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Kleiman NJ, Edmondson EF, Weil MM, Fallgren CM, King A, Schmidt C, Hall EJ. Radiation cataract in Heterogeneous Stock mice after γ-ray or HZE ion exposure. LIFE SCIENCES IN SPACE RESEARCH 2024; 40:97-105. [PMID: 38245354 PMCID: PMC10800003 DOI: 10.1016/j.lssr.2023.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 09/12/2023] [Accepted: 09/13/2023] [Indexed: 01/22/2024]
Abstract
Health effects of space radiation are a serious concern for astronauts on long-duration missions. The lens of the eye is one of the most radiosensitive tissues in the body and, therefore, ocular health risks for astronauts is a significant concern. Studies in humans and animals indicate that ionizing radiation exposure to the eye produces characteristic lens changes, termed "radiation cataract," that can affect visual function. Animal models of radiation cataractogenesis have previously utilized inbred mouse or rat strains. These studies were essential for determining morphological changes and dose-response relationships between radiation exposure and cataract. However, the relevance of these studies to human radiosensitivity is limited by the narrow phenotypic range of genetically homogeneous animal models. To model radiation cataract in genetically diverse populations, longitudinal cataract phenotyping was nested within a lifetime carcinogenesis study in male and female heterogeneous stock (HS/Npt) mice exposed to 0.4 Gy HZE ions (n = 609) or 3.0 Gy γ-rays (n = 602) and in unirradiated controls (n = 603). Cataractous change was quantified in each eye for up to 2 years using Merriam-Focht grading criteria by dilated slit lamp examination. Virtual Optomotry™ measurement of visual acuity and contrast sensitivity was utilized to assess visual function in a subgroup of mice. Prevalence and severity of posterior lens opacifications were 2.6-fold higher in HZE ion and 2.3-fold higher in γ-ray irradiated mice compared to unirradiated controls. Male mice were at greater risk for spontaneous and radiation associated cataracts. Risk for cataractogenesis was associated with family structure, demonstrating that HS/Npt mice are well-suited to evaluate genetic determinants of ocular radiosensitivity. Last, mice were extensively evaluated for cataract and tumor formation, which revealed an overlap between individual susceptibility to both cancer and cataract.
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Affiliation(s)
- Norman J Kleiman
- Department of Environmental Health Sciences, Eye Radiation and Environmental Research Laboratory, Columbia University, Mailman School of Public Health, 722 West 168th St., 11th Floor, New York, NY, 10032, United States.
| | - Elijah F Edmondson
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, 80523, United States; Frederick National Laboratory for Cancer Research, Frederick, Maryland, 21702, United States
| | - Michael M Weil
- Department of Environment and Radiological Health Sciences, Colorado State University, Fort Collins, CO, 80523, United States
| | - Christina M Fallgren
- Department of Environment and Radiological Health Sciences, Colorado State University, Fort Collins, CO, 80523, United States
| | - Adam King
- Department of Clinical Sciences, Colorado State University, Fort Collins, CO, 80523, United States; MedVet Chicago, Chicago, IL, 60618, United States
| | - Catherine Schmidt
- Department of Clinical Sciences, Colorado State University, Fort Collins, CO, 80523, United States; Veterinary Eye Specialists, Thornwood, NY, 10594, , United States
| | - Eric J Hall
- Center for Radiological Research, Columbia University, College of Physicians and Surgeons, 630W. 168th St., New York, NY,10032, , United States
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2
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Yosief RHS, Lone IM, Nachshon A, Himmelbauer H, Gat‐Viks I, Iraqi FA. Identifying genetic susceptibility to Aspergillus fumigatus infection using collaborative cross mice and RNA-Seq approach. Animal Model Exp Med 2024; 7:36-47. [PMID: 38356021 PMCID: PMC10961901 DOI: 10.1002/ame2.12386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 12/15/2023] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND Aspergillus fumigatus (Af) is one of the most ubiquitous fungi and its infection potency is suggested to be strongly controlled by the host genetic background. The aim of this study was to search for candidate genes associated with host susceptibility to Aspergillus fumigatus (Af) using an RNAseq approach in CC lines and hepatic gene expression. METHODS We studied 31 male mice from 25 CC lines at 8 weeks old; the mice were infected with Af. Liver tissues were extracted from these mice 5 days post-infection, and next-generation RNA-sequencing (RNAseq) was performed. The GENE-E analysis platform was used to generate a clustered heat map matrix. RESULTS Significant variation in body weight changes between CC lines was observed. Hepatic gene expression revealed 12 top prioritized candidate genes differentially expressed in resistant versus susceptible mice based on body weight changes. Interestingly, three candidate genes are located within genomic intervals of the previously mapped quantitative trait loci (QTL), including Gm16270 and Stox1 on chromosome 10 and Gm11033 on chromosome 8. CONCLUSIONS Our findings emphasize the CC mouse model's power in fine mapping the genetic components underlying susceptibility towards Af. As a next step, eQTL analysis will be performed for our RNA-Seq data. Suggested candidate genes from our study will be further assessed with a human cohort with aspergillosis.
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Affiliation(s)
- Roa'a H. S. Yosief
- Department of Clinical Microbiology and Immunology, Sackler Faculty of MedicineTel‐Aviv UniversityTel‐AvivIsrael
| | - Iqbal M. Lone
- Department of Clinical Microbiology and Immunology, Sackler Faculty of MedicineTel‐Aviv UniversityTel‐AvivIsrael
| | - Aharon Nachshon
- School of Molecular Cell Biology and Biotechnology, George S. Wise Faculty of Life SciencesTel Aviv UniversityTel AvivIsrael
| | - Heinz Himmelbauer
- Institute of Computational Biology, Department of Biotechnology, University of Natural Resources and Life Sciences, Muthgasse 181190 ViennaAustria
| | - Irit Gat‐Viks
- School of Molecular Cell Biology and Biotechnology, George S. Wise Faculty of Life SciencesTel Aviv UniversityTel AvivIsrael
| | - Fuad A. Iraqi
- Department of Clinical Microbiology and Immunology, Sackler Faculty of MedicineTel‐Aviv UniversityTel‐AvivIsrael
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3
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Philip VM, He H, Saul MC, Dickson PE, Bubier JA, Chesler EJ. Gene expression genetics of the striatum of Diversity Outbred mice. Sci Data 2023; 10:522. [PMID: 37543624 PMCID: PMC10404230 DOI: 10.1038/s41597-023-02426-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 07/28/2023] [Indexed: 08/07/2023] Open
Abstract
Brain transcriptional variation is a heritable trait that mediates complex behaviors, including addiction. Expression quantitative trait locus (eQTL) mapping reveals genomic regions harboring genetic variants that influence transcript abundance. In this study, we profiled transcript abundance in the striatum of 386 Diversity Outbred (J:DO) mice of both sexes using RNA-Seq. All mice were characterized using a behavioral battery of widely-used exploratory and risk-taking assays prior to transcriptional profiling. We performed eQTL mapping, incorporated the results into a browser-based eQTL viewer, and deposited co-expression network members in GeneWeaver. The eQTL viewer allows researchers to query specific genes to obtain allelic effect plots, analyze SNP associations, assess gene expression correlations, and apply mediation analysis to evaluate whether the regulatory variant is acting through the expression of another gene. GeneWeaver allows multi-species comparison of gene sets using statistical and combinatorial tools. This data resource allows users to find genetic variants that regulate differentially expressed transcripts and place them in the context of other studies of striatal gene expression and function in addiction-related behavior.
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Affiliation(s)
- Vivek M Philip
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, 04605, USA
| | - Hao He
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Michael C Saul
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, 04605, USA
| | - Price E Dickson
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine Marshall University, Huntington, WV, 25703, USA
| | - Jason A Bubier
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, 04605, USA
| | - Elissa J Chesler
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, 04605, USA.
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4
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Philip VM, He H, Saul MC, Dickson PE, Bubier JA, Chesler EJ. Gene expression genetics of the striatum of Diversity Outbred mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.11.540390. [PMID: 37214980 PMCID: PMC10197688 DOI: 10.1101/2023.05.11.540390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Brain transcriptional variation is a heritable trait that mediates complex behaviors, including addiction. Expression quantitative trait locus (eQTL) mapping reveals genomic regions harboring genetic variants that influence transcript abundance. In this study, we profiled transcript abundance in the striatum of 386 Diversity Outbred (J:DO) mice of both sexes using RNA-Seq. All mice were characterized using a behavioral battery of widely-used exploratory and risk-taking assays prior to transcriptional profiling. We performed eQTL mapping, incorporated the results into a browser-based eQTL viewer, and deposited co-expression network members in GeneWeaver. The eQTL viewer allows researchers to query specific genes to obtain allelic effect plots, analyze SNP associations, assess gene expression correlations, and apply mediation analysis to evaluate whether the regulatory variant is acting through the expression of another gene. GeneWeaver allows multi-species comparison of gene sets using statistical and combinatorial tools. This data resource allows users to find genetic variants that regulate differentially expressed transcripts and place them in the context of other studies of striatal gene expression and function in addiction-related behavior.
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Affiliation(s)
- Vivek M. Philip
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME 04605
| | - Hao He
- The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032
| | - Michael C. Saul
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME 04605
| | - Price E. Dickson
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine Marshall University, 1700 3rd Ave. Huntington, WV 25703
| | - Jason A. Bubier
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME 04605
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5
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Huynh K, Smith BR, Macdonald SJ, Long AD. Genetic variation in chromatin state across multiple tissues in Drosophila melanogaster. PLoS Genet 2023; 19:e1010439. [PMID: 37146087 PMCID: PMC10191298 DOI: 10.1371/journal.pgen.1010439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 05/17/2023] [Accepted: 04/20/2023] [Indexed: 05/07/2023] Open
Abstract
We use ATAC-seq to examine chromatin accessibility for four different tissues in Drosophila melanogaster: adult female brain, ovaries, and both wing and eye-antennal imaginal discs from males. Each tissue is assayed in eight different inbred strain genetic backgrounds, seven associated with a reference quality genome assembly. We develop a method for the quantile normalization of ATAC-seq fragments and test for differences in coverage among genotypes, tissues, and their interaction at 44099 peaks throughout the euchromatic genome. For the strains with reference quality genome assemblies, we correct ATAC-seq profiles for read mis-mapping due to nearby polymorphic structural variants (SVs). Comparing coverage among genotypes without accounting for SVs results in a highly elevated rate (55%) of identifying false positive differences in chromatin state between genotypes. After SV correction, we identify 1050, 30383, and 4508 regions whose peak heights are polymorphic among genotypes, among tissues, or exhibit genotype-by-tissue interactions, respectively. Finally, we identify 3988 candidate causative variants that explain at least 80% of the variance in chromatin state at nearby ATAC-seq peaks.
