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Chiang YC, Huang HN, Kuo KT, Hwu WL, Lin PH. Whole exome sequencing-based homologous recombination deficiency test for epithelial ovarian cancer. J Ovarian Res 2025; 18:19. [PMID: 39885596 PMCID: PMC11780812 DOI: 10.1186/s13048-024-01565-3] [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: 06/18/2024] [Accepted: 11/24/2024] [Indexed: 02/01/2025] Open
Abstract
BACKGROUND The homologous recombination deficiency (HRD) test is an important tool for identifying patients with epithelial ovarian cancer (EOC) benefit from the treatment with poly(adenosine diphosphate-ribose) polymerase inhibitor (PARPi). Using whole exome sequencing (WES)-based platform can provide information of gene mutations and HRD score; however, the clinical value of WES-based HRD test was less validated in EOC. METHODS We enrolled 40 patients with EOC in the training cohort and 23 in the validation cohort. The WES-based HRD score was calculated using the scarHRD software. We first evaluated the concordance of the HRD status defined by the Myriad MyChoice CDx and then assessed the value of HRD on clinical prognosis in patients with EOC. RESULTS The HRD score defined by the WES-based test was positively correlated with that of the Myriad MyChoice® CDx test (r = 0.82, p < 0.01) in the training cohort. In compared to HRD status of Myriad test, the sensitivity, specificity, positive predictive value, and negative predictive value of the WES-based HRD test were 93.5% (29/31), 77.8% (7/9), 93.5% (29/31), and 77.8% (7/9), respectively. Patients with positive HRD status defined by WES-based scarHRD test and Myriad MyChoice® CDx test were both highly associated with platinum sensitive response (both Fisher's exact test, p = 0.002) as well as the superior progression-free survival (both log-rank p = 0.002). The multi-variate Cox regression model incorporated with optimal debulking surgery showed that the recurrence risk was decreased in the patients with positive HRD status, either defined by Myriad MyChoice® CDx test (Hazard ratio (HR) 0.33, 95% confidence interval (CI) 0.14-0.79, p = 0.013) or WES-based test Myriad MyChoice® CDx test (HR 0.34, 95% CI 0.14-0.80, p = 0.014). Nine patients had mutations in the genes involved in HR DNA repair, and all of them were positive for HRD. In the validation group, 23 patients were defined as positive HRD by WES-based testing. Six positive HRD patients and 5 negative HRD patients received maintenance PARPi. The median responsive interval of PARPi was 17 months in positive HRD patients and 3 months in negative HRD patients. CONCLUSION The WES-based test is a potential option for determining the HRD status in EOC patients, and desires for further validation in large-scale cohorts.
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Affiliation(s)
- Ying-Cheng Chiang
- Department of Obstetrics and Gynecology, College of Medicine, National Taiwan University, Taipei City, Taiwan
- Department of Obstetrics and Gynecology, National Taiwan University Hospital, Taipei City, Taiwan
- Department of Obstetrics and Gynecology, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan
| | - Hsien-Neng Huang
- Department of Pathology, National Taiwan University Hospital Hsin-Chu Branch, Hsinchu, Taiwan
| | - Kuan-Ting Kuo
- Department of Pathology, College of Medicine, National Taiwan University, Taipei City, Taiwan
| | - Wuh-Liang Hwu
- Department of Pediatrics, National Taiwan University Hospital, Taipei City, Taiwan
| | - Po-Han Lin
- Department of Medical Genetics, National Taiwan University Hospital, 19F, No. 8, Chung-Shan South Road, Taipei City, Taiwan.
- Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei City, Taiwan.
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Zouaghi Y, Choudhary AM, Irshad S, Adamo M, Rehman KU, Fatima A, Shahid M, Najmi N, De Azevedo Correa F, Habibi I, Boizot A, Niederländer NJ, Ansar M, Santoni F, Acierno J, Pitteloud N. Genome sequencing reveals novel causative structural and single nucleotide variants in Pakistani families with congenital hypogonadotropic hypogonadism. BMC Genomics 2024; 25:787. [PMID: 39143522 PMCID: PMC11325732 DOI: 10.1186/s12864-024-10598-3] [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: 10/23/2023] [Accepted: 07/05/2024] [Indexed: 08/16/2024] Open
Abstract
BACKGROUND/OBJECTIVES This study aims to elucidate the genetic causes of congenital hypogonadotropic hypogonadism (CHH), a rare genetic disorder resulting in GnRH deficiency, in six families from Pakistan. METHODS Eighteen DNA samples from six families underwent genome sequencing followed by standard evaluation for pathogenic single nucleotide variants (SNVs) and small indels. All families were subsequently analyzed for pathogenic copy number variants (CNVs) using CoverageMaster. RESULTS Novel pathogenic homozygous SNVs in known CHH genes were identified in four families: two families with variants in GNRHR, and two others harboring KISS1R variants. Subsequent investigation of CNVs in the remaining two families identified novel unique large deletions in ANOS1. CONCLUSION A combined, systematic analysis of single nucleotide and CNVs helps to improve the diagnostic yield for variants in patients with CHH.
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Affiliation(s)
- Yassine Zouaghi
- University of Lausanne, Lausanne, Switzerland
- Service of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de La Sallaz 8, Lausanne, CH-1011, Switzerland
| | - Anbreen Mazhar Choudhary
- School of Biochemistry and Biotechnology, University of the Punjab, Lahore, Pakistan
- FMH College of Medicine & Dentistry, Lahore, Pakistan
| | - Saba Irshad
- School of Biochemistry and Biotechnology, University of the Punjab, Lahore, Pakistan
| | - Michela Adamo
- University of Lausanne, Lausanne, Switzerland
- Service of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de La Sallaz 8, Lausanne, CH-1011, Switzerland
| | | | - Ambrin Fatima
- Department of Biological and Biomedical Sciences, Aga Khan University, Karachi, Pakistan
| | - Mariam Shahid
- Centre of Excellence in Molecular Biology, University of the Punjab, Lahore, Pakistan
| | - Nida Najmi
- Department of Obstetrics and Gynaecology, The Aga Khan University Hospital, Karachi, Pakistan
| | - Fernanda De Azevedo Correa
- University of Lausanne, Lausanne, Switzerland
- Service of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de La Sallaz 8, Lausanne, CH-1011, Switzerland
| | - Imen Habibi
- University of Lausanne, Lausanne, Switzerland
- Service of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de La Sallaz 8, Lausanne, CH-1011, Switzerland
| | - Alexia Boizot
- University of Lausanne, Lausanne, Switzerland
- Service of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de La Sallaz 8, Lausanne, CH-1011, Switzerland
| | - Nicolas J Niederländer
- University of Lausanne, Lausanne, Switzerland
- Service of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de La Sallaz 8, Lausanne, CH-1011, Switzerland
| | - Muhammad Ansar
- Department of Ophthalmology, University of Lausanne, Jules Gonin Eye Hospital, Fondation Asile Des Aveugles, Lausanne, Switzerland
- Advanced Molecular Genetics and Genomics Disease Research and Treatment Centre, Dow University of Health Sciences, Karachi, Pakistan
| | - Federico Santoni
- University of Lausanne, Lausanne, Switzerland
- Service of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de La Sallaz 8, Lausanne, CH-1011, Switzerland
- , Medigenome, Geneva, Switzerland
| | - James Acierno
- Service of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de La Sallaz 8, Lausanne, CH-1011, Switzerland
| | - Nelly Pitteloud
- University of Lausanne, Lausanne, Switzerland.
- Service of Endocrinology, Diabetology and Metabolism, Lausanne University Hospital, Avenue de La Sallaz 8, Lausanne, CH-1011, Switzerland.
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3
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Tang G, Liu X, Cho M, Li Y, Tran DH, Wang X. Pan-cancer discovery of somatic mutations from RNA sequencing data. Commun Biol 2024; 7:619. [PMID: 38783092 PMCID: PMC11116503 DOI: 10.1038/s42003-024-06326-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: 09/14/2023] [Accepted: 05/14/2024] [Indexed: 05/25/2024] Open
Abstract
Identification of somatic mutations (SMs) is essential for characterizing cancer genomes. While DNA-seq is the prevalent method for identifying SMs, RNA-seq provides an alternative strategy to discover tumor mutations in the transcribed genome. Here, we have developed a machine learning based pipeline to discover SMs based on RNA-seq data (designated as RNA-SMs). Subsequently, we have conducted a pan-cancer analysis to systematically identify RNA-SMs from over 8,000 tumors in The Cancer Genome Atlas (TCGA). In this way, we have identified over 105,000 novel SMs that had not been reported in previous TCGA studies. These novel SMs have significant clinical implications in designing targeted therapy for improved patient outcomes. Further, we have combined the SMs identified by both RNA-seq and DNA-seq analyses to depict an updated mutational landscape across 32 cancer types. This new online SM atlas, OncoDB ( https://oncodb.org ), offers a more complete view of gene mutations that underline the development and progression of various cancers.
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Affiliation(s)
- Gongyu Tang
- Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, IL, USA
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO, USA
| | - Xinyi Liu
- Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Minsu Cho
- Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Yuanxiang Li
- Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Dan-Ho Tran
- Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Xiaowei Wang
- Department of Pharmacology and Regenerative Medicine, University of Illinois at Chicago, Chicago, IL, USA.
- University of Illinois Cancer Center, Chicago, IL, USA.
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Davies EA, Dutton L, Guiver M. Evaluation of a custom designed hybridisation assay for whole genome sequencing of human adenoviruses direct from clinical samples. J Clin Virol 2024; 171:105640. [PMID: 38219683 DOI: 10.1016/j.jcv.2024.105640] [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: 09/27/2023] [Revised: 01/05/2024] [Accepted: 01/10/2024] [Indexed: 01/16/2024]
Abstract
BACKGROUND Human Adenoviruses are a common cause of disease and can cause significant morbidity and mortality in immunocompromised patients. Nosocomial transmission events can occur with whole genome sequencing playing a crucial role. This study evaluates the performance of a custom designed SureSelectXT target enrichment assay based on 14 adenovirus genomes for sequencing direct from clinical samples. METHODS Modifications were made to the SureSelectXT low input protocol to enhance performance for viral targets. Consensus sequences were generated using an in-house designed three stage bioinformatics pipeline. We assessed, percentage of on target reads, average depth of coverage and percentage genome coverage to determine assay performance across a range of sample matrices. RESULTS Whole genome sequences were successfully generated for 91.6 % of samples assessed. Adenovirus DNA concentration was a good indicator of enrichment success. Highly specific enrichment was observed with only 6 % of samples showing < 50 % on target reads. Respiratory and faecal samples performed well where bloods showed higher levels of non-specific enrichment likely confounded by low adenovirus DNA concentrations. Protocol performance did not appear impacted by Adenovirus type or species. CONCLUSION Overall performance of this modified SureSelectXT protocol appears in line with previously published works although there are some confounding factors requiring further investigation. The use of a small RNA bait set has the potential to reduce associated costs which can be prohibitive.
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Affiliation(s)
- Emma Ann Davies
- UKHSA Manchester Virology Laboratory, Manchester Medical Microbiology Partnership, Manchester Foundation Trust, Manchester, UK.
| | - Laura Dutton
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester Foundation Trust, Manchester, UK
| | - Malcolm Guiver
- UKHSA Manchester Virology Laboratory, Manchester Medical Microbiology Partnership, Manchester Foundation Trust, Manchester, UK
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Schobers G, Derks R, den Ouden A, Swinkels H, van Reeuwijk J, Bosgoed E, Lugtenberg D, Sun SM, Corominas Galbany J, Weiss M, Blok MJ, Olde Keizer RACM, Hofste T, Hellebrekers D, de Leeuw N, Stegmann A, Kamsteeg EJ, Paulussen ADC, Ligtenberg MJL, Bradley XZ, Peden J, Gutierrez A, Pullen A, Payne T, Gilissen C, van den Wijngaard A, Brunner HG, Nelen M, Yntema HG, Vissers LELM. Genome sequencing as a generic diagnostic strategy for rare disease. Genome Med 2024; 16:32. [PMID: 38355605 PMCID: PMC10868087 DOI: 10.1186/s13073-024-01301-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 02/02/2024] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND To diagnose the full spectrum of hereditary and congenital diseases, genetic laboratories use many different workflows, ranging from karyotyping to exome sequencing. A single generic high-throughput workflow would greatly increase efficiency. We assessed whether genome sequencing (GS) can replace these existing workflows aimed at germline genetic diagnosis for rare disease. METHODS We performed short-read GS (NovaSeq™6000; 150 bp paired-end reads, 37 × mean coverage) on 1000 cases with 1271 known clinically relevant variants, identified across different workflows, representative of our tertiary diagnostic centers. Variants were categorized into small variants (single nucleotide variants and indels < 50 bp), large variants (copy number variants and short tandem repeats) and other variants (structural variants and aneuploidies). Variant calling format files were queried per variant, from which workflow-specific true positive rates (TPRs) for detection were determined. A TPR of ≥ 98% was considered the threshold for transition to GS. A GS-first scenario was generated for our laboratory, using diagnostic efficacy and predicted false negative as primary outcome measures. As input, we modeled the diagnostic path for all 24,570 individuals referred in 2022, combining the clinical referral, the transition of the underlying workflow(s) to GS, and the variant type(s) to be detected. RESULTS Overall, 95% (1206/1271) of variants were detected. Detection rates differed per variant category: small variants in 96% (826/860), large variants in 93% (341/366), and other variants in 87% (39/45). TPRs varied between workflows (79-100%), with 7/10 being replaceable by GS. Models for our laboratory indicate that a GS-first strategy would be feasible for 84.9% of clinical referrals (750/883), translating to 71% of all individuals (17,444/24,570) receiving GS as their primary test. An estimated false negative rate of 0.3% could be expected. CONCLUSIONS GS can capture clinically relevant germline variants in a 'GS-first strategy' for the majority of clinical indications in a genetics diagnostic lab.
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Affiliation(s)
- Gaby Schobers
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
- Research Institute for Medical Innovation, Radboudumc, Nijmegen, Netherlands
| | - Ronny Derks
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
| | - Amber den Ouden
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
| | - Hilde Swinkels
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
| | - Jeroen van Reeuwijk
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
- Research Institute for Medical Innovation, Radboudumc, Nijmegen, Netherlands
| | - Ermanno Bosgoed
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
| | | | - Su Ming Sun
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, Netherlands
| | - Jordi Corominas Galbany
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
- Research Institute for Medical Innovation, Radboudumc, Nijmegen, Netherlands
| | - Marjan Weiss
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
| | - Marinus J Blok
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, Netherlands
| | - Richelle A C M Olde Keizer
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
- Research Institute for Medical Innovation, Radboudumc, Nijmegen, Netherlands
| | - Tom Hofste
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
| | - Debby Hellebrekers
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, Netherlands
| | - Nicole de Leeuw
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
| | - Alexander Stegmann
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, Netherlands
| | | | - Aimee D C Paulussen
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, Netherlands
| | - Marjolijn J L Ligtenberg
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
- Research Institute for Medical Innovation, Radboudumc, Nijmegen, Netherlands
| | | | | | | | | | | | - Christian Gilissen
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
- Research Institute for Medical Innovation, Radboudumc, Nijmegen, Netherlands
| | | | - Han G Brunner
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
- Research Institute for Medical Innovation, Radboudumc, Nijmegen, Netherlands
- Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, Netherlands
| | - Marcel Nelen
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
| | - Helger G Yntema
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands
- Research Institute for Medical Innovation, Radboudumc, Nijmegen, Netherlands
| | - Lisenka E L M Vissers
- Department of Human Genetics, Radboudumc, Nijmegen, Netherlands.
- Research Institute for Medical Innovation, Radboudumc, Nijmegen, Netherlands.
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Johannesen KM, Tümer Z, Weckhuysen S, Barakat TS, Bayat A. Solving the unsolved genetic epilepsies: Current and future perspectives. Epilepsia 2023; 64:3143-3154. [PMID: 37750451 DOI: 10.1111/epi.17780] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/21/2023] [Accepted: 09/22/2023] [Indexed: 09/27/2023]
Abstract
Many patients with epilepsy undergo exome or genome sequencing as part of a diagnostic workup; however, many remain genetically unsolved. There are various factors that account for negative results in exome/genome sequencing for patients with epilepsy: (1) the underlying cause is not genetic; (2) there is a complex polygenic explanation; (3) the illness is monogenic but the causative gene remains to be linked to a human disorder; (4) family segregation with reduced penetrance; (5) somatic mosaicism or the complexity of, for example, a structural rearrangement; or (6) limited knowledge or diagnostic tools that hinder the proper classification of a variant, resulting in its designation as a variant of unknown significance. The objective of this review is to outline some of the diagnostic options that lie beyond the exome/genome, and that might become clinically relevant within the foreseeable future. These options include: (1) re-analysis of older exome/genome data as knowledge increases or symptoms change; (2) looking for somatic mosaicism or long-read sequencing to detect low-complexity repeat variants or specific structural variants missed by traditional exome/genome sequencing; (3) exploration of the non-coding genome including disruption of topologically associated domains, long range non-coding RNA, or other regulatory elements; and finally (4) transcriptomics, DNA methylation signatures, and metabolomics as complementary diagnostic methods that may be used in the assessment of variants of unknown significance. Some of these tools are currently not integrated into standard diagnostic workup. However, it is reasonable to expect that they will become increasingly available and improve current diagnostic capabilities, thereby enabling precision diagnosis in patients who are currently undiagnosed.
