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Bianchi A, Zelli V, D’Angelo A, Di Matteo A, Scoccia G, Cannita K, Dimas A, Glentis S, Zazzeroni F, Alesse E, Di Marco A, Tessitore A. A method to comprehensively identify germline SNVs, INDELs and CNVs from whole exome sequencing data of BRCA1/2 negative breast cancer patients. NAR Genom Bioinform 2024; 6:lqae033. [PMID: 38633426 PMCID: PMC11023157 DOI: 10.1093/nargab/lqae033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/22/2024] [Accepted: 04/03/2024] [Indexed: 04/19/2024] Open
Abstract
In the rapidly evolving field of genomics, understanding the genetic basis of complex diseases like breast cancer, particularly its familial/hereditary forms, is crucial. Current methods often examine genomic variants-such as Single Nucleotide Variants (SNVs), insertions/deletions (Indels), and Copy Number Variations (CNVs)-separately, lacking an integrated approach. Here, we introduced a robust, flexible methodology for a comprehensive variants' analysis using Whole Exome Sequencing (WES) data. Our approach uniquely combines meticulous validation with an effective variant filtering strategy. By reanalyzing two germline WES datasets from BRCA1/2 negative breast cancer patients, we demonstrated our tool's efficiency and adaptability, uncovering both known and novel variants. This contributed new insights for potential diagnostic, preventive, and therapeutic strategies. Our method stands out for its comprehensive inclusion of key genomic variants in a unified analysis, and its practical resolution of technical challenges, offering a pioneering solution in genomic research. This tool presents a breakthrough in providing detailed insights into the genetic alterations in genomes, with significant implications for understanding and managing hereditary breast cancer.
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Affiliation(s)
- Andrea Bianchi
- Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, L’Aquila 67100, Italy
| | - Veronica Zelli
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila 67100, Italy
| | - Andrea D’Angelo
- Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, L’Aquila 67100, Italy
| | - Alessandro Di Matteo
- Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, L’Aquila 67100, Italy
| | - Giulia Scoccia
- Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, L’Aquila 67100, Italy
| | - Katia Cannita
- Oncology Division, Mazzini Hospital, ASL Teramo, Teramo 64100, Italy
| | - Antigone S Dimas
- Institute for Bioinnovation, Biomedical Sciences Research Center, Alexander Fleming, Vari 16672, Greece
| | - Stavros Glentis
- Institute for Bioinnovation, Biomedical Sciences Research Center, Alexander Fleming, Vari 16672, Greece
- Pediatric Hematology/Oncology Unit (POHemU), First Department of Pediatrics, University of Athens, Aghia Sophia Children’s Hospital, Athens 11527, Grece
| | - Francesca Zazzeroni
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila 67100, Italy
| | - Edoardo Alesse
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila 67100, Italy
| | - Antinisca Di Marco
- Department of Information Engineering, Computer Science and Mathematics, University of L’Aquila, L’Aquila 67100, Italy
| | - Alessandra Tessitore
- Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila 67100, Italy
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2
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Holesova Z, Pös O, Gazdarica J, Kucharik M, Budis J, Hyblova M, Minarik G, Szemes T. Understanding genetic variability: exploring large-scale copy number variants through non-invasive prenatal testing in European populations. BMC Genomics 2024; 25:366. [PMID: 38622538 PMCID: PMC11017555 DOI: 10.1186/s12864-024-10267-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 03/28/2024] [Indexed: 04/17/2024] Open
Abstract
Large-scale copy number variants (CNVs) are structural alterations in the genome that involve the duplication or deletion of DNA segments, contributing to genetic diversity and playing a crucial role in the evolution and development of various diseases and disorders, as they can lead to the dosage imbalance of one or more genes. Massively parallel sequencing (MPS) has revolutionized the field of genetic analysis and contributed significantly to routine clinical diagnosis and screening. It offers a precise method for detecting CNVs with exceptional accuracy. In this context, a non-invasive prenatal test (NIPT) based on the sequencing of cell-free DNA (cfDNA) from pregnant women's plasma using a low-coverage whole genome MPS (WGS) approach represents a valuable source for population studies. Here, we analyzed genomic data of 12,732 pregnant women from the Slovak (9,230), Czech (1,583), and Hungarian (1,919) populations. We identified 5,062 CNVs ranging from 200 kbp and described their basic characteristics and differences between the subject populations. Our results suggest that re-analysis of sequencing data from routine WGS assays has the potential to obtain large-scale CNV population frequencies, which are not well known and may provide valuable information to support the classification and interpretation of this type of genetic variation. Furthermore, this could contribute to expanding knowledge about the central European genome without investing in additional laboratory work, as NIPTs are a relatively widely used screening method.
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Affiliation(s)
| | - Ondrej Pös
- Geneton Ltd, Bratislava, Slovakia
- Comenius University Science Park, Bratislava, Slovakia
| | - Juraj Gazdarica
- Geneton Ltd, Bratislava, Slovakia
- Slovak Centre of Scientific and Technical Information, Bratislava, Slovakia
- Department of Molecular Biology, Faculty of Natural Sciences, Comenius University, Bratislava, Slovakia
| | - Marcel Kucharik
- Geneton Ltd, Bratislava, Slovakia
- Comenius University Science Park, Bratislava, Slovakia
| | - Jaroslav Budis
- Geneton Ltd, Bratislava, Slovakia
- Comenius University Science Park, Bratislava, Slovakia
- Slovak Centre of Scientific and Technical Information, Bratislava, Slovakia
| | - Michaela Hyblova
- TRISOMYtest Ltd, Nitra, Slovakia
- Medirex Group Academy, Nitra, Slovakia
| | - Gabriel Minarik
- TRISOMYtest Ltd, Nitra, Slovakia
- Medirex Group Academy, Nitra, Slovakia
| | - Tomas Szemes
- Geneton Ltd, Bratislava, Slovakia
- Comenius University Science Park, Bratislava, Slovakia
- Department of Molecular Biology, Faculty of Natural Sciences, Comenius University, Bratislava, Slovakia
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3
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CNVs Associated with Different Clinical Phenotypes of Psoriasis and Anti-TNF-Induced Palmoplantar Pustulosis. J Pers Med 2022; 12:jpm12091452. [PMID: 36143237 PMCID: PMC9506507 DOI: 10.3390/jpm12091452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 09/01/2022] [Accepted: 09/02/2022] [Indexed: 11/16/2022] Open
Abstract
Background: Psoriasis can present different phenotypes and could affect diverse body areas. In contrast to the high effectiveness of biological drugs in the treatment of trunk and extremities plaque psoriasis, in palmoplantar phenotypes and in plaque scalp psoriasis, these same drugs usually have reduced efficacy. Anti-TNF drugs could induce the appearance of palmoplantar pustulosis (PPP) in patients with other inflammatory diseases. The objective of this study is to identify if there are DNA Copy Number Variations (CNVs) associated with these different clinical phenotypes, which could justify the differences found in clinical practice. Moreover, we intend to elucidate if anti-TNF-induced PPP has a similar genetic background to idiopathic PPP. Methods: Skin samples were collected from 39 patients with different patterns of psoriasis and six patients with anti-TNF-induced PPP. The CNVs were obtained from methylation array data (Illumina Infinium Human Methylation) using the conumee R package. Results: No significant CNVs were found between the different phenotypes and the locations of psoriasis compared. Nevertheless, we found two significant bins harboring five different genes associated with anti-TNF-induced PPP in patients with a different background other than psoriasis. Conclusions: Our results may help to predict which patients could develop anti-TNF-induced PPP.
