independent main effect HipV15a (Chr 15, 0-51 Mb) has an additive effect of 1.76 mm3 (9.0%) on the volume of the hippocampus proper. We used WebOTL, a recently described web-based tool, to examine genetic correlation of gene expression with hippocampal volume. We identified a number of genes that map within the OTL intervals and have highly correlated expression patterns. Using WebQTL's extensive database of published BXD phenotypes, we also detected a strong and potentially biologically meaningful correlation between hippocampal volume and the acoustic startle response.
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Affiliation(s)
- J L Peirce
- Center for Neuroscience, Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Monroe Avenue, Memphis, Tennessee 38163, USA
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Williams RW. Hot saltwater mouth baths. Br Dent J 2003; 194:584. [PMID: 12819669 DOI: 10.1038/sj.bdj.4810228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Denton GD, Williams RW, Pangaro L. Core problems reported by students in a palm OS and Internet-based problem entry system predicts performance on the third-year internal medicine clerkship. AMIA Annu Symp Proc 2003; 2003:827. [PMID: 14728332 PMCID: PMC1480291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
CWeblog is a web and palm OS-based system used by medical students to record the problems and diagnoses of patients encountered in third-year clerkships at the Uniformed Services University. Data is available for analysis by clerkship directors as soon as it is entered. A pretest is given on the first day of the internal medicine third-year clerkship (the clerkship), and the National Board of Medical Examiners shelf examination (NBME) is given during the final twelfth week. Internal medicine specialty societies publish a list of 20 core problems in internal medicine to be emphasized during the third-year clerkship.
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Affiliation(s)
- G D Denton
- Uniformed Services University of the Health Sciences
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Williams RW, Teeter MM. Raman spectroscopy of homologous plant toxins: crambin and .alpha.1- and .beta.-purothionin secondary structures, disulfide conformation, and tyrosine environment. Biochemistry 2002; 23:6796-802. [PMID: 6549379 DOI: 10.1021/bi00321a080] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The Raman spectrum of crambin crystals is different from the spectrum of crambin in solution. The amide I spectrum of crambin in solution is not different from the solution spectra of proteins homologous (greater than 40%) with crambin, alpha 1- and beta-purothionins. We have two interpretations of these results. One is that helical segments in crambin and the purothionins in solution are more irregular than those in crystalline crambin. Comparative analyses of amide I and amide III spectra, and of the conformational preferences of the amino acid sequences of these proteins, are consistent with this interpretation. The other is that, due to the way helical segments in crambin are stacked end on end along the same axis in the crystal, transition dipole coupling along the axis of these extended helixes enhances the amide I intensity of helical residues. On the basis of a combined Raman and sequence conformational analysis, we propose that the structure of the purothionins is the same as that of crambin in solution and that residues 7-12 in crystalline crambin are somewhat more regular and ordered than they are in solutions.
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Williams RW, Dubnau J, Enoch MA, Flaherty L, Sluyter F, Gannon KS, Maxson SC, Riedl CAL, Williams KD, Holmes A, Bolivar VJ, Crusio WE. Hot topics in behavioral and neural genetics. Genes Brain Behav 2002; 1:117-30. [PMID: 12884982 DOI: 10.1034/j.1601-183x.2002.10207.x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- R W Williams
- Center of Genomics and Bioinformatics, University of Tennessee, Health Science Center Memphis, TN, USA
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Stalcup H, Fauth MI, Watts JO, Williams RW. Reduction of Nitroglycerin by Catalytic Hydrogenolysis in Analysis of Propellants for Dioctyl Phthalate. Anal Chem 2002. [DOI: 10.1021/ac60130a025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Zhou G, Strom RC, Giguere V, Williams RW. Modulation of retinal cell populations and eye size in retinoic acid receptor knockout mice. Mol Vis 2001; 7:253-60. [PMID: 11723443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023] Open
Abstract
PURPOSE The retinoic acid receptors are expressed from early stages of development in the diverse tissues that make up the vertebrate eye. Their loss has subtle effects on eye development. We adapted sensitive quantitative trait locus (QTL) mapping methods to assess consequences of inactivating alleles of the alpha and beta receptors, Rara and Rarb, on eye and retinal development. Rara is of particular interest because this gene is a candidate for Nnc1, a QTL that controls retinal ganglion cell proliferation. METHODS We studied lines of mice in which expression of the a1 isoform of Rara or all isoforms of Rarb had been disrupted by gene targeting. We measured eye weight, lens weight, retinal area, and retinal ganglion cell number in each of six genotypes (Rara and Rarb -/-, +/-, +/+; 10-25 cases/genotype). RESULTS Loss of either protein is associated with a small but significant loss of eye weight and retinal area. However, only the Rarb knockout has a significant effect on the ganglion cell population and the loss of both wildtype alleles leads to an 8,000 cell deficit. Surprisingly, loss of the Rara a1 isoform that is expressed in this cell population from early stages has no effect on number. Null alleles of both genes have little if any effect on lens growth. CONCLUSIONS Despite its expression in embryonic retina, Rara is unlikely to be the Nnc1 QTL. In contrast, Rarb, a gene that maps to Chr 14 and which is not an Nnc1 candidate gene, has a significant effect on cell number and is therefore a QTL controlling this key population. This raises the intriguing possibility that normal allelic variants of Rarb modulate the ganglion cell population in other vertebrates, including humans.
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Affiliation(s)
- G Zhou
- Center for Neuroscience, University of Tennessee, Memphis, TN 38163, USA.
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Gabriel J, Williams RW, Courtney DJ. Unusual presentation of multiple sclerosis. Br Dent J 2001; 191:477. [PMID: 11726058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
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