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Johnson EO, Fisher HS, Sullivan KA, Corradin O, Sanchez-Roige S, Gaddis NC, Sami YN, Townsend A, Teixeira Prates E, Pavicic M, Kruse P, Chesler EJ, Palmer AA, Troiani V, Bubier JA, Jacobson DA, Maher BS. An emerging multi-omic understanding of the genetics of opioid addiction. J Clin Invest 2024; 134:e172886. [PMID: 39403933 PMCID: PMC11473141 DOI: 10.1172/jci172886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2024] Open
Abstract
Opioid misuse, addiction, and associated overdose deaths remain global public health crises. Despite the tremendous need for pharmacological treatments, current options are limited in number, use, and effectiveness. Fundamental leaps forward in our understanding of the biology driving opioid addiction are needed to guide development of more effective medication-assisted therapies. This Review focuses on the omics-identified biological features associated with opioid addiction. Recent GWAS have begun to identify robust genetic associations, including variants in OPRM1, FURIN, and the gene cluster SCAI/PPP6C/RABEPK. An increasing number of omics studies of postmortem human brain tissue examining biological features (e.g., histone modification and gene expression) across different brain regions have identified broad gene dysregulation associated with overdose death among opioid misusers. Drawn together by meta-analysis and multi-omic systems biology, and informed by model organism studies, key biological pathways enriched for opioid addiction-associated genes are emerging, which include specific receptors (e.g., GABAB receptors, GPCR, and Trk) linked to signaling pathways (e.g., Trk, ERK/MAPK, orexin) that are associated with synaptic plasticity and neuronal signaling. Studies leveraging the agnostic discovery power of omics and placing it within the context of functional neurobiology will propel us toward much-needed, field-changing breakthroughs, including identification of actionable targets for drug development to treat this devastating brain disease.
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Affiliation(s)
- Eric O. Johnson
- GenOmics and Translational Research Center and
- Fellow Program, RTI International, Research Triangle Park, North Carolina, USA
| | | | - Kyle A. Sullivan
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Olivia Corradin
- Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, UCSD, La Jolla, California, USA
- Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | | | - Yasmine N. Sami
- Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Alice Townsend
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | | | - Mirko Pavicic
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Peter Kruse
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | | | - Abraham A. Palmer
- Department of Psychiatry, UCSD, La Jolla, California, USA
- Institute for Genomic Medicine, UCSD, La Jolla, CA, USA
| | - Vanessa Troiani
- Geisinger College of Health Sciences, Scranton, Pennsylvania, USA
| | | | - Daniel A. Jacobson
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Brion S. Maher
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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Zhang X, Wang Y, Zheng M, Wei Q, Zhang R, Zhu K, Zhai Q, Xu Y. IMPC-based screening revealed that ROBO1 can regulate osteoporosis by inhibiting osteogenic differentiation. Front Cell Dev Biol 2024; 12:1450215. [PMID: 39439909 PMCID: PMC11494888 DOI: 10.3389/fcell.2024.1450215] [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: 07/10/2024] [Accepted: 09/26/2024] [Indexed: 10/25/2024] Open
Abstract
Introduction The utilization of denosumab in treating osteoporosis highlights promising prospects for osteoporosis intervention guided by gene targets. While omics-based research into osteoporosis pathogenesis yields a plethora of potential gene targets for clinical transformation, identifying effective gene targets has posed challenges. Methods We first queried the omics data of osteoporosis clinical samples on PubMed, used International Mouse Phenotyping Consortium (IMPC) to screen differentially expressed genes, and conducted preliminary functional verification of candidate genes in human Saos2 cells through osteogenic differentiation and mineralization experiments. We then selected the candidate genes with the most significant effects on osteogenic differentiation and further verified the osteogenic differentiation and mineralization functions in mouse 3T3-E1 and bone marrow mesenchymal stem cells (BMSC). Finally, we used RNA-seq to explore the regulation of osteogenesis by the target gene. Results We identified PPP2R2A, RRBP1, HSPB6, SLC22A15, ADAMTS4, ATP8B1, CTNNB1, ROBO1, and EFR3B, which may contribute to osteoporosis. ROBO1 was the most significant regulator of osteogenesis in both human and mouse osteoblast. The inhibitory effect of Robo1 knockdown on osteogenic differentiation may be related to the activation of inflammatory signaling pathways. Conclusion Our study provides several novel molecular mechanisms involved in the pathogenesis of osteoporosis. ROBO1 is a potential target for osteoporosis intervention.
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Affiliation(s)
- Xiangzheng Zhang
- The Osteoporosis Clinical Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yike Wang
- Department of Orthopaedics, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Miao Zheng
- The Osteoporosis Clinical Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Qi Wei
- The Osteoporosis Clinical Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Ruizhi Zhang
- Department of Orthopaedics, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Keyu Zhu
- Department of Orthopaedics, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Qiaocheng Zhai
- Division of Spine Surgery, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People’s Hospital, Quzhou, China
| | - Youjia Xu
- The Osteoporosis Clinical Center, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Department of Orthopaedics, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China
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53
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Rivest JF, Carter S, Goupil C, Antérieux P, Cyr D, Ung RV, Dal Soglio D, Mac-Way F, Waters PJ, Paganelli M, Doyon Y. In vivo dissection of the mouse tyrosine catabolic pathway with CRISPR-Cas9 identifies modifier genes affecting hereditary tyrosinemia type 1. Genetics 2024; 228:iyae139. [PMID: 39178380 PMCID: PMC11457941 DOI: 10.1093/genetics/iyae139] [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: 11/08/2023] [Accepted: 08/12/2024] [Indexed: 08/25/2024] Open
Abstract
Hereditary tyrosinemia type 1 is an autosomal recessive disorder caused by mutations (pathogenic variants) in fumarylacetoacetate hydrolase, an enzyme involved in tyrosine degradation. Its loss results in the accumulation of toxic metabolites that mainly affect the liver and kidneys and can lead to severe liver disease and liver cancer. Tyrosinemia type 1 has a global prevalence of approximately 1 in 100,000 births but can reach up to 1 in 1,500 births in some regions of Québec, Canada. Mutating functionally related "modifier' genes (i.e. genes that, when mutated, affect the phenotypic impacts of mutations in other genes) is an emerging strategy for treating human genetic diseases. In vivo somatic genome editing in animal models of these diseases is a powerful means to identify modifier genes and fuel treatment development. In this study, we demonstrate that mutating additional enzymes in the tyrosine catabolic pathway through liver-specific genome editing can relieve or worsen the phenotypic severity of a murine model of tyrosinemia type 1. Neonatal gene delivery using recombinant adeno-associated viral vectors expressing Staphylococcus aureus Cas9 under the control of a liver-specific promoter led to efficient gene disruption and metabolic rewiring of the pathway, with systemic effects that were distinct from the phenotypes observed in whole-body knockout models. Our work illustrates the value of using in vivo genome editing in model organisms to study the direct effects of combining pathological mutations with modifier gene mutations in isogenic settings.
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Affiliation(s)
- Jean-François Rivest
- Centre Hospitalier Universitaire de Québec Research Center and Faculty of Medicine, Laval University, Québec City, QC G1V 4G2, Canada
- Université Laval Cancer Research Centre, Québec City, QC G1V 0A6, Canada
| | - Sophie Carter
- Centre Hospitalier Universitaire de Québec Research Center and Faculty of Medicine, Laval University, Québec City, QC G1V 4G2, Canada
- Université Laval Cancer Research Centre, Québec City, QC G1V 0A6, Canada
| | - Claudia Goupil
- Centre Hospitalier Universitaire de Québec Research Center and Faculty of Medicine, Laval University, Québec City, QC G1V 4G2, Canada
- Université Laval Cancer Research Centre, Québec City, QC G1V 0A6, Canada
| | - Pénélope Antérieux
- Centre Hospitalier Universitaire de Québec Research Center and Faculty of Medicine, Laval University, Québec City, QC G1V 4G2, Canada
- Université Laval Cancer Research Centre, Québec City, QC G1V 0A6, Canada
| | - Denis Cyr
- Medical Genetics Service, Dept. Laboratory Medicine and Dept. Pediatrics, Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC J1H 5N4, Canada
| | - Roth-Visal Ung
- Centre Hospitalier Universitaire de Québec Research Center and Faculty of Medicine, Laval University, Québec City, QC G1V 4G2, Canada
| | - Dorothée Dal Soglio
- Centre Hospitalier Universitaire Sainte-Justine Research Center, Université de Montréal, Montréal, QC H3T 1C5, Canada
| | - Fabrice Mac-Way
- Centre Hospitalier Universitaire de Québec Research Center and Faculty of Medicine, Laval University, Québec City, QC G1V 4G2, Canada
| | - Paula J Waters
- Medical Genetics Service, Dept. Laboratory Medicine and Dept. Pediatrics, Centre Hospitalier Universitaire de Sherbrooke (CHUS), Sherbrooke, QC J1H 5N4, Canada
| | - Massimiliano Paganelli
- Centre Hospitalier Universitaire Sainte-Justine Research Center, Université de Montréal, Montréal, QC H3T 1C5, Canada
| | - Yannick Doyon
- Centre Hospitalier Universitaire de Québec Research Center and Faculty of Medicine, Laval University, Québec City, QC G1V 4G2, Canada
- Université Laval Cancer Research Centre, Québec City, QC G1V 0A6, Canada
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54
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Pavešković M, De-Paula RB, Ojelade SA, Tantry EK, Kochukov MY, Bao S, Veeraragavan S, Garza AR, Srivastava S, Song SY, Fujita M, Duong DM, Bennett DA, De Jager PL, Seyfried NT, Dickinson ME, Heaney JD, Arenkiel BR, Shulman JM. Alzheimer's disease risk gene CD2AP is a dose-sensitive determinant of synaptic structure and plasticity. Hum Mol Genet 2024; 33:1815-1832. [PMID: 39146503 PMCID: PMC11458016 DOI: 10.1093/hmg/ddae115] [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: 02/27/2024] [Revised: 06/15/2024] [Indexed: 08/17/2024] Open
Abstract
CD2-Associated protein (CD2AP) is a candidate susceptibility gene for Alzheimer's disease, but its role in the mammalian central nervous system remains largely unknown. We show that CD2AP protein is broadly expressed in the adult mouse brain, including within cortical and hippocampal neurons, where it is detected at pre-synaptic terminals. Deletion of Cd2ap altered dendritic branching and spine density, and impaired ubiquitin-proteasome system activity. Moreover, in mice harboring either one or two copies of a germline Cd2ap null allele, we noted increased paired-pulse facilitation at hippocampal Schaffer-collateral synapses, consistent with a haploinsufficient requirement for pre-synaptic release. Whereas conditional Cd2ap knockout in the brain revealed no gross behavioral deficits in either 3.5- or 12-month-old mice, Cd2ap heterozygous mice demonstrated subtle impairments in discrimination learning using a touchscreen task. Based on unbiased proteomics, partial or complete loss of Cd2ap triggered perturbation of proteins with roles in protein folding, lipid metabolism, proteostasis, and synaptic function. Overall, our results reveal conserved, dose-sensitive requirements for CD2AP in the maintenance of neuronal structure and function, including synaptic homeostasis and plasticity, and inform our understanding of possible cell-type specific mechanisms in Alzheimer's Disease.
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Affiliation(s)
- Matea Pavešković
- Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Ruth B De-Paula
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Quantitative and Computational Biology Program, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Shamsideen A Ojelade
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Evelyne K Tantry
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Mikhail Y Kochukov
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Suyang Bao
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Development, Disease Models, and Therapeutics Graduate Program, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Surabi Veeraragavan
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Alexandra R Garza
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Snigdha Srivastava
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Medical Scientist Training Program, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Si-Yuan Song
- Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
| | - Masashi Fujita
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, United States
| | - Duc M Duong
- Departments of Biochemistry and Neurology, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, United States
| | - David A Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, 600 S. Paulina Street, Chicago, IL 60612, United States
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, United States
| | - Nicholas T Seyfried
- Departments of Biochemistry and Neurology, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, United States
| | - Mary E Dickinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Jason D Heaney
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Benjamin R Arenkiel
- Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Joshua M Shulman
- Department of Neuroscience, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, 1250 Moursund Street, Houston, TX 77030, United States
- Department of Neurology, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
- Center for Alzheimer’s and Neurodegenerative Diseases, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
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Rad A, Bartsch O, Bakhtiari S, Zhu C, Xu Y, Monteiro FP, Kok F, Vulto-van Silfhout AT, Kruer MC, Bowl MR, Vona B. Expanding the spectrum of phenotypes for MPDZ: Report of four unrelated families and review of the literature. Clin Genet 2024; 106:413-426. [PMID: 38857973 DOI: 10.1111/cge.14563] [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: 02/22/2024] [Revised: 04/24/2024] [Accepted: 05/13/2024] [Indexed: 06/12/2024]
Abstract
MPDZ, a gene with diverse functions mediating cell-cell junction interactions, receptor signaling, and binding multivalent scaffold proteins, is associated with a spectrum of clinically heterogeneous phenotypes with biallelic perturbation. Despite its clinical relevance, the mechanistic underpinnings of these variants remain elusive, underscoring the need for extensive case series and functional investigations. In this study, we conducted a systematic review of cases in the literature through two electronic databases following the PRISMA guidelines. We selected nine studies, including 18 patients, with homozygous or compound heterozygous variants in MPDZ and added five patients from four unrelated families with novel MPDZ variants. To evaluate the role of Mpdz on hearing, we analyzed available auditory electrophysiology data from a knockout murine model (Mpdzem1(IMPC)J/em1(IMPC)J) generated by the International Mouse Phenotyping Consortium. Using exome and genome sequencing, we identified three families with compound heterozygous variants, and one family with a homozygous frameshift variant. MPDZ-related disease is clinically heterogenous with hydrocephaly, vision impairment, hearing impairment and cardiovascular disease occurring most frequently. Additionally, we describe two unrelated patients with spasticity, expanding the phenotypic spectrum. Our murine analysis of the Mpdzem1(IMPC)J/em1(IMPC)J allele showed severe hearing impairment. Overall, we expand understanding of MPDZ-related phenotypes and highlight hearing impairment and spasticity among the heterogeneous phenotypes.
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Affiliation(s)
- Aboulfazl Rad
- Department of Otolaryngology - Head and Neck Surgery, Tübingen Hearing Research Centre, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Oliver Bartsch
- Medical Care Centre Section Human Genetics and Institute of Human Genetics, University Medical Centre of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Somayeh Bakhtiari
- Barrow Neurological Institute, Phoenix Children's Hospital, Phoenix, Arizona, USA
- Department of Child Health, Cellular and Molecular Medicine, Genetics, and Neurology, University of Arizona College of Medicine-Phoenix, Phoenix, Arizona, USA
| | - Changlian Zhu
- Center for Brain Repair and Rehabilitation, Institute of Neuroscience and Physiology, University of Gothenburg, Göteborg, Sweden
- Henan Key Laboratory of Child Brain Injury and Henan Pediatric Clinical Research Center, Institute of Neuroscience and Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yiran Xu
- Henan Key Laboratory of Child Brain Injury and Henan Pediatric Clinical Research Center, Institute of Neuroscience and Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | | | - Fernando Kok
- Medical Department, Mendelics Genomic Analysis, Sao Paulo, Brazil
- Neurogenetics, Neurology Department, Hospital das Clínicas da Universidade de São Paulo, São Paulo, Brazil
| | - Anneke T Vulto-van Silfhout
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, the Netherlands
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Michael C Kruer
- Barrow Neurological Institute, Phoenix Children's Hospital, Phoenix, Arizona, USA
- Department of Child Health, Cellular and Molecular Medicine, Genetics, and Neurology, University of Arizona College of Medicine-Phoenix, Phoenix, Arizona, USA
| | - Michael R Bowl
- UCL Ear Institute, University College London, London, UK
| | - Barbara Vona
- Department of Otolaryngology - Head and Neck Surgery, Tübingen Hearing Research Centre, Eberhard Karls University Tübingen, Tübingen, Germany
- Institute of Human Genetics, University Medical Center Göttingen, Göttingen, Germany
- Institute for Auditory Neuroscience and InnerEarLab, University Medical Center Göttingen, Göttingen, Germany
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56
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Lecca M, Mauri L, Gana S, Del Longo A, Morelli F, Nicotra R, Plumari M, Galli J, Sirchia F, Valente EM, Cavallari U, Mazza M, Signorini S, Errichiello E. Novel molecular, structural and clinical findings in an Italian cohort of congenital cataract. Clin Genet 2024; 106:403-412. [PMID: 38840272 DOI: 10.1111/cge.14568] [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: 01/12/2024] [Revised: 05/16/2024] [Accepted: 05/24/2024] [Indexed: 06/07/2024]
Abstract
The current genetic diagnostic workup of congenital cataract (CC) is mainly based on NGS panels, whereas exome sequencing (ES) has occasionally been employed. In this multicentre study, we investigated by ES the detection yield, mutational spectrum and genotype-phenotype correlations in a CC cohort recruited between 2020 and mid-2022. The cohort consisted of 67 affected individuals from 51 unrelated families and included both non-syndromic (75%) and syndromic (25%) phenotypes, with extra-CC ocular/visual features present in both groups (48% and 76%, respectively). The functional effect of variants was predicted by 3D modelling and hydropathy properties changes. Variant clustering was used for the in-depth assessment of genotype-phenotype correlations. A diagnostic (pathogenic or likely pathogenic) variant was identified in 19 out of 51 probands/families (~37%). In a further 14 probands/families a candidate variant was identified: in 12 families a VUS was detected, of which 9 were considered plausibly pathogenic (i.e., 4 or 5 points according to ACMG criteria), while in 2 probands ES identified a single variant in an autosomal recessive gene associated with CC. Eighteen probands/families, manifesting primarily non-syndromic CC (15/18, 83%), remained unsolved. The identified variants (8 P, 12 LP, 10 VUS-PP, and 5 VUS), half of which were unreported in the literature, affected five functional categories of genes involved in transcription/splicing, lens formation/homeostasis (i.e., crystallin genes), membrane signalling, cell-cell interaction, and immune response. A phenotype-specific variant clustering was observed in four genes (KIF1A, MAF, PAX6, SPTAN1), whereas variable expressivity and potential phenotypic expansion in two (BCOR, NHS) and five genes (CWC27, KIF1A, IFIH1, PAX6, SPTAN1), respectively. Finally, ES allowed to detect variants in six genes not commonly included in commercial CC panels. These findings broaden the genotype-phenotype correlations in one of the largest CC cohorts tested by ES, providing novel insights into the underlying pathogenetic mechanisms and emphasising the power of ES as first-tier test.