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Affiliation(s)
- Katrine M Johannesen
- Department of Genetics, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Epilepsy Genetics and Personalized Medicine, The Danish Epilepsy Center, Dianalund, Denmark
| | - Zeynep Tümer
- Department of Genetics, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sarah Weckhuysen
- Applied and Translational Neurogenomics Group, VIB Centre for Molecular Neurology, Antwerp, Belgium
- Translational Neurosciences, Faculty of Medicine and Health Science, University of Antwerp, Antwerp, Belgium
- Department of Neurology, University Hospital Antwerp, Antwerp, Belgium
- μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Tahsin Stefan Barakat
- Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Discovery Unit, Department of Clinical Genetics, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- ENCORE Expertise Center for Neurodevelopmental Disorders, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Allan Bayat
- Department of Epilepsy Genetics and Personalized Medicine, The Danish Epilepsy Center, Dianalund, Denmark
- Department of Regional Health Research, University of Southern Denmark, Odense, Denmark
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
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Liu Y, Mao L, Huang H, Li W, Man J, Zhang W, Wang L, Li L, Sun Y, Zhai T, Guo X, Du L, Huang J, Li H, Wan Y, Wei X. Clinical diagnosis of genetic disorders at both single-nucleotide and chromosomal levels based on BGISEQ-500 platform. Hum Genome Var 2023; 10:15. [PMID: 37217505 PMCID: PMC10203365 DOI: 10.1038/s41439-023-00238-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 02/05/2023] [Accepted: 02/19/2023] [Indexed: 05/24/2023] Open
Abstract
Most variations in the human genome refer to single-nucleotide variation (SNV), small fragment insertions and deletions, and genomic copy number variation (CNV). Many human diseases including genetic disorders are associated with variations in the genome. These disorders are often difficult to be diagnosed because of their complex clinical conditions, therefore, an effective detection method is needed to facilitate clinical diagnosis and prevent birth defects. With the development of high-throughput sequencing technology, the method of targeted sequence capture chip has been extensively used owing to its high throughput, high accuracy, fast speed, and low cost. In this study, we designed a chip that potentially captured the coding region of 3043 genes associated with 4013 monogenic diseases, with an addition of 148 chromosomal abnormalities that can be identified by targeting specific regions. To assess the efficiency, a strategy of combining the BGISEQ500 sequencing platform with the designed chip was utilized to screen variants in 63 patients. Eventually, 67 disease-associated variants were found, 31 of which were novel. The results of the evaluation test also show that this combined strategy complies with the requirements of clinical testing and has proper clinical application value.
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Affiliation(s)
- Yanqiu Liu
- Department of Genetics, Jiangxi Maternal and Child Health Hospital, 330006, Nanchang, China
| | - Liangwei Mao
- BGI-Anhui Clinical Laboratory, BGI-Shenzhen, 236000, Fuyang, China
- The State Key Laboratory of Biocatalysis and Enzyme Engineering, College of Life Sciences, Hubei University, 430062, Wuhan, China
| | - Hui Huang
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
| | - Wei Li
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
| | - Jianfen Man
- BGI-Wuhan Clinical Laboratory, BGI-Shenzhen, 430074, Wuhan, China
| | - Wenqian Zhang
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
- BGI-Wuhan Clinical Laboratory, BGI-Shenzhen, 430074, Wuhan, China
- Department of Biology, University of Copenhagen, Copenhagen, DK-2200, Denmark
| | - Lina Wang
- BGI-Wuhan Clinical Laboratory, BGI-Shenzhen, 430074, Wuhan, China
| | - Long Li
- BGI-Wuhan Clinical Laboratory, BGI-Shenzhen, 430074, Wuhan, China
| | - Yan Sun
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
| | - Teng Zhai
- BGI Genomics, BGI-Shenzhen, 518083, Shenzhen, China
| | - Xueqin Guo
- BGI-Wuhan Clinical Laboratory, BGI-Shenzhen, 430074, Wuhan, China
| | - Lique Du
- BGI-Wuhan Clinical Laboratory, BGI-Shenzhen, 430074, Wuhan, China
| | - Jin Huang
- BGI-Wuhan Clinical Laboratory, BGI-Shenzhen, 430074, Wuhan, China
| | - Hao Li
- BGI-Anhui Clinical Laboratory, BGI-Shenzhen, 236000, Fuyang, China
| | - Yang Wan
- Department of Obstetrics and Gynecology, Fuyang People's Hospital, 236000, Fuyang, China.
| | - Xiaoming Wei
- BGI-Wuhan Clinical Laboratory, BGI-Shenzhen, 430074, Wuhan, China.
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Yaldiz B, Kucuk E, Hampstead J, Hofste T, Pfundt R, Corominas Galbany J, Rinne T, Yntema HG, Hoischen A, Nelen M, Gilissen C. Twist exome capture allows for lower average sequence coverage in clinical exome sequencing. Hum Genomics 2023; 17:39. [PMID: 37138343 PMCID: PMC10155375 DOI: 10.1186/s40246-023-00485-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 04/20/2023] [Indexed: 05/05/2023] Open
Abstract
BACKGROUND Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. RESULTS We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. CONCLUSION We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques.
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Affiliation(s)
- Burcu Yaldiz
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Erdi Kucuk
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Juliet Hampstead
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Tom Hofste
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Rolph Pfundt
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Jordi Corominas Galbany
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Tuula Rinne
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Helger G Yntema
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Alexander Hoischen
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Marcel Nelen
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands
| | - Christian Gilissen
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Geert Grooteplein 10, 6525 GA, Nijmegen, The Netherlands.
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9
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Perrier S, Guerrero K, Tran LT, Michell-Robinson MA, Legault G, Brais B, Sylvain M, Dorman J, Demos M, Köhler W, Pastinen T, Thiffault I, Bernard G. Solving inherited white matter disorder etiologies in the neurology clinic: Challenges and lessons learned using next-generation sequencing. Front Neurol 2023; 14:1148377. [PMID: 37077564 PMCID: PMC10108901 DOI: 10.3389/fneur.2023.1148377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 02/23/2023] [Indexed: 04/05/2023] Open
Abstract
IntroductionRare neurodevelopmental disorders, including inherited white matter disorders or leukodystrophies, often present a diagnostic challenge on a genetic level given the large number of causal genes associated with a range of disease subtypes. This study aims to demonstrate the challenges and lessons learned in the genetic investigations of leukodystrophies through presentation of a series of cases solved using exome or genome sequencing.MethodsEach of the six patients had a leukodystrophy associated with hypomyelination or delayed myelination on MRI, and inconclusive clinical diagnostic genetic testing results. We performed next generation sequencing (case-based exome or genome sequencing) to further investigate the genetic cause of disease.ResultsFollowing different lines of investigation, molecular diagnoses were obtained for each case, with patients harboring pathogenic variants in a range of genes including TMEM106B, GJA1, AGA, POLR3A, and TUBB4A. We describe the lessons learned in reaching the genetic diagnosis, including the importance of (a) utilizing proper multi-gene panels in clinical testing, (b) assessing the reliability of biochemical assays in supporting diagnoses, and (c) understanding the limitations of exome sequencing methods in regard to CNV detection and region coverage in GC-rich areas.DiscussionThis study illustrates the importance of applying a collaborative diagnostic approach by combining detailed phenotyping data and metabolic results from the clinical environment with advanced next generation sequencing analysis techniques from the research environment to increase the diagnostic yield in patients with genetically unresolved leukodystrophies.
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Affiliation(s)
- Stefanie Perrier
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Kether Guerrero
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Luan T. Tran
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Mackenzie A. Michell-Robinson
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
| | - Geneviève Legault
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Department of Pediatrics, McGill University, Montreal, QC, Canada
| | - Bernard Brais
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Michel Sylvain
- Division of Pediatric Neurology, Centre Mère-Enfant Soleil du CHU de Québec - Université Laval, Québec City, QC, Canada
| | - James Dorman
- John H. Stroger Jr. Hospital of Cook County, Chicago, IL, United States
- Department of Neurological Sciences, Rush Medical College, Chicago, IL, United States
| | - Michelle Demos
- Division of Neurology, Department of Pediatrics, University of British Columbia, BC Children's Hospital, Vancouver, BC, Canada
| | - Wolfgang Köhler
- Leukodystrophy Center, University of Leipzig Medical Center, Leipzig, Germany
| | - Tomi Pastinen
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, United States
- University of Missouri Kansas City School of Medicine, Kansas City, MO, United States
| | - Isabelle Thiffault
- Genomic Medicine Center, Children's Mercy Hospital, Kansas City, MO, United States
- University of Missouri Kansas City School of Medicine, Kansas City, MO, United States
- Department of Pathology and Laboratory Medicine, Children's Mercy Hospital, Kansas City, MO, United States
- Isabelle Thiffault
| | - Geneviève Bernard
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Child Health and Human Development Program, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Department of Pediatrics, McGill University, Montreal, QC, Canada
- Department of Human Genetics, McGill University, Montreal, QC, Canada
- Department of Specialized Medicine, Division of Medical Genetics, McGill University Health Center, Montreal, QC, Canada
- *Correspondence: Geneviève Bernard
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10
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Geng W, Li F, Zhang R, Cao L, Du X, Gu W, Xu M. Hand-foot-genital syndrome due to a duplication variant in the GC-rich region of HOXA13. Eur J Med Genet 2023; 66:104711. [PMID: 36702441 DOI: 10.1016/j.ejmg.2023.104711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 12/07/2022] [Accepted: 01/22/2023] [Indexed: 01/25/2023]
Abstract
BACKGROUND Hand-Foot-Genital Syndrome (HFGS) is an autosomal dominant disorder characterized by a broad phenotypic spectrum. Variants in HOXA13 gene were associated with HFGS. To date, only twenty families with HFGS have been reported. However, the challenge in HFGS is the limited sample sizes and phenotypic heterogeneity. The advent of next-generation sequencing has permitted the identification of patients with HOXA13 variants who do not manifest with the full HFGS syndromic features. METHODS Trio (parents-proband) Whole-exome sequence(WES) and whole-genome sequencing(WGS) was carried out in this study to investigate the underlying pathogenic genetic factor of the neonate with a wide variety of clinical abnormalities. RESULTS No possible pathogenetic variation was detected by trio-WES, and a duplication variant in HOXA13 (c.360_377dup, p.Ala128_Ala133dup), inherited from her mother, was identified by the subsequent WGS in the proband with malnutrition, feeding difficulties, electrolyte disorders, metabolic acidosis, recurrent urinary tract infections, hydronephrosis, nephrolithiasis, abnormal ureter morphology, cholelithiasis, uterus didelphys. Sequence analysis of the variant region (exon1) indicated a high GC content of 73.92%. In addition, further enquiry of the family history revealed that 5 members of the family in 4 generations had hand and foot anomalies. CONCLUSION The neonate was diagnosed with HFGS by genetic analysis. GC content had less influence on sequence coverage in WGS than WES analysis. This was the first report of trio-WGS study for HFGS genetic diagnosis, revealed that subsequent WGS was necessary for identification of potentially pathogenic variants in unexplained genetic disorders.
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Affiliation(s)
- Wenjin Geng
- Pediatric Intensive Care Unit, Hebei Children's Hospital, Shijiazhuang, China
| | - Fuwei Li
- Beijing Chigene Translational Medicine Research Center Co., Ltd, Beijing, China
| | - Ruoxuan Zhang
- School of Basic Medical Sciences, Hebei Medical University, Shijiazhuang, China
| | - Lijing Cao
- Pediatric Intensive Care Unit, Hebei Children's Hospital, Shijiazhuang, China
| | - Xilong Du
- Beijing Chigene Translational Medicine Research Center Co., Ltd, Beijing, China
| | - Weiyue Gu
- Beijing Chigene Translational Medicine Research Center Co., Ltd, Beijing, China
| | - Meixian Xu
- Pediatric Intensive Care Unit, Hebei Children's Hospital, Shijiazhuang, China.
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11
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Yao J, Ding Y, Liu X, Huang J, Zhang M, Zhang Y, Lv Y, Xie Z, Zuo J. Application value of whole exome sequencing in screening and identifying novel mutations of hypopharyngeal cancer. Sci Rep 2023; 13:107. [PMID: 36596842 PMCID: PMC9810646 DOI: 10.1038/s41598-022-27273-w] [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: 05/06/2022] [Accepted: 12/29/2022] [Indexed: 01/05/2023] Open
Abstract
The research on targeted therapy of hypopharyngeal cancer is very scarce. The discovery of new targeted driver genes will promote the progress of hypopharyngeal cancer therapy to a great extent. In our research, whole-exome sequencing in 10 patients with hypopharyngeal cancer was performed to identify single nucleotide variations (SNVs) and insertions and deletions (INDELs). American College of Medical Genetics and Genomics (ACMG) guidelines were used to evaluate the pathogenicity of the selected variants. 8113 mutation sites in 5326 genes were identified after strict screening. We identified 72 pathogenic mutations in 53 genes according to the ACMG guidelines. Gene Ontology (GO) annotation and KEGG enrichment analysis show the effect of these genes on cancer. Protein-protein interaction (PPI) was analyzed by string online software. The validation results of the ualcan database showed that 22 of the 53 genes may be related to the poor prognosis of patients with hypopharyngeal cancer. RBM20 has the most significant correlation with hypopharyngeal cancer, and it is likely to be the driver gene of hypopharyngeal cancer. In conclusion, we found possible therapeutic targets for hypopharyngeal cancer, especially RBM20 and KMT2C. Our study provides a basis for the pathogenesis and targeted therapy of hypopharyngeal cancer.
