401
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Figueiredo T, Melo US, Pessoa ALS, Nobrega PR, Kitajima JP, Rusch H, Vaz F, Lucato LT, Zatz M, Kok F, Santos S. A homozygous loss-of-function mutation in inositol monophosphatase 1 (IMPA1) causes severe intellectual disability. Mol Psychiatry 2016; 21:1125-9. [PMID: 26416544 DOI: 10.1038/mp.2015.150] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Revised: 08/17/2015] [Accepted: 08/19/2015] [Indexed: 11/09/2022]
Abstract
The genetic basis of intellectual disability (ID) is extremely heterogeneous and relatively little is known about the role of autosomal recessive traits. In a field study performed in a highly inbred area of Northeastern Brazil, we identified and investigated a large consanguineous family with nine adult members affected by severe ID associated with disruptive behavior. The Genome-Wide Human SNP Array 6.0 microarray was used to determine regions of homozygosity by descent from three affected and one normal family member. Whole-exome sequencing (WES) was performed in one affected patient using the Nextera Rapid-Capture Exome kit and Illumina HiSeq2500 system to identify the causative mutation. Potentially deleterious variants detected in regions of homozygosity by descent and not present in either 59 723 unrelated individuals from the Exome Aggregation Consortium (Browser) or 1484 Brazilians were subject to further scrutiny and segregation analysis by Sanger sequencing. Homozygosity-by-descent analysis disclosed a 20.7-Mb candidate region at 8q12.3-q21.2 (lod score: 3.11). WES identified a homozygous deleterious variant in inositol monophosphatase 1 (IMPA1) (NM_005536), consisting of a 5-bp duplication (c.489_493dupGGGCT; chr8: 82,583,247; GRCh37/hg19) leading to a frameshift and a premature stop codon (p.Ser165Trpfs*10) that cosegregated with the disease in 26 genotyped family members. The IMPA1 gene product is responsible for the final step of biotransformation of inositol triphosphate and diacylglycerol, two second messengers. Despite its many physiological functions, no clinical phenotype has been assigned to this gene dysfunction to date. Additionally, IMPA1 is the main target of lithium, a drug that is at the forefront of treatment for bipolar disorder.
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Affiliation(s)
- T Figueiredo
- Northeast Biotechnology Network (RENORBIO), Federal University of Paraiba (UFPB), Joao Pessoa, Brazil.,Department of Biology, Paraiba State University (UEPB), Campina Grande, Brazil.,Department of Genetics and Evolutionary Biology, Human Genome and Stem Cell Research Center, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, Brazil
| | - U S Melo
- Department of Genetics and Evolutionary Biology, Human Genome and Stem Cell Research Center, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, Brazil
| | - A L S Pessoa
- Department of Neurology, School of Medicine, University of Sao Paulo (USP), Sao Paulo, Brazil.,School of Medicine, Fortaleza University (UNIFOR), Fortaleza, Brazil
| | - P R Nobrega
- Department of Neurology, School of Medicine, University of Sao Paulo (USP), Sao Paulo, Brazil
| | | | - H Rusch
- Laboratory of Genetic Metabolic Diseases, Department of Clinical Chemistry, University of Amsterdam, Academic Medical Center (AMC), Amsterdam, The Netherlands
| | - F Vaz
- Laboratory of Genetic Metabolic Diseases, Department of Clinical Chemistry, University of Amsterdam, Academic Medical Center (AMC), Amsterdam, The Netherlands
| | - L T Lucato
- Institute of Radiology, School of Medicine, University of Sao Paulo (USP), Sao Paulo, Brazil
| | - M Zatz
- Department of Genetics and Evolutionary Biology, Human Genome and Stem Cell Research Center, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, Brazil
| | - F Kok
- Department of Genetics and Evolutionary Biology, Human Genome and Stem Cell Research Center, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, Brazil.,Department of Neurology, School of Medicine, University of Sao Paulo (USP), Sao Paulo, Brazil.,Mendelics Genomic Analysis, Sao Paulo, Brazil
| | - S Santos
- Northeast Biotechnology Network (RENORBIO), Federal University of Paraiba (UFPB), Joao Pessoa, Brazil.,Department of Biology, Paraiba State University (UEPB), Campina Grande, Brazil
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402
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Smith CEL, Murillo G, Brookes SJ, Poulter JA, Silva S, Kirkham J, Inglehearn CF, Mighell AJ. Deletion of amelotin exons 3-6 is associated with amelogenesis imperfecta. Hum Mol Genet 2016; 25:3578-3587. [PMID: 27412008 PMCID: PMC5179951 DOI: 10.1093/hmg/ddw203] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Revised: 06/17/2016] [Accepted: 06/21/2016] [Indexed: 11/15/2022] Open
Abstract
Amelogenesis imperfecta (AI) is a heterogeneous group of genetic conditions that result in defective dental enamel formation. Amelotin (AMTN) is a secreted protein thought to act as a promoter of matrix mineralization in the final stage of enamel development, and is strongly expressed, almost exclusively, in maturation stage ameloblasts. Amtn overexpression and Amtn knockout mouse models have defective enamel with no other associated phenotypes, highlighting AMTN as an excellent candidate gene for human AI. However, no AMTN mutations have yet been associated with human AI. Using whole exome sequencing, we identified an 8,678 bp heterozygous genomic deletion encompassing exons 3-6 of AMTN in a Costa Rican family segregating dominant hypomineralised AI. The deletion corresponds to an in-frame deletion of 92 amino acids, shortening the protein from 209 to 117 residues. Exfoliated primary teeth from an affected family member had enamel that was of a lower mineral density compared to control enamel and exhibited structural defects at least some of which appeared to be associated with organic material as evidenced using elemental analysis. This study demonstrates for the first time that AMTN mutations cause non-syndromic human AI and explores the human phenotype, comparing it with that of mice with disrupted Amtn function.
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Affiliation(s)
- Claire E L Smith
- Leeds Institute of Biomedical and Clinical Sciences, St James's University Hospital, University of Leeds, Leeds LS9 7TF, UK.,Department of Oral Biology, St James's University Hospital, University of Leeds, Leeds LS9 7TF, UK
| | - Gina Murillo
- University of Costa Rica, School of Dentistry, San Pedro, Costa Rica
| | - Steven J Brookes
- Department of Oral Biology, St James's University Hospital, University of Leeds, Leeds LS9 7TF, UK
| | - James A Poulter
- Leeds Institute of Biomedical and Clinical Sciences, St James's University Hospital, University of Leeds, Leeds LS9 7TF, UK
| | - Sandra Silva
- University of Costa Rica, Molecular Biology Cellular Centre (CBCM), San Pedro, Costa Rica and
| | - Jennifer Kirkham
- Department of Oral Biology, St James's University Hospital, University of Leeds, Leeds LS9 7TF, UK
| | - Chris F Inglehearn
- Leeds Institute of Biomedical and Clinical Sciences, St James's University Hospital, University of Leeds, Leeds LS9 7TF, UK
| | - Alan J Mighell
- Leeds Institute of Biomedical and Clinical Sciences, St James's University Hospital, University of Leeds, Leeds LS9 7TF, UK, .,School of Dentistry, University of Leeds, Leeds LS2 9LU, UK
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403
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Patni N, Brothers J, Xing C, Garg A. Type 1 hyperlipoproteinemia in a child with large homozygous deletion encompassing GPIHBP1. J Clin Lipidol 2016; 10:1035-1039.e2. [DOI: 10.1016/j.jacl.2016.04.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2015] [Revised: 03/30/2016] [Accepted: 04/03/2016] [Indexed: 01/12/2023]
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404
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Johnson B, Lowe GC, Futterer J, Lordkipanidzé M, MacDonald D, Simpson MA, Sanchez-Guiú I, Drake S, Bem D, Leo V, Fletcher SJ, Dawood B, Rivera J, Allsup D, Biss T, Bolton-Maggs PH, Collins P, Curry N, Grimley C, James B, Makris M, Motwani J, Pavord S, Talks K, Thachil J, Wilde J, Williams M, Harrison P, Gissen P, Mundell S, Mumford A, Daly ME, Watson SP, Morgan NV. Whole exome sequencing identifies genetic variants in inherited thrombocytopenia with secondary qualitative function defects. Haematologica 2016; 101:1170-1179. [PMID: 27479822 DOI: 10.3324/haematol.2016.146316] [Citation(s) in RCA: 96] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Accepted: 06/10/2016] [Indexed: 12/11/2022] Open
Abstract
Inherited thrombocytopenias are a heterogeneous group of disorders characterized by abnormally low platelet counts which can be associated with abnormal bleeding. Next-generation sequencing has previously been employed in these disorders for the confirmation of suspected genetic abnormalities, and more recently in the discovery of novel disease-causing genes. However its full potential has not yet been exploited. Over the past 6 years we have sequenced the exomes from 55 patients, including 37 index cases and 18 additional family members, all of whom were recruited to the UK Genotyping and Phenotyping of Platelets study. All patients had inherited or sustained thrombocytopenia of unknown etiology with platelet counts varying from 11×109/L to 186×109/L. Of the 51 patients phenotypically tested, 37 (73%), had an additional secondary qualitative platelet defect. Using whole exome sequencing analysis we have identified "pathogenic" or "likely pathogenic" variants in 46% (17/37) of our index patients with thrombocytopenia. In addition, we report variants of uncertain significance in 12 index cases, including novel candidate genetic variants in previously unreported genes in four index cases. These results demonstrate that whole exome sequencing is an efficient method for elucidating potential pathogenic genetic variants in inherited thrombocytopenia. Whole exome sequencing also has the added benefit of discovering potentially pathogenic genetic variants for further study in novel genes not previously implicated in inherited thrombocytopenia.
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Affiliation(s)
- Ben Johnson
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - Gillian C Lowe
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - Jane Futterer
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - Marie Lordkipanidzé
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - David MacDonald
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - Michael A Simpson
- Division of Genetics and Molecular Medicine, King's College, London, UK
| | - Isabel Sanchez-Guiú
- Centro Regional de Hemodonación, Universidad de Murcia, IMIB-Arrixaca, Murcia, Spain
| | - Sian Drake
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - Danai Bem
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - Vincenzo Leo
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Medical School, University of Sheffield, UK
| | - Sarah J Fletcher
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - Ban Dawood
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - José Rivera
- Centro Regional de Hemodonación, Universidad de Murcia, IMIB-Arrixaca, Murcia, Spain
| | - David Allsup
- Hull Haemophilia Treatment Centre, Hull and East Yorkshire Hospitals NHS Trust, Castle Hill Hospital, Hull, UK
| | - Tina Biss
- Department of Haematology, Royal Victoria Infirmary, Newcastle Upon Tyne, UK
| | | | - Peter Collins
- Arthur Bloom Haemophilia Centre, School of Medicine, Cardiff University, UK
| | - Nicola Curry
- Oxford Haemophilia & Thrombosis Centre, Churchill Hospital, Oxford, UK
| | | | - Beki James
- Regional Centre for Paediatric Haematology, Leeds Children's Hospital, UK
| | - Mike Makris
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Medical School, University of Sheffield, UK
| | | | - Sue Pavord
- Department of Haematology, Oxford University Hospitals NHS Foundation Trust, UK
| | - Katherine Talks
- Department of Haematology, Royal Victoria Infirmary, Newcastle Upon Tyne, UK
| | - Jecko Thachil
- Department of Haematology, Manchester Royal Infirmary, Manchester, UK
| | - Jonathan Wilde
- Adult Haemophilia Centre, Queen Elizabeth Hospital, Birmingham, UK
| | - Mike Williams
- Department of Haematology, Birmingham Children's Hospital, UK
| | - Paul Harrison
- School of Immunity and Infection, College of Medical and Dental Sciences, University of Birmingham, UK
| | - Paul Gissen
- Medical Research Council, Laboratory for Molecular Cell Biology, University College London, UK
| | - Stuart Mundell
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, UK
| | - Andrew Mumford
- School of Cellular and Molecular Medicine, University of Bristol, UK
| | - Martina E Daly
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield Medical School, University of Sheffield, UK
| | - Steve P Watson
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
| | - Neil V Morgan
- Institute for Cardiovascular Sciences, College of Medical and Dental Sciences, University of Birmingham, UK
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405
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San Lucas FA, Sivakumar S, Vattathil S, Fowler J, Vilar E, Scheet P. Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq. Bioinformatics 2016; 32:3015-7. [PMID: 27288500 PMCID: PMC5039922 DOI: 10.1093/bioinformatics/btw340] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Accepted: 05/26/2016] [Indexed: 11/13/2022] Open
Abstract
Motivation: The detection of subtle genomic allelic imbalance events has many potential applications. For example, identifying cancer-associated allelic imbalanced regions in low tumor-cellularity samples or in low-proportion tumor subclones can be used for early cancer detection, prognostic assessment and therapeutic selection in cancer patients. We developed hapLOHseq for the detection of subtle allelic imbalance events from next-generation sequencing data. Results: Our method identified events of 10 megabases or greater occurring in as little as 16% of the sample in exome sequencing data (at 80×) and 4% in whole genome sequencing data (at 30×), far exceeding the capabilities of existing software. We also found hapLOHseq to be superior at detecting large chromosomal changes across a series of pancreatic samples from TCGA. Availability and Implementation:hapLOHseq is available at scheet.org/software, distributed under an open source MIT license. Contact:pscheet@alum.wustl.edu Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- F Anthony San Lucas
- Department of Translational Molecular Pathology The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Smruthy Sivakumar
- Department of Translational Molecular Pathology Department of Epidemiology
| | - Selina Vattathil
- Department of Translational Molecular Pathology Department of Epidemiology
| | | | - Eduardo Vilar
- Department of Translational Molecular Pathology Department of Gastrointestinal Medical Oncology Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Paul Scheet
- The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA Department of Epidemiology
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406
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Mason-Suares H, Landry L, S. Lebo M. Detecting Copy Number Variation via Next Generation Technology. CURRENT GENETIC MEDICINE REPORTS 2016. [DOI: 10.1007/s40142-016-0091-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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407
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Nickerson ML, Witte N, Im KM, Turan S, Owens C, Misner K, Tsang SX, Cai Z, Wu S, Dean M, Costello JC, Theodorescu D. Molecular analysis of urothelial cancer cell lines for modeling tumor biology and drug response. Oncogene 2016; 36:35-46. [PMID: 27270441 PMCID: PMC5140783 DOI: 10.1038/onc.2016.172] [Citation(s) in RCA: 65] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Revised: 03/04/2016] [Accepted: 03/07/2016] [Indexed: 12/14/2022]
Abstract
The utility of tumor-derived cell lines is dependent on their ability to recapitulate underlying genomic aberrations and primary tumor biology. Here, we sequenced the exomes of 25 bladder cancer (BCa) cell lines and compared mutations, copy number alterations (CNAs), gene expression and drug response to BCa patient profiles in The Cancer Genome Atlas (TCGA). We observed a mutation pattern associated with altered CpGs and APOBEC-family cytosine deaminases similar to mutation signatures derived from somatic alterations in muscle-invasive (MI) primary tumors, highlighting a major mechanism(s) contributing to cancer-associated alterations in the BCa cell line exomes. Non-silent sequence alterations were confirmed in 76 cancer-associated genes, including mutations that likely activate oncogenes TERT and PIK3CA, and alter chromatin-associated proteins (MLL3, ARID1A, CHD6 and KDM6A) and established BCa genes (TP53, RB1, CDKN2A and TSC1). We identified alterations in signaling pathways and proteins with related functions, including the PI3K/mTOR pathway, altered in 60% of lines; BRCA DNA repair, 44% and SYNE1–SYNE2, 60%. Homozygous deletions of chromosome 9p21 are known to target the cell cycle regulators CDKN2A and CDKN2B. This loci was commonly lost in BCa cell lines and we show the deletions extended to the polyamine enzyme methylthioadenosine (MTA) phosphorylase (MTAP) in 36% of lines, transcription factor DMRTA1 (27%) and antiviral interferon epsilon (IFNE, 19%). Overall, the BCa cell line genomic aberrations were concordant with those found in BCa patient tumors. We used gene expression and copy number data to infer pathway activities for cell lines, then used the inferred pathway activities to build a predictive model of cisplatin response. When applied to platinum-treated patients gathered from TCGA, the model predicted treatment-specific response. Together, these data and analysis represent a valuable community resource to model basic tumor biology and to study the pharmacogenomics of BCa.
