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Radhakrishnan A, Kuppusamy G, Ponnusankar S, Mutalik S. Towards next-generation personalization of tacrolimus treatment: a review on advanced diagnostic and therapeutic approaches. Pharmacogenomics 2021; 22:1151-1175. [PMID: 34719935 DOI: 10.2217/pgs-2021-0008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The benefit of personalized medicine is that it allows the customization of drug therapy - maximizing efficacy while avoiding side effects. Genetic polymorphisms are one of the major contributors to interindividual variability. Currently, the only gold standard for applying personalized medicine is dose titration. Because of technological advancements, converting genotypic data into an optimum dose has become easier than in earlier years. However, for many medications, determining a personalized dose may be difficult, leading to a trial-and-error method. On the other hand, the technologically oriented pharmaceutical industry has a plethora of smart drug delivery methods that are underutilized in customized medicine. This article elaborates the genetic polymorphisms of tacrolimus as case study, and extensively covers the diagnostic and therapeutic technologies which aid in the delivery of personalized tacrolimus treatment for better clinical outcomes, thereby providing a new strategy for implementing personalized medicine.
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Affiliation(s)
- Arun Radhakrishnan
- Department of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education & Research, Ooty, Nilgiris, Tamilnadu, India
| | - Gowthamarajan Kuppusamy
- Department of Pharmaceutics, JSS College of Pharmacy, JSS Academy of Higher Education & Research, Ooty, Nilgiris, Tamilnadu, India
| | - Sivasankaran Ponnusankar
- Department of Pharmacy Practice, JSS College of Pharmacy, JSS Academy of Higher Education & Research, Ooty, Nilgiris, Tamilnadu, India
| | - Srinivas Mutalik
- Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Karnataka, India
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2
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Hariharan R, Mousa A, de Courten B. Influence of AMY1A copy number variations on obesity and other cardiometabolic risk factors: A review of the evidence. Obes Rev 2021; 22:e13205. [PMID: 33432778 DOI: 10.1111/obr.13205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 12/15/2020] [Accepted: 12/16/2020] [Indexed: 12/01/2022]
Abstract
The rising incidence of obesity and type 2 diabetes is contributing to the escalating burden of disease globally. These metabolic disorders are closely linked with diet and in particular with carbohydrate consumption; hence, it is important to understand the underlying mechanisms that influence carbohydrate metabolism. Amylase, the enzyme responsible for the digestion of starch, is coded by the genes AMY1A, AMY1B, and AMY1C (salivary amylase) and AMY2A and AMY2B (pancreatic amylase). Previous studies demonstrate wide variations in AMY1A copy numbers, which can be attributed to several genetic, nutritional, and geographical diversities seen in populations globally. Current literature suggests that AMY1A copy number variations are important in obesity and other cardiometabolic disorders through their effects on glucose and lipid homeostasis, inflammatory markers, and the gut microbiome. This review synthesizes the available evidence to improve understanding of the role of AMY1A in obesity and related cardiometabolic risk factors and disorders including insulin resistance and type 2 diabetes, cardiovascular risk and inflammation, and the gut microbiome.