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Affiliation(s)
- Jingwei Yao
- grid.412017.10000 0001 0266 8918Gastroenterology Department, The Affiliated Nanhua Hospital of University of South China, Hengyang, 421001 Hunan People’s Republic of China ,grid.12955.3a0000 0001 2264 7233Department of Hematology, The First Affiliated Hospital of Xiamen University and Institute of Hematology, School of Medicine, Xiamen University, Xiamen, 361003 People’s Republic of China ,grid.412017.10000 0001 0266 8918Transformation Research Lab, Hunan Province Key Laboratory of Tumor Cellular and Molecular Pathology, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan People’s Republic of China ,grid.412017.10000 0001 0266 8918Clinical Laboratory, The Third Affiliated Hospital of University of South China, Hengyang, 421000 Hunan People’s Republic of China
| | - Yubo Ding
- grid.412017.10000 0001 0266 8918Gastroenterology Department, The Affiliated Nanhua Hospital of University of South China, Hengyang, 421001 Hunan People’s Republic of China ,grid.412017.10000 0001 0266 8918Transformation Research Lab, Hunan Province Key Laboratory of Tumor Cellular and Molecular Pathology, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan People’s Republic of China
| | - Xiong Liu
- grid.284723.80000 0000 8877 7471Department of Otolaryngology-Head and Neck Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, 510515 People’s Republic of China
| | - Jialu Huang
- grid.412017.10000 0001 0266 8918Transformation Research Lab, Hunan Province Key Laboratory of Tumor Cellular and Molecular Pathology, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan People’s Republic of China
| | - Minghui Zhang
- grid.412017.10000 0001 0266 8918Transformation Research Lab, Hunan Province Key Laboratory of Tumor Cellular and Molecular Pathology, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan People’s Republic of China
| | - Yu Zhang
- grid.412017.10000 0001 0266 8918Transformation Research Lab, Hunan Province Key Laboratory of Tumor Cellular and Molecular Pathology, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan People’s Republic of China
| | - Yufan Lv
- grid.412017.10000 0001 0266 8918Gastroenterology Department, The Affiliated Nanhua Hospital of University of South China, Hengyang, 421001 Hunan People’s Republic of China ,grid.412017.10000 0001 0266 8918Transformation Research Lab, Hunan Province Key Laboratory of Tumor Cellular and Molecular Pathology, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan People’s Republic of China
| | - Zhuoyi Xie
- grid.412017.10000 0001 0266 8918Transformation Research Lab, Hunan Province Key Laboratory of Tumor Cellular and Molecular Pathology, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan People’s Republic of China
| | - Jianhong Zuo
- grid.412017.10000 0001 0266 8918Gastroenterology Department, The Affiliated Nanhua Hospital of University of South China, Hengyang, 421001 Hunan People’s Republic of China ,grid.412017.10000 0001 0266 8918Transformation Research Lab, Hunan Province Key Laboratory of Tumor Cellular and Molecular Pathology, Hengyang Medical School, University of South China, Hengyang, 421001 Hunan People’s Republic of China ,grid.412017.10000 0001 0266 8918Clinical Laboratory, The Third Affiliated Hospital of University of South China, Hengyang, 421000 Hunan People’s Republic of China
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12
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Hitti-Malin RJ, Dhaenens CM, Panneman DM, Corradi Z, Khan M, den Hollander AI, Farrar GJ, Gilissen C, Hoischen A, van de Vorst M, Bults F, Boonen EGM, Saunders P, Roosing S, Cremers FPM. Using single molecule Molecular Inversion Probes as a cost-effective, high-throughput sequencing approach to target all genes and loci associated with macular diseases. Hum Mutat 2022; 43:2234-2250. [PMID: 36259723 PMCID: PMC10092144 DOI: 10.1002/humu.24489] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 09/06/2022] [Accepted: 10/17/2022] [Indexed: 01/25/2023]
Abstract
Macular degenerations (MDs) are a subgroup of retinal disorders characterized by central vision loss. Knowledge is still lacking on the extent of genetic and nongenetic factors influencing inherited MD (iMD) and age-related MD (AMD) expression. Single molecule Molecular Inversion Probes (smMIPs) have proven effective in sequencing the ABCA4 gene in patients with Stargardt disease to identify associated coding and noncoding variation, however many MD patients still remain genetically unexplained. We hypothesized that the missing heritability of MDs may be revealed by smMIPs-based sequencing of all MD-associated genes and risk factors. Using 17,394 smMIPs, we sequenced the coding regions of 105 iMD and AMD-associated genes and noncoding or regulatory loci, known pseudo-exons, and the mitochondrial genome in two test cohorts that were previously screened for variants in ABCA4. Following detailed sequencing analysis of 110 probands, a diagnostic yield of 38% was observed. This established an ''MD-smMIPs panel," enabling a genotype-first approach in a high-throughput and cost-effective manner, whilst achieving uniform and high coverage across targets. Further analysis will identify known and novel variants in MD-associated genes to offer an accurate clinical diagnosis to patients. Furthermore, this will reveal new genetic associations for MD and potential genetic overlaps between iMD and AMD.
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Affiliation(s)
- Rebekkah J Hitti-Malin
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.,Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Claire-Marie Dhaenens
- Inserm, CHU Lille, U1172-LilNCog-Lille Neuroscience & Cognition, Univ. Lille, Lille, France
| | - Daan M Panneman
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.,Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Zelia Corradi
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.,Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mubeen Khan
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anneke I den Hollander
- Department of Ophthalmology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - G Jane Farrar
- The School of Genetics & Microbiology, The University of Dublin Trinity College, Dublin, Ireland
| | - Christian Gilissen
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.,Radboud Institute of Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Alexander Hoischen
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.,Radboud Institute of Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.,Department of Internal Medicine, Radboud University Medical Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maartje van de Vorst
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Femke Bults
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Erica G M Boonen
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | | | - Susanne Roosing
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.,Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frans P M Cremers
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.,Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
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13
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Zhang K, Yu L, Lin G, Li J. A multi-laboratory assessment of clinical exome sequencing for detection of hereditary disease variants: 4441 ClinVar variants for clinical genomic test development and validation. Clin Chim Acta 2022; 535:99-107. [PMID: 35985503 DOI: 10.1016/j.cca.2022.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 08/01/2022] [Accepted: 08/05/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS Whole-exome sequencing (WES) technology has become an essential tool in the clinical diagnostic for rare genetic disorders, however, the issues that reduce testing precision, sensitivity, and concordance are not clear under routine testing conditions. The study is to systematically evaluate the comparability of clinical WES testing results in laboratories under routine conditions. METHODS We designed a multi-laboratory study across 24 participating laboratories in China. We assessed sequencing quality across capture methods and sequencing platforms, benchmarked the impact of coverage and callable regions on detecting single nucleotide variants (SNVs), small insertions and deletions (Indels) under the same computational approaches, and compared the sensitivity, precision and reproducibility on detecting mutations across laboratories. RESULTS High inter-laboratory variability on variants detection were found across participating laboratories. Sample DNA concentration and sequencing evenness are two major variables that lead to the coverage variation. The difference in bioinformatics tools and computational settings affect the sensitivity and precision of the final output. Besides, copy-number variants (CNVs) identification is less reproducible than SNVs and Indels in the WES testing. We also compiled a list of 4441 low coverage ClinVar variants of 1176 genes from this study, which can be used as a source for creating in silico and synthetic DNA reference materials for clinical genetic disorder detection. CONCLUSIONS The considerable inter-laboratory variability seen in both sequencing coverage evenness and variants detection highlights the urgent need to improve the precision, sensitivity and comparability of the results generated across different laboratories. The list of low coverage variants can have important implications for the development and validation of clinical genetic disorder tests by laboratories. This study also serves to best practice inform guidelines for detecting clinical genetic disorders by exome sequencing.
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Affiliation(s)
- Kuo Zhang
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology, Beijing, PR China
| | - Lijia Yu
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology, Beijing, PR China; National Center for Clinical Laboratories, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China
| | - Guigao Lin
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology, Beijing, PR China
| | - Jinming Li
- National Center for Clinical Laboratories, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology, Beijing, PR China; National Center for Clinical Laboratories, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, PR China.
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14
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Wortmann SB, Oud MM, Alders M, Coene KLM, van der Crabben SN, Feichtinger RG, Garanto A, Hoischen A, Langeveld M, Lefeber D, Mayr JA, Ockeloen CW, Prokisch H, Rodenburg R, Waterham HR, Wevers RA, van de Warrenburg BPC, Willemsen MAAP, Wolf NI, Vissers LELM, van Karnebeek CDM. How to proceed after "negative" exome: A review on genetic diagnostics, limitations, challenges, and emerging new multiomics techniques. J Inherit Metab Dis 2022; 45:663-681. [PMID: 35506430 PMCID: PMC9539960 DOI: 10.1002/jimd.12507] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 04/26/2022] [Accepted: 04/27/2022] [Indexed: 11/28/2022]
Abstract
Exome sequencing (ES) in the clinical setting of inborn metabolic diseases (IMDs) has created tremendous improvement in achieving an accurate and timely molecular diagnosis for a greater number of patients, but it still leaves the majority of patients without a diagnosis. In parallel, (personalized) treatment strategies are increasingly available, but this requires the availability of a molecular diagnosis. IMDs comprise an expanding field with the ongoing identification of novel disease genes and the recognition of multiple inheritance patterns, mosaicism, variable penetrance, and expressivity for known disease genes. The analysis of trio ES is preferred over singleton ES as information on the allelic origin (paternal, maternal, "de novo") reduces the number of variants that require interpretation. All ES data and interpretation strategies should be exploited including CNV and mitochondrial DNA analysis. The constant advancements in available techniques and knowledge necessitate the close exchange of clinicians and molecular geneticists about genotypes and phenotypes, as well as knowledge of the challenges and pitfalls of ES to initiate proper further diagnostic steps. Functional analyses (transcriptomics, proteomics, and metabolomics) can be applied to characterize and validate the impact of identified variants, or to guide the genomic search for a diagnosis in unsolved cases. Future diagnostic techniques (genome sequencing [GS], optical genome mapping, long-read sequencing, and epigenetic profiling) will further enhance the diagnostic yield. We provide an overview of the challenges and limitations inherent to ES followed by an outline of solutions and a clinical checklist, focused on establishing a diagnosis to eventually achieve (personalized) treatment.
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Affiliation(s)
- Saskia B. Wortmann
- Radboud Center for Mitochondrial and Metabolic Medicine, Department of PediatricsAmalia Children's Hospital, Radboud University Medical CenterNijmegenThe Netherlands
- University Children's Hospital, Paracelsus Medical UniversitySalzburgAustria
| | - Machteld M. Oud
- United for Metabolic DiseasesAmsterdamThe Netherlands
- Department of Human GeneticsDonders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
| | - Mariëlle Alders
- Department of Human GeneticsAmsterdam UMC, University of Amsterdam, Amsterdam Reproduction and Development Research InstituteAmsterdamThe Netherlands
| | - Karlien L. M. Coene
- United for Metabolic DiseasesAmsterdamThe Netherlands
- Translational Metabolic Laboratory, Department of Laboratory MedicineRadboud University Medical CenterNijmegenThe Netherlands
| | - Saskia N. van der Crabben
- Department of Human GeneticsAmsterdam University Medical Centers, University of AmsterdamAmsterdamThe Netherlands
| | - René G. Feichtinger
- University Children's Hospital, Paracelsus Medical UniversitySalzburgAustria
| | - Alejandro Garanto
- Radboud Center for Mitochondrial and Metabolic Medicine, Department of PediatricsAmalia Children's Hospital, Radboud University Medical CenterNijmegenThe Netherlands
- Department of PediatricsAmalia Children's Hospital, Radboud Institute for Molecular LifesciencesNijmegenThe Netherlands
- Department of Human GeneticsRadboud Institute for Molecular LifesciencesNijmegenThe Netherlands
| | - Alex Hoischen
- Department of Human Genetics, Department of Internal Medicine and Radboud Center for Infectious DiseasesRadboud Institute of Medical Life Sciences, Radboud University Medical CenterNijmegenthe Netherlands
| | - Mirjam Langeveld
- Department of Endocrinology and MetabolismAmsterdam University Medical Centers, location AMC, University of AmsterdamAmsterdamThe Netherlands
| | - Dirk Lefeber
- United for Metabolic DiseasesAmsterdamThe Netherlands
- Translational Metabolic Laboratory, Department of Laboratory MedicineRadboud University Medical CenterNijmegenThe Netherlands
- Department of Neurology, Donders Institute for BrainCognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
| | - Johannes A. Mayr
- University Children's Hospital, Paracelsus Medical UniversitySalzburgAustria
| | - Charlotte W. Ockeloen
- Department of Human GeneticsRadboud Institute for Molecular LifesciencesNijmegenThe Netherlands
| | - Holger Prokisch
- School of MedicineInstitute of Human Genetics, Technical University Munich and Institute of NeurogenomicsNeuherbergGermany
| | - Richard Rodenburg
- Radboud Center for Mitochondrial and Metabolic MedicineTranslational Metabolic Laboratory, Department of Pediatrics, Radboud University Medical CenterNijmegenThe Netherlands
| | - Hans R. Waterham
- United for Metabolic DiseasesAmsterdamThe Netherlands
- Laboratory Genetic Metabolic Diseases, Department of Clinical ChemistryAmsterdam University Medical Centers, location AMC, University of AmsterdamAmsterdamThe Netherlands
| | - Ron A. Wevers
- United for Metabolic DiseasesAmsterdamThe Netherlands
- Translational Metabolic Laboratory, Department of Laboratory MedicineRadboud University Medical CenterNijmegenThe Netherlands
| | - Bart P. C. van de Warrenburg
- Department of Neurology, Donders Institute for BrainCognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
| | - Michel A. A. P. Willemsen
- Departments of Pediatric Neurology and PediatricsAmalia Children's Hospital, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical CenterNijmegenThe Netherlands
| | - Nicole I. Wolf
- Amsterdam Leukodystrophy Center, Department of Child NeurologyEmma Children's Hospital, Amsterdam University Medical Centers, Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Lisenka E. L. M. Vissers
- Department of Human GeneticsDonders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
| | - Clara D. M. van Karnebeek
- Radboud Center for Mitochondrial and Metabolic Medicine, Department of PediatricsAmalia Children's Hospital, Radboud University Medical CenterNijmegenThe Netherlands
- United for Metabolic DiseasesAmsterdamThe Netherlands
- Department of Human GeneticsAmsterdam UMC, University of Amsterdam, Amsterdam Reproduction and Development Research InstituteAmsterdamThe Netherlands
- Department of Pediatrics, Emma Center for Personalized MedicineAmsterdam University Medical Centers, Amsterdam, Amsterdam Genetics Endocrinology Metabolism Research Institute, University of AmsterdamAmsterdamThe Netherlands
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15
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Fan W, Eklund E, Sherman RM, Liu H, Pitts S, Ford B, Rajeshkumar NV, Laiho M. Widespread genetic heterogeneity of human ribosomal RNA genes. RNA (NEW YORK, N.Y.) 2022; 28:478-492. [PMID: 35110373 PMCID: PMC8925967 DOI: 10.1261/rna.078925.121] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 12/28/2021] [Indexed: 05/28/2023]
Abstract
Polymorphism drives survival under stress and provides adaptability. Genetic polymorphism of ribosomal RNA (rRNA) genes derives from internal repeat variation of this multicopy gene, and from interindividual variation. A considerable amount of rRNA sequence heterogeneity has been proposed but has been challenging to estimate given the scarcity of accurate reference sequences. We identified four rDNA copies on chromosome 21 (GRCh38) with 99% similarity to recently introduced reference sequence KY962518.1. We customized a GATK bioinformatics pipeline using the four rDNA loci, spanning a total 145 kb, for variant calling and used high-coverage whole-genome sequencing (WGS) data from the 1000 Genomes Project to analyze variants in 2504 individuals from 26 populations. We identified a total of 3791 variant positions. The variants positioned nonrandomly on the rRNA gene. Invariant regions included the promoter, early 5' ETS, most of 18S, 5.8S, ITS1, and large areas of the intragenic spacer. A total of 470 variant positions were observed on 28S rRNA. The majority of the 28S rRNA variants were located on highly flexible human-expanded rRNA helical folds ES7L and ES27L, suggesting that these represent positions of diversity and are potentially under continuous evolution. Several variants were validated based on RNA-seq analyses. Population analyses showed remarkable ancestry-linked genetic variance and the presence of both high penetrance and frequent variants in the 5' ETS, ITS2, and 28S regions segregating according to the continental populations. These findings provide a genetic view of rRNA gene array heterogeneity and raise the need to functionally assess how the 28S rRNA variants affect ribosome functions.
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Affiliation(s)
- Wenjun Fan
- Department of Radiation Oncology and Molecular Radiation Sciences, and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Eetu Eklund
- Department of Radiation Oncology and Molecular Radiation Sciences, and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Rachel M Sherman
- Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland 21287, USA
| | - Hester Liu
- Department of Radiation Oncology and Molecular Radiation Sciences, and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Stephanie Pitts
- Department of Radiation Oncology and Molecular Radiation Sciences, and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Brittany Ford
- Drug Research Program, Faculty of Pharmacy, University of Helsinki, 00014 Helsinki, Finland
| | - N V Rajeshkumar
- Department of Radiation Oncology and Molecular Radiation Sciences, and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
| | - Marikki Laiho
- Department of Radiation Oncology and Molecular Radiation Sciences, and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287, USA
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16
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Zhou G, Zhou M, Zeng F, Zhang N, Sun Y, Qiao Z, Guo X, Zhou S, Yun G, Xie J, Wang X, Liu F, Fan C, Wang Y, Fang Z, Tian Z, Dai W, Sun J, Peng Z, Song L. Performance characterization of PCR-free whole genome sequencing for clinical diagnosis. Medicine (Baltimore) 2022; 101:e28972. [PMID: 35451387 PMCID: PMC8913097 DOI: 10.1097/md.0000000000028972] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 02/10/2022] [Indexed: 01/04/2023] Open
Abstract
To evaluate the performance of polymerase chain reaction (PCR)-free whole genome sequencing (WGS) for clinical diagnosis, and thereby revealing how experimental parameters affect variant detection.Five NA12878 samples were sequenced using MGISEQ-2000. NA12878 samples underwent WGS with differing deoxyribonucleic acid (DNA) input and library preparation protocol (PCR-based vs PCR-free protocols for library preparation). The depth of coverage and genotype quality of each sample were compared. The performance of each sample was measured for sensitivity, coverage of depth and breadth of coverage of disease-related genes, and copy number variants. We also developed a systematic WGS pipeline (PCR-free) for the analysis of 11 clinical cases.In general, NA12878-2 (PCR-free WGS) showed better depth of coverage and genotype quality distribution than NA12878-1 (PCR-based WGS). With a mean depth of ∼40×, the sensitivity of homozygous and heterozygous single nucleotide polymorphisms (SNPs) of NA12878-2 showed higher sensitivity (>99.77% and >99.82%) than NA12878-1, and positive predictive value exceeded 99.98% and 99.07%. The sensitivity and positive predictive value of homozygous and heterozygous indels for NA12878-2 (PCR-free WGS) showed great improvement than NA128878-1. The breadths of coverage for disease-related genes and copy number variants are slightly better for samples with PCR-free library preparation protocol than the sample with PCR-based library preparation protocol. DNA input also influences the performance of variant detection in samples with PCR-free WGS. All the 19 previously confirmed variants in 11 clinical cases were successfully detected by our WGS pipeline (PCR free).Different experimental parameters may affect variant detection for clinical WGS. Clinical scientists should know the range of sensitivity of variants for different methods of WGS, which would be useful when interpreting and delivering clinical reports.
