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Pera M, Greene A, Cardon L, Carter GW, Chesler EJ, Churchill G, Kumar V, Lutz C, Munger S, Murray S, O'Connell K, Reinholdt L, Rosenthal NA. Improving the predictive power of mouse models. Nat Biotechnol 2024; 42:1175-1177. [PMID: 39143158 DOI: 10.1038/s41587-024-02349-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Affiliation(s)
| | | | - Lon Cardon
- The Jackson Laboratory, Bar Harbor, ME, USA
| | | | | | | | | | | | | | | | | | | | - Nadia A Rosenthal
- The Jackson Laboratory, Bar Harbor, ME, USA.
- National Heart and Lung Institute, Imperial Centre for Translational and Experimental Medicine, Imperial College London, London, UK.
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2
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Meade RK, Smith CM. Immunological roads diverged: mapping tuberculosis outcomes in mice. Trends Microbiol 2024:S0966-842X(24)00170-7. [PMID: 39034171 DOI: 10.1016/j.tim.2024.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 06/24/2024] [Accepted: 06/25/2024] [Indexed: 07/23/2024]
Abstract
The journey from phenotypic observation to causal genetic mechanism is a long and challenging road. For pathogens like Mycobacterium tuberculosis (Mtb), which causes tuberculosis (TB), host-pathogen coevolution has spanned millennia, costing millions of human lives. Mammalian models can systematically recapitulate host genetic variation, producing a spectrum of disease outcomes. Leveraging genome sequences and deep phenotyping data from infected mouse genetic reference populations (GRPs), quantitative trait locus (QTL) mapping approaches have successfully identified host genomic regions associated with TB phenotypes. Here, we review the ongoing optimization of QTL mapping study design alongside advances in mouse GRPs. These next-generation resources and approaches have enabled identification of novel host-pathogen interactions governing one of the most prevalent infectious diseases in the world today.
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Affiliation(s)
- Rachel K Meade
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA; University Program in Genetics and Genomics, Duke University, Durham, NC, USA
| | - Clare M Smith
- Department of Molecular Genetics and Microbiology, Duke University, Durham, NC, USA; University Program in Genetics and Genomics, Duke University, Durham, NC, USA.
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3
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Parikh C, Glenn RA, Shi Y, Chatterjee K, Swanzey EE, Singer S, Do SC, Zhan Y, Furuta Y, Tahiliani M, Apostolou E, Polyzos A, Koche R, Mezey JG, Vierbuchen T, Stadtfeld M. Genetic variation modulates susceptibility to aberrant DNA hypomethylation and imprint deregulation in naïve pluripotent stem cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.26.600805. [PMID: 38979237 PMCID: PMC11230387 DOI: 10.1101/2024.06.26.600805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Naïve pluripotent stem cells (nPSC) frequently undergo pathological and not readily reversible loss of DNA methylation marks at imprinted gene loci. This abnormality poses a hurdle for using pluripotent cell lines in biomedical applications and underscores the need to identify the causes of imprint instability in these cells. We show that nPSCs from inbred mouse strains exhibit pronounced strain-specific susceptibility to locus-specific deregulation of imprinting marks during reprogramming to pluripotency and upon culture with MAP kinase inhibitors, a common approach to maintain naïve pluripotency. Analysis of genetically highly diverse nPSCs from the Diversity Outbred (DO) stock confirms that genetic variation is a major determinant of epigenome stability in pluripotent cells. We leverage the variable DNA hypomethylation in DO lines to identify several trans-acting quantitative trait loci (QTLs) that determine epigenome stability at either specific target loci or genome-wide. Candidate factors encoded by two multi-target QTLs on chromosomes 4 and 17 suggest specific transcriptional regulators that contribute to DNA methylation maintenance in nPSCs. We propose that genetic variants represent candidate biomarkers to identify pluripotent cell lines with desirable properties and might serve as entry points for the targeted engineering of nPSCs with stable epigenomes. Highlights Naïve pluripotent stem cells from distinct inbred mouse strains exhibit variable DNA methylation levels at imprinted gene loci.The vulnerability of pluripotent stem cells to loss of genomic imprinting caused by MAP kinase inhibition strongly differs between inbred mouse strains.Genetically diverse pluripotent stem cell lines from Diversity Outbred mouse stock allow the identification of quantitative trait loci controlling DNA methylation stability.Genetic variants may serve as biomarkers to identify naïve pluripotent stem cell lines that are epigenetically stable in specific culture conditions.