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Affiliation(s)
- Rohit Hariharan
- Department of Medicine, School of Clinical Sciences, Monash University, Clayton, Australia
| | - Aya Mousa
- Monash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Monash University, Clayton, Australia
| | - Barbora de Courten
- Department of Medicine, School of Clinical Sciences, Monash University, Clayton, Australia
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3
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Jamaluddin J, Mohd Khair NK, Vinodamaney SD, Othman Z, Abubakar S. Copy number variation of CCL3L1 among three major ethnic groups in Malaysia. BMC Genet 2020; 21:1. [PMID: 31900126 PMCID: PMC6942282 DOI: 10.1186/s12863-019-0803-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2018] [Accepted: 12/17/2019] [Indexed: 11/30/2022] Open
Abstract
Background C-C motif Chemokine Ligand 3 Like 1 (CCL3L1) is a multiallelic copy number variable, which plays a crucial role in immunoregulatory and hosts defense through the production of macrophage inflammatory protein (MIP)-1α. Variable range of the CCL3L1 copies from 0 to 14 copies have been documented in several different populations. However, there is still lack of report on the range of CCL3L1 copy number exclusively among Malaysians who are a multi-ethnic population. Thus, this study aims to extensively examine the distribution of CCL3L1 copy number in the three major populations from Malaysia namely Malay, Chinese and Indian. A diploid copy number of CCL3L1 for 393 Malaysians (Malay = 178, Indian = 90, and Chinese = 125) was quantified using Paralogue Ratio Tests (PRTs) and then validated with microsatellites analysis. Results To our knowledge, this is the first report on the CCL3L1 copy number that has been attempted among Malaysians and the Chinese ethnic group exhibits a diverse pattern of CCL3L1 distribution copy number from the Malay and Indian (p < 0.0001). The CCL3L1 ranged from 0 to 8 copies for both the Malay and Indian ethnic groups while 0 to 10 copies for the Chinese ethnic. Consequently, the CCL3L1 copy number among major ethnic groups in the Malaysian population is found to be significantly varied when compared to the European population (p < 0.0001). The mean/median reported for the Malay, Chinese, Indian, and European are 2.759/2.869, 3.453/3.290, 2.437/1.970 and 2.001/1.940 respectively. Conclusion This study reveals the existence of genetic variation of CCL3L1 in the Malaysian population, and suggests by examining genetic diversity on the ethnicity, and specific geographical region could help in reconstructing human evolutionary history and for the prediction of disease risk related to the CCL3L1 copy number.
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Affiliation(s)
- Jalilah Jamaluddin
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, UPM, 43400, Serdang, Selangor, Malaysia
| | - Nur Khairina Mohd Khair
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, UPM, 43400, Serdang, Selangor, Malaysia
| | - Shameni Devi Vinodamaney
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, UPM, 43400, Serdang, Selangor, Malaysia
| | - Zulkefley Othman
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, UPM, 43400, Serdang, Selangor, Malaysia
| | - Suhaili Abubakar
- Department of Biomedical Science, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, UPM, 43400, Serdang, Selangor, Malaysia.
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Deng L, Lou H, Zhang X, Thiruvahindrapuram B, Lu D, Marshall CR, Liu C, Xie B, Xu W, Wong LP, Yew CW, Farhang A, Ong RTH, Hoque MZ, Thuhairah AR, Jong B, Phipps ME, Scherer SW, Teo YY, Kumar SV, Hoh BP, Xu S. Analysis of five deep-sequenced trio-genomes of the Peninsular Malaysia Orang Asli and North Borneo populations. BMC Genomics 2019; 20:842. [PMID: 31718558 PMCID: PMC6852992 DOI: 10.1186/s12864-019-6226-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 10/25/2019] [Indexed: 12/18/2022] Open
Abstract
Background Recent advances in genomic technologies have facilitated genome-wide investigation of human genetic variations. However, most efforts have focused on the major populations, yet trio genomes of indigenous populations from Southeast Asia have been under-investigated. Results We analyzed the whole-genome deep sequencing data (~ 30×) of five native trios from Peninsular Malaysia and North Borneo, and characterized the genomic variants, including single nucleotide variants (SNVs), small insertions and deletions (indels) and copy number variants (CNVs). We discovered approximately 6.9 million SNVs, 1.2 million indels, and 9000 CNVs in the 15 samples, of which 2.7% SNVs, 2.3% indels and 22% CNVs were novel, implying the insufficient coverage of population diversity in existing databases. We identified a higher proportion of novel variants in the Orang Asli (OA) samples, i.e., the indigenous people from Peninsular Malaysia, than that of the North Bornean (NB) samples, likely due to more complex demographic history and long-time isolation of the OA groups. We used the pedigree information to identify de novo variants and estimated the autosomal mutation rates to be 0.81 × 10− 8 – 1.33 × 10− 8, 1.0 × 10− 9 – 2.9 × 10− 9, and ~ 0.001 per site per generation for SNVs, indels, and CNVs, respectively. The trio-genomes also allowed for haplotype phasing with high accuracy, which serves as references to the future genomic studies of OA and NB populations. In addition, high-frequency inherited CNVs specific to OA or NB were identified. One example is a 50-kb duplication in DEFA1B detected only in the Negrito trios, implying plausible effects on host defense against the exposure of diverse microbial in tropical rainforest environment of these hunter-gatherers. The CNVs shared between OA and NB groups were much fewer than those specific to each group. Nevertheless, we identified a 142-kb duplication in AMY1A in all the 15 samples, and this gene is associated with the high-starch diet. Moreover, novel insertions shared with archaic hominids were identified in our samples. Conclusion Our study presents a full catalogue of the genome variants of the native Malaysian populations, which is a complement of the genome diversity in Southeast Asians. It implies specific population history of the native inhabitants, and demonstrated the necessity of more genome sequencing efforts on the multi-ethnic native groups of Malaysia and Southeast Asia.