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Affiliation(s)
- Guiju Zhou
- Department Obstetrics and Gynecology, The Second Affiliated Hospital, Anhui Medical University, Hefei, China
| | | | - Fanwei Zeng
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
- Department of Biology, Faculty of Science, University of Copenhagen, Copenhagen, Denmark
| | - Ningzhi Zhang
- Fuyang People's Hospital, 63 Luci Street, Fuyang, Anhui Province, China
| | - Yan Sun
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Zhihong Qiao
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Xueqin Guo
- BGI-Wuhan Clinical Laboratories, BGI-Shenzhen, Wuhan, China
| | - Shihao Zhou
- Department of Genetics and Eugenics, Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal University, Changsha, Hunan Province, China
| | - Guojun Yun
- Rehabilitation Ward, Shenzhen Children's Hospital, 7019 Yitian Road, Futian District, Shenzhen, Guangdong Province, China
| | - Jiansheng Xie
- Department of Prenatal Diagnosis, The University of Hongkong Shenzhen Hospital, 1 Haiyuan one Road, Shenzhen, Guangdong Province, China
| | - Xiaodan Wang
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Fengxia Liu
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Chunna Fan
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Yaoshen Wang
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Zhonghai Fang
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Zhongming Tian
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Wentao Dai
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Jun Sun
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
| | - Zhiyu Peng
- BGI Genomics, BGI-Shenzhen, Shenzhen, China
| | - Lijie Song
- Tianjin Medical Laboratory, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Binhai Genomics Institute, BGI-Tianjin, BGI-Shenzhen, Tianjin, China
- Bacterial Interactions and Evolution Group, Bioengineering, Technical University of Denmark, Kongens Lyngby, Denmark
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17
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Xu J, Li L, Ren J, Zhong X, Xie C, Zheng A, Abudukadier A, Tuerxun M, Zhang S, Tang L, Hairoula D, Zou X. Whole-Exome Sequencing Implicates the USP34 rs777591A > G Intron Variant in Chronic Obstructive Pulmonary Disease in a Kashi Cohort. Front Cell Dev Biol 2022; 9:792027. [PMID: 35198563 PMCID: PMC8859106 DOI: 10.3389/fcell.2021.792027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Accepted: 12/08/2021] [Indexed: 12/17/2022] Open
Abstract
Genetic factors are important factors in chronic obstructive pulmonary disease (COPD) onset. Plenty of risk and new causative genes for COPD have been identified in patients of the Chinese Han population. In contrast, we know considerably little concerning the genetics in the Kashi COPD population (Uyghur). This study aims at clarifying the genetic maps regarding COPD susceptibility in Kashi (China). Whole-exome sequencing (WES) was used to analyze three Uyghur families with COPD in Kashi (eight patients and one healthy control). Sanger sequencing was also used to verify the WES results in 541 unrelated Uyghur COPD patients and 534 Uyghur healthy controls. WES showed 72 single nucleotide variants (SNVs), two deletions, and small insertions (InDels), 26 copy number variants (CNVs), and 34 structural variants (SVs), including g.71230620T > A (rs12449210T > A, NC_000,016.10) in the HYDIN axonemal central pair apparatus protein (HYDIN) gene and g.61190482A > G (rs777591A > G, NC_000002.12) in the ubiquitin-specific protease 34 (USP34) gene. After Sanger sequencing, we found that rs777591“AA” under different genetic models except for the dominant model (adjusted OR = 0.8559, 95%CI 0.6568–1.115, p > .05), could significantly reduce COPD risk, but rs12449210T > A was not related to COPD. In stratified analysis of smoking status, rs777591“AA” reduced COPD risk significantly among the nonsmoker group. Protein and mRNA expression of USP34 in cigarette smoke extract-treated BEAS-2b cells increased significantly compared with those in the control group. Our findings associate the USP34 rs777591“AA” genotype as a protector factor in COPD.
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Affiliation(s)
- Jingran Xu
- Department of Medical College, Shihezi University, Shihezi, China
| | - Li Li
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Jie Ren
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Xuemei Zhong
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Chengxin Xie
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Aifang Zheng
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Ayiguzali Abudukadier
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Maimaitiaili Tuerxun
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Sujie Zhang
- Department of Medical College, Shihezi University, Shihezi, China
| | - Lifeng Tang
- Department of Medical College, Shihezi University, Shihezi, China
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Dilare Hairoula
- Department of Medical College, Shihezi University, Shihezi, China
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
| | - Xiaoguang Zou
- Department of Medical College, Shihezi University, Shihezi, China
- Department of Respiratory and Critical Care Medicine, First People’s Hospital of Kashi, Kashi, China
- *Correspondence: Xiaoguang Zou,
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18
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Belova V, Pavlova A, Afasizhev R, Moskalenko V, Korzhanova M, Krivoy A, Cheranev V, Nikashin B, Bulusheva I, Rebrikov D, Korostin D. System analysis of the sequencing quality of human whole exome samples on BGI NGS platform. Sci Rep 2022; 12:609. [PMID: 35022470 PMCID: PMC8755732 DOI: 10.1038/s41598-021-04526-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 12/16/2021] [Indexed: 12/05/2022] Open
Abstract
Human exome sequencing is a classical method used in most medical genetic applications. The leaders in the field are the manufacturers of enrichment kits based on hybridization of cRNA or cDNA biotinylated probes specific for a genomic region of interest. Recently, the platforms manufactured by the Chinese company MGI Tech have become widespread in Europe and Asia. The reliability and quality of the obtained data are already beyond any doubt. However, only a few kits compatible with these sequencers can be used for such specific tasks as exome sequencing. We developed our own solution for library pre-capture pooling and exome enrichment with Agilent probes. In this work, using a set of the standard benchmark samples from the Platinum Genome collection, we demonstrate that the qualitative and quantitative parameters of our protocol which we called "RSMU_exome" exceed those of the MGI Tech kit. Our protocol allows for identifying more SNV and indels, generates fewer PCR duplicates, enables pooling of more samples in a single enrichment procedure, and requires less raw data to obtain results comparable with the MGI Tech's protocol. The cost of our protocol is also lower than that of MGI Tech's solution.
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Affiliation(s)
- Vera Belova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997.
| | - Anna Pavlova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
| | - Robert Afasizhev
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
| | - Viktoriya Moskalenko
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
| | - Margarita Korzhanova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
| | - Andrey Krivoy
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
| | - Valery Cheranev
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
| | - Boris Nikashin
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
| | - Irina Bulusheva
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
| | - Denis Rebrikov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
| | - Dmitriy Korostin
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Medical University, Ostovityanova str. 1, Moscow, Russian Federation, 117997
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19
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Zou D, Wang L, Liao J, Xiao H, Duan J, Zhang T, Li J, Yin Z, Zhou J, Yan H, Huang Y, Zhan N, Yang Y, Ye J, Chen F, Zhu S, Wen F, Guo J. Genome sequencing of 320 Chinese children with epilepsy: a clinical and molecular study. Brain 2021; 144:3623-3634. [PMID: 34145886 PMCID: PMC8719847 DOI: 10.1093/brain/awab233] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Revised: 05/25/2021] [Accepted: 06/05/2021] [Indexed: 02/05/2023] Open
Abstract
The aim of this study is to evaluate the diagnostic value of genome sequencing in children with epilepsy, and to provide genome sequencing-based insights into the molecular genetic mechanisms of epilepsy to help establish accurate diagnoses, design appropriate treatments and assist in genetic counselling. We performed genome sequencing on 320 Chinese children with epilepsy, and interpreted single-nucleotide variants and copy number variants of all samples. The complete pedigree and clinical data of the probands were established and followed up. The clinical phenotypes, treatments, prognoses and genotypes of the patients were analysed. Age at seizure onset ranged from 1 day to 17 years, with a median of 4.3 years. Pathogenic/likely pathogenic variants were found in 117 of the 320 children (36.6%), of whom 93 (29.1%) had single-nucleotide variants, 22 (6.9%) had copy number variants and two had both single-nucleotide variants and copy number variants. Single-nucleotide variants were most frequently found in SCN1A (10/95, 10.5%), which is associated with Dravet syndrome, followed by PRRT2 (8/95, 8.4%), which is associated with benign familial infantile epilepsy, and TSC2 (7/95, 7.4%), which is associated with tuberous sclerosis. Among the copy number variants, there were three with a length <25 kilobases. The most common recurrent copy number variants were 17p13.3 deletions (5/24, 20.8%), 16p11.2 deletions (4/24, 16.7%), and 7q11.23 duplications (2/24, 8.3%), which are associated with epilepsy, developmental retardation and congenital abnormalities. Four particular 16p11.2 deletions and two 15q11.2 deletions were considered to be susceptibility factors contributing to neurodevelopmental disorders associated with epilepsy. The diagnostic yield was 75.0% in patients with seizure onset during the first postnatal month, and gradually decreased in patients with seizure onset at a later age. Forty-two patients (13.1%) were found to be specifically treatable for the underlying genetic cause identified by genome sequencing. Three of them received corresponding targeted therapies and demonstrated favourable prognoses. Genome sequencing provides complete genetic diagnosis, thus enabling individualized treatment and genetic counselling for the parents of the patients. Genome sequencing is expected to become the first choice of methods for genetic testing of patients with epilepsy.
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Affiliation(s)
- Dongfang Zou
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Lin Wang
- BGI-Shenzhen, Shenzhen 518083, China
| | - Jianxiang Liao
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | | | - Jing Duan
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | | | | | | | - Jing Zhou
- BGI-Shenzhen, Shenzhen 518083, China
| | | | | | | | - Ying Yang
- BGI-Shenzhen, Shenzhen 518083, China
| | - Jingyu Ye
- BGI-Shenzhen, Shenzhen 518083, China
| | - Fang Chen
- BGI-Shenzhen, Shenzhen 518083, China
| | - Shida Zhu
- BGI-Shenzhen, Shenzhen 518083, China
| | - Feiqiu Wen
- Department of Hematology and Oncology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Jian Guo
- BGI-Shenzhen, Shenzhen 518083, China
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20
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Chiang YC, Lin PH, Cheng WF. Homologous Recombination Deficiency Assays in Epithelial Ovarian Cancer: Current Status and Future Direction. Front Oncol 2021; 11:675972. [PMID: 34722237 PMCID: PMC8551835 DOI: 10.3389/fonc.2021.675972] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 09/17/2021] [Indexed: 01/02/2023] Open
Abstract
Epithelial ovarian cancer (EOC) patients are generally diagnosed at an advanced stage, usually relapse after initial treatments, which include debulking surgery and adjuvant platinum-based chemotherapy, and eventually have poor 5-year survival of less than 50%. In recent years, promising survival benefits from maintenance therapy with poly(ADP-ribose) polymerase (PARP) inhibitor (PARPi) has changed the management of EOC in newly diagnosed and recurrent disease. Identification of BRCA mutations and/or homologous recombination deficiency (HRD) is critical for selecting patients for PARPi treatment. However, the currently available HRD assays are not perfect predictors of the clinical response to PARPis in EOC patients. In this review, we introduce the concept of synthetic lethality, the rationale of using PARPi when HRD is present in tumor cells, the clinical trials of PARPi incorporating the HRD assays for EOC, the current HRD assays, and other HRD assays in development.
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Affiliation(s)
- Ying-Cheng Chiang
- Department of Obstetrics and Gynecology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Po-Han Lin
- Department of Medical Genetics, National Taiwan University Hospital, Taipei, Taiwan.,Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Wen-Fang Cheng
- Department of Obstetrics and Gynecology, College of Medicine, National Taiwan University, Taipei, Taiwan.,Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.,Graduate Institute of Oncology, College of Medicine, National Taiwan University, Taipei, Taiwan
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21
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Yang C, Harafuji N, O'Connor AK, Kesterson RA, Watts JA, Majmundar AJ, Braun DA, Lek M, Laricchia KM, Fathy HM, Mane S, Shril S, Hildebrandt F, Guay-Woodford LM. Cystin genetic variants cause autosomal recessive polycystic kidney disease associated with altered Myc expression. Sci Rep 2021; 11:18274. [PMID: 34521872 PMCID: PMC8440558 DOI: 10.1038/s41598-021-97046-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 07/22/2021] [Indexed: 11/08/2022] Open
Abstract
Mutation of the Cys1 gene underlies the renal cystic disease in the Cys1cpk/cpk (cpk) mouse that phenocopies human autosomal recessive polycystic kidney disease (ARPKD). Cystin, the protein product of Cys1, is expressed in the primary apical cilia of renal ductal epithelial cells. In previous studies, we showed that cystin regulates Myc expression via interaction with the tumor suppressor, necdin. Here, we demonstrate rescue of the cpk renal phenotype by kidney-specific expression of a cystin-GFP fusion protein encoded by a transgene integrated into the Rosa26 locus. In addition, we show that expression of the cystin-GFP fusion protein in collecting duct cells down-regulates expression of Myc in cpk kidneys. Finally, we report the first human patient with an ARPKD phenotype due to homozygosity for a deleterious splicing variant in CYS1. These findings suggest that mutations in Cys1/CYS1 cause an ARPKD phenotype in mouse and human, respectively, and that the renal cystic phenotype in the mouse is driven by overexpression of the Myc proto-oncogene.
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Affiliation(s)
- Chaozhe Yang
- Center for Translational Research, Children's National Research Institute, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Naoe Harafuji
- Center for Translational Research, Children's National Research Institute, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Amber K O'Connor
- Center for Translational Research, Children's National Research Institute, 111 Michigan Ave NW, Washington, DC, 20010, USA
| | - Robert A Kesterson
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Jacob A Watts
- Center for Translational Research, Children's National Research Institute, 111 Michigan Ave NW, Washington, DC, 20010, USA
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - Amar J Majmundar
- Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Daniela A Braun
- Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Monkol Lek
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kristen M Laricchia
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Hanan M Fathy
- Alexandria Faculty of Medicine, University of Alexandria, Alexandria, Egypt
| | - Shrikant Mane
- Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
- Yale Center for Mendelian Genomics, Yale University School of Medicine, New Haven, CT, USA
| | - Shirlee Shril
- Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Friedhelm Hildebrandt
- Department of Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Lisa M Guay-Woodford
- Center for Translational Research, Children's National Research Institute, 111 Michigan Ave NW, Washington, DC, 20010, USA.
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, 35294, USA.
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22
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Krygier M, Mazurkiewicz-Bełdzińska M. Milestones in genetics of cerebellar ataxias. Neurogenetics 2021; 22:225-234. [PMID: 34224032 PMCID: PMC8426223 DOI: 10.1007/s10048-021-00656-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 06/23/2021] [Indexed: 11/29/2022]
Abstract
Cerebellar ataxias (CAs) comprise a group of rare, neurological disorders characterized by extensive phenotypic and genetic heterogeneity. The core clinical feature is the cerebellar syndrome, which is often accompanied by other neurological or non-neurological signs. In the last 30 years, our understanding of the CA etiology has increased significantly, and numerous ataxia-associated genes have been discovered. Conventional variants or tandem repeat expansions, localized in the coding or non-coding DNA sequences, lead to hereditary ataxia, which can display different patterns of inheritance. Advances in molecular techniques have enabled a rapid and cost-effective detection of causative variants in a significant number of CA patients. However, despite performing extensive investigations, a definite diagnosis is still unknown in the majority of affected individuals. In this review, we discuss the major advances in the genetics of CAs over the last 30 years, focusing on the impact of next-generation sequencing on the genetic landscape of childhood- and adult-onset CAs. Additionally, we outline possible directions for further genetic research in hereditary and sporadic CAs in the era of increasing application of whole-genome sequencing and genome-wide association studies in various neurological disorders.
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Affiliation(s)
- Magdalena Krygier
- Department of Developmental Neurology, Medical University of Gdańsk, ul. Dębinki 7 80-952, Gdańsk, Poland.
