1
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Schäfer A, Gralinski LE, Leist SR, Hampton BK, Mooney MA, Jensen KL, Graham RL, Agnihothram S, Jeng S, Chamberlin S, Bell TA, Scobey DT, Linnertz CL, VanBlargan LA, Thackray LB, Hock P, Miller DR, Shaw GD, Diamond MS, de Villena FPM, McWeeney SK, Heise MT, Menachery VD, Ferris MT, Baric RS. Genetic loci regulate Sarbecovirus pathogenesis: A comparison across mice and humans. Virus Res 2024; 344:199357. [PMID: 38508400 PMCID: PMC10981091 DOI: 10.1016/j.virusres.2024.199357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 02/15/2024] [Accepted: 03/16/2024] [Indexed: 03/22/2024]
Abstract
Coronavirus (CoV) cause considerable morbidity and mortality in humans and other mammals, as evidenced by the emergence of Severe Acute Respiratory CoV (SARS-CoV) in 2003, Middle East Respiratory CoV (MERS-CoV) in 2012, and SARS-CoV-2 in 2019. Although poorly characterized, natural genetic variation in human and other mammals modulate virus pathogenesis, as reflected by the spectrum of clinical outcomes ranging from asymptomatic infections to lethal disease. Using multiple human epidemic and zoonotic Sarbecoviruses, coupled with murine Collaborative Cross genetic reference populations, we identify several dozen quantitative trait loci that regulate SARS-like group-2B CoV pathogenesis and replication. Under a Chr4 QTL, we deleted a candidate interferon stimulated gene, Trim14 which resulted in enhanced SARS-CoV titers and clinical disease, suggesting an antiviral role during infection. Importantly, about 60 % of the murine QTL encode susceptibility genes identified as priority candidates from human genome-wide association studies (GWAS) studies after SARS-CoV-2 infection, suggesting that similar selective forces have targeted analogous genes and pathways to regulate Sarbecovirus disease across diverse mammalian hosts. These studies provide an experimental platform in rodents to investigate the molecular-genetic mechanisms by which potential cross mammalian susceptibility loci and genes regulate type-specific and cross-SARS-like group 2B CoV replication, immunity, and pathogenesis in rodent models. Our study also provides a paradigm for identifying susceptibility loci for other highly heterogeneous and virulent viruses that sporadically emerge from zoonotic reservoirs to plague human and animal populations.
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Affiliation(s)
- Alexandra Schäfer
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Lisa E Gralinski
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Sarah R Leist
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brea K Hampton
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Michael A Mooney
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA; Division of Bioinformatics and Computational Biology, Oregon Health & Science University, Portland, OR, USA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Kara L Jensen
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rachel L Graham
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sudhakar Agnihothram
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sophia Jeng
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR, USA
| | - Steven Chamberlin
- Division of Bioinformatics and Computational Biology, Oregon Health & Science University, Portland, OR, USA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA
| | - Timothy A Bell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - D Trevor Scobey
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Colton L Linnertz
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Laura A VanBlargan
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Larissa B Thackray
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Pablo Hock
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Darla R Miller
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Michael S Diamond
- Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA; Department of Pathology & Immunology2, Washington University School of Medicine, St. Louis, MO, USA; Department of Molecular Microbiology3, Washington University School of Medicine, St. Louis, MO, USA
| | - Fernando Pardo Manuel de Villena
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Shannon K McWeeney
- Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA; Division of Bioinformatics and Computational Biology, Oregon Health & Science University, Portland, OR, USA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA; Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, OR, USA
| | - Mark T Heise
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Rapidly Emerging Antiviral Drug Discovery Initiative, University of North Carolina, Chapel Hill NC, USA
| | - Vineet D Menachery
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX, USA; Institute for Human Infection and Immunity, University of Texas Medical Branch, Galveston TX, USA; Department of Pathology and Center for Biodefense & Emerging Infectious Diseases, University of Texas Medical Branch, Galveston, TX, USA
| | - Martin T Ferris
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Ralph S Baric
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Rapidly Emerging Antiviral Drug Discovery Initiative, University of North Carolina, Chapel Hill NC, USA.
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2
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Schäfer A, Marzi A, Furuyama W, Catanzaro NJ, Nguyen C, Haddock E, Feldmann F, Meade-White K, Thomas T, Hubbard ML, Gully KL, Leist SR, Hock P, Bell TA, De la Cruz GE, Midkiff BR, Martinez DR, Shaw GD, Miller DR, Vernon MJ, Graham RL, Cowley DO, Montgomery SA, Schughart K, de Villena FPM, Wilkerson GK, Ferris MT, Feldmann H, Baric RS. Mapping of susceptibility loci for Ebola virus pathogenesis in mice. Cell Rep 2024; 43:114127. [PMID: 38652660 DOI: 10.1016/j.celrep.2024.114127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [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: 04/11/2023] [Revised: 03/11/2024] [Accepted: 04/03/2024] [Indexed: 04/25/2024] Open
Abstract
Ebola virus (EBOV), a major global health concern, causes severe, often fatal EBOV disease (EVD) in humans. Host genetic variation plays a critical role, yet the identity of host susceptibility loci in mammals remains unknown. Using genetic reference populations, we generate an F2 mapping cohort to identify host susceptibility loci that regulate EVD. While disease-resistant mice display minimal pathogenesis, susceptible mice display severe liver pathology consistent with EVD-like disease and transcriptional signatures associated with inflammatory and liver metabolic processes. A significant quantitative trait locus (QTL) for virus RNA load in blood is identified in chromosome (chr)8, and a severe clinical disease and mortality QTL is mapped to chr7, which includes the Trim5 locus. Using knockout mice, we validate the Trim5 locus as one potential driver of liver failure and mortality after infection. The identification of susceptibility loci provides insight into molecular genetic mechanisms regulating EVD progression and severity, potentially informing therapeutics and vaccination strategies.
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Affiliation(s)
- Alexandra Schäfer
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA.
| | - Andrea Marzi
- Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Hamilton, MT 59840, USA.
| | - Wakako Furuyama
- Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Hamilton, MT 59840, USA
| | - Nicholas J Catanzaro
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Cameron Nguyen
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Elaine Haddock
- Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Hamilton, MT 59840, USA
| | - Friederike Feldmann
- Rocky Mountain Veterinary Branch, Division of Intramural Research, NIAID, NIH, Hamilton, MT 59840, USA
| | - Kimberly Meade-White
- Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Hamilton, MT 59840, USA
| | - Tina Thomas
- Rocky Mountain Veterinary Branch, Division of Intramural Research, NIAID, NIH, Hamilton, MT 59840, USA
| | - Miranda L Hubbard
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Kendra L Gully
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Sarah R Leist
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Timothy A Bell
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Gabriela E De la Cruz
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Bentley R Midkiff
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - David R Martinez
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Darla R Miller
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Michael J Vernon
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Rachel L Graham
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Dale O Cowley
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Animal Models Core Facility, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Stephanie A Montgomery
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Klaus Schughart
- Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, TN 38163, USA; Institute of Virology, University of Muenster, 48149 Muenster, Germany
| | - Fernando Pardo Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Gregory K Wilkerson
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Martin T Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Heinz Feldmann
- Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Hamilton, MT 59840, USA
| | - Ralph S Baric
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27599, USA.
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3
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Graham JB, Swarts JL, Leist SR, Schäfer A, Bell TA, Hock P, Farrington J, Shaw GD, Ferris MT, Pardo-Manuel de Villena F, Baric RS, Lund JM. Unique immune profiles in collaborative cross mice linked to survival and viral clearance upon infection. iScience 2024; 27:109103. [PMID: 38361611 PMCID: PMC10867580 DOI: 10.1016/j.isci.2024.109103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/18/2023] [Accepted: 01/30/2024] [Indexed: 02/17/2024] Open
Abstract
The response to infection is generally heterogeneous and diverse, with some individuals remaining asymptomatic while others present with severe disease or a diverse range of symptoms. Here, we address the role of host genetics on immune phenotypes and clinical outcomes following viral infection by studying genetically diverse mice from the Collaborative Cross (CC), allowing for use of a small animal model with controlled genetic diversity while maintaining genetic replicates. We demonstrate variation by deeply profiling a broad range of innate and adaptive immune cell phenotypes at steady-state in 63 genetically distinct CC mouse strains and link baseline immune signatures with virologic and clinical disease outcomes following infection of mice with herpes simplex virus 2 (HSV-2) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This work serves as a resource for CC strain selection based on steady-state immune phenotypes or disease presentation upon viral infection, and further, points to possible pre-infection immune correlates of survival and early viral clearance upon infection.
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Affiliation(s)
- Jessica B. Graham
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jessica L. Swarts
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Sarah R. Leist
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alexandra Schäfer
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Timothy A. Bell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Pablo Hock
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joe Farrington
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ginger D. Shaw
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Martin T. Ferris
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ralph S. Baric
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jennifer M. Lund
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Global Health, University of Washington, Seattle, WA, USA
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4
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Blanchard MW, Sigmon JS, Brennan J, Ahulamibe C, Allen ME, Baric RS, Bell TA, Farrington J, Ciavatta D, Cruz Cisneros M, Drushal M, Ferris MT, Fry R, Gaines C, Gu B, Heise MT, Hodges RA, Kafri T, Lynch R, Magnuson T, Miller D, Murphy CEY, Nguyen DT, Noll KE, Proulx M, Sassetti C, Shaw GD, Simon JM, Smith C, Styblo M, Tarantino L, Woo J, Pardo Manuel de Villena F. The Updated Mouse Universal Genotyping Array Bioinformatic Pipeline Improves Genetic QC in Laboratory Mice. bioRxiv 2024:2024.02.29.582794. [PMID: 38464063 PMCID: PMC10925293 DOI: 10.1101/2024.02.29.582794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
The MiniMUGA genotyping array is a popular tool for genetic QC of laboratory mice and genotyping of samples from most types of experimental crosses involving laboratory strains, particularly for reduced complexity crosses. The content of the production version of the MiniMUGA array is fixed; however, there is the opportunity to improve array's performance and the associated report's usefulness by leveraging thousands of samples genotyped since the initial description of MiniMUGA in 2020. Here we report our efforts to update and improve marker annotation, increase the number and the reliability of the consensus genotypes for inbred strains and increase the number of constructs that can reliably be detected with MiniMUGA. In addition, we have implemented key changes in the informatics pipeline to identify and quantify the contribution of specific genetic backgrounds to the makeup of a given sample, remove arbitrary thresholds, include the Y Chromosome and mitochondrial genome in the ideogram, and improve robust detection of the presence of commercially available substrains based on diagnostic alleles. Finally, we have made changes to the layout of the report, to simplify the interpretation and completeness of the analysis and added a table summarizing the ideogram. We believe that these changes will be of general interest to the mouse research community and will be instrumental in our goal of improving the rigor and reproducibility of mouse-based biomedical research.
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5
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Cruz Cisneros MC, Anderson EJ, Hampton BK, Parotti B, Sarkar S, Taft-Benz S, Bell TA, Blanchard M, Dillard JA, Dinnon KH, Hock P, Leist SR, Madden EA, Shaw GD, West A, Baric RS, Baxter VK, Pardo-Manuel de Villena F, Heise MT, Ferris MT. Host Genetic Variation Impacts SARS-CoV-2 Vaccination Response in the Diversity Outbred Mouse Population. Vaccines (Basel) 2024; 12:103. [PMID: 38276675 PMCID: PMC10821422 DOI: 10.3390/vaccines12010103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 01/12/2024] [Accepted: 01/18/2024] [Indexed: 01/27/2024] Open
Abstract
The COVID-19 pandemic led to the rapid and worldwide development of highly effective vaccines against SARS-CoV-2. However, there is significant individual-to-individual variation in vaccine efficacy due to factors including viral variants, host age, immune status, environmental and host genetic factors. Understanding those determinants driving this variation may inform the development of more broadly protective vaccine strategies. While host genetic factors are known to impact vaccine efficacy for respiratory pathogens such as influenza and tuberculosis, the impact of host genetic variation on vaccine efficacy against COVID-19 is not well understood. To model the impact of host genetic variation on SARS-CoV-2 vaccine efficacy, while controlling for the impact of non-genetic factors, we used the Diversity Outbred (DO) mouse model. We found that DO mice immunized against SARS-CoV-2 exhibited high levels of variation in vaccine-induced neutralizing antibody responses. While the majority of the vaccinated mice were protected from virus-induced disease, similar to human populations, we observed vaccine breakthrough in a subset of mice. Importantly, we found that this variation in neutralizing antibody, virus-induced disease, and viral titer is heritable, indicating that the DO serves as a useful model system for studying the contribution of genetic variation of both vaccines and disease outcomes.
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Affiliation(s)
- Marta C. Cruz Cisneros
- Genetics and Molecular Biology Curriculum, University of North Carolina, Chapel Hill, NC 27599, USA; (M.C.C.C.); (B.K.H.)
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
| | - Elizabeth J. Anderson
- Division of Comparative Medicine, University of North Carolina, Chapel Hill, NC 27599, USA; (E.J.A.); (V.K.B.)
| | - Brea K. Hampton
- Genetics and Molecular Biology Curriculum, University of North Carolina, Chapel Hill, NC 27599, USA; (M.C.C.C.); (B.K.H.)