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Affiliation(s)
- Lian Deng
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Haiyi Lou
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Xiaoxi Zhang
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | | | - Dongsheng Lu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Christian R Marshall
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada.,Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.,Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Chang Liu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Bo Xie
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wanxing Xu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Lai-Ping Wong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore
| | - Chee-Wei Yew
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia
| | - Aghakhanian Farhang
- Jefrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, Jalan Lagoon Selatan, Sunway, 46150, Subang Jaya, Selangor, Malaysia.,Tropical Medicine and Biology Platform, Monash University Malaysia, Jalan Lagoon Selatan, 46150 Sunway, Subang Jaya, Selangor, Malaysia
| | - Rick Twee-Hee Ong
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore
| | - Mohammad Zahirul Hoque
- Faculty of Medicine and Health Sciences, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia
| | - Abdul Rahman Thuhairah
- Clinical Pathology Diagnostic Centre Research Laboratory, Faculty of Medicine, Universiti Teknologi MARA, Sungai Buloh Campus, 47000 Sg Buloh, Subang Jaya, Selangor, Malaysia
| | - Bhak Jong
- Personal Genomics Institute, Genome Research Foundation, Suwon, Republic of Korea.,Geromics, Ulsan, 44919, Republic of Korea.,Biomedical Engineering Department, The Genomics Institute, UNIST, Ulsan, Republic of Korea
| | - Maude E Phipps
- Tropical Medicine and Biology Platform, Monash University Malaysia, Jalan Lagoon Selatan, 46150 Sunway, Subang Jaya, Selangor, Malaysia
| | - Stephen W Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada.,Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada.,Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.,Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore.,NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, 117456, Singapore.,Life Sciences Institute, National University of Singapore, Singapore, Singapore.,Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore.,Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, 138672, Singapore
| | - Subbiah Vijay Kumar
- Biotechnology Research Institute, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.
| | - Boon-Peng Hoh
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,Faculty of Medicine and Health Sciences, UCSI University, Jalan Menara Gading, Taman Connaught, Cheras, 56000, Kuala Lumpur, Malaysia.
| | - Shuhua Xu
- Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. .,School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China. .,Collaborative Innovation Center of Genetics and Development, Shanghai, 200438, China. .,Human Phenome Institute, Fudan University, Shanghai, 201203, China.
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Nagelkerke SQ, Schmidt DE, de Haas M, Kuijpers TW. Genetic Variation in Low-To-Medium-Affinity Fcγ Receptors: Functional Consequences, Disease Associations, and Opportunities for Personalized Medicine. Front Immunol 2019; 10:2237. [PMID: 31632391 PMCID: PMC6786274 DOI: 10.3389/fimmu.2019.02237] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 09/04/2019] [Indexed: 12/23/2022] Open
Abstract
Fc-gamma receptors (FcγR) are the cellular receptors for Immunoglobulin G (IgG). Upon binding of complexed IgG, FcγRs can trigger various cellular immune effector functions, thereby linking the adaptive and innate immune systems. In humans, six classic FcγRs are known: one high-affinity receptor (FcγRI) and five low-to-medium-affinity FcγRs (FcγRIIA, -B and -C, FcγRIIIA and -B). In this review we describe the five genes encoding the low-to-medium -affinity FcγRs (FCGR2A, FCGR2B, FCGR2C, FCGR3A, and FCGR3B), including well-characterized functionally relevant single nucleotide polymorphisms (SNPs), haplotypes as well as copy number variants (CNVs), which occur in distinct copy number regions across the locus. The evolution of the locus is also discussed. Importantly, we recommend a consistent nomenclature of genetic variants in the FCGR2/3 locus. Next, we focus on the relevance of genetic variation in the FCGR2/3 locus in auto-immune and auto-inflammatory diseases, highlighting pathophysiological insights that are informed by genetic association studies. Finally, we illustrate how specific FcγR variants relate to variation in treatment responses and prognosis amongst autoimmune diseases, cancer and transplant immunology, suggesting novel opportunities for personalized medicine.