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23
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Lord J, Baralle D. Splicing in the Diagnosis of Rare Disease: Advances and Challenges. Front Genet 2021; 12:689892. [PMID: 34276790 PMCID: PMC8280750 DOI: 10.3389/fgene.2021.689892] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 06/07/2021] [Indexed: 12/13/2022] Open
Abstract
Mutations which affect splicing are significant contributors to rare disease, but are frequently overlooked by diagnostic sequencing pipelines. Greater ascertainment of pathogenic splicing variants will increase diagnostic yields, ending the diagnostic odyssey for patients and families affected by rare disorders, and improving treatment and care strategies. Advances in sequencing technologies, predictive modeling, and understanding of the mechanisms of splicing in recent years pave the way for improved detection and interpretation of splice affecting variants, yet several limitations still prohibit their routine ascertainment in diagnostic testing. This review explores some of these advances in the context of clinical application and discusses challenges to be overcome before these variants are comprehensively and routinely recognized in diagnostics.
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Affiliation(s)
- Jenny Lord
- School of Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
| | - Diana Baralle
- School of Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, United Kingdom
- Wessex Clinical Genetics Service, University Hospital Southampton NHS Foundation Trust, Southampton, United Kingdom
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24
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Lee IH, Lin Y, Alvarez WJ, Hernandez-Ferrer C, Mandl KD, Kong SW. WEScover: selection between clinical whole exome sequencing and gene panel testing. BMC Bioinformatics 2021; 22:259. [PMID: 34016036 PMCID: PMC8139020 DOI: 10.1186/s12859-021-04178-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 05/09/2021] [Indexed: 11/18/2022] Open
Abstract
Background Whole exome sequencing (WES) is widely adopted in clinical and research settings; however, one of the practical concerns is the potential false negatives due to incomplete breadth and depth of coverage for several exons in clinically implicated genes. In some cases, a targeted gene panel testing may be a dependable option to ascertain true negatives for genomic variants in known disease-associated genes. We developed a web-based tool to quickly gauge whether all genes of interest would be reliably covered by WES or whether targeted gene panel testing should be considered instead to minimize false negatives in candidate genes. Results WEScover is a novel web application that provides an intuitive user interface for discovering breadth and depth of coverage across population-scale WES datasets, searching either by phenotype, by targeted gene panel(s) or by gene(s). Moreover, the application shows metrics from the Genome Aggregation Database to provide gene-centric view on breadth of coverage. Conclusions WEScover allows users to efficiently query genes and phenotypes for the coverage of associated exons by WES and recommends use of panel tests for the genes with potential incomplete coverage by WES. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04178-5.
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Affiliation(s)
- In-Hee Lee
- Computational Health Informatics Program, Boston Children's Hospital, 401 Park Drive, Mail Stop BCH3187, LM5528.4, Boston, MA, 02115, USA
| | - Yufei Lin
- Computational Health Informatics Program, Boston Children's Hospital, 401 Park Drive, Mail Stop BCH3187, LM5528.4, Boston, MA, 02115, USA
| | - William Jefferson Alvarez
- Computational Health Informatics Program, Boston Children's Hospital, 401 Park Drive, Mail Stop BCH3187, LM5528.4, Boston, MA, 02115, USA.,Agios Pharmaceuticals, Boston, MA, USA
| | - Carles Hernandez-Ferrer
- Computational Health Informatics Program, Boston Children's Hospital, 401 Park Drive, Mail Stop BCH3187, LM5528.4, Boston, MA, 02115, USA.,Centre Nacional d'Anàlisi Genòmica (CNAG-CRG), Barcelona, Spain
| | - Kenneth D Mandl
- Computational Health Informatics Program, Boston Children's Hospital, 401 Park Drive, Mail Stop BCH3187, LM5528.4, Boston, MA, 02115, USA.,Department of Pediatrics, Harvard Medical School, Boston, MA, 02115, USA.,Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA
| | - Sek Won Kong
- Computational Health Informatics Program, Boston Children's Hospital, 401 Park Drive, Mail Stop BCH3187, LM5528.4, Boston, MA, 02115, USA. .,Department of Pediatrics, Harvard Medical School, Boston, MA, 02115, USA.
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25
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Zhou J, Zhang M, Li X, Wang Z, Pan D, Shi Y. Performance comparison of four types of target enrichment baits for exome DNA sequencing. Hereditas 2021; 158:10. [PMID: 33597004 PMCID: PMC7888174 DOI: 10.1186/s41065-021-00171-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 01/19/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Next-generation sequencing technology is developing rapidly and target capture sequencing has become an important technique. Several different platforms for library preparation and target capture with different bait types respectively are commercially available. Here we compare the performance of the four platforms with different bait types to find out their advantages and limitations. The purpose of this study is to help investigators and clinicians select the appropriate platform for their particular application and lay the foundation for the development of a better target capture platform for next-generation sequencing. RESULTS We formulate capture efficiency as a novel parameter that can be used to better evaluations of specificity and coverage depth among the different capture platforms. Target coverage, capture efficiency, GC bias, AT Dropout, sensitivity in single nucleotide polymorphisms, small insertions and deletions detection, and the feature of each platform were compared for low input samples. In general, all platforms perform well and small differences among them are revealed. In our results, RNA baits have stronger binding power than DNA baits, and with ultra deep sequencing, double stranded RNA baits perform better than single stranded RNA baits in all aspects. DNA baits got better performance in the region with high GC content and RNA baits got lower AT dropout suggesting that the binding power is different between DNA and RNA baits to genome regions with different characteristics. CONCLUSIONS The platforms with double stranded RNA baits have the most balanced capture performance. Our results show the key differences in performance among the four updated platforms with four different bait types. The better performance of double stranded RNA bait with ultra deep sequencing suggests that it may improve the sensitivity of ultra low frequent mutation detection. In addition, we further propose that the mixed baits of double stranded RNA and single stranded DNA may improve target capture performance.
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Grants
- 2017YFC0908105, 2019YFA0905400 the National Key R&D Program of China
- 2017SHZDZX01 Shanghai Municipal Science and Technology Major Project
- U1804284, 81421061, 81701321, 32070679, 81501154 the Natural Science Foundation of China
- 15XD1502200 the Program of Shanghai Subject Chief Scientist
- 13dz2260500 the National Program for Support of Top-Notch Young Professionals, Shanghai Key Laboratory of Psychotic Disorders
- SHDC12016115 the National Program for Support of Top-Notch Young Professionals, Shanghai Hospital Development Center
- 17JC1402900, 17490712200, 18DZ2260200 Shanghai Municipal Commission of Science and Technology
- ZK2015B01, 201540114 shanghai municipal health commission
- 19X150010012 Scientific Research and Development Fund of Shanghai Jiao Tong University
- the National Key R&D Program of China
- the National Program for Support of Top-Notch Young Professionals, Shanghai Hospital Development Center
- shanghai municipal health commission
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Affiliation(s)
- Juan Zhou
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Mancang Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Xiaoqi Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Zhuo Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Dun Pan
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Collaborative Innovation Center for Brain Science, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China.
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26
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Caspar SM, Schneider T, Stoll P, Meienberg J, Matyas G. Potential of whole-genome sequencing-based pharmacogenetic profiling. Pharmacogenomics 2021; 22:177-190. [PMID: 33517770 DOI: 10.2217/pgs-2020-0155] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Pharmacogenetics represents a major driver of precision medicine, promising individualized drug selection and dosing. Traditionally, pharmacogenetic profiling has been performed using targeted genotyping that focuses on common/known variants. Recently, whole-genome sequencing (WGS) is emerging as a more comprehensive short-read next-generation sequencing approach, enabling both gene diagnostics and pharmacogenetic profiling, including rare/novel variants, in a single assay. Using the example of the pharmacogene CYP2D6, we demonstrate the potential of WGS-based pharmacogenetic profiling as well as emphasize the limitations of short-read next-generation sequencing. In the near future, we envision a shift toward long-read sequencing as the predominant method for gene diagnostics and pharmacogenetic profiling, providing unprecedented data quality and improving patient care.
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Affiliation(s)
- Sylvan Manuel Caspar
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland.,Department of Health Sciences & Technology, Laboratory of Translational Nutrition Biology, ETH Zurich, Schwerzenbach 8603, Switzerland
| | - Timo Schneider
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland
| | - Patricia Stoll
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland
| | - Janine Meienberg
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland
| | - Gabor Matyas
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland.,Zurich Center for Integrative Human Physiology, University of Zurich, Zurich 8057, Switzerland
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27
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Di Resta C, Pipitone GB, Carrera P, Ferrari M. Current scenario of the genetic testing for rare neurological disorders exploiting next generation sequencing. Neural Regen Res 2021; 16:475-481. [PMID: 32985468 PMCID: PMC7996035 DOI: 10.4103/1673-5374.293135] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Next generation sequencing is currently a cornerstone of genetic testing in routine diagnostics, allowing for the detection of sequence variants with so far unprecedented large scale, mainly in genetically heterogenous diseases, such as neurological disorders. It is a fast-moving field, where new wet enrichment protocols and bioinformatics tools are constantly being developed to overcome initial limitations. Despite the as yet undiscussed advantages, however, there are still some challenges in data analysis and the interpretation of variants. In this review, we address the current state of next generation sequencing diagnostic testing for inherited human disorders, particularly giving an overview of the available high-throughput sequencing approaches; including targeted, whole-exome and whole-genome sequencing; and discussing the main critical aspects of the bioinformatic process, from raw data analysis to molecular diagnosis.
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Affiliation(s)
- Chiara Di Resta
- Vita-Salute San Raffaele University; Unit of Genomics for Human Disease Diagnosis, Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Paola Carrera
- Unit of Genomics for Human Disease Diagnosis, Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute; Clinical Molecular Biology Laboratory, IRCCS San Raffaele Hospital, Milan, Italy
| | - Maurizio Ferrari
- Vita-Salute San Raffaele University; Unit of Genomics for Human Disease Diagnosis, Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute; Clinical Molecular Biology Laboratory, IRCCS San Raffaele Hospital, Milan, Italy
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28
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Díaz-de Usera A, Lorenzo-Salazar JM, Rubio-Rodríguez LA, Muñoz-Barrera A, Guillen-Guio B, Marcelino-Rodríguez I, García-Olivares V, Mendoza-Alvarez A, Corrales A, Íñigo-Campos A, González-Montelongo R, Flores C. Evaluation of Whole-Exome Enrichment Solutions: Lessons from the High-End of the Short-Read Sequencing Scale. J Clin Med 2020; 9:jcm9113656. [PMID: 33202991 PMCID: PMC7696786 DOI: 10.3390/jcm9113656] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 11/10/2020] [Accepted: 11/10/2020] [Indexed: 12/13/2022] Open
Abstract
Whole-exome sequencing has become a popular technique in research and clinical settings, assisting in disease diagnosis and increasing the understanding of disease pathogenesis. In this study, we aimed to compare common enrichment capture solutions available in the market. Peripheral blood-purified DNA samples were enriched with SureSelectQXT V6 (Agilent) and various Illumina solutions: TruSeq DNA Nano, TruSeq DNA Exome, Nextera DNA Exome, and Illumina DNA Prep with Enrichment, and sequenced on a HiSeq 4000. We found that their percentage of duplicate reads was as much as 2 times higher than previously reported values for the previous HiSeq series. SureSelectQXT and Illumina DNA Prep with Enrichment showed the best average on-target coverage, which improved when off-target regions were included. At high coverage levels and in shared bases, these two solutions and TruSeq DNA Exome provided three of the best performances. With respect to the number of small variants detected, SureSelectQXT presented the lowest number of detected variants in target regions. When off-target regions were considered, its ability equalized to other solutions. Our results show SureSelectQXT and Illumina DNA Prep with Enrichment to be the best enrichment capture solutions.
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Affiliation(s)
- Ana Díaz-de Usera
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), 38600 Santa Cruz de Tenerife, Spain; (A.D.-d.U.); (J.M.L.-S.); (L.A.R.-R.); (A.M.-B.); (V.G.-O.); (A.Í.-C.); (R.G.-M.)
| | - Jose M. Lorenzo-Salazar
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), 38600 Santa Cruz de Tenerife, Spain; (A.D.-d.U.); (J.M.L.-S.); (L.A.R.-R.); (A.M.-B.); (V.G.-O.); (A.Í.-C.); (R.G.-M.)
| | - Luis A. Rubio-Rodríguez
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), 38600 Santa Cruz de Tenerife, Spain; (A.D.-d.U.); (J.M.L.-S.); (L.A.R.-R.); (A.M.-B.); (V.G.-O.); (A.Í.-C.); (R.G.-M.)
| | - Adrián Muñoz-Barrera
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), 38600 Santa Cruz de Tenerife, Spain; (A.D.-d.U.); (J.M.L.-S.); (L.A.R.-R.); (A.M.-B.); (V.G.-O.); (A.Í.-C.); (R.G.-M.)
| | - Beatriz Guillen-Guio
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, 38010 Santa Cruz de Tenerife, Spain; (B.G.-G.); (I.M.-R.); (A.M.-A.); (A.C.)
| | - Itahisa Marcelino-Rodríguez
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, 38010 Santa Cruz de Tenerife, Spain; (B.G.-G.); (I.M.-R.); (A.M.-A.); (A.C.)
- Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, 38200 San Cristóbal de La Laguna, Spain
| | - Víctor García-Olivares
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), 38600 Santa Cruz de Tenerife, Spain; (A.D.-d.U.); (J.M.L.-S.); (L.A.R.-R.); (A.M.-B.); (V.G.-O.); (A.Í.-C.); (R.G.-M.)
| | - Alejandro Mendoza-Alvarez
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, 38010 Santa Cruz de Tenerife, Spain; (B.G.-G.); (I.M.-R.); (A.M.-A.); (A.C.)
| | - Almudena Corrales
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, 38010 Santa Cruz de Tenerife, Spain; (B.G.-G.); (I.M.-R.); (A.M.-A.); (A.C.)
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Antonio Íñigo-Campos
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), 38600 Santa Cruz de Tenerife, Spain; (A.D.-d.U.); (J.M.L.-S.); (L.A.R.-R.); (A.M.-B.); (V.G.-O.); (A.Í.-C.); (R.G.-M.)
| | - Rafaela González-Montelongo
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), 38600 Santa Cruz de Tenerife, Spain; (A.D.-d.U.); (J.M.L.-S.); (L.A.R.-R.); (A.M.-B.); (V.G.-O.); (A.Í.-C.); (R.G.-M.)
| | - Carlos Flores
- Genomics Division, Instituto Tecnológico y de Energías Renovables (ITER), 38600 Santa Cruz de Tenerife, Spain; (A.D.-d.U.); (J.M.L.-S.); (L.A.R.-R.); (A.M.-B.); (V.G.-O.); (A.Í.-C.); (R.G.-M.)
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, 38010 Santa Cruz de Tenerife, Spain; (B.G.-G.); (I.M.-R.); (A.M.-A.); (A.C.)
- Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, 38200 San Cristóbal de La Laguna, Spain
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, 28029 Madrid, Spain
- Correspondence: ; Tel.: +34-922-602938
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29
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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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30
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Haunschild CE, Tewari KS. The current landscape of molecular profiling in the treatment of epithelial ovarian cancer. Gynecol Oncol 2020; 160:333-345. [PMID: 33055011 DOI: 10.1016/j.ygyno.2020.09.043] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 09/27/2020] [Indexed: 01/05/2023]
Abstract
Advances in next generation sequencing have allowed for rapid and economical germline and tumor genomic profiling. Targeted therapies based on molecular tumor profiling are now integrated into treatment guidelines for many solid tumors. In epithelial ovarian cancer, 50% of tumors possess damaging mutations in homologous recombination repair genes (aka homologous recombination deficiency or HRD) which includes the BRCA genes. Deleterious BRCA mutations and HRD have recently emerged as predictive biomarkers for the use of PARP inhibitors in ovarian cancer. Every patient with ovarian cancer must be referred for genetic counseling and germline testing for BRCA mutations. Multigene panel genetic testing may be more informative and cost-effective than limited testing of cancer susceptibility genes. Patients without a germline deleterious BRCA mutation must be assessed for a somatic BRCA mutation. Assays for HRD may help guide treatment options in women who do not have a BRCA mutation. Currently, all patients with a germline or somatic BRCA mutation should be offered upfront maintenance therapy with a PARP inhibitor. During May 2020, options for maintenance therapy with a PARP inhibitor were expanded to patients with HRD and HR-proficient tumors.
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Affiliation(s)
- Carolyn E Haunschild
- The Division of Gynecologic Oncology, The Chao Family Comprehensive Cancer Center, University of California, Irvine Medical Center, United States of America
| | - Krishnansu S Tewari
- The Division of Gynecologic Oncology, The Chao Family Comprehensive Cancer Center, University of California, Irvine Medical Center, United States of America.