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
| | - Breantié Parotti
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
| | - Sanjay Sarkar
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
| | - Sharon Taft-Benz
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
| | - Timothy A. Bell
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
| | - Matthew Blanchard
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
| | - Jacob A. Dillard
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC 27599, USA; (J.A.D.); (E.A.M.); (R.S.B.)
| | - Kenneth H. Dinnon
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC 27599, USA; (J.A.D.); (E.A.M.); (R.S.B.)
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
| | - Sarah R. Leist
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; (S.R.L.)
| | - Emily A. Madden
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC 27599, USA; (J.A.D.); (E.A.M.); (R.S.B.)
| | - Ginger D. Shaw
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
| | - Ande West
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; (S.R.L.)
| | - Ralph S. Baric
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC 27599, USA; (J.A.D.); (E.A.M.); (R.S.B.)
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; (S.R.L.)
| | - Victoria K. Baxter
- Division of Comparative Medicine, University of North Carolina, Chapel Hill, NC 27599, USA; (E.J.A.); (V.K.B.)
- Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
- Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Mark T. Heise
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC 27599, USA; (J.A.D.); (E.A.M.); (R.S.B.)
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Martin T. Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; (B.P.); (S.S.); (S.T.-B.); (T.A.B.); (M.B.); (P.H.); (G.D.S.); (F.P.-M.d.V.); (M.T.H.)
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6
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Faber JE, Zhang H, Xenakis JG, Bell TA, Hock P, Pardo-Manuel de Villena F, Ferris MT, Rzechorzek W. Large differences in collateral blood vessel abundance among individuals arise from multiple genetic variants. J Cereb Blood Flow Metab 2023; 43:1983-2004. [PMID: 37572089 PMCID: PMC10676139 DOI: 10.1177/0271678x231194956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/21/2023] [Accepted: 07/24/2023] [Indexed: 08/14/2023]
Abstract
Collateral blood flow varies greatly among humans for reasons that remain unclear, resulting in significant differences in ischemic tissue damage. A similarly large variation has also been found in mice that is caused by genetic background-dependent differences in the extent of collateral formation, termed collaterogenesis-a unique angiogenic process that occurs during development and determines collateral number and diameter in the adult. Previous studies have identified several quantitative trait loci (QTL) linked to this variation. However, understanding has been hampered by the use of closely related inbred strains that do not model the wide genetic variation present in the "outbred" human population. The Collaborative Cross (CC) multiparent mouse genetic reference panel was developed to address this limitation. Herein we measured the number and average diameter of cerebral collaterals in 60 CC strains, their 8 founder strains, 8 F1 crosses of CC strains selected for abundant versus sparse collaterals, and 2 intercross populations created from the latter. Collateral number evidenced 47-fold variation among the 60 CC strains, with 14% having poor, 25% poor-to-intermediate, 47% intermediate-to-good, and 13% good collateral abundance, that was associated with large differences in post-stroke infarct volume. Collateral number in skeletal muscle and intestine of selected high- and low-collateral strains evidenced the same relative abundance as in brain. Genome-wide mapping demonstrated that collateral abundance is a highly polymorphic trait. Subsequent analysis identified: 6 novel QTL circumscribing 28 high-priority candidate genes harboring putative loss-of-function polymorphisms (SNPs) associated with low collateral number; 335 predicted-deleterious SNPs present in their human orthologs; and 32 genes associated with vascular development but lacking protein coding variants. Six additional suggestive QTL (LOD > 4.5) were also identified in CC-wide QTL mapping. This study provides a comprehensive set of candidate genes for future investigations aimed at identifying signaling proteins within the collaterogenesis pathway whose variants potentially underlie genetic-dependent collateral insufficiency in brain and other tissues.
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Affiliation(s)
- James E Faber
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, USA
- Curriculum in Neuroscience, University of North Carolina, Chapel Hill, NC, USA
- McAllister Heart Institute, University of North Carolina, Chapel Hill, NC, USA
| | - Hua Zhang
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, USA
| | - James G Xenakis
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Timothy A Bell
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Martin T Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Wojciech Rzechorzek
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, USA
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7
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Faber JE, Zhang H, Xenakis JG, Bell TA, Hock P, de Villena FPM, Ferris MT, Rzechorzek W. Large differences in collateral blood vessel abundance among individuals arise from multiple genetic variants. bioRxiv 2023:2023.05.28.542633. [PMID: 37398475 PMCID: PMC10312463 DOI: 10.1101/2023.05.28.542633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Collateral blood flow varies greatly among humans for reasons that remain unclear, resulting in significant differences in ischemic tissue damage. A similarly large variation has also been found in mice that is caused by genetic background-dependent differences in the extent of collateral formation, termed collaterogenesis-a unique angiogenic process that occurs during development and determines collateral number and diameter in the adult. Previous studies have identified several quantitative trait loci (QTL) linked to this variation. However, understanding has been hampered by the use of closely related inbred strains that do not model the wide genetic variation present in the "outbred" human population. The Collaborative Cross (CC) multiparent mouse genetic reference panel was developed to address this limitation. Herein we measured the number and average diameter of cerebral collaterals in 60 CC strains, their 8 founder strains, 8 F1 crosses of CC strains selected for abundant versus sparse collaterals, and 2 intercross populations created from the latter. Collateral number evidenced 47-fold variation among the 60 CC strains, with 14% having poor, 25% poor-to-intermediate, 47% intermediate-to-good, and 13% good collateral abundance, that was associated with large differences in post-stroke infarct volume. Genome-wide mapping demonstrated that collateral abundance is a highly polymorphic trait. Subsequent analysis identified: 6 novel QTL circumscribing 28 high-priority candidate genes harboring putative loss-of-function polymorphisms (SNPs) associated with low collateral number; 335 predicted-deleterious SNPs present in their human orthologs; and 32 genes associated with vascular development but lacking protein coding variants. This study provides a comprehensive set of candidate genes for future investigations aimed at identifying signaling proteins within the collaterogenesis pathway whose variants potentially underlie genetic-dependent collateral insufficiency in brain and other tissues.
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8
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Arkatkar T, Davé VA, Cruz Talavera I, Graham JB, Swarts JL, Hughes SM, Bell TA, Hock P, Farrington J, Shaw GD, Kirby AC, Fialkow M, Huang ML, Jerome KR, Ferris MT, Hladik F, Schiffer JT, Prlic M, Lund JM. Memory T cells possess an innate-like function in local protection from mucosal infection. J Clin Invest 2023; 133:162800. [PMID: 36951943 PMCID: PMC10178838 DOI: 10.1172/jci162800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 03/22/2023] [Indexed: 03/24/2023] Open
Abstract
Mucosal infections pose a significant global health burden. Antigen-specific tissue resident T cells are critical to maintaining barrier immunity. Previous studies in the context of systemic infection suggest that memory CD8 T cells may also provide innate-like protection against antigenically unrelated pathogens independent of TCR engagement. Whether "bystander T cell activation" is also an important defense mechanism in the mucosa is poorly understood. Here, we investigated if innate-like memory CD8 T cells could protect against a model mucosal virus infection, herpes simplex virus 2 (HSV-2). We found that immunization with an irrelevant antigen delayed disease progression from lethal HSV-2 challenge, suggesting that memory CD8 T cells may mediate protection despite the lack of antigen-specificity. Upon HSV-2 infection, we observed an early infiltration, rather than substantial local proliferation, of antigen-non-specific CD8 T cells, which became bystander-activated only within the infected mucosal tissue. Critically, we show that bystander-activated CD8 T cells are sufficient to reduce early viral burden after HSV-2 infection. Finally, local cytokine cues within the tissue microenvironment after infection were sufficient for bystander activation of mucosal tissue memory CD8 T cells from mice and humans. Altogether, our findings suggest that local bystander-activation of CD8 memory T cells contribute a fast and effective innate-like response to infection in mucosal tissue.
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Affiliation(s)
- Tanvi Arkatkar
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - Veronica A Davé
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - Irene Cruz Talavera
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - Jessica B Graham
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - Jessica L Swarts
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - Sean M Hughes
- Department of Obstetrics and Gynecology, University of Washington, Seattle, United States of America
| | - Timothy A Bell
- Department of Genetics, University of North Carolina, Chapel Hill, United States of America
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, United States of America
| | - Joe Farrington
- Department of Genetics, University of North Carolina, Chapel Hill, United States of America
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina, Chapel Hill, United States of America
| | - Anna C Kirby
- Department of Obstetrics and Gynecology, University of Washington, Seattle, United States of America
| | - Michael Fialkow
- Department of Obstetrics and Gynecology, University of Washington, Seattle, United States of America
| | - Meei-Li Huang
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, United States of America
| | - Keith R Jerome
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - Martin T Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, United States of America
| | - Florian Hladik
- Department of Obstetrics and Gynecology, University of Washington, Seattle, United States of America
| | - Joshua T Schiffer
- Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - Martin Prlic
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - Jennifer M Lund
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States of America
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9
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Zhang T, Keele GR, Gyuricza IG, Vincent M, Brunton C, Bell TA, Hock P, Shaw GD, Munger SC, de Villena FPM, Ferris MT, Paulo JA, Gygi SP, Churchill GA. Multi-omics analysis identifies drivers of protein phosphorylation. Genome Biol 2023; 24:52. [PMID: 36944993 PMCID: PMC10031968 DOI: 10.1186/s13059-023-02892-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 03/09/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Phosphorylation of proteins is a key step in the regulation of many cellular processes including activation of enzymes and signaling cascades. The abundance of a phosphorylated peptide (phosphopeptide) is determined by the abundance of its parent protein and the proportion of target sites that are phosphorylated. RESULTS We quantified phosphopeptides, proteins, and transcripts in heart, liver, and kidney tissue samples of mice from 58 strains of the Collaborative Cross strain panel. We mapped ~700 phosphorylation quantitative trait loci (phQTL) across the three tissues and applied genetic mediation analysis to identify causal drivers of phosphorylation. We identified kinases, phosphatases, cytokines, and other factors, including both known and potentially novel interactions between target proteins and genes that regulate site-specific phosphorylation. Our analysis highlights multiple targets of pyruvate dehydrogenase kinase 1 (PDK1), a regulator of mitochondrial function that shows reduced activity in the NZO/HILtJ mouse, a polygenic model of obesity and type 2 diabetes. CONCLUSIONS Together, this integrative multi-omics analysis in genetically diverse CC strains provides a powerful tool to identify regulators of protein phosphorylation. The data generated in this study provides a resource for further exploration.
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Affiliation(s)
- Tian Zhang
- Harvard Medical School, Boston, MA, 02115, USA
| | | | | | | | | | - Timothy A Bell
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | | | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Martin T Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
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10
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Hampton BK, Plante KS, Whitmore AC, Linnertz CL, Madden EA, Noll KE, Boyson SP, Parotti B, Xenakis JG, Bell TA, Hock P, Shaw GD, de Villena FPM, Ferris MT, Heise MT. Forward genetic screen of homeostatic antibody levels in the Collaborative Cross identifies MBD1 as a novel regulator of B cell homeostasis. PLoS Genet 2022; 18:e1010548. [PMID: 36574452 PMCID: PMC9829176 DOI: 10.1371/journal.pgen.1010548] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 01/09/2023] [Accepted: 11/28/2022] [Indexed: 12/28/2022] Open
Abstract
Variation in immune homeostasis, the state in which the immune system is maintained in the absence of stimulation, is highly variable across populations. This variation is attributed to both genetic and environmental factors. However, the identity and function of specific regulators have been difficult to identify in humans. We evaluated homeostatic antibody levels in the serum of the Collaborative Cross (CC) mouse genetic reference population. We found heritable variation in all antibody isotypes and subtypes measured. We identified 4 quantitative trait loci (QTL) associated with 3 IgG subtypes: IgG1, IgG2b, and IgG2c. While 3 of these QTL map to genome regions of known immunological significance (major histocompatibility and immunoglobulin heavy chain locus), Qih1 (associated with variation in IgG1) mapped to a novel locus on Chromosome 18. We further associated this locus with B cell proportions in the spleen and identify Methyl-CpG binding domain protein 1 under this locus as a novel regulator of homeostatic IgG1 levels in the serum and marginal zone B cells (MZB) in the spleen, consistent with a role in MZB differentiation to antibody secreting cells.