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Affiliation(s)
- Mauro Lecca
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
| | - Lucia Mauri
- Medical Genetics Unit, Department of Laboratory Medicine, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Simone Gana
- Medical Genetics Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Alessandra Del Longo
- Pediatric Ophthalmology Unit, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
- European Reference Network on Eye Diseases (ERN-EYE), ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Federica Morelli
- Developmental Neuro-ophthalmology Unit, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Roberta Nicotra
- Developmental Neuro-ophthalmology Unit, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | - Massimo Plumari
- Medical Genetics Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Jessica Galli
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
- Unit of Child Neurology and Psychiatry, ASST Spedali Civili of Brescia, Brescia, Italy
| | - Fabio Sirchia
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
- Medical Genetics Unit, IRCCS San Matteo Foundation, Pavia, Italy
| | - Enza Maria Valente
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
- Medical Genetics Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Ugo Cavallari
- Medical Genetics Unit, Department of Laboratory Medicine, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Marco Mazza
- Pediatric Ophthalmology Unit, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
- European Reference Network on Eye Diseases (ERN-EYE), ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Sabrina Signorini
- Developmental Neuro-ophthalmology Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Edoardo Errichiello
- Department of Molecular Medicine, University of Pavia, Pavia, Italy
- Medical Genetics Unit, IRCCS Mondino Foundation, Pavia, Italy
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57
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Madsen AL, Bonàs-Guarch S, Gheibi S, Prasad R, Vangipurapu J, Ahuja V, Cataldo LR, Dwivedi O, Hatem G, Atla G, Guindo-Martínez M, Jørgensen AM, Jonsson AE, Miguel-Escalada I, Hassan S, Linneberg A, Ahluwalia TS, Drivsholm T, Pedersen O, Sørensen TIA, Astrup A, Witte D, Damm P, Clausen TD, Mathiesen E, Pers TH, Loos RJF, Hakaste L, Fex M, Grarup N, Tuomi T, Laakso M, Mulder H, Ferrer J, Hansen T. Genetic architecture of oral glucose-stimulated insulin release provides biological insights into type 2 diabetes aetiology. Nat Metab 2024; 6:1897-1912. [PMID: 39420167 PMCID: PMC11496110 DOI: 10.1038/s42255-024-01140-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 09/02/2024] [Indexed: 10/19/2024]
Abstract
The genetics of β-cell function (BCF) offer valuable insights into the aetiology of type 2 diabetes (T2D)1,2. Previous studies have expanded the catalogue of BCF genetic associations through candidate gene studies3-7, large-scale genome-wide association studies (GWAS) of fasting BCF8,9 or functional islet studies on T2D risk variants10-14. Nonetheless, GWAS focused on BCF traits derived from oral glucose tolerance test (OGTT) data have been limited in sample size15,16 and have often overlooked the potential for related traits to capture distinct genetic features of insulin-producing β-cells17,18. We reasoned that investigating the genetic basis of multiple BCF estimates could provide a broader understanding of β-cell physiology. Here, we aggregate GWAS data of eight OGTT-based BCF traits from ~26,000 individuals of European descent, identifying 55 independent genetic associations at 44 loci. By examining the effects of BCF genetic signals on related phenotypes, we uncover diverse disease mechanisms whereby genetic regulation of BCF may influence T2D risk. Integrating BCF-GWAS data with pancreatic islet transcriptomic and epigenomic datasets reveals 92 candidate effector genes. Gene silencing in β-cell models highlights ACSL1 and FAM46C as key regulators of insulin secretion. Overall, our findings yield insights into the biology of insulin release and the molecular processes linking BCF to T2D risk, shedding light on the heterogeneity of T2D pathophysiology.
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Affiliation(s)
- A L Madsen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - S Bonàs-Guarch
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - S Gheibi
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University, Malmö, Sweden
| | - R Prasad
- Department of Clinical Sciences, Unit of Genomics, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - J Vangipurapu
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - V Ahuja
- Institute for Molecular Medicine Finland and Research Program of Clinical and Molecular Medicine, University of Helsinki, Helsinki, Finland
| | - L R Cataldo
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University, Malmö, Sweden
| | - O Dwivedi
- Institute for Molecular Medicine Finland and Research Program of Clinical and Molecular Medicine, University of Helsinki, Helsinki, Finland
- Folkhalsan Research Centre, Helsinki, Finland
| | - G Hatem
- Department of Clinical Sciences, Unit of Genomics, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - G Atla
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - M Guindo-Martínez
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - A M Jørgensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - A E Jonsson
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - I Miguel-Escalada
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - S Hassan
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - A Linneberg
- Center for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health Sciences, UCPH, Copenhagen, Denmark
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- The Bioinformatics Center, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - T Drivsholm
- Center for Clinical Research and Prevention, Copenhagen University Hospital-Bispebjerg and Frederiksberg, Copenhagen, Denmark
- Section of General Practice, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - O Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - T I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
- Department of Public Health Sciences (Section of Epidemiology), University of Copenhagen, Copenhagen, Denmark
| | - A Astrup
- Novo Nordisk Fonden, Hellerup, Denmark
| | - D Witte
- Institut for Folkesundhed-Epidemiologi, Aarhus University, Aarhus, Denmark
| | - P Damm
- Center for Pregnant Women with Diabetes and Department of Gynecology, Fertility, and Obstetrics and Department of Clinical Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - T D Clausen
- Center for Pregnant Women with Diabetes and Department of Gynecology, Fertility, and Obstetrics and Department of Clinical Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - E Mathiesen
- Center for Pregnant Women with Diabetes, Department of Nephrology and Endocrinology and Department of Clinical Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - T H Pers
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - R J F Loos
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - L Hakaste
- Institute for Molecular Medicine Finland and Research Program of Clinical and Molecular Medicine, University of Helsinki, Helsinki, Finland
- Folkhalsan Research Centre, Helsinki, Finland
| | - M Fex
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University, Malmö, Sweden
| | - N Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark
| | - T Tuomi
- Department of Clinical Sciences, Unit of Genomics, Diabetes and Endocrinology, Lund University, Malmö, Sweden
- Institute for Molecular Medicine Finland and Research Program of Clinical and Molecular Medicine, University of Helsinki, Helsinki, Finland
- Folkhalsan Research Centre, Helsinki, Finland
- Helsinki University Hospital, Abdominal Centre / Endocrinology, Helsinki, Finland
| | - M Laakso
- Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - H Mulder
- Department of Clinical Sciences, Unit of Molecular Metabolism, Lund University, Malmö, Sweden
| | - J Ferrer
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain.
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
| | - T Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen (UCPH), Copenhagen, Denmark.
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58
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Van Sciver RE, Caspary T. A prioritization tool for cilia-associated genes and their in vivo resources unveils new avenues for ciliopathy research. Dis Model Mech 2024; 17:dmm052000. [PMID: 39263856 PMCID: PMC11512102 DOI: 10.1242/dmm.052000] [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: 06/19/2024] [Accepted: 09/04/2024] [Indexed: 09/13/2024] Open
Abstract
Defects in ciliary signaling or mutations in proteins that localize to primary cilia lead to a class of human diseases known as ciliopathies. Approximately 10% of mammalian genes encode cilia-associated proteins, and a major gap in the cilia research field is knowing which genes to prioritize to study and finding the in vivo vertebrate mutant alleles and reagents available for their study. Here, we present a unified resource listing the cilia-associated human genes cross referenced to available mouse and zebrafish mutant alleles, and their associated phenotypes, as well as expression data in the kidney and functional data for vertebrate Hedgehog signaling. This resource empowers researchers to easily sort and filter genes based on their own expertise and priorities, cross reference with newly generated -omics datasets, and quickly find in vivo resources and phenotypes associated with a gene of interest.
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Affiliation(s)
- Robert E. Van Sciver
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Tamara Caspary
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
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59
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McIlwraith EK, Loganathan N, Mak KWY, He W, Belsham DD. Phoenixin knockout mice show no impairment in fertility or differences in metabolic response to a high-fat diet, but exhibit behavioral differences in an open field test. J Neuroendocrinol 2024; 36:e13398. [PMID: 38733120 DOI: 10.1111/jne.13398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Revised: 03/27/2024] [Accepted: 04/21/2024] [Indexed: 05/13/2024]
Abstract
Phoenixin (PNX) is a conserved secreted peptide that was identified 10 years ago with numerous studies published on its pleiotropic functions. PNX is associated with estrous cycle length, protection from a high-fat diet, and reduction of anxiety behavior. However, no study had yet evaluated the impact of deleting PNX in the whole animal. We sought to evaluate a mouse model lacking the PNX parent gene, small integral membrane protein 20 (Smim20), and the resulting effect on reproduction, energy homeostasis, and anxiety. We found that the Smim20 knockout mice had normal fertility and estrous cycle lengths. Consistent with normal fertility, the hypothalamii of the knockout mice showed no changes in the levels of reproduction-related genes, but the male mice had some changes in energy homeostasis-related genes, such as melanocortin receptor 4 (Mc4r). When placed on a high-fat diet, the wildtype and knockout mice responded similarly, but the male heterozygous mice gained slightly less weight. When placed in an open field test box, the female knockout mice traveled less distance in the outer zone, indicating alterations in anxiety or locomotor behavior. In summary, the homozygous knockout of PNX did not alter fertility and modestly alters a few neuroendocrine genes in response to a high-fat diet, especially in the female mice. However, it altered the behavior of mice in an open field test. PNX therefore may not be crucial for reproductive function or weight, however, we cannot rule out possible compensatory mechanisms in the knockout model. Understanding the role of PNX in physiology may ultimately lead to an enhanced understanding of neuroendocrine mechanisms involving this enigmatic peptide.
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Affiliation(s)
- Emma K McIlwraith
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Neruja Loganathan
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Kimberly W Y Mak
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Wenyuan He
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Denise D Belsham
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
- Department of Obstetrics and Gynaecology, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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60
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Standley A, Xie J, Lau AW, Grote L, Gifford AJ. Working with Miraculous Mice: Mus musculus as a Model Organism. Curr Protoc 2024; 4:e70021. [PMID: 39435766 DOI: 10.1002/cpz1.70021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2024]
Abstract
The laboratory mouse has been described as a "miracle" model organism, providing a window by which we may gain an understanding of ourselves. Since the first recorded mouse experiment in 1664, the mouse has become the most used animal model in biomedical research. Mice are ideally suited as a model organism because of their small size, short gestation period, large litter size, and genetic similarity to humans. This article provides a broad overview of the laboratory mouse as a model organism and is intended for undergraduates and those new to working with mice. We delve into the history of the laboratory mouse and outline important terminology to accurately describe research mice. The types of laboratory mice available to researchers are reviewed, including outbred stocks, inbred strains, immunocompromised mice, and genetically engineered mice. The critical role mice have played in advancing knowledge in the areas of oncology, immunology, and pharmacology is highlighted by examining the significant contribution of mice to Nobel Prize winning research. International mouse mutagenesis programs and accurate phenotyping of mouse models are outlined. We also explain important considerations for working with mice, including animal ethics; the welfare principles of replacement, refinement, and reduction; and the choice of mouse model in experimental design. Finally, we present practical advice for maintaining a mouse colony, which involves adequate training of staff, the logistics of mouse housing, monitoring colony health, and breeding strategies. Useful resources for working with mice are also listed. The aim of this overview is to equip the reader with a broad appreciation of the enormous potential and some of the complexities of working with the laboratory mouse in a quest to improve human health. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC.
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Affiliation(s)
- Anick Standley
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia
| | - Jinhan Xie
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia
| | - Angelica Wy Lau
- Garvan Institute of Medical Research, St Vincent's Clinical School, Darlinghurst, NSW, Australia
| | - Lauren Grote
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia
| | - Andrew J Gifford
- Children's Cancer Institute, Lowy Cancer Research Centre, UNSW Sydney, Sydney, NSW, Australia
- Anatomical Pathology, NSW Heath Pathology, Prince of Wales Hospital, Randwick, NSW, Australia
- School of Clinical Medicine, UNSW Medicine & Health, UNSW Sydney, Sydney, NSW, Australia
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61
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Matentzoglu N, Bello SM, Stefancsik R, Alghamdi SM, Anagnostopoulos AV, Balhoff JP, Balk MA, Bradford YM, Bridges Y, Callahan TJ, Caufield H, Cuzick A, Carmody LC, Caron AR, de Souza V, Engel SR, Fey P, Fisher M, Gehrke S, Grove C, Hansen P, Harris NL, Harris MA, Harris L, Ibrahim A, Jacobsen JO, Köhler S, McMurry JA, Munoz-Fuentes V, Munoz-Torres MC, Parkinson H, Pendlington ZM, Pilgrim C, Robb SMC, Robinson PN, Seager J, Segerdell E, Smedley D, Sollis E, Toro S, Vasilevsky N, Wood V, Haendel MA, Mungall CJ, McLaughlin JA, Osumi-Sutherland D. The Unified Phenotype Ontology (uPheno): A framework for cross-species integrative phenomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.18.613276. [PMID: 39345458 PMCID: PMC11429889 DOI: 10.1101/2024.09.18.613276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses. A major impediment in phenomics is the wide range of distinct and disconnected approaches to recording the observable characteristics of an organism. Phenotype data are collected and curated using free text, single terms or combinations of terms, using multiple vocabularies, terminologies, or ontologies. Integrating these heterogeneous and often siloed data enables the application of biological knowledge both within and across species. Existing integration efforts are typically limited to mappings between pairs of terminologies; a generic knowledge representation that captures the full range of cross-species phenomics data is much needed. We have developed the Unified Phenotype Ontology (uPheno) framework, a community effort to provide an integration layer over domain-specific phenotype ontologies, as a single, unified, logical representation. uPheno comprises (1) a system for consistent computational definition of phenotype terms using ontology design patterns, maintained as a community library; (2) a hierarchical vocabulary of species-neutral phenotype terms under which their species-specific counterparts are grouped; and (3) mapping tables between species-specific ontologies. This harmonized representation supports use cases such as cross-species integration of genotype-phenotype associations from different organisms and cross-species informed variant prioritization.
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Affiliation(s)
| | | | | | | | | | - James P. Balhoff
- Renaissance Computing Institute, University of North Carolina, Chapel Hill, NC USA
| | - Meghan A. Balk
- Natural History Museum, University of Oslo, Oslo, Norway
| | | | | | - Tiffany J. Callahan
- Department of Biomedical Informatics, Columbia University Irving Medical Center
| | - Harry Caufield
- Lawrence Berkeley National. Laboratory, Berkeley, CA, USA
| | | | | | | | | | | | | | - Malcolm Fisher
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, US
| | | | | | | | - Nomi L. Harris
- Lawrence Berkeley National. Laboratory, Berkeley, CA, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Erik Segerdell
- Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, US
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62
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Perry AS, Amancherla K, Huang X, Lance ML, Farber-Eger E, Gajjar P, Amrute J, Stolze L, Zhao S, Sheng Q, Joynes CM, Peng Z, Tanaka T, Drakos SG, Lavine KJ, Selzman C, Visker JR, Shankar TS, Ferrucci L, Das S, Wilcox J, Patel RB, Kalhan R, Shah SJ, Walker KA, Wells Q, Tucker N, Nayor M, Shah RV, Khan SS. Clinical-transcriptional prioritization of the circulating proteome in human heart failure. Cell Rep Med 2024; 5:101704. [PMID: 39226894 PMCID: PMC11524958 DOI: 10.1016/j.xcrm.2024.101704] [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: 12/15/2023] [Revised: 06/15/2024] [Accepted: 08/07/2024] [Indexed: 09/05/2024]
Abstract
Given expanding studies in epidemiology and disease-oriented human studies offering hundreds of associations between the human "ome" and disease, prioritizing molecules relevant to disease mechanisms among this growing breadth is important. Here, we link the circulating proteome to human heart failure (HF) propensity (via echocardiographic phenotyping and clinical outcomes) across the lifespan, demonstrating key pathways of fibrosis, inflammation, metabolism, and hypertrophy. We observe a broad array of genes encoding proteins linked to HF phenotypes and outcomes in clinical populations dynamically expressed at a transcriptional level in human myocardium during HF and cardiac recovery (several in a cell-specific fashion). Many identified targets do not have wide precedent in large-scale genomic discovery or human studies, highlighting the complementary roles for proteomic and tissue transcriptomic discovery to focus epidemiological targets to those relevant in human myocardium for further interrogation.