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4
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Palmer JA, Rosenthal N, Teichmann SA, Litvinukova M. Revisiting Cardiac Biology in the Era of Single Cell and Spatial Omics. Circ Res 2024; 134:1681-1702. [PMID: 38843288 PMCID: PMC11149945 DOI: 10.1161/circresaha.124.323672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 04/16/2024] [Accepted: 04/24/2024] [Indexed: 06/09/2024]
Abstract
Throughout our lifetime, each beat of the heart requires the coordinated action of multiple cardiac cell types. Understanding cardiac cell biology, its intricate microenvironments, and the mechanisms that govern their function in health and disease are crucial to designing novel therapeutical and behavioral interventions. Recent advances in single-cell and spatial omics technologies have significantly propelled this understanding, offering novel insights into the cellular diversity and function and the complex interactions of cardiac tissue. This review provides a comprehensive overview of the cellular landscape of the heart, bridging the gap between suspension-based and emerging in situ approaches, focusing on the experimental and computational challenges, comparative analyses of mouse and human cardiac systems, and the rising contextualization of cardiac cells within their niches. As we explore the heart at this unprecedented resolution, integrating insights from both mouse and human studies will pave the way for novel diagnostic tools and therapeutic interventions, ultimately improving outcomes for patients with cardiovascular diseases.
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Affiliation(s)
- Jack A. Palmer
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom (J.A.P., S.A.T.)
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus (J.A.P., S.A.T.), University of Cambridge, United Kingdom
| | - Nadia Rosenthal
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME (N.R.)
- National Heart and Lung Institute, Imperial College London, United Kingdom (N.R.)
| | - Sarah A. Teichmann
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom (J.A.P., S.A.T.)
- Wellcome-MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus (J.A.P., S.A.T.), University of Cambridge, United Kingdom
- Theory of Condensed Matter Group, Department of Physics, Cavendish Laboratory (S.A.T.), University of Cambridge, United Kingdom
| | - Monika Litvinukova
- University Hospital Würzburg, Germany (M.L.)
- Würzburg Institute of Systems Immunology, Max Planck Research Group at the Julius-Maximilians-Universität Würzburg, Germany (M.L.)
- Helmholtz Pioneer Campus, Helmholtz Munich, Germany (M.L.)
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5
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Glenn RA, Do SC, Guruvayurappan K, Corrigan EK, Santini L, Medina-Cano D, Singer S, Cho H, Liu J, Broman K, Czechanski A, Reinholdt L, Koche R, Furuta Y, Kunz M, Vierbuchen T. A PLURIPOTENT STEM CELL PLATFORM FOR IN VITRO SYSTEMS GENETICS STUDIES OF MOUSE DEVELOPMENT. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.06.597758. [PMID: 38895226 PMCID: PMC11185710 DOI: 10.1101/2024.06.06.597758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
The directed differentiation of pluripotent stem cells (PSCs) from panels of genetically diverse individuals is emerging as a powerful experimental system for characterizing the impact of natural genetic variation on developing cell types and tissues. Here, we establish new PSC lines and experimental approaches for modeling embryonic development in a genetically diverse, outbred mouse stock (Diversity Outbred mice). We show that a range of inbred and outbred PSC lines can be stably maintained in the primed pluripotent state (epiblast stem cells -- EpiSCs) and establish the contribution of genetic variation to phenotypic differences in gene regulation and directed differentiation. Using pooled in vitro fertilization, we generate and characterize a genetic reference panel of Diversity Outbred PSCs (n = 230). Finally, we demonstrate the feasibility of pooled culture of Diversity Outbred EpiSCs as "cell villages", which can facilitate the differentiation of large numbers of EpiSC lines for forward genetic screens. These data can complement and inform similar efforts within the stem cell biology and human genetics communities to model the impact of natural genetic variation on phenotypic variation and disease-risk.