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Affiliation(s)
- Khoi Huynh
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California, United States of America
| | - Brittny R. Smith
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America
| | - Stuart J. Macdonald
- Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas, United States of America
- Center for Computational Biology, University of Kansas, Lawrence, Kansas, United States of America
| | - Anthony D. Long
- Department of Ecology and Evolutionary Biology, University of California, Irvine, California, United States of America
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Garretson A, Dumont BL, Handel MA. Reproductive genomics of the mouse: implications for human fertility and infertility. Development 2023; 150:dev201313. [PMID: 36779988 PMCID: PMC10836652 DOI: 10.1242/dev.201313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/14/2023]
Abstract
Genetic analyses of mammalian gametogenesis and fertility have the potential to inform about two important and interrelated clinical areas: infertility and contraception. Here, we address the genetics and genomics underlying gamete formation, productivity and function in the context of reproductive success in mammalian systems, primarily mouse and human. Although much is known about the specific genes and proteins required for meiotic processes and sperm function, we know relatively little about other gametic determinants of overall fertility, such as regulation of gamete numbers, duration of gamete production, and gamete selection and function in fertilization. As fertility is not a binary trait, attention is now appropriately focused on the oligogenic, quantitative aspects of reproduction. Multiparent mouse populations, created by complex crossing strategies, exhibit genetic diversity similar to human populations and will be valuable resources for genetic discovery, helping to overcome current limitations to our knowledge of mammalian reproductive genetics. Finally, we discuss how what we know about the genomics of reproduction can ultimately be brought to the clinic, informing our concepts of human fertility and infertility, and improving assisted reproductive technologies.
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Affiliation(s)
- Alexis Garretson
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
- Tufts University, Graduate School of Biomedical Sciences, 136 Harrison Ave, Boston, MA 02111, USA
| | - Beth L. Dumont
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
- Tufts University, Graduate School of Biomedical Sciences, 136 Harrison Ave, Boston, MA 02111, USA
| | - Mary Ann Handel
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
- Tufts University, Graduate School of Biomedical Sciences, 136 Harrison Ave, Boston, MA 02111, USA
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7
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Tabbaa M, Knoll A, Levitt P. Mouse population genetics phenocopies heterogeneity of human Chd8 haploinsufficiency. Neuron 2023; 111:539-556.e5. [PMID: 36738737 PMCID: PMC9960295 DOI: 10.1016/j.neuron.2023.01.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 11/13/2022] [Accepted: 01/11/2023] [Indexed: 02/05/2023]
Abstract
Preclinical models of neurodevelopmental disorders typically use single inbred mouse strains, which fail to capture the genetic diversity and symptom heterogeneity that is common clinically. We tested whether modeling genetic background diversity in mouse genetic reference panels would recapitulate population and individual differences in responses to a syndromic mutation in the high-confidence autism risk gene, CHD8. We measured clinically relevant phenotypes in >1,000 mice from 33 strains, including brain and body weights and cognition, activity, anxiety, and social behaviors, using 5 behavioral assays: cued fear conditioning, open field tests in dark and bright light, direct social interaction, and social dominance. Trait disruptions mimicked those seen clinically, with robust strain and sex differences. Some strains exhibited large effect-size trait disruptions, sometimes in opposite directions, and-remarkably-others expressed resilience. Therefore, systematically introducing genetic diversity into models of neurodevelopmental disorders provides a better framework for discovering individual differences in symptom etiologies.
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Affiliation(s)
- Manal Tabbaa
- Children's Hospital Los Angeles, The Saban Research Institute, Los Angeles, CA 90027, USA; Keck School of Medicine of the University of Southern California, Los Angeles, CA 90033, USA
| | - Allison Knoll
- Children's Hospital Los Angeles, The Saban Research Institute, Los Angeles, CA 90027, USA; Keck School of Medicine of the University of Southern California, Los Angeles, CA 90033, USA
| | - Pat Levitt
- Children's Hospital Los Angeles, The Saban Research Institute, Los Angeles, CA 90027, USA; Keck School of Medicine of the University of Southern California, Los Angeles, CA 90033, USA.
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8
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Genetic Mapping of Behavioral Traits Using the Collaborative Cross Resource. Int J Mol Sci 2022; 24:ijms24010682. [PMID: 36614124 PMCID: PMC9821145 DOI: 10.3390/ijms24010682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 12/14/2022] [Accepted: 12/23/2022] [Indexed: 01/03/2023] Open
Abstract
The complicated interactions between genetic background, environment and lifestyle factors make it difficult to study the genetic basis of complex phenotypes, such as cognition and anxiety levels, in humans. However, environmental and other factors can be tightly controlled in mouse studies. The Collaborative Cross (CC) is a mouse genetic reference population whose common genetic and phenotypic diversity is on par with that of humans. Therefore, we leveraged the power of the CC to assess 52 behavioral measures associated with locomotor activity, anxiety level, learning and memory. This is the first application of the CC in novel object recognition tests, Morris water maze tasks, and fear conditioning tests. We found substantial continuous behavioral variations across the CC strains tested, and mapped six quantitative trait loci (QTLs) which influenced these traits, defining candidate genetic variants underlying these QTLs. Overall, our findings highlight the potential of the CC population in behavioral genetic research, while the identified genomic loci and genes driving the variation of relevant behavioral traits provide a foundation for further studies.
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9
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Bagley JR, Bailey LS, Gagnon LH, He H, Philip VM, Reinholdt LG, Tarantino LM, Chesler EJ, Jentsch JD. Behavioral phenotypes revealed during reversal learning are linked with novel genetic loci in diversity outbred mice. ADDICTION NEUROSCIENCE 2022; 4:100045. [PMID: 36714272 PMCID: PMC9879139 DOI: 10.1016/j.addicn.2022.100045] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Impulsive behavior and impulsivity are heritable phenotypes that are strongly associated with risk for substance use disorders. Identifying the neurogenetic mechanisms that influence impulsivity may also reveal novel biological insights into addiction vulnerability. Our past studies using the BXD and Collaborative Cross (CC) recombinant inbred mouse panels have revealed that behavioral indicators of impulsivity measured in a reversal-learning task are heritable and are genetically correlated with aspects of intravenous cocaine self-administration. Genome-wide linkage studies in the BXD panel revealed a quantitative trait locus (QTL) on chromosome 10, but we expect to identify additional QTL by testing in a population with more genetic diversity. To this end, we turned to Diversity Outbred (DO) mice; 392 DO mice (156 males, 236 females) were phenotyped using the same reversal learning test utilized previously. Our primary indicator of impulsive responding, a measure that isolates the relative difficulty mice have with reaching performance criteria under reversal conditions, revealed a genome-wide significant QTL on chromosome 7 (max LOD score = 8.73, genome-wide corrected p<0.05). A measure of premature responding akin to that implemented in the 5-choice serial reaction time task yielded a suggestive QTL on chromosome 17 (max LOD score = 9.14, genome-wide corrected <0.1). Candidate genes were prioritized (2900076A07Rik, Wdr73 and Zscan2) based upon expression QTL data we collected in DO and CC mice and analyses using publicly available gene expression and phenotype databases. These findings may advance understanding of the genetics that drive impulsive behavior and enhance risk for substance use disorders.
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Affiliation(s)
- Jared R. Bagley
- Department of Psychology, Binghamton University, Binghamton, NY, USA
- Center for Systems Neurogenetics of Addiction at The Jackson Laboratory, Bar Harbor, ME, USA
| | - Lauren S. Bailey
- Department of Psychology, Binghamton University, Binghamton, NY, USA
- Center for Systems Neurogenetics of Addiction at The Jackson Laboratory, Bar Harbor, ME, USA
| | - Leona H. Gagnon
- Center for Systems Neurogenetics of Addiction at The Jackson Laboratory, Bar Harbor, ME, USA
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - Hao He
- Center for Systems Neurogenetics of Addiction at The Jackson Laboratory, Bar Harbor, ME, USA
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - Vivek M. Philip
- Center for Systems Neurogenetics of Addiction at The Jackson Laboratory, Bar Harbor, ME, USA
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - Laura G. Reinholdt
- Center for Systems Neurogenetics of Addiction at The Jackson Laboratory, Bar Harbor, ME, USA
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - Lisa M. Tarantino
- Center for Systems Neurogenetics of Addiction at The Jackson Laboratory, Bar Harbor, ME, USA
- Department of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, USA
| | - Elissa J. Chesler
- Center for Systems Neurogenetics of Addiction at The Jackson Laboratory, Bar Harbor, ME, USA
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - James D. Jentsch
- Department of Psychology, Binghamton University, Binghamton, NY, USA
- Center for Systems Neurogenetics of Addiction at The Jackson Laboratory, Bar Harbor, ME, USA
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10
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Olatunde AC, Cornwall DH, Roedel M, Lamb TJ. Mouse Models for Unravelling Immunology of Blood Stage Malaria. Vaccines (Basel) 2022; 10:1525. [PMID: 36146602 PMCID: PMC9501382 DOI: 10.3390/vaccines10091525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2022] [Revised: 09/05/2022] [Accepted: 09/06/2022] [Indexed: 11/16/2022] Open
Abstract
Malaria comprises a spectrum of disease syndromes and the immune system is a major participant in malarial disease. This is particularly true in relation to the immune responses elicited against blood stages of Plasmodium-parasites that are responsible for the pathogenesis of infection. Mouse models of malaria are commonly used to dissect the immune mechanisms underlying disease. While no single mouse model of Plasmodium infection completely recapitulates all the features of malaria in humans, collectively the existing models are invaluable for defining the events that lead to the immunopathogenesis of malaria. Here we review the different mouse models of Plasmodium infection that are available, and highlight some of the main contributions these models have made with regards to identifying immune mechanisms of parasite control and the immunopathogenesis of malaria.
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Affiliation(s)
| | | | | | - Tracey J. Lamb
- Department of Pathology, University of Utah, Emma Eccles Jones Medical Research Building, 15 N Medical Drive E, Room 1420A, Salt Lake City, UT 84112, USA
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11
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Olguín V, Durán A, Las Heras M, Rubilar JC, Cubillos FA, Olguín P, Klein AD. Genetic Background Matters: Population-Based Studies in Model Organisms for Translational Research. Int J Mol Sci 2022; 23:7570. [PMID: 35886916 PMCID: PMC9316598 DOI: 10.3390/ijms23147570] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 06/28/2022] [Accepted: 07/04/2022] [Indexed: 02/01/2023] Open
Abstract
We are all similar but a bit different. These differences are partially due to variations in our genomes and are related to the heterogeneity of symptoms and responses to treatments that patients exhibit. Most animal studies are performed in one single strain with one manipulation. However, due to the lack of variability, therapies are not always reproducible when treatments are translated to humans. Panels of already sequenced organisms are valuable tools for mimicking human phenotypic heterogeneities and gene mapping. This review summarizes the current knowledge of mouse, fly, and yeast panels with insightful applications for translational research.
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Affiliation(s)
- Valeria Olguín
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Anyelo Durán
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Macarena Las Heras
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Juan Carlos Rubilar
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
| | - Francisco A. Cubillos
- Departamento de Biología, Santiago, Facultad de Química y Biología, Universidad de Santiago de Chile, Santiago 9170022, Chile;
- Millennium Institute for Integrative Biology (iBio), Santiago 7500565, Chile
| | - Patricio Olguín
- Program in Human Genetics, Institute of Biomedical Sciences, Biomedical Neurosciences Institute, Department of Neuroscience, Facultad de Medicina, Universidad de Chile, Santiago 8380453, Chile;
| | - Andrés D. Klein
- Centro de Genética y Genómica, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Santiago 7610658, Chile; (V.O.); (A.D.); (M.L.H.); (J.C.R.)