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Affiliation(s)
- Andrew S Perry
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Kaushik Amancherla
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Xiaoning Huang
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - Eric Farber-Eger
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Priya Gajjar
- Sections of Cardiovascular Medicine and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Junedh Amrute
- Cardiology Division, Washington University School of Medicine, St. Louis, MO, USA
| | - Lindsey Stolze
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shilin Zhao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Quanhu Sheng
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Cassandra M Joynes
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Zhongsheng Peng
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Stavros G Drakos
- Division of Cardiovascular Medicine, University of Utah and Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), Salt Lake City, UT, USA
| | - Kory J Lavine
- Cardiology Division, Washington University School of Medicine, St. Louis, MO, USA
| | - Craig Selzman
- Department of Cardiac Surgery, University of Utah School of Medicine, Division of Cardiothoracic Surgery, University of Utah and Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), Salt Lake City, UT, USA
| | - Joseph R Visker
- Division of Cardiovascular Medicine, University of Utah and Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), Salt Lake City, UT, USA
| | - Thirupura S Shankar
- Division of Cardiovascular Medicine, University of Utah and Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), Salt Lake City, UT, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Saumya Das
- Cardiovascular Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jane Wilcox
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Ravi B Patel
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Ravi Kalhan
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Sanjiv J Shah
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Quinn Wells
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | | | - Matthew Nayor
- Sections of Cardiovascular Medicine and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Ravi V Shah
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.
| | - Sadiya S Khan
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
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63
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Zhu D, Zhang J, Ma X, Hu M, Gao F, Hashem JB, Lyu J, Wei J, Cui Y, Qiu S, Chen C. Overabundant endocannabinoids in neurons are detrimental to cognitive function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.17.613513. [PMID: 39345517 PMCID: PMC11430108 DOI: 10.1101/2024.09.17.613513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
2-Arachidonoylglycerol (2-AG) is the most prevalent endocannabinoid involved in maintaining brain homeostasis. Previous studies have demonstrated that inactivating monoacylglycerol lipase (MAGL), the primary enzyme responsible for degrading 2-AG in the brain, alleviates neuropathology and prevents synaptic and cognitive decline in animal models of neurodegenerative diseases. However, we show that selectively inhibiting 2-AG metabolism in neurons impairs cognitive function in mice. This cognitive impairment appears to result from decreased expression of synaptic proteins and synapse numbers, impaired long-term synaptic plasticity and cortical circuit functional connectivity, and diminished neurogenesis. Interestingly, the synaptic and cognitive deficits induced by neuronal MAGL inactivation can be counterbalanced by inhibiting astrocytic 2-AG metabolism. Transcriptomic analyses reveal that inhibiting neuronal 2-AG degradation leads to widespread changes in expression of genes associated with synaptic function. These findings suggest that crosstalk in 2-AG signaling between astrocytes and neurons is crucial for maintaining synaptic and cognitive functions and that excessive 2-AG in neurons alone is detrimental to cognitive function.
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Affiliation(s)
- Dexiao Zhu
- Department of Cellular and Integrative Physiology, Joe R. & Teresa Lozano Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, 78229
| | - Jian Zhang
- Department of Cellular and Integrative Physiology, Joe R. & Teresa Lozano Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, 78229
| | - Xiaokuang Ma
- Departments of Basic Medical Sciences, University of Arizona College of Medicine, Phoenix, AZ 85004, USA
| | - Mei Hu
- Department of Cellular and Integrative Physiology, Joe R. & Teresa Lozano Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, 78229
| | - Fei Gao
- Department of Cellular and Integrative Physiology, Joe R. & Teresa Lozano Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, 78229
| | - Jack B. Hashem
- Department of Cellular and Integrative Physiology, Joe R. & Teresa Lozano Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, 78229
| | - Jianlu Lyu
- Department of Cellular and Integrative Physiology, Joe R. & Teresa Lozano Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, 78229
| | - Jing Wei
- Departments of Basic Medical Sciences, University of Arizona College of Medicine, Phoenix, AZ 85004, USA
| | - Yuehua Cui
- Departments of Basic Medical Sciences, University of Arizona College of Medicine, Phoenix, AZ 85004, USA
| | - Shenfeng Qiu
- Departments of Basic Medical Sciences, University of Arizona College of Medicine, Phoenix, AZ 85004, USA
| | - Chu Chen
- Department of Cellular and Integrative Physiology, Joe R. & Teresa Lozano Long School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas, 78229
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64
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Mackay HL, Stone HR, Ronson GE, Ellis K, Lanz A, Aghabi Y, Walker AK, Starowicz K, Garvin AJ, Van Eijk P, Koestler SA, Anthony EJ, Piberger AL, Chauhan AS, Conway-Thomas P, Vaitsiankova A, Vijayendran S, Beesley JF, Petermann E, Brown EJ, Densham RM, Reed SH, Dobbs F, Saponaro M, Morris JR. USP50 suppresses alternative RecQ helicase use and deleterious DNA2 activity during replication. Nat Commun 2024; 15:8102. [PMID: 39284827 PMCID: PMC11405836 DOI: 10.1038/s41467-024-52250-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 08/30/2024] [Indexed: 09/22/2024] Open
Abstract
Mammalian DNA replication relies on various DNA helicase and nuclease activities to ensure accurate genetic duplication, but how different helicase and nuclease activities are properly directed remains unclear. Here, we identify the ubiquitin-specific protease, USP50, as a chromatin-associated protein required to promote ongoing replication, fork restart, telomere maintenance, cellular survival following hydroxyurea or pyridostatin treatment, and suppression of DNA breaks near GC-rich sequences. We find that USP50 supports proper WRN-FEN1 localisation at or near stalled replication forks. Nascent DNA in cells lacking USP50 shows increased association of the DNA2 nuclease and RECQL4 and RECQL5 helicases and replication defects in cells lacking USP50, or FEN1 are driven by these proteins. Consequently, suppression of DNA2 or RECQL4/5 improves USP50-depleted cell resistance to agents inducing replicative stress and restores telomere stability. These data define an unexpected regulatory protein that promotes the balance of helicase and nuclease use at ongoing and stalled replication forks.
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Affiliation(s)
- Hannah L Mackay
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Helen R Stone
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
- CCTT-C Cancer Research UK, Clinical trials unit, Sir Robert Aitken building, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK
| | - George E Ronson
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Katherine Ellis
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
- School of Chemical, Materials and Biological Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK
| | - Alexander Lanz
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Yara Aghabi
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Alexandra K Walker
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Katarzyna Starowicz
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
- Adthera Bio, Lyndon House, 62 Hagley Road, Birmingham, B16 8PE, UK
| | - Alexander J Garvin
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
- SUMO Biology Lab, School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK
| | - Patrick Van Eijk
- Broken String Biosciences Ltd., BioData Innovation Centre, Unit AB3-03, Level 3, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1DR, UK
- Division of Cancer & Genetics School of Medicine, Cardiff University, Heath Park, Cardiff, CF14 4XN, UK
| | - Stefan A Koestler
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Elizabeth J Anthony
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Ann Liza Piberger
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Anoop S Chauhan
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Poppy Conway-Thomas
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Alina Vaitsiankova
- Genome Damage and Stability Centre, School of Life Sciences, University of Sussex, Falmer, Brighton, BN1 9RQ, UK
- Department of Genetics and Development, Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, New York, NY, USA
| | - Sobana Vijayendran
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
- University Hospital Birmingham N.H.S. Foundation Trust, Queen Elizabeth Hospital Birmingham, Mindelsohn Way, Birmingham, B15 2TH, UK
| | - James F Beesley
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Eva Petermann
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Eric J Brown
- Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 421 Curie Boulevard PA, 19104-6160, USA
| | - Ruth M Densham
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Simon H Reed
- Broken String Biosciences Ltd., BioData Innovation Centre, Unit AB3-03, Level 3, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1DR, UK
- Division of Cancer & Genetics School of Medicine, Cardiff University, Heath Park, Cardiff, CF14 4XN, UK
| | - Felix Dobbs
- Broken String Biosciences Ltd., BioData Innovation Centre, Unit AB3-03, Level 3, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1DR, UK
- Division of Cancer & Genetics School of Medicine, Cardiff University, Heath Park, Cardiff, CF14 4XN, UK
| | - Marco Saponaro
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Joanna R Morris
- Birmingham Centre for Genome Biology and Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK.
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Abood A, Mesner LD, Jeffery ED, Murali M, Lehe MD, Saquing J, Farber CR, Sheynkman GM. Long-read proteogenomics to connect disease-associated sQTLs to the protein isoform effectors of disease. Am J Hum Genet 2024; 111:1914-1931. [PMID: 39079539 PMCID: PMC11393689 DOI: 10.1016/j.ajhg.2024.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 07/01/2024] [Accepted: 07/02/2024] [Indexed: 08/07/2024] Open
Abstract
A major fraction of loci identified by genome-wide association studies (GWASs) mediate alternative splicing, but mechanistic interpretation is hindered by the technical limitations of short-read RNA sequencing (RNA-seq), which cannot directly link splicing events to full-length protein isoforms. Long-read RNA-seq represents a powerful tool to characterize transcript isoforms, and recently, infer protein isoform existence. Here, we present an approach that integrates information from GWASs, splicing quantitative trait loci (sQTLs), and PacBio long-read RNA-seq in a disease-relevant model to infer the effects of sQTLs on the ultimate protein isoform products they encode. We demonstrate the utility of our approach using bone mineral density (BMD) GWAS data. We identified 1,863 sQTLs from the Genotype-Tissue Expression (GTEx) project in 732 protein-coding genes that colocalized with BMD associations (H4PP ≥ 0.75). We generated PacBio Iso-Seq data (N = ∼22 million full-length reads) on human osteoblasts, identifying 68,326 protein-coding isoforms, of which 17,375 (25%) were unannotated. By casting the sQTLs onto protein isoforms, we connected 809 sQTLs to 2,029 protein isoforms from 441 genes expressed in osteoblasts. Overall, we found that 74 sQTLs influenced isoforms likely impacted by nonsense-mediated decay and 190 that potentially resulted in the expression of unannotated protein isoforms. Finally, we functionally validated colocalizing sQTLs in TPM2, in which siRNA-mediated knockdown in osteoblasts showed two TPM2 isoforms with opposing effects on mineralization but exhibited no effect upon knockdown of the entire gene. Our approach should be to generalize across diverse clinical traits and to provide insights into protein isoform activities modulated by GWAS loci.
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Affiliation(s)
- Abdullah Abood
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA
| | - Larry D Mesner
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
| | - Erin D Jeffery
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Mayank Murali
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Micah D Lehe
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Jamie Saquing
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA.
| | - Gloria M Sheynkman
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908, USA; Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA, USA; UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA, USA.
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66
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Noordam R, Wang W, Nagarajan P, Wang H, Brown MR, Bentley AR, Hui Q, Kraja AT, Morrison JL, O'Connel JR, Lee S, Schwander K, Bartz TM, de las Fuentes L, Feitosa MF, Guo X, Hanfei X, Harris SE, Huang Z, Kals M, Lefevre C, Mangino M, Milaneschi Y, van der Most P, Pacheco NL, Palmer ND, Rao V, Rauramaa R, Sun Q, Tabara Y, Vojinovic D, Wang Y, Weiss S, Yang Q, Zhao W, Zhu W, Abu Yusuf Ansari M, Aschard H, Anugu P, Assimes TL, Attia J, Baker LD, Ballantyne C, Bazzano L, Boerwinkle E, Cade B, Chen HH, Chen W, Ida Chen YD, Chen Z, Cho K, De Anda-Duran I, Dimitrov L, Do A, Edwards T, Faquih T, Hingorani A, Fisher-Hoch SP, Gaziano JM, Gharib SA, Giri A, Ghanbari M, Grabe HJ, Graff M, Gu CC, He J, Heikkinen S, Hixson J, Ho YL, Hood MM, Houghton SC, Karvonen-Gutierrez CA, Kawaguchi T, Kilpeläinen TO, Komulainen P, Lin HJ, Linchangco GV, Luik AI, Ma J, Meigs JB, McCormick JB, Menni C, Nolte IM, Norris JM, Petty LE, Polikowsky HG, Raffield LM, Rich SS, Riha RL, Russ TC, Ruiz-Narvaez EA, Sitlani CM, Smith JA, Snieder H, Sofer T, Shen B, Tang J, Taylor KD, Teder-Laving M, Triatin R, Tsai MY, Völzke H, Westerman KE, Xia R, Yao J, Young KL, Zhang R, Zonderman AB, Zhu X, Below JE, Cox SR, Evans M, Fornage M, Fox ER, Franceschini N, Harlow SD, Holliday E, Ikram MA, Kelly T, Lakka TA, Lawlor DA, Li C, Liu CT, Mägi R, Manning AK, Matsuda F, Morrison AC, Nauck M, North KE, Penninx BW, Province MA, Psaty BM, Rotter JI, Spector TD, Wagenknecht LE, Willems van Dijk K, Study LC, Jaquish CE, Wilson PW, Peyser PA, Munroe PB, de Vries PS, Gauderman WJ, Sun YV, Chen H, Miller CL, Winkler TW, Rao DC, Redline S, van Heemst D. A Large-Scale Genome-Wide Gene-Sleep Interaction Study in 732,564 Participants Identifies Lipid Loci Explaining Sleep-Associated Lipid Disturbances. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.09.02.24312466. [PMID: 39281768 PMCID: PMC11398441 DOI: 10.1101/2024.09.02.24312466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/18/2024]
Abstract
We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify novel genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. We collected data from 55 cohorts with a combined sample size of 732,564 participants (87% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for the one-degree of freedom tests of interaction and two-degree of freedom joint tests of the main and interaction effect. In the cross-population meta-analyses, the one-degree of freedom variant-sleep interaction test identified 10 loci (P int <5.0e-9) not previously observed for lipids. Of interest, the ASPH locus (TG, LTST) is a target for aspartic and succinic acid metabolism previously shown to improve sleep and cardiovascular risk. The two-degree of freedom analyses identified an additional 7 loci that showed evidence for variant-sleep interaction (P joint <5.0e-9 in combination with P int <6.6e-6). Of these, the SLC8A1 locus (TG, STST) has been considered a potential treatment target for reduction of ischemic damage after acute myocardial infarction. Collectively, the 17 (9 with STST; 8 with LTST) loci identified in this large-scale initiative provides evidence into the biomolecular mechanisms underpinning sleep-duration-associated changes in lipid levels. The identified druggable targets may contribute to the development of novel therapies for dyslipidemia in people with sleep disturbances.
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Bernard DJ, Pangilinan F, Mendina C, Desporte T, Wincovitch SM, Walsh DJ, Porter RK, Molloy AM, Shane B, Brody LC. SLC25A48 influences plasma levels of choline and localizes to the inner mitochondrial membrane. Mol Genet Metab 2024; 143:108518. [PMID: 39047301 DOI: 10.1016/j.ymgme.2024.108518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 06/14/2024] [Accepted: 06/17/2024] [Indexed: 07/27/2024]
Abstract
Choline contributes to the biogenesis of methyl groups, neurotransmitters, and cell membranes. Our genome-wide association study (GWAS) of circulating choline in 2228 college students found that alleles in SLC25A48 (rs6596270) influence choline concentrations in men (p = 9.6 × 10-8), but not women. Previously, the subcellular location and function of SLC25A48 were unknown. Using super-resolution immunofluorescence microscopy, we localized SLC25A48 to the inner mitochondrial membrane. Our results suggest that SLC25A48 transports choline across the inner mitochondrial membrane.
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Affiliation(s)
- David J Bernard
- Gene and Environment Interaction Section, SBRB, NHGRI, NIH, Bethsda, Maryland, USA
| | - Faith Pangilinan
- Gene and Environment Interaction Section, SBRB, NHGRI, NIH, Bethsda, Maryland, USA
| | - Caitlin Mendina
- Gene and Environment Interaction Section, SBRB, NHGRI, NIH, Bethsda, Maryland, USA
| | - Tara Desporte
- Gene and Environment Interaction Section, SBRB, NHGRI, NIH, Bethsda, Maryland, USA
| | | | - Darren J Walsh
- Gene and Environment Interaction Section, SBRB, NHGRI, NIH, Bethsda, Maryland, USA
| | - Richard K Porter
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Ireland
| | - Anne M Molloy
- Department of Clinical Medicine, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Barry Shane
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, CA, USA
| | - Lawrence C Brody
- Gene and Environment Interaction Section, SBRB, NHGRI, NIH, Bethsda, Maryland, USA.