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Affiliation(s)
- Rachel A. Glenn
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Stem Cell Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Cell and Developmental Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, USA
| | - Stephanie C. Do
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Stem Cell Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Emily K. Corrigan
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Stem Cell Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Present address: Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA and Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Laura Santini
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Stem Cell Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Daniel Medina-Cano
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Stem Cell Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Sarah Singer
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hyein Cho
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Stem Cell Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jing Liu
- Mouse Genetics Core Facility, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Karl Broman
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI USA
| | | | | | - Richard Koche
- Center for Epigenetics Research, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yasuhide Furuta
- Mouse Genetics Core Facility, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Meik Kunz
- The Bioinformatics CRO, Sanford Florida, 32771 USA
| | - Thomas Vierbuchen
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Center for Stem Cell Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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6
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Cortes DE, Escudero M, Korgan AC, Mitra A, Edwards A, Aydin SC, Munger SC, Charland K, Zhang ZW, O'Connell KMS, Reinholdt LG, Pera MF. An in vitro neurogenetics platform for precision disease modeling in the mouse. SCIENCE ADVANCES 2024; 10:eadj9305. [PMID: 38569042 PMCID: PMC10990289 DOI: 10.1126/sciadv.adj9305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 02/27/2024] [Indexed: 04/05/2024]
Abstract
The power and scope of disease modeling can be markedly enhanced through the incorporation of broad genetic diversity. The introduction of pathogenic mutations into a single inbred mouse strain sometimes fails to mimic human disease. We describe a cross-species precision disease modeling platform that exploits mouse genetic diversity to bridge cell-based modeling with whole organism analysis. We developed a universal protocol that permitted robust and reproducible neural differentiation of genetically diverse human and mouse pluripotent stem cell lines and then carried out a proof-of-concept study of the neurodevelopmental gene DYRK1A. Results in vitro reliably predicted the effects of genetic background on Dyrk1a loss-of-function phenotypes in vivo. Transcriptomic comparison of responsive and unresponsive strains identified molecular pathways conferring sensitivity or resilience to Dyrk1a1A loss and highlighted differential messenger RNA isoform usage as an important determinant of response. This cross-species strategy provides a powerful tool in the functional analysis of candidate disease variants identified through human genetic studies.
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Affiliation(s)
| | | | | | - Arojit Mitra
- The Jackson Laboratory, Bar Harbor, ME 04660, USA
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7
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O’Connor C, Keele GR, Martin W, Stodola T, Gatti D, Hoffman BR, Korstanje R, Churchill GA, Reinholdt LG. Unraveling the genetics of arsenic toxicity with cellular morphology QTL. PLoS Genet 2024; 20:e1011248. [PMID: 38662777 PMCID: PMC11075906 DOI: 10.1371/journal.pgen.1011248] [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: 12/13/2023] [Revised: 05/07/2024] [Accepted: 04/03/2024] [Indexed: 05/08/2024] Open
Abstract
The health risks that arise from environmental exposures vary widely within and across human populations, and these differences are largely determined by genetic variation and gene-by-environment (gene-environment) interactions. However, risk assessment in laboratory mice typically involves isogenic strains and therefore, does not account for these known genetic effects. In this context, genetically heterogenous cell lines from laboratory mice are promising tools for population-based screening because they provide a way to introduce genetic variation in risk assessment without increasing animal use. Cell lines from genetic reference populations of laboratory mice offer genetic diversity, power for genetic mapping, and potentially, predictive value for in vivo experimentation in genetically matched individuals. To explore this further, we derived a panel of fibroblast lines from a genetic reference population of laboratory mice (the Diversity Outbred, DO). We then used high-content imaging to capture hundreds of cell morphology traits in cells exposed to the oxidative stress-inducing arsenic metabolite monomethylarsonous acid (MMAIII). We employed dose-response modeling to capture latent parameters of response and we then used these parameters to identify several hundred cell morphology quantitative trait loci (cmQTL). Response cmQTL encompass genes with established associations with cellular responses to arsenic exposure, including Abcc4 and Txnrd1, as well as novel gene candidates like Xrcc2. Moreover, baseline trait cmQTL highlight the influence of natural variation on fundamental aspects of nuclear morphology. We show that the natural variants influencing response include both coding and non-coding variation, and that cmQTL haplotypes can be used to predict response in orthogonal cell lines. Our study sheds light on the major molecular initiating events of oxidative stress that are under genetic regulation, including the NRF2-mediated antioxidant response, cellular detoxification pathways, DNA damage repair response, and cell death trajectories.