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4
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Auwerx C, Lepamets M, Sadler MC, Patxot M, Stojanov M, Baud D, Mägi R, Porcu E, Reymond A, Kutalik Z, Metspalu A, Milani L, Mägi R, Nelis M. The individual and global impact of copy-number variants on complex human traits. Am J Hum Genet 2022; 109:647-668. [PMID: 35240056 PMCID: PMC9069145 DOI: 10.1016/j.ajhg.2022.02.010] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 02/09/2022] [Indexed: 12/25/2022] Open
Abstract
The impact of copy-number variations (CNVs) on complex human traits remains understudied. We called CNVs in 331,522 UK Biobank participants and performed genome-wide association studies (GWASs) between the copy number of CNV-proxy probes and 57 continuous traits, revealing 131 signals spanning 47 phenotypes. Our analysis recapitulated well-known associations (e.g., 1q21 and height), revealed the pleiotropy of recurrent CNVs (e.g., 26 and 16 traits for 16p11.2-BP4-BP5 and 22q11.21, respectively), and suggested gene functionalities (e.g., MARF1 in female reproduction). Forty-eight CNV signals (38%) overlapped with single-nucleotide polymorphism (SNP)-GWASs signals for the same trait. For instance, deletion of PDZK1, which encodes a urate transporter scaffold protein, decreased serum urate levels, while deletion of RHD, which encodes the Rhesus blood group D antigen, associated with hematological traits. Other signals overlapped Mendelian disorder regions, suggesting variable expressivity and broad impact of these loci, as illustrated by signals mapping to Rotor syndrome (SLCO1B1/3), renal cysts and diabetes syndrome (HNF1B), or Charcot-Marie-Tooth (PMP22) loci. Total CNV burden negatively impacted 35 traits, leading to increased adiposity, liver/kidney damage, and decreased intelligence and physical capacity. Thirty traits remained burden associated after correcting for CNV-GWAS signals, pointing to a polygenic CNV architecture. The burden negatively correlated with socio-economic indicators, parental lifespan, and age (survivorship proxy), suggesting a contribution to decreased longevity. Together, our results showcase how studying CNVs can expand biological insights, emphasizing the critical role of this mutational class in shaping human traits and arguing in favor of a continuum between Mendelian and complex diseases.
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Affiliation(s)
- Chiara Auwerx
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland; Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; University Center for Primary Care and Public Health, Lausanne 1010, Switzerland
| | - Maarja Lepamets
- Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia; Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Marie C Sadler
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; University Center for Primary Care and Public Health, Lausanne 1010, Switzerland
| | - Marion Patxot
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland
| | - Miloš Stojanov
- Materno-fetal and Obstetrics Research Unit, Department Woman-Mother-Child, CHUV, Lausanne 1011, Switzerland
| | - David Baud
- Materno-fetal and Obstetrics Research Unit, Department Woman-Mother-Child, CHUV, Lausanne 1011, Switzerland
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
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- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
| | - Eleonora Porcu
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; University Center for Primary Care and Public Health, Lausanne 1010, Switzerland
| | - Alexandre Reymond
- Center for Integrative Genomics, University of Lausanne, Lausanne 1015, Switzerland.
| | - Zoltán Kutalik
- Department of Computational Biology, University of Lausanne, Lausanne 1015, Switzerland; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland; University Center for Primary Care and Public Health, Lausanne 1010, Switzerland.
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5
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Giles Doran C, Pennington SR. Copy number alteration signatures as biomarkers in cancer: a review. Biomark Med 2022; 16:371-386. [PMID: 35195030 DOI: 10.2217/bmm-2021-0476] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
Within certain cancers, extensive copy number alterations (CNAs) contribute to a complex and heterogenic genomic profile. This makes it difficult to understand and unravel the distinct molecular dynamics shaping the disease while preventing clinically effective patient stratification. CNA signature analysis represents a novel genomic stratification tool for probing this complexity, offering an intricate framework for deriving CNA patterns at the molecular level. This allows the underlying genomic mechanisms of specific cancers to be revealed, leading to the potential identification of therapeutic targets and prognostic associations. This review outlines the molecular and methodological basis of CNA signatures and focuses on recent advances highlighting their clinical utility, limitations and prospective future as novel diagnostic and prognostic cancer biomarkers.
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Affiliation(s)
- Conor Giles Doran
- UCD Conway Institute, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland
| | - Stephen R Pennington
- UCD Conway Institute, School of Medicine, University College Dublin, Belfield, Dublin 4, Ireland
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6
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Comprehensive characterization of copy number variation (CNV) called from array, long- and short-read data. BMC Genomics 2021; 22:826. [PMID: 34789167 PMCID: PMC8596897 DOI: 10.1186/s12864-021-08082-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 10/13/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND SNP arrays, short- and long-read genome sequencing are genome-wide high-throughput technologies that may be used to assay copy number variants (CNVs) in a personal genome. Each of these technologies comes with its own limitations and biases, many of which are well-known, but not all of them are thoroughly quantified. RESULTS We assembled an ensemble of public datasets of published CNV calls and raw data for the well-studied Genome in a Bottle individual NA12878. This assembly represents a variety of methods and pipelines used for CNV calling from array, short- and long-read technologies. We then performed cross-technology comparisons regarding their ability to call CNVs. Different from other studies, we refrained from using the golden standard. Instead, we attempted to validate the CNV calls by the raw data of each technology. CONCLUSIONS Our study confirms that long-read platforms enable recalling CNVs in genomic regions inaccessible to arrays or short reads. We also found that the reproducibility of a CNV by different pipelines within each technology is strongly linked to other CNV evidence measures. Importantly, the three technologies show distinct public database frequency profiles, which differ depending on what technology the database was built on.