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68
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Wen J, Liu J, Feng Q, Lu Y, Yuan K, Zhang X, Zhang C, Gao Y, Wang X, Mamatyusupu D, Xu S. Ancestral origins and post-admixture adaptive evolution of highland Tajiks. Natl Sci Rev 2024; 11:nwae284. [PMID: 40040643 PMCID: PMC11879426 DOI: 10.1093/nsr/nwae284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 08/04/2024] [Accepted: 08/04/2024] [Indexed: 03/06/2025] Open
Abstract
It remains debatable how many genes and how various the mechanisms are behind human adaptation to extreme environments, such as high altitudes. Despite extensive studies on Tibetans, Andeans and Ethiopians, new insights are expected to be provided with careful analysis of underrepresented highlanders living in a different geographical region, such as the Tajiks, who reside on the Pamir Plateau at an average altitude exceeding 4000 meters. Moreover, genetic admixture, as we observed in the current whole-genome deep-sequencing study of Xinjiang Tajiks (XJT), offers a unique opportunity to explore how admixture may facilitate adaptation to high-altitude environments. Compared with other extensively studied highlanders, XJT showed pronounced admixture patterns: most of their ancestry are derived from West Eurasians (34.5%-48.3%) and South Asians (21.4%-40.0%), and some minor ancestry from East Asians and Siberians (3.62%-17.5%). The greater genetic diversity in XJT than in their ancestral source populations provides a genetic basis for their adaptation to high-altitude environments. The admixture gain of functional adaptive components from ancestral populations could facilitate adaptation to high-altitude environments. Specifically, admixture-facilitated adaptation was strongly associated with skin-related candidate genes that respond to UV radiation (e.g. HERC2 and BNC2) and cardiovascular-system-related genes (e.g. MPI and BEST1). Notably, no adaptive variants of genes showing outstanding natural selection signatures in the Tibetan or Andean highlanders were identified in XJT, including EPAS1 and EGLN1, indicating that a different set of genes contributed to XJT's survival on the Pamir Plateau, although some genes underlying natural selection in XJT have been previously reported in other highlanders. Our results highlight the unique genetic adaptations in XJT and propose that admixture may play a vital role in facilitating high-altitude adaptation. By introducing and elevating diversity, admixture likely induces novel genetic factors that contribute to the survival of populations in extreme environments like the highlands.
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Affiliation(s)
- Jia Wen
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jiaojiao Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Qidi Feng
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Lu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 200438, China
| | - Kai Yuan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaoxi Zhang
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Chao Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xiaoji Wang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University, Urumqi 830046, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
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69
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Miao B, Ge L, He C, Wang X, Wu J, Li X, Chen K, Wan J, Xing S, Ren L, Shi Z, Liu S, Hu Y, Chen J, Yu Y, Feng L, Flores NM, Liang Z, Xu X, Wang R, Zhou J, Fan J, Xiang B, Li E, Mao Y, Cheng J, Zhao K, Mazur PK, Cai J, Lan F. SMYD5 is a ribosomal methyltransferase that catalyzes RPL40 lysine methylation to enhance translation output and promote hepatocellular carcinoma. Cell Res 2024; 34:648-660. [PMID: 39103523 PMCID: PMC11369092 DOI: 10.1038/s41422-024-01013-3] [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: 06/19/2024] [Accepted: 07/23/2024] [Indexed: 08/07/2024] Open
Abstract
While lysine methylation is well-known for regulating gene expression transcriptionally, its implications in translation have been largely uncharted. Trimethylation at lysine 22 (K22me3) on RPL40, a core ribosomal protein located in the GTPase activation center, was first reported 27 years ago. Yet, its methyltransferase and role in translation remain unexplored. Here, we report that SMYD5 has robust in vitro activity toward RPL40 K22 and primarily catalyzes RPL40 K22me3 in cells. The loss of SMYD5 and RPL40 K22me3 leads to reduced translation output and disturbed elongation as evidenced by increased ribosome collisions. SMYD5 and RPL40 K22me3 are upregulated in hepatocellular carcinoma (HCC) and negatively correlated with patient prognosis. Depleting SMYD5 renders HCC cells hypersensitive to mTOR inhibition in both 2D and 3D cultures. Additionally, the loss of SMYD5 markedly inhibits HCC development and growth in both genetically engineered mouse and patient-derived xenograft (PDX) models, with the inhibitory effect in the PDX model further enhanced by concurrent mTOR suppression. Our findings reveal a novel role of the SMYD5 and RPL40 K22me3 axis in translation elongation and highlight the therapeutic potential of targeting SMYD5 in HCC, particularly with concurrent mTOR inhibition. This work also conceptually broadens the understanding of lysine methylation, extending its significance from transcriptional regulation to translational control.
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Affiliation(s)
- Bisi Miao
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ling Ge
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Chenxi He
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xinghao Wang
- China Novartis Institutes for BioMedical Research, Shanghai, China
| | - Jibo Wu
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Xiang Li
- Minhang Hospital & Institutes of Biomedical Sciences, Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Fudan University, Shanghai, China
| | - Kun Chen
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jinkai Wan
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shenghui Xing
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Lingnan Ren
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhennan Shi
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Shengnan Liu
- China Novartis Institutes for BioMedical Research, Shanghai, China
| | - Yajun Hu
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jiajia Chen
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yanyan Yu
- China Novartis Institutes for BioMedical Research, Shanghai, China
| | - Lijian Feng
- China Novartis Institutes for BioMedical Research, Shanghai, China
| | - Natasha M Flores
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Zhihui Liang
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xinyi Xu
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ruoxin Wang
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jian Zhou
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jia Fan
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Bin Xiang
- China Novartis Institutes for BioMedical Research, Shanghai, China
| | - En Li
- China Novartis Institutes for BioMedical Research, Shanghai, China
| | - Yuanhui Mao
- Department of Neurology of The Second Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jingdong Cheng
- Minhang Hospital & Institutes of Biomedical Sciences, Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Fudan University, Shanghai, China
| | - Kehao Zhao
- China Novartis Institutes for BioMedical Research, Shanghai, China
| | - Pawel K Mazur
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Jiabin Cai
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
| | - Fei Lan
- Shanghai Key Laboratory of Medical Epigenetics, International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Key Laboratory of Carcinogenesis and Cancer Invasion, Ministry of Education, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
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70
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Mackay TFC, Anholt RRH. Pleiotropy, epistasis and the genetic architecture of quantitative traits. Nat Rev Genet 2024; 25:639-657. [PMID: 38565962 PMCID: PMC11330371 DOI: 10.1038/s41576-024-00711-3] [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] [Accepted: 02/14/2024] [Indexed: 04/04/2024]
Abstract
Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.
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Affiliation(s)
- Trudy F C Mackay
- Center for Human Genetics, Clemson University, Greenwood, SC, USA.
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC, USA.
| | - Robert R H Anholt
- Center for Human Genetics, Clemson University, Greenwood, SC, USA.
- Department of Genetics and Biochemistry, Clemson University, Clemson, SC, USA.
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71
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Lace B, Faqeih E, Kaya N, Krumina Z, Mayr JA, Micule I, Wright NT, Achleitner MT, AlQudairy H, Pajusalu S, Stavusis J, Zayakin P, Inashkina I. The phenotypic spectrum of PTCD3 deficiency. JIMD Rep 2024; 65:297-304. [PMID: 39544688 PMCID: PMC11558465 DOI: 10.1002/jmd2.12424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 04/15/2024] [Accepted: 04/18/2024] [Indexed: 11/17/2024] Open
Abstract
The PTCD3 gene product (protein PTCD3 or MRPS39) forms the entry channel of the mitochondrial small ribosomal subunit and binds to single-stranded mRNA. Here, we expand on the clinical manifestations of PTCD3 pathogenic variants by describing an early-onset patient with Leigh-like syndrome and two patients with milder form of disease, with combined oxidative phosphorylation deficiency. A 34-year-old male and his 33-year-old sister both have horizontal nystagmus, pronounced rough tremor, truncal ataxia, dysmetria, spasticity and hyperreflexia. The basal respiration rate decreased significantly for the male patient and his mother (p < 0.0001) compared to the controls. The whole genome sequencing analysis revealed two heterozygous variants in the PTCD3: c.1182T>A, p.(Tyr394Ter) and c.805C>T, p.(His269Tyr). Tyr394Ter variant ablates the C-terminal half of the protein, including a significant portion of the central fold. In silico modelling for the variant His269Tyr shows that the inclusion of the slightly larger tyrosine sidechain is well tolerated, with no significant change in either the position or the movement of the surrounding area. The third case is a 9-year-old boy, who has a global developmental delay, central hypotonia, hyperreflexia and abnormal MRI. PTCD3 pathogenic variant c.538+4A>G was identified by whole exome sequencing. To test the variant's effect on splicing, an RT-PCR experiment was performed, which revealed skipping of an out-of-frame exon 7.
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Affiliation(s)
- Baiba Lace
- Riga East Clinical University HospitalRigaLatvia
- Institute of Clinical and Preventive Medicine, University of LatviaRigaLatvia
| | - Eissa Faqeih
- Section of Medical GeneticsChildren's Specialist Hospital, King Fahad Medical CityRiyadhSaudi Arabia
| | - Namik Kaya
- Translational Genomics DepartmentMBC: 26, Centre for Genomic MedicineRiyadhSaudi Arabia
| | - Zita Krumina
- Department of Biology and MicrobiologyRiga Stradiņš UniversityRigaLatvia
| | - Johannes A. Mayr
- University Children’s Hospital, Laboratory Salzburger Landeskliniken Universitaetsklinikum of the Paracelsus Medical University SalzburgSalzburgAustria
| | - Ieva Micule
- Department of Medical Genetics and Prenatal DiagnosticsChildren's University HospitalRigaLatvia
| | | | - Melanie T. Achleitner
- University Children’s Hospital, Laboratory Salzburger Landeskliniken Universitaetsklinikum of the Paracelsus Medical University SalzburgSalzburgAustria
| | - Hanan AlQudairy
- Translational Genomics DepartmentMBC: 26, Centre for Genomic MedicineRiyadhSaudi Arabia
| | - Sander Pajusalu
- Department of Clinical Genetics, Genetics and Personalized Medicine ClinicTartu University HospitalTartuEstonia
- Department of Genetics and Personalized MedicineInstitute of Clinical Medicine, Faculty of Medicine, University of TartuTartuEstonia
| | | | - Pawel Zayakin
- Latvian Biomedical Research and Study CentreRigaLatvia
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Kamineni M, Raghu V, Truong B, Alaa A, Schuermans A, Friedman S, Reeder C, Bhattacharya R, Libby P, Ellinor PT, Maddah M, Philippakis A, Hornsby W, Yu Z, Natarajan P. Deep learning-derived splenic radiomics, genomics, and coronary artery disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.16.24312129. [PMID: 39185532 PMCID: PMC11343250 DOI: 10.1101/2024.08.16.24312129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/27/2024]
Abstract
Background Despite advances in managing traditional risk factors, coronary artery disease (CAD) remains the leading cause of mortality. Circulating hematopoietic cells influence risk for CAD, but the role of a key regulating organ, spleen, is unknown. The understudied spleen is a 3-dimensional structure of the hematopoietic system optimally suited for unbiased radiologic investigations toward novel mechanistic insights. Methods Deep learning-based image segmentation and radiomics techniques were utilized to extract splenic radiomic features from abdominal MRIs of 42,059 UK Biobank participants. Regression analysis was used to identify splenic radiomics features associated with CAD. Genome-wide association analyses were applied to identify loci associated with these radiomics features. Overlap between loci associated with CAD and the splenic radiomics features was explored to understand the underlying genetic mechanisms of the role of the spleen in CAD. Results We extracted 107 splenic radiomics features from abdominal MRIs, and of these, 10 features were associated with CAD. Genome-wide association analysis of CAD-associated features identified 219 loci, including 35 previously reported CAD loci, 7 of which were not associated with conventional CAD risk factors. Notably, variants at 9p21 were associated with splenic features such as run length non-uniformity. Conclusions Our study, combining deep learning with genomics, presents a new framework to uncover the splenic axis of CAD. Notably, our study provides evidence for the underlying genetic connection between the spleen as a candidate causal tissue-type and CAD with insight into the mechanisms of 9p21, whose mechanism is still elusive despite its initial discovery in 2007. More broadly, our study provides a unique application of deep learning radiomics to non-invasively find associations between imaging, genetics, and clinical outcomes.
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Affiliation(s)
| | - Vineet Raghu
- Cardiovascular Imaging Research Center, Department of Radiology, MGH and HMS
- Artificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, Massachusetts
| | - Buu Truong
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Ahmed Alaa
- Computational Precision Health Program, University of California, Berkeley, Berkeley, CA 94720
- Computational Precision Health Program, University of California, San Francisco, San Francisco, CA 94143
| | - Art Schuermans
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
- Faculty of Medicine, KU Leuven, Leuven, Belgium
| | - Sam Friedman
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Christopher Reeder
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Romit Bhattacharya
- Division of Cardiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston MA 02114
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Peter Libby
- Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115
| | - Patrick T. Ellinor
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
- Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Demoulas Center for Cardiac Arrhythmias, Massachusetts General Hospital, Boston, MA, USA
| | - Mahnaz Maddah
- Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA
| | | | - Whitney Hornsby
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Zhi Yu
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
| | - Pradeep Natarajan
- Harvard Medical School, Boston, MA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
- Center for Genomic Medicine and Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA
- Personalized Medicine, Mass General Brigham, Boston, MA
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Alvarado K, Tang WJ, Watson CJ, Ahmed AR, Gomez AE, Donaka R, Amemiya C, Karasik D, Hsu YH, Kwon RY. Loss of cped1 does not affect bone and lean tissue in zebrafish. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.10.601974. [PMID: 39026892 PMCID: PMC11257572 DOI: 10.1101/2024.07.10.601974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Human genetic studies have nominated Cadherin-like and PC-esterase Domain-containing 1 (CPED1) as a candidate target gene mediating bone mineral density (BMD) and fracture risk heritability. Recent efforts to define the role of CPED1 in bone in mouse and human models have revealed complex alternative splicing and inconsistent results arising from gene targeting, making its function in bone difficult to interpret. To better understand the role of CPED1 in adult bone mass and morphology, we conducted a comprehensive genetic and phenotypic analysis of cped1 in zebrafish, an emerging model for bone and mineral research. We analyzed two different cped1 mutant lines and performed deep phenotyping to characterize more than 200 measures of adult vertebral, craniofacial, and lean tissue morphology. We also examined alternative splicing of zebrafish cped1 and gene expression in various cell/tissue types. Our studies fail to support an essential role of cped1 in adult zebrafish bone. Specifically, homozygous mutants for both cped1 mutant alleles, which are expected to result in loss-of-function and impact all cped1 isoforms, exhibited no significant differences in the measures examined when compared to their respective wildtype controls, suggesting that cped1 does not significantly contribute to these traits. We identified sequence differences in critical residues of the catalytic triad between the zebrafish and mouse orthologs of CPED1, suggesting that differences in key residues, as well as distinct alternative splicing, could underlie different functions of CPED1 orthologs in the two species. Our studies fail to support a requirement of cped1 in zebrafish bone and lean tissue, adding to evidence that variants at 7q31.31 can act independently of CPED1 to influence BMD and fracture risk.
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Affiliation(s)
- Kurtis Alvarado
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - W. Joyce Tang
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Claire J. Watson
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Ali R. Ahmed
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Arianna Ericka Gomez
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | | | - Chris Amemiya
- Department of Molecular and Cell Biology and Quantitative and Systems Biology Program, University of California, Merced, CA, USA
| | - David Karasik
- The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
- Hebrew SeniorLife, Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, USA
| | - Yi-Hsiang Hsu
- Hebrew SeniorLife, Hinda and Arthur Marcus Institute for Aging Research, Boston, MA, USA
| | - Ronald Young Kwon
- Department of Orthopaedic Surgery and Sports Medicine, University of Washington School of Medicine, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
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Lara MK, Chitre AS, Chen D, Johnson BB, Nguyen K, Cohen KA, Muckadam SA, Lin B, Ziegler S, Beeson A, Sanches TM, Solberg Woods LC, Polesskaya O, Palmer AA, Mitchell SH. Genome-wide association study of delay discounting in Heterogeneous Stock rats. GENES, BRAIN, AND BEHAVIOR 2024; 23:e12909. [PMID: 39119916 PMCID: PMC11310854 DOI: 10.1111/gbb.12909] [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: 12/18/2023] [Revised: 06/27/2024] [Accepted: 07/18/2024] [Indexed: 08/10/2024]
Abstract
Delay discounting refers to the behavioral tendency to devalue rewards as a function of their delay in receipt. Heightened delay discounting has been associated with substance use disorders and multiple co-occurring psychopathologies. Human and animal genetic studies have established that delay discounting is heritable, but only a few associated genes have been identified. We aimed to identify novel genetic loci associated with delay discounting through a genome-wide association study (GWAS) using Heterogeneous Stock (HS) rats, a genetically diverse outbred population derived from eight inbred founder strains. We assessed delay discounting in 650 male and female HS rats using an adjusting amount procedure in which rats chose between smaller immediate sucrose rewards or a larger reward at various delays. Preference switch points were calculated and both exponential and hyperbolic functions were fitted to these indifference points. Area under the curve (AUC) and the discounting parameter k of both functions were used as delay discounting measures. GWAS for AUC, exponential k, and one indifference point identified significant loci on chromosomes 20 and 14. The gene Slc35f1, which encodes a member of the solute carrier family, was the sole gene within the chromosome 20 locus. That locus also contained an eQTL for Slc35f1, suggesting that heritable differences in the expression might be responsible for the association with behavior. Adgrl3, which encodes a latrophilin subfamily G-protein coupled receptor, was the sole gene within the chromosome 14 locus. These findings implicate novel genes in delay discounting and highlight the need for further exploration.