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Affiliation(s)
- Callan O’Connor
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
- Graduate School of Biomedical Sciences, Tufts University, Boston, Massachusetts, United States of America
| | - Gregory R. Keele
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
- RTI International, Research Triangle Park, Durham, North Carolina, United States of America
| | - Whitney Martin
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Timothy Stodola
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Daniel Gatti
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Brian R. Hoffman
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Ron Korstanje
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
- Graduate School of Biomedical Sciences, Tufts University, Boston, Massachusetts, United States of America
| | - Gary A. Churchill
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
- Graduate School of Biomedical Sciences, Tufts University, Boston, Massachusetts, United States of America
| | - Laura G. Reinholdt
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
- Graduate School of Biomedical Sciences, Tufts University, Boston, Massachusetts, United States of America
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8
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Lee J, Kim H, Kang YW, Kim Y, Park MY, Song JH, Jo Y, Dao T, Ryu D, Lee J, Oh CM, Park S. LY6D is crucial for lipid accumulation and inflammation in nonalcoholic fatty liver disease. Exp Mol Med 2023:10.1038/s12276-023-01033-w. [PMID: 37394588 PMCID: PMC10394021 DOI: 10.1038/s12276-023-01033-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 02/07/2023] [Accepted: 04/17/2023] [Indexed: 07/04/2023] Open
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a serious metabolic disorder characterized by excess fat accumulation in the liver. Over the past decade, NAFLD prevalence and incidence have risen globally. There are currently no effective licensed drugs for its treatment. Thus, further study is required to identify new targets for NAFLD prevention and treatment. In this study, we fed C57BL6/J mice one of three diets, a standard chow diet, high-sucrose diet, or high-fat diet, and then characterized them. The mice fed a high-sucrose diet had more severely compacted macrovesicular and microvesicular lipid droplets than those in the other groups. Mouse liver transcriptome analysis identified lymphocyte antigen 6 family member D (Ly6d) as a key regulator of hepatic steatosis and the inflammatory response. Data from the Genotype-Tissue Expression project database showed that individuals with high liver Ly6d expression had more severe NAFLD histology than those with low liver Ly6d expression. In AML12 mouse hepatocytes, Ly6d overexpression increased lipid accumulation, while Ly6d knockdown decreased lipid accumulation. Inhibition of Ly6d ameliorated hepatic steatosis in a diet-induced NAFLD mouse model. Western blot analysis showed that Ly6d phosphorylated and activated ATP citrate lyase, which is a key enzyme in de novo lipogenesis. In addition, RNA- and ATAC-sequencing analyses revealed that Ly6d drives NAFLD progression by causing genetic and epigenetic changes. In conclusion, Ly6d is responsible for the regulation of lipid metabolism, and inhibiting Ly6d can prevent diet-induced steatosis in the liver. These findings highlight Ly6d as a novel therapeutic target for NAFLD.
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Affiliation(s)
- Jibeom Lee
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Hyeonhui Kim
- Graduate School of Medical Science, Brain Korea 21 Project, Yonsei University College of Medicine, Seoul, Korea
| | - Yun-Won Kang
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Yumin Kim
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Moon-Young Park
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Ji-Hong Song
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea
| | - Yunju Jo
- Department of Molecular Cell Biology, Sungkyunkwan University (SKKU) School of Medicine, Suwon, Korea
| | - Tam Dao
- Department of Molecular Cell Biology, Sungkyunkwan University (SKKU) School of Medicine, Suwon, Korea
| | - Dongryeol Ryu
- Department of Molecular Cell Biology, Sungkyunkwan University (SKKU) School of Medicine, Suwon, Korea
| | - Junguee Lee
- Department of Pathology, St Mary's Hospital, the Catholic University of Korea, Daejeon, Korea
| | - Chang-Myung Oh
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology, Gwangju, Korea.
| | - Sangkyu Park
- Department of Precision Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea.
- Mitohormesis Research Center, Yonsei University Wonju College of Medicine, Wonju, Gangwon-do, Korea.
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9
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Anczuków O, Airhart S, Chuang JH, Coussens LM, Kuchel GA, Korstanje R, Li S, Lucido AL, McAllister SS, Politi K, Polyak K, Ratliff T, Ren G, Trowbridge JJ, Ucar D, Palucka K. Challenges and opportunities for modeling aging and cancer. Cancer Cell 2023; 41:641-645. [PMID: 37001528 PMCID: PMC10185379 DOI: 10.1016/j.ccell.2023.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/05/2023] [Accepted: 03/06/2023] [Indexed: 04/12/2023]
Abstract
Age is among the main risk factors for cancer, and any cancer study in adults is faced with an aging tissue and organism. Yet, pre-clinical studies are carried out using young mice and are not able to address the impact of aging and associated comorbidities on disease biology and treatment outcomes. Here, we discuss the limitations of current mouse cancer models and suggest strategies for developing novel models to address these major gaps in knowledge and experimental approaches.