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12
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Seemiller LR, Logue SF, Gould TJ. Inbred mouse strain differences in alcohol and nicotine addiction-related phenotypes from adolescence to adulthood. Pharmacol Biochem Behav 2022; 218:173429. [PMID: 35820468 DOI: 10.1016/j.pbb.2022.173429] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 06/18/2022] [Accepted: 07/06/2022] [Indexed: 11/20/2022]
Abstract
Understanding the genetic basis of a predisposition for nicotine and alcohol use across the lifespan is important for public health efforts because genetic contributions may change with age. However, parsing apart subtle genetic contributions to complex human behaviors is a challenge. Animal models provide the opportunity to study the effects of genetic background and age on drug-related phenotypes, while controlling important experimental variables such as amount and timing of drug exposure. Addiction research in inbred, or isogenic, mouse lines has demonstrated genetic contributions to nicotine and alcohol abuse- and addiction-related behaviors. This review summarizes inbred mouse strain differences in alcohol and nicotine addiction-related phenotypes including voluntary consumption/self-administration, initial sensitivity to the drug as measured by sedative, hypothermic, and ataxic effects, locomotor effects, conditioned place preference or place aversion, drug metabolism, and severity of withdrawal symptoms. This review also discusses how these alcohol and nicotine addiction-related phenotypes change from adolescence to adulthood.
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Affiliation(s)
- Laurel R Seemiller
- Department of Biobehavioral Health, Penn State University, University Park, PA, USA
| | - Sheree F Logue
- Department of Biobehavioral Health, Penn State University, University Park, PA, USA
| | - Thomas J Gould
- Department of Biobehavioral Health, Penn State University, University Park, PA, USA.
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13
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Reagan AM, Onos KD, Heuer SE, Sasner M, Howell GR. Improving mouse models for the study of Alzheimer's disease. Curr Top Dev Biol 2022; 148:79-113. [PMID: 35461569 DOI: 10.1016/bs.ctdb.2021.12.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Alzheimer's disease (AD) is a complex neurodegenerative disease whose risk is influenced by genetic and environmental factors. Although a number of pathological hallmarks have been extensively studied over the last several decades, a complete picture of disease initiation and progression remains unclear. We now understand that numerous cell types and systems are involved in AD pathogenesis, and that this cellular profile may present differently for each individual, making the creation of relevant mouse models challenging. However, with increasingly diverse data made available by genome-wide association studies, we can identify and examine new genes and pathways involved in genetic risk for AD, many of which involve vascular health and inflammation. When developing mouse models, it is critical to assess (1) an aging timeline that represents onset and progression in humans, (2) genetic variants and context, (3) environmental factors present in human populations that result in both neuropathological and functional changes-themes that we address in this chapter.
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Affiliation(s)
| | | | - Sarah E Heuer
- The Jackson Laboratory, Bar Harbor, ME, United States; Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, MA, United States
| | | | - Gareth R Howell
- The Jackson Laboratory, Bar Harbor, ME, United States; Graduate Biomedical Sciences, Tufts University School of Medicine, Boston, MA, United States; Graduate School of Biomedical Sciences and Engineering, University of Maine, Orono, ME, United States.
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14
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Zou J, Gopalakrishnan S, Parker CC, Nicod J, Mott R, Cai N, Lionikas A, Davies RW, Palmer AA, Flint J. Analysis of independent cohorts of outbred CFW mice reveals novel loci for behavioral and physiological traits and identifies factors determining reproducibility. G3 (BETHESDA, MD.) 2022; 12:jkab394. [PMID: 34791208 PMCID: PMC8728023 DOI: 10.1093/g3journal/jkab394] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 10/17/2021] [Indexed: 12/12/2022]
Abstract
Combining samples for genetic association is standard practice in human genetic analysis of complex traits, but is rarely undertaken in rodent genetics. Here, using 23 phenotypes and genotypes from two independent laboratories, we obtained a sample size of 3076 commercially available outbred mice and identified 70 loci, more than double the number of loci identified in the component studies. Fine-mapping in the combined sample reduced the number of likely causal variants, with a median reduction in set size of 51%, and indicated novel gene associations, including Pnpo, Ttll6, and GM11545 with bone mineral density, and Psmb9 with weight. However, replication at a nominal threshold of 0.05 between the two component studies was low, with less than one-third of loci identified in one study replicated in the second. In addition to overestimates in the effect size in the discovery sample (Winner's Curse), we also found that heterogeneity between studies explained the poor replication, but the contribution of these two factors varied among traits. Leveraging these observations, we integrated information about replication rates, study-specific heterogeneity, and Winner's Curse corrected estimates of power to assign variants to one of four confidence levels. Our approach addresses concerns about reproducibility and demonstrates how to obtain robust results from mapping complex traits in any genome-wide association study.
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Affiliation(s)
- Jennifer Zou
- Department of Computer Science, University of California, Los Angeles, CA 90024, USA
| | - Shyam Gopalakrishnan
- Faculty of Health and Medical Sciences, GLOBE Institute, University of Copenhagen, Copenhagen DK-1353, Denmark
| | - Clarissa C Parker
- Department of Psychology and Program in Neuroscience, Middlebury College, Middlebury, VT 05753, USA
| | | | - Richard Mott
- UCL Department of Genetics, Evolution & Environment, UCL Genetics Institute, London WC1E 6BT, UK
| | - Na Cai
- Helmholtz Zentrum Muenchen, Helmoltz Pioneer Campus, Neuherberg 85764, Germany
| | - Arimantas Lionikas
- School of Medicine, Medical Sciences and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen AB24 3FX, UK
| | - Robert W Davies
- Department of Statistics, University of Oxford, Oxford OX1 2JD, UK
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA
| | - Jonathan Flint
- Department of Biobehavioral Sciences, University of California, Los Angeles, CA 90024, USA
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15
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Bailey LS, Bagley JR, Dodd R, Olson A, Bolduc M, Philip VM, Reinholdt LG, Sukoff Rizzo SJ, Tarantino L, Gagnon L, Chesler EJ, Jentsch JD. Heritable variation in locomotion, reward sensitivity and impulsive behaviors in a genetically diverse inbred mouse panel. GENES, BRAIN, AND BEHAVIOR 2021; 20:e12773. [PMID: 34672075 PMCID: PMC9044817 DOI: 10.1111/gbb.12773] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/14/2021] [Accepted: 09/15/2021] [Indexed: 12/13/2022]
Abstract
Drugs of abuse, including alcohol and stimulants like cocaine, produce effects that are subject to individual variability, and genetic variation accounts for at least a portion of those differences. Notably, research in both animal models and human subjects point toward reward sensitivity and impulsivity as being trait characteristics that predict relatively greater positive subjective responses to stimulant drugs. Here we describe use of the eight collaborative cross (CC) founder strains and 38 (reversal learning) or 10 (all other tests) CC strains to examine the heritability of reward sensitivity and impulsivity traits, as well as genetic correlations between these measures and existing addiction-related phenotypes. Strains were all tested for activity in an open field and reward sensitivity (intake of chocolate BOOST®). Mice were then divided into two counterbalanced groups and underwent reversal learning (impulsive action and waiting impulsivity) or delay discounting (impulsive choice). CC and founder mice show significant heritability for impulsive action, impulsive choice, waiting impulsivity, locomotor activity, and reward sensitivity, with each impulsive phenotype determined to be non-correlating, independent traits. This research was conducted within the broader, inter-laboratory effort of the Center for Systems Neurogenetics of Addiction (CSNA) to characterize CC and DO mice for multiple, cocaine abuse related traits. These data will facilitate the discovery of genetic correlations between predictive traits, which will then guide discovery of genes and genetic variants that contribute to addictive behaviors.
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Affiliation(s)
- Lauren S Bailey
- State University of New York - Binghamton University, Binghamton, New York, USA
| | - Jared R Bagley
- State University of New York - Binghamton University, Binghamton, New York, USA
| | - Rainy Dodd
- The Jackson Laboratory, Bar Harbor, Maine, USA
| | | | | | | | | | - Stacey J Sukoff Rizzo
- The Jackson Laboratory, Bar Harbor, Maine, USA
- University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Lisa Tarantino
- The Jackson Laboratory, Bar Harbor, Maine, USA
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | | | | | - James David Jentsch
- State University of New York - Binghamton University, Binghamton, New York, USA
- The Jackson Laboratory, Bar Harbor, Maine, USA
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16
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Thomas MH, Gui Y, Garcia P, Karout M, Gomez Ramos B, Jaeger C, Michelucci A, Gaigneaux A, Kollmus H, Centeno A, Schughart K, Balling R, Mittelbronn M, Nadeau JH, Sauter T, Williams RW, Sinkkonen L, Buttini M. Quantitative trait locus mapping identifies a locus linked to striatal dopamine and points to collagen IV alpha-6 chain as a novel regulator of striatal axonal branching in mice. GENES BRAIN AND BEHAVIOR 2021; 20:e12769. [PMID: 34453370 DOI: 10.1111/gbb.12769] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 08/09/2021] [Accepted: 08/25/2021] [Indexed: 11/30/2022]
Abstract
Dopaminergic neurons (DA neurons) are controlled by multiple factors, many involved in neurological disease. Parkinson's disease motor symptoms are caused by the demise of nigral DA neurons, leading to loss of striatal dopamine (DA). Here, we measured DA concentration in the dorsal striatum of 32 members of Collaborative Cross (CC) family and their eight founder strains. Striatal DA varied greatly in founders, and differences were highly heritable in the inbred CC progeny. We identified a locus, containing 164 genes, linked to DA concentration in the dorsal striatum on chromosome X. We used RNAseq profiling of the ventral midbrain of two founders with substantial difference in striatal DA-C56BL/6 J and A/J-to highlight potential protein-coding candidates modulating this trait. Among the five differentially expressed genes within the locus, we found that the gene coding for the collagen IV alpha 6 chain (Col4a6) was expressed nine times less in A/J than in C57BL/6J. Using single cell RNA-seq data from developing human midbrain, we found that COL4A6 is highly expressed in radial glia-like cells and neuronal progenitors, indicating a role in neuronal development. Collagen IV alpha-6 chain (COL4A6) controls axogenesis in simple model organisms. Consistent with these findings, A/J mice had less striatal axonal branching than C57BL/6J mice. We tentatively conclude that DA concentration and axonal branching in dorsal striatum are modulated by COL4A6, possibly during development. Our study shows that genetic mapping based on an easily measured Central Nervous System (CNS) trait, using the CC population, combined with follow-up observations, can parse heritability of such a trait, and nominate novel functions for commonly expressed proteins.