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Affiliation(s)
- Brea K. Hampton
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kenneth S. Plante
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Alan C. Whitmore
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Colton L. Linnertz
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Emily A. Madden
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kelsey E. Noll
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Samuel P. Boyson
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Breantie Parotti
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - James G. Xenakis
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Timothy A. Bell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Pablo Hock
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ginger D. Shaw
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Martin T. Ferris
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Mark T. Heise
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, United States of America
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11
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Xenakis JG, Douillet C, Bell TA, Hock P, Farrington J, Liu T, Murphy CEY, Saraswatula A, Shaw GD, Nativio G, Shi Q, Venkatratnam A, Zou F, Fry RC, Stýblo M, Pardo-Manuel de Villena F. An interaction of inorganic arsenic exposure with body weight and composition on type 2 diabetes indicators in Diversity Outbred mice. Mamm Genome 2022; 33:575-589. [PMID: 35819478 PMCID: PMC9761582 DOI: 10.1007/s00335-022-09957-w] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 05/24/2022] [Indexed: 12/01/2022]
Abstract
Type 2 diabetes (T2D) is a complex metabolic disorder with no cure and high morbidity. Exposure to inorganic arsenic (iAs), a ubiquitous environmental contaminant, is associated with increased T2D risk. Despite growing evidence linking iAs exposure to T2D, the factors underlying inter-individual differences in susceptibility remain unclear. This study examined the interaction between chronic iAs exposure and body composition in a cohort of 75 Diversity Outbred mice. The study design mimics that of an exposed human population where the genetic diversity of the mice provides the variation in response, in contrast to a design that includes untreated mice. Male mice were exposed to iAs in drinking water (100 ppb) for 26 weeks. Metabolic indicators used as diabetes surrogates included fasting blood glucose and plasma insulin (FBG, FPI), blood glucose and plasma insulin 15 min after glucose challenge (BG15, PI15), homeostatic model assessment for [Formula: see text]-cell function and insulin resistance (HOMA-B, HOMA-IR), and insulinogenic index. Body composition was determined using magnetic resonance imaging, and the concentrations of iAs and its methylated metabolites were measured in liver and urine. Associations between cumulative iAs consumption and FPI, PI15, HOMA-B, and HOMA-IR manifested as significant interactions between iAs and body weight/composition. Arsenic speciation analyses in liver and urine suggest little variation in the mice's ability to metabolize iAs. The observed interactions accord with current research aiming to disentangle the effects of multiple complex factors on T2D risk, highlighting the need for further research on iAs metabolism and its consequences in genetically diverse mouse strains.
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Affiliation(s)
- James G Xenakis
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Curriculum in Toxicology and Environmental Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Christelle Douillet
- Department of Nutrition, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Timothy A Bell
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Pablo Hock
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Joseph Farrington
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Tianyi Liu
- Department of Biostatistics, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Caroline E Y Murphy
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Avani Saraswatula
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Ginger D Shaw
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Gustavo Nativio
- Department of Environmental Science and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Qing Shi
- Department of Nutrition, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Abhishek Venkatratnam
- Department of Nutrition, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Environmental Science and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Fei Zou
- Department of Biostatistics, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Rebecca C Fry
- Department of Environmental Science and Engineering, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Curriculum in Toxicology and Environmental Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Institute for Environmental Health Solutions, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
| | - Miroslav Stýblo
- Department of Nutrition, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Curriculum in Toxicology and Environmental Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Institute for Environmental Health Solutions, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, School of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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12
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Schäfer A, Leist SR, Gralinski LE, Martinez DR, Winkler ES, Okuda K, Hawkins PE, Gully KL, Graham RL, Scobey DT, Bell TA, Hock P, Shaw GD, Loome JF, Madden EA, Anderson E, Baxter VK, Taft-Benz SA, Zweigart MR, May SR, Dong S, Clark M, Miller DR, Lynch RM, Heise MT, Tisch R, Boucher RC, Pardo Manuel de Villena F, Montgomery SA, Diamond MS, Ferris MT, Baric RS. A Multitrait Locus Regulates Sarbecovirus Pathogenesis. bioRxiv 2022. [PMID: 35677067 DOI: 10.1101/2022.06.01.494461] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Infectious diseases have shaped the human population genetic structure, and genetic variation influences the susceptibility to many viral diseases. However, a variety of challenges have made the implementation of traditional human Genome-wide Association Studies (GWAS) approaches to study these infectious outcomes challenging. In contrast, mouse models of infectious diseases provide an experimental control and precision, which facilitates analyses and mechanistic studies of the role of genetic variation on infection. Here we use a genetic mapping cross between two distinct Collaborative Cross mouse strains with respect to SARS-CoV disease outcomes. We find several loci control differential disease outcome for a variety of traits in the context of SARS-CoV infection. Importantly, we identify a locus on mouse Chromosome 9 that shows conserved synteny with a human GWAS locus for SARS-CoV-2 severe disease. We follow-up and confirm a role for this locus, and identify two candidate genes, CCR9 and CXCR6 that both play a key role in regulating the severity of SARS-CoV, SARS-CoV-2 and a distantly related bat sarbecovirus disease outcomes. As such we provide a template for using experimental mouse crosses to identify and characterize multitrait loci that regulate pathogenic infectious outcomes across species.
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13
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Cruz Cisneros MC, Parotti B, Noll K, Bell TA, Hock P, Heise MT, Ferris MT. Genetic analysis of differential responses to adjuvanted influenza vaccination. The Journal of Immunology 2022. [DOI: 10.4049/jimmunol.208.supp.64.08] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Abstract
Each year the seasonal influenza vaccine is administered to protect individuals from infection, but vaccination often shows variable efficacy against influenza infections. While the inclusion of adjuvants can boost vaccine efficacy, individuals also vary in their response to adjuvants, and understanding the basis of this variation would provide insights into adjuvant mechanisms and advance vaccine development. Host genetics contribute to variation in vaccine response, but the specific genetic factors that impact immune responses to adjuvanted vaccination are not well understood. To better understand how the genetic background of individuals can modify vaccine and adjuvant-induced immune responses, we screened a set of Collaborative Cross (CC) mouse strains with immunization via inactivated influenza with or without alum. Across these genetically diverse CC strains, we observed wide variation in levels of influenza specific antibodies and isotypes (e.g., IgG1, IgG2). We further focused on two strains, CC002 and CC072, that had contrasting antibody responses to vaccine + alum. To understand the genetic factors driving these responses, we generated an F2 population to map quantitative trait loci (qtl) driving the differences between CC002 and CC072 in vaccine responses. Among the F2 population, variation across antibody levels were observed in mice vaccinated with the vaccine with and without alum that reflected the variation in the parent strains. QTL were mapped for variation in antibody levels for mice vaccinated without alum, further supporting a role for host genetics in regulating vaccine responses. Future analysis will focus on analyzing specific host factors modulating antibody responses to adjuvanted vaccination.
Supported by grants from NIH (U19 AI100625, 5T32 GM007092, 1T32 GM135128, 5R25 GM055336-19) and Burroughs Wellcome Fund GDEP to MCC.
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Affiliation(s)
| | - Breantié Parotti
- 2Department of Genetics, University of North Carolina at Chapel Hill
| | - Kelsey Noll
- 3Microbiology, University of North Carolina at Chapel Hill
| | - Timothy A Bell
- 2Department of Genetics, University of North Carolina at Chapel Hill
| | - Pablo Hock
- 2Department of Genetics, University of North Carolina at Chapel Hill
| | - Mark T Heise
- 2Department of Genetics, University of North Carolina at Chapel Hill
| | - Martin T Ferris
- 2Department of Genetics, University of North Carolina at Chapel Hill
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14
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Smith CM, Baker RE, Proulx MK, Mishra BB, Long JE, Park SW, Lee HN, Kiritsy MC, Bellerose MM, Olive AJ, Murphy KC, Papavinasasundaram K, Boehm FJ, Reames CJ, Meade RK, Hampton BK, Linnertz CL, Shaw GD, Hock P, Bell TA, Ehrt S, Schnappinger D, Pardo-Manuel de Villena F, Ferris MT, Ioerger TR, Sassetti CM. Host-pathogen genetic interactions underlie tuberculosis susceptibility in genetically diverse mice. eLife 2022; 11:74419. [PMID: 35112666 PMCID: PMC8846590 DOI: 10.7554/elife.74419] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/27/2022] [Indexed: 11/21/2022] Open
Abstract
The outcome of an encounter with Mycobacterium tuberculosis (Mtb) depends on the pathogen’s ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically diverse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to create a resource for associating bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb transposon mutant fitness (TnSeq) across the CC panel revealed that many virulence pathways are only required in specific host microenvironments, identifying a large fraction of the pathogen’s genome that has been maintained to ensure fitness in a diverse population. Both immunological and bacterial traits can be associated with genetic variants distributed across the mouse genome, making the CC a unique population for identifying specific host-pathogen genetic interactions that influence pathogenesis.
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Affiliation(s)
- Clare M Smith
- Department of Molecular Genetics and Microbiology, Duke University, Durham, United States
| | - Richard E Baker
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Megan K Proulx
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Bibhuti B Mishra
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Jarukit E Long
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Sae Woong Park
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Ha-Na Lee
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Michael C Kiritsy
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Michelle M Bellerose
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Andrew J Olive
- Microbiology and Molecular Genetics, Michigan State University, East Lansing, United States
| | - Kenan C Murphy
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Kadamba Papavinasasundaram
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Frederick J Boehm
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Charlotte J Reames
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
| | - Rachel K Meade
- Department of Molecular Genetics and Microbiology, Duke University, Durham, United States
| | - Brea K Hampton
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Colton L Linnertz
- Department of Genetics, University of North Carolina at Chapel Hill, Morrisville, United States
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Pablo Hock
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Timothy A Bell
- Department of Genetics,, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Sabine Ehrt
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | - Dirk Schnappinger
- Department of Microbiology and Immunology, Weill Cornell Medical College, New York, United States
| | | | - Martin T Ferris
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, United States
| | - Thomas R Ioerger
- Department of Computer Science and Engineering, Texas A&M University, College Station, United States
| | - Christopher M Sassetti
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, United States
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15
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Keele GR, Zhang T, Pham DT, Vincent M, Bell TA, Hock P, Shaw GD, Paulo JA, Munger SC, Pardo-Manuel de Villena F, Ferris MT, Gygi SP, Churchill GA. Regulation of protein abundance in genetically diverse mouse populations. Cell Genom 2021; 1:100003. [PMID: 36212994 PMCID: PMC9536773 DOI: 10.1016/j.xgen.2021.100003] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Genetically diverse mouse populations are powerful tools for characterizing the regulation of the proteome and its relationship to whole-organism phenotypes. We used mass spectrometry to profile and quantify the abundance of 6,798 proteins in liver tissue from mice of both sexes across 58 Collaborative Cross (CC) inbred strains. We previously collected liver proteomics data from the related Diversity Outbred (DO) mice and their founder strains. We show concordance across the proteomics datasets despite being generated from separate experiments, allowing comparative analysis. We map protein abundance quantitative trait loci (pQTLs), identifying 1,087 local and 285 distal in the CC mice and 1,706 local and 414 distal in the DO mice. We find that regulatory effects on individual proteins are conserved across the mouse populations, in particular for local genetic variation and sex differences. In comparison, proteins that form complexes are often co-regulated, displaying varying genetic architectures, and overall show lower heritability and map fewer pQTLs. We have made this resource publicly available to enable quantitative analyses of the regulation of the proteome.
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Affiliation(s)
| | - Tian Zhang
- Harvard Medical School, Boston, MA 02115, USA
| | - Duy T. Pham
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | | | - Timothy A. Bell
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Ginger D. Shaw
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | | | | | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA,Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Martin T. Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | | | - Gary A. Churchill
- The Jackson Laboratory, Bar Harbor, ME 04609, USA,Corresponding author
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16
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Schäfer A, Gralinski LE, Leist SR, Winkler ES, Hampton BK, Mooney MA, Jensen KL, Graham RL, Agnihothram S, Jeng S, Chamberlin S, Bell TA, Scobey DT, VanBlargan LA, Thackray LB, Hock P, Miller DR, Shaw GD, de Villena FPM, McWeeney SK, Montgomery SA, Diamond MS, Heise MT, Menachery VD, Ferris MT, Baric RS. Common Mechanism of SARS-CoV and SARS-CoV-2 Pathogenesis across Species. bioRxiv 2021:2021.05.14.444205. [PMID: 34013261 PMCID: PMC8132217 DOI: 10.1101/2021.05.14.444205] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Sarbecovirus (CoV) infections, including Severe Acute Respiratory CoV (SARS-CoV) and SARS-CoV-2, are considerable human threats. Human GWAS studies have recently identified loci associated with variation in SARS-CoV-2 susceptibility. However, genetically tractable models that reproduce human CoV disease outcomes are needed to mechanistically evaluate genetic determinants of CoV susceptibility. We used the Collaborative Cross (CC) and human GWAS datasets to elucidate host susceptibility loci that regulate CoV infections and to identify host quantitative trait loci that modulate severe CoV and pan-CoV disease outcomes including a major disease regulating loci including CCR9. CCR9 ablation resulted in enhanced titer, weight loss, respiratory dysfunction, mortality, and inflammation, providing mechanistic support in mitigating protection from severe SARS-CoV-2 pathogenesis across species. This study represents a comprehensive analysis of susceptibility loci for an entire genus of human pathogens conducted, identifies a large collection of susceptibility loci and candidate genes that regulate multiple aspects type-specific and cross-CoV pathogenesis, and also validates the paradigm of using the CC platform to identify common cross-species susceptibility loci and genes for newly emerging and pre-epidemic viruses.