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31
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A comparative study of single nucleotide variant detection performance using three massively parallel sequencing methods. PLoS One 2020; 15:e0239850. [PMID: 32986766 PMCID: PMC7521702 DOI: 10.1371/journal.pone.0239850] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 09/14/2020] [Indexed: 12/22/2022] Open
Abstract
Massively parallel sequencing (MPS) has revolutionised clinical genetics and research within human genetics by enabling the detection of variants in multiple genes in several samples at the same time. Today, multiple approaches for MPS of DNA are available, including targeted gene sequencing (TGS) panels, whole exome sequencing (WES), and whole genome sequencing (WGS). As MPS is becoming an integrated part of the work in genetic laboratories, it is important to investigate the variant detection performance of the various MPS methods. We compared the results of single nucleotide variant (SNV) detection of three MPS methods: WGS, WES, and HaloPlex target enrichment sequencing (HES) using matched DNA of 10 individuals. The detection performance was investigated in 100 genes associated with cardiomyopathies and channelopathies. The results showed that WGS overall performed better than those of WES and HES. WGS had a more uniform and widespread coverage of the investigated regions compared to WES and HES, which both had a right-skewed coverage distribution and difficulties in covering regions and genes with high GC-content. WGS and WES showed roughly the same high sensitivities for detection of SNVs, whereas HES showed a lower sensitivity due to a higher number of false negative results.
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32
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Bailey MH, Meyerson WU, Dursi LJ, Wang LB, Dong G, Liang WW, Weerasinghe A, Li S, Li Y, Kelso S, Saksena G, Ellrott K, Wendl MC, Wheeler DA, Getz G, Simpson JT, Gerstein MB, Ding L. Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples. Nat Commun 2020; 11:4748. [PMID: 32958763 PMCID: PMC7505971 DOI: 10.1038/s41467-020-18151-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 07/28/2020] [Indexed: 02/03/2023] Open
Abstract
The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.
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Affiliation(s)
- Matthew H Bailey
- The McDonnell Genome Institute at Washington University, St. Louis, MO, 63108, USA
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
- Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - William U Meyerson
- Yale School of Medicine, Yale University, New Haven, CT, 06520, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Lewis Jonathan Dursi
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, M5G 0A3, Canada
- The Hospital for Sick Children, Toronto, ON, M5G 1X8, Canada
| | - Liang-Bo Wang
- The McDonnell Genome Institute at Washington University, St. Louis, MO, 63108, USA
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Guanlan Dong
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Wen-Wei Liang
- The McDonnell Genome Institute at Washington University, St. Louis, MO, 63108, USA
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Amila Weerasinghe
- The McDonnell Genome Institute at Washington University, St. Louis, MO, 63108, USA
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Shantao Li
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Yize Li
- The McDonnell Genome Institute at Washington University, St. Louis, MO, 63108, USA
| | - Sean Kelso
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA
| | - Gordon Saksena
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Kyle Ellrott
- Biomedical Engineering, Oregon Health and Science University, Portland, OR, 97239, USA
| | - Michael C Wendl
- The McDonnell Genome Institute at Washington University, St. Louis, MO, 63108, USA
- Department of Mathematics, Washington University in St. Louis, St. Louis, MO, 63130, USA
- Department of Genetics, Washington University School of Medicine, St.Louis, MO, 63110, USA
| | - David A Wheeler
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Gad Getz
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Harvard Medical School, Boston, MA, 02115, USA
- Center for Cancer Research, Massachusetts General Hospital, Boston, MA, 02114, USA
- Department of Pathology, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Jared T Simpson
- Computational Biology Program, Ontario Institute for Cancer Research, Toronto, ON, M5G 0A3, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, M5S, Canada
| | - Mark B Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA.
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA.
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA.
| | - Li Ding
- The McDonnell Genome Institute at Washington University, St. Louis, MO, 63108, USA.
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, 63108, USA.
- Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, 63108, USA.
- Department of Medicine and Department of Genetics, Washington University School of Medicine, St. Louis, MO, 63110, USA.
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33
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Hakonen AH, Lehtonen J, Kivirikko S, Keski-Filppula R, Moilanen J, Kivisaari R, Almusa H, Jakkula E, Saarela J, Avela K, Aittomäki K. Recessive MYH3 variants cause "Contractures, pterygia, and variable skeletal fusions syndrome 1B" mimicking Escobar variant multiple pterygium syndrome. Am J Med Genet A 2020; 182:2605-2610. [PMID: 32902138 DOI: 10.1002/ajmg.a.61836] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 07/06/2020] [Accepted: 08/01/2020] [Indexed: 11/09/2022]
Abstract
The multiple pterygium syndromes (MPS) are rare disorders with disease severity ranging from lethal to milder forms. The nonlethal Escobar variant MPS (EVMPS) is characterized by multiple pterygia and arthrogryposis, as well as various additional features including congenital anomalies. The genetic etiology of EVMPS is heterogeneous and the diagnosis has been based either on the detection of pathogenic CHRNG variants (~23% of patients), or suggestive clinical features. We describe four patients with a clinical suspicion of EVMPS who manifested with multiple pterygia, mild flexion contractures of several joints, and vertebral anomalies. We revealed recessively inherited MYH3 variants as the underlying cause in all patients: two novel variants, c.1053C>G, p.(Tyr351Ter) and c.3102+5G>C, as compound heterozygous with the hypomorphic MYH3 variant c.-9+1G>A. Recessive MYH3 variants have been previously associated with spondylocarpotarsal synostosis syndrome. Our findings now highlight multiple pterygia as an important feature in patients with recessive MYH3 variants. Based on all patients with recessive MYH3 variants reported up to date, we consider that this disease entity should be designated as "Contractures, pterygia, and variable skeletal fusions syndrome 1B," as recently suggested by OMIM. Our findings underline the importance of analyzing MYH3 in the differential diagnosis of EVMPS, particularly as the hypomorphic MYH3 variant might remain undetected by routine exome sequencing.
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Affiliation(s)
- Anna H Hakonen
- Department of Clinical Genetics, HUSLAB, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Johanna Lehtonen
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland.,Folkhälsan Research Center, Helsinki, Finland
| | - Sirpa Kivirikko
- Department of Clinical Genetics, HUSLAB, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Riikka Keski-Filppula
- Department of Clinical Genetics, Oulu University Hospital, Medical Research Center Oulu and PEDEGO Research Unit, University of Oulu, Oulu, Finland
| | - Jukka Moilanen
- Department of Clinical Genetics, Oulu University Hospital, Medical Research Center Oulu and PEDEGO Research Unit, University of Oulu, Oulu, Finland
| | - Reetta Kivisaari
- HUS Medical Imaging Center, Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Henrikki Almusa
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland
| | - Eveliina Jakkula
- Department of Clinical Genetics, HUSLAB, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Janna Saarela
- Institute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland.,Centre for Molecular Medicine Norway (NCMM), University of Oslo, Oslo, Norway.,HUSLAB, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Kristiina Avela
- Department of Clinical Genetics, HUSLAB, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Kristiina Aittomäki
- Department of Clinical Genetics, HUSLAB, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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Chinn IK, Orange JS. A 2020 update on the use of genetic testing for patients with primary immunodeficiency. Expert Rev Clin Immunol 2020; 16:897-909. [DOI: 10.1080/1744666x.2020.1814145] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Ivan K. Chinn
- Department of Pediatrics, Section of Immunology, Allergy, and Retrovirology, Baylor College of Medicine, Houston, TX, USA
- Center for Human Immunobiology, Texas Children’s Hospital, Houston, TX, USA
| | - Jordan S. Orange
- Department of Pediatrics, Columbia University College of Physicians and Surgeons, New York, NY, USA
- NewYork-Presbyterian Morgan Stanley Children's Hospita, New York, USA
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Rockowitz S, LeCompte N, Carmack M, Quitadamo A, Wang L, Park M, Knight D, Sexton E, Smith L, Sheidley B, Field M, Holm IA, Brownstein CA, Agrawal PB, Kornetsky S, Poduri A, Snapper SB, Beggs AH, Yu TW, Williams DA, Sliz P. Children's rare disease cohorts: an integrative research and clinical genomics initiative. NPJ Genom Med 2020; 5:29. [PMID: 32655885 PMCID: PMC7338382 DOI: 10.1038/s41525-020-0137-0] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Accepted: 06/03/2020] [Indexed: 12/16/2022] Open
Abstract
While genomic data is frequently collected under distinct research protocols and disparate clinical and research regimes, there is a benefit in streamlining sequencing strategies to create harmonized databases, particularly in the area of pediatric rare disease. Research hospitals seeking to implement unified genomics workflows for research and clinical practice face numerous challenges, as they need to address the unique requirements and goals of the distinct environments and many stakeholders, including clinicians, researchers and sequencing providers. Here, we present outcomes of the first phase of the Children’s Rare Disease Cohorts initiative (CRDC) that was completed at Boston Children’s Hospital (BCH). We have developed a broadly sharable database of 2441 exomes from 15 pediatric rare disease cohorts, with major contributions from early onset epilepsy and early onset inflammatory bowel disease. All sequencing data is integrated and combined with phenotypic and research data in a genomics learning system (GLS). Phenotypes were both manually annotated and pulled automatically from patient medical records. Deployment of a genomically-ordered relational database allowed us to provide a modular and robust platform for centralized storage and analysis of research and clinical data, currently totaling 8516 exomes and 112 genomes. The GLS integrates analytical systems, including machine learning algorithms for automated variant classification and prioritization, as well as phenotype extraction via natural language processing (NLP) of clinical notes. This GLS is extensible to additional analytic systems and growing research and clinical collections of genomic and other types of data.
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Affiliation(s)
- Shira Rockowitz
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115 USA.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA
| | - Nicholas LeCompte
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115 USA.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA
| | - Mary Carmack
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115 USA.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA
| | - Andrew Quitadamo
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115 USA.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA
| | - Lily Wang
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115 USA.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA
| | - Meredith Park
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115 USA.,Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Boston Children's Hospital, Boston, MA 02115 USA
| | - Devon Knight
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115 USA.,Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Boston Children's Hospital, Boston, MA 02115 USA
| | - Emma Sexton
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115 USA.,Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Boston Children's Hospital, Boston, MA 02115 USA
| | - Lacey Smith
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115 USA.,Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Boston Children's Hospital, Boston, MA 02115 USA
| | - Beth Sheidley
- Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115 USA.,Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Boston Children's Hospital, Boston, MA 02115 USA
| | - Michael Field
- Division of Gastroenterology, Hepatology and Nutrition, Boston Children's Hospital, Boston, MA 02115 USA
| | - Ingrid A Holm
- The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA.,Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115 USA
| | - Catherine A Brownstein
- The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA.,Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115 USA
| | - Pankaj B Agrawal
- The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA.,Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115 USA.,Division of Newborn Medicine, Boston Children's Hospital, Boston, MA 02115 USA
| | - Susan Kornetsky
- Research Administration, Boston Children's Hospital, Boston, MA 02115 USA
| | - Annapurna Poduri
- Harvard Medical School, Boston, MA 02115 USA.,Department of Neurology, F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115 USA.,Division of Epilepsy and Clinical Neurophysiology and Epilepsy Genetics Program, Boston Children's Hospital, Boston, MA 02115 USA
| | - Scott B Snapper
- Harvard Medical School, Boston, MA 02115 USA.,Division of Gastroenterology, Hepatology and Nutrition, Boston Children's Hospital, Boston, MA 02115 USA
| | - Alan H Beggs
- The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA.,Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115 USA
| | - Timothy W Yu
- The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA.,Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA 02115 USA
| | - David A Williams
- Harvard Medical School, Boston, MA 02115 USA.,Division of Hematology/Oncology, Dana-Farber/Boston Children's Cancer and Blood Disorders Center, Boston, MA 02115 USA
| | - Piotr Sliz
- Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115 USA.,The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, MA 02115 USA.,Harvard Medical School, Boston, MA 02115 USA
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Shedding light on dark genes: enhanced targeted resequencing by optimizing the combination of enrichment technology and DNA fragment length. Sci Rep 2020; 10:9424. [PMID: 32523024 PMCID: PMC7287100 DOI: 10.1038/s41598-020-66331-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 04/23/2020] [Indexed: 12/16/2022] Open
Abstract
The exome contains many obscure regions difficult to explore with current short-read sequencing methods. Repetitious genomic regions prevent the unique alignment of reads, which is essential for the identification of clinically-relevant genetic variants. Long-read technologies attempt to resolve multiple-mapping regions, but they still produce many sequencing errors. Thus, a new approach is required to enlighten the obscure regions of the genome and rescue variants that would be otherwise neglected. This work aims to improve the alignment of multiple-mapping reads through the extension of the standard DNA fragment size. As Illumina can sequence fragments up to 550 bp, we tested different DNA fragment lengths using four major commercial WES platforms and found that longer DNA fragments achieved a higher genotypability. This metric, which indicates base calling calculated by combining depth of coverage with the confidence of read alignment, increased from hundreds to thousands of genes, including several associated with clinical phenotypes. While depth of coverage has been considered crucial for the assessment of WES performance, we demonstrated that genotypability has a greater impact in revealing obscure regions, with ~1% increase in variant calling in respect to shorter DNA fragments. Results confirmed that this approach enlightened many regions previously not explored.
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Borges MG, Rocha CS, Carvalho BS, Lopes-Cendes I. Methodological differences can affect sequencing depth with a possible impact on the accuracy of genetic diagnosis. Genet Mol Biol 2020; 43:e20190270. [PMID: 32343762 PMCID: PMC7198014 DOI: 10.1590/1678-4685-gmb-2019-0270] [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: 08/28/2019] [Accepted: 02/16/2020] [Indexed: 11/24/2022] Open
Abstract
For a better interpretation of variants, evidence-based databases, such as
ClinVar, compile data on the presumed relationships between variants and
phenotypes. In this study, we aimed to analyze the pattern of sequencing depth
in variants from whole-exome sequencing data in the 1000 Genomes project phase
3, focusing on the variants present in the ClinVar database that were predicted
to affect protein-coding regions. We demonstrate that the distribution of the
sequencing depth varies across different sequencing centers (pair-wise
comparison, p < 0.001). Most importantly, we found that the
distribution pattern of sequencing depth is specific to each facility, making it
possible to correctly assign 96.9% of the samples to their sequencing center.
Thus, indicating the presence of a systematic bias, related to the methods used
in the different facilities, which generates significant variations in breadth
and depth in whole-exome sequencing data in clinically relevant regions. Our
results show that methodological differences, leading to significant
heterogeneity in sequencing depth, may potentially influence the accuracy of
genetic diagnosis. Furthermore, our findings highlight how it is still
challenging to integrate results from different sequencing centers, which may
also have an impact on genomic research.
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Affiliation(s)
- Murilo G Borges
- Universidade Estadual de Campinas (UNICAMP), Faculdade de Ciências Médicas, Departamento de Genética Médica e Medicina Genômica, Campinas, SP, Brazil.,Instituto Brasileiro de Neurociência e Neurotecnologia (BRAINN), Campinas, SP, Brazil.,Universidade Estadual de Campinas (UNICAMP), Instituto de Física "Gleb Wataghin". Campinas, SP, Brazil
| | - Cristiane S Rocha
- Universidade Estadual de Campinas (UNICAMP), Faculdade de Ciências Médicas, Departamento de Genética Médica e Medicina Genômica, Campinas, SP, Brazil.,Instituto Brasileiro de Neurociência e Neurotecnologia (BRAINN), Campinas, SP, Brazil
| | - Benilton S Carvalho
- Instituto Brasileiro de Neurociência e Neurotecnologia (BRAINN), Campinas, SP, Brazil.,Universidade Estadual de Campinas (UNICAMP), Instituto de Matemática, Estatística e Computação Científica, Departamento de Estatística, Campinas, SP, Brazil
| | - Iscia Lopes-Cendes
- Universidade Estadual de Campinas (UNICAMP), Faculdade de Ciências Médicas, Departamento de Genética Médica e Medicina Genômica, Campinas, SP, Brazil.,Instituto Brasileiro de Neurociência e Neurotecnologia (BRAINN), Campinas, SP, Brazil
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38
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Caspar SM, Schneider T, Meienberg J, Matyas G. Added Value of Clinical Sequencing: WGS-Based Profiling of Pharmacogenes. Int J Mol Sci 2020; 21:ijms21072308. [PMID: 32225115 PMCID: PMC7178228 DOI: 10.3390/ijms21072308] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 03/23/2020] [Accepted: 03/24/2020] [Indexed: 12/13/2022] Open
Abstract
Although several pharmacogenetic (PGx) predispositions affecting drug efficacy and safety are well established, drug selection and dosing as well as clinical trials are often performed in a non-pharmacogenetically-stratified manner, ultimately burdening healthcare systems. Pre-emptive PGx testing offers a solution which is often performed using microarrays or targeted gene panels, testing for common/known PGx variants. However, as an added value, whole-genome sequencing (WGS) could detect not only disease-causing but also pharmacogenetically-relevant variants in a single assay. Here, we present our WGS-based pipeline that extends the genetic testing of Mendelian diseases with PGx profiling, enabling the detection of rare/novel PGx variants as well. From our in-house WGS (PCR-free 60× PE150) data of 547 individuals we extracted PGx variants with drug-dosing recommendations of the Dutch Pharmacogenetics Working Group (DPWG). Furthermore, we explored the landscape of DPWG pharmacogenes in gnomAD and our in-house cohort as well as compared bioinformatic tools for WGS-based structural variant detection in CYP2D6. We show that although common/known PGx variants comprise the vast majority of detected DPWG pharmacogene alleles, for better precision medicine, PGx testing should move towards WGS-based approaches. Indeed, WGS-based PGx profiling is not only feasible and future-oriented but also the most comprehensive all-in-one approach without generating significant additional costs.