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Affiliation(s)
- Mélanie H Thomas
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch/Alzette, Luxembourg.,Luxembourg Centre of Neuropathology (LCNP), Luxembourg
| | - Yujuan Gui
- Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg
| | - Pierre Garcia
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch/Alzette, Luxembourg.,Luxembourg Centre of Neuropathology (LCNP), Luxembourg.,National Center of Pathology (NCP), Laboratoire National de Santé (LNS), Dudelange, Luxembourg
| | - Mona Karout
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch/Alzette, Luxembourg
| | - Borja Gomez Ramos
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch/Alzette, Luxembourg.,Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg
| | - Christian Jaeger
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch/Alzette, Luxembourg
| | - Alessandro Michelucci
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch/Alzette, Luxembourg.,Neuro-Immunology Group, Department of Oncology (DONC), Luxembourg Institute of Health (LIH), Luxembourg, Luxembourg
| | - Anthoula Gaigneaux
- Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg
| | - Heike Kollmus
- Department of Infection Genetics, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Arthur Centeno
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Klaus Schughart
- Department of Infection Genetics, Helmholtz Centre for Infection Research, Braunschweig, Germany.,University of Veterinary Medicine Hannover, Hannover, Germany.,Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Rudi Balling
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch/Alzette, Luxembourg
| | - Michel Mittelbronn
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch/Alzette, Luxembourg.,Luxembourg Centre of Neuropathology (LCNP), Luxembourg.,Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg.,National Center of Pathology (NCP), Laboratoire National de Santé (LNS), Dudelange, Luxembourg.,Neuro-Immunology Group, Department of Oncology (DONC), Luxembourg Institute of Health (LIH), Luxembourg, Luxembourg
| | - Joseph H Nadeau
- Pacific Northwest Research Institute, Seattle, Washington, USA.,Maine Medical Center Research Institute, Scarborough, Maine, USA
| | - Thomas Sauter
- Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg
| | - Robert W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Lasse Sinkkonen
- Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg
| | - Manuel Buttini
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch/Alzette, Luxembourg.,Luxembourg Centre of Neuropathology (LCNP), Luxembourg
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17
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Bagley JR, Chesler EJ, Philip VM, Jentsch JD. Heritability of ethanol consumption and pharmacokinetics in a genetically diverse panel of collaborative cross mouse strains and their inbred founders. Alcohol Clin Exp Res 2021; 45:697-708. [PMID: 33619752 PMCID: PMC8441258 DOI: 10.1111/acer.14582] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 02/06/2021] [Accepted: 02/12/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND Interindividual variation in voluntary ethanol consumption and ethanol response is partially influenced by genetic variation. Discovery of the genes and allelic variants that affect these phenotypes may clarify the etiology and pathophysiology of problematic alcohol use, including alcohol use disorder. Genetically diverse mouse populations, which demonstrate heritable variation in ethanol consumption, can be utilized to discover the genes and gene networks that influence this trait. The Collaborative Cross (CC) recombinant inbred strains, Diversity Outbred (DO) population and their 8 founder strains are complementary mouse resources that capture substantial genetic diversity and can demonstrate expansive phenotypic variation in heritable traits. These populations may be utilized to discover candidate genes and gene networks that moderate ethanol consumption and other ethanol-related traits. METHODS We characterized ethanol consumption, preference, and pharmacokinetics in the 8 founder strains and 10 CC strains in 12-hour drinking sessions during the dark phase of the circadian cycle. RESULTS Ethanol consumption was substantially heritable, both early in ethanol access and over a chronic intermittent access schedule. Ethanol pharmacokinetics were also heritable; however, no association between strain-level ethanol consumption and pharmacokinetics was detected. The PWK/PhJ strain was the highest drinking strain, with consumption substantially exceeding that of the C57BL/6J strain, which is commonly used as a model of "high" or "binge" drinking. Notably, we found strong evidence that sex moderated genetic effects on voluntary ethanol drinking. CONCLUSIONS Collectively, this research serves as a foundation for expanded genetic study of ethanol consumption in the CC/DO and related populations. Moreover, we identified reference strains with extreme consumption phenotypes that effectively represent polygenic models of excessive ethanol use.
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Affiliation(s)
- Jared R Bagley
- Department of Psychology, Binghamton University, Binghamton, NY, USA
| | - Elissa J Chesler
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
| | - Vivek M Philip
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
| | - James D Jentsch
- Department of Psychology, Binghamton University, Binghamton, NY, USA
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18
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Davis CM, Allen AR, Bowles DE. Consequences of space radiation on the brain and cardiovascular system. JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH. PART C, TOXICOLOGY AND CARCINOGENESIS 2021; 39:180-218. [PMID: 33902387 DOI: 10.1080/26896583.2021.1891825] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Staying longer in outer space will inevitably increase the health risks of astronauts due to the exposures to galactic cosmic rays and solar particle events. Exposure may pose a significant hazard to space flight crews not only during the mission but also later, when slow-developing adverse effects could finally become apparent. The body of literature examining ground-based outcomes in response to high-energy charged-particle radiation suggests differential effects in response to different particles and energies. Numerous animal and cellular models have repeatedly demonstrated the negative effects of high-energy charged-particle on the brain and cognitive function. However, research on the role of space radiation in potentiating cardiovascular dysfunction is still in its early stages. This review summarizes the available data from studies using ground-based animal models to evaluate the response of the brain and heart to the high-energy charged particles of GCR and SPE, addresses potential sex differences in these effects, and aims to highlight gaps in the current literature for future study.
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Affiliation(s)
- Catherine M Davis
- Department of Pharmacology and Molecular Therapeutics, Uniformed Services University of the Health Sciences Bethesda, MD, USA
| | - Antiño R Allen
- Division of Radiation Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA
- Department of Pharmaceutical Sciences, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Dawn E Bowles
- Division of Surgical Sciences, Department of Surgery, Duke University, Durham, NC, USA
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19
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Patterson AM, Plett PA, Chua HL, Sampson CH, Fisher A, Feng H, Unthank JL, Miller SJ, Katz BP, MacVittie TJ, Orschell CM. Development of a Model of the Acute and Delayed Effects of High Dose Radiation Exposure in Jackson Diversity Outbred Mice; Comparison to Inbred C57BL/6 Mice. HEALTH PHYSICS 2020; 119:633-646. [PMID: 32932286 PMCID: PMC9374540 DOI: 10.1097/hp.0000000000001344] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Development of medical countermeasures against radiation relies on robust animal models for efficacy testing. Mouse models have advantages over larger species due to economics, ease of conducting aging studies, existence of historical databases, and research tools allowing for sophisticated mechanistic studies. However, the radiation dose-response relationship of inbred strains is inherently steep and sensitive to experimental variables, and inbred models have been criticized for lacking genetic diversity. Jackson Diversity Outbred (JDO) mice are the most genetically diverse strain available, developed by the Collaborative Cross Consortium using eight founder strains, and may represent a more accurate model of humans than inbred strains. Herein, models of the Hematopoietic-Acute Radiation Syndrome and the Delayed Effects of Acute Radiation Exposure were developed in JDO mice and compared to inbred C57BL/6. The dose response relationship curve in JDO mice mirrored the more shallow curves of primates and humans, characteristic of genetic diversity. JDO mice were more radioresistant than C57BL/6 and differed in sensitivity to antibiotic countermeasures. The model was validated with pegylated-G-CSF, which provided significantly enhanced 30-d survival and accelerated blood recovery. Long-term JDO survivors exhibited increased recovery of blood cells and functional bone marrow hematopoietic progenitors compared to C57BL/6. While JDO hematopoietic stem cells declined more in number, they maintained a greater degree of quiescence compared to C57BL/6, which is essential for maintaining function. These JDO radiation models offer many of the advantages of small animals with the genetic diversity of large animals, providing an attractive alternative to currently available radiation animal models.
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Affiliation(s)
- Andrea M. Patterson
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - P. Artur Plett
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Hui Lin Chua
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Carol H. Sampson
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Alexa Fisher
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Hailin Feng
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Joseph L. Unthank
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Steve J. Miller
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Barry P. Katz
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Thomas J. MacVittie
- Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, MD
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20
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Facilitating Complex Trait Analysis via Reduced Complexity Crosses. Trends Genet 2020; 36:549-562. [PMID: 32482413 DOI: 10.1016/j.tig.2020.05.003] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Revised: 05/05/2020] [Accepted: 05/12/2020] [Indexed: 01/02/2023]
Abstract
Genetically diverse inbred strains are frequently used in quantitative trait mapping to identify sequence variants underlying trait variation. Poor locus resolution and high genetic complexity impede variant discovery. As a solution, we explore reduced complexity crosses (RCCs) between phenotypically divergent, yet genetically similar, rodent substrains. RCCs accelerate functional variant discovery via decreasing the number of segregating variants by orders of magnitude. The simplified genetic architecture of RCCs often permit immediate identification of causal variants or rapid fine-mapping of broad loci to smaller intervals. Whole-genome sequences of substrains make RCCs possible by supporting the development of array- and targeted sequencing-based genotyping platforms, coupled with rapid genome editing for variant validation. In summary, RCCs enhance discovery-based genetics of complex traits.
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21
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Zhou X, St Pierre CL, Gonzales NM, Zou J, Cheng R, Chitre AS, Sokoloff G, Palmer AA. Genome-Wide Association Study in Two Cohorts from a Multi-generational Mouse Advanced Intercross Line Highlights the Difficulty of Replication Due to Study-Specific Heterogeneity. G3 (BETHESDA, MD.) 2020; 10:951-965. [PMID: 31974095 PMCID: PMC7056977 DOI: 10.1534/g3.119.400763] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 10/17/2019] [Indexed: 12/12/2022]
Abstract
There has been extensive discussion of the "Replication Crisis" in many fields, including genome-wide association studies (GWAS). We explored replication in a mouse model using an advanced intercross line (AIL), which is a multigenerational intercross between two inbred strains. We re-genotyped a previously published cohort of LG/J x SM/J AIL mice (F34; n = 428) using a denser marker set and genotyped a new cohort of AIL mice (F39-43; n = 600) for the first time. We identified 36 novel genome-wide significant loci in the F34 and 25 novel loci in the F39-43 cohort. The subset of traits that were measured in both cohorts (locomotor activity, body weight, and coat color) showed high genetic correlations, although the SNP heritabilities were slightly lower in the F39-43 cohort. For this subset of traits, we attempted to replicate loci identified in either F34 or F39-43 in the other cohort. Coat color was robustly replicated; locomotor activity and body weight were only partially replicated, which was inconsistent with our power simulations. We used a random effects model to show that the partial replications could not be explained by Winner's Curse but could be explained by study-specific heterogeneity. Despite this heterogeneity, we performed a mega-analysis by combining F34 and F39-43 cohorts (n = 1,028), which identified four novel loci associated with locomotor activity and body weight. These results illustrate that even with the high degree of genetic and environmental control possible in our experimental system, replication was hindered by study-specific heterogeneity, which has broad implications for ongoing concerns about reproducibility.
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Affiliation(s)
- Xinzhu Zhou
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, 92092
| | - Celine L St Pierre
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63110
| | | | - Jennifer Zou
- Department of Computer Science, University of California, Los Angeles, CA, 90095
| | | | | | - Greta Sokoloff
- Department of Psychological & Brain Sciences, University of Iowa, Iowa City, IO, 52242
| | - Abraham A Palmer
- Department of Psychiatry,
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, 92037 and
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22
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Saul MC, Philip VM, Reinholdt LG, Chesler EJ. High-Diversity Mouse Populations for Complex Traits. Trends Genet 2019; 35:501-514. [PMID: 31133439 DOI: 10.1016/j.tig.2019.04.003] [Citation(s) in RCA: 102] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 04/19/2019] [Accepted: 04/22/2019] [Indexed: 12/21/2022]
Abstract
Contemporary mouse genetic reference populations are a powerful platform to discover complex disease mechanisms. Advanced high-diversity mouse populations include the Collaborative Cross (CC) strains, Diversity Outbred (DO) stock, and their isogenic founder strains. When used in systems genetics and integrative genomics analyses, these populations efficiently harnesses known genetic variation for precise and contextualized identification of complex disease mechanisms. Extensive genetic, genomic, and phenotypic data are already available for these high-diversity mouse populations and a growing suite of data analysis tools have been developed to support research on diverse mice. This integrated resource can be used to discover and evaluate disease mechanisms relevant across species.
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Affiliation(s)
- Michael C Saul
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
| | - Vivek M Philip
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
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- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA; UNC Chapel Hill, Chapel Hill, NC, USA; SUNY Binghamton, Binghamton, NY, USA; Pittsburgh University, Pittsburgh, PA, USA
| | - Elissa J Chesler
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA.
