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Kanzi AM, San JE, Chimukangara B, Wilkinson E, Fish M, Ramsuran V, de Oliveira T. Next Generation Sequencing and Bioinformatics Analysis of Family Genetic Inheritance. Front Genet 2020; 11:544162. [PMID: 33193618 PMCID: PMC7649788 DOI: 10.3389/fgene.2020.544162] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Accepted: 09/21/2020] [Indexed: 12/29/2022] Open
Abstract
Mendelian and complex genetic trait diseases continue to burden and affect society both socially and economically. The lack of effective tests has hampered diagnosis thus, the affected lack proper prognosis. Mendelian diseases are caused by genetic mutations in a singular gene while complex trait diseases are caused by the accumulation of mutations in either linked or unlinked genomic regions. Significant advances have been made in identifying novel diseases associated mutations especially with the introduction of next generation and third generation sequencing. Regardless, some diseases are still without diagnosis as most tests rely on SNP genotyping panels developed from population based genetic analyses. Analysis of family genetic inheritance using whole genomes, whole exomes or a panel of genes has been shown to be effective in identifying disease-causing mutations. In this review, we discuss next generation and third generation sequencing platforms, bioinformatic tools and genetic resources commonly used to analyze family based genomic data with a focus on identifying inherited or novel disease-causing mutations. Additionally, we also highlight the analytical, ethical and regulatory challenges associated with analyzing personal genomes which constitute the data used for family genetic inheritance.
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Affiliation(s)
- Aquillah M. Kanzi
- Kwazulu-Natal Research and Innovation Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
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Ohnmacht J, May P, Sinkkonen L, Krüger R. Missing heritability in Parkinson's disease: the emerging role of non-coding genetic variation. J Neural Transm (Vienna) 2020; 127:729-748. [PMID: 32248367 PMCID: PMC7242266 DOI: 10.1007/s00702-020-02184-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 03/24/2020] [Indexed: 02/01/2023]
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder caused by a complex interplay of genetic and environmental factors. For the stratification of PD patients and the development of advanced clinical trials, including causative treatments, a better understanding of the underlying genetic architecture of PD is required. Despite substantial efforts, genome-wide association studies have not been able to explain most of the observed heritability. The majority of PD-associated genetic variants are located in non-coding regions of the genome. A systematic assessment of their functional role is hampered by our incomplete understanding of genotype-phenotype correlations, for example through differential regulation of gene expression. Here, the recent progress and remaining challenges for the elucidation of the role of non-coding genetic variants is reviewed with a focus on PD as a complex disease with multifactorial origins. The function of gene regulatory elements and the impact of non-coding variants on them, and the means to map these elements on a genome-wide level, will be delineated. Moreover, examples of how the integration of functional genomic annotations can serve to identify disease-associated pathways and to prioritize disease- and cell type-specific regulatory variants will be given. Finally, strategies for functional validation and considerations for suitable model systems are outlined. Together this emphasizes the contribution of rare and common genetic variants to the complex pathogenesis of PD and points to remaining challenges for the dissection of genetic complexity that may allow for better stratification, improved diagnostics and more targeted treatments for PD in the future.
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Affiliation(s)
- Jochen Ohnmacht
- LCSB, University of Luxembourg, Belvaux, Luxembourg
- Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg
| | - Patrick May
- LCSB, University of Luxembourg, Belvaux, Luxembourg
| | - Lasse Sinkkonen
- Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg
| | - Rejko Krüger
- LCSB, University of Luxembourg, Belvaux, Luxembourg.
- Luxembourg Institute of Health (LIH), Transversal Translational Medicine, Strassen, Luxembourg.
- Parkinson Research Clinic, Centre Hospitalier de Luxembourg (CHL), Luxembourg, Luxembourg.
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Wang Y, Liyanarachchi S, Miller KE, Nieminen TT, Comiskey DF, Li W, Brock P, Symer DE, Akagi K, DeLap KE, He H, Koboldt DC, de la Chapelle A. Identification of Rare Variants Predisposing to Thyroid Cancer. Thyroid 2019; 29:946-955. [PMID: 30957677 PMCID: PMC6648188 DOI: 10.1089/thy.2018.0736] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background: Familial non-medullary thyroid cancer (NMTC) accounts for a relatively small proportion of thyroid cancer cases, but it displays strong genetic predisposition. So far, only a few NMTC susceptible genes and low-penetrance variants contributing to NMTC have been described. This study aimed to identify rare germline variants that may predispose individuals to NMTC by sequencing a cohort of 17 NMTC families. Methods: Whole-genome sequencing and genome-wide linkage analysis were performed in 17 NMTC families. MendelScan and BasePlayer were applied to screen germline variants followed by customized filtering. The remaining candidate variants were subsequently validated by Sanger sequencing. A panel of 277 known cancer predisposition genes was also screened in these families. Results: A total of 41 rare coding candidate variants in 40 genes identified by whole-genome sequencing are reported, including 24 missense, five frameshift, five splice change, and seven nonsense variants. Sanger sequencing confirmed all 41 rare variants and proved their co-segregation with NMTC in the extended pedigrees. In silico functional analysis of the candidate genes using Ingenuity Pathway Analysis showed that cancer was the top category of "Diseases and Disorders." Additionally, a targeted search displayed six variants in known cancer predisposition genes, including one frameshift variant and five missense variants. Conclusions: The data identify rare germline variants that may play important roles in NMTC predisposition. It is proposed that in future research including functional characterization, these variants and genes be considered primary candidates for thyroid cancer predisposition.