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Affiliation(s)
- Montana Kay Lara
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Apurva S. Chitre
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Denghui Chen
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Benjamin B. Johnson
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Khai‐Minh Nguyen
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Katarina A. Cohen
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Sakina A. Muckadam
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Bonnie Lin
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Shae Ziegler
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Angela Beeson
- Department of Internal Medicine, Wake Forest School of MedicineWake Forest UniversityWinston‐SalemNorth CarolinaUSA
| | - Thiago M. Sanches
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Leah C. Solberg Woods
- Department of Internal Medicine, Wake Forest School of MedicineWake Forest UniversityWinston‐SalemNorth CarolinaUSA
| | - Oksana Polesskaya
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Abraham A. Palmer
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
- Institute for Genomic MedicineUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Suzanne H. Mitchell
- Department of Behavioral Neuroscience, Psychiatry, the Oregon Institute of Occupational Health SciencesOregon Health & Science UniversityPortlandOregonUSA
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Deuis JR, Klasfauseweh T, Walker L, Vetter I. The 'dispanins' and related proteins in physiology and neurological disease. Trends Neurosci 2024; 47:622-634. [PMID: 39025729 DOI: 10.1016/j.tins.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 05/15/2024] [Accepted: 06/21/2024] [Indexed: 07/20/2024]
Abstract
The dispanins are a family of 15 transmembrane proteins that have diverse and often unclear physiological functions. Many dispanins, including synapse differentiation induced gene 1 (SynDIG1), proline-rich transmembrane protein 1 (PRRT1)/SynDIG4, and PRRT2, are expressed in the central nervous system (CNS), where they are involved in the development of synapses, regulation of neurotransmitter release, and interactions with ion channels, including AMPA receptors (AMPARs). Others, including transmembrane protein 233 (TMEM233) and trafficking regulator of GLUT4-1 (TRARG1), are expressed in the peripheral nervous system (PNS); however, the function of these dispanins is less clear. Recently, a family of neurotoxins isolated from the giant Australian stinging tree was shown to target TMEM233 to modulate the function of voltage-gated sodium (NaV) channels, suggesting that the dispanins are inherently druggable. Here, we review current knowledge about the structure and function of the dispanins, in particular TMEM233 and its two most closely related homologs PRRT2 and TRARG1, which may be drug targets involved in neurological disease.
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Affiliation(s)
- Jennifer R Deuis
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia
| | - Tabea Klasfauseweh
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia
| | - Lucinda Walker
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia
| | - Irina Vetter
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD, Australia; School of Pharmacy, The University of Queensland, Woolloongabba, QLD, Australia.
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76
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Zeng T, Spence JP, Mostafavi H, Pritchard JK. Bayesian estimation of gene constraint from an evolutionary model with gene features. Nat Genet 2024; 56:1632-1643. [PMID: 38977852 DOI: 10.1038/s41588-024-01820-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 05/29/2024] [Indexed: 07/10/2024]
Abstract
Measures of selective constraint on genes have been used for many applications, including clinical interpretation of rare coding variants, disease gene discovery and studies of genome evolution. However, widely used metrics are severely underpowered at detecting constraints for the shortest ~25% of genes, potentially causing important pathogenic mutations to be overlooked. Here we developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, shet. Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease and other phenotypes, especially for short genes. Our estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve the estimation of many gene-level properties, such as rare variant burden or gene expression differences.
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Affiliation(s)
- Tony Zeng
- Department of Genetics, Stanford University, Stanford, CA, USA.
| | | | - Hakhamanesh Mostafavi
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Population Health, New York University, New York, NY, USA
| | - Jonathan K Pritchard
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Department of Biology, Stanford University, Stanford, CA, USA.
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77
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Zhong X, Moresco JJ, SoRelle JA, Song R, Jiang Y, Nguyen MT, Wang J, Bu CH, Moresco EMY, Beutler B, Choi JH. Disruption of the ZFP574-THAP12 complex suppresses B cell malignancies in mice. Proc Natl Acad Sci U S A 2024; 121:e2409232121. [PMID: 39047044 PMCID: PMC11295075 DOI: 10.1073/pnas.2409232121] [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: 05/08/2024] [Accepted: 06/24/2024] [Indexed: 07/27/2024] Open
Abstract
Despite the availability of life-extending treatments for B cell leukemias and lymphomas, many of these cancers remain incurable. Thus, the development of new molecular targets and therapeutics is needed to expand treatment options. To identify new molecular targets, we used a forward genetic screen in mice to identify genes required for development or survival of lymphocytes. Here, we describe Zfp574, an essential gene encoding a zinc finger protein necessary for normal and malignant lymphocyte survival. We show that ZFP574 interacts with zinc finger protein THAP12 and promotes the G1-to-S-phase transition during cell cycle progression. Mutation of ZFP574 impairs nuclear localization of the ZFP574-THAP12 complex. ZFP574 or THAP12 deficiency results in cell cycle arrest and impaired lymphoproliferation. Germline mutation, acute gene deletion, or targeted degradation of ZFP574 suppressed Myc-driven B cell leukemia in mice, but normal B cells were largely spared, permitting long-term survival, whereas complete lethality was observed in control animals. Our findings support the identification of drugs targeting ZFP574-THAP12 as a unique strategy to treat B cell malignancies.
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Affiliation(s)
- Xue Zhong
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - James J. Moresco
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Jeffrey A. SoRelle
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Ran Song
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Yiao Jiang
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Mylinh T. Nguyen
- Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Jianhui Wang
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Chun Hui Bu
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Eva Marie Y. Moresco
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Bruce Beutler
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
| | - Jin Huk Choi
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX75390
- Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX75390
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78
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Jurgens JA, Barry BJ, Chan WM, MacKinnon S, Whitman MC, Matos Ruiz PM, Pratt BM, England EM, Pais L, Lemire G, Groopman E, Glaze C, Russell KA, Singer-Berk M, Di Gioia SA, Lee AS, Andrews C, Shaaban S, Wirth MM, Bekele S, Toffoloni M, Bradford VR, Foster EE, Berube L, Rivera-Quiles C, Mensching FM, Sanchis-Juan A, Fu JM, Wong I, Zhao X, Wilson MW, Weisburd B, Lek M, Brand H, Talkowski ME, MacArthur DG, O'Donnell-Luria A, Robson CD, Hunter DG, Engle EC. Expanding the genetics and phenotypes of ocular congenital cranial dysinnervation disorders. Genet Med 2024; 27:101216. [PMID: 39033378 PMCID: PMC11739428 DOI: 10.1016/j.gim.2024.101216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 07/10/2024] [Accepted: 07/12/2024] [Indexed: 07/23/2024] Open
Abstract
PURPOSE This study aimed to identify genetic etiologies and genotype/phenotype associations for unsolved ocular congenital cranial dysinnervation disorders (oCCDDs). METHODS We coupled phenotyping with exome or genome sequencing of 467 probands (550 affected and 1108 total individuals) with genetically unsolved oCCDDs, integrating analyses of pedigrees, human and animal model phenotypes, and de novo variants to identify rare candidate single-nucleotide variants, insertion/deletions, and structural variants disrupting protein-coding regions. Prioritized variants were classified for pathogenicity and evaluated for genotype/phenotype correlations. RESULTS Analyses elucidated phenotypic subgroups, identified pathogenic/likely pathogenic variant(s) in 43 of 467 probands (9.2%), and prioritized variants of uncertain significance in 70 of 467 additional probands (15.0%). These included known and novel variants in established oCCDD genes, genes associated with syndromes that sometimes include oCCDDs (eg, MYH10 [HGNC:7568], KIF21B [HGNC:29442], TGFBR2 [HGNC:11773], and TUBB6 [HGNC:20776]), genes that fit the syndromic component of the phenotype but had no prior oCCDD association (eg, CDK13 [HGNC:1733], TGFB2 [HGNC:11768]), genes with no reported association with oCCDDs or the syndromic phenotypes (eg, TUBA4A [HGNC:12407], KIF5C [HGNC:6325], CTNNA1 [HGNC:2509], KLB [HGNC:15527], FGF21 [HGNC:3678]), and genes associated with oCCDD phenocopies that had resulted in misdiagnoses. CONCLUSION This study suggests that unsolved oCCDDs are clinically and genetically heterogeneous disorders often overlapping other Mendelian conditions and nominates many candidates for future replication and functional studies.
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Affiliation(s)
- Julie A Jurgens
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA; Department of Neurology, Boston Children's Hospital, Boston, MA; Department of Neurology, Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA
| | - Brenda J Barry
- Department of Neurology, Boston Children's Hospital, Boston, MA; Howard Hughes Medical Institute, Chevy Chase, MD
| | - Wai-Man Chan
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA; Department of Neurology, Boston Children's Hospital, Boston, MA; Department of Neurology, Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Howard Hughes Medical Institute, Chevy Chase, MD
| | - Sarah MacKinnon
- Department of Ophthalmology, Boston Children's Hospital, Boston, MA; Department of Ophthalmology, Harvard Medical School, Boston, MA
| | - Mary C Whitman
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA; Department of Ophthalmology, Boston Children's Hospital, Boston, MA; Department of Ophthalmology, Harvard Medical School, Boston, MA
| | | | - Brandon M Pratt
- Department of Neurology, Boston Children's Hospital, Boston, MA
| | - Eleina M England
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Lynn Pais
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Gabrielle Lemire
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Emily Groopman
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Carmen Glaze
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Kathryn A Russell
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Moriel Singer-Berk
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Silvio Alessandro Di Gioia
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA; Department of Neurology, Boston Children's Hospital, Boston, MA; Department of Neurology, Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Regeneron Pharmaceuticals, Tarrytown, NY
| | - Arthur S Lee
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA; Department of Neurology, Boston Children's Hospital, Boston, MA; Department of Neurology, Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA
| | | | - Sherin Shaaban
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA; Department of Neurology, Boston Children's Hospital, Boston, MA; Department of Neurology, Harvard Medical School, Boston, MA; Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT
| | - Megan M Wirth
- Department of Neurology, Boston Children's Hospital, Boston, MA
| | - Sarah Bekele
- Department of Neurology, Boston Children's Hospital, Boston, MA
| | | | | | - Emma E Foster
- Department of Neurology, Boston Children's Hospital, Boston, MA
| | - Lindsay Berube
- Department of Neurology, Boston Children's Hospital, Boston, MA
| | | | | | - Alba Sanchis-Juan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Jack M Fu
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Isaac Wong
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Xuefang Zhao
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Michael W Wilson
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Ben Weisburd
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Monkol Lek
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Harrison Brand
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA; Pediatric Surgical Research Laboratories, Massachusetts General Hospital, Boston, MA
| | - Michael E Talkowski
- Department of Neurology, Harvard Medical School, Boston, MA; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Daniel G MacArthur
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
| | - Anne O'Donnell-Luria
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
| | - Caroline D Robson
- Division of Neuroradiology, Department of Radiology, Boston Children's Hospital, Boston, MA; Department of Radiology, Harvard Medical School, Boston, MA
| | - David G Hunter
- Department of Ophthalmology, Boston Children's Hospital, Boston, MA; Department of Ophthalmology, Harvard Medical School, Boston, MA
| | - Elizabeth C Engle
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA; Department of Neurology, Boston Children's Hospital, Boston, MA; Department of Neurology, Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Howard Hughes Medical Institute, Chevy Chase, MD; Department of Ophthalmology, Boston Children's Hospital, Boston, MA; Department of Ophthalmology, Harvard Medical School, Boston, MA; Division of Genetics and Genomics, Boston Children's Hospital, Harvard Medical School, Boston, MA.
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79
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Wang H, Nagarajan P, Winkler T, Bentley A, Miller C, Kraja A, Schwander K, Lee S, Wang W, Brown M, Morrison J, Giri A, O'Connell J, Bartz T, de las Fuentes L, Gudmundsdottir V, Guo X, Harris S, Huang Z, Kals M, Kho M, Lefevre C, Luan J, Lyytikäinen LP, Mangino M, Milaneschi Y, Palmer N, Rao V, Rauramaa R, Shen B, Stadler S, Sun Q, Tang J, Thériault S, van der Graaf A, van der Most P, Wang Y, Weiss S, Westerman K, Yang Q, Yasuharu T, Zhao W, Zhu W, Altschul D, Ansari MAY, Anugu P, Argoty-Pantoja A, Arzt M, Aschard H, Attia J, Bazzano L, Breyer M, Brody J, Cade B, Chen HH, Chen YDI, Chen Z, de Vries P, Dimitrov L, Do A, Du J, Dupont C, Edwards T, Evans M, Faquih T, Felix S, Fisher-Hoch S, Floyd J, Graff M, Charles Gu C, Gu D, Hairston K, Hanley A, Heid I, Heikkinen S, Highland H, Hood M, Kähönen M, Karvonen-Gutierrez C, Kawaguchi T, Kazuya S, Tanika K, Komulainen P, Levy D, Lin H, Liu P, Marques-Vidal P, McCormick J, Mei H, Meigs J, Menni C, Nam K, Nolte I, Pacheco N, Petty L, Polikowsky H, Province M, Psaty B, Raffield L, Raitakari O, Rich S, Riha R, Risch L, Risch M, Ruiz-Narvaez E, Scott R, Sitlani C, Smith J, Sofer T, Teder-Laving M, Völker U, Vollenweider P, Wang G, van Dijk KWI, Wilson O, Xia R, Yao J, Young K, Zhang R, Zhu X, Below J, Böger C, Conen D, Cox S, Dörr M, Feitosa M, Fox E, Franceschini N, Gharib S, Gudnason V, Harlow S, He J, Holliday E, Kutalik Z, Lakka T, Lawlor D, Lee S, Lehtimäki T, Li C, Liu CT, Mägi R, Matsuda F, Morrison A, Penninx BWJH, Peyser P, Rotter J, Snieder H, Spector T, Wagenknecht L, Wareham N, Zonderman A, North K, Fornage M, Hung A, Manning A, Gauderman W, Chen H, Munroe P, Rao D, van Heemst D, Redline S, Noordam R. A Large-Scale Genome-Wide Study of Gene-Sleep Duration Interactions for Blood Pressure in 811,405 Individuals from Diverse Populations. RESEARCH SQUARE 2024:rs.3.rs-4163414. [PMID: 39070651 PMCID: PMC11276021 DOI: 10.21203/rs.3.rs-4163414/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Although both short and long sleep duration are associated with elevated hypertension risk, our understanding of their interplay with biological pathways governing blood pressure remains limited. To address this, we carried out genome-wide cross-population gene-by-short-sleep and long-sleep duration interaction analyses for three blood pressure traits (systolic, diastolic, and pulse pressure) in 811,405 individuals from diverse population groups. We discover 22 novel gene-sleep duration interaction loci for blood pressure, mapped to 23 genes. Investigating these genes' functional implications shed light on neurological, thyroidal, bone metabolism, and hematopoietic pathways that necessitate future investigation for blood pressure management that caters to sleep health lifestyle. Non-overlap between short sleep (12) and long sleep (10) interactions underscores the plausible nature of distinct influences of both sleep duration extremes in cardiovascular health. Several of our loci are specific towards a particular population background or sex, emphasizing the importance of addressing heterogeneity entangled in gene-environment interactions, when considering precision medicine design approaches for blood pressure management.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Michael Brown
- The University of Texas Health Science Center at Houston
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Nicholette Palmer
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
| | | | | | | | | | - Quan Sun
- University of North Carolina, USA
| | | | | | | | | | | | - Stefan Weiss
- University Medicine Greifswald & University of Greifswald
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Sami Heikkinen
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus
| | | | | | | | | | | | | | | | | | | | | | | | | | - Joseph McCormick
- The University of Texas Health Science Center at Houston (UTHealth) School of Public Health
| | - Hao Mei
- University of Mississippi Medical Center
| | | | | | | | - Ilja Nolte
- University of Groningen, University Medical Center Groningen
| | | | | | | | | | | | | | - Olli Raitakari
- Turku University Hospital and Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku
| | | | | | | | | | | | - Rodney Scott
- University of Newcastle and the Hunter Medical Research Institute
| | | | | | | | | | | | | | | | | | | | - Rui Xia
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Jiang He
- Tulane University School of Public Health and Tropical Medicine
| | | | | | | | | | | | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University
| | - Changwei Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | | | | | | | | | | | - Patricia Peyser
- Department of Epidemiology, School of Public Health, University of Michigan
| | - Jerome Rotter
- The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
| | | | | | | | | | | | | | - Myriam Fornage
- 1. Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center
- 2. Human Genetics Center, Department of Epidemiology, School of Public Health
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80
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Sonti S, Littleton SH, Pahl MC, Zimmerman AJ, Chesi A, Palermo J, Lasconi C, Brown EB, Pippin JA, Wells AD, Doldur-Balli F, Pack AI, Gehrman PR, Keene AC, Grant SFA. Perturbation of the insomnia WDR90 genome-wide association studies locus pinpoints rs3752495 as a causal variant influencing distal expression of neighboring gene, PIG-Q. Sleep 2024; 47:zsae085. [PMID: 38571402 PMCID: PMC11236950 DOI: 10.1093/sleep/zsae085] [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: 08/15/2023] [Revised: 01/28/2024] [Indexed: 04/05/2024] Open
Abstract
Although genome-wide association studies (GWAS) have identified loci for sleep-related traits, they do not directly uncover the underlying causal variants and corresponding effector genes. The majority of such variants reside in non-coding regions and are therefore presumed to impact cis-regulatory elements. Our previously reported 'variant-to-gene mapping' effort in human induced pluripotent stem cell (iPSC)-derived neural progenitor cells (NPCs), combined with validation in both Drosophila and zebrafish, implicated phosphatidyl inositol glycan (PIG)-Q as a functionally relevant gene at the insomnia "WDR90" GWAS locus. However, importantly that effort did not characterize the corresponding underlying causal variant. Specifically, our previous 3D genomic datasets nominated a shortlist of three neighboring single nucleotide polymorphisms (SNPs) in strong linkage disequilibrium within an intronic enhancer region of WDR90 that contacted the open PIG-Q promoter. We sought to investigate the influence of these SNPs collectively and then individually on PIG-Q modulation to pinpoint the causal "regulatory" variant. Starting with gross level perturbation, deletion of the entire region in NPCs via CRISPR-Cas9 editing and subsequent RNA sequencing revealed expression changes in specific PIG-Q transcripts. Results from individual luciferase reporter assays for each SNP in iPSCs revealed that the region with the rs3752495 risk allele (RA) induced a ~2.5-fold increase in luciferase expression. Importantly, rs3752495 also exhibited an allele-specific effect, with the RA increasing the luciferase expression by ~2-fold versus the non-RA. In conclusion, our variant-to-function approach and in vitro validation implicate rs3752495 as a causal insomnia variant embedded within WDR90 while modulating the expression of the distally located PIG-Q.