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23
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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, MD.) 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] [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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24
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A Diallel of the Mouse Collaborative Cross Founders Reveals Strong Strain-Specific Maternal Effects on Litter Size. G3-GENES GENOMES GENETICS 2019; 9:1613-1622. [PMID: 30877080 PMCID: PMC6505174 DOI: 10.1534/g3.118.200847] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Reproductive success in the eight founder strains of the Collaborative Cross (CC) was measured using a diallel-mating scheme. Over a 48-month period we generated 4,448 litters, and provided 24,782 weaned pups for use in 16 different published experiments. We identified factors that affect the average litter size in a cross by estimating the overall contribution of parent-of-origin, heterosis, inbred, and epistatic effects using a Bayesian zero-truncated overdispersed Poisson mixed model. The phenotypic variance of litter size has a substantial contribution (82%) from unexplained and environmental sources, but no detectable effect of seasonality. Most of the explained variance was due to additive effects (9.2%) and parental sex (maternal vs. paternal strain; 5.8%), with epistasis accounting for 3.4%. Within the parental effects, the effect of the dam's strain explained more than the sire's strain (13.2% vs. 1.8%), and the dam's strain effects account for 74.2% of total variation explained. Dams from strains C57BL/6J and NOD/ShiLtJ increased the expected litter size by a mean of 1.66 and 1.79 pups, whereas dams from strains WSB/EiJ, PWK/PhJ, and CAST/EiJ reduced expected litter size by a mean of 1.51, 0.81, and 0.90 pups. Finally, there was no strong evidence for strain-specific effects on sex ratio distortion. Overall, these results demonstrate that strains vary substantially in their reproductive ability depending on their genetic background, and that litter size is largely determined by dam's strain rather than sire's strain effects, as expected. This analysis adds to our understanding of factors that influence litter size in mammals, and also helps to explain breeding successes and failures in the extinct lines and surviving CC strains.
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25
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Abstract
One of the most fruitful resources for systems genetic studies of nonhuman mammals is a panel of inbred strains that exhibits significant genetic diversity between strains but genetic stability (isogenicity) within strains. These characteristics allow for fine mapping of complex phenotypes (QTLs) and provide statistical power to identify loci which contribute nominally to the phenotype. This type of resource also allows the planning and performance of investigations using the same genetic backgrounds over several generations of the test animals. Often, rats are preferred over mice for physiologic and behavioral studies because of their larger size and more distinguishable anatomy (particularly for their central nervous system). The Hybrid Rat Diversity Panel (HRDP) is a panel of inbred rat strains, which combines two recombinant inbred panels (the HXB/BXH, 30 strains; the LEXF/FXLE, 34 strains and 35 more strains of inbred rats which were selected for genetic diversity, based on their fully sequenced genomes and/or thorough genotyping). The genetic diversity and statistical power of this panel for mapping studies rivals or surpasses currently available panels in mouse. The genetic stability of this panel makes it particularly suitable for collection of high-throughput omics data as relevant technology becomes available for engaging in truly integrative systems biology. The PhenoGen website ( http://phenogen.org ) is the repository for the initial transcriptome data, making the raw data, the processed data, and the analysis results, e.g., organ-specific protein coding and noncoding transcripts, isoform analysis, expression quantitative trait loci, and co-expression networks, available to the research public. The data sets and tools being developed will complement current efforts to analyze the human transcriptome and its genetic controls (the Genotype-Tissue Expression Project (GTEx)) and allow for dissection of genetic networks that predispose to particular phenotypes and gene-by-environment interactions that are difficult or even impossible to study in humans. The HRDP is an essential population for exploring truly integrative systems genetics.
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Genetic Factors in Cannabinoid Use and Dependence. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1162:129-150. [DOI: 10.1007/978-3-030-21737-2_7] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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Molenhuis RT, Bruining H, Brandt MJV, van Soldt PE, Abu-Toamih Atamni HJ, Burbach JPH, Iraqi FA, Mott RF, Kas MJH. Modeling the quantitative nature of neurodevelopmental disorders using Collaborative Cross mice. Mol Autism 2018; 9:63. [PMID: 30559955 PMCID: PMC6293525 DOI: 10.1186/s13229-018-0252-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 11/28/2018] [Indexed: 01/21/2023] Open
Abstract
Background Animal models for neurodevelopmental disorders (NDD) generally rely on a single genetic mutation on a fixed genetic background. Recent human genetic studies however indicate that a clinical diagnosis with ASDAutism Spectrum Disorder (ASD) is almost always associated with multiple genetic fore- and background changes. The translational value of animal model studies would be greatly enhanced if genetic insults could be studied in a more quantitative framework across genetic backgrounds. Methods We used the Collaborative Cross (CC), a novel mouse genetic reference population, to investigate the quantitative genetic architecture of mouse behavioral phenotypes commonly used in animal models for NDD. Results Classical tests of social recognition and grooming phenotypes appeared insufficient for quantitative studies due to genetic dilution and limited heritability. In contrast, digging, locomotor activity, and stereotyped exploratory patterns were characterized by continuous distribution across our CC sample and also mapped to quantitative trait loci containing genes associated with corresponding phenotypes in human populations. Conclusions These findings show that the CC can move animal model studies beyond comparative single gene-single background designs, and point out which type of behavioral phenotypes are most suitable to quantify the effect of developmental etiologies across multiple genetic backgrounds.
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Affiliation(s)
- Remco T. Molenhuis
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Hilgo Bruining
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Myrna J. V. Brandt
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Petra E. van Soldt
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Hanifa J. Abu-Toamih Atamni
- Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, 69978 Tel Aviv, Israel
| | - J. Peter H. Burbach
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Universiteitsweg 100, 3584 CG Utrecht, The Netherlands
| | - Fuad A. Iraqi
- Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, 69978 Tel Aviv, Israel
| | - Richard F. Mott
- Genetics Institute, University College London, Gower Street, London, WC1E 6BT UK
| | - Martien J. H. Kas
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Nijenborgh 7, 9747 AG Groningen, The Netherlands
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Dickson PE, Roy TA, McNaughton KA, Wilcox TD, Kumar P, Chesler EJ. Systems genetics of sensation seeking. GENES BRAIN AND BEHAVIOR 2018; 18:e12519. [PMID: 30221471 PMCID: PMC6399063 DOI: 10.1111/gbb.12519] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2018] [Revised: 09/09/2018] [Accepted: 09/11/2018] [Indexed: 02/06/2023]
Abstract
Sensation seeking is a multifaceted, heritable trait which predicts the development of substance use and abuse in humans; similar phenomena have been observed in rodents. Genetic correlations among sensation seeking and substance use indicate shared biological mechanisms, but the genes and networks underlying these relationships remain elusive. Here, we used a systems genetics approach in the BXD recombinant inbred mouse panel to identify shared genetic mechanisms underlying substance use and preference for sensory stimuli, an intermediate phenotype of sensation seeking. Using the operant sensation seeking (OSS) paradigm, we quantified preference for sensory stimuli in 120 male and 127 female mice from 62 BXD strains and the C57BL/6J and DBA/2J founder strains. We used relative preference for the active and inactive levers to dissociate preference for sensory stimuli from locomotion and exploration phenotypes. We identified genomic regions on chromosome 4 (155.236‐155.742 Mb) and chromosome 13 (72.969‐89.423 Mb) associated with distinct behavioral components of OSS. Using publicly available behavioral data and mRNA expression data from brain regions involved in reward processing, we identified (a) genes within these behavioral QTL exhibiting genome‐wide significant cis‐eQTL and (b) genetic correlations among OSS phenotypes, ethanol phenotypes and mRNA expression. From these analyses, we nominated positional candidates for behavioral QTL associated with distinct OSS phenotypes including Gnb1 and Mef2c. Genetic covariation of Gnb1 expression, preference for sensory stimuli and multiple ethanol phenotypes suggest that heritable variation in Gnb1 expression in reward circuitry partially underlies the widely reported relationship between sensation seeking and substance use.
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Affiliation(s)
- Price E. Dickson
- Center for Systems Neurogenetics of AddictionThe Jackson LaboratoryBar HarborMaine
| | - Tyler A. Roy
- Center for Systems Neurogenetics of AddictionThe Jackson LaboratoryBar HarborMaine
| | | | - Troy D. Wilcox
- Center for Systems Neurogenetics of AddictionThe Jackson LaboratoryBar HarborMaine
| | - Padam Kumar
- Center for Systems Neurogenetics of AddictionThe Jackson LaboratoryBar HarborMaine
| | - Elissa J. Chesler
- Center for Systems Neurogenetics of AddictionThe Jackson LaboratoryBar HarborMaine
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Howe DG, Blake JA, Bradford YM, Bult CJ, Calvi BR, Engel SR, Kadin JA, Kaufman TC, Kishore R, Laulederkind SJF, Lewis SE, Moxon SAT, Richardson JE, Smith C. Model organism data evolving in support of translational medicine. Lab Anim (NY) 2018; 47:277-289. [PMID: 30224793 PMCID: PMC6322546 DOI: 10.1038/s41684-018-0150-4] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 08/13/2018] [Indexed: 02/07/2023]
Abstract
Model organism databases (MODs) have been collecting and integrating biomedical research data for 30 years and were designed to meet specific needs of each model organism research community. The contributions of model organism research to understanding biological systems would be hard to overstate. Modern molecular biology methods and cost reductions in nucleotide sequencing have opened avenues for direct application of model organism research to elucidating mechanisms of human diseases. Thus, the mandate for model organism research and databases has now grown to include facilitating use of these data in translational applications. Challenges in meeting this opportunity include the distribution of research data across many databases and websites, a lack of data format standards for some data types, and sustainability of scale and cost for genomic database resources like MODs. The issues of widely distributed data and application of data standards are some of the challenges addressed by FAIR (Findable, Accessible, Interoperable, and Re-usable) data principles. The Alliance of Genome Resources is now moving to address these challenges by bringing together expertly curated research data from fly, mouse, rat, worm, yeast, zebrafish, and the Gene Ontology consortium. Centralized multi-species data access, integration, and format standardization will lower the data utilization barrier in comparative genomics and translational applications and will provide a framework in which sustainable scale and cost can be addressed. This article presents a brief historical perspective on how the Alliance model organisms are complementary and how they have already contributed to understanding the etiology of human diseases. In addition, we discuss four challenges for using data from MODs in translational applications and how the Alliance is working to address them, in part by applying FAIR data principles. Ultimately, combined data from these animal models are more powerful than the sum of the parts.