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Affiliation(s)
- Yanqiang Wang
- Human Cancer Genetics Program and Department of Cancer Biology and Genetics, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Sandya Liyanarachchi
- Human Cancer Genetics Program and Department of Cancer Biology and Genetics, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Katherine E. Miller
- Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio
| | - Taina T. Nieminen
- Human Cancer Genetics Program and Department of Cancer Biology and Genetics, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Daniel F. Comiskey
- Human Cancer Genetics Program and Department of Cancer Biology and Genetics, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Wei Li
- Human Cancer Genetics Program and Department of Cancer Biology and Genetics, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Pamela Brock
- Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - David E. Symer
- Department of Lymphoma and Myeloma, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Keiko Akagi
- Department of Thoracic/Head and Neck Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Katherine E. DeLap
- Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Huiling He
- Human Cancer Genetics Program and Department of Cancer Biology and Genetics, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
| | - Daniel C. Koboldt
- Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, Ohio
| | - Albert de la Chapelle
- Human Cancer Genetics Program and Department of Cancer Biology and Genetics, The Ohio State University Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio
- Address correspondence to: Albert de la Chapelle, MD, PhD, Human Cancer Genetics Program, Comprehensive Cancer Center, The Ohio State University, 804 Biomedical Research Tower, 460 W. 12th Avenue, Columbus, OH 43210
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Rhoades R, Jackson F, Teng S. Discovery of rare variants implicated in schizophrenia using next-generation sequencing. JOURNAL OF TRANSLATIONAL GENETICS AND GENOMICS 2019; 3:1-20. [PMID: 33981965 PMCID: PMC8112455 DOI: 10.20517/jtgg.2018.26] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
Schizophrenia is a highly heritable psychiatric disorder that affects 1% of the population. Genome-wide association studies have identified common variants in candidate genes associated with schizophrenia, but the genetics mechanisms of this disorder have not yet been elucidated. The discovery of rare genetic variants that contribute to schizophrenia symptoms promises to help explain the missing heritability of the disease. Next generation sequencing techniques are revolutionizing the field of psychiatric genetics. Various statistical approaches have been developed for rare variant association testing in case-control and family studies. Targeted resequencing, whole exome sequencing and whole genome sequencing combined with these computational tools are used for the discovery of rare genetic variations in schizophrenia. The findings provide useful information for characterizing the rare mutations and elucidating the genetic mechanisms by which the variants cause schizophrenia.