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17
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Sigmon JS, Blanchard MW, Baric RS, Bell TA, Brennan J, Brockmann GA, Burks AW, Calabrese JM, Caron KM, Cheney RE, Ciavatta D, Conlon F, Darr DB, Faber J, Franklin C, Gershon TR, Gralinski L, Gu B, Gaines CH, Hagan RS, Heimsath EG, Heise MT, Hock P, Ideraabdullah F, Jennette JC, Kafri T, Kashfeen A, Kulis M, Kumar V, Linnertz C, Livraghi-Butrico A, Lloyd KCK, Lutz C, Lynch RM, Magnuson T, Matsushima GK, McMullan R, Miller DR, Mohlke KL, Moy SS, Murphy CEY, Najarian M, O'Brien L, Palmer AA, Philpot BD, Randell SH, Reinholdt L, Ren Y, Rockwood S, Rogala AR, Saraswatula A, Sassetti CM, Schisler JC, Schoenrock SA, Shaw GD, Shorter JR, Smith CM, St Pierre CL, Tarantino LM, Threadgill DW, Valdar W, Vilen BJ, Wardwell K, Whitmire JK, Williams L, Zylka MJ, Ferris MT, McMillan L, Manuel de Villena FP. Content and Performance of the MiniMUGA Genotyping Array: A New Tool To Improve Rigor and Reproducibility in Mouse Research. Genetics 2020; 216:905-930. [PMID: 33067325 PMCID: PMC7768238 DOI: 10.1534/genetics.120.303596] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 10/06/2020] [Indexed: 12/14/2022] Open
Abstract
The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research.
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Affiliation(s)
- John Sebastian Sigmon
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Matthew W Blanchard
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Mutant Mouse Resource and Research Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Ralph S Baric
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Timothy A Bell
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Jennifer Brennan
- Mutant Mouse Resource and Research Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | | | - A Wesley Burks
- Department of Pediatrics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - J Mauro Calabrese
- Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Kathleen M Caron
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Richard E Cheney
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Dominic Ciavatta
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Frank Conlon
- Department of Biology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - David B Darr
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - James Faber
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Craig Franklin
- Department of Veterinary Pathobiology, University of Missouri, Columbia, Missouri 65211
| | - Timothy R Gershon
- Department of Neurology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Lisa Gralinski
- Department of Epidemiology, Gillings School of Public Health, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Bin Gu
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Christiann H Gaines
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Robert S Hagan
- Division of Pulmonary Diseases and Critical Care Medicine, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Ernest G Heimsath
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Mark T Heise
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Folami Ideraabdullah
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
- Department of Nutrition, Gillings School of Public Health, University of North Carolina, Chapel Hill, North Carolina 27599
| | - J Charles Jennette
- Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Tal Kafri
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, North Carolina 27599
- Gene Therapy Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Anwica Kashfeen
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Mike Kulis
- Department of Pediatrics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Vivek Kumar
- The Jackson Laboratory, Bar Harbor, Maine 04609
| | - Colton Linnertz
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Alessandra Livraghi-Butrico
- Marsico Lung Institute/UNC Cystic Fibrosis Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - K C Kent Lloyd
- Department of Surgery, University of California Davis, Davis, California 95616
- School of Medicine, University of California Davis, California 95616
- Mouse Biology Program, University of California Davis, California 95616
| | | | - Rachel M Lynch
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Terry Magnuson
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Mutant Mouse Resource and Research Center, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Glenn K Matsushima
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, North Carolina 27599
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Rachel McMullan
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Darla R Miller
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Sheryl S Moy
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina 27599
- Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Caroline E Y Murphy
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Maya Najarian
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Lori O'Brien
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | | | - Benjamin D Philpot
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
- Marsico Lung Institute/UNC Cystic Fibrosis Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Scott H Randell
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | | | - Yuyu Ren
- University of California San Diego, La Jolla, California 92093
| | | | - Allison R Rogala
- Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, North Carolina 27599
- Division of Comparative Medicine, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Avani Saraswatula
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Christopher M Sassetti
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts 01655
| | - Jonathan C Schisler
- Department of Pharmacology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Sarah A Schoenrock
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - John R Shorter
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Clare M Smith
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts 01655
| | | | - Lisa M Tarantino
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, North Carolina 27599
| | - David W Threadgill
- University of California San Diego, La Jolla, California 92093
- Department of Biochemistry and Biophysics, Texas A&M University, Texas 77843
| | - William Valdar
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Barbara J Vilen
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, North Carolina 27599
| | | | - Jason K Whitmire
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Lucy Williams
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Mark J Zylka
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Martin T Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Fernando Pardo Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599
- Mutant Mouse Resource and Research Center, University of North Carolina, Chapel Hill, North Carolina 27599
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
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18
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Gu B, Shorter JR, Williams LH, Bell TA, Hock P, Dalton KA, Pan Y, Miller DR, Shaw GD, Philpot BD, Pardo-Manuel de Villena F. Collaborative Cross mice reveal extreme epilepsy phenotypes and genetic loci for seizure susceptibility. Epilepsia 2020; 61:2010-2021. [PMID: 32852103 DOI: 10.1111/epi.16617] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [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: 01/03/2020] [Revised: 06/25/2020] [Accepted: 06/26/2020] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Animal studies remain essential for understanding mechanisms of epilepsy and identifying new therapeutic targets. However, existing animal models of epilepsy do not reflect the high level of genetic diversity found in the human population. The Collaborative Cross (CC) population is a genetically diverse recombinant inbred panel of mice. The CC offers large genotypic and phenotypic diversity, inbred strains with stable genomes that allow for repeated phenotypic measurements, and genomic tools including whole genome sequence to identify candidate genes and candidate variants. METHODS We evaluated multiple complex epileptic traits in a sampling of 35 CC inbred strains using the flurothyl-induced seizure and kindling paradigm. We created an F2 population of 297 mice with extreme seizure susceptibility and performed quantitative trait loci (QTL) mapping to identify genomic regions associated with seizure sensitivity. We used quantitative RNA sequencing from CC hippocampal tissue to identify candidate genes and whole genome sequence to identify genetic variants likely affecting gene expression. RESULTS We identified new mouse models with extreme seizure susceptibility, seizure propagation, epileptogenesis, and SUDEP (sudden unexpected death in epilepsy). We performed QTL mapping and identified one known and seven novel loci associated with seizure sensitivity. We combined whole genome sequencing and hippocampal gene expression to pinpoint biologically plausible candidate genes (eg, Gabra2) and variants associated with seizure sensitivity. SIGNIFICANCE New mouse models of epilepsy are needed to better understand the complex genetic architecture of seizures and to identify therapeutics. We performed a phenotypic screen utilizing a novel genetic reference population of CC mice. The data we provide enable the identification of protective/risk genes and novel molecular mechanisms linked to complex seizure traits that are currently challenging to study and treat.
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Affiliation(s)
- Bin Gu
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, USA.,Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA
| | - John R Shorter
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.,Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA.,Institute of Biological Psychiatry, Mental Health Centre Sct. Hans, Mental Health Services, Copenhagen, Denmark.,iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark
| | - Lucy H Williams
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Timothy A Bell
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.,Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Pablo Hock
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.,Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Katherine A Dalton
- Neuroscience Curriculum, University of North Carolina, Chapel Hill, NC, USA
| | - Yiyun Pan
- Neuroscience Curriculum, University of North Carolina, Chapel Hill, NC, USA
| | - Darla R Miller
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.,Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Ginger D Shaw
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.,Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Benjamin D Philpot
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, USA.,Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA.,Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA.,Neuroscience Curriculum, University of North Carolina, Chapel Hill, NC, USA
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.,Carolina Institute for Developmental Disabilities, University of North Carolina, Chapel Hill, NC, USA.,Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
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19
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Fry RC, Addo KA, Bell TA, Douillet C, Martin E, Stýblo M, Pardo-Manuel de Villena F. Effects of Preconception and in Utero Inorganic Arsenic Exposure on the Metabolic Phenotype of Genetically Diverse Collaborative Cross Mice. Chem Res Toxicol 2019; 32:1487-1490. [PMID: 31251040 DOI: 10.1021/acs.chemrestox.9b00107] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
In humans and mice, in utero exposure to inorganic arsenic (iAs) is associated with adverse health outcomes later in life. The contribution of preconception exposure to the adverse outcomes in offspring has never been studied. Here combined in utero and postnatal exposures produce insulin resistance in two collaborative cross strains. Furthermore, combined preconception and in utero exposure resulted in increased birth weight and developed insulin resistance in one strain. Thus, preconception exposure to arsenic may contribute to the metabolic disorders later in life, but the susceptibility to the effects of this exposure is determined, at least in part, by genetics.
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20
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Morgan AP, Bell TA, Crowley JJ, Pardo-Manuel de Villena F. Instability of the Pseudoautosomal Boundary in House Mice. Genetics 2019; 212:469-487. [PMID: 31028113 PMCID: PMC6553833 DOI: 10.1534/genetics.119.302232] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 04/23/2019] [Indexed: 12/14/2022] Open
Abstract
Faithful segregation of homologous chromosomes at meiosis requires pairing and recombination. In taxa with dimorphic sex chromosomes, pairing between them in the heterogametic sex is limited to a narrow interval of residual sequence homology known as the pseudoautosomal region (PAR). Failure to form the obligate crossover in the PAR is associated with male infertility in house mice (Mus musculus) and humans. Yet despite this apparent functional constraint, the boundary and organization of the PAR is highly variable in mammals, and even between subspecies of mice. Here, we estimate the genetic map in a previously documented expansion of the PAR in the M. musculus castaneus subspecies and show that the local recombination rate is 100-fold higher than the autosomal background. We identify an independent shift in the PAR boundary in the M. musculus musculus subspecies and show that it involves a complex rearrangement, but still recombines in heterozygous males. Finally, we demonstrate pervasive copy-number variation at the PAR boundary in wild populations of M. m. domesticus, M. m. musculus, and M. m. castaneus Our results suggest that the intensity of recombination activity in the PAR, coupled with relatively weak constraints on its sequence, permit the generation and maintenance of unusual levels of polymorphism in the population of unknown functional significance.
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Affiliation(s)
- Andrew P Morgan
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27514
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27514
| | - Timothy A Bell
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27514
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27514
| | - James J Crowley
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27514
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27514
- Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina 27514
- Department of Clinical Neuroscience, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27514
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27514
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21
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Shorter JR, Najarian ML, Bell TA, Blanchard M, Ferris MT, Hock P, Kashfeen A, Kirchoff KE, Linnertz CL, Sigmon JS, Miller DR, McMillan L, Pardo-Manuel de Villena F. Whole Genome Sequencing and Progress Toward Full Inbreeding of the Mouse Collaborative Cross Population. G3 (Bethesda) 2019; 9:1303-1311. [PMID: 30858237 PMCID: PMC6505143 DOI: 10.1534/g3.119.400039] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 03/08/2019] [Indexed: 12/20/2022]
Abstract
Two key features of recombinant inbred panels are well-characterized genomes and reproducibility. Here we report on the sequenced genomes of six additional Collaborative Cross (CC) strains and on inbreeding progress of 72 CC strains. We have previously reported on the sequences of 69 CC strains that were publicly available, bringing the total of CC strains with whole genome sequence up to 75. The sequencing of these six CC strains updates the efforts toward inbreeding undertaken by the UNC Systems Genetics Core. The timing reflects our competing mandates to release to the public as many CC strains as possible while achieving an acceptable level of inbreeding. The new six strains have a higher than average founder contribution from non-domesticus strains than the previously released CC strains. Five of the six strains also have high residual heterozygosity (>14%), which may be related to non-domesticus founder contributions. Finally, we report on updated estimates on residual heterozygosity across the entire CC population using a novel, simple and cost effective genotyping platform on three mice from each strain. We observe a reduction in residual heterozygosity across all previously released CC strains. We discuss the optimal use of different genetic resources available for the CC population.
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Affiliation(s)
| | | | - Timothy A Bell
- Department of Genetics
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
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22
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McMullan RC, Ferris MT, Bell TA, Menachery VD, Baric RS, Hua K, Pomp D, Smith‐Ryan AE, de Villena FP. CC002/Unc females are mouse models of exercise-induced paradoxical fat response. Physiol Rep 2018; 6:e13716. [PMID: 29924460 PMCID: PMC6009762 DOI: 10.14814/phy2.13716] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Accepted: 05/03/2018] [Indexed: 12/13/2022] Open
Abstract
Exercise results in beneficial health outcomes and protects against a variety of chronic diseases. However, U.S. exercise guidelines recommend identical exercise programs for everyone, despite individual variation in responses to these programs, including paradoxical fat gain. Experimental models of exercise-induced paradoxical outcomes may enable the dissection of underlying physiological mechanisms as well as the evaluation of potential interventions. Whereas several studies have identified individual mice exhibiting paradoxical fat gain following exercise, no systematic effort has been conducted to identify and characterize models of paradoxical response. Strains from the Collaborative Cross (CC) genetic reference population were used due to its high levels of genetic variation, its reproducible nature, and the observation that the CC is a rich source of novel disease models, to assess the impact genetic background has on exercise responses. We identified the strain CC002/Unc as an exercise-induced paradoxical fat response model in a controlled voluntary exercise study across multiple ages in female mice. We also found sex and genetic differences were consistent with this pattern in a study of forced exercise programs. These results provide a novel model for studies to determine the mechanisms behind paradoxical metabolic responses to exercise, and enable development of more rational personalized exercise recommendations based on factors such as age, sex, and genetic background.