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Affiliation(s)
- Olga Anczuków
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
| | - Susie Airhart
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
| | - Jeffrey H Chuang
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Lisa M Coussens
- Department of Cell, Developmental and Cancer Biology, Oregon Health & Science University, Portland, OR, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
| | - George A Kuchel
- UConn Center on Aging, University of Connecticut School of Medicine, Farmington, CT, USA
| | - Ron Korstanje
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
| | - Sheng Li
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Anna Lisa Lucido
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Sandra S McAllister
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Broad Institute of Harvard and MIT, Cambridge, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA
| | - Katerina Politi
- Departments of Pathology, and Medicine (Section of Medical Oncology), Yale School of Medicine and Yale Cancer Center, New Haven, CT, USA
| | - Kornelia Polyak
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; The Broad Institute of MIT and Harvard, Cambridge, MA, USA; The Ludwig Center at Harvard, Boston, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA
| | - Timothy Ratliff
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN, USA
| | - Gary Ren
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
| | | | - Duygu Ucar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Karolina Palucka
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA.
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10
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Jurrjens AW, Seldin MM, Giles C, Meikle PJ, Drew BG, Calkin AC. The potential of integrating human and mouse discovery platforms to advance our understanding of cardiometabolic diseases. eLife 2023; 12:e86139. [PMID: 37000167 PMCID: PMC10065800 DOI: 10.7554/elife.86139] [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: 01/16/2023] [Accepted: 03/15/2023] [Indexed: 04/01/2023] Open
Abstract
Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.
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Affiliation(s)
- Aaron W Jurrjens
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
| | - Marcus M Seldin
- Department of Biological Chemistry and Center for Epigenetics and Metabolism, University of California, Irvine, Irvine, United States
| | - Corey Giles
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
- Baker Department of Cardiovascular Research Translation and Implementation, La Trobe University, Bundoora, Australia
| | - Brian G Drew
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
| | - Anna C Calkin
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Monash University, Melbourne, Australia
- Baker Department of Cardiometabolic Health, University of Melbourne, Melbourne, Australia
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11
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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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Yam P, VerHague M, Albright J, Gertz E, Pardo-Manuel de Villena F, Bennett BJ. Altered macronutrient composition and genetics influence the complex transcriptional network associated with adiposity in the Collaborative Cross. GENES & NUTRITION 2022; 17:13. [PMID: 35945490 PMCID: PMC9364539 DOI: 10.1186/s12263-022-00714-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 07/04/2022] [Indexed: 11/10/2022]
Abstract
Background Obesity is a serious disease with a complex etiology characterized by overaccumulation of adiposity resulting in detrimental health outcomes. Given the liver’s critical role in the biological processes that attenuate adiposity accumulation, elucidating the influence of genetics and dietary patterns on hepatic gene expression is fundamental for improving methods of obesity prevention and treatment. To determine how genetics and diet impact obesity development, mice from 22 strains of the genetically diverse recombinant inbred Collaborative Cross (CC) mouse panel were challenged to either a high-protein or high-fat high-sucrose diet, followed by extensive phenotyping and analysis of hepatic gene expression. Results Over 1000 genes differentially expressed by perturbed dietary macronutrient composition were enriched for biological processes related to metabolic pathways. Additionally, over 9000 genes were differentially expressed by strain and enriched for biological process involved in cell adhesion and signaling. Weighted gene co-expression network analysis identified multiple gene clusters (modules) associated with body fat % whose average expression levels were influenced by both dietary macronutrient composition and genetics. Each module was enriched for distinct types of biological functions. Conclusions Genetic background affected hepatic gene expression in the CC overall, but diet macronutrient differences also altered expression of a specific subset of genes. Changes in macronutrient composition altered gene expression related to metabolic processes, while genetic background heavily influenced a broad range of cellular functions and processes irrespective of adiposity. Understanding the individual role of macronutrient composition, genetics, and their interaction is critical to developing therapeutic strategies and policy recommendations for precision nutrition. Supplementary Information The online version contains supplementary material available at 10.1186/s12263-022-00714-x.