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Affiliation(s)
- M L Nickerson
- Cancer and Inflammation Program, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - N Witte
- Computational Bioscience Program, University of Colorado, Aurora, CO, USA
| | - K M Im
- Data Science for Genomics, LLC, Ellicott City, MD, USA
| | - S Turan
- Cancer and Inflammation Program, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - C Owens
- Department of Surgery (Urology), University of Colorado, Aurora, CO, USA
| | - K Misner
- Cancer and Inflammation Program, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | | | - Z Cai
- Shenzhen Second People's Hospital, Shenzhen, China
| | - S Wu
- Shenzhen Second People's Hospital, Shenzhen, China
| | - M Dean
- Cancer and Inflammation Program, National Cancer Institute, National Institutes of Health, Frederick, MD, USA
| | - J C Costello
- Computational Bioscience Program, University of Colorado, Aurora, CO, USA.,Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.,University of Colorado Comprehensive Cancer Center, Aurora, CO, USA
| | - D Theodorescu
- Department of Surgery (Urology), University of Colorado, Aurora, CO, USA.,Department of Pharmacology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.,University of Colorado Comprehensive Cancer Center, Aurora, CO, USA
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408
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Peng CH, Liao CT, Ng KP, Tai AS, Peng SC, Yeh JP, Chen SJ, Tsao KC, Yen TC, Hsieh WP. Somatic copy number alterations detected by ultra-deep targeted sequencing predict prognosis in oral cavity squamous cell carcinoma. Oncotarget 2016; 6:19891-906. [PMID: 26087196 PMCID: PMC4637328 DOI: 10.18632/oncotarget.4336] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 05/23/2015] [Indexed: 12/20/2022] Open
Abstract
Background Ultra-deep targeted sequencing (UDT-Seq) has advanced our knowledge on the incidence and functional significance of somatic mutations. However, the utility of UDT-Seq in detecting copy number alterations (CNAs) remains unclear. With the goal of improving molecular prognostication and identifying new therapeutic targets, we designed this study to assess whether UDT-Seq may be useful for detecting CNA in oral cavity squamous cell carcinoma (OSCC). Methods We sequenced a panel of clinically actionable cancer mutations in 310 formalin-fixed paraffin-embedded OSCC specimens. A linear model was developed to overcome uneven coverage across target regions and multiple samples. The 5-year rates of secondary primary tumors, local recurrence, neck recurrence, distant metastases, and survival served as the outcome measures. We confirmed the prognostic significance of the CNA signatures in an independent sample of 105 primary OSCC specimens. Results The CNA burden across 10 targeted genes was found to predict prognosis in two independent cohorts. FGFR1 and PIK3CAamplifications were associated with prognosis independent of clinical risk factors. Genes exhibiting CNA were clustered in the proteoglycan metabolism, the FOXO signaling, and the PI3K-AKT signaling pathways, for which targeted drugs are already available or currently under development. Conclusions UDT-Seq is clinically useful to identify CNA, which significantly improve the prognostic information provided by traditional clinicopathological risk factors in OSCC patients.
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Affiliation(s)
- Chien-Hua Peng
- Departments of Resource Center for Clinical Research, Chang Gung Memorial Hospital, Taoyuan, Taiwan, R.O.C
| | - Chun-Ta Liao
- Otorhinolaryngology, Head and Neck Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan, R.O.C.,Head and Neck Oncology Group, Chang Gung Memorial Hospital, Taoyuan, Taiwan, R.O.C
| | - Ka-Pou Ng
- Institute of Statistics, National Tsing Hua University, Hsinchu, Taiwan, R.O.C
| | - An-Shun Tai
- Institute of Statistics, National Tsing Hua University, Hsinchu, Taiwan, R.O.C
| | - Shih-Chi Peng
- Department of Nuclear Medicine and Molecular Imaging Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan, R.O.C
| | - Jen-Pao Yeh
- Institute of Statistics, National Tsing Hua University, Hsinchu, Taiwan, R.O.C
| | - Shu-Jen Chen
- Department of Biomedical Sciences, School of Medicine, Chang Gung University, Taoyuan, Taiwan, R.O.C
| | - Kuo-Chien Tsao
- Medical Biotechnology and Laboratory Science, Research Center for Emerging Viral Infections, Chang Gung Memorial Hospital, Taoyuan, Taiwan, R.O.C.,Laboratory Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan, R.O.C
| | - Tzu-Chen Yen
- Department of Nuclear Medicine and Molecular Imaging Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan, R.O.C
| | - Wen-Ping Hsieh
- Otorhinolaryngology, Head and Neck Surgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan, R.O.C
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409
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Candidate driver genes involved in genome maintenance and DNA repair in Sézary syndrome. Blood 2016; 127:3387-97. [PMID: 27121473 DOI: 10.1182/blood-2016-02-699843] [Citation(s) in RCA: 76] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2016] [Accepted: 04/13/2016] [Indexed: 12/13/2022] Open
Abstract
Sézary syndrome (SS) is a leukemic variant of cutaneous T-cell lymphoma (CTCL) and represents an ideal model for study of T-cell transformation. We describe whole-exome and single-nucleotide polymorphism array-based copy number analyses of CD4(+) tumor cells from untreated patients at diagnosis and targeted resequencing of 101 SS cases. A total of 824 somatic nonsynonymous gene variants were identified including indels, stop-gain/loss, splice variants, and recurrent gene variants indicative of considerable molecular heterogeneity. Driver genes identified using MutSigCV include POT1, which has not been previously reported in CTCL; and TP53 and DNMT3A, which were also identified consistent with previous reports. Mutations in PLCG1 were detected in 11% of tumors including novel variants not previously described in SS. This study is also the first to show BRCA2 defects in a significant proportion (14%) of SS tumors. Aberrations in PRKCQ were found to occur in 20% of tumors highlighting selection for activation of T-cell receptor/NF-κB signaling. A complex but consistent pattern of copy number variants (CNVs) was detected and many CNVs involved genes identified as putative drivers. Frequent defects involving the POT1 and ATM genes responsible for telomere maintenance were detected and may contribute to genomic instability in SS. Genomic aberrations identified were enriched for genes implicated in cell survival and fate, specifically PDGFR, ERK, JAK STAT, MAPK, and TCR/NF-κB signaling; epigenetic regulation (DNMT3A, ASLX3, TET1-3); and homologous recombination (RAD51C, BRCA2, POLD1). This study now provides the basis for a detailed functional analysis of malignant transformation of mature T cells and improved patient stratification and treatment.
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410
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Talevich E, Shain AH, Botton T, Bastian BC. CNVkit: Genome-Wide Copy Number Detection and Visualization from Targeted DNA Sequencing. PLoS Comput Biol 2016; 12:e1004873. [PMID: 27100738 PMCID: PMC4839673 DOI: 10.1371/journal.pcbi.1004873] [Citation(s) in RCA: 1137] [Impact Index Per Article: 142.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 03/16/2016] [Indexed: 01/19/2023] Open
Abstract
Germline copy number variants (CNVs) and somatic copy number alterations (SCNAs) are of significant importance in syndromic conditions and cancer. Massively parallel sequencing is increasingly used to infer copy number information from variations in the read depth in sequencing data. However, this approach has limitations in the case of targeted re-sequencing, which leaves gaps in coverage between the regions chosen for enrichment and introduces biases related to the efficiency of target capture and library preparation. We present a method for copy number detection, implemented in the software package CNVkit, that uses both the targeted reads and the nonspecifically captured off-target reads to infer copy number evenly across the genome. This combination achieves both exon-level resolution in targeted regions and sufficient resolution in the larger intronic and intergenic regions to identify copy number changes. In particular, we successfully inferred copy number at equivalent to 100-kilobase resolution genome-wide from a platform targeting as few as 293 genes. After normalizing read counts to a pooled reference, we evaluated and corrected for three sources of bias that explain most of the extraneous variability in the sequencing read depth: GC content, target footprint size and spacing, and repetitive sequences. We compared the performance of CNVkit to copy number changes identified by array comparative genomic hybridization. We packaged the components of CNVkit so that it is straightforward to use and provides visualizations, detailed reporting of significant features, and export options for integration into existing analysis pipelines. CNVkit is freely available from https://github.com/etal/cnvkit.
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Affiliation(s)
- Eric Talevich
- Department of Dermatology, University of California, San Francisco, San Francisco, California, United States of America
- Department of Pathology, University of California, San Francisco, San Francisco, California, United States of America
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, United States of America
| | - A. Hunter Shain
- Department of Dermatology, University of California, San Francisco, San Francisco, California, United States of America
- Department of Pathology, University of California, San Francisco, San Francisco, California, United States of America
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, United States of America
| | - Thomas Botton
- Department of Dermatology, University of California, San Francisco, San Francisco, California, United States of America
- Department of Pathology, University of California, San Francisco, San Francisco, California, United States of America
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, United States of America
| | - Boris C. Bastian
- Department of Dermatology, University of California, San Francisco, San Francisco, California, United States of America
- Department of Pathology, University of California, San Francisco, San Francisco, California, United States of America
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, United States of America
- * E-mail:
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411
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Abulí A, Boada M, Rodríguez-Santiago B, Coroleu B, Veiga A, Armengol L, Barri PN, Pérez-Jurado LA, Estivill X. NGS-Based Assay for the Identification of Individuals Carrying Recessive Genetic Mutations in Reproductive Medicine. Hum Mutat 2016; 37:516-23. [PMID: 26990548 DOI: 10.1002/humu.22989] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2016] [Accepted: 03/09/2016] [Indexed: 12/25/2022]
Abstract
Next-generation sequencing (NGS) has the capacity of carrier screening in gamete donation (GD) programs. We have developed and validated an NGS carrier-screening test (qCarrier test) that includes 200 genes associated with 368 disorders (277 autosomal recessive and 37 X-linked). Carrier screening is performed on oocyte donation candidates and the male partner of oocyte recipient. Carriers of X-linked conditions are excluded from the GD program, whereas donors are chosen who do not carry mutations for the same gene/disease as the recipients. The validation phase showed a high sensitivity (>99% sensitivity) detecting all single-nucleotide variants, 13 indels, and 25 copy-number variants included in the validation set. A total of 1,301 individuals were analysed with the qCarrier test, including 483 candidate oocyte donors and 635 receptor couples, 105 females receiving sperm donation, and 39 couples seeking pregnancy. We identified 56% of individuals who are carriers for at least one genetic condition and 1.7% of female donors who were excluded from the program due to a carrier state of X-linked conditions. Globally, 3% of a priori assigned donations had a high reproductive risk that could be minimized after testing. Genetic counselling at different stages is essential for helping to facilitate a successful and healthy pregnancy.
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Affiliation(s)
- Anna Abulí
- Unit of Medical Genomics, Department of Obstetrics, Gynaecology and Reproduction, Dexeus Women's Health, Barcelona, Spain
| | - Montserrat Boada
- Service of Reproduction Medicine, Obstetrics, Department of Obstetrics, Gynaecology and Reproduction, Dexeus Women's Health, Barcelona, Spain
| | | | - Buenaventura Coroleu
- Service of Reproduction Medicine, Obstetrics, Department of Obstetrics, Gynaecology and Reproduction, Dexeus Women's Health, Barcelona, Spain
| | - Anna Veiga
- Service of Reproduction Medicine, Obstetrics, Department of Obstetrics, Gynaecology and Reproduction, Dexeus Women's Health, Barcelona, Spain
| | - Lluís Armengol
- Research and Development Department, qGenomics Laboratory, Barcelona, Spain
| | - Pedro N Barri
- Service of Reproduction Medicine, Obstetrics, Department of Obstetrics, Gynaecology and Reproduction, Dexeus Women's Health, Barcelona, Spain
| | - Luis A Pérez-Jurado
- Genetics Unit, Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), Barcelona, Spain.,Hospital del Mar Research Institute (IMIM), Barcelona, Spain.,CIBER in Rare Disorders (CIBERER), Barcelona, Spain
| | - Xavier Estivill
- Unit of Medical Genomics, Department of Obstetrics, Gynaecology and Reproduction, Dexeus Women's Health, Barcelona, Spain.,Genetics Unit, Department of Experimental and Health Sciences, Pompeu Fabra University (UPF), Barcelona, Spain.,Hospital del Mar Research Institute (IMIM), Barcelona, Spain.,Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.,CIBER in Epidemiology and Public Health (CIBERESP), Barcelona, Spain.,Experimental Genetics Division, Sidra Medical and Research Centre, Doha, Qatar
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412
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A high-throughput sequencing test for diagnosing inherited bleeding, thrombotic, and platelet disorders. Blood 2016; 127:2791-803. [PMID: 27084890 DOI: 10.1182/blood-2015-12-688267] [Citation(s) in RCA: 134] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2015] [Accepted: 04/07/2016] [Indexed: 12/17/2022] Open
Abstract
Inherited bleeding, thrombotic, and platelet disorders (BPDs) are diseases that affect ∼300 individuals per million births. With the exception of hemophilia and von Willebrand disease patients, a molecular analysis for patients with a BPD is often unavailable. Many specialized tests are usually required to reach a putative diagnosis and they are typically performed in a step-wise manner to control costs. This approach causes delays and a conclusive molecular diagnosis is often never reached, which can compromise treatment and impede rapid identification of affected relatives. To address this unmet diagnostic need, we designed a high-throughput sequencing platform targeting 63 genes relevant for BPDs. The platform can call single nucleotide variants, short insertions/deletions, and large copy number variants (though not inversions) which are subjected to automated filtering for diagnostic prioritization, resulting in an average of 5.34 candidate variants per individual. We sequenced 159 and 137 samples, respectively, from cases with and without previously known causal variants. Among the latter group, 61 cases had clinical and laboratory phenotypes indicative of a particular molecular etiology, whereas the remainder had an a priori highly uncertain etiology. All previously detected variants were recapitulated and, when the etiology was suspected but unknown or uncertain, a molecular diagnosis was reached in 56 of 61 and only 8 of 76 cases, respectively. The latter category highlights the need for further research into novel causes of BPDs. The ThromboGenomics platform thus provides an affordable DNA-based test to diagnose patients suspected of having a known inherited BPD.