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Affiliation(s)
- Douglas G Howe
- The Institute of Neuroscience, University of Oregon, Eugene, OR, USA.
| | | | - Yvonne M Bradford
- The Institute of Neuroscience, University of Oregon, Eugene, OR, USA
| | | | - Brian R Calvi
- Department of Biology, Indiana University, Bloomington, IN, USA
| | - Stacia R Engel
- Department of Genetics, Stanford University, Palo Alto, CA, USA
| | | | | | - Ranjana Kishore
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Stanley J F Laulederkind
- Department of Biomedical Engineering, Medical College of Wisconsin and Marquette University, Milwaukee, WI, USA
| | - Suzanna E Lewis
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Sierra A T Moxon
- The Institute of Neuroscience, University of Oregon, Eugene, OR, USA
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Graham JB, Swarts JL, Mooney M, Choonoo G, Jeng S, Miller DR, Ferris MT, McWeeney S, Lund JM. Extensive Homeostatic T Cell Phenotypic Variation within the Collaborative Cross. Cell Rep 2018; 21:2313-2325. [PMID: 29166619 PMCID: PMC5728448 DOI: 10.1016/j.celrep.2017.10.093] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Revised: 07/14/2017] [Accepted: 10/25/2017] [Indexed: 12/11/2022] Open
Abstract
The Collaborative Cross (CC) is a panel of reproducible recombinant inbred mouse strains with high levels of standing genetic variation, affording an unprecedented opportunity to perform experiments in a small animal model containing controlled genetic diversity while allowing for genetic replicates. Here, we advance the utility of this unique mouse resource for immunology research because it allows for both examination and genetic dissection of mechanisms behind adaptive immune states in mice with distinct and defined genetic makeups. This approach is based on quantitative trait locus mapping: identifying genetically variant genome regions associated with phenotypic variance in traits of interest. Furthermore, the CC can be utilized for mouse model development; distinct strains have unique immunophenotypes and immune properties, making them suitable for research on particular diseases and infections. Here, we describe variations in cellular immune phenotypes across F1 crosses of CC strains and reveal quantitative trait loci responsible for several immune phenotypes. The Collaborative Cross models the phenotypic diversity observed in human immunity QTL mapping in the CC reveals candidate genes linked to T cell phenotypes
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Affiliation(s)
- Jessica B Graham
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Jessica L Swarts
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Michael Mooney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR 97239, USA; OHSU Knight Cancer Center Institute, Oregon Health and Science University, Portland, OR 97239, USA
| | - Gabrielle Choonoo
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR 97239, USA; OHSU Knight Cancer Center Institute, Oregon Health and Science University, Portland, OR 97239, USA
| | - Sophia Jeng
- Oregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, OR 97239, USA
| | - Darla R Miller
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Martin T Ferris
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Shannon McWeeney
- Division of Bioinformatics and Computational Biology, Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University, Portland, OR 97239, USA; OHSU Knight Cancer Center Institute, Oregon Health and Science University, Portland, OR 97239, USA; Oregon Clinical and Translational Research Institute, Oregon Health and Science University, Portland, OR 97239, USA
| | - Jennifer M Lund
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Department of Global Health, University of Washington, Seattle, WA 98195, USA.
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Yuan JT, Gatti DM, Philip VM, Kasparek S, Kreuzman AM, Mansky B, Sharif K, Taterra D, Taylor WM, Thomas M, Ward JO, Holmes A, Chesler EJ, Parker CC. Genome-wide association for testis weight in the diversity outbred mouse population. Mamm Genome 2018; 29:310-324. [PMID: 29691636 DOI: 10.1007/s00335-018-9745-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 04/16/2018] [Indexed: 12/28/2022]
Abstract
Testis weight is a genetically mediated trait associated with reproductive efficiency across numerous species. We sought to evaluate the genetically diverse, highly recombinant Diversity Outbred (DO) mouse population as a tool to identify and map quantitative trait loci (QTLs) associated with testis weight. Testis weights were recorded for 502 male DO mice and the mice were genotyped on the GIGAMuga array at ~ 143,000 SNPs. We performed a genome-wide association analysis and identified one significant and two suggestive QTLs associated with testis weight. Using bioinformatic approaches, we developed a list of candidate genes and identified those with known roles in testicular size and development. Candidates of particular interest include the RNA demethylase gene Alkbh5, the cyclin-dependent kinase inhibitor gene Cdkn2c, the dynein axonemal heavy chain gene Dnah11, the phospholipase D gene Pld6, the trans-acting transcription factor gene Sp4, and the spermatogenesis-associated gene Spata6, each of which has a human ortholog. Our results demonstrate the utility of DO mice in high-resolution genetic mapping of complex traits, enabling us to identify developmentally important genes in adult mice. Understanding how genetic variation in these genes influence testis weight could aid in the understanding of mechanisms of mammalian reproductive function.
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Affiliation(s)
- Joshua T Yuan
- Department of Computer Science, Program in Molecular Biology & Biochemistry, Middlebury College, Middlebury, VT, 05753, USA
| | - Daniel M Gatti
- The Jackson Laboratory, 610 Main Street, Bar Harbor, ME, 04609, USA
| | - Vivek M Philip
- The Jackson Laboratory, 610 Main Street, Bar Harbor, ME, 04609, USA
| | - Steven Kasparek
- Department of Psychology, Middlebury College, Middlebury, VT, 05753, USA
| | - Andrew M Kreuzman
- Program in Neuroscience, Middlebury College, Middlebury, VT, 05753, USA
| | - Benjamin Mansky
- Program in Neuroscience, Middlebury College, Middlebury, VT, 05753, USA
| | - Kayvon Sharif
- Program in Neuroscience, Middlebury College, Middlebury, VT, 05753, USA
| | - Dominik Taterra
- Program in Neuroscience, Middlebury College, Middlebury, VT, 05753, USA
| | - Walter M Taylor
- Program in Neuroscience, Middlebury College, Middlebury, VT, 05753, USA
| | - Mary Thomas
- Program in Neuroscience, Middlebury College, Middlebury, VT, 05753, USA
| | - Jeremy O Ward
- Department of Biology, Program in Molecular Biology & Biochemistry, Middlebury College, Middlebury, VT, 05753, USA
| | - Andrew Holmes
- Laboratory of Behavioral and Genomic Neuroscience, National Institute on Alcoholism and Alcohol Abuse (NIAAA), US National Institutes of Health (NIH), Bethesda, MD, USA
| | - Elissa J Chesler
- The Jackson Laboratory, 610 Main Street, Bar Harbor, ME, 04609, USA
| | - Clarissa C Parker
- Department of Psychology, Middlebury College, Middlebury, VT, 05753, USA. .,Program in Neuroscience, Middlebury College, Middlebury, VT, 05753, USA.
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Ashbrook DG, Mulligan MK, Williams RW. Post-genomic behavioral genetics: From revolution to routine. GENES, BRAIN, AND BEHAVIOR 2018; 17:e12441. [PMID: 29193773 PMCID: PMC5876106 DOI: 10.1111/gbb.12441] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 11/02/2017] [Accepted: 11/20/2017] [Indexed: 12/16/2022]
Abstract
What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www. RESEARCH va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.
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Affiliation(s)
- D G Ashbrook
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, College of Medicine, Memphis, Tennessee
| | - M K Mulligan
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, College of Medicine, Memphis, Tennessee
| | - R W Williams
- Department of Genetics, Genomics and Informatics, University of Tennessee Health Sciences Center, College of Medicine, Memphis, Tennessee
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Dornbos P, LaPres JJ. Incorporating population-level genetic variability within laboratory models in toxicology: From the individual to the population. Toxicology 2018; 395:1-8. [PMID: 29275117 PMCID: PMC5801153 DOI: 10.1016/j.tox.2017.12.007] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2017] [Revised: 11/22/2017] [Accepted: 12/18/2017] [Indexed: 12/20/2022]
Abstract
Humans respond to chemical exposures differently due to many factors, such as previous and concurrent stressors, age, sex, and genetic background. The vast majority of laboratory-based toxicology studies, however, have not considered the impact of population-level variability within dose-response relationships. The lack of data dealing with the influence of genetic diversity on the response to chemical exposure provides a difficult challenge for risk assessment as individuals within the population will display a wide-range of responses following toxicant challenge. Notably, the genetic background of individuals plays a major role in the variability seen in a population-level response to a drug or chemical and, thus, there is growing interest in including genetic diversity into laboratory-models. Here we outline several laboratory-based models that can be used to assay the influence of genetic variability on an individual's response to chemicals: 1) genetically-diverse cell lines, 2) human primary cells, 3) and genetically-diverse mouse panels. We also provide a succinct review for several seminal studies to highlight the capability, feasibility, and power of each of these models. This article is intended to highlight the need to include population-level genetic diversity into toxicological study designs via laboratory-based models with the goal to provide and supplement evidence in assessing the risk posed by chemicals to the human population. As such, incorporation of genetic variability will positively impact human-based risk assessment and provide empirical data to aid and influence decision-making processes in relation to chemical exposures.
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Affiliation(s)
- Peter Dornbos
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI, USA
| | - John J LaPres
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI, USA; Center for Mitochondrial Science and Medicine, Michigan State University, East Lansing, MI, USA.
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Sukoff Rizzo SJ, Crawley JN. Behavioral Phenotyping Assays for Genetic Mouse Models of Neurodevelopmental, Neurodegenerative, and Psychiatric Disorders. Annu Rev Anim Biosci 2017; 5:371-389. [PMID: 28199172 DOI: 10.1146/annurev-animal-022516-022754] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Animal models offer heuristic research tools to understand the causes of human diseases and to identify potential treatments. With rapidly evolving genetic engineering technologies, mutations identified in a human disorder can be generated in the mouse genome. Phenotypic outcomes of the mutation are then explicated to confirm hypotheses about causes and to discover effective therapeutics. Most neurodevelopmental, neurodegenerative, and psychiatric disorders are diagnosed primarily by their prominent behavioral symptoms. Mouse behavioral assays analogous to the human symptoms have been developed to analyze the consequences of mutations and to evaluate proposed therapeutics preclinically. Here we describe the range of mouse behavioral tests available in the established behavioral neuroscience literature, along with examples of their translational applications. Concepts presented have been successfully used in other species, including flies, worms, fish, rats, pigs, and nonhuman primates. Identical strategies can be employed to test hypotheses about environmental causes and gene × environment interactions.
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Affiliation(s)
| | - Jacqueline N Crawley
- MIND Institute, Department of Psychiatry and Behavioral Sciences, University of California, Davis School of Medicine, Sacramento, California 95817;
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Male Infertility Is Responsible for Nearly Half of the Extinction Observed in the Mouse Collaborative Cross. Genetics 2017; 206:557-572. [PMID: 28592496 DOI: 10.1534/genetics.116.199596] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2017] [Accepted: 03/09/2017] [Indexed: 11/18/2022] Open
Abstract
The goal of the Collaborative Cross (CC) project was to generate and distribute over 1000 independent mouse recombinant inbred strains derived from eight inbred founders. With inbreeding nearly complete, we estimated the extinction rate among CC lines at a remarkable 95%, which is substantially higher than in the derivation of other mouse recombinant inbred populations. Here, we report genome-wide allele frequencies in 347 extinct CC lines. Contrary to expectations, autosomes had equal allelic contributions from the eight founders, but chromosome X had significantly lower allelic contributions from the two inbred founders with underrepresented subspecific origins (PWK/PhJ and CAST/EiJ). By comparing extinct CC lines to living CC strains, we conclude that a complex genetic architecture is driving extinction, and selection pressures are different on the autosomes and chromosome X Male infertility played a large role in extinction as 47% of extinct lines had males that were infertile. Males from extinct lines had high variability in reproductive organ size, low sperm counts, low sperm motility, and a high rate of vacuolization of seminiferous tubules. We performed QTL mapping and identified nine genomic regions associated with male fertility and reproductive phenotypes. Many of the allelic effects in the QTL were driven by the two founders with underrepresented subspecific origins, including a QTL on chromosome X for infertility that was driven by the PWK/PhJ haplotype. We also performed the first example of cross validation using complementary CC resources to verify the effect of sperm curvilinear velocity from the PWK/PhJ haplotype on chromosome 2 in an independent population across multiple generations. While selection typically constrains the examination of reproductive traits toward the more fertile alleles, the CC extinct lines provided a unique opportunity to study the genetic architecture of fertility in a widely genetically variable population. We hypothesize that incompatibilities between alleles with different subspecific origins is a key driver of infertility. These results help clarify the factors that drove strain extinction in the CC, reveal the genetic regions associated with poor fertility in the CC, and serve as a resource to further study mammalian infertility.