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Affiliation(s)
- Rachel C. McMullan
- Department of GeneticsSchool of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
- Genetics and Molecular Biology CurriculumSchool of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Martin T. Ferris
- Department of GeneticsSchool of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Timothy A. Bell
- Department of GeneticsSchool of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Vineet D. Menachery
- Department of EpidemiologyGillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Ralph S. Baric
- Department of EpidemiologyGillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Kunjie Hua
- Department of GeneticsSchool of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Daniel Pomp
- Department of GeneticsSchool of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Abbie E. Smith‐Ryan
- Department of Exercise and Sport ScienceCollege of Arts and SciencesUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
| | - Fernando Pardo‐Manuel de Villena
- Department of GeneticsSchool of MedicineUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
- Lineberger Comprehensive Cancer CenterUniversity of North Carolina at Chapel HillChapel HillNorth Carolina
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23
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Morgan AP, Holt JM, McMullan RC, Bell TA, Clayshulte AMF, Didion JP, Yadgary L, Thybert D, Odom DT, Flicek P, McMillan L, de Villena FPM. The Evolutionary Fates of a Large Segmental Duplication in Mouse. Genetics 2016; 204:267-85. [PMID: 27371833 PMCID: PMC5012392 DOI: 10.1534/genetics.116.191007] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 06/27/2016] [Indexed: 01/21/2023] Open
Abstract
Gene duplication and loss are major sources of genetic polymorphism in populations, and are important forces shaping the evolution of genome content and organization. We have reconstructed the origin and history of a 127-kbp segmental duplication, R2d, in the house mouse (Mus musculus). R2d contains a single protein-coding gene, Cwc22 De novo assembly of both the ancestral (R2d1) and the derived (R2d2) copies reveals that they have been subject to nonallelic gene conversion events spanning tens of kilobases. R2d2 is also a hotspot for structural variation: its diploid copy number ranges from zero in the mouse reference genome to >80 in wild mice sampled from around the globe. Hemizygosity for high copy-number alleles of R2d2 is associated in cis with meiotic drive; suppression of meiotic crossovers; and copy-number instability, with a mutation rate in excess of 1 per 100 transmissions in some laboratory populations. Our results provide a striking example of allelic diversity generated by duplication and demonstrate the value of de novo assembly in a phylogenetic context for understanding the mutational processes affecting duplicate genes.
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Affiliation(s)
- Andrew P Morgan
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - J Matthew Holt
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Rachel C McMullan
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Timothy A Bell
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Amelia M-F Clayshulte
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - John P Didion
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Liran Yadgary
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
| | - David Thybert
- European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge, CB10 1SD, United Kingdom
| | - Duncan T Odom
- Cancer Research United Kingdom Cambridge Institute, University of Cambridge, CB2 0RE, United Kingdom Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, United Kingdom
| | - Paul Flicek
- European Bioinformatics Institute, European Molecular Biology Laboratory, Wellcome Genome Campus, Cambridge, CB10 1SD, United Kingdom Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, CB10 1SA, United Kingdom
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina, Chapel Hill, North Carolina 27599
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics and Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599
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24
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Didion JP, Morgan AP, Yadgary L, Bell TA, McMullan RC, Ortiz de Solorzano L, Britton-Davidian J, Bult CJ, Campbell KJ, Castiglia R, Ching YH, Chunco AJ, Crowley JJ, Chesler EJ, Förster DW, French JE, Gabriel SI, Gatti DM, Garland T, Giagia-Athanasopoulou EB, Giménez MD, Grize SA, Gündüz İ, Holmes A, Hauffe HC, Herman JS, Holt JM, Hua K, Jolley WJ, Lindholm AK, López-Fuster MJ, Mitsainas G, da Luz Mathias M, McMillan L, Ramalhinho MDGM, Rehermann B, Rosshart SP, Searle JB, Shiao MS, Solano E, Svenson KL, Thomas-Laemont P, Threadgill DW, Ventura J, Weinstock GM, Pomp D, Churchill GA, Pardo-Manuel de Villena F. R2d2 Drives Selfish Sweeps in the House Mouse. Mol Biol Evol 2016; 33:1381-95. [PMID: 26882987 PMCID: PMC4868115 DOI: 10.1093/molbev/msw036] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
A selective sweep is the result of strong positive selection driving newly occurring or standing genetic variants to fixation, and can dramatically alter the pattern and distribution of allelic diversity in a population. Population-level sequencing data have enabled discoveries of selective sweeps associated with genes involved in recent adaptations in many species. In contrast, much debate but little evidence addresses whether “selfish” genes are capable of fixation—thereby leaving signatures identical to classical selective sweeps—despite being neutral or deleterious to organismal fitness. We previously described R2d2, a large copy-number variant that causes nonrandom segregation of mouse Chromosome 2 in females due to meiotic drive. Here we show population-genetic data consistent with a selfish sweep driven by alleles of R2d2 with high copy number (R2d2HC) in natural populations. We replicate this finding in multiple closed breeding populations from six outbred backgrounds segregating for R2d2 alleles. We find that R2d2HC rapidly increases in frequency, and in most cases becomes fixed in significantly fewer generations than can be explained by genetic drift. R2d2HC is also associated with significantly reduced litter sizes in heterozygous mothers, making it a true selfish allele. Our data provide direct evidence of populations actively undergoing selfish sweeps, and demonstrate that meiotic drive can rapidly alter the genomic landscape in favor of mutations with neutral or even negative effects on overall Darwinian fitness. Further study will reveal the incidence of selfish sweeps, and will elucidate the relative contributions of selfish genes, adaptation and genetic drift to evolution.
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Affiliation(s)
- John P Didion
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Andrew P Morgan
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Liran Yadgary
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Timothy A Bell
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Rachel C McMullan
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Lydia Ortiz de Solorzano
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | - Janice Britton-Davidian
- Institut des Sciences de l'Evolution, Université De Montpellier, CNRS, IRD, EPHE, Montpellier, France
| | | | - Karl J Campbell
- Island Conservation, Puerto Ayora, Galápagos Island, Ecuador School of Geography, Planning & Environmental Management, The University of Queensland, St Lucia, QLD, Australia
| | - Riccardo Castiglia
- Department of Biology and Biotechnologies "Charles Darwin", University of Rome "La Sapienza", Rome, Italy
| | - Yung-Hao Ching
- Department of Molecular Biology and Human Genetics, Tzu Chi University, Hualien City, Taiwan
| | | | - James J Crowley
- Department of Genetics, The University of North Carolina at Chapel Hill
| | | | - Daniel W Förster
- Department of Evolutionary Genetics, Leibniz-Institute for Zoo and Wildlife Research, Berlin, Germany
| | - John E French
- National Toxicology Program, National Institute of Environmental Sciences, NIH, Research Triangle Park, NC
| | - Sofia I Gabriel
- Department of Animal Biology & CESAM - Centre for Environmental and Marine Studies, Faculty of Sciences, University of Lisbon, Lisboa, Portugal
| | | | | | | | - Mabel D Giménez
- Instituto de Biología Subtropical, CONICET - Universidad Nacional de Misiones, Posadas, Misiones, Argentina
| | - Sofia A Grize
- Institute of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - İslam Gündüz
- Department of Biology, Faculty of Arts and Sciences, University of Ondokuz Mayis, Samsun, Turkey
| | - Andrew Holmes
- Laboratory of Behavioral and Genomic Neuroscience, National Institute on Alcohol Abuse and Alcoholism, NIH, Bethesda, MD
| | - Heidi C Hauffe
- Department of Biodiversity and Molecular Ecology, Research and Innovation Centre, Fondazione Edmund Mach, San Michele All'adige, TN, Italy
| | - Jeremy S Herman
- Department of Natural Sciences, National Museums Scotland, Edinburgh, United Kingdom
| | - James M Holt
- Department of Computer Science, The University of North Carolina at Chapel Hill
| | - Kunjie Hua
- Department of Genetics, The University of North Carolina at Chapel Hill
| | | | - Anna K Lindholm
- Institute of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | | | - George Mitsainas
- Section of Animal Biology, Department of Biology, University of Patras, Patras, Greece
| | - Maria da Luz Mathias
- Department of Animal Biology & CESAM - Centre for Environmental and Marine Studies, Faculty of Sciences, University of Lisbon, Lisboa, Portugal
| | - Leonard McMillan
- Department of Computer Science, The University of North Carolina at Chapel Hill
| | - Maria da Graça Morgado Ramalhinho
- Department of Animal Biology & CESAM - Centre for Environmental and Marine Studies, Faculty of Sciences, University of Lisbon, Lisboa, Portugal
| | - Barbara Rehermann
- Immunology Section, Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD
| | - Stephan P Rosshart
- Immunology Section, Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD
| | - Jeremy B Searle
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY
| | - Meng-Shin Shiao
- Research Center, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Emanuela Solano
- Department of Biology and Biotechnologies "Charles Darwin", University of Rome "La Sapienza", Rome, Italy
| | | | | | - David W Threadgill
- Department of Veterinary Pathobiology, Texas A&M University, College Station Department of Molecular and Cellular Medicine, Texas A&M University, College Station
| | - Jacint Ventura
- Departament de Biologia Animal, de Biologia Vegetal y de Ecologia, Facultat de Biociències, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Daniel Pomp
- Department of Genetics, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
| | | | - Fernando Pardo-Manuel de Villena
- Department of Genetics, The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill Carolina Center for Genome Science, The University of North Carolina at Chapel Hill
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25
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Gralinski LE, Ferris MT, Aylor DL, Whitmore AC, Green R, Frieman MB, Deming D, Menachery VD, Miller DR, Buus RJ, Bell TA, Churchill GA, Threadgill DW, Katze MG, McMillan L, Valdar W, Heise MT, Pardo-Manuel de Villena F, Baric RS. Genome Wide Identification of SARS-CoV Susceptibility Loci Using the Collaborative Cross. PLoS Genet 2015; 11:e1005504. [PMID: 26452100 PMCID: PMC4599853 DOI: 10.1371/journal.pgen.1005504] [Citation(s) in RCA: 118] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2015] [Accepted: 08/15/2015] [Indexed: 01/21/2023] Open
Abstract
New systems genetics approaches are needed to rapidly identify host genes and genetic networks that regulate complex disease outcomes. Using genetically diverse animals from incipient lines of the Collaborative Cross mouse panel, we demonstrate a greatly expanded range of phenotypes relative to classical mouse models of SARS-CoV infection including lung pathology, weight loss and viral titer. Genetic mapping revealed several loci contributing to differential disease responses, including an 8.5Mb locus associated with vascular cuffing on chromosome 3 that contained 23 genes and 13 noncoding RNAs. Integrating phenotypic and genetic data narrowed this region to a single gene, Trim55, an E3 ubiquitin ligase with a role in muscle fiber maintenance. Lung pathology and transcriptomic data from mice genetically deficient in Trim55 were used to validate its role in SARS-CoV-induced vascular cuffing and inflammation. These data establish the Collaborative Cross platform as a powerful genetic resource for uncovering genetic contributions of complex traits in microbial disease severity, inflammation and virus replication in models of outbred populations.