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Affiliation(s)
- Shilpa Sonti
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sheridan H Littleton
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Cell and Molecular Biology Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew C Pahl
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Amber J Zimmerman
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory, Medicine University of Pennsylvania Perelman School of Medicine, Philadelphia PA, USA
| | - Justin Palermo
- Department of Biology, Texas A&M University, College Station, TX, USA
| | - Chiara Lasconi
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Elizabeth B Brown
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - James A Pippin
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Fusun Doldur-Balli
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Allan I Pack
- Division of Sleep Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Phillip R Gehrman
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alex C Keene
- Department of Biology, Texas A&M University, College Station, TX, USA
| | - Struan F A Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Divisions of Human Genetics and Endocrinology & Diabetes, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
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81
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Liu H, Brostoff T, Ramirez A, Wong T, Rowland DJ, Heffner M, Flores A, Willis B, Evans JJ, Lanoue L, Lloyd KCK, Coffey LL. Establishment and characterization of an h ACE2/hTMPRSS2 knock-in mouse model to study SARS-CoV-2. Front Immunol 2024; 15:1428711. [PMID: 39050847 PMCID: PMC11266032 DOI: 10.3389/fimmu.2024.1428711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Accepted: 06/25/2024] [Indexed: 07/27/2024] Open
Abstract
Despite a substantial body of research, we lack fundamental understanding of the pathophysiology of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) including pulmonary and cardiovascular outcomes, in part due to limitations of murine models. Most models use transgenic mice (K18) that express the human (h) angiotensin converting enzyme 2 (ACE2), ACE2 knock-in (KI) mice, or mouse-adapted strains of SARS-CoV-2. Further, many SARS-CoV-2 variants produce fatal neurologic disease in K18 mice and most murine studies focus only on acute disease in the first 14 days post inoculation (dpi). To better enable understanding of both acute (<14 dpi) and post-acute (>14 dpi) infection phases, we describe the development and characterization of a novel non-lethal KI mouse that expresses both the ACE2 and transmembrane serine protease 2 (TMPRSS2) genes (hACE2/hTMPRSS2). The human genes were engineered to replace the orthologous mouse gene loci but remain under control of their respective murine promoters, resulting in expression of ACE2 and TMPRSS2 instead of their murine counterparts. After intranasal inoculation with an omicron strain of SARS-CoV-2, hACE2/hTMPRSS2 KI mice transiently lost weight but recovered by 7 dpi. Infectious SARS-CoV-2 was detected in nasopharyngeal swabs 1-2 dpi and in lung tissues 2-6 dpi, peaking 4 dpi. These outcomes were similar to those in K18 mice that were inoculated in parallel. To determine the extent to which hACE2/hTMPRSS2 KI mice are suitable to model pulmonary and cardiovascular outcomes, physiological assessments measuring locomotion, behavior and reflexes, biomonitoring to measure cardiac activity and respiration, and micro computed tomography to assess lung function were conducted frequently to 6 months post inoculation. Male but not female SARS-CoV-2 inoculated hACE2/hTMPRSS2 KI mice showed a transient reduction in locomotion compared to control saline treated mice. No significant changes in respiration, oxygen saturation, heart rate variability, or conductivity were detected in SARS-CoV-2 inoculated mice of either sex. When re-inoculated 6 months after the first inoculation, hACE2/hTMPRSS2 KI became re-infected with disease signs similar to after the first inoculation. Together these data show that a newly generated hACE2/hTMPRSS2 KI mouse can be used to study mild COVID-19.
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Affiliation(s)
- Hongwei Liu
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA, United States
| | - Terza Brostoff
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA, United States
| | - Ana Ramirez
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA, United States
| | - Talia Wong
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA, United States
| | - Douglas J. Rowland
- Center for Molecular and Genomic Imaging, College of Engineering, University of California, Davis, Davis, CA, United States
| | - Mollie Heffner
- Mouse Biology Program, University of California, Davis, Davis, CA, United States
| | - Arturo Flores
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA, United States
| | - Brandon Willis
- Mouse Biology Program, University of California, Davis, Davis, CA, United States
| | - Jeffrey J. Evans
- Mouse Biology Program, University of California, Davis, Davis, CA, United States
| | - Louise Lanoue
- Mouse Biology Program, University of California, Davis, Davis, CA, United States
| | - K. C. Kent Lloyd
- Mouse Biology Program, University of California, Davis, Davis, CA, United States
- Department of Surgery, School of Medicine, University of California, Davis, Davis, CA, United States
| | - Lark L. Coffey
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California, Davis, CA, United States
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82
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Venkatesh SS, Ganjgahi H, Palmer DS, Coley K, Linchangco GV, Hui Q, Wilson P, Ho YL, Cho K, Arumäe K, Wittemans LBL, Nellåker C, Vainik U, Sun YV, Holmes C, Lindgren CM, Nicholson G. Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records. Nat Commun 2024; 15:5801. [PMID: 38987242 PMCID: PMC11237142 DOI: 10.1038/s41467-024-49998-0] [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: 01/25/2023] [Accepted: 06/25/2024] [Indexed: 07/12/2024] Open
Abstract
Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.
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Affiliation(s)
- Samvida S Venkatesh
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - Habib Ganjgahi
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Duncan S Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Kayesha Coley
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Gregorio V Linchangco
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Qin Hui
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Peter Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kadri Arumäe
- Institute of Psychology, Faculty of Social Sciences, University of Tartu, Tartu, Estonia
| | - Laura B L Wittemans
- Novo Nordisk Research Centre Oxford, Oxford, UK
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Christoffer Nellåker
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Uku Vainik
- Institute of Psychology, Faculty of Social Sciences, University of Tartu, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
- Department of Neurology and Neurosurgery, Faculty of Medicine and Health Sciences, University of McGill, Montreal, Canada
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Chris Holmes
- Department of Statistics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, Medical Sciences Division, University of Oxford, Oxford, UK
- The Alan Turing Institute, London, UK
| | - Cecilia M Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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83
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Roston RA, Whikehart SM, Rolfe SM, Maga M. Morphological simulation tests the limits on phenotype discovery in 3D image analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.30.601430. [PMID: 39005442 PMCID: PMC11244899 DOI: 10.1101/2024.06.30.601430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
In the past few decades, advances in 3D imaging have created new opportunities for reverse genetic screens. Rapidly growing datasets of 3D images of genetic knockouts require high-throughput, automated computational approaches for identifying and characterizing new phenotypes. However, exploratory, discovery-oriented image analysis pipelines used to discover these phenotypes can be difficult to validate because, by their nature, the expected outcome is not known a priori . Introducing known morphological variation through simulation can help distinguish between real phenotypic differences and random variation; elucidate the effects of sample size; and test the sensitivity and reproducibility of morphometric analyses. Here we present a novel approach for 3D morphological simulation that uses open-source, open-access tools available in 3D Slicer, SlicerMorph, and Advanced Normalization Tools in R (ANTsR). While we focus on diffusible-iodine contrast-enhanced micro-CT (diceCT) images, this approach can be used on any volumetric image. We then use our simulated datasets to test whether tensor-based morphometry (TBM) can recover our introduced differences; to test how effect size and sample size affect detectability; and to determine the reproducibility of our results. In our approach to morphological simulation, we first generate a simulated deformation based on a reference image and then propagate this deformation to subjects using inverse transforms obtained from the registration of subjects to the reference. This produces a new dataset with a shifted population mean while retaining individual variability because each sample deforms more or less based on how different or similar it is from the reference. TBM is a widely-used technique that statistically compares local volume differences associated with local deformations. Our results showed that TBM recovered our introduced morphological differences, but that detectability was dependent on the effect size, the sample size, and the region of interest (ROI) included in the analysis. Detectability of subtle phenotypes can be improved both by increasing the sample size and by limiting analyses to specific body regions. However, it is not always feasible to increase sample sizes in screens of essential genes. Therefore, methodical use of ROIs is a promising way to increase the power of TBM to detect subtle phenotypes. Generating known morphological variation through simulation has broad applicability in developmental, evolutionary, and biomedical morphometrics and is a useful way to distinguish between a failure to detect morphological difference and a true lack of morphological difference. Morphological simulation can also be applied to AI-based supervised learning to augment datasets and overcome dataset limitations.
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84
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Cacheiro P, Lawson S, Van den Veyver IB, Marengo G, Zocche D, Murray SA, Duyzend M, Robinson PN, Smedley D. Lethal phenotypes in Mendelian disorders. Genet Med 2024; 26:101141. [PMID: 38629401 PMCID: PMC11232373 DOI: 10.1016/j.gim.2024.101141] [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: 02/05/2024] [Revised: 04/08/2024] [Accepted: 04/09/2024] [Indexed: 04/26/2024] Open
Abstract
PURPOSE Existing resources that characterize the essentiality status of genes are based on either proliferation assessment in human cell lines, viability evaluation in mouse knockouts, or constraint metrics derived from human population sequencing studies. Several repositories document phenotypic annotations for rare disorders; however, there is a lack of comprehensive reporting on lethal phenotypes. METHODS We queried Online Mendelian Inheritance in Man for terms related to lethality and classified all Mendelian genes according to the earliest age of death recorded for the associated disorders, from prenatal death to no reports of premature death. We characterized the genes across these lethality categories, examined the evidence on viability from mouse models and explored how this information could be used for novel gene discovery. RESULTS We developed the Lethal Phenotypes Portal to showcase this curated catalog of human essential genes. Differences in the mode of inheritance, physiological systems affected, and disease class were found for genes in different lethality categories, as well as discrepancies between the lethal phenotypes observed in mouse and human. CONCLUSION We anticipate that this resource will aid clinicians in the diagnosis of early lethal conditions and assist researchers in investigating the properties that make these genes essential for human development.
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Affiliation(s)
- Pilar Cacheiro
- William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
| | - Samantha Lawson
- ITS Research, Queen Mary University of London, London, United Kingdom
| | - Ignatia B Van den Veyver
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX; Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX
| | - Gabriel Marengo
- William Harvey Research Institute, Queen Mary University of London, London, United Kingdom
| | - David Zocche
- North West Thames Regional Genetics Service, Northwick Park and St Mark's Hospitals, London, United Kingdom
| | | | - Michael Duyzend
- Massachusetts General Hospital, Boston, MA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Department of Pediatrics, Boston Children's Hospital and Harvard Medical School, Boston, MA
| | - Peter N Robinson
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Damian Smedley
- William Harvey Research Institute, Queen Mary University of London, London, United Kingdom.
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85
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Reed JN, Huang J, Li Y, Ma L, Banka D, Wabitsch M, Wang T, Ding W, Björkegren JL, Civelek M. Systems genetics analysis of human body fat distribution genes identifies adipocyte processes. Life Sci Alliance 2024; 7:e202402603. [PMID: 38702075 PMCID: PMC11068934 DOI: 10.26508/lsa.202402603] [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: 01/18/2024] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 05/06/2024] Open
Abstract
Excess abdominal fat is a sexually dimorphic risk factor for cardio-metabolic disease and is approximated by the waist-to-hip ratio adjusted for body mass index (WHRadjBMI). Whereas this trait is highly heritable, few causal genes are known. We aimed to identify novel drivers of WHRadjBMI using systems genetics. We used two independent cohorts of adipose tissue gene expression and constructed sex- and depot-specific Bayesian networks to model gene-gene interactions from 8,492 genes. Using key driver analysis, we identified genes that, in silico and putatively in vitro, regulate many others. 51-119 key drivers in each network were replicated in both cohorts. In other cell types, 23 of these genes are found in crucial adipocyte pathways: Wnt signaling or mitochondrial function. We overexpressed or down-regulated seven key driver genes in human subcutaneous pre-adipocytes. Key driver genes ANAPC2 and RSPO1 inhibited adipogenesis, whereas PSME3 increased adipogenesis. RSPO1 increased Wnt signaling activity. In differentiated adipocytes, MIGA1 and UBR1 down-regulation led to mitochondrial dysfunction. These five genes regulate adipocyte function, and we hypothesize that they regulate fat distribution.
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Affiliation(s)
- Jordan N Reed
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Jiansheng Huang
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Yong Li
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Lijiang Ma
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dhanush Banka
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
| | - Martin Wabitsch
- Division of Paediatric Endocrinology and Diabetes, Department of Paediatrics and Adolescent Medicine, Ulm University Medical Centre, Ulm, Germany
| | - Tianfang Wang
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Wen Ding
- Novo Nordisk Research Center China, Novo Nordisk A/S, Beijing, China
| | - Johan Lm Björkegren
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Mete Civelek
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
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86
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Peterson L, Yacoub MH, Ayares D, Yamada K, Eisenson D, Griffith BP, Mohiuddin MM, Eyestone W, Venter JC, Smolenski RT, Rothblatt M. Physiological basis for xenotransplantation from genetically modified pigs to humans. Physiol Rev 2024; 104:1409-1459. [PMID: 38517040 PMCID: PMC11390123 DOI: 10.1152/physrev.00041.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 03/06/2024] [Accepted: 03/14/2024] [Indexed: 03/23/2024] Open
Abstract
The collective efforts of scientists over multiple decades have led to advancements in molecular and cellular biology-based technologies including genetic engineering and animal cloning that are now being harnessed to enhance the suitability of pig organs for xenotransplantation into humans. Using organs sourced from pigs with multiple gene deletions and human transgene insertions, investigators have overcome formidable immunological and physiological barriers in pig-to-nonhuman primate (NHP) xenotransplantation and achieved prolonged pig xenograft survival. These studies informed the design of Revivicor's (Revivicor Inc, Blacksburg, VA) genetically engineered pigs with 10 genetic modifications (10 GE) (including the inactivation of 4 endogenous porcine genes and insertion of 6 human transgenes), whose hearts and kidneys have now been studied in preclinical human xenotransplantation models with brain-dead recipients. Additionally, the first two clinical cases of pig-to-human heart xenotransplantation were recently performed with hearts from this 10 GE pig at the University of Maryland. Although this review focuses on xenotransplantation of hearts and kidneys, multiple organs, tissues, and cell types from genetically engineered pigs will provide much-needed therapeutic interventions in the future.