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Affiliation(s)
- Raina Rhoades
- Department of Biology, Howard University, Washington, DC 20059, USA
| | - Fatimah Jackson
- Department of Biology, Howard University, Washington, DC 20059, USA
| | - Shaolei Teng
- Department of Biology, Howard University, Washington, DC 20059, USA
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Kinay D, Oliver KL, Tüzün E, Damiano JA, Ulusoy C, Andermann E, Hildebrand MS, Bahlo M, Berkovic SF. Evidence of linkage to chromosome 5p13.2-q11.1 in a large inbred family with genetic generalized epilepsy. Epilepsia 2018; 59:e125-e129. [DOI: 10.1111/epi.14506] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/06/2018] [Indexed: 12/16/2022]
Affiliation(s)
- Demet Kinay
- Okmeydani Education and Research Hospital; Istanbul Turkey
| | - Karen L. Oliver
- Epilepsy Research Centre; Austin Health; University of Melbourne; Heidelberg Victoria Australia
- Population Health and Immunity Division; Walter and Eliza Hall Institute of Medical Research; Parkville Victoria Australia
| | - Erdem Tüzün
- Department of Neuroscience; Aziz Sancar Institute of Experimental Medicine; Istanbul University; Istanbul Turkey
| | - John A. Damiano
- Epilepsy Research Centre; Austin Health; University of Melbourne; Heidelberg Victoria Australia
| | - Canan Ulusoy
- Department of Neuroscience; Aziz Sancar Institute of Experimental Medicine; Istanbul University; Istanbul Turkey
| | - Eva Andermann
- Neurogenetics Unit; Montreal Neurological Hospital and Institute; Montreal Quebec Canada
| | - Michael S. Hildebrand
- Epilepsy Research Centre; Austin Health; University of Melbourne; Heidelberg Victoria Australia
| | - Melanie Bahlo
- Population Health and Immunity Division; Walter and Eliza Hall Institute of Medical Research; Parkville Victoria Australia
- Department of Medical Biology; University of Melbourne; Parkville Victoria Australia
| | - Samuel F. Berkovic
- Epilepsy Research Centre; Austin Health; University of Melbourne; Heidelberg Victoria Australia
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Nikkola E, Ko A, Alvarez M, Cantor RM, Garske K, Kim E, Gee S, Rodriguez A, Muxel R, Matikainen N, Söderlund S, Motazacker MM, Borén J, Lamina C, Kronenberg F, Schneider WJ, Palotie A, Laakso M, Taskinen MR, Pajukanta P. Family-specific aggregation of lipid GWAS variants confers the susceptibility to familial hypercholesterolemia in a large Austrian family. Atherosclerosis 2017; 264:58-66. [PMID: 28772107 DOI: 10.1016/j.atherosclerosis.2017.07.024] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Revised: 06/27/2017] [Accepted: 07/21/2017] [Indexed: 01/01/2023]
Abstract
BACKGROUND AND AIMS Hypercholesterolemia confers susceptibility to cardiovascular disease (CVD). Both serum total cholesterol (TC) and LDL-cholesterol (LDL-C) exhibit a strong genetic component (heritability estimates 0.41-0.50). However, a large part of this heritability cannot be explained by the variants identified in recent extensive genome-wide association studies (GWAS) on lipids. Our aim was to find genetic causes leading to high LDL-C levels and ultimately CVD in a large Austrian family presenting with what appears to be autosomal dominant inheritance for familial hypercholesterolemia (FH). METHODS We utilized linkage analysis followed by whole-exome sequencing and genetic risk score analysis using an Austrian multi-generational family with various dyslipidemias, including elevated TC and LDL-C, and one family branch with elevated lipoprotein (a) (Lp(a)). RESULTS We did not find evidence for genome-wide significant linkage for LDL-C or apparent causative variants in the known FH genes rather, we discovered a particular family-specific combination of nine GWAS LDL-C SNPs (p = 0.02 by permutation), and putative less severe familial hypercholesterolemia mutations in the LDLR and APOB genes in a subset of the affected family members. Separately, high Lp(a) levels observed in one branch of the family were explained primarily by the LPA locus, including short (<23) Kringle IV repeats and rs3798220. CONCLUSIONS Taken together, some forms of FH may be explained by family-specific combinations of LDL-C GWAS SNPs.
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Affiliation(s)
- Elina Nikkola
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Arthur Ko
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA; Molecular Biology Institute at UCLA, Los Angeles, USA
| | - Marcus Alvarez
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Rita M Cantor
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Kristina Garske
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Elliot Kim
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Stephanie Gee
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Alejandra Rodriguez
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | | | - Niina Matikainen
- Endocrinology, Abdominal Centre, Helsinki University Hospital, Finland; Heart and Lung Center, Helsinki University Hospital, Finland; Research Programs Unit, Diabetes and Obesity, University of Helsinki, Finland
| | - Sanni Söderlund
- Heart and Lung Center, Helsinki University Hospital, Finland; Research Programs Unit, Diabetes and Obesity, University of Helsinki, Finland
| | - Mahdi M Motazacker
- Department of Clinical Genetics, Academic Medical Center at the University of Amsterdam, The Netherlands
| | - Jan Borén
- Department of Molecular and Clinical Medicine/Wallenberg Laboratory, University of Gothenburg and Sahlgrenska University Hospital, Sweden
| | - Claudia Lamina
- Division of Genetic Epidemiology, Medical University of Innsbruck, Austria
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Medical University of Innsbruck, Austria
| | - Wolfgang J Schneider
- Department Medical Biochemistry, Medical University Vienna and Max F. Perutz Laboratories, Austria
| | - Aarno Palotie
- Institute for Molecular Medicine, University of Helsinki, Finland; The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Massachusetts General Hospital, Boston, MA, USA
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Marja-Riitta Taskinen
- Heart and Lung Center, Helsinki University Hospital, Finland; Research Programs Unit, Diabetes and Obesity, University of Helsinki, Finland
| | - Päivi Pajukanta
- Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA; Molecular Biology Institute at UCLA, Los Angeles, USA; Bioinformatics Interdepartmental Program, UCLA, Los Angeles, CA, USA.