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Affiliation(s)
- Sietse Q Nagelkerke
- Sanquin Research and Landsteiner Laboratory, Department of Blood Cell Research, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.,Pediatric Hematology, Immunology and Infectious Diseases, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - David E Schmidt
- Sanquin Research and Landsteiner Laboratory, Department of Experimental Immunology, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Masja de Haas
- Sanquin Diagnostic Services, Department of Immunohematology Diagnostics, Amsterdam, Netherlands.,Sanquin Research, Center for Clinical Transfusion Research, Leiden, Netherlands.,Jon J. van Rood Center for Clinical Transfusion Science, Leiden University Medical Center, Leiden, Netherlands.,Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, Netherlands
| | - Taco W Kuijpers
- Sanquin Research and Landsteiner Laboratory, Department of Blood Cell Research, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands.,Pediatric Hematology, Immunology and Infectious Diseases, Emma Children's Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
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6
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Rahbari R, Zuccherato LW, Tischler G, Chihota B, Ozturk H, Saleem S, Tarazona‐Santos E, Machado LR, Hollox EJ. Understanding the Genomic Structure of Copy-Number Variation of the Low-Affinity Fcγ Receptor Region Allows Confirmation of the Association of FCGR3B Deletion with Rheumatoid Arthritis. Hum Mutat 2017; 38:390-399. [PMID: 27995740 PMCID: PMC5363352 DOI: 10.1002/humu.23159] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Accepted: 12/14/2016] [Indexed: 11/23/2022]
Abstract
Fcγ receptors are a family of cell-surface receptors that are expressed by a host of different innate and adaptive immune cells, and mediate inflammatory responses by binding the Fc portion of immunoglobulin G. In humans, five low-affinity receptors are encoded by the genes FCGR2A, FCGR2B, FCGR2C, FCGR3A, and FCGR3B, which are located in an 82.5-kb segmental tandem duplication on chromosome 1q23.3, which shows extensive copy-number variation (CNV). Deletions of FCGR3B have been suggested to increase the risk of inflammatory diseases such as systemic lupus erythematosus and rheumatoid arthritis (RA). In this study, we identify the deletion breakpoints of FCGR3B deletion alleles in the UK population and endogamous native American population, and show that some but not all alleles are likely to be identical-by-descent. We also localize a duplication breakpoint, confirming that the mechanism of CNV generation is nonallelic homologous recombination, and identify several alleles with gene conversion events using fosmid sequencing data. We use information on the structure of the deletion alleles to distinguish FCGR3B deletions from FCGR3A deletions in whole-genome array comparative genomic hybridization (aCGH) data. Reanalysis of published aCGH data using this approach supports association of FCGR3B deletion with increased risk of RA in a large cohort of 1,982 cases and 3,271 controls (odds ratio 1.61, P = 2.9×10-3 ).