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Ye L, Wang L, Yang J, Hu P, Zhang C, Tong S, Liu Z, Tian D. Identification of Tumor Antigens and Immune Landscape in Glioblastoma for mRNA Vaccine Development. Front Genet 2021; 12:701065. [PMID: 34527020 PMCID: PMC8435740 DOI: 10.3389/fgene.2021.701065] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 07/29/2021] [Indexed: 12/21/2022] Open
Abstract
Background: Clinical benefits from standard therapies against glioblastoma (GBM) are limited in part due to the intrinsic radio- and chemo-resistance. As an essential part of tumor immunotherapy for adjunct, therapeutic tumor vaccines have been effective against multiple solid cancers, while their efficacy against GBM remains undefined. Therefore, this study aims to find the possible tumor antigens of GBM and identify the suitable population for cancer vaccination through immunophenotyping. Method: The genomic and responding clinical data of 169 GBM samples and five normal brain samples were obtained from The Cancer Genome Atlas (TCGA). The mRNA_seq data of 940 normal brain tissue were downloaded from Genotype-Tissue Expression (GTEx). Potential GBM mRNA antigens were screened out by differential expression, copy number variant (CNV), and mutation analysis. K-M survival and Cox analysis were carried out to investigate the prognostic association of potential tumor antigens. Tumor Immune Estimation Resource (TIMER) was used to explore the association between the antigens and tumor immune infiltrating cells (TIICs). Immunophenotyping of 169 samples was performed through consensus clustering based on the abundance of 22 kinds of immune cells. The characteristics of the tumor immune microenvironment (TIME) in each cluster were explored through single-sample gene set enrichment analysis based on 29 kinds of immune-related hallmarks and pathways. Weighted gene co-expression network analysis (WGCNA) was performed to cluster the genes related to immune subtypes. Finally, pathway enrichment analyses were performed to annotate the potential function of modules screened through WGCNA. Results: Two potential tumor antigens selected were significantly positively associated with the antigen-presenting immune cells (APCs) in GBM. Furthermore, the expression of antigens was verified at the protein level by Immunohistochemistry. Two robust immune subtypes, immune subtype 1 (IS1) and immune subtype 2 (IS2), representing immune status "immune inhibition" and "immune inflamed", respectively, had distinct clinical outcomes in GBM. Conclusion: ARPC1B and HK3 were potential mRNA antigens for developing GBM mRNA vaccination, and the patients in IS2 were considered the most suitable population for vaccination in GBM.
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Affiliation(s)
- Liguo Ye
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Long Wang
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ji'an Yang
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Ping Hu
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Chunyu Zhang
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Shi'ao Tong
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhennan Liu
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
| | - Daofeng Tian
- Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, China
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Stefekova A, Capkova P, Capkova Z, Curtisova V, Srovnal J, Mracka E, Klaskova E, Prochazka M. MLPA analysis of 32 foetuses with a congenital heart defect and 1 foetus with renal defects - pilot study. The significant frequency rate of presented pathological CNV. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub 2021; 166:187-194. [PMID: 33824538 DOI: 10.5507/bp.2021.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 03/17/2021] [Indexed: 11/23/2022] Open
Abstract
AIMS The aim of this retrospective study was to determine the detection rate of the pathogenic copy number variants (CNVs) in a cohort of 33 foetuses - 32 with CHD (congenital heart defects) and 1 with kidney defect, after exclusion of common aneuploidies (trisomy 13, 18, 21, and monosomy X) by karyotyping, Multiplex ligation - dependent probe amplification (MLPA) and chromosomal microarray analysis (CMA). We also assess the effectivity of MLPA as a method of the first tier for quick and inexpensive detection of mutations, causing congenital malformations in foetuses. METHODS MLPA with probe mixes P070, P036 - Telomere 3 and 5, P245 - microdeletions, P250 - DiGeorge syndrome, and P311 - CHD (Congenital heart defects) was performed in 33 samples of amniotic fluid and chorionic villi. CMA was performed in 10 relevant cases. RESULTS Pathogenic CNVs were found in 5 samples: microdeletions in region 22q11.2 (≈2 Mb) in two foetuses, one distal microdeletion of the 22q11.2 region containing genes LZTR1, CRKL, AIFM3 and SNAP29 (≈416 kb) in the foetus with bilateral renal agenesis, 8p23.1 (3.8 Mb) microdeletion syndrome and microdeletion in area 9q34.3 (1.7 Mb, Kleefstra syndrome). MLPA as an initial screening method revealed unambiguously pathogenic CNVs in 15.2 % of samples. CONCLUSION Our study suggests that MLPA and CMA are a reliable and high-resolution technology and should be used as the first-tier test for prenatal diagnosis of congenital heart disease. Determination of the cause of the abnormality is crucial for genetic counselling and further management of the pregnancy.
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Affiliation(s)
- Andrea Stefekova
- Department of Medical Genetics, University Hospital Olomouc, Czech Republic.,Faculty of Medicine and Dentistry, Palacky University Olomouc, Olomouc, Czech Republic
| | - Pavlina Capkova
- Department of Medical Genetics, University Hospital Olomouc, Czech Republic.,Faculty of Medicine and Dentistry, Palacky University Olomouc, Olomouc, Czech Republic
| | - Zuzana Capkova
- Department of Medical Genetics, University Hospital Olomouc, Czech Republic.,Faculty of Medicine and Dentistry, Palacky University Olomouc, Olomouc, Czech Republic
| | - Vaclava Curtisova
- Department of Medical Genetics, University Hospital Olomouc, Czech Republic
| | - Josef Srovnal
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University Olomouc, Czech Republic.,Department of Pediatrics, University Hospital Olomouc, Czech Republic
| | - Enkhjargalan Mracka
- Department of Medical Genetics, University Hospital Olomouc, Czech Republic.,Faculty of Medicine and Dentistry, Palacky University Olomouc, Olomouc, Czech Republic
| | - Eva Klaskova
- Faculty of Medicine and Dentistry, Palacky University Olomouc, Olomouc, Czech Republic.,Department of Pediatrics, University Hospital Olomouc, Czech Republic
| | - Martin Prochazka
- Department of Medical Genetics, University Hospital Olomouc, Czech Republic.,Faculty of Medicine and Dentistry, Palacky University Olomouc, Olomouc, Czech Republic
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Minoche AE, Lundie B, Peters GB, Ohnesorg T, Pinese M, Thomas DM, Zankl A, Roscioli T, Schonrock N, Kummerfeld S, Burnett L, Dinger ME, Cowley MJ. ClinSV: clinical grade structural and copy number variant detection from whole genome sequencing data. Genome Med 2021; 13:32. [PMID: 33632298 PMCID: PMC7908648 DOI: 10.1186/s13073-021-00841-x] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 02/02/2021] [Indexed: 01/09/2023] Open
Abstract
Whole genome sequencing (WGS) has the potential to outperform clinical microarrays for the detection of structural variants (SV) including copy number variants (CNVs), but has been challenged by high false positive rates. Here we present ClinSV, a WGS based SV integration, annotation, prioritization, and visualization framework, which identified 99.8% of simulated pathogenic ClinVar CNVs > 10 kb and 11/11 pathogenic variants from matched microarrays. The false positive rate was low (1.5-4.5%) and reproducibility high (95-99%). In clinical practice, ClinSV identified reportable variants in 22 of 485 patients (4.7%) of which 35-63% were not detectable by current clinical microarray designs. ClinSV is available at https://github.com/KCCG/ClinSV .