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Affiliation(s)
- Sylvan M. Caspar
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, 8952 Schlieren-Zurich, Switzerland; (S.M.C.); (T.S.); (J.M.)
- Laboratory of Translational Nutrition Biology, Department of Health Sciences and Technology, ETH Zurich, 8603 Schwerzenbach, Switzerland
| | - Timo Schneider
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, 8952 Schlieren-Zurich, Switzerland; (S.M.C.); (T.S.); (J.M.)
| | - Janine Meienberg
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, 8952 Schlieren-Zurich, Switzerland; (S.M.C.); (T.S.); (J.M.)
| | - Gabor Matyas
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, 8952 Schlieren-Zurich, Switzerland; (S.M.C.); (T.S.); (J.M.)
- Zurich Center for Integrative Human Physiology, University of Zurich, 8057 Zurich, Switzerland
- Correspondence: ; Tel.: +41-43-433-86-86
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Mazzarotto F, Olivotto I, Walsh R. Advantages and Perils of Clinical Whole-Exome and Whole-Genome Sequencing in Cardiomyopathy. Cardiovasc Drugs Ther 2020; 34:241-253. [DOI: 10.1007/s10557-020-06948-4] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Siggs OM, Souzeau E, Pasutto F, Dubowsky A, Smith JEH, Taranath D, Pater J, Rait JL, Narita A, Mauri L, Del Longo A, Reis A, Chappell A, Kearns LS, Staffieri SE, Elder JE, Ruddle JB, Hewitt AW, Burdon KP, Mackey DA, Craig JE. Prevalence of FOXC1 Variants in Individuals With a Suspected Diagnosis of Primary Congenital Glaucoma. JAMA Ophthalmol 2020; 137:348-355. [PMID: 30653210 DOI: 10.1001/jamaophthalmol.2018.5646] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Importance Both primary and secondary forms of childhood glaucoma have many distinct causative mechanisms, and in many cases a cause is not immediately clear. The broad phenotypic spectrum of secondary glaucoma, particularly in individuals with variants in FOXC1 or PITX2 genes associated with Axenfeld-Rieger syndrome, makes it more difficult to diagnose patients with milder phenotypes. These cases are occasionally classified and managed as primary congenital glaucoma. Objective To investigate the prevalence of FOXC1 variants in participants with a suspected diagnosis of primary congenital glaucoma. Design, Setting, and Participants Australian and Italian cohorts were recruited from January 1, 2007, through March 1, 2016. Australian individuals were recruited through the Australian and New Zealand Registry of Advanced Glaucoma and Italian individuals through the Genetic and Ophthalmology Unit of l'Azienda Socio-Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda in Milan, Italy. We performed exome sequencing, in combination with Sanger sequencing and multiplex ligation-dependent probe amplification, to detect variants of FOXC1 in individuals with a suspected diagnosis of primary congenital glaucoma established by their treating specialist. Data analysis was completed from June 2015 to November 2017. Main Outcome and Measures Identification of single-nucleotide and copy number variants in FOXC1, along with phenotypic characterization of the individuals who carried them. Results A total of 131 individuals with a suspected diagnosis of primary congenital glaucoma were included. The mean (SD) age at recruitment in the Australian cohort was 24.3 (18.1) years; 37 of 84 Australian participants (44.0%) were female, and 71 of 84 (84.5%) were of European ancestry. The mean (SD) age at recruitment was 22.5 (18.4) years in the Italian cohort; 21 of 47 Italian participants (44.7%) were female, and 45 of 47 (95.7%) were of European ancestry. We observed rare, predicted deleterious FOXC1 variants in 8 of 131 participants (6.1%), or 8 of 166 participants (4.8%) when including those explained by variants in CYP1B1. On reexamination or reinvestigation, all of these individuals had at least 1 detectable ocular and/or systemic feature associated with Axenfeld-Rieger syndrome. Conclusions and Relevance These data highlight the genetic and phenotypic heterogeneity of childhood glaucoma and support the use of gene panels incorporating FOXC1 as a diagnostic aid, especially because clinical features of Axenfeld-Rieger syndrome can be subtle. Further replication of these results will be needed to support the future use of such panels.
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Affiliation(s)
- Owen M Siggs
- Department of Ophthalmology, Flinders University, Flinders Medical Centre, Adelaide, Australia
| | - Emmanuelle Souzeau
- Department of Ophthalmology, Flinders University, Flinders Medical Centre, Adelaide, Australia
| | - Francesca Pasutto
- Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | | | - James E H Smith
- Department of Ophthalmology, Children's Hospital at Westmead, Sydney, Australia.,Discipline of Ophthalmology, University of Sydney, Sydney, Australia.,Department of Ophthalmology, Macquarie University, Sydney, Australia
| | - Deepa Taranath
- Department of Ophthalmology, Flinders University, Flinders Medical Centre, Adelaide, Australia
| | - John Pater
- Department of Ophthalmology, Flinders University, Flinders Medical Centre, Adelaide, Australia
| | - Julian L Rait
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia
| | | | - Lucia Mauri
- Medical Genetics Unit, Department of Laboratory Medicine, l'Azienda Socio-Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Alessandra Del Longo
- Pediatric Ophthalmology Unit, l'Azienda Socio-Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - André Reis
- Institute of Human Genetics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Angela Chappell
- Department of Ophthalmology, Flinders University, Flinders Medical Centre, Adelaide, Australia
| | - Lisa S Kearns
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia
| | - Sandra E Staffieri
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia.,Department of Ophthalmology, Royal Children's Hospital, Melbourne, Australia
| | - James E Elder
- Department of Ophthalmology, Royal Children's Hospital, Melbourne, Australia.,Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Jonathan B Ruddle
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia.,Department of Ophthalmology, Royal Children's Hospital, Melbourne, Australia
| | - Alex W Hewitt
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, Melbourne, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Melbourne, Australia.,Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - Kathryn P Burdon
- Department of Ophthalmology, Flinders University, Flinders Medical Centre, Adelaide, Australia.,Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - David A Mackey
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia.,Centre for Ophthalmology and Visual Science and Lions Eye Institute, University of Western Australia, Perth, Australia
| | - Jamie E Craig
- Department of Ophthalmology, Flinders University, Flinders Medical Centre, Adelaide, Australia
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Barbitoff YA, Polev DE, Glotov AS, Serebryakova EA, Shcherbakova IV, Kiselev AM, Kostareva AA, Glotov OS, Predeus AV. Systematic dissection of biases in whole-exome and whole-genome sequencing reveals major determinants of coding sequence coverage. Sci Rep 2020; 10:2057. [PMID: 32029882 PMCID: PMC7005158 DOI: 10.1038/s41598-020-59026-y] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 01/22/2020] [Indexed: 12/30/2022] Open
Abstract
Advantages and diagnostic effectiveness of the two most widely used resequencing approaches, whole exome (WES) and whole genome (WGS) sequencing, are often debated. WES dominated large-scale resequencing projects because of lower cost and easier data storage and processing. Rapid development of 3rd generation sequencing methods and novel exome sequencing kits predicate the need for a robust statistical framework allowing informative and easy performance comparison of the emerging methods. In our study we developed a set of statistical tools to systematically assess coverage of coding regions provided by several modern WES platforms, as well as PCR-free WGS. We identified a substantial problem in most previously published comparisons which did not account for mappability limitations of short reads. Using regression analysis and simple machine learning, as well as several novel metrics of coverage evenness, we analyzed the contribution from the major determinants of CDS coverage. Contrary to a common view, most of the observed bias in modern WES stems from mappability limitations of short reads and exome probe design rather than sequence composition. We also identified the ~ 500 kb region of human exome that could not be effectively characterized using short read technology and should receive special attention during variant analysis. Using our novel metrics of sequencing coverage, we identified main determinants of WES and WGS performance. Overall, our study points out avenues for improvement of enrichment-based methods and development of novel approaches that would maximize variant discovery at optimal cost.
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Affiliation(s)
- Yury A Barbitoff
- Bioinformatics Institute, Saint Petersburg, Russia.,Department of Genomic Medicine, D. O. Ott Research Institute of Obstetrics, Gynecology, and Reproduction, Saint Petersburg, Russia.,Department of Genetics and Biotechnology, Saint Petersburg State University, Saint Petersburg, Russia.,Cerbalab LTD, Saint Petersburg, Russia
| | | | - Andrey S Glotov
- Department of Genomic Medicine, D. O. Ott Research Institute of Obstetrics, Gynecology, and Reproduction, Saint Petersburg, Russia.,Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia.,City Hospital №40, Saint Petersburg, Russia.,Institute of Living Systems, Immanuel Kant Baltic Federal University, Kaliningrad, Russia
| | - Elena A Serebryakova
- Department of Genomic Medicine, D. O. Ott Research Institute of Obstetrics, Gynecology, and Reproduction, Saint Petersburg, Russia
| | - Irina V Shcherbakova
- Molecular Biology Division, Biomedical Center, LMU Munich, 82152, Planegg-Martinsried, Germany
| | - Artem M Kiselev
- Almazov National Medical Research Centre, Saint Petersburg, Russia
| | - Anna A Kostareva
- Almazov National Medical Research Centre, Saint Petersburg, Russia
| | - Oleg S Glotov
- Department of Genomic Medicine, D. O. Ott Research Institute of Obstetrics, Gynecology, and Reproduction, Saint Petersburg, Russia.,City Hospital №40, Saint Petersburg, Russia
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Najafi A, Caspar SM, Meienberg J, Rohrbach M, Steinmann B, Matyas G. Variant filtering, digenic variants, and other challenges in clinical sequencing: a lesson from fibrillinopathies. Clin Genet 2020; 97:235-245. [PMID: 31506931 PMCID: PMC7004123 DOI: 10.1111/cge.13640] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 09/04/2019] [Accepted: 09/07/2019] [Indexed: 12/23/2022]
Abstract
Genome-scale high-throughput sequencing enables the detection of unprecedented numbers of sequence variants. Variant filtering and interpretation are facilitated by mutation databases, in silico tools, and population-based reference datasets such as ExAC/gnomAD, while variants are classified using the ACMG/AMP guidelines. These methods, however, pose clinically relevant challenges. We queried the gnomAD dataset for (likely) pathogenic variants in genes causing autosomal-dominant disorders. Furthermore, focusing on the fibrillinopathies Marfan syndrome (MFS) and congenital contractural arachnodactyly (CCA), we screened 500 genomes of our patients for co-occurring variants in FBN1 and FBN2. In gnomAD, we detected 2653 (likely) pathogenic variants in 253 genes associated with autosomal-dominant disorders, enabling the estimation of variant-filtering thresholds and disease predisposition/prevalence rates. In our database, we discovered two families with hitherto unreported co-occurrence of FBN1/FBN2 variants causing phenotypes with mixed or modified MFS/CCA clinical features. We show that (likely) pathogenic gnomAD variants may be more frequent than expected and are challenging to classify according to the ACMG/AMP guidelines as well as that fibrillinopathies are likely underdiagnosed and may co-occur. Consequently, selection of appropriate frequency cutoffs, recognition of digenic variants, and variant classification represent considerable challenges in variant interpretation. Neglecting these challenges may lead to incomplete or missed diagnoses.
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Affiliation(s)
- Arash Najafi
- Center for Cardiovascular Genetics and Gene DiagnosticsFoundation for People with Rare DiseasesSchlieren‐ZurichSwitzerland
- Cantonal Hospital WinterthurInstitute of Radiology and Nuclear MedicineWinterthurSwitzerland
| | - Sylvan M. Caspar
- Center for Cardiovascular Genetics and Gene DiagnosticsFoundation for People with Rare DiseasesSchlieren‐ZurichSwitzerland
| | - Janine Meienberg
- Center for Cardiovascular Genetics and Gene DiagnosticsFoundation for People with Rare DiseasesSchlieren‐ZurichSwitzerland
| | - Marianne Rohrbach
- Division of Metabolism and Children's Research CenterUniversity Children's Hospital Zurich Eleonore FoundationZurichSwitzerland
| | - Beat Steinmann
- Division of Metabolism and Children's Research CenterUniversity Children's Hospital Zurich Eleonore FoundationZurichSwitzerland
| | - Gabor Matyas
- Center for Cardiovascular Genetics and Gene DiagnosticsFoundation for People with Rare DiseasesSchlieren‐ZurichSwitzerland
- Zurich Center for Integrative Human PhysiologyUniversity of ZurichZurichSwitzerland
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Abstract
ctDNA provided by liquid biopsy offers a promising alternative to tumor biopsy as it gives a non-invasive and «real-time» access to the cancer genome and reflects tumor intra and extra heterogeneity. ctDNA has shown growing clinical interest for cancer diagnosis, prognosis, theragnostics, therapeutic monitoring, and clonal evolution tracking. A major technical limit for ctDNA analysis from body fluids is the extremely low proportion of ctDNA compared to non-malignant cell-free DNA, underscoring the need for highly sensitive and specific detection techniques. The control of pre-analytical procedures appears essential for optimal ctDNA analysis and need to be standardized for clinical research applications. This chapter provides insights into major current technologies for ctDNA detection. Overall, PCR-based techniques are able to detect limited molecular alterations and have a high sensitivity suitable for monitoring purposes while NGS-based approaches are broad range molecular screening assays more specifically indicated for treatment selection. We briefly reviewed new technical innovations that are now available for ctDNA detection.
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Affiliation(s)
- Pauline Gilson
- Université de Lorraine, CNRS UMR 7039 CRAN, Institut de Cancérologie de Lorraine, Service de Biopathologie, 54000, Nancy, France.
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Debode F, Hulin J, Charloteaux B, Coppieters W, Hanikenne M, Karim L, Berben G. Detection and identification of transgenic events by next generation sequencing combined with enrichment technologies. Sci Rep 2019; 9:15595. [PMID: 31666537 PMCID: PMC6821802 DOI: 10.1038/s41598-019-51668-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 09/20/2019] [Indexed: 12/12/2022] Open
Abstract
Next generation sequencing (NGS) is a promising tool for analysing the quality and safety of food and feed products. The detection and identification of genetically modified organisms (GMOs) is complex, as the diversity of transgenic events and types of structural elements introduced in plants continue to increase. In this paper, we show how a strategy that combines enrichment technologies with NGS can be used to detect a large panel of structural elements and partially or completely reconstruct the new sequence inserted into the plant genome in a single analysis, even at low GMO percentages. The strategy of enriching sequences of interest makes the approach applicable even to mixed products, which was not possible before due to insufficient coverage of the different genomes present. This approach is also the first step towards a more complete characterisation of agrifood products in a single analysis.