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Affiliation(s)
- Leigh Peterson
- United Therapeutics Corporation, Silver Spring, Maryland, United States
| | | | - David Ayares
- United Therapeutics Corporation, Silver Spring, Maryland, United States
| | - Kazuhiko Yamada
- Department of Surgery, Division of Transplantation, Johns Hopkins Medicine, Baltimore, Maryland, United States
| | - Daniel Eisenson
- Department of Surgery, Division of Transplantation, Johns Hopkins Medicine, Baltimore, Maryland, United States
| | - Bartley P Griffith
- University of Maryland Medical Center, Baltimore, Maryland, United States
| | | | - Willard Eyestone
- United Therapeutics Corporation, Silver Spring, Maryland, United States
| | - J Craig Venter
- J. Craig Venter Institute, Rockville, Maryland, United States
| | | | - Martine Rothblatt
- United Therapeutics Corporation, Silver Spring, Maryland, United States
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87
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Federspiel JD, Catlin NR, Nowland WS, Stethem CM, Mathialagan N, Fernandez Ocaña M, Bowman CJ. Differential Analysis of Cereblon Neosubstrates in Rabbit Embryos Using Targeted Proteomics. Mol Cell Proteomics 2024; 23:100797. [PMID: 38866076 PMCID: PMC11263748 DOI: 10.1016/j.mcpro.2024.100797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 05/31/2024] [Accepted: 06/06/2024] [Indexed: 06/14/2024] Open
Abstract
Targeted protein degradation is the selective removal of a protein of interest through hijacking intracellular protein cleanup machinery. This rapidly growing field currently relies heavily on the use of the E3 ligase cereblon (CRBN) to target proteins for degradation, including the immunomodulatory drugs (IMiDs) thalidomide, lenalidomide, and pomalidomide which work through a molecular glue mechanism of action with CRBN. While CRBN recruitment can result in degradation of a specific protein of interest (e.g., efficacy), degradation of other proteins (called CRBN neosubstrates) also occurs. Degradation of one or more of these CRBN neosubstrates is believed to play an important role in thalidomide-related developmental toxicity observed in rabbits and primates. We identified a set of 25 proteins of interest associated with CRBN-related protein homeostasis and/or embryo/fetal development. We developed a targeted assay for these proteins combining peptide immunoaffinity enrichment and high-resolution mass spectrometry and successfully applied this assay to rabbit embryo samples from pregnant rabbits dosed with three IMiDs. We confirmed previously reported in vivo decreases in neosubstrates like SALL4, as well as provided evidence of neosubstrate changes for proteins only examined in vitro previously. While there were many proteins that were similarly decreased by all three IMiDs, no compound had the exact same neosubstrate degradation profile as another. We compared our data to previous literature reports of IMiD-induced degradation and known developmental biology associations. Based on our observations, we recommend monitoring at least a major subset of these neosubstrates in a developmental test system to improve CRBN-binding compound-specific risk assessment. A strength of our assay is that it is configurable, and the target list can be readily adapted to focus on only a subset of proteins of interest or expanded to incorporate new findings as additional information about CRBN biology is discovered.
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Affiliation(s)
- Joel D Federspiel
- Drug Safety Research & Development, Pfizer, Inc, Andover, Massachusetts, USA
| | - Natasha R Catlin
- Drug Safety Research & Development, Pfizer, Inc, Groton, Connecticut, USA
| | - William S Nowland
- Drug Safety Research & Development, Pfizer, Inc, Groton, Connecticut, USA
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88
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Li X, Morel JD, Sulc J, De Masi A, Lalou A, Benegiamo G, Poisson J, Liu Y, Von Alvensleben GVG, Gao AW, Bou Sleiman M, Auwerx J. Systems genetics of metabolic health in the BXD mouse genetic reference population. Cell Syst 2024; 15:497-509.e3. [PMID: 38866010 DOI: 10.1016/j.cels.2024.05.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 02/29/2024] [Accepted: 05/20/2024] [Indexed: 06/14/2024]
Abstract
Susceptibility to metabolic syndrome (MetS) is dependent on genetics, environment, and gene-by-environment interactions, rendering the study of underlying mechanisms challenging. The majority of experiments in model organisms do not incorporate genetic variation and lack specific evaluation criteria for MetS. Here, we derived a continuous metric, the metabolic health score (MHS), based on standard clinical parameters and defined its molecular signatures in the liver and circulation. In human UK Biobank, the MHS associated with MetS status and was predictive of future disease incidence, even in individuals without MetS. Using quantitative trait locus analyses in mice, we found two MHS-associated genetic loci and replicated them in unrelated mouse populations. Through a prioritization scheme in mice and human genetic data, we identified TNKS and MCPH1 as candidates mediating differences in the MHS. Our findings provide insights into the molecular mechanisms sustaining metabolic health across species and uncover likely regulators. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Xiaoxu Li
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jean-David Morel
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jonathan Sulc
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Alessia De Masi
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Amélia Lalou
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Giorgia Benegiamo
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Johanne Poisson
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Yasmine Liu
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Giacomo V G Von Alvensleben
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Arwen W Gao
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Maroun Bou Sleiman
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
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89
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Zhong X, Peddada N, Moresco JJ, Wang J, Jiang Y, Rios JJ, Moresco EMY, Choi JH, Beutler B. Viable mutations of mouse midnolin suppress B cell malignancies. J Exp Med 2024; 221:e20232132. [PMID: 38625151 PMCID: PMC11022886 DOI: 10.1084/jem.20232132] [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: 11/18/2023] [Revised: 02/20/2024] [Accepted: 03/28/2024] [Indexed: 04/17/2024] Open
Abstract
In a genetic screen, we identified two viable missense alleles of the essential gene Midnolin (Midn) that were associated with reductions in peripheral B cells. Causation was confirmed in mice with targeted deletion of four of six MIDN protein isoforms. MIDN was expressed predominantly in lymphocytes where it augmented proteasome activity. We showed that purified MIDN directly stimulated 26S proteasome activity in vitro in a manner dependent on the ubiquitin-like domain and a C-terminal region. MIDN-deficient B cells displayed aberrant activation of the IRE-1/XBP-1 pathway of the unfolded protein response. Partial or complete MIDN deficiency strongly suppressed Eμ-Myc-driven B cell leukemia and the antiapoptotic effects of Eμ-BCL2 on B cells in vivo and induced death of Sp2/0 hybridoma cells in vitro, but only partially impaired normal lymphocyte development. Thus, MIDN is required for proteasome activity in support of normal lymphopoiesis and is essential for malignant B cell proliferation over a broad range of differentiation states.
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Affiliation(s)
- Xue Zhong
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Nagesh Peddada
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - James J. Moresco
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jianhui Wang
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Yiao Jiang
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jonathan J. Rios
- Center for Pediatric Bone Biology and Translational Research, Scottish Rite for Children, Dallas, TX, USA
- McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Orthopaedic Surgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Eva Marie Y. Moresco
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jin Huk Choi
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bruce Beutler
- Center for the Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX, USA
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90
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Cacheiro P, Pava D, Parkinson H, VanZanten M, Wilson R, Gunes O, The International Mouse Phenotyping Consortium, Smedley D. Computational identification of disease models through cross-species phenotype comparison. Dis Model Mech 2024; 17:dmm050604. [PMID: 38881316 PMCID: PMC11247498 DOI: 10.1242/dmm.050604] [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: 11/13/2023] [Accepted: 06/11/2024] [Indexed: 06/18/2024] Open
Abstract
The use of standardised phenotyping screens to identify abnormal phenotypes in mouse knockouts, together with the use of ontologies to describe such phenotypic features, allows the implementation of an automated and unbiased pipeline to identify new models of disease by performing phenotype comparisons across species. Using data from the International Mouse Phenotyping Consortium (IMPC), approximately half of mouse mutants are able to mimic, at least partially, the human ortholog disease phenotypes as computed by the PhenoDigm algorithm. We found the number of phenotypic abnormalities in the mouse and the corresponding Mendelian disorder, the pleiotropy and severity of the disease, and the viability and zygosity status of the mouse knockout to be associated with the ability of mouse models to recapitulate the human disorder. An analysis of the IMPC impact on disease gene discovery through a publication-tracking system revealed that the resource has been implicated in at least 109 validated rare disease-gene associations over the last decade.
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Affiliation(s)
- Pilar Cacheiro
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Diego Pava
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Helen Parkinson
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Maya VanZanten
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Robert Wilson
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Osman Gunes
- European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | | | - Damian Smedley
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
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91
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Pedro MP, Lund K, Kang SWS, Chen T, Stuelten CH, Porat-Shliom N, Iglesias-Bartolome R. GPCR Screening Reveals that the Metabolite Receptor HCAR3 Regulates Epithelial Proliferation, Migration, and Cellular Respiration. J Invest Dermatol 2024; 144:1311-1321.e7. [PMID: 38103827 PMCID: PMC11116076 DOI: 10.1016/j.jid.2023.12.002] [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: 10/12/2023] [Revised: 11/24/2023] [Accepted: 12/04/2023] [Indexed: 12/19/2023]
Abstract
Epithelial cells in the skin and other tissues rely on signals from their environment to maintain homeostasis and respond to injury, and GPCRs play a critical role in this communication. A better understanding of the GPCRs expressed in epithelial cells will contribute to understanding the relationship between cells and their niche and could lead to developing new therapies to modulate cell fate. This study used human primary keratinocytes as a model to investigate the specific GPCRs regulating epithelial cell proliferation and differentiation. We identified 3 key receptors-HCAR3, LTB4R, and GPR137-and found that knockdown of these receptors led to changes in numerous gene networks that are important for maintaining cell identity and promoting proliferation while inhibiting differentiation. Our study also revealed that the metabolite receptor HCAR3 regulates keratinocyte migration and cellular metabolism. Knockdown of HCAR3 led to reduced keratinocyte migration and respiration, which could be attributed to altered metabolite use and aberrant mitochondrial morphology caused by the absence of the receptor. This study contributes to understanding the complex interplay between GPCR signaling and epithelial cell fate decisions.
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Affiliation(s)
- M Pilar Pedro
- Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Katherine Lund
- Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Sun Woo Sophie Kang
- Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Ting Chen
- Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Christina H Stuelten
- Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Natalie Porat-Shliom
- Thoracic and GI Malignancies Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Ramiro Iglesias-Bartolome
- Laboratory of Cellular and Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
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92
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Tomar A, Gomez-Velazquez M, Gerlini R, Comas-Armangué G, Makharadze L, Kolbe T, Boersma A, Dahlhoff M, Burgstaller JP, Lassi M, Darr J, Toppari J, Virtanen H, Kühnapfel A, Scholz M, Landgraf K, Kiess W, Vogel M, Gailus-Durner V, Fuchs H, Marschall S, Hrabě de Angelis M, Kotaja N, Körner A, Teperino R. Epigenetic inheritance of diet-induced and sperm-borne mitochondrial RNAs. Nature 2024; 630:720-727. [PMID: 38839949 PMCID: PMC11186758 DOI: 10.1038/s41586-024-07472-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 04/26/2024] [Indexed: 06/07/2024]
Abstract
Spermatozoa harbour a complex and environment-sensitive pool of small non-coding RNAs (sncRNAs)1, which influences offspring development and adult phenotypes1-7. Whether spermatozoa in the epididymis are directly susceptible to environmental cues is not fully understood8. Here we used two distinct paradigms of preconception acute high-fat diet to dissect epididymal versus testicular contributions to the sperm sncRNA pool and offspring health. We show that epididymal spermatozoa, but not developing germ cells, are sensitive to the environment and identify mitochondrial tRNAs (mt-tRNAs) and their fragments (mt-tsRNAs) as sperm-borne factors. In humans, mt-tsRNAs in spermatozoa correlate with body mass index, and paternal overweight at conception doubles offspring obesity risk and compromises metabolic health. Sperm sncRNA sequencing of mice mutant for genes involved in mitochondrial function, and metabolic phenotyping of their wild-type offspring, suggest that the upregulation of mt-tsRNAs is downstream of mitochondrial dysfunction. Single-embryo transcriptomics of genetically hybrid two-cell embryos demonstrated sperm-to-oocyte transfer of mt-tRNAs at fertilization and suggested their involvement in the control of early-embryo transcription. Our study supports the importance of paternal health at conception for offspring metabolism, shows that mt-tRNAs are diet-induced and sperm-borne and demonstrates, in a physiological setting, father-to-offspring transfer of sperm mitochondrial RNAs at fertilization.
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MESH Headings
- Animals
- Female
- Humans
- Male
- Mice
- Body Mass Index
- Diet, High-Fat/adverse effects
- Embryo, Mammalian/cytology
- Embryo, Mammalian/embryology
- Embryo, Mammalian/metabolism
- Epididymis/cytology
- Epigenesis, Genetic/genetics
- Fertilization/genetics
- Gene Expression Profiling
- Gene Expression Regulation, Developmental
- Mice, Inbred C57BL
- Mitochondria/genetics
- Mitochondria/metabolism
- Mitochondria/pathology
- Obesity/genetics
- Obesity/metabolism
- Obesity/etiology
- Oocytes/metabolism
- Overweight/genetics
- Overweight/metabolism
- Paternal Inheritance/genetics
- RNA, Mitochondrial/genetics
- RNA, Mitochondrial/metabolism
- RNA, Small Untranslated/genetics
- RNA, Small Untranslated/metabolism
- RNA, Transfer/genetics
- RNA, Transfer/metabolism
- Spermatozoa/metabolism
- Testis/cytology
- Transcription, Genetic
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Affiliation(s)
- A Tomar
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - M Gomez-Velazquez
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - R Gerlini
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - G Comas-Armangué
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - L Makharadze
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - T Kolbe
- Unit of in vivo and in vitro Models, Center for Biological Sciences, Department of Biological Sciences and Pathobiology, University of Veterinary Medicine Vienna, Vienna, Austria
- IFA-Tulln, University of Natural Resources and Life Sciences, Vienna, Austria
| | - A Boersma
- Unit of in vivo and in vitro Models, Center for Biological Sciences, Department of Biological Sciences and Pathobiology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - M Dahlhoff
- Unit of in vivo and in vitro Models, Center for Biological Sciences, Department of Biological Sciences and Pathobiology, University of Veterinary Medicine Vienna, Vienna, Austria
| | - J P Burgstaller
- Institute of Animal Breeding and Genetics, Department of Biological Sciences and Pathobiology, University of Veterinary Medicine Vienna, Vienna, Austria
- Group Molecular Reproduction, IFA-Tulln, Tulln, Austria
| | - M Lassi
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - J Darr
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
| | - J Toppari
- Institute of Biomedicine, Integrative Physiology and Pharmacology Unit, University of Turku, Turku, Finland
- Center for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - H Virtanen
- Institute of Biomedicine, Integrative Physiology and Pharmacology Unit, University of Turku, Turku, Finland
- Center for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - A Kühnapfel
- University of Leipzig, Medical Faculty, Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany
| | - M Scholz
- University of Leipzig, Medical Faculty, Institute for Medical Informatics, Statistics and Epidemiology, Leipzig, Germany
| | - K Landgraf
- Center for Pediatric Research Leipzig (CPL), Hospital for Children & Adolescents, University of Leipzig, Leipzig, Germany
| | - W Kiess
- Center for Pediatric Research Leipzig (CPL), Hospital for Children & Adolescents, University of Leipzig, Leipzig, Germany
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - M Vogel
- Center for Pediatric Research Leipzig (CPL), Hospital for Children & Adolescents, University of Leipzig, Leipzig, Germany
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - V Gailus-Durner
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - H Fuchs
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - S Marschall
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - M Hrabě de Angelis
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- German Center for Diabetes Research (DZD), Neuherberg, Germany
- German Mouse Clinic, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany
- Chair of Experimental Genetics, TUM School of Life Sciences, Technische Universität München, Freising, Germany
| | - N Kotaja
- Institute of Biomedicine, Integrative Physiology and Pharmacology Unit, University of Turku, Turku, Finland
| | - A Körner
- Center for Pediatric Research Leipzig (CPL), Hospital for Children & Adolescents, University of Leipzig, Leipzig, Germany
- LIFE Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany
- Helmholtz Institute for Metabolic Obesity and Vascular Research (HI-MAG), Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
| | - R Teperino
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
- German Center for Diabetes Research (DZD), Neuherberg, Germany.
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Kasprzyk-Pawelec A, Tan M, Rahhal R, McIntosh A, Fernandez H, Mosaoa R, Jiang L, Pearson GW, Glasgow E, Vockley J, Albanese C, Avantaggiati ML. Loss of the mitochondrial carrier, SLC25A1, during embryogenesis induces a unique senescence program controlled by p53. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.18.549409. [PMID: 37503155 PMCID: PMC10370133 DOI: 10.1101/2023.07.18.549409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Germline inactivating mutations of the SLC25A1 gene contribute to various human developmental disorders, including combined D/L-2-hydroxyglutaric aciduria (D/L-2HGA), a severe systemic syndrome characterized by the accumulation of both enantiomers of 2-hydroxyglutaric acid (2HG). The mechanisms by which SLC25A1 deficiency leads to this disease and the role of 2HG are unclear and no therapies exist. We now show that mice lacking both Slc25a1 alleles display a spectrum of alterations that resemble human D/L-2HGA. Mechanistically, SLC25A1 loss results in a proliferation defect and activates two distinct senescence pathways, oncogene-induced senescence (OIS) and mitochondrial dysfunction-induced senescence (MiDAS), both involving the p53 tumor suppressor and driven by two discernible signals: the accumulation of 2HG, inducing OIS, and mitochondrial dysfunction, triggering MiDAS. Inhibiting these senescence programs or blocking p53 activity reverses the growth defect caused by SLC25A1 dysfunction and restores proliferation. These findings reveal novel pathogenic roles of senescence in human disorders and suggest potential strategies to correct the molecular alterations caused by SLC25A1 loss.