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Affiliation(s)
- Raheleh Rahbari
- Department of GeneticsUniversity of LeicesterLeicesterUnited Kingdom
- Wellcome Trust Sanger InstituteHinxtonUnited Kingdom
| | - Luciana W Zuccherato
- Department of GeneticsUniversity of LeicesterLeicesterUnited Kingdom
- Departmento de Biologia GeralInstituto de Ciências BiológicasUniversidade Federal de Minas GeraisBelo HorizonteBrazil
| | | | - Belinda Chihota
- School of HealthUniversity of NorthamptonNorthamptonUnited Kingdom
| | - Hasret Ozturk
- Department of GeneticsUniversity of LeicesterLeicesterUnited Kingdom
| | - Sara Saleem
- Department of GeneticsUniversity of LeicesterLeicesterUnited Kingdom
| | - Eduardo Tarazona‐Santos
- Departmento de Biologia GeralInstituto de Ciências BiológicasUniversidade Federal de Minas GeraisBelo HorizonteBrazil
| | - Lee R Machado
- Department of GeneticsUniversity of LeicesterLeicesterUnited Kingdom
- School of HealthUniversity of NorthamptonNorthamptonUnited Kingdom
| | - Edward J Hollox
- Department of GeneticsUniversity of LeicesterLeicesterUnited Kingdom
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7
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Abstract
Copy number variation (CNV), where a segment of DNA differs in copy number between different individuals, is an extensive and often underappreciated source of genetic variation within species. However, reliably determining copy number of a particular DNA sequence for a large number of samples can be challenging. Here, I describe and review the paralogue ratio test (PRT) in detail. PRT was developed to robustly type the CNV of the beta-defensin locus using small amounts of genomic DNA in a high-throughput manner, and has been applied successfully at many other loci. I discuss the strategies for designing successful PRT assays using both manual and bioinformatics methods, how to optimize experimental conditions, and approaches for analyzing the data. I discuss strengths and weaknesses of the approach, and how to troubleshoot results, as well as the range of problems to which PRT can be a potential solution.
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8
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Qi YY, Zhou XJ, Bu DF, Hou P, Lv JC, Zhang H. Comparison of Multiple Methods for Determination of FCGR3A/B Genomic Copy Numbers in HapMap Asian Populations with Two Public Databases. Front Genet 2016; 7:220. [PMID: 28083015 PMCID: PMC5183586 DOI: 10.3389/fgene.2016.00220] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2016] [Accepted: 12/12/2016] [Indexed: 01/23/2023] Open
Abstract
Low FCGR3 copy numbers (CNs) has been associated with susceptibility to several systemic autoimmune diseases. However, inconsistent associations were reported and errors caused by shaky methods were suggested to be the major causes. In large scale case control association studies, robust copy number determination method is thus warranted, which was the main focus of the current study. In the present study, FCGR3 CNs of 90 HapMap Asians were firstly checked using four assays including paralog ratio test combined with restriction enzyme digest variant ratio (PRT-REDVR), real-time quantitative (qPCR) using TaqMan assay, real-time qPCR using SYBR Green dye and short tenden repeat (STR). To improve the comparison precision reproductively, the results were compared with those from recently released sequencing data from 1000 genomes project as well as whole-genome tiling BAC array data. The tendencies of inconsistent samples by these methods were also characterized. Refined in-home TaqMan qPCR assay showed the highest correlation with array-CGH results (r = 0.726, p < 0.001) and the highest concordant rate with 1000 genome sequencing data (FCGR3A 91.76%, FCGR3B 85.88%, and FCGR3 81.18%). For samples with copy number variations, comprehensive analysis of multiple methods was required in order to improve detection accuracy. All these method were prone to detect copy number to be higher than that from direct sequencing. All the four PCR based CN determination methods (qPCR using TaqMan probes or SYBR Green, PRT, STR) were prone to higher estimation errors and thus may lead to artificial associations in large-scale case-control association studies. But different to previous reports, we observed that properly refined TaqMan qPCR assay was not inferior to or even more accurate than PRT when using sequencing data as the reference.