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413
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Beltman JB, Urbanus J, Velds A, van Rooij N, Rohr JC, Naik SH, Schumacher TN. Reproducibility of Illumina platform deep sequencing errors allows accurate determination of DNA barcodes in cells. BMC Bioinformatics 2016; 17:151. [PMID: 27038897 PMCID: PMC4818877 DOI: 10.1186/s12859-016-0999-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2015] [Accepted: 03/23/2016] [Indexed: 12/31/2022] Open
Abstract
Background Next generation sequencing (NGS) of amplified DNA is a powerful tool to describe genetic heterogeneity within cell populations that can both be used to investigate the clonal structure of cell populations and to perform genetic lineage tracing. For applications in which both abundant and rare sequences are biologically relevant, the relatively high error rate of NGS techniques complicates data analysis, as it is difficult to distinguish rare true sequences from spurious sequences that are generated by PCR or sequencing errors. This issue, for instance, applies to cellular barcoding strategies that aim to follow the amount and type of offspring of single cells, by supplying these with unique heritable DNA tags. Results Here, we use genetic barcoding data from the Illumina HiSeq platform to show that straightforward read threshold-based filtering of data is typically insufficient to filter out spurious barcodes. Importantly, we demonstrate that specific sequencing errors occur at an approximately constant rate across different samples that are sequenced in parallel. We exploit this observation by developing a novel approach to filter out spurious sequences. Conclusions Application of our new method demonstrates its value in the identification of true sequences amongst spurious sequences in biological data sets. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-0999-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Joost B Beltman
- Division of Immunology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands. .,Division of Toxicology, Leiden Academic Centre for Drug Research, Leiden University, 2333 CC, Leiden, The Netherlands.
| | - Jos Urbanus
- Division of Immunology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Arno Velds
- Genomics Core Facility, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Nienke van Rooij
- Division of Immunology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Jan C Rohr
- Division of Immunology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Center for Chronic Immunodeficiency (CCI), University Medical Center Freiburg and University of Freiburg, Freiburg, Germany
| | - Shalin H Naik
- Division of Immunology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, VIC, 3052, Australia.,Department of Medical Biology, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Ton N Schumacher
- Division of Immunology, The Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
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414
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Al-Hebshi NN, Li S, Nasher AT, El-Setouhy M, Alsanosi R, Blancato J, Loffredo C. Exome sequencing of oral squamous cell carcinoma in users of Arabian snuff reveals novel candidates for driver genes. Int J Cancer 2016; 139:363-72. [PMID: 26934577 DOI: 10.1002/ijc.30068] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Accepted: 02/16/2016] [Indexed: 02/06/2023]
Abstract
The study sought to identify genetic aberrations driving oral squamous cell carcinoma (OSCC) development among users of shammah, an Arabian preparation of smokeless tobacco. Twenty archival OSCC samples, 15 of which with a history of shammah exposure, were whole-exome sequenced at an average depth of 127×. Somatic mutations were identified using a novel, matched controls-independent filtration algorithm. CODEX and Exomedepth coupled with a novel, Database of Genomic Variant-based filter were employed to call somatic gene-copy number variations. Significantly mutated genes were identified with Oncodrive FM and the Youn and Simon's method. Candidate driver genes were nominated based on Gene Set Enrichment Analysis. The observed mutational spectrum was similar to that reported by the TCGA project. In addition to confirming known genes of OSCC (TP53, CDKNA2, CASP8, PIK3CA, HRAS, FAT1, TP63, CCND1 and FADD) the analysis identified several candidate novel driver events including mutations of NOTCH3, CSMD3, CRB1, CLTCL1, OSMR and TRPM2, amplification of the proto-oncogenes FOSL1, RELA, TRAF6, MDM2, FRS2 and BAG1, and deletion of the recently described tumor suppressor SMARCC1. Analysis also revealed significantly altered pathways not previously implicated in OSCC including Oncostatin-M signalling pathway, AP-1 and C-MYB transcription networks and endocytosis. There was a trend for higher number of mutations, amplifications and driver events in samples with history of shammah exposure particularly those that tested EBV positive, suggesting an interaction between tobacco exposure and EBV. The work provides further evidence for the genetic heterogeneity of oral cancer and suggests shammah-associated OSCC is characterized by extensive amplification of oncogenes.
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Affiliation(s)
- Nezar Noor Al-Hebshi
- Department of Preventive Dentistry, College of Dentistry, Jazan University, Jazan, Kingdom of Saudi Arabia
| | - Shiyong Li
- Department of Oncology and Pharmacogenomics, Beijing Genome Institute (BGI), Shenzhen, Republic of China
| | - Akram Thabet Nasher
- Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Sana'a University, Yemen
| | - Maged El-Setouhy
- Substance Abuse Research Center (SARC), Jazan University, Jazan, Kingdom of Saudi Arabia
| | - Rashad Alsanosi
- Substance Abuse Research Center (SARC), Jazan University, Jazan, Kingdom of Saudi Arabia
| | - Jan Blancato
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
| | - Christopher Loffredo
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC, USA
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415
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Lewis-Smith D, Kamer KJ, Griffin H, Childs AM, Pysden K, Titov D, Duff J, Pyle A, Taylor RW, Yu-Wai-Man P, Ramesh V, Horvath R, Mootha VK, Chinnery PF. Homozygous deletion in MICU1 presenting with fatigue and lethargy in childhood. NEUROLOGY-GENETICS 2016; 2:e59. [PMID: 27123478 PMCID: PMC4830195 DOI: 10.1212/nxg.0000000000000059] [Citation(s) in RCA: 80] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2015] [Accepted: 01/08/2016] [Indexed: 01/19/2023]
Abstract
OBJECTIVE To define the mechanism responsible for fatigue, lethargy, and weakness in 2 cousins who had a normal muscle biopsy. METHODS Exome sequencing, long-range PCR, and Sanger sequencing to identify the pathogenic mutation. Functional analysis in the patient fibroblasts included oxygen consumption measurements, extracellular acidification studies, Western blotting, and calcium imaging, followed by overexpression of the wild-type protein. RESULTS Analysis of the exome sequencing depth revealed a homozygous deletion of exon 1 of MICU1 within a 2,755-base pair deletion. No MICU1 protein was detected in patient fibroblasts, which had impaired mitochondrial calcium uptake that was rescued through the overexpression of the wild-type allele. CONCLUSIONS MICU1 mutations cause fatigue and lethargy in patients with normal mitochondrial enzyme activities in muscle. The fluctuating clinical course is likely mediated through the mitochondrial calcium uniporter, which is regulated by MICU1.
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Affiliation(s)
- David Lewis-Smith
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Kimberli J Kamer
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Helen Griffin
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Anne-Marie Childs
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Karen Pysden
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Denis Titov
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Jennifer Duff
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Angela Pyle
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Robert W Taylor
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Patrick Yu-Wai-Man
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Venkateswaran Ramesh
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Rita Horvath
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Vamsi K Mootha
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
| | - Patrick F Chinnery
- Wellcome Trust Centre for Mitochondrial Research (D.L.-S., H.G., J.D., A.P., R.W.T., P.Y.-W.-M., R.H., P.F.C.), Institute of Genetic Medicine (D.L.-S., H.G., J.D., A.P., P.Y.-W.-M., R.H.), and Institute of Neuroscience (R.W.T.), Newcastle University, Newcastle upon Tyne, United Kingdom; Howard Hughes Medical Institute (K.J.K., D.T., V.K.M.), Department of Molecular Biology, Massachusetts General Hospital, Boston, MA; Department of Paediatric Neurology (A.-M.C., K.P.), The General Infirmary, Leeds, United Kingdom; Department of Child Neurology (V.R.), The Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, United Kingdom; Department of Systems Biology (V.K.M.), Harvard Medical School, Boston, MA; Broad Institute (V.K.M.), Cambridge, MA; Department of Clinical Neurosciences (P.F.C.), University of Cambridge; and MRC Mitochondrial Biology Unit (P.F.C.), Cambridge Biomedical Campus, United Kingdom
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416
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Woollard WJ, Kalaivani NP, Jones CL, Roper C, Tung L, Lee JJ, Thomas BR, Tosi I, Ferreira S, Beyers CZ, McKenzie RCT, Butler RM, Lorenc A, Whittaker SJ, Mitchell TJ. Independent Loss of Methylthioadenosine Phosphorylase (MTAP) in Primary Cutaneous T-Cell Lymphoma. J Invest Dermatol 2016; 136:1238-1246. [PMID: 26872600 DOI: 10.1016/j.jid.2016.01.028] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2015] [Revised: 12/07/2015] [Accepted: 01/20/2016] [Indexed: 10/22/2022]
Abstract
Methylthioadenosine phosphorylase (MTAP) and the tumor suppressor genes CDKN2A-CDKN2B are frequently deleted in malignancies. The specific role of MTAP in cutaneous T-cell lymphoma subgroups, mycosis fungoides (MF) and Sézary syndrome (SS), is unknown. In 213 skin samples from patients with MF/SS, MTAP copy number loss (34%) was more frequent than CDKN2A (12%) in all cutaneous T-cell lymphoma stages using quantitative reverse transcription PCR. Importantly, in early stage MF, MTAP loss occurred independently of CDKN2A loss in 37% of samples. In peripheral blood mononuclear cells from patients with SS, codeletion with CDKN2A occurred in 18% of samples but loss of MTAP alone was uncommon. In CD4(+) cells from SS, reduced MTAP mRNA expression correlated with MTAP copy number loss (P < 0.01) but reduced MTAP expression was also detected in the absence of copy number loss. Deep sequencing of MTAP/CDKN2A-CDKN2B loci in 77 peripheral blood mononuclear cell DNA samples from patients with SS did not show any nonsynonymous mutations, but read-depth analysis suggested focal deletions consistent with MTAP and CDKN2A copy number loss detected with quantitative reverse transcription PCR. In a cutaneous T-cell lymphoma cell line, promoter hypermethylation was shown to downregulate MTAP expression and may represent a mechanism of MTAP inactivation. In conclusion, our findings suggest that there may be selection in early stages of MF for MTAP deletion within the cutaneous tumor microenvironment.
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Affiliation(s)
- Wesley J Woollard
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Nithyha P Kalaivani
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Christine L Jones
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Catherine Roper
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Lam Tung
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Jae Jin Lee
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Bjorn R Thomas
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Isabella Tosi
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Silvia Ferreira
- Viapath, Skin Tumour Unit, St John's Institute of Dermatology, Guy's Hospital, London, UK
| | - Carl Z Beyers
- Viapath, Skin Tumour Unit, St John's Institute of Dermatology, Guy's Hospital, London, UK
| | - Robert C T McKenzie
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Rosie M Butler
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Anna Lorenc
- Transformational Bioinformatics, NIHR Research Biomedical Research Center at Guy's and St Thomas' Hospital Foundation Trust and Kings College London, London, UK
| | - Sean J Whittaker
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Tracey J Mitchell
- St John's Institute of Dermatology, Division of Genetics and Molecular Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK.
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417
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Ellingford JM, Barton S, Bhaskar S, Williams SG, Sergouniotis PI, O'Sullivan J, Lamb JA, Perveen R, Hall G, Newman WG, Bishop PN, Roberts SA, Leach R, Tearle R, Bayliss S, Ramsden SC, Nemeth AH, Black GCM. Whole Genome Sequencing Increases Molecular Diagnostic Yield Compared with Current Diagnostic Testing for Inherited Retinal Disease. Ophthalmology 2016; 123:1143-50. [PMID: 26872967 PMCID: PMC4845717 DOI: 10.1016/j.ophtha.2016.01.009] [Citation(s) in RCA: 97] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2015] [Revised: 01/07/2016] [Accepted: 01/07/2016] [Indexed: 10/25/2022] Open
Abstract
PURPOSE To compare the efficacy of whole genome sequencing (WGS) with targeted next-generation sequencing (NGS) in the diagnosis of inherited retinal disease (IRD). DESIGN Case series. PARTICIPANTS A total of 562 patients diagnosed with IRD. METHODS We performed a direct comparative analysis of current molecular diagnostics with WGS. We retrospectively reviewed the findings from a diagnostic NGS DNA test for 562 patients with IRD. A subset of 46 of 562 patients (encompassing potential clinical outcomes of diagnostic analysis) also underwent WGS, and we compared mutation detection rates and molecular diagnostic yields. In addition, we compared the sensitivity and specificity of the 2 techniques to identify known single nucleotide variants (SNVs) using 6 control samples with publically available genotype data. MAIN OUTCOME MEASURES Diagnostic yield of genomic testing. RESULTS Across known disease-causing genes, targeted NGS and WGS achieved similar levels of sensitivity and specificity for SNV detection. However, WGS also identified 14 clinically relevant genetic variants through WGS that had not been identified by NGS diagnostic testing for the 46 individuals with IRD. These variants included large deletions and variants in noncoding regions of the genome. Identification of these variants confirmed a molecular diagnosis of IRD for 11 of the 33 individuals referred for WGS who had not obtained a molecular diagnosis through targeted NGS testing. Weighted estimates, accounting for population structure, suggest that WGS methods could result in an overall 29% (95% confidence interval, 15-45) uplift in diagnostic yield. CONCLUSIONS We show that WGS methods can detect disease-causing genetic variants missed by current NGS diagnostic methodologies for IRD and thereby demonstrate the clinical utility and additional value of WGS.
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Affiliation(s)
- Jamie M Ellingford
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom; Institute of Human Development, University of Manchester, Manchester, United Kingdom
| | - Stephanie Barton
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Sanjeev Bhaskar
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Simon G Williams
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Panagiotis I Sergouniotis
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom; Institute of Human Development, University of Manchester, Manchester, United Kingdom; Manchester Royal Eye Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - James O'Sullivan
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom; Institute of Human Development, University of Manchester, Manchester, United Kingdom
| | - Janine A Lamb
- Institute of Population Health, University of Manchester, Manchester, United Kingdom
| | - Rahat Perveen
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom; Institute of Human Development, University of Manchester, Manchester, United Kingdom
| | - Georgina Hall
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - William G Newman
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom; Institute of Human Development, University of Manchester, Manchester, United Kingdom
| | - Paul N Bishop
- Institute of Human Development, University of Manchester, Manchester, United Kingdom; Manchester Royal Eye Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Stephen A Roberts
- Centre for Biostatistics, Institute of Population Health, University of Manchester, Manchester, United Kingdom
| | - Rick Leach
- Complete Genomics, Inc., Mountain View, California
| | - Rick Tearle
- Complete Genomics, Inc., Mountain View, California
| | - Stuart Bayliss
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Simon C Ramsden
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Andrea H Nemeth
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Graeme C M Black
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom; Institute of Human Development, University of Manchester, Manchester, United Kingdom; Manchester Royal Eye Hospital, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom.