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94
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Martinez-Mayer J, Brinkmeier ML, O'Connell SP, Ukagwu A, Marti MA, Miras M, Forclaz MV, Benzrihen MG, Cheung LYM, Camper SA, Ellsworth BS, Raetzman LT, Pérez-Millán MI, Davis SW. Knockout mice with pituitary malformations help identify human cases of hypopituitarism. Genome Med 2024; 16:75. [PMID: 38822427 PMCID: PMC11140907 DOI: 10.1186/s13073-024-01347-y] [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: 10/09/2023] [Accepted: 05/20/2024] [Indexed: 06/03/2024] Open
Abstract
BACKGROUND Congenital hypopituitarism (CH) and its associated syndromes, septo-optic dysplasia (SOD) and holoprosencephaly (HPE), are midline defects that cause significant morbidity for affected people. Variants in 67 genes are associated with CH, but a vast majority of CH cases lack a genetic diagnosis. Whole exome and whole genome sequencing of CH patients identifies sequence variants in genes known to cause CH, and in new candidate genes, but many of these are variants of uncertain significance (VUS). METHODS The International Mouse Phenotyping Consortium (IMPC) is an effort to establish gene function by knocking-out all genes in the mouse genome and generating corresponding phenotype data. We used mouse embryonic imaging data generated by the Deciphering Mechanisms of Developmental Disorders (DMDD) project to screen 209 embryonic lethal and sub-viable knockout mouse lines for pituitary malformations. RESULTS Of the 209 knockout mouse lines, we identified 51 that have embryonic pituitary malformations. These genes not only represent new candidates for CH, but also reveal new molecular pathways not previously associated with pituitary organogenesis. We used this list of candidate genes to mine whole exome sequencing data of a cohort of patients with CH, and we identified variants in two unrelated cases for two genes, MORC2 and SETD5, with CH and other syndromic features. CONCLUSIONS The screening and analysis of IMPC phenotyping data provide proof-of-principle that recessive lethal mouse mutants generated by the knockout mouse project are an excellent source of candidate genes for congenital hypopituitarism in children.
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Affiliation(s)
- Julian Martinez-Mayer
- Institute of Biosciences, Biotechnology and Translational Biology (iB3), University of Buenos Aires, Intendente Güiraldes 2160, Ciudad Universitaria, C1428EGA, Buenos Aires, Argentina
| | - Michelle L Brinkmeier
- Department of Human Genetics, University of Michigan, 1241 Catherine St., Ann Arbor, MI, 48109-5618, USA
| | - Sean P O'Connell
- Department of Biological Sciences, University of South Carolina, 715 Sumter St., Columbia, SC, 29208, USA
| | - Arnold Ukagwu
- Department of Physiology, Southern Illinois University, 1135 Lincoln Dr, Carbondale, IL, 62901, USA
| | - Marcelo A Marti
- Instituto de Química Biológica de La Facultad de Ciencias Exactas y Naturales (IQUIBICEN), Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Mirta Miras
- Hospital De Niños de La Santísima Trinidad, Córdoba, Argentina
| | - Maria V Forclaz
- Servicio de Endocrinología, Hospital Posadas, Buenos Aires, Argentina
| | - Maria G Benzrihen
- Servicio de Endocrinología, Hospital Posadas, Buenos Aires, Argentina
| | - Leonard Y M Cheung
- Department of Human Genetics, University of Michigan, 1241 Catherine St., Ann Arbor, MI, 48109-5618, USA
- Department of Physiology and Biophyscis, Renaissance School of Medicine, Stony Brook University, Stony Brook, NY, 11794, USA
| | - Sally A Camper
- Department of Human Genetics, University of Michigan, 1241 Catherine St., Ann Arbor, MI, 48109-5618, USA
| | - Buffy S Ellsworth
- Department of Physiology, Southern Illinois University, 1135 Lincoln Dr, Carbondale, IL, 62901, USA
| | - Lori T Raetzman
- Department of Molecular and Integrative Physiology, University of Illinois, Champaign-Urbana, Urbana, IL, 61801, USA
| | - Maria I Pérez-Millán
- Institute of Biosciences, Biotechnology and Translational Biology (iB3), University of Buenos Aires, Intendente Güiraldes 2160, Ciudad Universitaria, C1428EGA, Buenos Aires, Argentina.
| | - Shannon W Davis
- Department of Biological Sciences, University of South Carolina, 715 Sumter St., Columbia, SC, 29208, USA.
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95
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Cox RM, Papoulas O, Shril S, Lee C, Gardner T, Battenhouse AM, Lee M, Drew K, McWhite CD, Yang D, Leggere JC, Durand D, Hildebrandt F, Wallingford JB, Marcotte EM. Ancient eukaryotic protein interactions illuminate modern genetic traits and disorders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.26.595818. [PMID: 38853926 PMCID: PMC11160598 DOI: 10.1101/2024.05.26.595818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
All eukaryotes share a common ancestor from roughly 1.5 - 1.8 billion years ago, a single-celled, swimming microbe known as LECA, the Last Eukaryotic Common Ancestor. Nearly half of the genes in modern eukaryotes were present in LECA, and many current genetic diseases and traits stem from these ancient molecular systems. To better understand these systems, we compared genes across modern organisms and identified a core set of 10,092 shared protein-coding gene families likely present in LECA, a quarter of which are uncharacterized. We then integrated >26,000 mass spectrometry proteomics analyses from 31 species to infer how these proteins interact in higher-order complexes. The resulting interactome describes the biochemical organization of LECA, revealing both known and new assemblies. We analyzed these ancient protein interactions to find new human gene-disease relationships for bone density and congenital birth defects, demonstrating the value of ancestral protein interactions for guiding functional genetics today.
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Affiliation(s)
- Rachael M Cox
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Ophelia Papoulas
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Shirlee Shril
- Division of Nephrology, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA 02215, USA
| | - Chanjae Lee
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Tynan Gardner
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Anna M Battenhouse
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Muyoung Lee
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Kevin Drew
- Department of Biological Sciences, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Claire D McWhite
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | - David Yang
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Janelle C Leggere
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Dannie Durand
- Department of Biological Sciences, Carnegie Mellon University, 4400 5th Avenue Pittsburgh, PA 15213, USA
| | - Friedhelm Hildebrandt
- Division of Nephrology, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA 02215, USA
| | - John B Wallingford
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
| | - Edward M Marcotte
- Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA
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96
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Bower G, Hollingsworth EW, Jacinto S, Clock B, Cao K, Liu M, Dziulko A, Alcaina-Caro A, Xu Q, Skowronska-Krawczyk D, Lopez-Rios J, Dickel DE, Bardet AF, Pennacchio LA, Visel A, Kvon EZ. Conserved Cis-Acting Range Extender Element Mediates Extreme Long-Range Enhancer Activity in Mammals. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.26.595809. [PMID: 38826394 PMCID: PMC11142232 DOI: 10.1101/2024.05.26.595809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
While most mammalian enhancers regulate their cognate promoters over moderate distances of tens of kilobases (kb), some enhancers act over distances in the megabase range. The sequence features enabling such extreme-distance enhancer-promoter interactions remain elusive. Here, we used in vivo enhancer replacement experiments in mice to show that short- and medium-range enhancers cannot initiate gene expression at extreme-distance range. We uncover a novel conserved cis-acting element, Range EXtender (REX), that confers extreme-distance regulatory activity and is located next to a long-range enhancer of Sall1. The REX element itself has no endogenous enhancer activity. However, addition of the REX to other short- and mid-range enhancers substantially increases their genomic interaction range. In the most extreme example observed, addition of the REX increased the range of an enhancer by an order of magnitude, from its native 71kb to 840kb. The REX element contains highly conserved [C/T]AATTA homeodomain motifs. These motifs are enriched around long-range limb enhancers genome-wide, including the ZRS, a benchmark long-range limb enhancer of Shh. Mutating the [C/T]AATTA motifs within the ZRS does not affect its limb-specific enhancer activity at short range, but selectively abolishes its long-range activity, resulting in severe limb reduction in knock-in mice. In summary, we identify a sequence signature globally associated with long-range enhancer-promoter interactions and describe a prototypical REX element that is necessary and sufficient to confer extreme-distance gene activation by remote enhancers.
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Affiliation(s)
- Grace Bower
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92967, USA
| | - Ethan W. Hollingsworth
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92967, USA
- Medical Scientist Training Program, University of California, Irvine, CA 92967, USA
| | - Sandra Jacinto
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92967, USA
| | - Benjamin Clock
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92967, USA
| | - Kaitlyn Cao
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92967, USA
| | - Mandy Liu
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92967, USA
| | - Adam Dziulko
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Ana Alcaina-Caro
- Centro Andaluz de Biología del Desarrollo (CABD), CSIC-Universidad Pablo de Olavide-Junta de Andalucía, Seville, 41013, Spain
| | - Qianlan Xu
- Department of Physiology and Biophysics, Department of Ophthalmology, Center for Translational Vision Research, School of Medicine, University of California, Irvine, CA, USA
| | - Dorota Skowronska-Krawczyk
- Department of Physiology and Biophysics, Department of Ophthalmology, Center for Translational Vision Research, School of Medicine, University of California, Irvine, CA, USA
| | - Javier Lopez-Rios
- Centro Andaluz de Biología del Desarrollo (CABD), CSIC-Universidad Pablo de Olavide-Junta de Andalucía, Seville, 41013, Spain
| | - Diane E. Dickel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Anaïs F. Bardet
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Université de Strasbourg, CNRS UMR7104, INSERM U1258, 67400 Illkirch, France
| | - Len A. Pennacchio
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- U.S. Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA
- Comparative Biochemistry Program, University of California, Berkeley, CA 94720, USA
| | - Axel Visel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
- U.S. Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA
- School of Natural Sciences, University of California, Merced, CA 95343, USA
| | - Evgeny Z. Kvon
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92967, USA
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97
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Zhao Y, Ansarullah, Kumar P, Mahoney JM, He H, Baker C, George J, Li S. Causal network perturbation analysis identifies known and novel type-2 diabetes driver genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.22.595431. [PMID: 38826370 PMCID: PMC11142180 DOI: 10.1101/2024.05.22.595431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
The molecular pathogenesis of diabetes is multifactorial, involving genetic predisposition and environmental factors that are not yet fully understood. However, pancreatic β-cell failure remains among the primary reasons underlying the progression of type-2 diabetes (T2D) making targeting β-cell dysfunction an attractive pathway for diabetes treatment. To identify genetic contributors to β-cell dysfunction, we investigated single-cell gene expression changes in β-cells from healthy (C57BL/6J) and diabetic (NZO/HlLtJ) mice fed with normal or high-fat, high-sugar diet (HFHS). Our study presents an innovative integration of the causal network perturbation assessment (ssNPA) framework with meta-cell transcriptome analysis to explore the genetic underpinnings of type-2 diabetes (T2D). By generating a reference causal network and in silico perturbation, we identified novel genes implicated in T2D and validated our candidates using the Knockout Mouse Phenotyping (KOMP) Project database.
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Affiliation(s)
- Yue Zhao
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Ansarullah
- Center for Biometric Analysis, The Jackson Laboratory, Bar Harbor, ME, USA
| | - Parveen Kumar
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | | | - Hao He
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Candice Baker
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Joshy George
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
| | - Sheng Li
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA
- Department of Genetics and Genome Sciences, University of Connecticut School of Medicine, Farmington, CT, USA
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98
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Dorans E, Jagadeesh K, Dey K, Price AL. Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.24.24307813. [PMID: 38826240 PMCID: PMC11142273 DOI: 10.1101/2024.05.24.24307813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Methods that analyze single-cell paired RNA-seq and ATAC-seq multiome data have shown great promise in linking regulatory elements to genes. However, existing methods differ in their modeling assumptions and approaches to account for biological and technical noise-leading to low concordance in their linking scores-and do not capture the effects of genomic distance. We propose pgBoost, an integrative modeling framework that trains a non-linear combination of existing linking strategies (including genomic distance) on fine-mapped eQTL data to assign a probabilistic score to each candidate SNP-gene link. We applied pgBoost to single-cell multiome data from 85k cells representing 6 major immune/blood cell types. pgBoost attained higher enrichment for fine-mapped eSNP-eGene pairs (e.g. 21x at distance >10kb) than existing methods (1.2-10x; p-value for difference = 5e-13 vs. distance-based method and < 4e-35 for each other method), with larger improvements at larger distances (e.g. 35x vs. 0.89-6.6x at distance >100kb; p-value for difference < 0.002 vs. each other method). pgBoost also outperformed existing methods in enrichment for CRISPR-validated links (e.g. 4.8x vs. 1.6-4.1x at distance >10kb; p-value for difference = 0.25 vs. distance-based method and < 2e-5 for each other method), with larger improvements at larger distances (e.g. 15x vs. 1.6-2.5x at distance >100kb; p-value for difference < 0.009 for each other method). Similar improvements in enrichment were observed for links derived from Activity-By-Contact (ABC) scores and GWAS data. We further determined that restricting pgBoost to features from a focal cell type improved the identification of SNP-gene links relevant to that cell type. We highlight several examples where pgBoost linked fine-mapped GWAS variants to experimentally validated or biologically plausible target genes that were not implicated by other methods. In conclusion, a non-linear combination of linking strategies, including genomic distance, improves power to identify target genes underlying GWAS associations.
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99
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Li G, Liu Y, Feng X, Diao S, Zhong Z, Li B, Teng J, Zhang W, Zeng H, Cai X, Gao Y, Liu X, Yuan X, Li J, Zhang Z. Integrating Multiple Database Resources to Elucidate the Gene Flow in Southeast Asian Pig Populations. Int J Mol Sci 2024; 25:5689. [PMID: 38891877 PMCID: PMC11171535 DOI: 10.3390/ijms25115689] [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: 04/17/2024] [Revised: 05/16/2024] [Accepted: 05/18/2024] [Indexed: 06/21/2024] Open
Abstract
The domestic pig (Sus scrofa) and its subfamilies have experienced long-term and extensive gene flow, particularly in Southeast Asia. Here, we analyzed 236 pigs, focusing on Yunnan indigenous, European commercial, East Asian, and Southeast Asian breeds, using the Pig Genomics Reference Panel (PGRP v1) of Pig Genotype-Tissue Expression (PigGTEx) to investigate gene flow and associated complex traits by integrating multiple database resources. In this study, we discovered evidence of admixtures from European pigs into the genome of Yunnan indigenous pigs. Additionally, we hypothesized that a potential conceptual gene flow route that may have contributed to the genetic composition of the Diannan small-ear pig is a gene exchange from the Vietnamese pig. Based on the most stringent gene introgression scan using the fd statistic, we identified three specific loci on chromosome 8, ranging from 51.65 to 52.45 Mb, which exhibited strong signatures of selection and harbored the NAF1, NPY1R, and NPY5R genes. These genes are associated with complex traits, such as fat mass, immunity, and litter weight, in pigs, as supported by multiple bio-functionalization databases. We utilized multiple databases to explore the potential dynamics of genetic exchange in Southeast Asian pig populations and elucidated specific gene functionalities.
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Affiliation(s)
- Guangzhen Li
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Yuqiang Liu
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Xueyan Feng
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Shuqi Diao
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Zhanming Zhong
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Bolang Li
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Jinyan Teng
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Wenjing Zhang
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Haonan Zeng
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Xiaodian Cai
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Yahui Gao
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Xiaohong Liu
- State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China;
| | - Xiaolong Yuan
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Jiaqi Li
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
| | - Zhe Zhang
- National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou 510642, China; (G.L.); (Y.L.); (X.F.); (S.D.); (Z.Z.); (B.L.); (J.T.); (W.Z.); (H.Z.); (X.C.); (Y.G.); (X.Y.)
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100
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Dillard LJ, Calabrese GM, Mesner LD, Farber CR. Cell type-specific network analysis in Diversity Outbred mice identifies genes potentially responsible for human bone mineral density GWAS associations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.20.594981. [PMID: 38826475 PMCID: PMC11142079 DOI: 10.1101/2024.05.20.594981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Genome-wide association studies (GWASs) have identified many sources of genetic variation associated with bone mineral density (BMD), a clinical predictor of fracture risk and osteoporosis. Aside from the identification of causal genes, other difficult challenges to informing GWAS include characterizing the roles of predicted causal genes in disease and providing additional functional context, such as the cell type predictions or biological pathways in which causal genes operate. Leveraging single-cell transcriptomics (scRNA-seq) can assist in informing BMD GWAS by linking disease-associated variants to genes and providing a cell type context for which these causal genes drive disease. Here, we use large-scale scRNA-seq data from bone marrow-derived stromal cells cultured under osteogenic conditions (BMSC-OBs) from Diversity Outbred (DO) mice to generate cell type-specific networks and contextualize BMD GWAS-implicated genes. Using trajectories inferred from the scRNA-seq data, we identify networks enriched with genes that exhibit the most dynamic changes in expression across trajectories. We discover 21 network driver genes, which are likely to be causal for human BMD GWAS associations that colocalize with expression/splicing quantitative trait loci (eQTL/sQTL). These driver genes, including Fgfrl1 and Tpx2, along with their associated networks, are predicted to be novel regulators of BMD via their roles in the differentiation of mesenchymal lineage cells. In this work, we showcase the use of single-cell transcriptomics from mouse bone-relevant cells to inform human BMD GWAS and prioritize genetic targets with potential causal roles in the development of osteoporosis.
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Affiliation(s)
- Luke J Dillard
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908
| | - Gina M Calabrese
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908
| | - Larry D Mesner
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22908
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22908
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22908
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