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Affiliation(s)
- Lisa E. Gralinski
- Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Martin T. Ferris
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - David L. Aylor
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Alan C. Whitmore
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Richard Green
- Department of Microbiology, University of Washington, Seattle, Washington, United States of America
| | - Matthew B. Frieman
- Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Damon Deming
- Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Vineet D. Menachery
- Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Darla R. Miller
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ryan J. Buus
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Timothy A. Bell
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | | | - David W. Threadgill
- Department of Veterinary Pathobiology, Texas A&M University, College Station, Texas, United States of America
| | - Michael G. Katze
- Department of Microbiology, University of Washington, Seattle, Washington, United States of America
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - William Valdar
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Mark T. Heise
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Ralph S. Baric
- Department of Epidemiology, University of North Carolina, Chapel Hill, Chapel Hill, North Carolina, United States of America
- * E-mail:
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26
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Crowley JJ, Zhabotynsky V, Sun W, Huang S, Pakatci IK, Kim Y, Wang JR, Morgan AP, Calaway JD, Aylor DL, Yun Z, Bell TA, Buus RJ, Calaway ME, Didion JP, Gooch TJ, Hansen SD, Robinson NN, Shaw GD, Spence JS, Quackenbush CR, Barrick CJ, Nonneman RJ, Kim K, Xenakis J, Xie Y, Valdar W, Lenarcic AB, Wang W, Welsh CE, Fu CP, Zhang Z, Holt J, Guo Z, Threadgill DW, Tarantino LM, Miller DR, Zou F, McMillan L, Sullivan PF, de Villena FPM. Corrigendum: analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance. Nat Genet 2015; 47:690. [PMID: 26018903 DOI: 10.1038/ng0615-690a] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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27
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Crowley JJ, Zhabotynsky V, Sun W, Huang S, Pakatci IK, Kim Y, Wang JR, Morgan AP, Calaway JD, Aylor DL, Yun Z, Bell TA, Buus RJ, Calaway ME, Didion JP, Gooch TJ, Hansen SD, Robinson NN, Shaw GD, Spence JS, Quackenbush CR, Barrick CJ, Nonneman RJ, Kim K, Xenakis J, Xie Y, Valdar W, Lenarcic AB, Wang W, Welsh CE, Fu CP, Zhang Z, Holt J, Guo Z, Threadgill DW, Tarantino LM, Miller DR, Zou F, McMillan L, Sullivan PF, Pardo-Manuel de Villena F. Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance. Nat Genet 2015; 47:353-60. [PMID: 25730764 PMCID: PMC4380817 DOI: 10.1038/ng.3222] [Citation(s) in RCA: 162] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Accepted: 01/26/2015] [Indexed: 12/15/2022]
Abstract
Complex human traits are influenced by variation in regulatory DNA through mechanisms that are not fully understood. Since regulatory elements are conserved between humans and mice, a thorough annotation of cis regulatory variants in mice could aid in this process. Here we provide a detailed portrait of mouse gene expression across multiple tissues in a three-way diallel. Greater than 80% of mouse genes have cis regulatory variation. These effects influence complex traits and usually extend to the human ortholog. Further, we estimate that at least one in every thousand SNPs creates a cis regulatory effect. We also observe two types of parent-of-origin effects, including classical imprinting and a novel, global allelic imbalance in favor of the paternal allele. We conclude that, as with humans, pervasive regulatory variation influences complex genetic traits in mice and provide a new resource toward understanding the genetic control of transcription in mammals.
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Affiliation(s)
- James J Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Vasyl Zhabotynsky
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Wei Sun
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Shunping Huang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Isa Kemal Pakatci
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yunjung Kim
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jeremy R Wang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Andrew P Morgan
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - John D Calaway
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - David L Aylor
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Zaining Yun
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Timothy A Bell
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ryan J Buus
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Mark E Calaway
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - John P Didion
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Terry J Gooch
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Stephanie D Hansen
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nashiya N Robinson
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ginger D Shaw
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jason S Spence
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Corey R Quackenbush
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Cordelia J Barrick
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Randal J Nonneman
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Kyungsu Kim
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - James Xenakis
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yuying Xie
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - William Valdar
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Alan B Lenarcic
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Wei Wang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Catherine E Welsh
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Chen-Ping Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Zhaojun Zhang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - James Holt
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Zhishan Guo
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - David W Threadgill
- Department of Molecular and Cellular Medicine, Texas A&M Health Science Center, College Station, Texas, USA
| | - Lisa M Tarantino
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Darla R Miller
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Fei Zou
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Patrick F Sullivan
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [4] Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fernando Pardo-Manuel de Villena
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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28
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Didion JP, Morgan AP, Clayshulte AMF, Mcmullan RC, Yadgary L, Petkov PM, Bell TA, Gatti DM, Crowley JJ, Hua K, Aylor DL, Bai L, Calaway M, Chesler EJ, French JE, Geiger TR, Gooch TJ, Garland T, Harrill AH, Hunter K, McMillan L, Holt M, Miller DR, O'Brien DA, Paigen K, Pan W, Rowe LB, Shaw GD, Simecek P, Sullivan PF, Svenson KL, Weinstock GM, Threadgill DW, Pomp D, Churchill GA, Pardo-Manuel de Villena F. A multi-megabase copy number gain causes maternal transmission ratio distortion on mouse chromosome 2. PLoS Genet 2015; 11:e1004850. [PMID: 25679959 PMCID: PMC4334553 DOI: 10.1371/journal.pgen.1004850] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2014] [Accepted: 10/24/2014] [Indexed: 12/29/2022] Open
Abstract
Significant departures from expected Mendelian inheritance ratios (transmission ratio distortion, TRD) are frequently observed in both experimental crosses and natural populations. TRD on mouse Chromosome (Chr) 2 has been reported in multiple experimental crosses, including the Collaborative Cross (CC). Among the eight CC founder inbred strains, we found that Chr 2 TRD was exclusive to females that were heterozygous for the WSB/EiJ allele within a 9.3 Mb region (Chr 2 76.9 - 86.2 Mb). A copy number gain of a 127 kb-long DNA segment (designated as responder to drive, R2d) emerged as the strongest candidate for the causative allele. We mapped R2d sequences to two loci within the candidate interval. R2d1 is located near the proximal boundary, and contains a single copy of R2d in all strains tested. R2d2 maps to a 900 kb interval, and the number of R2d copies varies from zero in classical strains (including the mouse reference genome) to more than 30 in wild-derived strains. Using real-time PCR assays for the copy number, we identified a mutation (R2d2WSBdel1) that eliminates the majority of the R2d2WSB copies without apparent alterations of the surrounding WSB/EiJ haplotype. In a three-generation pedigree segregating for R2d2WSBdel1, the mutation is transmitted to the progeny and Mendelian segregation is restored in females heterozygous for R2d2WSBdel1, thus providing direct evidence that the copy number gain is causal for maternal TRD. We found that transmission ratios in R2d2WSB heterozygous females vary between Mendelian segregation and complete distortion depending on the genetic background, and that TRD is under genetic control of unlinked distorter loci. Although the R2d2WSB transmission ratio was inversely correlated with average litter size, several independent lines of evidence support the contention that female meiotic drive is the cause of the distortion. We discuss the implications and potential applications of this novel meiotic drive system.
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Affiliation(s)
- John P. Didion
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Andrew P. Morgan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Amelia M.-F. Clayshulte
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Rachel C. Mcmullan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Liran Yadgary
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Petko M. Petkov
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Timothy A. Bell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Daniel M. Gatti
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - James J. Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kunjie Hua
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - David L. Aylor
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Ling Bai
- Laboratory of Cancer Biology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Mark Calaway
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | | | - John E. French
- National Toxicology Program, National Institute of Environmental Sciences, NIH, Research Triangle Park, North Carolina, United States of America
| | - Thomas R. Geiger
- Laboratory of Cancer Biology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Terry J. Gooch
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Theodore Garland
- Department of Biology, University of California Riverside, Riverside, California, United States of America
| | - Alison H. Harrill
- Department of Environmental and Occupational Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America
| | - Kent Hunter
- Laboratory of Cancer Biology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Matt Holt
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Darla R. Miller
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Deborah A. O'Brien
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kenneth Paigen
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Wenqi Pan
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Lucy B. Rowe
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Ginger D. Shaw
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Petr Simecek
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Karen L Svenson
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - George M. Weinstock
- Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America
| | - David W. Threadgill
- Department of Veterinary Pathobiology and Department of Molecular and Cellular Medicine, Texas A&M University, College Station, Texas, United States of America
| | - Daniel Pomp
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | | | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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Rogala AR, Morgan AP, Christensen AM, Gooch TJ, Bell TA, Miller DR, Godfrey VL, de Villena FPM. The Collaborative Cross as a resource for modeling human disease: CC011/Unc, a new mouse model for spontaneous colitis. Mamm Genome 2014; 25:95-108. [PMID: 24487921 PMCID: PMC3960486 DOI: 10.1007/s00335-013-9499-2] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2013] [Accepted: 12/09/2013] [Indexed: 02/07/2023]
Abstract
Inflammatory bowel disease (IBD) is an immune-mediated condition driven by improper responses to intestinal microflora in the context of environmental and genetic background. GWAS in humans have identified many loci associated with IBD, but animal models are valuable for dissecting the underlying molecular mechanisms, characterizing environmental and genetic contributions and developing treatments. Mouse models rely on interventions such as chemical treatment or introduction of an infectious agent to induce disease. Here, we describe a new model for IBD in which the disease develops spontaneously in 20-week-old mice in the absence of known murine pathogens. The model is part of the Collaborative Cross and came to our attention due to a high incidence of rectal prolapse in an incompletely inbred line. Necropsies revealed a profound proliferative colitis with variable degrees of ulceration and vasculitis, splenomegaly and enlarged mesenteric lymph nodes with no discernible anomalies of other organ systems. Phenotypic characterization of the CC011/Unc mice with homozygosity ranging from 94.1 to 99.8% suggested that the trait was fixed and acted recessively in crosses to the colitis-resistant C57BL/6J inbred strain. Using a QTL approach, we identified four loci, Ccc1, Ccc2, Ccc3 and Ccc4 on chromosomes 12, 14, 1 and 8 that collectively explain 27.7% of the phenotypic variation. Surprisingly, we also found that minute levels of residual heterozygosity in CC011/Unc have significant impact on the phenotype. This work demonstrates the utility of the CC as a source of models of human disease that arises through new combinations of alleles at susceptibility loci.
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Affiliation(s)
- Allison R. Rogala
- Division of Laboratory Animal Medicine, University of North Carolina, Chapel Hill, NC USA
| | - Andrew P. Morgan
- Department of Genetics, Lineberger Comprehensive Cancer Center, and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC USA
| | - Alexis M. Christensen
- Division of Laboratory Animal Medicine, University of North Carolina, Chapel Hill, NC USA
| | - Terry J. Gooch
- Department of Genetics, Lineberger Comprehensive Cancer Center, and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC USA
| | - Timothy A. Bell
- Department of Genetics, Lineberger Comprehensive Cancer Center, and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC USA
| | - Darla R. Miller
- Department of Genetics, Lineberger Comprehensive Cancer Center, and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC USA
| | - Virginia L. Godfrey
- Division of Laboratory Animal Medicine, University of North Carolina, Chapel Hill, NC USA
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, NC USA
- Department of Genetics, Lineberger Comprehensive Cancer Center, and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC USA
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30
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Phillippi J, Xie Y, Miller DR, Bell TA, Zhang Z, Lenarcic AB, Aylor DL, Krovi SH, Threadgill DW, de Villena FPM, Wang W, Valdar W, Frelinger JA. Using the emerging Collaborative Cross to probe the immune system. Genes Immun 2013; 15:38-46. [PMID: 24195963 PMCID: PMC4004367 DOI: 10.1038/gene.2013.59] [Citation(s) in RCA: 65] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2013] [Revised: 10/02/2013] [Accepted: 10/04/2013] [Indexed: 12/21/2022]
Abstract
The Collaborative Cross (CC) is an emerging panel of recombinant inbred (RI) mouse strains. Each strain is genetically distinct but all descended from the same eight inbred founders. In 66 strains from incipient lines of the CC (pre-CC), as well as the 8 CC founders and some of their F1 offspring, we examined subsets of lymphocytes and antigen-presenting cells. We found significant variation among the founders, with even greater diversity in the pre-CC. Genome-wide association using inferred haplotypes detected highly significant loci controlling B-to-T cell ratio, CD8 T-cell numbers, CD11c and CD23 expression. Comparison of overall strain effects in the CC founders with strain effects at QTL in the pre-CC revealed sharp contrasts in the genetic architecture of two traits with significant loci: variation in CD23 can be explained largely by additive genetics at one locus, whereas variation in B-to-T ratio has a more complex etiology. For CD23, we found a strong QTL whose confidence interval contained the CD23 structural gene Fcer2a. Our data on the pre-CC demonstrate the utility of the CC for studying immunophenotypes and the value of integrating founder, CC and F1 data. The extreme immunophenotypes observed could have pleiotropic effects in other CC experiments.