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Affiliation(s)
- Frédéric Debode
- Walloon Agricultural Research Center (CRA-W), Unit Traceability and Authentication, chaussée de Namur 24, 5030, Gembloux, Belgium.
| | - Julie Hulin
- Walloon Agricultural Research Center (CRA-W), Unit Traceability and Authentication, chaussée de Namur 24, 5030, Gembloux, Belgium
| | - Benoît Charloteaux
- University of Liège, GIGA - Genomics Platform, B34, 4000, Liège (Sart Tilman), Belgium
| | - Wouter Coppieters
- University of Liège, GIGA - Genomics Platform, B34, 4000, Liège (Sart Tilman), Belgium
| | - Marc Hanikenne
- University of Liège, InBioS - PhytoSystems, Functional Genomics and Plant Molecular Imaging, Chemin de la Vallée, 4, B22, 4000, Liège (Sart Tilman), Belgium
| | - Latifa Karim
- University of Liège, GIGA - Genomics Platform, B34, 4000, Liège (Sart Tilman), Belgium
| | - Gilbert Berben
- Walloon Agricultural Research Center (CRA-W), Unit Traceability and Authentication, chaussée de Namur 24, 5030, Gembloux, Belgium
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Mahajan MC, McLellan AS. Whole-Exome Sequencing (WES) for Illumina Short Read Sequencers Using Solution-Based Capture. Methods Mol Biol 2019; 2076:85-108. [PMID: 31586323 DOI: 10.1007/978-1-4939-9882-1_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Next-generation sequencing (NGS) is transforming clinical research and diagnostics, vastly enhancing our ability to identify novel disease-causing genetic mutations and perform comprehensive diagnostic testing in the clinic. Whole-exome sequencing (WES) is a commonly used method which captures the majority of coding regions of the genome for sequencing, as these regions contain the majority of disease-causing mutations. The clinical applications of WES are not limited to diagnosis; the technique can be employed to help determine an optimal therapeutic strategy for a patient considering their mutation profile. WES may also be used to predict a patient's risk of developing a disease, e.g., type 2 diabetes (T2D), and can therefore be used to tailor advice for the patient about lifestyle choices that could mitigate those risks. Thus, genome sequencing strategies, such as WES, underpin the emerging field of personalized medicine. Initiatives also exist for sharing WES data in public repositories, e.g., the Exome Aggregation Consortium (ExAC) database. In time, by mining these valuable data resources, we will acquire a better understanding of the roles of both single rare mutations and specific combinations of common mutations (mutation signatures) in the pathology of complex diseases such as diabetes.Herein, we describe a protocol for performing WES on genomic DNA extracted from blood or saliva. Starting with gDNA extraction, we document preparation of a library for sequencing on Illumina instruments and the enrichment of the protein-coding regions from the library using the Roche NimbleGen SeqCap EZ Exome v3 kit; a solution-based capture method. We include details of how to efficiently purify the products of each step using the AMPure XP System and describe how to use qPCR to test the efficiency of capture, and thus determine finished library quality.
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Chinn IK, Chan AY, Chen K, Chou J, Dorsey MJ, Hajjar J, Jongco AM, Keller MD, Kobrynski LJ, Kumanovics A, Lawrence MG, Leiding JW, Lugar PL, Orange JS, Patel K, Platt CD, Puck JM, Raje N, Romberg N, Slack MA, Sullivan KE, Tarrant TK, Torgerson TR, Walter JE. Diagnostic interpretation of genetic studies in patients with primary immunodeficiency diseases: A working group report of the Primary Immunodeficiency Diseases Committee of the American Academy of Allergy, Asthma & Immunology. J Allergy Clin Immunol 2019; 145:46-69. [PMID: 31568798 DOI: 10.1016/j.jaci.2019.09.009] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 09/02/2019] [Accepted: 09/20/2019] [Indexed: 12/19/2022]
Abstract
Genetic testing has become an integral component of the diagnostic evaluation of patients with suspected primary immunodeficiency diseases. Results of genetic testing can have a profound effect on clinical management decisions. Therefore clinical providers must demonstrate proficiency in interpreting genetic data. Because of the need for increased knowledge regarding this practice, the American Academy of Allergy, Asthma & Immunology Primary Immunodeficiency Diseases Committee established a work group that reviewed and summarized information concerning appropriate methods, tools, and resources for evaluating variants identified by genetic testing. Strengths and limitations of tests frequently ordered by clinicians were examined. Summary statements and tables were then developed to guide the interpretation process. Finally, the need for research and collaboration was emphasized. Greater understanding of these important concepts will improve the diagnosis and management of patients with suspected primary immunodeficiency diseases.
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Affiliation(s)
- Ivan K Chinn
- Department of Pediatrics, Baylor College of Medicine, Houston, Tex; Section of Immunology, Allergy, and Rheumatology, Texas Children's Hospital, Houston, Tex.
| | - Alice Y Chan
- Department of Pediatrics, Division of Allergy, Immunology, and Bone Marrow Transplantation, University of California at San Francisco, San Francisco, Calif
| | - Karin Chen
- Division of Allergy and Immunology, Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, Utah
| | - Janet Chou
- Department of Pediatrics, Harvard Medical School, Boston, Mass; Division of Allergy and Immunology, Boston Children's Hospital, Boston, Mass
| | - Morna J Dorsey
- Department of Pediatrics, Division of Allergy, Immunology, and Bone Marrow Transplantation, University of California at San Francisco, San Francisco, Calif
| | - Joud Hajjar
- Department of Pediatrics, Baylor College of Medicine, Houston, Tex; Section of Immunology, Allergy, and Rheumatology, Texas Children's Hospital, Houston, Tex
| | - Artemio M Jongco
- Departments of Medicine and Pediatrics, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Great Neck, NY; Center for Health Innovations and Outcomes Research, Feinstein Institute for Medical Research, Great Neck, NY; Division of Allergy & Immunology, Cohen Children's Medical Center of New York, Great Neck, NY
| | - Michael D Keller
- Department of Allergy and Immunology, Children's National Hospital, Washington, DC
| | - Lisa J Kobrynski
- Department of Pediatrics, Division of Allergy and Immunology, Emory University School of Medicine, Atlanta, Ga
| | - Attila Kumanovics
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minn
| | - Monica G Lawrence
- Department of Medicine, Division of Asthma, Allergy and Immunology, University of Virginia Health System, Charlottesville, Va
| | - Jennifer W Leiding
- Departments of Pediatrics and Medicine, University of South Florida, St Petersburg, Fla; Division of Pediatric Allergy/Immunology, Johns Hopkins-All Children's Hospital, St Petersburg, Fla; Cancer and Blood Disorders Institute, Johns Hopkins-All Children's Hospital, St Petersburg, Fla
| | - Patricia L Lugar
- Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University Medical Center, Durham, NC
| | - Jordan S Orange
- Department of Pediatrics, Columbia University College of Physicians and Surgeons, New York, NY; New York Presbyterian Morgan Stanley Children's Hospital, New York, NY
| | - Kiran Patel
- Department of Pediatrics, Division of Allergy and Immunology, Emory University School of Medicine, Atlanta, Ga
| | - Craig D Platt
- Department of Pediatrics, Harvard Medical School, Boston, Mass; Division of Allergy and Immunology, Boston Children's Hospital, Boston, Mass
| | - Jennifer M Puck
- Department of Pediatrics, Division of Allergy, Immunology, and Bone Marrow Transplantation, University of California at San Francisco, San Francisco, Calif
| | - Nikita Raje
- Department of Pediatrics, University of Missouri-Kansas City, Kansas City, Mo; Division of Allergy/Asthma/Immunology, Children's Mercy Hospital, Kansas City, Mo
| | - Neil Romberg
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa; Division of Allergy/Immunology, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Maria A Slack
- Department of Medicine, Division of Allergy, Immunology, and Rheumatology, University of Rochester Medical Center, Rochester, NY; Department of Pediatrics, Division of Pediatric Allergy and Immunology, University of Rochester Medical Center, Rochester, NY
| | - Kathleen E Sullivan
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pa; Division of Allergy/Immunology, Children's Hospital of Philadelphia, Philadelphia, Pa
| | - Teresa K Tarrant
- Department of Medicine, Division of Rheumatology and Immunology, Duke University Medical Center, Durham, NC
| | - Troy R Torgerson
- Department of Pediatrics, University of Washington School of Medicine, Seattle, Wash; Center for Immunity and Immunotherapies, Seattle Children's Research Institute, Seattle, Wash
| | - Jolan E Walter
- Departments of Pediatrics and Medicine, University of South Florida, St Petersburg, Fla; Division of Pediatric Allergy/Immunology, Johns Hopkins-All Children's Hospital, St Petersburg, Fla; Division of Pediatric Allergy Immunology, Massachusetts General Hospital, Boston, Mass
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47
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Caspar SM, Dubacher N, Kopps AM, Meienberg J, Henggeler C, Matyas G. Clinical sequencing: From raw data to diagnosis with lifetime value. Clin Genet 2019; 93:508-519. [PMID: 29206278 DOI: 10.1111/cge.13190] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Revised: 11/28/2017] [Accepted: 11/30/2017] [Indexed: 12/22/2022]
Abstract
High-throughput sequencing (HTS) has revolutionized genetics by enabling the detection of sequence variants at hitherto unprecedented large scale. Despite these advances, however, there are still remaining challenges in the complete coverage of targeted regions (genes, exome or genome) as well as in HTS data analysis and interpretation. Moreover, it is easy to get overwhelmed by the plethora of available methods and tools for HTS. Here, we review the step-by-step process from the generation of sequence data to molecular diagnosis of Mendelian diseases. Highlighting advantages and limitations, this review addresses the current state of (1) HTS technologies, considering targeted, whole-exome, and whole-genome sequencing on short- and long-read platforms; (2) read alignment, variant calling and interpretation; as well as (3) regulatory issues related to genetic counseling, reimbursement, and data storage.
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Affiliation(s)
- S M Caspar
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich, Switzerland
| | - N Dubacher
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich, Switzerland
| | - A M Kopps
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich, Switzerland
| | - J Meienberg
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich, Switzerland
| | - C Henggeler
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich, Switzerland
| | - G Matyas
- Center for Cardiovascular Genetics and Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich, Switzerland.,Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
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48
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Odgerel Z, Sonti S, Hernandez N, Park J, Ottman R, Louis ED, Clark LN. Whole genome sequencing and rare variant analysis in essential tremor families. PLoS One 2019; 14:e0220512. [PMID: 31404076 PMCID: PMC6690583 DOI: 10.1371/journal.pone.0220512] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 07/17/2019] [Indexed: 11/19/2022] Open
Abstract
Essential tremor (ET) is one of the most common movement disorders. The etiology of ET remains largely unexplained. Whole genome sequencing (WGS) is likely to be of value in understanding a large proportion of ET with Mendelian and complex disease inheritance patterns. In ET families with Mendelian inheritance patterns, WGS may lead to gene identification where WES analysis failed to identify the causative single nucleotide variant (SNV) or indel due to incomplete coverage of the entire coding region of the genome, in addition to accurate detection of larger structural variants (SVs) and copy number variants (CNVs). Alternatively, in ET families with complex disease inheritance patterns with gene x gene and gene x environment interactions enrichment of functional rare coding and non-coding variants may explain the heritability of ET. We performed WGS in eight ET families (n = 40 individuals) enrolled in the Family Study of Essential Tremor. The analysis included filtering WGS data based on allele frequency in population databases, rare SNV and indel classification and association testing using the Mixed-Model Kernel Based Adaptive Cluster (MM-KBAC) test. A separate analysis of rare SV and CNVs segregating within ET families was also performed. Prioritization of candidate genes identified within families was performed using phenolyzer. WGS analysis identified candidate genes for ET in 5/8 (62.5%) of the families analyzed. WES analysis in a subset of these families in our previously published study failed to identify candidate genes. In one family, we identified a deleterious and damaging variant (c.1367G>A, p.(Arg456Gln)) in the candidate gene, CACNA1G, which encodes the pore forming subunit of T-type Ca(2+) channels, CaV3.1, and is expressed in various motor pathways and has been previously implicated in neuronal autorhythmicity and ET. Other candidate genes identified include SLIT3 which encodes an axon guidance molecule and in three families, phenolyzer prioritized genes that are associated with hereditary neuropathies (family A, KARS, family B, KIF5A and family F, NTRK1). Functional studies of CACNA1G and SLIT3 suggest a role for these genes in ET disease pathogenesis.
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Affiliation(s)
- Zagaa Odgerel
- Department of Pathology and Cell Biology, College of Physicians and Surgeons, Columbia University, New York, NY, United States of America
| | - Shilpa Sonti
- Department of Pathology and Cell Biology, College of Physicians and Surgeons, Columbia University, New York, NY, United States of America
| | - Nora Hernandez
- Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT, United States of America
| | - Jemin Park
- Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT, United States of America
| | - Ruth Ottman
- G.H Sergievsky Center, Columbia University, New York, NY, United States of America
- Department of Neurology, College of Physicians and Surgeons, Columbia University New York, NY, United States of America
- Department of Epidemiology, Mailman School of Public Health, Columbia University, NY, United States of America
- Division of Epidemiology, New York State Psychiatric Institute, New York, NY, United States of America
| | - Elan D. Louis
- Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT, United States of America
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, United States of America
| | - Lorraine N. Clark
- Department of Pathology and Cell Biology, College of Physicians and Surgeons, Columbia University, New York, NY, United States of America
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY, United States of America
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49
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Mallampati S, Duose DY, Harmon MA, Mehrotra M, Kanagal-Shamanna R, Zalles S, Wistuba II, Sun X, Luthra R. Rational "Error Elimination" Approach to Evaluating Molecular Barcoded Next-Generation Sequencing Data Identifies Low-Frequency Mutations in Hematologic Malignancies. J Mol Diagn 2019; 21:471-482. [PMID: 30794984 PMCID: PMC6521894 DOI: 10.1016/j.jmoldx.2019.01.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Revised: 10/31/2018] [Accepted: 01/18/2019] [Indexed: 12/18/2022] Open
Abstract
The emergence of highly sensitive molecular diagnostic approaches, such as droplet digital PCR, has allowed the accurate identification of low-frequency variant alleles in clinical specimens; however, the multiplex capabilities of droplet digital PCR for variant detection are inadequate. The incorporation of molecular barcodes or unique IDs into next-generation sequencing libraries through PCR has enabled the detection of low-frequency variant alleles across multiple genomic regions. However, rational library preparation and sequencing data analytic strategies that integrate molecular barcodes have rarely been applied to clinical settings. In this study, we evaluated the parameters that are crucial in the use of molecular barcodes in next-generation sequencing for genotyping clinical specimens from patients with hematologic malignancies. The uniform incorporation of molecular barcodes into DNA templates through PCR was found to be crucial, and the extent of uniformity was governed by multiple interdependent variables. An error elimination strategy was developed for removing sequencing background errors by using molecular barcode sequence information as an alternative to the conventional error correction approach. This approach was successfully used to identify mutations with frequencies as low as 0.15%, and the clonal heterogeneity of hematologic malignancies was revealed. These findings have implications for elucidating heterogeneity and temporal and spatial clonal evolution, evaluating response to therapy, and monitoring relapse in patients with hematologic malignancies.
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Affiliation(s)
- Saradhi Mallampati
- Department of Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Dzifa Y Duose
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | | | - Meenakshi Mehrotra
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Rashmi Kanagal-Shamanna
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Stephanie Zalles
- Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Ignacio I Wistuba
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Xiaoping Sun
- Department of Laboratory Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas.
| | - Rajyalakshmi Luthra
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
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50
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Tian S, Yan H, Klee EW, Kalmbach M, Slager SL. Comparative analysis of de novo assemblers for variation discovery in personal genomes. Brief Bioinform 2019; 19:893-904. [PMID: 28407084 PMCID: PMC6169673 DOI: 10.1093/bib/bbx037] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2016] [Accepted: 03/08/2017] [Indexed: 12/30/2022] Open
Abstract
Current variant discovery approaches often rely on an initial read mapping to the reference sequence. Their effectiveness is limited by the presence of gaps, potential misassemblies, regions of duplicates with a high-sequence similarity and regions of high-sequence divergence in the reference. Also, mapping-based approaches are less sensitive to large INDELs and complex variations and provide little phase information in personal genomes. A few de novo assemblers have been developed to identify variants through direct variant calling from the assembly graph, micro-assembly and whole-genome assembly, but mainly for whole-genome sequencing (WGS) data. We developed SGVar, a de novo assembly workflow for haplotype-based variant discovery from whole-exome sequencing (WES) data. Using simulated human exome data, we compared SGVar with five variation-aware de novo assemblers and with BWA-MEM together with three haplotype- or local de novo assembly-based callers. SGVar outperforms the other assemblers in sensitivity and tolerance of sequencing errors. We recapitulated the findings on whole-genome and exome data from a Utah residents with Northern and Western European ancestry (CEU) trio, showing that SGVar had high sensitivity both in the highly divergent human leukocyte antigen (HLA) region and in non-HLA regions of chromosome 6. In particular, SGVar is robust to sequencing error, k-mer selection, divergence level and coverage depth. Unlike mapping-based approaches, SGVar is capable of resolving long-range phase and identifying large INDELs from WES, more prominently from WGS. We conclude that SGVar represents an ideal platform for WES-based variant discovery in highly divergent regions and across the whole genome.
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Affiliation(s)
- Shulan Tian
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Huihuang Yan
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Eric W Klee
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.,Center for Individualized Medicine Bioinformatics Program, Mayo Clinic, USA
| | - Michael Kalmbach
- Division of Information Management and Analytics, Department of Information Technology, Mayo Clinic, USA
| | - Susan L Slager
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
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