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418
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Kremer L, Distelmaier F, Alhaddad B, Hempel M, Iuso A, Küpper C, Mühlhausen C, Kovacs-Nagy R, Satanovskij R, Graf E, Berutti R, Eckstein G, Durbin R, Sauer S, Hoffmann G, Strom T, Santer R, Meitinger T, Klopstock T, Prokisch H, Haack T. Bi-allelic Truncating Mutations in TANGO2 Cause Infancy-Onset Recurrent Metabolic Crises with Encephalocardiomyopathy. Am J Hum Genet 2016; 98:358-62. [PMID: 26805782 DOI: 10.1016/j.ajhg.2015.12.009] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2015] [Accepted: 12/21/2015] [Indexed: 10/22/2022] Open
Abstract
Molecular diagnosis of mitochondrial disorders is challenging because of extreme clinical and genetic heterogeneity. By exome sequencing, we identified three different bi-allelic truncating mutations in TANGO2 in three unrelated individuals with infancy-onset episodic metabolic crises characterized by encephalopathy, hypoglycemia, rhabdomyolysis, arrhythmias, and laboratory findings suggestive of a defect in mitochondrial fatty acid oxidation. Over the course of the disease, all individuals developed global brain atrophy with cognitive impairment and pyramidal signs. TANGO2 (transport and Golgi organization 2) encodes a protein with a putative function in redistribution of Golgi membranes into the endoplasmic reticulum in Drosophila and a mitochondrial localization has been confirmed in mice. Investigation of palmitate-dependent respiration in mutant fibroblasts showed evidence of a functional defect in mitochondrial β-oxidation. Our results establish TANGO2 deficiency as a clinically recognizable cause of pediatric disease with multi-organ involvement.
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419
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Lefterova MI, Shen P, Odegaard JI, Fung E, Chiang T, Peng G, Davis RW, Wang W, Kharrazi M, Schrijver I, Scharfe C. Next-Generation Molecular Testing of Newborn Dried Blood Spots for Cystic Fibrosis. J Mol Diagn 2016; 18:267-82. [PMID: 26847993 DOI: 10.1016/j.jmoldx.2015.11.005] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2015] [Revised: 10/21/2015] [Accepted: 11/19/2015] [Indexed: 12/19/2022] Open
Abstract
Newborn screening for cystic fibrosis enables early detection and management of this debilitating genetic disease. Implementing comprehensive CFTR analysis using Sanger sequencing as a component of confirmatory testing of all screen-positive newborns has remained impractical due to relatively lengthy turnaround times and high cost. Here, we describe CFseq, a highly sensitive, specific, rapid (<3 days), and cost-effective assay for comprehensive CFTR gene analysis from dried blood spots, the common newborn screening specimen. The unique design of CFseq integrates optimized dried blood spot sample processing, a novel multiplex amplification method from as little as 1 ng of genomic DNA, and multiplex next-generation sequencing of 96 samples in a single run to detect all relevant CFTR mutation types. Sequence data analysis utilizes publicly available software supplemented by an expert-curated compendium of >2000 CFTR variants. Validation studies across 190 dried blood spots demonstrated 100% sensitivity and a positive predictive value of 100% for single-nucleotide variants and insertions and deletions and complete concordance across the polymorphic poly-TG and consecutive poly-T tracts. Additionally, we accurately detected both a known exon 2,3 deletion and a previously undetected exon 22,23 deletion. CFseq is thus able to replace all existing CFTR molecular assays with a single robust, definitive assay at significant cost and time savings and could be adapted to high-throughput screening of other inherited conditions.
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Affiliation(s)
- Martina I Lefterova
- Department of Pathology, Stanford University Medical Center, Stanford, California
| | - Peidong Shen
- Stanford Genome Technology Center, Stanford University, Palo Alto, California
| | - Justin I Odegaard
- Department of Pathology, Stanford University Medical Center, Stanford, California
| | - Eula Fung
- Department of Pathology, Stanford University Medical Center, Stanford, California
| | - Tsoyu Chiang
- Department of Pathology, Stanford University Medical Center, Stanford, California
| | - Gang Peng
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Ronald W Davis
- Stanford Genome Technology Center, Stanford University, Palo Alto, California
| | - Wenyi Wang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Martin Kharrazi
- California Department of Public Health, Environmental Health Investigations Branch, Richmond, California
| | - Iris Schrijver
- Department of Pathology, Stanford University Medical Center, Stanford, California; Department of Pediatrics, Stanford University Medical Center, Stanford, California
| | - Curt Scharfe
- Department of Pathology, Stanford University Medical Center, Stanford, California; Stanford Genome Technology Center, Stanford University, Palo Alto, California.
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420
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Urquhart J, Roberts R, de Silva D, Shalev S, Chervinsky E, Nampoothiri S, Sznajer Y, Revencu N, Gunasekera R, Suri M, Ellingford J, Williams S, Bhaskar S, Clayton-Smith J. Exploring the genetic basis of 3MC syndrome: Findings in 12 further families. Am J Med Genet A 2016; 170A:1216-24. [DOI: 10.1002/ajmg.a.37564] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Accepted: 12/22/2015] [Indexed: 12/18/2022]
Affiliation(s)
- Jill Urquhart
- Faculty of Medical and Human Sciences, Institute of Human Development, Manchester Centre for Genomic Medicine, University of Manchester; Manchester Academic Health Science Centre (MAHSC); Manchester United Kingdom
- Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust; MAHSC; Manchester United Kingdom
| | - Rebecca Roberts
- Manchester Medical School; University of Manchester; Manchester United Kingdom
| | - Deepthi de Silva
- Faculty of Medicine, Department of Physiology; University of Kelaniya; Ragama Sri Lanka
| | - Stavit Shalev
- Genetic Institute; Ha'Emek Medical Center; Afula Israel
| | | | | | - Yves Sznajer
- Cliniques Universitaires Saint-Luc; Centre for Human Genetics; Brussels Belgium
| | - Nicole Revencu
- Cliniques Universitaires Saint-Luc; Centre for Human Genetics; Brussels Belgium
| | - Romesh Gunasekera
- Department of Plastic Surgery; Lady Ridgeway Hospital; Colombo Sri Lanka
| | - Mohnish Suri
- Nottingham Clinical Genetics Service, Nottingham University Hospitals NHS Trust; City Hospital Campus; Nottingham United Kingdom
| | - Jamie Ellingford
- Faculty of Medical and Human Sciences, Institute of Human Development, Manchester Centre for Genomic Medicine, University of Manchester; Manchester Academic Health Science Centre (MAHSC); Manchester United Kingdom
- Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust; MAHSC; Manchester United Kingdom
| | - Simon Williams
- Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust; MAHSC; Manchester United Kingdom
| | - Sanjeev Bhaskar
- Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust; MAHSC; Manchester United Kingdom
| | - Jill Clayton-Smith
- Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust; MAHSC; Manchester United Kingdom
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421
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Weisschuh N, Mayer AK, Strom TM, Kohl S, Glöckle N, Schubach M, Andreasson S, Bernd A, Birch DG, Hamel CP, Heckenlively JR, Jacobson SG, Kamme C, Kellner U, Kunstmann E, Maffei P, Reiff CM, Rohrschneider K, Rosenberg T, Rudolph G, Vámos R, Varsányi B, Weleber RG, Wissinger B. Mutation Detection in Patients with Retinal Dystrophies Using Targeted Next Generation Sequencing. PLoS One 2016; 11:e0145951. [PMID: 26766544 PMCID: PMC4713063 DOI: 10.1371/journal.pone.0145951] [Citation(s) in RCA: 82] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Accepted: 12/10/2015] [Indexed: 11/24/2022] Open
Abstract
Retinal dystrophies (RD) constitute a group of blinding diseases that are characterized by clinical variability and pronounced genetic heterogeneity. The different nonsyndromic and syndromic forms of RD can be attributed to mutations in more than 200 genes. Consequently, next generation sequencing (NGS) technologies are among the most promising approaches to identify mutations in RD. We screened a large cohort of patients comprising 89 independent cases and families with various subforms of RD applying different NGS platforms. While mutation screening in 50 cases was performed using a RD gene capture panel, 47 cases were analyzed using whole exome sequencing. One family was analyzed using whole genome sequencing. A detection rate of 61% was achieved including mutations in 34 known and two novel RD genes. A total of 69 distinct mutations were identified, including 39 novel mutations. Notably, genetic findings in several families were not consistent with the initial clinical diagnosis. Clinical reassessment resulted in refinement of the clinical diagnosis in some of these families and confirmed the broad clinical spectrum associated with mutations in RD genes.
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Affiliation(s)
- Nicole Weisschuh
- Molecular Genetics Laboratory, Institute for Ophthalmic Research, Centre for Ophthalmology, University of Tuebingen, Tuebingen, Germany
- * E-mail:
| | - Anja K. Mayer
- Molecular Genetics Laboratory, Institute for Ophthalmic Research, Centre for Ophthalmology, University of Tuebingen, Tuebingen, Germany
| | - Tim M. Strom
- Institute of Human Genetics, Helmholtz Zentrum Muenchen, Neuherberg, Germany
| | - Susanne Kohl
- Molecular Genetics Laboratory, Institute for Ophthalmic Research, Centre for Ophthalmology, University of Tuebingen, Tuebingen, Germany
| | | | - Max Schubach
- Institute of Medical Genetics and Human Genetics, Charité – Universitaetsmedizin Berlin, Berlin, Germany
| | | | - Antje Bernd
- University Eye Hospital, Centre for Ophthalmology, University of Tuebingen, Tuebingen, Germany
| | - David G. Birch
- The Retina Foundation of the Southwest, Dallas, Texas, United States of America
| | | | - John R. Heckenlively
- Department of Ophthalmology and Visual Sciences, Kellogg Eye Center, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Samuel G. Jacobson
- Scheie Eye Institute, Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | | | - Ulrich Kellner
- Rare Retinal Disease Center, AugenZentrum Siegburg, MVZ ADTC Siegburg GmbH, Siegburg, Germany
| | - Erdmute Kunstmann
- Institute of Human Genetics, Julius-Maximilian-University, Wuerzburg, Germany
| | - Pietro Maffei
- Department of Medicine, University Hospital of Padua, Padua, Italy
| | | | | | - Thomas Rosenberg
- National Eye Clinic, Department of Ophthalmology, Glostrup Hospital, Glostrup, Denmark
| | - Günther Rudolph
- University Eye Hospital, Ludwig Maximilians University, Munich, Germany
| | - Rita Vámos
- Department of Ophthalmology, Semmelweis University, Budapest, Hungary
| | - Balázs Varsányi
- Department of Ophthalmology, Semmelweis University, Budapest, Hungary
- Department of Ophthalmology, University of Pécs Medical School, Pécs, Hungary
| | - Richard G. Weleber
- Casey Eye Institute, Oregon Retinal Degeneration Center, Oregon Health & Science University, Portland, Oregon, United States of America
| | - Bernd Wissinger
- Molecular Genetics Laboratory, Institute for Ophthalmic Research, Centre for Ophthalmology, University of Tuebingen, Tuebingen, Germany
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422
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Samarakoon PS, Sorte HS, Stray-Pedersen A, Rødningen OK, Rognes T, Lyle R. cnvScan: a CNV screening and annotation tool to improve the clinical utility of computational CNV prediction from exome sequencing data. BMC Genomics 2016; 17:51. [PMID: 26764020 PMCID: PMC4712464 DOI: 10.1186/s12864-016-2374-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2015] [Accepted: 01/06/2016] [Indexed: 12/30/2022] Open
Abstract
Background With advances in next generation sequencing technology and analysis methods, single nucleotide variants (SNVs) and indels can be detected with high sensitivity and specificity in exome sequencing data. Recent studies have demonstrated the ability to detect disease-causing copy number variants (CNVs) in exome sequencing data. However, exonic CNV prediction programs have shown high false positive CNV counts, which is the major limiting factor for the applicability of these programs in clinical studies. Results We have developed a tool (cnvScan) to improve the clinical utility of computational CNV prediction in exome data. cnvScan can accept input from any CNV prediction program. cnvScan consists of two steps: CNV screening and CNV annotation. CNV screening evaluates CNV prediction using quality scores and refines this using an in-house CNV database, which greatly reduces the false positive rate. The annotation step provides functionally and clinically relevant information using multiple source datasets. We assessed the performance of cnvScan on CNV predictions from five different prediction programs using 64 exomes from Primary Immunodeficiency (PIDD) patients, and identified PIDD-causing CNVs in three individuals from two different families. Conclusions In summary, cnvScan reduces the time and effort required to detect disease-causing CNVs by reducing the false positive count and providing annotation. This improves the clinical utility of CNV detection in exome data. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2374-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Hanne Sørmo Sorte
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway.
| | - Asbjørg Stray-Pedersen
- Norwegian National Newborn Screening, Oslo University Hospital, Oslo, Norway. .,Center for Human Immunobiology/Section of Immunology, Allergy, and Rheumatology, Texas Children's Hospital, Houston, TX, USA. .,Baylor-Hopkins Center for Mendelian Genomics of the Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
| | - Olaug Kristin Rødningen
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway.
| | - Torbjørn Rognes
- Department of Informatics, University of Oslo, Oslo, Norway. .,Department of Microbiology, Oslo University Hospital, Oslo, Norway.
| | - Robert Lyle
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway.
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423
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Smith MJ, Urquhart JE, Harkness EF, Miles EK, Bowers NL, Byers HJ, Bulman M, Gokhale C, Wallace AJ, Newman WG, Evans DG. The Contribution of Whole Gene Deletions and Large Rearrangements to the Mutation Spectrum in Inherited Tumor Predisposing Syndromes. Hum Mutat 2016; 37:250-6. [DOI: 10.1002/humu.22938] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Accepted: 11/20/2015] [Indexed: 12/27/2022]
Affiliation(s)
- Miriam J. Smith
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
| | - Jill E. Urquhart
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
| | - Elaine F. Harkness
- Centre for Imaging Sciences; University of Manchester; Manchester M13 9PY UK
| | - Emma K. Miles
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
| | - Naomi L. Bowers
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
| | - Helen J. Byers
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
| | - Michael Bulman
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
| | - Carolyn Gokhale
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
| | - Andrew J. Wallace
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
| | - William G. Newman
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
| | - D. Gareth Evans
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester Academic Health Sciences Centre (MAHSC); University of Manchester; Manchester M13 9WL UK
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424
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Davidson A, Liskova P, Evans C, Dudakova L, Nosková L, Pontikos N, Hartmannová H, Hodaňová K, Stránecký V, Kozmík Z, Levis H, Idigo N, Sasai N, Maher G, Bellingham J, Veli N, Ebenezer N, Cheetham M, Daniels J, Thaung C, Jirsova K, Plagnol V, Filipec M, Kmoch S, Tuft S, Hardcastle A. Autosomal-Dominant Corneal Endothelial Dystrophies CHED1 and PPCD1 Are Allelic Disorders Caused by Non-coding Mutations in the Promoter of OVOL2. Am J Hum Genet 2016; 98:75-89. [PMID: 26749309 PMCID: PMC4716680 DOI: 10.1016/j.ajhg.2015.11.018] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Accepted: 11/13/2015] [Indexed: 11/27/2022] Open
Abstract
Congenital hereditary endothelial dystrophy 1 (CHED1) and posterior polymorphous corneal dystrophy 1 (PPCD1) are autosomal-dominant corneal endothelial dystrophies that have been genetically mapped to overlapping loci on the short arm of chromosome 20. We combined genetic and genomic approaches to identify the cause of disease in extensive pedigrees comprising over 100 affected individuals. After exclusion of pathogenic coding, splice-site, and copy-number variations, a parallel approach using targeted and whole-genome sequencing facilitated the identification of pathogenic variants in a conserved region of the OVOL2 proximal promoter sequence in the index families (c.−339_361dup for CHED1 and c.−370T>C for PPCD1). Direct sequencing of the OVOL2 promoter in other unrelated affected individuals identified two additional mutations within the conserved proximal promoter sequence (c.−274T>G and c.−307T>C). OVOL2 encodes ovo-like zinc finger 2, a C2H2 zinc-finger transcription factor that regulates mesenchymal-to-epithelial transition and acts as a direct transcriptional repressor of the established PPCD-associated gene ZEB1. Interestingly, we did not detect OVOL2 expression in the normal corneal endothelium. Our in vitro data demonstrate that all four mutated OVOL2 promoters exhibited more transcriptional activity than the corresponding wild-type promoter, and we postulate that the mutations identified create cryptic cis-acting regulatory sequence binding sites that drive aberrant OVOL2 expression during endothelial cell development. Our data establish CHED1 and PPCD1 as allelic conditions and show that CHED1 represents the extreme of what can be considered a disease spectrum. They also implicate transcriptional dysregulation of OVOL2 as a common cause of dominantly inherited corneal endothelial dystrophies.