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Affiliation(s)
- Andre E Minoche
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia.
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia.
| | - Ben Lundie
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
| | - Greg B Peters
- Sydney Genome Diagnostics, The Children's Hospital at Westmead, Hawkesbury Road & Hainsworth Street, Westmead, NSW, Australia
| | - Thomas Ohnesorg
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- Genome.One, Darlinghurst, NSW, Australia
| | - Mark Pinese
- Children's Cancer Institute, University of New South Wales, Randwick, Sydney, NSW, Australia
- School of Women's and Children's Health, UNSW, Sydney, NSW, Australia
| | - David M Thomas
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia
- The Kinghorn Cancer Centre and Cancer Division, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
| | - Andreas Zankl
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- Department of Clinical Genetics, The Children's Hospital at Westmead, Hawkesbury Road, Westmead, NSW, Australia
- Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia
| | - Tony Roscioli
- NSW Health Pathology Randwick, Sydney, NSW, Australia
- Centre for Clinical Genetics, Sydney Children's Hospital, Randwick, NSW, Australia
- Prince of Wales Clinical School, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, University of New South Wales, Randwick, Sydney, NSW, Australia
| | - Nicole Schonrock
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- Genome.One, Darlinghurst, NSW, Australia
| | - Sarah Kummerfeld
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia
| | - Leslie Burnett
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia
- Genome.One, Darlinghurst, NSW, Australia
- Sydney Medical School, The University of Sydney, Camperdown, NSW, Australia
| | - Marcel E Dinger
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW, Sydney, NSW, Australia
| | - Mark J Cowley
- Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, 370 Victoria Street, Darlinghurst, NSW, Australia.
- St Vincent's Clinical School, UNSW, Sydney, NSW, Australia.
- Children's Cancer Institute, University of New South Wales, Randwick, Sydney, NSW, Australia.
- School of Women's and Children's Health, UNSW, Sydney, NSW, Australia.
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10
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Thygesen JH, Presman A, Harju-Seppänen J, Irizar H, Jones R, Kuchenbaecker K, Lin K, Alizadeh BZ, Austin-Zimmerman I, Bartels-Velthuis A, Bhat A, Bruggeman R, Cahn W, Calafato S, Crespo-Facorro B, de Haan L, de Zwarte SMC, Di Forti M, Díez-Revuelta Á, Hall J, Hall MH, Iyegbe C, Jablensky A, Kahn R, Kalaydjieva L, Kravariti E, Lawrie S, Luykx JJ, Mata I, McDonald C, McIntosh AM, McQuillin A, Muir R, Ophoff R, Picchioni M, Prata DP, Ranlund S, Rujescu D, Rutten BPF, Schulze K, Shaikh M, Schirmbeck F, Simons CJP, Toulopoulou T, van Amelsvoort T, van Haren N, van Os J, van Winkel R, Vassos E, Walshe M, Weisbrod M, Zartaloudi E, Bell V, Powell J, Lewis CM, Murray RM, Bramon E. Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study. Mol Psychiatry 2021; 26:5307-5319. [PMID: 32719466 PMCID: PMC8589646 DOI: 10.1038/s41380-020-0820-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 06/11/2020] [Accepted: 06/11/2020] [Indexed: 02/06/2023]
Abstract
The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.
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Affiliation(s)
- Johan H. Thygesen
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Amelia Presman
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Jasmine Harju-Seppänen
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Haritz Irizar
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Rebecca Jones
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Karoline Kuchenbaecker
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK ,grid.83440.3b0000000121901201UCL Genetics Institute, University College London, London, UK
| | - Kuang Lin
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK ,grid.4991.50000 0004 1936 8948Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Behrooz Z. Alizadeh
- grid.4494.d0000 0000 9558 4598University of Groningen, University Medical Center Groningen, University Center for Psychiatry, Rob Giel Research Center, Groningen, The Netherlands ,grid.4494.d0000 0000 9558 4598Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands
| | | | - Agna Bartels-Velthuis
- grid.4494.d0000 0000 9558 4598University of Groningen, University Medical Center Groningen, University Center for Psychiatry, Rob Giel Research Center, Groningen, The Netherlands
| | - Anjali Bhat
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Richard Bruggeman
- grid.4494.d0000 0000 9558 4598University of Groningen, University Medical Center Groningen, University Center for Psychiatry, Rob Giel Research Center, Groningen, The Netherlands ,grid.4830.f0000 0004 0407 1981Department of Clinical and Developmental Neuropsychology, University of Groningen, Groningen, The Netherlands
| | - Wiepke Cahn
- grid.5477.10000000120346234University Medical Center Utrecht, Department of Psychiatry, Brain Centre Rudolf Magnus, Utrecht University, Utrecht, The Netherlands ,grid.413664.2Altrecht, General Mental Health Care, Utrecht, The Netherlands
| | - Stella Calafato
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Benedicto Crespo-Facorro
- grid.469673.90000 0004 5901 7501CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Sevilla, Spain ,grid.7821.c0000 0004 1770 272XUniversity Hospital Marqués de Valdecilla, University of Cantabria–IDIVAL, Santander, Spain ,grid.9224.d0000 0001 2168 1229Hospital Universitario Virgen del Rocío, IBiS, Department of Psychiatry, School of Medicine, University of Sevilla, Sevilla, Spain
| | - Liewe de Haan
- grid.7177.60000000084992262Amsterdam UMC, Department of Psychiatry, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands ,grid.491093.60000 0004 0378 2028Arkin, Institute for Mental Health, Amsterdam, The Netherlands
| | - Sonja M. C. de Zwarte
- grid.5477.10000000120346234University Medical Center Utrecht, Department of Psychiatry, Brain Centre Rudolf Magnus, Utrecht University, Utrecht, The Netherlands
| | - Marta Di Forti
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK
| | - Álvaro Díez-Revuelta
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK ,grid.5690.a0000 0001 2151 2978Laboratory of Cognitive and Computational Neuroscience—Centre for Biomedical Technology (CTB), Complutense University and Technical University of Madrid, Madrid, Spain
| | - Jeremy Hall
- grid.5600.30000 0001 0807 5670School of Medicine, Cardiff University, Hadyn Ellis Building, Maindy Road, Cardiff, UK
| | - Mei-Hua Hall
- grid.38142.3c000000041936754XPsychosis Neurobiology Laboratory, Harvard Medical School, McLean Hospital, Belmont, MA USA
| | - Conrad Iyegbe
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK
| | - Assen Jablensky
- grid.1012.20000 0004 1936 7910Centre for Clinical Research in Neuropsychiatry, The University of Western Australia, Perth, WA Australia
| | - Rene Kahn
- grid.5477.10000000120346234University Medical Center Utrecht, Department of Psychiatry, Brain Centre Rudolf Magnus, Utrecht University, Utrecht, The Netherlands ,grid.59734.3c0000 0001 0670 2351Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Luba Kalaydjieva
- grid.1012.20000 0004 1936 7910Harry Perkins Institute of Medical Research and Centre for Medical Research, The University of Western Australia, Perth, WA Australia
| | - Eugenia Kravariti
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK
| | - Stephen Lawrie
- grid.4305.20000 0004 1936 7988Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, Scotland UK
| | - Jurjen J. Luykx
- grid.5477.10000000120346234University Medical Center Utrecht, Department of Psychiatry, Brain Centre Rudolf Magnus, Utrecht University, Utrecht, The Netherlands ,grid.7692.a0000000090126352Department of Translational Neuroscience, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands ,grid.491146.f0000 0004 0478 3153Second opinion outpatient clinic, GGNet Mental Health, Warsnveld, The Netherlands