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Bachmann AM, Morel JD, El Alam G, Rodríguez-López S, Imamura de Lima T, Goeminne LJE, Benegiamo G, Loric S, Conti M, Sleiman MB, Auwerx J. Genetic background and sex control the outcome of high-fat diet feeding in mice. iScience 2022; 25:104468. [PMID: 35677645 PMCID: PMC9167980 DOI: 10.1016/j.isci.2022.104468] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/04/2022] [Accepted: 05/19/2022] [Indexed: 01/21/2023] Open
Abstract
The sharp increase in obesity prevalence worldwide is mainly attributable to changes in physical activity and eating behavior but the metabolic and clinical impacts of these obesogenic conditions vary between sexes and genetic backgrounds. This warrants personalized treatments of obesity and its complications, which require a thorough understanding of the diversity of metabolic responses to high-fat diet intake. By analyzing nine genetically diverse mouse strains, we show that much like humans, mice exhibit a huge variety of physiological and biochemical responses to high-fat diet. The strains exhibit various degrees of alterations in their phenotypic makeup. At the transcriptome level, we observe dysregulations of immunity, translation machinery, and mitochondrial genes. At the biochemical level, the enzymatic activity of mitochondrial complexes is affected. The diversity across mouse strains, diets, and sexes parallels that found in humans and supports the use of diverse mouse populations in future mechanistic or preclinical studies on metabolic dysfunctions. Strain- and sex-specific profile of metabolic dysfunction in mice Liver mitochondrial complex activity in vivo associates with metabolic traits Open data source for evaluating different mouse strains for metabolic disease Interactive data exploration through an online application
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Affiliation(s)
- Alexis Maximilien Bachmann
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Jean-David Morel
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Gaby El Alam
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Sandra Rodríguez-López
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Tanes Imamura de Lima
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Ludger J E Goeminne
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Giorgia Benegiamo
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Sylvain Loric
- Inserm U938 CRSA, St Antoine University Hospital, Paris, France
| | - Marc Conti
- Inserm U938 CRSA, St Antoine University Hospital, Paris, France.,Integracell, Longjumeau, France
| | - Maroun Bou Sleiman
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne, Lausanne 1015, Switzerland
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Auwerx C, Sadler MC, Reymond A, Kutalik Z. From pharmacogenetics to pharmaco-omics: Milestones and future directions. HGG ADVANCES 2022; 3:100100. [PMID: 35373152 PMCID: PMC8971318 DOI: 10.1016/j.xhgg.2022.100100] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Marie C. Sadler
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- University Center for Primary Care and Public Health, Lausanne, Switzerland
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15
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Iglesias-Carres L, Neilson AP. Utilizing preclinical models of genetic diversity to improve translation of phytochemical activities from rodents to humans and inform personalized nutrition. Food Funct 2021; 12:11077-11105. [PMID: 34672309 DOI: 10.1039/d1fo02782d] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Mouse models are an essential tool in different areas of research, including nutrition and phytochemical research. Traditional inbred mouse models have allowed the discovery of therapeutical targets and mechanisms of action and expanded our knowledge of health and disease. However, these models lack the genetic variability typically found in human populations, which hinders the translatability of the results found in mice to humans. The development of genetically diverse mouse models, such as the collaborative cross (CC) or the diversity outbred (DO) models, has been a useful tool to overcome this obstacle in many fields, such as cancer, immunology and toxicology. However, these tools have not yet been widely adopted in the field of phytochemical research. As demonstrated in other disciplines, use of CC and DO models has the potential to provide invaluable insights for translation of phytochemicals from rodents to humans, which are desperately needed given the challenges and numerous failed clinical trials in this field. These models may prove informative for personalized use of phytochemicals in humans, including: predicting interindividual variability in phytochemical bioavailability and efficacy, identifying genetic loci or genes governing response to phytochemicals, identifying phytochemical mechanisms of action and therapeutic targets, and understanding the impact of genetic variability on individual response to phytochemicals. Such insights would prove invaluable for personalized implementation of phytochemicals in humans. This review will focus on the current work performed with genetically diverse mouse populations, and the research opportunities and advantages that these models can offer to phytochemical research.
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Affiliation(s)
- Lisard Iglesias-Carres
- Plants for Human Health Institute, Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University, Kannapolis, NC, USA.
| | - Andrew P Neilson
- Plants for Human Health Institute, Department of Food, Bioprocessing and Nutrition Sciences, North Carolina State University, Kannapolis, NC, USA.