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425
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Shen W, Szankasi P, Sederberg M, Schumacher J, Frizzell KA, Gee EP, Patel JL, South ST, Xu X, Kelley TW. Concurrent detection of targeted copy number variants and mutations using a myeloid malignancy next generation sequencing panel allows comprehensive genetic analysis using a single testing strategy. Br J Haematol 2016; 173:49-58. [PMID: 26728869 DOI: 10.1111/bjh.13921] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2015] [Accepted: 11/19/2015] [Indexed: 02/06/2023]
Abstract
Currently, comprehensive genetic testing of myeloid malignancies requires multiple testing strategies with high costs. Somatic mutations can be detected by next generation sequencing (NGS) but copy number variants (CNVs) require cytogenetic methods including karyotyping, fluorescence in situ hybidization and microarray. Here, we evaluated a new method for CNV detection using read depth data derived from a targeted NGS mutation panel. In a cohort of 270 samples, we detected pathogenic mutations in 208 samples and targeted CNVs in 68 cases. The most frequent CNVs were 7q deletion including LUC7L2 and EZH2, TP53 deletion, ETV6 deletion, gain of RAD21 on 8q, and 5q deletion, including NSD1 and NPM1. We were also able to detect exon-level duplications, including so-called KMT2A (MLL) partial tandem duplication, in 9 cases. In the 63 cases that were negative for mutations, targeted CNVs were observed in 4 cases. Targeted CNV detection by NGS had very high concordance with single nucleotide polymorphism microarray, the current gold standard. We found that ETV6 deletion was strongly associated with TP53 alterations and 7q deletion was associated with mutations in TP53, KRAS and IDH1. This proof-of-concept study demonstrates the feasibility of using the same NGS data to simultaneously detect both somatic mutations and targeted CNVs.
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Affiliation(s)
- Wei Shen
- ARUP Laboratories, Salt Lake City, UT, USA
| | | | | | | | | | | | - Jay L Patel
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Sarah T South
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Xinjie Xu
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Todd W Kelley
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA
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426
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Pugh TJ, Amr SS, Bowser MJ, Gowrisankar S, Hynes E, Mahanta LM, Rehm HL, Funke B, Lebo MS. VisCap: inference and visualization of germ-line copy-number variants from targeted clinical sequencing data. Genet Med 2015; 18:712-9. [PMID: 26681316 PMCID: PMC4940431 DOI: 10.1038/gim.2015.156] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2015] [Accepted: 09/15/2015] [Indexed: 01/10/2023] Open
Abstract
Purpose: To develop and validate VisCap, a software program targeted to clinical laboratories for inference and visualization of germ-line copy-number variants (CNVs) from targeted next-generation sequencing data. Genet Med18 7, 712–719. Methods: VisCap calculates the fraction of overall sequence coverage assigned to genomic intervals and computes log2 ratios of these values to the median of reference samples profiled using the same test configuration. Candidate CNVs are called when log2 ratios exceed user-defined thresholds. Genet Med18 7, 712–719. Results: We optimized VisCap using 14 cases with known CNVs, followed by prospective analysis of 1,104 cases referred for diagnostic DNA sequencing. To verify calls in the prospective cohort, we used droplet digital polymerase chain reaction (PCR) to confirm 10/27 candidate CNVs and 72/72 copy-neutral genomic regions scored by VisCap. We also used a genome-wide bead array to confirm the absence of CNV calls across panels applied to 10 cases. To improve specificity, we instituted a visual scoring system that enabled experienced reviewers to differentiate true-positive from false-positive calls with minimal impact on laboratory workflow. Genet Med18 7, 712–719. Conclusions: VisCap is a sensitive method for inferring CNVs from targeted sequence data from targeted gene panels. Visual scoring of data underlying CNV calls is a critical step to reduce false-positive calls for follow-up testing. Genet Med18 7, 712–719.
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Affiliation(s)
- Trevor J Pugh
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Sami S Amr
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, Massachusetts, USA.,Department of Pathology, Brigham and Women's Hospital and Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Pathology, Harvard Medical School, Boston, Massachusetts, USA
| | - Mark J Bowser
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, Massachusetts, USA
| | - Sivakumar Gowrisankar
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, Massachusetts, USA
| | - Elizabeth Hynes
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, Massachusetts, USA
| | - Lisa M Mahanta
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, Massachusetts, USA
| | - Heidi L Rehm
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, Massachusetts, USA.,Department of Pathology, Brigham and Women's Hospital and Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Pathology, Harvard Medical School, Boston, Massachusetts, USA
| | - Birgit Funke
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, Massachusetts, USA.,Department of Pathology, Brigham and Women's Hospital and Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Pathology, Harvard Medical School, Boston, Massachusetts, USA
| | - Matthew S Lebo
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Boston, Massachusetts, USA.,Department of Pathology, Brigham and Women's Hospital and Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Pathology, Harvard Medical School, Boston, Massachusetts, USA
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427
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Seaby EG, Pengelly RJ, Ennis S. Exome sequencing explained: a practical guide to its clinical application. Brief Funct Genomics 2015; 15:374-84. [PMID: 26654982 DOI: 10.1093/bfgp/elv054] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Next-generation sequencing has catapulted healthcare into a revolutionary genomics era. One such technology, whole-exome sequencing, which targets the protein-coding regions of the genome, has proven success in identifying new causal mutations for diseases of previously unknown etiology. With a successful diagnostic rate approaching 25% for rare disease in recent studies, its clinical utility is becoming increasingly popular. However, the interpretation of whole-exome sequencing data requires expertise in genomic informatics and clinical medicine to ensure the accurate and safe reporting of findings back to the bedside. This is challenged by vast amounts of sequencing data harbouring approximately 25 000 variants per sequenced individual. Computational strategies and fastidious filtering frameworks are thus required to extricate candidate variants in a sea of common polymorphisms. Once prioritized, identified variants require intensive scrutiny at a biological level, and require judicious assessment alongside the clinical phenotype. In the final step, all evidence is collated and documented alongside pathogenicity guidelines to produce an exome report that returns to the clinic. This review provides a practical guide for clinicians and genomic informaticians on the clinical application of whole-exome sequencing. We address sequencing capture and methodology, quality control parameters at different stages of sequencing analysis and propose an exome data filtering strategy that includes primary filtering (for the removal of probable benign variants) and secondary filtering for the prioritization of remaining candidates.
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428
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Zhang H, Zhao YY, Song J, Zhu QY, Yang H, Zheng ML, Xuan ZL, Wei Y, Chen Y, Yuan PB, Yu Y, Li DW, Liang JB, Fan L, Chen CJ, Qiao J. Statistical Approach to Decreasing the Error Rate of Noninvasive Prenatal Aneuploid Detection caused by Maternal Copy Number Variation. Sci Rep 2015; 5:16106. [PMID: 26534864 PMCID: PMC4632076 DOI: 10.1038/srep16106] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Accepted: 09/29/2015] [Indexed: 12/18/2022] Open
Abstract
Analyses of cell-free fetal DNA (cff-DNA) from maternal plasma using massively parallel sequencing enable the noninvasive detection of feto-placental chromosome aneuploidy; this technique has been widely used in clinics worldwide. Noninvasive prenatal tests (NIPT) based on cff-DNA have achieved very high accuracy; however, they suffer from maternal copy-number variations (CNV) that may cause false positives and false negatives. In this study, we developed an algorithm to exclude the effect of maternal CNV and refined the Z-score that is used to determine fetal aneuploidy. The simulation results showed that the algorithm is robust against variations of fetal concentration and maternal CNV size. We also introduced a method based on the discrepancy between feto-placental concentrations to help reduce the false-positive ratio. A total of 6615 pregnant women were enrolled in a prospective study to validate the accuracy of our method. All 106 fetuses with T21, 20 with T18, and three with T13 were tested using our method, with sensitivity of 100% and specificity of 99.97%. In the results, two cases with maternal duplications in chromosome 21, which were falsely predicted as T21 by the previous NIPT method, were correctly classified as normal by our algorithm, which demonstrated the effectiveness of our approach.
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Affiliation(s)
- Han Zhang
- Annoroad Gene Technology Co., Ltd, Beijing, China
| | - Yang-Yu Zhao
- Department of Gynecology and Obstetrics, Peking University Third Hospital, Beijing, China
| | - Jing Song
- Department of Obstetrics, Beijing Obsterics and Gynecology Hospital, Capital Medical University, Beijing, China
| | - Qi-Ying Zhu
- The Obstetric Department of First Affiliated Hospital of Xinjiang Medical University, Urumqi, China
| | - Hua Yang
- Department of Obstetrics and Gynecology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Mei-Ling Zheng
- Department of Obstetrics and Gynecology, First Hospital of Shanxi Medical University, Shanxi, China
| | | | - Yuan Wei
- Department of Gynecology and Obstetrics, Peking University Third Hospital, Beijing, China
| | - Yang Chen
- Annoroad Gene Technology Co., Ltd, Beijing, China
| | - Peng-Bo Yuan
- Department of Gynecology and Obstetrics, Peking University Third Hospital, Beijing, China
| | - Yang Yu
- Department of Gynecology and Obstetrics, Peking University Third Hospital, Beijing, China
| | - Da-Wei Li
- Annoroad Gene Technology Co., Ltd, Beijing, China
| | | | - Ling Fan
- Department of Obstetrics, Beijing Obsterics and Gynecology Hospital, Capital Medical University, Beijing, China
| | | | - Jie Qiao
- Department of Gynecology and Obstetrics, Peking University Third Hospital, Beijing, China
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429
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Lopes L, Murphy C, Syrris P, Dalageorgou C, McKenna W, Elliott P, Plagnol V. Use of high-throughput targeted exome-sequencing to screen for copy number variation in hypertrophic cardiomyopathy. Eur J Med Genet 2015; 58:611-6. [DOI: 10.1016/j.ejmg.2015.10.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2015] [Revised: 09/11/2015] [Accepted: 10/02/2015] [Indexed: 10/22/2022]
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430
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Melo US, Macedo-Souza LI, Figueiredo T, Muotri AR, Gleeson JG, Coux G, Armas P, Calcaterra NB, Kitajima JP, Amorim S, Olávio TR, Griesi-Oliveira K, Coatti GC, Rocha CRR, Martins-Pinheiro M, Menck CFM, Zaki MS, Kok F, Zatz M, Santos S. Overexpression of KLC2 due to a homozygous deletion in the non-coding region causes SPOAN syndrome. Hum Mol Genet 2015; 24:6877-85. [PMID: 26385635 DOI: 10.1093/hmg/ddv388] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2015] [Accepted: 09/14/2015] [Indexed: 02/06/2023] Open
Abstract
SPOAN syndrome is a neurodegenerative disorder mainly characterized by spastic paraplegia, optic atrophy and neuropathy (SPOAN). Affected patients are wheelchair bound after 15 years old, with progressive joint contractures and spine deformities. SPOAN patients also have sub normal vision secondary to apparently non-progressive congenital optic atrophy. A potential causative gene was mapped at 11q13 ten years ago. Here we performed next-generation sequencing in SPOAN-derived samples. While whole-exome sequencing failed to identify the causative mutation, whole-genome sequencing allowed to detect a homozygous 216-bp deletion (chr11.hg19:g.66,024,557_66,024,773del) located at the non-coding upstream region of the KLC2 gene. Expression assays performed with patient's fibroblasts and motor neurons derived from SPOAN patients showed KLC2 overexpression. Luciferase assay in constructs with 216-bp deletion confirmed the overexpression of gene reporter, varying from 48 to 74%, as compared with wild-type. Knockdown and overexpression of klc2 in Danio rerio revealed mild to severe curly-tail phenotype, which is suggestive of a neuromuscular disorder. Overexpression of a gene caused by a small deletion in the non-coding region is a novel mechanism, which to the best of our knowledge, was never reported before in a recessive condition. Although the molecular mechanism of KLC2 up-regulation still remains to be uncovered, such example adds to the importance of non-coding regions in human pathology.