| | - Igancio Mata
- grid.469673.90000 0004 5901 7501CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Sevilla, Spain ,Fundación Argibide, Pamplona, Spain
| | - Colm McDonald
- grid.6142.10000 0004 0488 0789The Centre for Neuroimaging & Cognitive Genomics (NICOG) and NCBES Galway Neuroscience Centre, National University of Ireland Galway, Galway, Ireland
| | - Andrew M. McIntosh
- grid.4305.20000 0004 1936 7988Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, Scotland UK ,grid.4305.20000 0004 1936 7988Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Andrew McQuillin
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Rebecca Muir
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Roel Ophoff
- grid.19006.3e0000 0000 9632 6718Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA ,grid.5645.2000000040459992XDepartment of Psychiatry, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marco Picchioni
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK
| | - Diana P. Prata
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK ,grid.9983.b0000 0001 2181 4263Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciencias da Universidade de Lisboa, Lisboa, Portugal ,grid.45349.3f0000 0001 2220 8863Centre for Psychological Research and Social Intervention, ISCTE-IUL, Lisboa, Portugal
| | - Siri Ranlund
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK ,grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK
| | - Dan Rujescu
- grid.5252.00000 0004 1936 973XDepartment of Psychiatry, Ludwig-Maximilians University of Munich, Munich, Germany ,grid.9018.00000 0001 0679 2801Department of Psychiatry, Psychotherapy and Psychosomatics, University of Halle Wittenberg, Halle, Germany
| | - Bart P. F. Rutten
- grid.412966.e0000 0004 0480 1382Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands ,grid.412966.e0000 0004 0480 1382The Brain+Nerve Centre, Maastricht University Medical Centre+ (MUMC+), Maastricht, The Netherlands
| | - Katja Schulze
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK ,grid.37640.360000 0000 9439 0839South London and Maudsley NHS Foundation Trust, London, UK
| | - Madiha Shaikh
- grid.451079.e0000 0004 0428 0265North East London Foundation Trust, London, UK ,grid.83440.3b0000000121901201Research Department of Clinical, Educational and Health Psychology, University College London, London, UK
| | - Frederike Schirmbeck
- grid.7177.60000000084992262Amsterdam UMC, Department of Psychiatry, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands ,grid.491093.60000 0004 0378 2028Arkin, Institute for Mental Health, Amsterdam, The Netherlands
| | - Claudia J. P. Simons
- grid.412966.e0000 0004 0480 1382Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands ,grid.491104.9GGzE Institute for Mental Health Care, Eindhoven, The Netherlands
| | - Timothea Toulopoulou
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK ,grid.18376.3b0000 0001 0723 2427Department of Psychology, Bilkent University, Main Campus, Bilkent, Ankara Turkey
| | - Therese van Amelsvoort
- grid.412966.e0000 0004 0480 1382Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Neeltje van Haren
- grid.5477.10000000120346234University Medical Center Utrecht, Department of Psychiatry, Brain Centre Rudolf Magnus, Utrecht University, Utrecht, The Netherlands ,grid.5645.2000000040459992XDepartment of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Sophia’s Children Hospital, Rotterdam, The Netherlands
| | - Jim van Os
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK ,grid.412966.e0000 0004 0480 1382Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands ,grid.7692.a0000000090126352Department of Psychiatry, UMC Utrecht Brain Center, Utrecht, The Netherlands
| | - Ruud van Winkel
- grid.5596.f0000 0001 0668 7884KU Leuven, Department of Neuroscience, Research Group Psychiatry, Leuven, Belgium
| | - Evangelos Vassos
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK
| | - Muriel Walshe
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Matthias Weisbrod
- grid.7700.00000 0001 2190 4373Department of General Psychiatry, Center of Psychosocial Medicine, University of Heidelberg, Heidelberg, Germany ,grid.490718.30000000406368535SRH Klinikum, Karlsbad-Langensteinbach, Germany
| | - Eirini Zartaloudi
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - Vaughan Bell
- grid.83440.3b0000000121901201Division of Psychiatry, University College London, London, UK
| | - John Powell
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK
| | - Cathryn M. Lewis
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK
| | - Robin M. Murray
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology & Neuroscience at King’s College London, London, UK ,grid.37640.360000 0000 9439 0839South London and Maudsley NHS Foundation Trust, London, UK
| | - Elvira Bramon
- Division of Psychiatry, University College London, London, UK. .,Institute of Psychiatry, Psychology & Neuroscience at King's College London, London, UK. .,Institute of Cognitive Neuroscience, University College London, London, UK.
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11
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Pathak GA, Polimanti R, Silzer TK, Wendt FR, Chakraborty R, Phillips NR. Genetically-regulated transcriptomics & copy number variation of proctitis points to altered mitochondrial and DNA repair mechanisms in individuals of European ancestry. BMC Cancer 2020; 20:954. [PMID: 33008348 PMCID: PMC7530964 DOI: 10.1186/s12885-020-07457-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Accepted: 09/23/2020] [Indexed: 02/08/2023] Open
Abstract
Background Proctitis is an inflammation of the rectum and may be induced by radiation treatment for cancer. The genetic heritability of developing radiotoxicity and prior role of genetic variants as being associated with side-effects of radiotherapy necessitates further investigation for underlying molecular mechanisms. In this study, we investigated gene expression regulated by genetic variants, and copy number variation in prostate cancer survivors with radiotoxicity. Methods We investigated proctitis as a radiotoxic endpoint in prostate cancer patients who received radiotherapy (n = 222). We analyzed the copy number variation and genetically regulated gene expression profiles of whole-blood and prostate tissue associated with proctitis. The SNP and copy number data were genotyped on Affymetrix® Genome-wide Human SNP Array 6.0. Following QC measures, the genotypes were used to obtain gene expression by leveraging GTEx, a reference dataset for gene expression association based on genotype and RNA-seq information for prostate (n = 132) and whole-blood tissue (n = 369). Results In prostate tissue, 62 genes were significantly associated with proctitis, and 98 genes in whole-blood tissue. Six genes - CABLES2, ATP6AP1L, IFIT5, ATRIP, TELO2, and PARD6G were common to both tissues. The copy number analysis identified seven regions associated with proctitis, one of which (ALG1L2) was also associated with proctitis based on transcriptomic profiles in the whole-blood tissue. The genes identified via transcriptomics and copy number variation association were further investigated for enriched pathways and gene ontology. Some of the enriched processes were DNA repair, mitochondrial apoptosis regulation, cell-to-cell signaling interaction processes for renal and urological system, and organismal injury. Conclusions We report gene expression changes based on genetic polymorphisms. Integrating gene-network information identified these genes to relate to canonical DNA repair genes and processes. This investigation highlights genes involved in DNA repair processes and mitochondrial malfunction possibly via inflammation. Therefore, it is suggested that larger studies will provide more power to infer the extent of underlying genetic contribution for an individual’s susceptibility to developing radiotoxicity.