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Impacts of Bisphenol A and Ethinyl Estradiol on Male and Female CD-1 Mouse Spleen. Sci Rep 2017; 7:856. [PMID: 28404993 PMCID: PMC5429804 DOI: 10.1038/s41598-017-00961-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Accepted: 03/17/2017] [Indexed: 11/08/2022] Open
Abstract
The endocrine disruptor bisphenol A (BPA) and the pharmaceutical 17α-ethinyl estradiol (EE) are synthetic chemicals with estrogen-like activities. Despite ubiquitous human exposure to BPA, and the wide-spread clinical use of EE as oral contraceptive adjuvant, the impact of these estrogenic endocrine disrupting chemicals (EDCs) on the immune system is unclear. Here we report results of in vivo dose response studies that analyzed the histology and microstructural changes in the spleen of adult male and female CD-1 mice exposed to 4 to 40,000 μg/kg/day BPA or 0.02 to 2 μg/kg/day EE from conception until 12–14 weeks of age. Results of that analysis indicate that both BPA and EE have dose- and sex-specific impacts on the cellular and microanatomical structures of the spleens that reveal minor alterations in immunomodulatory and hematopoietic functions. These findings support previous studies demonstrating the murine immune system as a sensitive target for estrogens, and that oral exposures to BPA and EE can have estrogen-like immunomodulatory affects in both sexes.
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Abstract
Identifying genes and pathways that contribute to differences in neurobehavioural traits is a key goal in psychiatric research. Despite considerable success in identifying quantitative trait loci (QTLs) associated with behaviour in laboratory rodents, pinpointing the causal variants and genes is more challenging. For a long time, the main obstacle was the size of QTLs, which could encompass tens if not hundreds of genes. However, recent studies have exploited mouse and rat resources that allow mapping of phenotypes to narrow intervals, encompassing only a few genes. Here, we review these studies, showcase the rodent resources they have used and highlight the insights into neurobehavioural traits provided to date. We discuss what we see as the biggest challenge in the field - translating QTLs into biological knowledge by experimentally validating and functionally characterizing candidate genes - and propose that the CRISPR/Cas genome-editing system holds the key to overcoming this obstacle. Finally, we challenge traditional views on inbred versus outbred resources in the light of recent resource and technology developments.
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Affiliation(s)
- Amelie Baud
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jonathan Flint
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, Los Angeles, CA 90095-1761, USA
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Colville AM, Iancu OD, Oberbeck DL, Darakjian P, Zheng CL, Walter NAR, Harrington CA, Searles RP, McWeeney S, Hitzemann RJ. Effects of selection for ethanol preference on gene expression in the nucleus accumbens of HS-CC mice. GENES BRAIN AND BEHAVIOR 2017; 16:462-471. [PMID: 28058793 DOI: 10.1111/gbb.12367] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2016] [Revised: 12/16/2016] [Accepted: 01/03/2017] [Indexed: 12/15/2022]
Abstract
Previous studies on changes in murine brain gene expression associated with the selection for ethanol preference have used F2 intercross or heterogeneous stock (HS) founders, derived from standard laboratory strains. However, these populations represent only a small proportion of the genetic variance available in Mus musculus. To investigate a wider range of genetic diversity, we selected mice for ethanol preference using an HS derived from the eight strains of the collaborative cross. These HS mice were selectively bred (four generations) for high and low ethanol preference. The nucleus accumbens shell of naive S4 mice was interrogated using RNA sequencing (RNA-Seq). Gene networks were constructed using the weighted gene coexpression network analysis assessing both coexpression and cosplicing. Selection targeted one of the network coexpression modules (greenyellow) that was significantly enriched in genes associated with receptor signaling activity including Chrna7, Grin2a, Htr2a and Oprd1. Connectivity in the module as measured by changes in the hub nodes was significantly reduced in the low preference line. Of particular interest was the observation that selection had marked effects on a large number of cell adhesion molecules, including cadherins and protocadherins. In addition, the coexpression data showed that selection had marked effects on long non-coding RNA hub nodes. Analysis of the cosplicing network data showed a significant effect of selection on a large cluster of Ras GTPase-binding genes including Cdkl5, Cyfip1, Ndrg1, Sod1 and Stxbp5. These data in part support the earlier observation that preference is linked to Ras/Mapk pathways.
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Affiliation(s)
- A M Colville
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - O D Iancu
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - D L Oberbeck
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - P Darakjian
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - C L Zheng
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - N A R Walter
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - C A Harrington
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - R P Searles
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - S McWeeney
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - R J Hitzemann
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA.,Research Service, Portland Veterans Affairs Medical Center, Portland, OR, USA
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Molenhuis RT, Bruining H, Kas MJ. Modelling Autistic Features in Mice Using Quantitative Genetic Approaches. ADVANCES IN ANATOMY, EMBRYOLOGY, AND CELL BIOLOGY 2017; 224:65-84. [PMID: 28551751 DOI: 10.1007/978-3-319-52498-6_4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Animal studies provide a unique opportunity to study the consequences of genetic variants at the behavioural level. Human studies have identified hundreds of risk genes for autism spectrum disorder (ASD) that can lead to understanding on how genetic variation contributes to individual differences in social interaction and stereotyped behaviour in people with ASD. To develop rational therapeutic interventions, systematic animal model studies are needed to understand the relationships between genetic variation, pathogenic processes and the expression of autistic behaviours. Genetic and non-genetic animal model strategies are here reviewed in their propensity to study the underpinnings of behavioural trait variation. We conclude that an integration of reverse and forward genetic approaches may be essential to unravel the neurobiological mechanisms underlying ASD.
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Affiliation(s)
- Remco T Molenhuis
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hilgo Bruining
- Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Martien J Kas
- Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands.
- Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands.
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40
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Bosetti F, Galis ZS, Bynoe MS, Charette M, Cipolla MJ, Del Zoppo GJ, Gould D, Hatsukami TS, Jones TLZ, Koenig JI, Lutty GA, Maric-Bilkan C, Stevens T, Tolunay HE, Koroshetz W. "Small Blood Vessels: Big Health Problems?": Scientific Recommendations of the National Institutes of Health Workshop. J Am Heart Assoc 2016; 5:JAHA.116.004389. [PMID: 27815267 PMCID: PMC5210346 DOI: 10.1161/jaha.116.004389] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Francesca Bosetti
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD
| | - Zorina S Galis
- National Heart, Lung and Blood Institute, National Institutes of Health (NIH), Bethesda, MD
| | | | - Marc Charette
- National Heart, Lung and Blood Institute, National Institutes of Health (NIH), Bethesda, MD
| | | | | | | | | | - Teresa L Z Jones
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health (NIH), Bethesda, MD
| | - James I Koenig
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD
| | | | - Christine Maric-Bilkan
- National Heart, Lung and Blood Institute, National Institutes of Health (NIH), Bethesda, MD
| | | | - H Eser Tolunay
- National Heart, Lung and Blood Institute, National Institutes of Health (NIH), Bethesda, MD
| | - Walter Koroshetz
- National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD
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41
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Nachshon A, Abu-Toamih Atamni HJ, Steuerman Y, Sheikh-Hamed R, Dorman A, Mott R, Dohm JC, Lehrach H, Sultan M, Shamir R, Sauer S, Himmelbauer H, Iraqi FA, Gat-Viks I. Dissecting the Effect of Genetic Variation on the Hepatic Expression of Drug Disposition Genes across the Collaborative Cross Mouse Strains. Front Genet 2016; 7:172. [PMID: 27761138 PMCID: PMC5050206 DOI: 10.3389/fgene.2016.00172] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 09/09/2016] [Indexed: 12/26/2022] Open
Abstract
A central challenge in pharmaceutical research is to investigate genetic variation in response to drugs. The Collaborative Cross (CC) mouse reference population is a promising model for pharmacogenomic studies because of its large amount of genetic variation, genetic reproducibility, and dense recombination sites. While the CC lines are phenotypically diverse, their genetic diversity in drug disposition processes, such as detoxification reactions, is still largely uncharacterized. Here we systematically measured RNA-sequencing expression profiles from livers of 29 CC lines under baseline conditions. We then leveraged a reference collection of metabolic biotransformation pathways to map potential relations between drugs and their underlying expression quantitative trait loci (eQTLs). By applying this approach on proximal eQTLs, including eQTLs acting on the overall expression of genes and on the expression of particular transcript isoforms, we were able to construct the organization of hepatic eQTL-drug connectivity across the CC population. The analysis revealed a substantial impact of genetic variation acting on drug biotransformation, allowed mapping of potential joint genetic effects in the context of individual drugs, and demonstrated crosstalk between drug metabolism and lipid metabolism. Our findings provide a resource for investigating drug disposition in the CC strains, and offer a new paradigm for integrating biotransformation reactions to corresponding variations in DNA sequences.
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Affiliation(s)
- Aharon Nachshon
- Department of Cell Research and Immunology, Faculty of Life Sciences, Tel-Aviv University Tel-Aviv, Israel
| | - Hanifa J Abu-Toamih Atamni
- Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel- Aviv University Tel-Aviv, Israel
| | - Yael Steuerman
- Department of Cell Research and Immunology, Faculty of Life Sciences, Tel-Aviv University Tel-Aviv, Israel
| | - Roa'a Sheikh-Hamed
- Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel- Aviv University Tel-Aviv, Israel
| | - Alexandra Dorman
- Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel- Aviv University Tel-Aviv, Israel
| | - Richard Mott
- Genetics Institute, University College of London London, UK
| | - Juliane C Dohm
- Genomics Unit, Center for Genomic RegulationBarcelona, Spain; Universitat Pompeu FabraBarcelona, Spain; Department of Biotechnology, University of Natural Resources and Life Sciences Vienna (BOKU)Vienna, Austria
| | - Hans Lehrach
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics Berlin, Germany
| | - Marc Sultan
- Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics Berlin, Germany
| | - Ron Shamir
- The Blavatnik School of Computer Science, Tel Aviv University Tel Aviv, Israel
| | - Sascha Sauer
- Department of Vertebrate Genomics, Max Planck Institute for Molecular GeneticsBerlin, Germany; CU Systems Medicine, University of WürzburgWürzburg, Germany
| | - Heinz Himmelbauer
- Genomics Unit, Center for Genomic RegulationBarcelona, Spain; Universitat Pompeu FabraBarcelona, Spain; Department of Biotechnology, University of Natural Resources and Life Sciences Vienna (BOKU)Vienna, Austria
| | - Fuad A Iraqi
- Department of Clinical Microbiology and Immunology, Sackler Faculty of Medicine, Tel- Aviv University Tel-Aviv, Israel
| | - Irit Gat-Viks
- Department of Cell Research and Immunology, Faculty of Life Sciences, Tel-Aviv University Tel-Aviv, Israel
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Abstract
In this issue of Neuron, Sittig et al. (2016) present research that calls into question the way laboratory mice are used to address questions in basic science and experimental medicine. This research demonstrates strong interactions between mutant alleles and genetic background.
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Affiliation(s)
- Richard A Miller
- Department of Pathology, University of Michigan School of Medicine, Ann Arbor, MI 48109-2200, USA.
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43
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Parker CC, Gopalakrishnan S, Carbonetto P, Gonzales NM, Leung E, Park YJ, Aryee E, Davis J, Blizard DA, Ackert-Bicknell CL, Lionikas A, Pritchard JK, Palmer AA. Genome-wide association study of behavioral, physiological and gene expression traits in outbred CFW mice. Nat Genet 2016; 48:919-26. [PMID: 27376237 PMCID: PMC4963286 DOI: 10.1038/ng.3609] [Citation(s) in RCA: 79] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 06/08/2016] [Indexed: 12/15/2022]
Abstract
Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice.