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Affiliation(s)
- Uirá S Melo
- Human Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP 05508-090, Brazil
| | - Lucia I Macedo-Souza
- Human Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP 05508-090, Brazil
| | - Thalita Figueiredo
- Northeast Biotechnology Network (RENORBIO), Federal University of Paraiba (UFPB), Joao Pessoa, PB 58051-900, Brazil, Department of Biology, Paraiba State University (UEPB), Campina Grande, PB 58429-500, Brazil
| | - Alysson R Muotri
- Department of Pediatrics/Rady Children's Hospital San Diego, University of California San Diego, La Jolla, CA 92093, USA
| | - Joseph G Gleeson
- Laboratory for Pediatric Brain Disease, The Rockefeller University, New York, NY 10065, USA
| | - Gabriela Coux
- Instituto de Biología Molecular y Celular de Rosario (IBR), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) - Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario (UNR), Rosario, SF S2002LRK, Argentina
| | - Pablo Armas
- Instituto de Biología Molecular y Celular de Rosario (IBR), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) - Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario (UNR), Rosario, SF S2002LRK, Argentina
| | - Nora B Calcaterra
- Instituto de Biología Molecular y Celular de Rosario (IBR), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) - Facultad de Ciencias Bioquímicas y Farmacéuticas, Universidad Nacional de Rosario (UNR), Rosario, SF S2002LRK, Argentina
| | | | - Simone Amorim
- Department of Neurology, School of Medicine, University of Sao Paulo (USP), São Paulo, SP 01246-903, Brazil
| | - Thiago R Olávio
- Human Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP 05508-090, Brazil
| | - Karina Griesi-Oliveira
- Human Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP 05508-090, Brazil
| | - Giuliana C Coatti
- Human Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP 05508-090, Brazil
| | - Clarissa R R Rocha
- Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, SP 05508-900, Brazil and
| | - Marinalva Martins-Pinheiro
- Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, SP 05508-900, Brazil and
| | - Carlos F M Menck
- Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo (USP), São Paulo, SP 05508-900, Brazil and
| | - Maha S Zaki
- Department of Clinical Genetics, Human Genetics and Genome Research Division, National Research Center, Cairo 12311, Egypt
| | - Fernando Kok
- Human Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP 05508-090, Brazil, Mendelics Genomic Analysis, São Paulo, SP 04013-000, Brazil
| | - Mayana Zatz
- Human Genome and Stem Cell Research Center, Department of Genetics and Evolutionary Biology, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP 05508-090, Brazil,
| | - Silvana Santos
- Northeast Biotechnology Network (RENORBIO), Federal University of Paraiba (UFPB), Joao Pessoa, PB 58051-900, Brazil, Department of Biology, Paraiba State University (UEPB), Campina Grande, PB 58429-500, Brazil
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431
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Packer JS, Maxwell EK, O'Dushlaine C, Lopez AE, Dewey FE, Chernomorsky R, Baras A, Overton JD, Habegger L, Reid JG. CLAMMS: a scalable algorithm for calling common and rare copy number variants from exome sequencing data. Bioinformatics 2015; 32:133-5. [PMID: 26382196 PMCID: PMC4681995 DOI: 10.1093/bioinformatics/btv547] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Accepted: 09/09/2015] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Several algorithms exist for detecting copy number variants (CNVs) from human exome sequencing read depth, but previous tools have not been well suited for large population studies on the order of tens or hundreds of thousands of exomes. Their limitations include being difficult to integrate into automated variant-calling pipelines and being ill-suited for detecting common variants. To address these issues, we developed a new algorithm--Copy number estimation using Lattice-Aligned Mixture Models (CLAMMS)--which is highly scalable and suitable for detecting CNVs across the whole allele frequency spectrum. RESULTS In this note, we summarize the methods and intended use-case of CLAMMS, compare it to previous algorithms and briefly describe results of validation experiments. We evaluate the adherence of CNV calls from CLAMMS and four other algorithms to Mendelian inheritance patterns on a pedigree; we compare calls from CLAMMS and other algorithms to calls from SNP genotyping arrays for a set of 3164 samples; and we use TaqMan quantitative polymerase chain reaction to validate CNVs predicted by CLAMMS at 39 loci (95% of rare variants validate; across 19 common variant loci, the mean precision and recall are 99% and 94%, respectively). In the Supplementary Materials (available at the CLAMMS Github repository), we present our methods and validation results in greater detail. AVAILABILITY AND IMPLEMENTATION https://github.com/rgcgithub/clamms (implemented in C). CONTACT jeffrey.reid@regeneron.com SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | | | | | | | | | | | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY 10591, USA
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432
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Duan J, Wan M, Deng HW, Wang YP. A Sparse Model Based Detection of Copy Number Variations From Exome Sequencing Data. IEEE Trans Biomed Eng 2015; 63:496-505. [PMID: 26258935 DOI: 10.1109/tbme.2015.2464674] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
GOAL Whole-exome sequencing provides a more cost-effective way than whole-genome sequencing for detecting genetic variants, such as copy number variations (CNVs). Although a number of approaches have been proposed to detect CNVs from whole-genome sequencing, a direct adoption of these approaches to whole-exome sequencing will often fail because exons are separately located along a genome. Therefore, an appropriate method is needed to target the specific features of exome sequencing data. METHODS In this paper, a novel sparse model based method is proposed to discover CNVs from multiple exome sequencing data. First, exome sequencing data are represented with a penalized matrix approximation, and technical variability and random sequencing errors are assumed to follow a generalized Gaussian distribution. Second, an iteratively reweighted least squares algorithm is used to estimate the solution. RESULTS The method is tested and validated on both synthetic and real data, and compared with other approaches including CoNIFER, XHMM, and cn.MOPS. The test demonstrates that the proposed method outperform other approaches. CONCLUSION The proposed sparse model can detect CNVs from exome sequencing data with high power and precision. Significance: Sparse model can target the specific features of exome sequencing data. The software codes are freely available at http://www.tulane.edu/ wyp/software/Exon_CNV.m.
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433
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Nam JY, Kim NKD, Kim SC, Joung JG, Xi R, Lee S, Park PJ, Park WY. Evaluation of somatic copy number estimation tools for whole-exome sequencing data. Brief Bioinform 2015. [PMID: 26210357 DOI: 10.1093/bib/bbv055] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Whole-exome sequencing (WES) has become a standard method for detecting genetic variants in human diseases. Although the primary use of WES data has been the identification of single nucleotide variations and indels, these data also offer a possibility of detecting copy number variations (CNVs) at high resolution. However, WES data have uneven read coverage along the genome owing to the target capture step, and the development of a robust WES-based CNV tool is challenging. Here, we evaluate six WES somatic CNV detection tools: ADTEx, CONTRA, Control-FREEC, EXCAVATOR, ExomeCNV and Varscan2. Using WES data from 50 kidney chromophobe, 50 bladder urothelial carcinoma, and 50 stomach adenocarcinoma patients from The Cancer Genome Atlas, we compared the CNV calls from the six tools with a reference CNV set that was identified by both single nucleotide polymorphism array 6.0 and whole-genome sequencing data. We found that these algorithms gave highly variable results: visual inspection reveals significant differences between the WES-based segmentation profiles and the reference profile, as well as among the WES-based profiles. Using a 50% overlap criterion, 13-77% of WES CNV calls were covered by CNVs from the reference set, up to 21% of the copy gains were called as losses or vice versa, and dramatic differences in CNV sizes and CNV numbers were observed. Overall, ADTEx and EXCAVATOR had the best performance with relatively high precision and sensitivity. We suggest that the current algorithms for somatic CNV detection from WES data are limited in their performance and that more robust algorithms are needed.
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434
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Taylor JC, Martin HC, Lise S, Broxholme J, Cazier JB, Rimmer A, Kanapin A, Lunter G, Fiddy S, Allan C, Aricescu AR, Attar M, Babbs C, Becq J, Beeson D, Bento C, Bignell P, Blair E, Buckle VJ, Bull K, Cais O, Cario H, Chapel H, Copley RR, Cornall R, Craft J, Dahan K, Davenport EE, Dendrou C, Devuyst O, Fenwick AL, Flint J, Fugger L, Gilbert RD, Goriely A, Green A, Greger IH, Grocock R, Gruszczyk AV, Hastings R, Hatton E, Higgs D, Hill A, Holmes C, Howard M, Hughes L, Humburg P, Johnson D, Karpe F, Kingsbury Z, Kini U, Knight JC, Krohn J, Lamble S, Langman C, Lonie L, Luck J, McCarthy D, McGowan SJ, McMullin MF, Miller KA, Murray L, Németh AH, Nesbit MA, Nutt D, Ormondroyd E, Oturai AB, Pagnamenta A, Patel SY, Percy M, Petousi N, Piazza P, Piret SE, Polanco-Echeverry G, Popitsch N, Powrie F, Pugh C, Quek L, Robbins PA, Robson K, Russo A, Sahgal N, van Schouwenburg PA, Schuh A, Silverman E, Simmons A, Sørensen PS, Sweeney E, Taylor J, Thakker RV, Tomlinson I, Trebes A, Twigg SR, Uhlig HH, Vyas P, Vyse T, Wall SA, Watkins H, Whyte MP, Witty L, Wright B, Yau C, Buck D, Humphray S, Ratcliffe PJ, Bell JI, Wilkie AO, Bentley D, Donnelly P, McVean G. Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Nat Genet 2015; 47:717-726. [PMID: 25985138 PMCID: PMC4601524 DOI: 10.1038/ng.3304] [Citation(s) in RCA: 250] [Impact Index Per Article: 27.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2014] [Accepted: 04/22/2015] [Indexed: 12/12/2022]
Abstract
To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.
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Affiliation(s)
- Jenny C Taylor
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Hilary C Martin
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Stefano Lise
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - John Broxholme
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Andy Rimmer
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Alexander Kanapin
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Gerton Lunter
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Simon Fiddy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Chris Allan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - A Radu Aricescu
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Moustafa Attar
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Christian Babbs
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | | | - David Beeson
- Neurosciences Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Celeste Bento
- Hematology Department, Centro Hospitalar e Universitário de Coimbra, Portugal
| | - Patricia Bignell
- Molecular Haematology Department, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Edward Blair
- Department of Clinical Genetics, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Veronica J Buckle
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Katherine Bull
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Centre for Cellular and Molecular Physiology, University of Oxford, Oxford, UK
| | - Ondrej Cais
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Holger Cario
- Department of Pediatrics and Adolescent Medicine, University Medical Center, Ulm, Germany
| | - Helen Chapel
- Primary Immunodeficiency Unit, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Richard R Copley
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Richard Cornall
- Centre for Cellular and Molecular Physiology, University of Oxford, Oxford, UK
| | - Jude Craft
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Karin Dahan
- Centre de Génétique Humaine, Institut de Génétique et de Pathologie, Gosselies, Belgium
- Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium
| | - Emma E Davenport
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Calliope Dendrou
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Olivier Devuyst
- Institute of Physiology, Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Aimée L Fenwick
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Jonathan Flint
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Lars Fugger
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Rodney D Gilbert
- University Hospital Southampton NHS Foundation Trust, University of Southampton, Southampton, UK
| | - Anne Goriely
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Angie Green
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Ingo H Greger
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | | | - Anja V Gruszczyk
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Robert Hastings
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Edouard Hatton
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Doug Higgs
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Adrian Hill
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- The Jenner Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Chris Holmes
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Malcolm Howard
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Linda Hughes
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Peter Humburg
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - David Johnson
- Craniofacial Unit, Department of Plastic and Reconstructive Surgery, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Fredrik Karpe
- Oxford Laboratory for Integrative Physiology, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | | | - Usha Kini
- Department of Clinical Genetics, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Julian C Knight
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Jonathan Krohn
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Sarah Lamble
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Craig Langman
- Kidney Diseases, Feinberg School of Medicine, Northwestern University and the Ann and Robert H Lurie Children's Hospital of Chicago, Chicago, Illinois, USA
| | - Lorne Lonie
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Joshua Luck
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Davis McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Simon J McGowan
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | | | - Kerry A Miller
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Lisa Murray
- Illumina Cambridge Limited, Saffron Walden, UK
| | - Andrea H Németh
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - M Andrew Nesbit
- Academic Endocrine Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | - David Nutt
- Centre for Neuropsychopharmacology, Division of Brain Sciences, Imperial College, London, UK
| | - Elizabeth Ormondroyd
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Annette Bang Oturai
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Alistair Pagnamenta
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Smita Y Patel
- Primary Immunodeficiency Unit, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Melanie Percy
- Department of Haematology, Belfast City Hospital, Belfast, UK
| | - Nayia Petousi
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Paolo Piazza
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Sian E Piret
- Academic Endocrine Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | | | - Niko Popitsch
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Fiona Powrie
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Chris Pugh
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Lynn Quek
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Peter A Robbins
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Kathryn Robson
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Alexandra Russo
- Department of Pediatrics, University Hospital, Mainz, Germany
| | - Natasha Sahgal
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Anna Schuh
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Department of Oncology, University of Oxford, Oxford, UK
| | - Earl Silverman
- Division of Rheumatology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Alison Simmons
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Per Soelberg Sørensen
- Danish Multiple Sclerosis Center, Department of Neurology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Elizabeth Sweeney
- Department of Clinical Genetics, Liverpool Women's NHS Foundation Trust, Liverpool, UK
| | - John Taylor
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Oxford NHS Regional Molecular Genetics Laboratory, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Rajesh V Thakker
- Academic Endocrine Unit, Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, UK
| | - Ian Tomlinson
- NIHR Comprehensive Biomedical Research Centre, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Amy Trebes
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Stephen Rf Twigg
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Holm H Uhlig
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Paresh Vyas
- MRC Molecular Haematology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Tim Vyse
- Division of Genetics, King's College London, Guy's Hospital, London, UK
| | - Steven A Wall
- Craniofacial Unit, Department of Plastic and Reconstructive Surgery, Oxford University Hospitals NHS Trust, Oxford, UK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Michael P Whyte
- Center for Metabolic Bone Disease and Molecular Research, Shriners Hospital for Children, St Louis, Missouri, USA
| | - Lorna Witty
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Ben Wright
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Chris Yau
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - David Buck
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | | | - John I Bell
- Office of the Regius Professor of Medicine, University of Oxford, Oxford, UK
| | - Andrew Om Wilkie
- Clinical Genetics Group, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | | | - Peter Donnelly
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Gilean McVean
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
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435
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Alsters SIM, Goldstone AP, Buxton JL, Zekavati A, Sosinsky A, Yiorkas AM, Holder S, Klaber RE, Bridges N, van Haelst MM, le Roux CW, Walley AJ, Walters RG, Mueller M, Blakemore AIF. Truncating Homozygous Mutation of Carboxypeptidase E (CPE) in a Morbidly Obese Female with Type 2 Diabetes Mellitus, Intellectual Disability and Hypogonadotrophic Hypogonadism. PLoS One 2015; 10:e0131417. [PMID: 26120850 PMCID: PMC4485893 DOI: 10.1371/journal.pone.0131417] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2015] [Accepted: 06/02/2015] [Indexed: 01/25/2023] Open
Abstract
Carboxypeptidase E is a peptide processing enzyme, involved in cleaving numerous peptide precursors, including neuropeptides and hormones involved in appetite control and glucose metabolism. Exome sequencing of a morbidly obese female from a consanguineous family revealed homozygosity for a truncating mutation of the CPE gene (c.76_98del; p.E26RfsX68). Analysis detected no CPE expression in whole blood-derived RNA from the proband, consistent with nonsense-mediated decay. The morbid obesity, intellectual disability, abnormal glucose homeostasis and hypogonadotrophic hypogonadism seen in this individual recapitulates phenotypes in the previously described fat/fat and Cpe knockout mouse models, evidencing the importance of this peptide/hormone-processing enzyme in regulating body weight, metabolism, and brain and reproductive function in humans.