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Affiliation(s)
- Gita A Pathak
- Department of Microbiology, Immunology & Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, Yale University, New Haven, CT, USA.,Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Talisa K Silzer
- Department of Microbiology, Immunology & Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Frank R Wendt
- Department of Psychiatry, Yale School of Medicine, Yale University, New Haven, CT, USA.,Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Ranajit Chakraborty
- Department of Microbiology, Immunology & Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA
| | - Nicole R Phillips
- Department of Microbiology, Immunology & Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107, USA.
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12
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Saeed S, Arslan M, Manzoor J, Din SM, Janjua QM, Ayesha H, Ain QT, Inam L, Lobbens S, Vaillant E, Durand E, Derhourhi M, Amanzougarene S, Badreddine A, Berberian L, Gaget S, Khan WI, Butt TA, Bonnefond A, Froguel P. Genetic Causes of Severe Childhood Obesity: A Remarkably High Prevalence in an Inbred Population of Pakistan. Diabetes 2020; 69:1424-1438. [PMID: 32349990 DOI: 10.2337/db19-1238] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 04/25/2020] [Indexed: 11/13/2022]
Abstract
Monogenic forms of obesity have been identified in ≤10% of severely obese European patients. However, the overall spectrum of deleterious variants (point mutations and structural variants) responsible for childhood severe obesity remains elusive. In this study, we genetically screened 225 severely obese children from consanguineous Pakistani families through a combination of techniques, including an in-house-developed augmented whole-exome sequencing method (CoDE-seq) that enables simultaneous detection of whole-exome copy number variations (CNVs) and point mutations in coding regions. We identified 110 (49%) probands carrying 55 different pathogenic point mutations and CNVs in 13 genes/loci responsible for nonsyndromic and syndromic monofactorial obesity. CoDE-seq also identified 28 rare or novel CNVs associated with intellectual disability in 22 additional obese subjects (10%). Additionally, we highlight variants in candidate genes for obesity warranting further investigation. Altogether, 59% of cases in the studied cohort are likely to have a discrete genetic cause, with 13% of these as a result of CNVs, demonstrating a remarkably higher prevalence of monofactorial obesity than hitherto reported and a plausible overlapping of obesity and intellectual disabilities in several cases. Finally, inbred populations with a high prevalence of obesity provide unique, genetically enriched material in the quest of new genes/variants influencing energy balance.
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Affiliation(s)
- Sadia Saeed
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, U.K
| | - Muhammad Arslan
- School of Life Sciences, Forman Christian College (A Chartered University), Lahore, Pakistan
| | - Jaida Manzoor
- Department of Paediatric Endocrinology, Children's Hospital, Lahore, Pakistan
| | - Sadia M Din
- Institute of Molecular Biology and Biotechnology, University of Lahore, Lahore, Pakistan
| | - Qasim M Janjua
- Institute of Molecular Biology and Biotechnology, University of Lahore, Lahore, Pakistan
- Department of Physiology, University College of Medicine and Dentistry, University of Lahore, Lahore, Pakistan
| | - Hina Ayesha
- Department of Paediatrics, Punjab Medical College, Faisalabad, Pakistan
| | - Qura-Tul Ain
- Institute of Molecular Biology and Biotechnology, University of Lahore, Lahore, Pakistan
| | - Laraib Inam
- School of Life Sciences, Forman Christian College (A Chartered University), Lahore, Pakistan
| | - Stephane Lobbens
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
| | - Emmanuel Vaillant
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
| | - Emmanuelle Durand
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
| | - Mehdi Derhourhi
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
| | - Souhila Amanzougarene
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
| | - Alaa Badreddine
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
| | - Lionel Berberian
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
| | - Stefan Gaget
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
| | - Waqas I Khan
- The Children Hospital and the Institute of Child Health, Multan, Pakistan
| | - Taeed A Butt
- Department of Pediatrics, Fatima Memorial Hospital, Lahore, Pakistan
| | - Amélie Bonnefond
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, U.K
| | - Philippe Froguel
- Université de Lille, INSERM UMR1283, CNRS-UMR 8199-European Genomic Institute for Diabetes, and Lille University Hospital, Lille, France
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, U.K
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13
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Sudden Cardiac Death and Copy Number Variants: What Do We Know after 10 Years of Genetic Analysis? Forensic Sci Int Genet 2020; 47:102281. [PMID: 32248082 DOI: 10.1016/j.fsigen.2020.102281] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Revised: 03/02/2020] [Accepted: 03/18/2020] [Indexed: 02/07/2023]
Abstract
Over the last ten years, analysis of copy number variants has increasingly been applied to the study of arrhythmogenic pathologies associated with sudden death, mainly due to significant advances in the field of massive genetic sequencing. Nevertheless, few published reports have focused on the prevalence of copy number variants associated with sudden cardiac death. As a result, the frequency of these genetic alterations in arrhythmogenic diseases as well as their genetic interpretation and clinical translation has not been established. This review summarizes the current available data concerning copy number variants in sudden cardiac death-related diseases.