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Affiliation(s)
- Clarissa C. Parker
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
- Department of Psychology, Middlebury College, Middlebury, VT 05753, USA
- Program in Neuroscience, Middlebury College, Middlebury, VT 05753, USA
| | - Shyam Gopalakrishnan
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
- Museum of Natural History, Copenhagen University, Copenhagen, Denmark
| | - Peter Carbonetto
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
- AncestryDNA, San Francisco, CA 94105, USA
| | | | - Emily Leung
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Yeonhee J Park
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Emmanuel Aryee
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Joe Davis
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - David A. Blizard
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA 16802, USA
| | - Cheryl L. Ackert-Bicknell
- Center for Musculoskeletal Research, University of Rochester, Rochester, NY 14624, USA
- Department of Orthopaedics and Rehabilitation, University of Rochester, Rochester, NY 14624, USA
| | - Arimantas Lionikas
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill Aberdeen, Scotland UK
| | - Jonathan K. Pritchard
- Department of Genetics, Stanford University, Palo Alto, CA 94305, USA
- Department of Biology, Stanford University, Palo Alto, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Palo Alto, CA 94305, USA
| | - Abraham A. Palmer
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL 60637, USA
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92103, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92103, USA
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44
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Systems genetics of intravenous cocaine self-administration in the BXD recombinant inbred mouse panel. Psychopharmacology (Berl) 2016; 233:701-14. [PMID: 26581503 PMCID: PMC4803082 DOI: 10.1007/s00213-015-4147-z] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2015] [Accepted: 10/31/2015] [Indexed: 12/31/2022]
Abstract
RATIONALE Cocaine addiction is a major public health problem with a substantial genetic basis for which the biological mechanisms remain largely unknown. Systems genetics is a powerful method for discovering novel mechanisms underlying complex traits, and intravenous drug self-administration (IVSA) is the gold standard for assessing volitional drug use in preclinical studies. We have integrated these approaches to identify novel genes and networks underlying cocaine use in mice. METHODS Mice from 39 BXD strains acquired cocaine IVSA (0.56 mg/kg/infusion). Mice from 29 BXD strains completed a full dose-response curve (0.032-1.8 mg/kg/infusion). We identified independent genetic correlations between cocaine IVSA and measures of environmental exploration and cocaine sensitization. We identified genome-wide significant quantitative trait loci (QTL) on chromosomes 7 and 11 associated with shifts in the dose-response curve and on chromosome 16 associated with sessions to acquire cocaine IVSA. Using publicly available gene expression data from the nucleus accumbens, midbrain, and prefrontal cortex of drug-naïve mice, we identified Aplp1 and Cyfip2 as positional candidates underlying the behavioral QTL on chromosomes 7 and 11, respectively. A genome-wide significant trans-eQTL linking Fam53b (a GWAS candidate for human cocaine dependence) on chromosome 7 to the cocaine IVSA behavioral QTL on chromosome 11 was identified in the midbrain; Fam53b and Cyfip2 were co-expressed genome-wide significantly in the midbrain. This finding indicates that cocaine IVSA studies using mice can identify genes involved in human cocaine use. CONCLUSIONS These data provide novel candidate genes underlying cocaine IVSA in mice and suggest mechanisms driving human cocaine use.
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45
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Bult CJ, Eppig JT, Blake JA, Kadin JA, Richardson JE. Mouse genome database 2016. Nucleic Acids Res 2015; 44:D840-7. [PMID: 26578600 PMCID: PMC4702860 DOI: 10.1093/nar/gkv1211] [Citation(s) in RCA: 66] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2015] [Accepted: 10/23/2015] [Indexed: 01/09/2023] Open
Abstract
The Mouse Genome Database (MGD; http://www.informatics.jax.org) is the primary community model organism database for the laboratory mouse and serves as the source for key biological reference data related to mouse genes, gene functions, phenotypes and disease models with a strong emphasis on the relationship of these data to human biology and disease. As the cost of genome-scale sequencing continues to decrease and new technologies for genome editing become widely adopted, the laboratory mouse is more important than ever as a model system for understanding the biological significance of human genetic variation and for advancing the basic research needed to support the emergence of genome-guided precision medicine. Recent enhancements to MGD include new graphical summaries of biological annotations for mouse genes, support for mobile access to the database, tools to support the annotation and analysis of sets of genes, and expanded support for comparative biology through the expansion of homology data.
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Affiliation(s)
- Carol J Bult
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA
| | - Janan T Eppig
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA
| | - Judith A Blake
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA
| | - James A Kadin
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA
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46
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Wilking JA, Stitzel JA. Natural genetic variability of the neuronal nicotinic acetylcholine receptor subunit genes in mice: Consequences and confounds. Neuropharmacology 2015; 96:205-12. [PMID: 25498233 PMCID: PMC4461559 DOI: 10.1016/j.neuropharm.2014.11.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2014] [Revised: 11/11/2014] [Accepted: 11/27/2014] [Indexed: 01/15/2023]
Abstract
Recent human genetic studies have identified genetic variants in multiple nicotinic acetylcholine receptor (nAChR) subunit genes that are associated with risk for nicotine dependence and other smoking-related measures. Genetic variability also exists in the nAChR subunit genes in mice. Most studies on mouse nAChR subunit gene variability to date have focused on Chrna4, the gene that encodes the α4 nAChR subunit and Chrna7, the gene that encodes the α7 nAChR subunit. However, genetic variability exists for all nAChR genes in mice. In this review, we will describe what is known about nAChR subunit gene polymorphisms in mice and how it relates to variability in nAChR expression and function in brain. The relationship between nAChR genetic variability in mice and the effects of nicotine on several behavioral and physiological measures also will be discussed. In addition, an overview of the contribution of other genetic variation to nicotine sensitivity in mice will be provided. Finally, the potential for natural genetic variability to confound and/or modify the results of studies that utilize genetically engineered mice will be considered. As an example of the ability of a natural genetic variant to modify the effect of an engineered mutation, data will be presented that demonstrate that the effect of Chrna5 deletion on oral nicotine intake is dependent upon naturally occurring variant alleles of Chrna4. This article is part of the Special Issue entitled 'The Nicotinic Acetylcholine Receptor: From Molecular Biology to Cognition'.
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Affiliation(s)
- Jennifer A Wilking
- Institute for Behavioral Genetics, USA; Department of Integrative Physiology, UCB447, Boulder, CO, 80309, USA
| | - Jerry A Stitzel
- Institute for Behavioral Genetics, USA; Department of Integrative Physiology, UCB447, Boulder, CO, 80309, USA.
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47
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Collaborative Cross and Diversity Outbred data resources in the Mouse Phenome Database. Mamm Genome 2015; 26:511-20. [PMID: 26286858 PMCID: PMC4602074 DOI: 10.1007/s00335-015-9595-6] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2015] [Accepted: 08/10/2015] [Indexed: 10/27/2022]
Abstract
The Mouse Phenome Database was originally conceived as a platform for the integration of phenotype data collected on a defined collection of 40 inbred mouse strains--the "phenome panel." This model provided an impetus for community data sharing, and integration was readily achieved through the reproducible genotypes of the phenome panel strains. Advances in the development of mouse populations lead to an expanded role of the Mouse Phenome Database to encompass new strain panels and inbred strain crosses. The recent introduction of the Collaborative Cross and Diversity Outbred mice, which share an extensive pool of genetic variation from eight founder inbred strains, presents new opportunities and challenges for community data resources. A wide variety of molecular and clinical phenotypes are being collected across genotypes, tissues, ages, environmental exposures, interventions, and treatments. The Mouse Phenome Database provides a framework for retrieval, integration, analysis, and display of these data, enabling them to be evaluated in the context of existing data from standard inbred strains. Primary data in the Mouse Phenome Database are supported by extensive metadata on protocols and procedures. These are centrally curated to ensure accuracy and reproducibility and to provide data in consistent formats. The Mouse Phenome Database represents an established and growing community data resource for mouse phenotype data and encourages submissions from new mouse resources, enabling investigators to integrate existing data into their studies of the phenotypic consequences of genetic variation.
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48
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Eppig JT, Richardson JE, Kadin JA, Smith CL, Blake JA, Bult CJ. Mouse Genome Database: From sequence to phenotypes and disease models. Genesis 2015; 53:458-73. [PMID: 26150326 PMCID: PMC4545690 DOI: 10.1002/dvg.22874] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Revised: 06/30/2015] [Accepted: 07/02/2015] [Indexed: 12/19/2022]
Abstract
The Mouse Genome Database (MGD, www.informatics.jax.org) is the international scientific database for genetic, genomic, and biological data on the laboratory mouse to support the research requirements of the biomedical community. To accomplish this goal, MGD provides broad data coverage, serves as the authoritative standard for mouse nomenclature for genes, mutants, and strains, and curates and integrates many types of data from literature and electronic sources. Among the key data sets MGD supports are: the complete catalog of mouse genes and genome features, comparative homology data for mouse and vertebrate genes, the authoritative set of Gene Ontology (GO) annotations for mouse gene functions, a comprehensive catalog of mouse mutations and their phenotypes, and a curated compendium of mouse models of human diseases. Here, we describe the data acquisition process, specifics about MGD's key data areas, methods to access and query MGD data, and outreach and user help facilities. genesis 53:458–473, 2015. © 2015 The Authors. Genesis Published by Wiley Periodicals, Inc.
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49
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Bello SM, Smith CL, Eppig JT. Allele, phenotype and disease data at Mouse Genome Informatics: improving access and analysis. Mamm Genome 2015; 26:285-94. [PMID: 26162703 PMCID: PMC4534497 DOI: 10.1007/s00335-015-9582-y] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2015] [Accepted: 06/23/2015] [Indexed: 11/16/2022]
Abstract
A core part of the Mouse Genome Informatics (MGI) resource is the collection of mouse mutations and the annotation phenotypes and diseases displayed by mice carrying these mutations. These data are integrated with the rest of data in MGI and exported to numerous other resources. The use of mouse phenotype data to drive translational research into human disease has expanded rapidly with the improvements in sequencing technology. MGI has implemented many improvements in allele and phenotype data annotation, search, and display to facilitate access to these data through multiple avenues. For example, the description of alleles has been modified to include more detailed categories of allele attributes. This allows improved discrimination between mutation types. Further, connections have been created between mutations involving multiple genes and each of the genes overlapping the mutation. This allows users to readily find all mutations affecting a gene and see all genes affected by a mutation. In a similar manner, the genes expressed by transgenic or knock-in alleles are now connected to these alleles. The advanced search forms and public reports have been updated to take advantage of these improvements. These search forms and reports are used by an expanding number of researchers to identify novel human disease genes and mouse models of human disease.
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Affiliation(s)
- Susan M Bello
- Mouse Genome Informatics, The Jackson Laboratory, Bar Harbor, ME, 04609, USA,
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50
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Morgan AP, Welsh CE. Informatics resources for the Collaborative Cross and related mouse populations. Mamm Genome 2015; 26:521-39. [PMID: 26135136 DOI: 10.1007/s00335-015-9581-z] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Accepted: 06/23/2015] [Indexed: 02/05/2023]
Affiliation(s)
- Andrew P Morgan
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Catherine E Welsh
- Department of Mathematics & Computer Science, Rhodes College, Memphis, TN, USA.
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