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Affiliation(s)
- Suzanne I. M. Alsters
- Section of Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Imperial College London, London, United Kingdom
| | - Anthony P. Goldstone
- Imperial Centre for Endocrinology, Imperial College Healthcare NHS Trust, Hammersmith Hospital, London, United Kingdom
- Centre for Neuropsychopharmacology and Computational, Cognitive and Clinical Neuroimaging Laboratory, Division of Brain Sciences, Department of Medicine, Imperial College London, Hammersmith Hospital, London, United Kingdom
- Metabolic and Molecular Imaging Group, MRC Clinical Sciences Centre, Imperial College London, Hammersmith Hospital, London, United Kingdom
- * E-mail: (AG); (AB)
| | - Jessica L. Buxton
- Section of Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Imperial College London, London, United Kingdom
- Centre for Cardiovascular Genetics, UCL Institute of Cardiovascular Science, London, United Kingdom
| | - Anna Zekavati
- NIHR Imperial BRC Genomics Facility, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Alona Sosinsky
- NIHR Imperial BRC Genomics Facility, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Andrianos M. Yiorkas
- Section of Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Imperial College London, London, United Kingdom
| | - Susan Holder
- NW Thames Regional Genetics Service, Kennedy Galton Centre, North West London Hospitals NHS Trust, Northwick Park Hospital, Harrow, United Kingdom
| | - Robert E. Klaber
- Department of Paediatrics, Imperial College Healthcare NHS Trust, St Mary's Hospital, London, United Kingdom
| | - Nicola Bridges
- Department of Paediatric Endocrinology, Chelsea and Westminster Hospital, London, United Kingdom
| | - Mieke M. van Haelst
- Department of Medical Genetics, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Carel W. le Roux
- Section of Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Imperial College London, London, United Kingdom
- Diabetes Complications Research Centre, Conway Institute, School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | - Andrew J. Walley
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Robin G. Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Michael Mueller
- NIHR Imperial BRC Genomics Facility, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Alexandra I. F. Blakemore
- Section of Investigative Medicine, Division of Diabetes, Endocrinology, and Metabolism, Department of Medicine, Imperial College London, London, United Kingdom
- * E-mail: (AG); (AB)
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436
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Castro-Fernández C, Arias M, Blanco-Arias P, Santomé-Collazo L, Amigo J, Carracedo Á, Sobrido MJ. Targeted NGS meets expert clinical characterization: Efficient diagnosis of spastic paraplegia type 11. Appl Transl Genom 2015; 5:33-6. [PMID: 26937357 PMCID: PMC4745395 DOI: 10.1016/j.atg.2015.05.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Accepted: 05/30/2015] [Indexed: 12/12/2022]
Abstract
Next generation sequencing (NGS) is transforming the diagnostic approach for neurological disorders, since it allows simultaneous analysis of hundreds of genes, even based on just a broad, syndromic patient categorization. However, such an approach bears a high risk of incidental and uncertain genetic findings. We report a patient with spastic paraplegia whose comprehensive neurological and imaging examination raised a high clinical suspicion of SPG11. Thus, although our NGS pipeline for this group of disorders includes gene panel and exome sequencing, in this sample only the spatacsin gene region was captured and subsequently searched for mutations. Two probably pathogenic variants were quickly and clearly identified, confirming the diagnosis of SPG11. This case illustrates how combination of expert clinical characterization with highly oriented NGS protocols leads to a fast, cost-efficient diagnosis, minimizing the risk of findings with unclear significance.
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Affiliation(s)
- Cristina Castro-Fernández
- Instituto de Investigación Sanitaria de Santiago-IDIS, Spain; Grupo de Medicina Xenómica, CIBERER, Universidade de Santiago de Compostela, Spain
| | - Manuel Arias
- Instituto de Investigación Sanitaria de Santiago-IDIS, Spain; Servicio de Neurología, Complejo Hospitalario de Santiago de Compostela, Spain
| | - Patricia Blanco-Arias
- Instituto de Investigación Sanitaria de Santiago-IDIS, Spain; Grupo de Medicina Xenómica, CIBERER, Universidade de Santiago de Compostela, Spain; Fundación Pública Galega de Medicina Xenómica, Spain
| | - Luis Santomé-Collazo
- Instituto de Investigación Sanitaria de Santiago-IDIS, Spain; Fundación Pública Galega de Medicina Xenómica, Spain
| | - Jorge Amigo
- Instituto de Investigación Sanitaria de Santiago-IDIS, Spain; Grupo de Medicina Xenómica, CIBERER, Universidade de Santiago de Compostela, Spain; Fundación Pública Galega de Medicina Xenómica, Spain
| | - Ángel Carracedo
- Instituto de Investigación Sanitaria de Santiago-IDIS, Spain; Grupo de Medicina Xenómica, CIBERER, Universidade de Santiago de Compostela, Spain; Fundación Pública Galega de Medicina Xenómica, Spain; Center of Excellence in Genomic Medicine, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Maria-Jesús Sobrido
- Instituto de Investigación Sanitaria de Santiago-IDIS, Spain; Grupo de Medicina Xenómica, CIBERER, Universidade de Santiago de Compostela, Spain; Fundación Pública Galega de Medicina Xenómica, Spain
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437
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Mencacci N, Rubio-Agusti I, Zdebik A, Asmus F, Ludtmann M, Ryten M, Plagnol V, Hauser AK, Bandres-Ciga S, Bettencourt C, Forabosco P, Hughes D, Soutar M, Peall K, Morris H, Trabzuni D, Tekman M, Stanescu H, Kleta R, Carecchio M, Zorzi G, Nardocci N, Garavaglia B, Lohmann E, Weissbach A, Klein C, Hardy J, Pittman A, Foltynie T, Abramov A, Gasser T, Bhatia K, Wood N. A missense mutation in KCTD17 causes autosomal dominant myoclonus-dystonia. Am J Hum Genet 2015; 96:938-47. [PMID: 25983243 DOI: 10.1016/j.ajhg.2015.04.008] [Citation(s) in RCA: 93] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Accepted: 04/13/2015] [Indexed: 12/25/2022] Open
Abstract
Myoclonus-dystonia (M-D) is a rare movement disorder characterized by a combination of non-epileptic myoclonic jerks and dystonia. SGCE mutations represent a major cause for familial M-D being responsible for 30%-50% of cases. After excluding SGCE mutations, we identified through a combination of linkage analysis and whole-exome sequencing KCTD17 c.434 G>A p.(Arg145His) as the only segregating variant in a dominant British pedigree with seven subjects affected by M-D. A subsequent screening in a cohort of M-D cases without mutations in SGCE revealed the same KCTD17 variant in a German family. The clinical presentation of the KCTD17-mutated cases was distinct from the phenotype usually observed in M-D due to SGCE mutations. All cases initially presented with mild myoclonus affecting the upper limbs. Dystonia showed a progressive course, with increasing severity of symptoms and spreading from the cranio-cervical region to other sites. KCTD17 is abundantly expressed in all brain regions with the highest expression in the putamen. Weighted gene co-expression network analysis, based on mRNA expression profile of brain samples from neuropathologically healthy individuals, showed that KCTD17 is part of a putamen gene network, which is significantly enriched for dystonia genes. Functional annotation of the network showed an over-representation of genes involved in post-synaptic dopaminergic transmission. Functional studies in mutation bearing fibroblasts demonstrated abnormalities in endoplasmic reticulum-dependent calcium signaling. In conclusion, we demonstrate that the KCTD17 c.434 G>A p.(Arg145His) mutation causes autosomal dominant M-D. Further functional studies are warranted to further characterize the nature of KCTD17 contribution to the molecular pathogenesis of M-D.
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438
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Leveraging the power of high performance computing for next generation sequencing data analysis: tricks and twists from a high throughput exome workflow. PLoS One 2015; 10:e0126321. [PMID: 25942438 PMCID: PMC4420499 DOI: 10.1371/journal.pone.0126321] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2014] [Accepted: 03/31/2015] [Indexed: 12/26/2022] Open
Abstract
Next generation sequencing (NGS) has been a great success and is now a standard method of research in the life sciences. With this technology, dozens of whole genomes or hundreds of exomes can be sequenced in rather short time, producing huge amounts of data. Complex bioinformatics analyses are required to turn these data into scientific findings. In order to run these analyses fast, automated workflows implemented on high performance computers are state of the art. While providing sufficient compute power and storage to meet the NGS data challenge, high performance computing (HPC) systems require special care when utilized for high throughput processing. This is especially true if the HPC system is shared by different users. Here, stability, robustness and maintainability are as important for automated workflows as speed and throughput. To achieve all of these aims, dedicated solutions have to be developed. In this paper, we present the tricks and twists that we utilized in the implementation of our exome data processing workflow. It may serve as a guideline for other high throughput data analysis projects using a similar infrastructure. The code implementing our solutions is provided in the supporting information files.
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439
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An efficient screening method for simultaneous detection of recurrent copy number variants associated with psychiatric disorders. Clin Chim Acta 2015; 445:34-40. [DOI: 10.1016/j.cca.2015.03.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2014] [Accepted: 03/05/2015] [Indexed: 12/18/2022]
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440
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Sun Y, Ruivenkamp CAL, Hoffer MJV, Vrijenhoek T, Kriek M, van Asperen CJ, den Dunnen JT, Santen GWE. Next-generation diagnostics: gene panel, exome, or whole genome? Hum Mutat 2015; 36:648-55. [PMID: 25772376 DOI: 10.1002/humu.22783] [Citation(s) in RCA: 100] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2014] [Accepted: 02/27/2015] [Indexed: 01/19/2023]
Abstract
Although the benefits of next-generation sequencing (NGS) for the diagnosis of heterogeneous diseases such as intellectual disability (ID) are undisputed, there is little consensus on the relative merits of targeted enrichment, whole-exome sequencing (WES) or whole-genome sequencing (WGS). To answer this question, WES and WGS data from the same nine samples were compared, and WES was shown not to miss any variants identified by WGS in a gene panel including ∼500 genes linked to ID (500GP). Additionally, deeply sequenced WES data were shown to adequately cover ∼99% of the 500GP; thus, little additional benefit was to be expected from a targeted enrichment approach. To reduce costs, minimal sequencing criteria were determined by investigating the relation between sequenced reads and outcome parameters such as coverage and variant yield. Our analysis indicated that 60 million reads yielded a mean coverage of ∼60×: ∼97% of the 500GP sequences were sufficiently covered to exclude variants, whereas variant yield was ∼99.5% and false-positive and false-negative rates were controlled. Our findings indicate that WES is currently the optimal approach to ID diagnostics. This result depends on the capture kit and sequencing strategy used. The developed framework however is amenable to other sequencing approaches.
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Affiliation(s)
- Yu Sun
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Claudia A L Ruivenkamp
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Mariëtte J V Hoffer
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Terry Vrijenhoek
- Centre for Genome Diagnostics, Department of Medical Genetics, Universitair Medisch Centrum Utrecht, Utrecht, The Netherlands
| | - Marjolein Kriek
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Christi J van Asperen
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Johan T den Dunnen
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Gijs W E Santen
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
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441
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Wang W, Wang W, Sun W, Crowley JJ, Szatkiewicz JP. Allele-specific copy-number discovery from whole-genome and whole-exome sequencing. Nucleic Acids Res 2015; 43:e90. [PMID: 25883151 PMCID: PMC4538801 DOI: 10.1093/nar/gkv319] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2014] [Accepted: 03/27/2015] [Indexed: 11/14/2022] Open
Abstract
Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detection and produce allele-specific copy number (ASCN) calls. Although statistical methods have been developed to detect CNVs using whole-genome sequence (WGS) and/or whole-exome sequence (WES) data, information from allele-specific read counts has not yet been adequately exploited. In this paper, we develop an integrated method, called AS-GENSENG, which incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data. To evaluate the performance of AS-GENSENG, we conducted extensive simulations, generated empirical data using existing WGS and WES data sets and validated predicted CNVs using an independent methodology. We conclude that AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data. Our novel, user-friendly and computationally efficient method and a complete analytic protocol is freely available at https://sourceforge.net/projects/asgenseng/.
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Affiliation(s)
- WeiBo Wang
- Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599-3175, USA
| | - Wei Wang
- Department of Computer Science, University of California, Los Angeles, CA 90095, USA
| | - Wei Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, NC 27599-7400, USA
| | - James J Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, NC 27599-7264, USA
| | - Jin P Szatkiewicz
- Department of Genetics, University of North Carolina at Chapel Hill, NC 27599-7264, USA
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442
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Scheidecker S, Etard C, Haren L, Stoetzel C, Hull S, Arno G, Plagnol V, Drunat S, Passemard S, Toutain A, Obringer C, Koob M, Geoffroy V, Marion V, Strähle U, Ostergaard P, Verloes A, Merdes A, Moore A, Dollfus H. Mutations in TUBGCP4 alter microtubule organization via the γ-tubulin ring complex in autosomal-recessive microcephaly with chorioretinopathy. Am J Hum Genet 2015; 96:666-74. [PMID: 25817018 DOI: 10.1016/j.ajhg.2015.02.011] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2014] [Accepted: 02/19/2015] [Indexed: 12/27/2022] Open
Abstract
We have identified TUBGCP4 variants in individuals with autosomal-recessive microcephaly and chorioretinopathy. Whole-exome sequencing performed on one family with two affected siblings and independently on another family with one affected child revealed compound-heterozygous mutations in TUBGCP4. Subsequent Sanger sequencing was performed on a panel of individuals from 12 French families affected by microcephaly and ophthalmic manifestations, and one other individual was identified with compound-heterozygous mutations in TUBGCP4. One synonymous variant was common to all three families and was shown to induce exon skipping; the other mutations were frameshift mutations and a deletion. TUBGCP4 encodes γ-tubulin complex protein 4, a component belonging to the γ-tubulin ring complex (γ-TuRC) and known to regulate the nucleation and organization of microtubules. Functional analysis of individual fibroblasts disclosed reduced levels of the γ-TuRC, altered nucleation and organization of microtubules, abnormal nuclear shape, and aneuploidy. Moreover, zebrafish treated with morpholinos against tubgcp4 were found to have reduced head volume and eye developmental anomalies with chorioretinal dysplasia. In summary, the identification of TUBGCP4 mutations in individuals with microcephaly and a spectrum of anomalies in eye development, particularly photoreceptor anomalies, provides evidence of an important role for the γ-TuRC in brain and eye development.
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443
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McInerney-Leo A, Harris J, Leo P, Marshall M, Gardiner B, Kinning E, Leong H, McKenzie F, Ong W, Vodopiutz J, Wicking C, Brown M, Zankl A, Duncan E. Whole exome sequencing is an efficient, sensitive and specific method for determining the genetic cause of short-rib thoracic dystrophies. Clin Genet 2015; 88:550-7. [DOI: 10.1111/cge.12550] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2014] [Revised: 12/02/2014] [Accepted: 12/04/2014] [Indexed: 01/14/2023]
Affiliation(s)
- A.M. McInerney-Leo
- The University of Queensland Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital; Woolloongabba QLD 4102 Australia
| | - J.E. Harris
- The University of Queensland Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital; Woolloongabba QLD 4102 Australia
| | - P.J. Leo
- The University of Queensland Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital; Woolloongabba QLD 4102 Australia
| | - M.S. Marshall
- The University of Queensland Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital; Woolloongabba QLD 4102 Australia
| | - B. Gardiner
- The University of Queensland Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital; Woolloongabba QLD 4102 Australia
| | - E. Kinning
- West of Scotland Genetics Service; Southern General Hospital; Glasgow G51 4TF UK
| | - H.Y. Leong
- Genetics Department; Hospital Kuala Lumpur; Kuala Lumpur Malaysia
| | - F. McKenzie
- Genetic Services of Western Australia; Subiaco WA 6008 Australia
- School of Paediatrics and Child Health; The University of Western Australia; Crawley WA 6009 Australia
| | - W.P. Ong
- Genetics Department; Hospital Kuala Lumpur; Kuala Lumpur Malaysia
| | - J. Vodopiutz
- Department of Pediatrics and Adolescent Medicine Medical University of Vienna; A-1090 Vienna Waehringerguertel 18-20 Vienna Austria
| | - C. Wicking
- Institute for Molecular Bioscience; The University of Queensland; St Lucia QLD 4072 Australia
| | - M.A. Brown
- The University of Queensland Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital; Woolloongabba QLD 4102 Australia
| | - A. Zankl
- Discipline of Genetic Medicine; The University of Sydney; Sydney Australia
- Academic Department of Medical Genetics; Sydney Children's Hospital Network (Westmead); Sydney Australia
| | - E.L. Duncan
- The University of Queensland Diamantina Institute, Translational Research Institute, Princess Alexandra Hospital; Woolloongabba QLD 4102 Australia
- Department of Endocrinology, James Mayne Building; Royal Brisbane and Women's Hospital; Butterfield Road Herston QLD 4029 Australia
- The University of Queensland, University of Queensland Centre for Clinical Research; Herston QLD 4029 Australia
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444
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Cost effective assay choice for rare disease study designs. Orphanet J Rare Dis 2015; 10:10. [PMID: 25648394 PMCID: PMC4334400 DOI: 10.1186/s13023-015-0226-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2014] [Accepted: 01/13/2015] [Indexed: 11/10/2022] Open
Abstract
High throughput assays tend to be expensive per subject. Often studies are limited not so much by the number of subjects available as by assay costs, making assay choice a critical issue. We have developed a framework for assay choice that maximises the number of true disease causing mechanisms ‘seen’, given limited resources. Although straightforward, some of the ramifications of our methodology run counter to received wisdom on study design. We illustrate our methodology with examples, and have built a website allowing calculation of quantities of interest to those designing rare disease studies.