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Affiliation(s)
- J Phillippi
- Department of Immunobiology, University of Arizona, Tucson, AZ, USA
| | - Y Xie
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - D R Miller
- 1] Department of Genetics, University of North Carolina, Chapel Hill, NC, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - T A Bell
- 1] Department of Genetics, University of North Carolina, Chapel Hill, NC, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - Z Zhang
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - A B Lenarcic
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - D L Aylor
- 1] Department of Genetics, University of North Carolina, Chapel Hill, NC, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - S H Krovi
- Department of Immunobiology, University of Arizona, Tucson, AZ, USA
| | - D W Threadgill
- Department of Genetics, North Carolina State University, Raleigh, NC, USA
| | - F Pardo-Manuel de Villena
- 1] Department of Genetics, University of North Carolina, Chapel Hill, NC, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - W Wang
- Department of Computer Science, and the Jonsson Comprehensive Cancer Center, University of California, Los Angeles, CA, USA
| | - W Valdar
- 1] Department of Genetics, University of North Carolina, Chapel Hill, NC, USA [2] Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, USA
| | - J A Frelinger
- Department of Immunobiology, University of Arizona, Tucson, AZ, USA
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Ferris MT, Aylor DL, Bottomly D, Whitmore AC, Aicher LD, Bell TA, Bradel-Tretheway B, Bryan JT, Buus RJ, Gralinski LE, Haagmans BL, McMillan L, Miller DR, Rosenzweig E, Valdar W, Wang J, Churchill GA, Threadgill DW, McWeeney SK, Katze MG, Pardo-Manuel de Villena F, Baric RS, Heise MT. Modeling host genetic regulation of influenza pathogenesis in the collaborative cross. PLoS Pathog 2013; 9:e1003196. [PMID: 23468633 PMCID: PMC3585141 DOI: 10.1371/journal.ppat.1003196] [Citation(s) in RCA: 158] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2012] [Accepted: 01/02/2013] [Indexed: 11/22/2022] Open
Abstract
Genetic variation contributes to host responses and outcomes following infection by influenza A virus or other viral infections. Yet narrow windows of disease symptoms and confounding environmental factors have made it difficult to identify polymorphic genes that contribute to differential disease outcomes in human populations. Therefore, to control for these confounding environmental variables in a system that models the levels of genetic diversity found in outbred populations such as humans, we used incipient lines of the highly genetically diverse Collaborative Cross (CC) recombinant inbred (RI) panel (the pre-CC population) to study how genetic variation impacts influenza associated disease across a genetically diverse population. A wide range of variation in influenza disease related phenotypes including virus replication, virus-induced inflammation, and weight loss was observed. Many of the disease associated phenotypes were correlated, with viral replication and virus-induced inflammation being predictors of virus-induced weight loss. Despite these correlations, pre-CC mice with unique and novel disease phenotype combinations were observed. We also identified sets of transcripts (modules) that were correlated with aspects of disease. In order to identify how host genetic polymorphisms contribute to the observed variation in disease, we conducted quantitative trait loci (QTL) mapping. We identified several QTL contributing to specific aspects of the host response including virus-induced weight loss, titer, pulmonary edema, neutrophil recruitment to the airways, and transcriptional expression. Existing whole-genome sequence data was applied to identify high priority candidate genes within QTL regions. A key host response QTL was located at the site of the known anti-influenza Mx1 gene. We sequenced the coding regions of Mx1 in the eight CC founder strains, and identified a novel Mx1 allele that showed reduced ability to inhibit viral replication, while maintaining protection from weight loss. Host responses to an infectious agent are highly variable across the human population, however, it is not entirely clear how various factors such as pathogen dose, demography, environment and host genetic polymorphisms contribute to variable host responses and infectious outcomes. In this study, a new in vivo experimental model was used that recapitulates many of the genetic characteristics of an outbred population, such as humans. By controlling viral dose, environment and demographic variables, we were able to focus on the role that host genetic variation plays in influenza virus infection. Both the range of disease phenotypes and the combinations of sets of disease phenotypes at 4 days post infection across this population exhibited a large amount of diversity, reminiscent of the variation seen across the human population. Multiple host genome regions were identified that contributed to different aspects of the host response to influenza infection. Taken together, these results emphasize the critical role of host genetics in the response to infectious diseases. Given the breadth of host responses seen within this population, several new models for unique host responses to infection were identified.
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Affiliation(s)
- Martin T Ferris
- Carolina Vaccine Institute, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, United States of America.
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Yang H, Wang JR, Didion JP, Buus RJ, Bell TA, Welsh CE, Bonhomme F, Yu AHT, Nachman MW, Pialek J, Tucker P, Boursot P, McMillan L, Churchill GA, de Villena FPM. Subspecific origin and haplotype diversity in the laboratory mouse. Nat Genet 2011; 43:648-55. [PMID: 21623374 PMCID: PMC3125408 DOI: 10.1038/ng.847] [Citation(s) in RCA: 336] [Impact Index Per Article: 25.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2010] [Accepted: 05/05/2011] [Indexed: 11/09/2022]
Abstract
Here we provide a genome-wide, high-resolution map of the phylogenetic origin of the genome of most extant laboratory mouse inbred strains. Our analysis is based on the genotypes of wild-caught mice from three subspecies of Mus musculus. We show that classical laboratory strains are derived from a few fancy mice with limited haplotype diversity. Their genomes are overwhelmingly Mus musculus domesticus in origin, and the remainder is mostly of Japanese origin. We generated genome-wide haplotype maps based on identity by descent from fancy mice and show that classical inbred strains have limited and non-randomly distributed genetic diversity. In contrast, wild-derived laboratory strains represent a broad sampling of diversity within M. musculus. Intersubspecific introgression is pervasive in these strains, and contamination by laboratory stocks has played a role in this process. The subspecific origin, haplotype diversity and identity by descent maps can be visualized using the Mouse Phylogeny Viewer (see URLs).
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Affiliation(s)
- Hyuna Yang
- The Jackson Laboratory, Bar Harbor, Maine, USA
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33
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Aylor DL, Valdar W, Foulds-Mathes W, Buus RJ, Verdugo RA, Baric RS, Ferris MT, Frelinger JA, Heise M, Frieman MB, Gralinski LE, Bell TA, Didion JD, Hua K, Nehrenberg DL, Powell CL, Steigerwalt J, Xie Y, Kelada SNP, Collins FS, Yang IV, Schwartz DA, Branstetter LA, Chesler EJ, Miller DR, Spence J, Liu EY, McMillan L, Sarkar A, Wang J, Wang W, Zhang Q, Broman KW, Korstanje R, Durrant C, Mott R, Iraqi FA, Pomp D, Threadgill D, de Villena FPM, Churchill GA. Genetic analysis of complex traits in the emerging Collaborative Cross. Genome Res 2011; 21:1213-22. [PMID: 21406540 DOI: 10.1101/gr.111310.110] [Citation(s) in RCA: 260] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The Collaborative Cross (CC) is a mouse recombinant inbred strain panel that is being developed as a resource for mammalian systems genetics. Here we describe an experiment that uses partially inbred CC lines to evaluate the genetic properties and utility of this emerging resource. Genome-wide analysis of the incipient strains reveals high genetic diversity, balanced allele frequencies, and dense, evenly distributed recombination sites-all ideal qualities for a systems genetics resource. We map discrete, complex, and biomolecular traits and contrast two quantitative trait locus (QTL) mapping approaches. Analysis based on inferred haplotypes improves power, reduces false discovery, and provides information to identify and prioritize candidate genes that is unique to multifounder crosses like the CC. The number of expression QTLs discovered here exceeds all previous efforts at eQTL mapping in mice, and we map local eQTL at 1-Mb resolution. We demonstrate that the genetic diversity of the CC, which derives from random mixing of eight founder strains, results in high phenotypic diversity and enhances our ability to map causative loci underlying complex disease-related traits.
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Affiliation(s)
- David L Aylor
- Department of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina 27599, USA
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Eversley CD, Clark T, Xie Y, Steigerwalt J, Bell TA, de Villena FPM, Threadgill DW. Genetic mapping and developmental timing of transmission ratio distortion in a mouse interspecific backcross. BMC Genet 2010; 11:98. [PMID: 21044349 PMCID: PMC2992037 DOI: 10.1186/1471-2156-11-98] [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] [Received: 05/23/2010] [Accepted: 11/03/2010] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Transmission ratio distortion (TRD), defined as statistically significant deviation from expected 1:1 Mendelian ratios of allele inheritance, results in a reduction of the expected progeny of a given genotype. Since TRD is a common occurrence within interspecific crosses, a mouse interspecific backcross was used to genetically map regions showing TRD, and a developmental analysis was performed to identify the timing of allele loss. RESULTS Three independent events of statistically significant deviation from the expected 50:50 Mendelian inheritance ratios were observed in an interspecific backcross between the Mus musculus A/J and the Mus spretus SPRET/EiJ inbred strains. At weaning M. musculus alleles are preferentially inherited on Chromosome (Chr) 7, while M. spretus alleles are preferentially inherited on Chrs 10 and 11. Furthermore, alleles on Chr 3 modify the TRD on Chr 11. All TRD loci detected at weaning were present in Mendelian ratios at mid-gestation and at birth. CONCLUSIONS Given that Mendelian ratios of inheritance are observed for Chr 7, 10 and 11 during development and at birth, the underlying causes for the interspecific TRD events are the differential post-natal survival of pups with specific genotypes. These results are consistent with the TRD mechanism being deviation from Mendelian inheritance rather than meiotic drive or segregation distortion.
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Affiliation(s)
- Chevonne D Eversley
- Department of Genetics, Curriculum in Genetics and Molecular Biology, and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC 27599, USA
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Abstract
The method previously developed by us for the pure-culture fermentation of brined cucumbers and other vegetables has been applied successfully to Manzanillo variety olives. Field-run grade fruit was processed first by conventional procedures to remove most of the bitterness. Then the relative abilities of Lactobacillus plantarum, L. brevis, Pediococcus cerevisiae, and Leuconostoc mesenteroides to become established and produce acid in both heat-shocked (74 C for 3 min) and unheated olives, brined at 4.7 to 5.9% NaCl (w/v basis), were evaluated. The heat-shock treatment not only proved effective in ridding the fruit of naturally occurring, interfering, and competitive microbial groups prior to brining and inoculation, but also made the olives highly fermentable with respect to growth and acid production by the introduced culture, particularly L. plantarum. Of the four species used as inocula, L. plantarum was by far the most vigorous in fermentation ability. It consistently produced the highest levels of brine acidity (1.0 to 1.2% calculated as lactic acid) and the lowest pH values (3.8 to 3.9) during the fermentation of heat-shocked olives. Also, L. plantarum completely dominated fermentations when used in two-species (with P. cerevisiae) and three-species (with P. cerevisiae and L. brevis) combinations as inocula. In contrast, when L. plantarum was inoculated into the brines of unheated olives it failed to become properly established; the same was true for the other species tested, but even to a more pronounced degree. L. brevis was the only species used that failed to develop in brines of both heat-shocked and unheated olives. Modification of the curing brine by the addition of lactic acid at the outset, either with or without dextrose, led to a much earlier onset of fermentation with accompanying acid development, as compared to treatments with dextrose alone or nonadditive controls. Reasons for the marked improvement of the fermentability of Manzanillo olives receiving the prebrining heat-shock treatment are discussed.
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Affiliation(s)
- J L Etchells
- U.S. Food Fermentation Laboratory, Southern Utilization Research and Development Division, U.S. Department of Agriculture, Raleigh, North Carolina
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Vemuganti SA, Bell TA, Scarlett CO, Parker CE, de Villena FPM, O'Brien DA. Three male germline-specific aldolase A isozymes are generated by alternative splicing and retrotransposition. Dev Biol 2007; 309:18-31. [PMID: 17659271 DOI: 10.1016/j.ydbio.2007.06.010] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.0] [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] [Received: 04/27/2007] [Revised: 06/09/2007] [Accepted: 06/12/2007] [Indexed: 10/23/2022]
Abstract
Enzymes in the glycolytic pathway of mammalian sperm are modified extensively and are localized in the flagellum, where several are tightly bound to the fibrous sheath. This study provides the first evidence for three novel aldolase isozymes in mouse sperm, two encoded by Aldoart1 and Aldoart2 retrogenes on different chromosomes and another by Aldoa_v2, a splice variant of Aldoa. Phylogenetic analyses and comparative genomics indicate that the retrogenes and splice variant have remained functional and have been under positive selection for millions of years. Their expression is restricted to the male germline and is tightly regulated at both transcriptional and translational levels. All three isozymes are present only in spermatids and sperm and have distinctive features that may be important for localization in the flagellum and/or altered metabolic regulation. Both ALDOART1 and ALDOA_V2 have unusual N-terminal extensions not found in other aldolases. The N-terminal extension of ALDOA_V2 is highly conserved in mammals, suggesting a conserved function in sperm. We hypothesize that the N-terminal extensions are responsible for localizing components of the glycolytic pathway to the fibrous sheath and that this localization is required to provide sufficient ATP along the length of the flagellum to support sperm motility.
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Affiliation(s)
- Soumya A Vemuganti
- Laboratories for Reproductive Biology, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA
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37
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Yang H, Bell TA, Churchill GA, Pardo-Manuel de Villena F. On the subspecific origin of the laboratory mouse. Nat Genet 2007; 39:1100-7. [PMID: 17660819 DOI: 10.1038/ng2087] [Citation(s) in RCA: 236] [Impact Index Per Article: 13.9] [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] [Received: 02/13/2007] [Accepted: 05/31/2007] [Indexed: 01/20/2023]
Abstract
The genome of the laboratory mouse is thought to be a mosaic of regions with distinct subspecific origins. We have developed a high-resolution map of the origin of the laboratory mouse by generating 25,400 phylogenetic trees at 100-kb intervals spanning the genome. On average, 92% of the genome is of Mus musculus domesticus origin, and the distribution of diversity is markedly nonrandom among the chromosomes. There are large regions of extremely low diversity, which represent blind spots for studies of natural variation and complex traits, and hot spots of diversity. In contrast with the mosaic model, we found that most of the genome has intermediate levels of variation of intrasubspecific origin. Finally, mouse strains derived from the wild that are supposed to represent different mouse subspecies show substantial intersubspecific introgression, which has strong implications for evolutionary studies that assume these are pure representatives of a given subspecies.