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14
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Pfeiffer D, Chen B, Schlicht K, Ginsbach P, Abboud S, Bersano A, Bevan S, Brandt T, Caso V, Debette S, Erhart P, Freitag-Wolf S, Giacalone G, Grau AJ, Hayani E, Jern C, Jiménez-Conde J, Kloss M, Krawczak M, Lee JM, Lemmens R, Leys D, Lichy C, Maguire JM, Martin JJ, Metso AJ, Metso TM, Mitchell BD, Pezzini A, Rosand J, Rost NS, Stenman M, Tatlisumak T, Thijs V, Touzé E, Traenka C, Werner I, Woo D, Del Zotto E, Engelter ST, Kittner SJ, Cole JW, Grond-Ginsbach C, Lyrer PA, Lindgren A. Genetic Imbalance Is Associated With Functional Outcome After Ischemic Stroke. Stroke 2019; 50:298-304. [PMID: 30661490 DOI: 10.1161/strokeaha.118.021856] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Background and Purpose- We sought to explore the effect of genetic imbalance on functional outcome after ischemic stroke (IS). Methods- Copy number variation was identified in high-density single-nucleotide polymorphism microarray data of IS patients from the CADISP (Cervical Artery Dissection and Ischemic Stroke Patients) and SiGN (Stroke Genetics Network)/GISCOME (Genetics of Ischaemic Stroke Functional Outcome) networks. Genetic imbalance, defined as total number of protein-coding genes affected by copy number variations in an individual, was compared between patients with favorable (modified Rankin Scale score of 0-2) and unfavorable (modified Rankin Scale score of ≥3) outcome after 3 months. Subgroup analyses were confined to patients with imbalance affecting ohnologs-a class of dose-sensitive genes, or to those with imbalance not affecting ohnologs. The association of imbalance with outcome was analyzed by logistic regression analysis, adjusted for age, sex, stroke subtype, stroke severity, and ancestry. Results- The study sample comprised 816 CADISP patients (age 44.2±10.3 years) and 2498 SiGN/GISCOME patients (age 67.7±14.2 years). Outcome was unfavorable in 122 CADISP and 889 SiGN/GISCOME patients. Multivariate logistic regression analysis revealed that increased genetic imbalance was associated with less favorable outcome in both samples (CADISP: P=0.0007; odds ratio=0.89; 95% CI, 0.82-0.95 and SiGN/GISCOME: P=0.0036; odds ratio=0.94; 95% CI, 0.91-0.98). The association was independent of age, sex, stroke severity on admission, stroke subtype, and ancestry. On subgroup analysis, imbalance affecting ohnologs was associated with outcome (CADISP: odds ratio=0.88; 95% CI, 0.80-0.95 and SiGN/GISCOME: odds ratio=0.93; 95% CI, 0.89-0.98) whereas imbalance without ohnologs lacked such an association. Conclusions- Increased genetic imbalance was associated with poorer functional outcome after IS in both study populations. Subgroup analysis revealed that this association was driven by presence of ohnologs in the respective copy number variations, suggesting a causal role of the deleterious effects of genetic imbalance.
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Affiliation(s)
- Dorothea Pfeiffer
- From the Department of Neurology, Heidelberg University Hospital, Germany (D.P., T.B., E.H., M. Kloss, I.W., C.G.-G.)
| | - Bowang Chen
- Department of Biology, Southern University of Science and Technology, Shenzhen, China (B.C.)
| | - Kristina Schlicht
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein Campus Kiel, Germany (K.S., S.F.-W., M. Krawczak)
| | - Philip Ginsbach
- School of Informatics, University of Edinburgh, United Kingdom (P.G.)
| | - Sherine Abboud
- Laboratory of Experimental Neurology, Université Libre de Bruxelles, Brussels, Belgium (S.A.)
| | - Anna Bersano
- Cerebrovascular Unit IRCCS Foundation C. Besta Neurological Institute, Milan, Italy (A.B.)
| | - Steve Bevan
- School of Life Science, University of Lincoln, United Kingdom (S.B.)
| | - Tobias Brandt
- From the Department of Neurology, Heidelberg University Hospital, Germany (D.P., T.B., E.H., M. Kloss, I.W., C.G.-G.).,Suva/Swiss National Accident Insurance Fund, Lucerne, Switzerland (T.B.)
| | - Valeria Caso
- Stroke Unit, Perugia University Hospital, Italy (V.C.)
| | - Stéphanie Debette
- Inserm, Bordeaux Population Health Research Center, UMR 1219, University of Bordeaux, France (S.D.).,Department of Neurology, Bordeaux University Hospital, France (S.D.)
| | - Philipp Erhart
- Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Germany (P.E.)
| | - Sandra Freitag-Wolf
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein Campus Kiel, Germany (K.S., S.F.-W., M. Krawczak)
| | - Giacomo Giacalone
- Department of Neurology, San Raffaele University Hospital, Milan, Italy (G.G.)
| | - Armin J Grau
- Department of Neurology, Klinikum Ludwigshafen, Germany (A.J.G.)
| | - Eyad Hayani
- From the Department of Neurology, Heidelberg University Hospital, Germany (D.P., T.B., E.H., M. Kloss, I.W., C.G.-G.)
| | - Christina Jern
- The Sahlgrenska Academy, University of Gothenburg, Sweden (C.J.).,Sahlgrenska University Hospital, Sweden (C.J.)
| | | | - Manja Kloss
- From the Department of Neurology, Heidelberg University Hospital, Germany (D.P., T.B., E.H., M. Kloss, I.W., C.G.-G.)
| | - Michael Krawczak
- Institute of Medical Informatics and Statistics, Kiel University, University Hospital Schleswig-Holstein Campus Kiel, Germany (K.S., S.F.-W., M. Krawczak)
| | - Jin-Moo Lee
- Department of Neurology, Washington University School of Medicine, St Louis, MO (J.-M.L.)
| | - Robin Lemmens
- Department of Neurosciences, Experimental Neurology, and Leuven Brain Institute, KU Leuven, University of Leuven, Belgium (R.L.).,VIB, Center for Brain & Disease Research, Laboratory of Neurobiology, Leuven, Belgium (R.L.).,Department of Neurology, University Hospitals Leuven, Belgium (R.L.)
| | - Didier Leys
- Department of Neurology, University of Lille, France (D.L.)
| | | | - Jane M Maguire
- Faculty of Health, University of Technology Sydney, Australia (J.M.M.).,Hunter Medical Research Institute, Priority Research Centre for Stroke and Traumatic Brain Injury, University of Newcastle, Australia (J.M.M.)
| | - Juan J Martin
- Department of Neurology, Sanatorio Allende, Cordoba, Argentina (J.J.M.)
| | - Antti J Metso
- Department of Neurology, Helsinki University Central Hospital, Finland (A.J.M., T.M.M., T.T.)
| | - Tiina M Metso
- Department of Neurology, Helsinki University Central Hospital, Finland (A.J.M., T.M.M., T.T.)