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445
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Would raising the total cholesterol diagnostic cut-off from 7.5 mmol/L to 9.3 mmol/L improve detection rate of patients with monogenic familial hypercholesterolaemia? Atherosclerosis 2015; 239:295-8. [PMID: 25682026 PMCID: PMC4373788 DOI: 10.1016/j.atherosclerosis.2015.01.028] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Revised: 01/14/2015] [Accepted: 01/15/2015] [Indexed: 11/23/2022]
Abstract
A previous report suggested that 88% of individuals in the general population with total cholesterol (TC) > 9.3 mmol/L have familial hypercholesterolaemia (FH). We tested this hypothesis in a cohort of 4896 UK civil servants, mean (SD) age 44 (±6) years, using next generation sequencing to achieve a comprehensive genetic diagnosis. 25 (0.5%) participants (mean age 49.2 years) had baseline TC > 9.3 mmol/L, and overall we found an FH-causing mutation in the LDLR gene in seven (28%) subjects. The detection rate increased to 39% by excluding eight participants with triglyceride levels over 2.3 mmol/L, and reached 75% in those with TC > 10.4 mmol/L. By extrapolation, the detection rate would be ∼25% by including all participants with TC > 8.6 mmol/L (2.5 standard deviations from the mean). Based on the 1/500 FH frequency, 30% of all FH-cases in this cohort would be missed using the 9.3 mmol/L cut-off. Given that an overall detection rate of 25% is considered economically acceptable, these data suggest that a diagnostic TC cut-off of 8.6 mmol/L, rather than 9.3 mmol/L would be clinically useful for FH in the general population. 28% of sequenced UK individuals with total cholesterol >9.3 mmol/L were found to have an FH mutation using NGS. Detection rate was higher (39%) in individuals with triglycerides lower than 2.3 mmol/L. By extrapolation, a 8.6 mmol/L (2.5 SD from the mean) cholesterol cut-off may be most economically sustainable.
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446
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Jiang Y, Oldridge DA, Diskin SJ, Zhang NR. CODEX: a normalization and copy number variation detection method for whole exome sequencing. Nucleic Acids Res 2015; 43:e39. [PMID: 25618849 PMCID: PMC4381046 DOI: 10.1093/nar/gku1363] [Citation(s) in RCA: 100] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2014] [Accepted: 12/19/2014] [Indexed: 01/24/2023] Open
Abstract
High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures.
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Affiliation(s)
- Yuchao Jiang
- Genomics and Computational Biology Graduate Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Derek A Oldridge
- Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Division of Oncology and Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sharon J Diskin
- Division of Oncology and Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nancy R Zhang
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
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447
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Hemophagocytic lymphohistiocytosis in 2 patients with underlying IFN-γ receptor deficiency. J Allergy Clin Immunol 2015; 135:1638-41. [PMID: 25592983 DOI: 10.1016/j.jaci.2014.11.030] [Citation(s) in RCA: 64] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2014] [Revised: 11/18/2014] [Accepted: 11/20/2014] [Indexed: 12/14/2022]
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448
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Hwang MY, Moon S, Heo L, Kim YJ, Oh JH, Kim YJ, Kim YK, Lee J, Han BG, Kim BJ. Combinatorial approach to estimate copy number genotype using whole-exome sequencing data. Genomics 2014; 105:145-9. [PMID: 25535679 DOI: 10.1016/j.ygeno.2014.12.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2014] [Revised: 12/08/2014] [Accepted: 12/16/2014] [Indexed: 11/29/2022]
Abstract
Copy number variations (CNVs) are known risk factors in complex diseases. Array-based approaches have been widely used to detect CNVs, but limitations of array-based CNV detection methods, such as noisy signal and low resolution, have hindered detection of small CNVs. Recently, the development of next-generation sequencing techniques has increased rapidly owing to declines in cost. Particularly, whole-exome sequencing has proved useful for finding causal genes and variants in complex diseases. Because gene copy number may affect expression, CNV genotyping can be very valuable in disease association studies. However, almost all current CNV detection tools consider only two types of CNV genotypes. In this study, we propose a CNV genotype estimation approach using a combination of existing methods. Our approach was comprehensively compared with the customized Agilent array-comparative genomic hybridization. We found that our genotyping approach proved to be accurate, and reproducible, suggesting that it can complement existing CNV genotyping methods.
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Affiliation(s)
- Mi Yeong Hwang
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea
| | - Sanghoon Moon
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea
| | - Lyong Heo
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea
| | - Young Jin Kim
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea
| | - Ji Hee Oh
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea
| | - Yeon-Jung Kim
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea
| | - Yun Kyoung Kim
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea
| | - Juyoung Lee
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea
| | - Bok-Ghee Han
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea
| | - Bong-Jo Kim
- Division of Structural and Functional Genomics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 361-951, Republic of Korea.
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449
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Figueiredo T, Melo US, Pessoa ALS, Nobrega PR, Kitajima JP, Correa I, Zatz M, Kok F, Santos S. Homozygous missense mutation in MED25 segregates with syndromic intellectual disability in a large consanguineous family. J Med Genet 2014; 52:123-7. [PMID: 25527630 DOI: 10.1136/jmedgenet-2014-102793] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
BACKGROUND Intellectual disability (ID) is a highly heterogeneous condition affecting 2% of the population worldwide. In a field study conducted in a highly inbred area of Northeastern Brazil, we investigated a consanguineous family in which seven adults presented syndromic ID. METHODS Genome-Wide Human SNP Array 6.0 (Affymetrix) microarray was used to determine regions of homozygosity-by-descent and whole exome sequencing (WES) was performed in one affected individual using Extended Nextera Rapid-Capture Exome and Illumina HiSeq2500. RESULTS We found two regions with an logarithm of the odds (LOD) score of 3.234: a region spanning 4.0 Mb in 19q13.32-q13.33 and a pericentromeric 20 Mb area in chromosome 2 (2p12-q11.2). WES disclosed in the critical region of chromosome 19 a homozygous variant (c.418C>T, p.Arg140Trp) in Mediator complex subunit 25 (MED25), predicted as deleterious by PolyPhen-2, Provean, Mutation Taster and Sorting Intolerant From Tolerant (SIFT). MED25 is a component of the Mediator complex, involved in regulation of transcription of nearly all RNA polymerase II-dependent genes. Deleterious mutations in MED12, MED17 and MED23 have already been associated with ID. CONCLUSIONS These findings demonstrate that the combination of field investigation of families in highly inbred regions with modern technologies is an effective way for identifying new genes associated with ID.
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Affiliation(s)
- Thalita Figueiredo
- Northeast Biotechnology Network (RENORBIO), Federal University of Paraiba (UFPB), Joao Pessoa, PB, Brazil Department of Biology, Paraiba State University (UEPB), Campina Grande, PB, Brazil
| | - Uirá Souto Melo
- Human Genome and Stem Cell Research Center, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP, Brazil
| | - André Luiz Santos Pessoa
- Department of Neurology, School of Medicine, University of Sao Paulo (USP), Sao Paulo, SP, Brazil Fortaleza University (UNIFOR), Fortaleza, CE, Brazil
| | - Paulo Ribeiro Nobrega
- Department of Neurology, School of Medicine, University of Sao Paulo (USP), Sao Paulo, SP, Brazil
| | | | - Igor Correa
- Mendelics Genomic Analysis, Sao Paulo, SP, Brazil
| | - Mayana Zatz
- Human Genome and Stem Cell Research Center, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP, Brazil
| | - Fernando Kok
- Human Genome and Stem Cell Research Center, Biosciences Institute, University of Sao Paulo (USP), Sao Paulo, SP, Brazil Department of Neurology, School of Medicine, University of Sao Paulo (USP), Sao Paulo, SP, Brazil
| | - Silvana Santos
- Northeast Biotechnology Network (RENORBIO), Federal University of Paraiba (UFPB), Joao Pessoa, PB, Brazil Department of Biology, Paraiba State University (UEPB), Campina Grande, PB, Brazil
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450
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Yang JF, Ding XF, Chen L, Mat WK, Xu MZ, Chen JF, Wang JM, Xu L, Poon WS, Kwong A, Leung GKK, Tan TC, Yu CH, Ke YB, Xu XY, Ke XY, Ma RC, Chan JC, Wan WQ, Zhang LW, Kumar Y, Tsang SY, Li S, Wang HY, Xue H. Copy number variation analysis based on AluScan sequences. J Clin Bioinforma 2014; 4:15. [PMID: 25558350 PMCID: PMC4273479 DOI: 10.1186/s13336-014-0015-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2014] [Accepted: 11/12/2014] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND AluScan combines inter-Alu PCR using multiple Alu-based primers with opposite orientations and next-generation sequencing to capture a huge number of Alu-proximal genomic sequences for investigation. Its requirement of only sub-microgram quantities of DNA facilitates the examination of large numbers of samples. However, the special features of AluScan data rendered difficult the calling of copy number variation (CNV) directly using the calling algorithms designed for whole genome sequencing (WGS) or exome sequencing. RESULTS In this study, an AluScanCNV package has been assembled for efficient CNV calling from AluScan sequencing data employing a Geary-Hinkley transformation (GHT) of read-depth ratios between either paired test-control samples, or between test samples and a reference template constructed from reference samples, to call the localized CNVs, followed by use of a GISTIC-like algorithm to identify recurrent CNVs and circular binary segmentation (CBS) to reveal large extended CNVs. To evaluate the utility of CNVs called from AluScan data, the AluScans from 23 non-cancer and 38 cancer genomes were analyzed in this study. The glioma samples analyzed yielded the familiar extended copy-number losses on chromosomes 1p and 9. Also, the recurrent somatic CNVs identified from liver cancer samples were similar to those reported for liver cancer WGS with respect to a striking enrichment of copy-number gains in chromosomes 1q and 8q. When localized or recurrent CNV-features capable of distinguishing between liver and non-liver cancer samples were selected by correlation-based machine learning, a highly accurate separation of the liver and non-liver cancer classes was attained. CONCLUSIONS The results obtained from non-cancer and cancerous tissues indicated that the AluScanCNV package can be employed to call localized, recurrent and extended CNVs from AluScan sequences. Moreover, both the localized and recurrent CNVs identified by this method could be subjected to machine-learning selection to yield distinguishing CNV-features that were capable of separating between liver cancers and other types of cancers. Since the method is applicable to any human DNA sample with or without the availability of a paired control, it can also be employed to analyze the constitutional CNVs of individuals.
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Affiliation(s)
- Jian-Feng Yang
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Xiao-Fan Ding
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Lei Chen
- National Center for Liver Cancer Research and Eastern Hepatobiliary Surgery Hospital, 225 Changhai Road, Shanghai, 200438 China
| | - Wai-Kin Mat
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Michelle Zhi Xu
- Department of Oncology, Nanjing First Hospital, No. 68 Changle Road, Nanjing, 210006 China
| | - Jin-Fei Chen
- Department of Oncology, Nanjing First Hospital, No. 68 Changle Road, Nanjing, 210006 China
| | - Jian-Min Wang
- Department of Hematology, Changhai Hospital, Second Military Medical University, 174 Changhai Road, Shanghai, 200433 China
| | - Lin Xu
- Department of Thoracic Surgery, Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Nanjing Medical University Affiliated Cancer Hospital, Cancer Institute of Jiangsu Province, Baiziting 42, Nanjing, 210009 China
| | - Wai-Sang Poon
- Division of Neurosurgery, Department of Surgery, Prince of Wales Hospital, Chinese University of Hong Kong, 30-32 Ngan Shing Street, Sha Tin, Hong Kong, China
| | - Ava Kwong
- Division of Neurosurgery, Department of Surgery, Li Ka Shing Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China
| | - Gilberto Ka-Kit Leung
- Division of Neurosurgery, Department of Surgery, Li Ka Shing Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, 102 Pokfulam Road, Hong Kong, China
| | - Tze-Ching Tan
- Department of Neurosurgery, Queen Elizabeth Hospital, 30 Gascoigne Road, Kowloon, Hong Kong, China
| | - Chi-Hung Yu
- Department of Neurosurgery, Queen Elizabeth Hospital, 30 Gascoigne Road, Kowloon, Hong Kong, China
| | - Yue-Bin Ke
- Shenzhen Center for Disease Control and Prevention, No 8 Longyuan Road, Nanshan district, Shenzhen City, 518055 China
| | - Xin-Yun Xu
- Shenzhen Center for Disease Control and Prevention, No 8 Longyuan Road, Nanshan district, Shenzhen City, 518055 China
| | - Xiao-Yan Ke
- Nanjing Brain Hospital and Nanjing Institute of Neuropsychiatry, Nanjing Medical University, Nanjing, 210029 China
| | - Ronald Cw Ma
- Department of Medicine and Therapeutics, 9th floor, Clinical Sciences Building, The Prince of Wales Hospital, Shatin, Hong Kong
| | - Juliana Cn Chan
- Department of Medicine and Therapeutics, 9th floor, Clinical Sciences Building, The Prince of Wales Hospital, Shatin, Hong Kong
| | - Wei-Qing Wan
- Department of Neurosurgery, Beijing Tiantan Hospital, 6 Tiantan Xili, Dongcheng District, Capital Medical University, Beijing, 100050 China
| | - Li-Wei Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, 6 Tiantan Xili, Dongcheng District, Capital Medical University, Beijing, 100050 China
| | - Yogesh Kumar
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Shui-Ying Tsang
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Shao Li
- MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, Beijing, 100084 China
| | - Hong-Yang Wang
- National Center for Liver Cancer Research and Eastern Hepatobiliary Surgery Hospital, 225 Changhai Road, Shanghai, 200438 China.,International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, 225 Changhai Road, Shanghai, 200438 China
| | - Hong Xue
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
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