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Affiliation(s)
- Hyuna Yang
- The Jackson Laboratory, Bar Harbor, Maine 04609, USA
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38
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Abstract
The relative abilities of Pediococcus cerevisiae, Lactobacillus plantarum, L. brevis, and several other species of lactic acid bacteria to grow and produce acid in brined cucumbers were evaluated in pure culture fermentations. Such fermentations were made possibly by the use of two techniques, gamma radiation (0.83 to 1.00 Mrad) and hot-water blanching (66 to 80 C for 5 min), designed first to rid the cucumbers of naturally occurring, interfering, and competitive microbial groups prior to brining, followed by inoculation with the desired lactic acid bacteria. Of the nine species tested, strains of the three common to cucumber fermentations, P. cerevisiae, L. plantarum, and L. brevis, grew to the highest populations, and produced the highest levels of brine acidity and the lowest pH values in fermentations at 5.4 to 5.6% NaCl by weight; also, their sequence of active development in fermentations, with the use of a three-species mixture for inoculation, was in the species order just named. This sequence of occurrence was similar to that estimated by others for natural fermentations. The rates of growth and acid production in fermentations with a mixture of P. cerevisiae, L. plantarum, and L. brevis increased as the incubation temperature was increased from 21 to 27 to 32 C; however, the maximal populations and acidities attained were essentially the same for fermentations at each temperature. Further, these same three species were found to be the most salt tolerant of those tested; their upper limit for appreciable growth and measurable acid production was about 8% salt, whereas thermophilic species such as L. thermophilus, L. lactis, L. helveticus, L. fermenti, and L. delbrueckii exhibited a much lower salt tolerance, ranging from about 2.5 to 4.0%. However, certain strains of L. delbrueckii grew very rapidly in cucumbers brined at 2.5 to 3.0% salt, and produced sufficient acid in about 30 hr at 48 C to reduce the brine pH from above 7.0 to below 4.0. An inexpensive, pure culture fermentor which was suitable for gamma radiation, resistant to salt and acid, and which permitted repeated aseptic sampling of the fermenting brine, is illustrated and the specifications are given.
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Affiliation(s)
- J L Etchells
- Fermentation Laboratory, U.S. Department of Agriculture and Department of Food Science, North Carolina Agricultural Experiment Station, Raleigh, North Carolina
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Bell TA, de la Casa-Esperón E, Doherty HE, Ideraabdullah F, Kim K, Wang Y, Lange LA, Wilhemsen K, Lange EM, Sapienza C, de Villena FPM. The paternal gene of the DDK syndrome maps to the Schlafen gene cluster on mouse chromosome 11. Genetics 2005; 172:411-23. [PMID: 16172501 PMCID: PMC1456169 DOI: 10.1534/genetics.105.047118] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.5] [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: 11/18/2022] Open
Abstract
The DDK syndrome is an early embryonic lethal phenotype observed in crosses between females of the DDK inbred mouse strain and many non-DDK males. Lethality results from an incompatibility between a maternal DDK factor and a non-DDK paternal gene, both of which have been mapped to the Ovum mutant (Om) locus on mouse chromosome 11. Here we define a 465-kb candidate interval for the paternal gene by recombinant progeny testing. To further refine the candidate interval we determined whether males from 17 classical and wild-derived inbred strains are interfertile with DDK females. We conclude that the incompatible paternal allele arose in the Mus musculus domesticus lineage and that incompatible strains should share a common haplotype spanning the paternal gene. We tested for association between paternal allele compatibility/incompatibility and 167 genetic variants located in the candidate interval. Two diallelic SNPs, located in the Schlafen gene cluster, are completely predictive of the polar-lethal phenotype. These SNPs also predict the compatible or incompatible status of males of five additional strains.
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Affiliation(s)
- Timothy A Bell
- Department of Pathology and Laboratory Medicine, Temple University School of Medicine, Philadelphia, Pennsylvania 19140, USA
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Ideraabdullah FY, de la Casa-Esperón E, Bell TA, Detwiler DA, Magnuson T, Sapienza C, de Villena FPM. Genetic and haplotype diversity among wild-derived mouse inbred strains. Genome Res 2004; 14:1880-7. [PMID: 15466288 PMCID: PMC524411 DOI: 10.1101/gr.2519704] [Citation(s) in RCA: 79] [Impact Index Per Article: 4.0] [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: 11/24/2022]
Abstract
With the completion of the mouse genome sequence, it is possible to define the amount, type, and organization of the genetic variation in this species. Recent reports have provided an overview of the structure of genetic variation among classical laboratory mice. On the other hand, little is known about the structure of genetic variation among wild-derived strains with the exception of the presence of higher levels of diversity. We have estimated the sequence diversity due to substitutions and insertions/deletions among 20 inbred strains of Mus musculus, chosen to enable interpretation of the molecular variation within a clear evolutionary framework. Here, we show that the level of sequence diversity present among these strains is one to two orders of magnitude higher than the level of sequence diversity observed in the human population, and only a minor fraction of the sequence differences observed is found among classical laboratory strains. Our analyses also demonstrate that deletions are significantly more frequent than insertions. We estimate that 50% of the total variation identified in M. musculus may be recovered in intrasubspecific crosses. Alleles at variants positions can be classified into 164 strain distribution patterns, a number exceeding those reported and predicted in panels of classical inbred strains. The number of strains, the analysis of multiple loci scattered across the genome, and the mosaic nature of the genome in hybrid and classical strains contribute to the observed diversity of strain distribution patterns. However, phylogenetic analyses demonstrate that ancient polymorphisms that segregate across species and subspecies play a major role in the generation of strain distribution patterns.
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Affiliation(s)
- Folami Y Ideraabdullah
- Department of Genetics, University of North Carolina at Chapel Hill, North Carolina 27599, USA
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Wilson W, Pardo-Manuel de Villena F, Lyn-Cook BD, Chatterjee PK, Bell TA, Detwiler DA, Gilmore RC, Valladeras IC, Wright CC, Threadgill DW, Grant DJ. Characterization of a common deletion polymorphism of the UGT2B17 gene linked to UGT2B15. Genomics 2004; 84:707-14. [PMID: 15475248 DOI: 10.1016/j.ygeno.2004.06.011] [Citation(s) in RCA: 105] [Impact Index Per Article: 5.3] [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] [Received: 02/20/2004] [Accepted: 06/23/2004] [Indexed: 10/26/2022]
Abstract
Members of the human UDP-glucuronosyltransferase 2B family are located in a cluster on chromosome 4q13 and code for enzymes whose gene products are responsible for the normal catabolism of steroid hormones. Two members of this family, UGT2B15 and UGT2B17, share over 95% sequence identity. However, UGT2B17 exhibits broader substrate specificity due to a single amino acid difference. Using gene-specific primers to explore the genomic organization of these two genes, it was determined that UGT2B17 is absent in some human DNA samples. The gene-specific primers demonstrated the presence or absence of a 150 kb genomic interval spanning the entire UGT2B17 gene, revealing that UGT2B17 is present in the human genome as a deletion polymorphism linked to UGT2B15. Furthermore, it is shown that the UGT2B17 deletion polymorphism shows Mendelian segregation and allele frequencies that differ between African Americans and Caucasians.
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Affiliation(s)
- Willie Wilson
- Cancer Research Program, JLC-Biomedical/Biotechnology Research Institute, North Carolina Central University, 1801 Fayetteville Street, Durham, NC 27707, USA
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Jewell ML, Gold AH, Bell TA, Narins RS. Treatment of the nasolabial folds. Aesthet Surg J 2001; 21:537-44. [PMID: 19331940 DOI: 10.1067/maj.2001.121284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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Johnson KR, Braden CR, Cairns KL, Field KW, Colombel AC, Yang Z, Woodley CL, Morlock GP, Weber AM, Boudreau AY, Bell TA, Onorato IM, Valway SE, Stehr-Green PA. Transmission of Mycobacterium tuberculosis from medical waste. JAMA 2000; 284:1683-8. [PMID: 11015799 DOI: 10.1001/jama.284.13.1683] [Citation(s) in RCA: 39] [Impact Index Per Article: 1.6] [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: 11/14/2022]
Abstract
CONTEXT Washington State has a relatively low incidence rate of tuberculosis (TB) infection. However, from May to September 1997, 3 cases of pulmonary TB were reported among medical waste treatment workers at 1 facility in Washington. There is no previous documentation of Mycobacterium tuberculosis transmission as a result of processing medical waste. OBJECTIVE To identify the source(s) of these 3 TB infections. DESIGN, SETTING, AND PARTICIPANTS Interviews of the 3 infected patient-workers and their contacts, review of patient-worker medical records and the state TB registry, and collection of all multidrug-resistant TB (MDR-TB) isolates identified after January 1, 1995, from the facility's catchment area; DNA fingerprinting of all isolates; polymerase chain reaction and automated DNA sequencing to determine genetic mutations associated with drug resistance; and occupational safety and environmental evaluations of the facility. MAIN OUTCOME MEASURES Previous exposures of patient-workers to TB; verification of patient-worker tuberculin skin test histories; identification of other cases of TB in the community and at the facility; drug susceptibility of patient-worker isolates; and potential for worker exposure to live M tuberculosis cultures. RESULTS All 3 patient-workers were younger than 55 years, were born in the United States, and reported no known exposures to TB. We did not identify other TB cases. The 3 patient-workers' isolates had different DNA fingerprints. One of 10 MDR-TB catchment-area isolates matched an MDR-TB patient-worker isolate by DNA fingerprint pattern. DNA sequencing demonstrated the same rare mutation in these isolates. There was no evidence of personal contact between these 2 individuals. The laboratory that initially processed the matching isolate sent contaminated waste to the treatment facility. The facility accepted contaminated medical waste where it was shredded, blown, compacted, and finally deactivated. Equipment failures, insufficient employee training, and respiratory protective equipment inadequacies were identified at the facility. CONCLUSION Processing contaminated medical waste resulted in transmission of M tuberculosis to at least 1 medical waste treatment facility worker. JAMA. 2000;284:1683-1688.
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Affiliation(s)
- K R Johnson
- Centers for Disease Control and Prevention, 1600 Clifton Rd NE, MS E-23, Atlanta, GA 30333, USA.
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Oriani JA, Bell TA. Performance of field trials and data collection as part of the Investigational New Animal Drug Application (INAD). Vet Hum Toxicol 1998; 40 Suppl 2:43-7. [PMID: 9823585] [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] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Affiliation(s)
- J A Oriani
- Office of New Animal Drug Evaluation, Food and Drug Administration, Center for Veterinary Medicine, Rockville, MD 20855, USA
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Greenlees KJ, Bell TA. Aquaculture crop grouping and new animal drug approvals: a CVM perspective. Vet Hum Toxicol 1998; 40 Suppl 2:19-23. [PMID: 9823578] [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] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Affiliation(s)
- K J Greenlees
- Office of New Animal Drug Evaluation, Center for Veterinary Medicine, US Food and Drug Administration, Rockville, MD 20855, USA
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Affiliation(s)
- T A Bell
- Cowlitz County Health Department, Longview, WA, USA
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Feise HJ, Bell TA. 8. Ein einfaches Modell für den Volumenstrom einer Förderschnecke. CHEM-ING-TECH 1998. [DOI: 10.1002/cite.330700912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Affiliation(s)
- V J Kattapong
- Department of Health Services and Preventive Medicine Residency, School of Public Health and Community Medicine, University of Washington, Seattle 98195, USA
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Fischer M, Hedberg K, Cardosi P, Plikaytis BD, Hoesly FC, Steingart KR, Bell TA, Fleming DW, Wenger JD, Perkins BA. Tobacco smoke as a risk factor for meningococcal disease. Pediatr Infect Dis J 1997; 16:979-83. [PMID: 9380476 DOI: 10.1097/00006454-199710000-00015] [Citation(s) in RCA: 138] [Impact Index Per Article: 5.1] [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: 02/05/2023]
Abstract
BACKGROUND Since 1992 the US Pacific Northwest has experienced a substantial increase in the incidence of serogroup B meningococcal disease. The current meningococcal polysaccharide vaccine is poorly immunogenic in young children and does not protect against N. meningitidis serogroup B. Defining alternative approaches to the prevention and control of meningococcal disease is of considerable public health importance. METHODS We performed a case-control study comparing 129 patients in Oregon and southwest Washington with 274 age- and area-matched controls. We used conditional logistic regression analysis to determine which exposures remained associated with disease after adjusting for other risk factors and confounders and calculated the proportion of disease attributable to modifiable exposures. RESULTS After adjustment for all other significant exposures identified, having a mother who smokes was the strongest independent risk factor for invasive meningococcal disease in children < 18 years of age [odds ratio (OR), 3.8; 95% confidence interval (CI) 1.6 to 8.9)], with 37% (CI 15 to 65) of all cases in this age group potentially attributable to maternal smoking. Adult patients were more likely than controls to have a chronic underlying illness (OR 10.8, CI 2.7 to 43.3), passive tobacco smoke exposure (OR 2.5, CI 0.9 to 6.9) and to smoke tobacco (OR 2.4, CI 0.9 to 6.6). Dose-response effects were seen for passive smoke exposure and risk of disease in all age groups. CONCLUSION Tobacco smoke exposure independently increases the risk of developing meningococcal disease.
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Affiliation(s)
- M Fischer
- Division of Bacterial and Mycotic Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA
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Affiliation(s)
- T A Bell
- Lewis County Department of Human Services, Chehalis, WA, USA
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