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Geuther B, Chen M, Galante RJ, Han O, Lian J, George J, Pack AI, Kumar V. High-throughput visual assessment of sleep stages in mice using machine learning. Sleep 2021; 45:6414386. [PMID: 34718812 DOI: 10.1093/sleep/zsab260] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 08/23/2021] [Indexed: 11/13/2022] Open
Abstract
STUDY OBJECTIVES Sleep is an important biological process that is perturbed in numerous diseases, and assessment its substages currently requires implantation of electrodes to carry out electroencephalogram/electromyogram (EEG/EMG) analysis. Although accurate, this method comes at a high cost of invasive surgery and experts trained to score EEG/EMG data. Here, we leverage modern computer vision methods to directly classify sleep substages from video data. This bypasses the need for surgery and expert scoring, provides a path to high-throughput studies of sleep in mice. METHODS We collected synchronized high-resolution video and EEG/EMG data in 16 male C57BL/6J mice. We extracted features from the video that are time and frequency-based and used the human expert-scored EEG/EMG data to train a visual classifier. We investigated several classifiers and data augmentation methods. RESULTS Our visual sleep classifier proved to be highly accurate in classifying wake, non-rapid eye movement sleep (NREM), and rapid eye movement sleep (REM) states, and achieves an overall accuracy of 0.92 +/- 0.05 (mean +/- SD). We discover and genetically validate video features that correlate with breathing rates, and show low and high variability in NREM and REM sleep, respectively. Finally, we apply our methods to non-invasively detect that sleep stage disturbances induced by amphetamine administration. CONCLUSIONS We conclude that machine learning based visual classification of sleep is a viable alternative to EEG/EMG based scoring. Our results will enable non-invasive high-throughput sleep studies and will greatly reduce the barrier to screening mutant mice for abnormalities in sleep.
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Affiliation(s)
- Brian Geuther
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME
| | - Mandy Chen
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME
| | - Raymond J Galante
- University of Pennsylvania, John Miclot Professor of Medicine, Division of Sleep Medicine/Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, 125 South 31st Street, Suite 2100, Philadelphia, PA
| | - Owen Han
- University of Pennsylvania, John Miclot Professor of Medicine, Division of Sleep Medicine/Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, 125 South 31st Street, Suite 2100, Philadelphia, PA
| | - Jie Lian
- University of Pennsylvania, John Miclot Professor of Medicine, Division of Sleep Medicine/Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, 125 South 31st Street, Suite 2100, Philadelphia, PA
| | - Joshy George
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME
| | - Allan I Pack
- University of Pennsylvania, John Miclot Professor of Medicine, Division of Sleep Medicine/Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, 125 South 31st Street, Suite 2100, Philadelphia, PA
| | - Vivek Kumar
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME
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Forejt J, Jansa P, Parvanov E. Hybrid sterility genes in mice (Mus musculus): a peculiar case of PRDM9 incompatibility. Trends Genet 2021; 37:1095-1108. [PMID: 34238593 DOI: 10.1016/j.tig.2021.06.008] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 06/08/2021] [Accepted: 06/10/2021] [Indexed: 12/14/2022]
Abstract
Hybrid sterility is a critical step in the evolution of reproductive barriers between diverging taxa during the process of speciation. Recent studies of young subspecies of the house mouse revealed a multigenic nature and frequent polymorphism of hybrid sterility genes as well as the recurrent engagement of the meiosis-specific gene PR domain-containing 9 (Prdm9) and X-linked loci. Prdm9-controlled hybrid sterility is essentially chromosomal in nature, conditioned by the sequence divergence between subspecies. Depending on the Prdm9 interallelic interactions and the X-linked Hstx2 locus, the same homologs either regularly recombine and synapse, or show impaired DNA DSB repair, asynapsis, and early meiotic arrest. Thus, Prdm9-dependent hybrid sterility points to incompatibilities affecting meiotic recombination as a possible mechanism of reproductive isolation between (sub)species.
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Affiliation(s)
- Jiri Forejt
- Department of Mouse Molecular Genetics, Institute of Molecular Genetics, Czech Academy of Sciences, Vestec 252 50, Czech Republic.
| | - Petr Jansa
- Department of Mouse Molecular Genetics, Institute of Molecular Genetics, Czech Academy of Sciences, Vestec 252 50, Czech Republic
| | - Emil Parvanov
- Department of Mouse Molecular Genetics, Institute of Molecular Genetics, Czech Academy of Sciences, Vestec 252 50, Czech Republic
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