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Affiliation(s)
- Yuan-Yuan Qi
- Renal Division, Peking University First HospitalBeijing, China; Peking University Institute of NephrologyBeijing, China; Key Laboratory of Renal Disease, Ministry of Health of ChinaBeijing, China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of EducationBeijing, China
| | - Xu-Jie Zhou
- Renal Division, Peking University First HospitalBeijing, China; Peking University Institute of NephrologyBeijing, China; Key Laboratory of Renal Disease, Ministry of Health of ChinaBeijing, China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of EducationBeijing, China
| | - Ding-Fang Bu
- Research Central Institute, Peking University First Hospital Beijing, China
| | - Ping Hou
- Renal Division, Peking University First HospitalBeijing, China; Peking University Institute of NephrologyBeijing, China; Key Laboratory of Renal Disease, Ministry of Health of ChinaBeijing, China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of EducationBeijing, China
| | - Ji-Cheng Lv
- Renal Division, Peking University First HospitalBeijing, China; Peking University Institute of NephrologyBeijing, China; Key Laboratory of Renal Disease, Ministry of Health of ChinaBeijing, China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of EducationBeijing, China
| | - Hong Zhang
- Renal Division, Peking University First HospitalBeijing, China; Peking University Institute of NephrologyBeijing, China; Key Laboratory of Renal Disease, Ministry of Health of ChinaBeijing, China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment, Peking University, Ministry of EducationBeijing, China
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9
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Shueb RH, Jusoh SK, Zakaria Z, Haridan US, Sim BLH, Zaid M, Mustaffa N, Mustafa M, Nik 'Yusoff NK, Lee CKC, AbuBakar S, Hoh BP. The identification of copy number variation of CD209 ( DCSIGN ) gene among dengue patients from peninsular Malaysia. Meta Gene 2016. [DOI: 10.1016/j.mgene.2016.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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10
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Erbe AK, Wang W, Gallenberger M, Hank JA, Sondel PM. Genotyping Single Nucleotide Polymorphisms and Copy Number Variability of the FCGRs Expressed on NK Cells. Methods Mol Biol 2016; 1441:43-56. [PMID: 27177655 DOI: 10.1007/978-1-4939-3684-7_4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Natural killer (NK) cells are one of the main effector immune cells involved in antibody-dependent cell-mediated cytotoxicity (ADCC). Upon recognition of cell-bound IgG antibodies, which occurs through Fc gamma receptors (FCGRs) expressed on the cell surface of NK cells, NK cells become activated and lyse target tumor or infected cells. The FCGRs, FCGR3A and FCGR2C, expressed on the surface of NK cells have single nucleotide polymorphisms (SNPs) that result in differential activity of NK cells. In addition to SNP genetic variation within each of these genes, the FCGRs are subject to copy number variation (CNV), which leads to variable protein expression levels on the cell surface. Studies have found that FCGR genotype for FCGR3A and FCGR2C is associated with variation in the response to immunotherapy.Due to high sequence homology within FCGR3 and FCGR2 families, there are difficulties associated with genotyping these specific receptors related to cross-amplification of non-targeted FCGRs. To improve specificity for both FCGR3A and FCGR2C, Rnase-H (RH) primers were designed to amplify specifically FCGR3A (while not co-amplifying FCGR3B) and FCGR2C (while not co-amplifying FCGR2B). In addition, fluorescently labeled locked nucleic acid (LNA) probes provide additional precision for determination of the SNPs within both FCGR3A and FCGR2C. For CNV determination, separate fluorescently labeled probes for FCGR3A, and for FCGR2C, can be used with the same RH primers for each gene. These probes can be combined in the same well with control primers/probe for a known diploid gene and used to calculate the copy number of both FCGR3A and FCGR2C. Here we provide new detailed methodology that allows for the specific amplification of these FCGRs in a single PCR reaction, allowing for genotyping of both the SNPs and CNVs using real-time PCR.
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Affiliation(s)
- Amy K Erbe
- Department of Human Oncology, University of Wisconsin, 1111 Highland Avenue, 4136 WIMR Bldg., Madison, WI, 53705, USA.
| | - Wei Wang
- Department of Human Oncology, University of Wisconsin, 1111 Highland Avenue, 4136 WIMR Bldg., Madison, WI, 53705, USA
| | - Mikayla Gallenberger
- Department of Human Oncology, University of Wisconsin, 1111 Highland Avenue, 4136 WIMR Bldg., Madison, WI, 53705, USA
| | - Jacquelyn A Hank
- Department of Human Oncology, University of Wisconsin, 1111 Highland Avenue, 4136 WIMR Bldg., Madison, WI, 53705, USA
| | - Paul M Sondel
- Department of Human Oncology, University of Wisconsin, 1111 Highland Avenue, 4136 WIMR Bldg., Madison, WI, 53705, USA
- Department of Pediatrics, University of Wisconsin, Madison, WI, USA
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