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Tokutomi T, Fukushima A, Yamamoto K, Bansho Y, Hachiya T, Shimizu A. f-treeGC: a questionnaire-based family tree-creation software for genetic counseling and genome cohort studies. BMC MEDICAL GENETICS 2017; 18:71. [PMID: 28705149 PMCID: PMC5512935 DOI: 10.1186/s12881-017-0433-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 06/27/2017] [Indexed: 11/10/2022]
Abstract
BACKGROUND The Tohoku Medical Megabank project aims to create a next-generation personalized healthcare system by conducting large-scale genome-cohort studies involving three generations of local residents in the areas affected by the Great East Japan Earthquake. We collected medical and genomic information for developing a biobank to be used for this healthcare system. We designed a questionnaire-based pedigree-creation software program named "f-treeGC," which enables even less experienced medical practitioners to accurately and rapidly collect family health history and create pedigree charts. RESULTS f-treeGC may be run on Adobe AIR. Pedigree charts are created in the following manner: 1) At system startup, the client is prompted to provide required information on the presence or absence of children; f-treeGC is capable of creating a pedigree up to three generations. 2) An interviewer fills out a multiple-choice questionnaire on genealogical information. 3) The information requested includes name, age, gender, general status, infertility status, pregnancy status, fetal status, and physical features or health conditions of individuals over three generations. In addition, information regarding the client and the proband, and birth order information, including multiple gestation, custody, multiple individuals, donor or surrogate, adoption, and consanguinity may be included. 4) f-treeGC shows only marriages between first cousins via the overlay function. 5) f-treeGC automatically creates a pedigree chart, and the chart-creation process is visible for inspection on the screen in real time. 6) The genealogical data may be saved as a file in the original format. The created/modified date and time may be changed as required, and the file may be password-protected and/or saved in read-only format. To enable sorting or searching from the database, the file name automatically contains the terms typed into the entry fields, including physical features or health conditions, by default. 7) Alternatively, family histories are collected using a completed foldable interview paper sheet named "f-sheet", which is identical to the questionnaire in f-treeGC. CONCLUSIONS We developed a questionnaire-based family tree-creation software, named f-treeGC, which is fully compliant with international recommendations for standardized human pedigree nomenclature. The present software simplifies the process of collecting family histories and pedigrees, and has a variety of uses, from genome cohort studies or primary care to genetic counseling.
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Affiliation(s)
- Tomoharu Tokutomi
- Department of Clinical Genetics, School of Medicine, Iwate Medical University, Morioka, Iwate, 020-8505, Japan.,Division of Innovation and Education, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa, Iwate, 028-3694, Japan
| | - Akimune Fukushima
- Department of Clinical Genetics, School of Medicine, Iwate Medical University, Morioka, Iwate, 020-8505, Japan. .,Division of Innovation and Education, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa, Iwate, 028-3694, Japan.
| | - Kayono Yamamoto
- Department of Clinical Genetics, School of Medicine, Iwate Medical University, Morioka, Iwate, 020-8505, Japan.,Division of Innovation and Education, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa, Iwate, 028-3694, Japan
| | | | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa, Iwate, 028-3694, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa, Iwate, 028-3694, Japan
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Abstract
PURPOSE OF REVIEW Recent international expert consensus statements have updated the clinical and genetic diagnoses of patients suffering from arrhythmogenic diseases. However, a lack of genotype-phenotype correlations has hampered the development of a risk stratification scale for sudden cardiac death. RECENT FINDINGS The improvement in the field of genetics has prompted the discovery of new genes associated with sudden cardiac death. Sudden cardiac death is a socially devastating event, especially when it occurs in the pediatric population. Physical activity can often trigger the arrhythmia and sudden death may be the first symptom. These inherited cardiac diseases may be difficult to diagnose, leaving family members also at risk. Thanks to the development of new high-throughput technologies, genetics may be used in the diagnosis of these diseases and even cases that remain unexplained after a comprehensive autopsy. Genetic testing cannot only identify the causative genetic variant in the index case, but it enables the detection of relatives at risk of sudden death, despite remaining clinically asymptomatic. SUMMARY We review the recent advances in the genetics of inherited arrhythmias associated with sudden cardiac death. We focus on the pediatric population, the main group of people suffering from lethal inherited arrhythmias.
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Karchin R, Cline MS. Human genetics special issue on computational molecular medicine. Hum Genet 2015; 134:455-7. [PMID: 25805167 DOI: 10.1007/s00439-015-1545-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Rachel Karchin
- Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, USA,
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