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore (B.D.M.).,Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, MD (B.D.M.)
| | - Alessandro Pezzini
- Department of Clinical and Experimental Sciences, Neurology Clinic, University of Brescia, Italy (A.P., E.D.Z.)
| | - Jonathan Rosand
- Center for Genomic Medicine (J.R.), Massachusetts General Hospital, Boston
| | - Natalia S Rost
- Department of Neurology (N.S.R.), Massachusetts General Hospital, Boston
| | - Martin Stenman
- Department of Clinical Sciences Lund, Neurology, Lund University, Sweden (M.S., A.L.).,Department of Neurology and Rehabilitation Medicine, Skåne University Hospital, Lund, Sweden (M.S., A.L.)
| | - Turgut Tatlisumak
- Department of Neurology, Helsinki University Central Hospital, Finland (A.J.M., T.M.M., T.T.).,Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden (T.T.).,Department of Neurology, Sahlgrenska University Hospital, Gothenburg, Sweden (T.T.)
| | - Vincent Thijs
- Stroke Division, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Heidelberg, Victoria, Australia (V.T.).,Department of Neurology, Austin Health, Heidelberg, Victoria, Australia (V.T.)
| | - Emmanuel Touzé
- Paris Descartes University, INSERM UMR S894, Department of Neurology, Sainte-Anne Hospital, Paris, France (E.T.).,Normandie Université, Université Caen-Normandie, Inserm U1237, CHU Côte de Nacre, Service de Neurologie, Caen, France (E.T.)
| | - Christopher Traenka
- Department of Neurology and Stroke Center, University Hospital Basel, Switzerland (C.T., S.T.E., P.A.L.)
| | - Inge Werner
- From the Department of Neurology, Heidelberg University Hospital, Germany (D.P., T.B., E.H., M. Kloss, I.W., C.G.-G.)
| | - Daniel Woo
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, OH (D.W.)
| | - Elisabetta Del Zotto
- Department of Clinical and Experimental Sciences, Neurology Clinic, University of Brescia, Italy (A.P., E.D.Z.)
| | - Stefan T Engelter
- Department of Neurology and Stroke Center, University Hospital Basel, Switzerland (C.T., S.T.E., P.A.L.).,Neurorehabilitation Unit, University of Basel, Switzerland (S.T.E.).,University Center for Medicine of Aging, Felix Platter Hospital, Basel, Switzerland (S.T.E.)
| | - Steven J Kittner
- Department of Neurology, Veterans Affairs Medical Center, Baltimore, MD (S.J.K., J.W.C.); and Department of Neurology University of Maryland School of Medicine, Baltimore (S.J.K., J.W.C.)
| | - John W Cole
- Department of Neurology, Veterans Affairs Medical Center, Baltimore, MD (S.J.K., J.W.C.); and Department of Neurology University of Maryland School of Medicine, Baltimore (S.J.K., J.W.C.)
| | - Caspar Grond-Ginsbach
- From the Department of Neurology, Heidelberg University Hospital, Germany (D.P., T.B., E.H., M. Kloss, I.W., C.G.-G.)
| | - Philippe A Lyrer
- Department of Neurology and Stroke Center, University Hospital Basel, Switzerland (C.T., S.T.E., P.A.L.)
| | - Arne Lindgren
- Department of Clinical Sciences Lund, Neurology, Lund University, Sweden (M.S., A.L.).,Department of Neurology and Rehabilitation Medicine, Skåne University Hospital, Lund, Sweden (M.S., A.L.)
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15
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Dron JS, Wang J, McIntyre AD, Cao H, Robinson JF, Duell PB, Manjoo P, Feng J, Movsesyan I, Malloy MJ, Pullinger CR, Kane JP, Hegele RA. Partial LPL deletions: rare copy-number variants contributing towards severe hypertriglyceridemia. J Lipid Res 2019; 60:1953-1958. [PMID: 31519763 DOI: 10.1194/jlr.p119000335] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Revised: 09/09/2019] [Indexed: 01/31/2023] Open
Abstract
Severe hypertriglyceridemia (HTG) is a relatively common form of dyslipidemia with a complex pathophysiology and serious health complications. HTG can develop in the presence of rare genetic factors disrupting genes involved in the triglyceride (TG) metabolic pathway, including large-scale copy-number variants (CNVs). Improvements in next-generation sequencing technologies and bioinformatic analyses have better allowed assessment of CNVs as possible causes of or contributors to severe HTG. We screened targeted sequencing data of 632 patients with severe HTG and identified partial deletions of the LPL gene, encoding the central enzyme involved in the metabolism of TG-rich lipoproteins, in four individuals (0.63%). We confirmed the genomic breakpoints in each patient with Sanger sequencing. Three patients carried an identical heterozygous deletion spanning the 5' untranslated region (UTR) to LPL exon 2, and one patient carried a heterozygous deletion spanning the 5'UTR to LPL exon 1. All four heterozygous CNV carriers were determined to have multifactorial severe HTG. The predicted null nature of our identified LPL deletions may contribute to relatively higher TG levels and a more severe clinical phenotype than other forms of genetic variation associated with the disease, particularly in the polygenic state. The identification of novel CNVs in patients with severe HTG suggests that methods for CNV detection should be included in the diagnostic workup and molecular genetic evaluation of patients with high TG levels.
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Affiliation(s)
- Jacqueline S Dron
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada.,Departments of Biochemistry Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
| | - Jian Wang
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
| | - Adam D McIntyre
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
| | - Henian Cao
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
| | - John F Robinson
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
| | - P Barton Duell
- Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR 97239
| | - Priya Manjoo
- Department of Medicine, Gordon and Leslie Diamond Centre, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
| | - James Feng
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA 94158
| | - Irina Movsesyan
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA 94158
| | - Mary J Malloy
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA 94158
| | - Clive R Pullinger
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA 94158
| | - John P Kane
- Cardiovascular Research Institute, University of California San Francisco, San Francisco, CA 94158
| | - Robert A Hegele
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada .,Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada.,Medicine, Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5B7, Canada
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16
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Pös O, Budis J, Kubiritova Z, Kucharik M, Duris F, Radvanszky J, Szemes T. Identification of Structural Variation from NGS-Based Non-Invasive Prenatal Testing. Int J Mol Sci 2019; 20:E4403. [PMID: 31500242 PMCID: PMC6769840 DOI: 10.3390/ijms20184403] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 09/03/2019] [Accepted: 09/04/2019] [Indexed: 01/18/2023] Open
Abstract
Copy number variants (CNVs) are an important type of human genome variation, which play a significant role in evolution contribute to population diversity and human genetic diseases. In recent years, next generation sequencing has become a valuable tool for clinical diagnostics and to provide sensitive and accurate approaches for detecting CNVs. In our previous work, we described a non-invasive prenatal test (NIPT) based on low-coverage massively parallel whole-genome sequencing of total plasma DNA for detection of CNV aberrations ≥600 kbp. We reanalyzed NIPT genomic data from 5018 patients to evaluate CNV aberrations in the Slovak population. Our analysis of autosomal chromosomes identified 225 maternal CNVs (47 deletions; 178 duplications) ranging from 600 to 7820 kbp. According to the ClinVar database, 137 CNVs (60.89%) were fully overlapping with previously annotated variants, 66 CNVs (29.33%) were in partial overlap, and 22 CNVs (9.78%) did not overlap with any previously described variant. Identified variants were further classified with the AnnotSV method. In summary, we identified 129 likely benign variants, 13 variants of uncertain significance, and 83 likely pathogenic variants. In this study, we use NIPT as a valuable source of population specific data. Our results suggest the utility of genomic data from commercial CNV analysis test as background for a population study.
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Affiliation(s)
- Ondrej Pös
- Faculty of Natural Sciences, Comenius University, 841 04 Bratislava, Slovakia.
- Geneton Ltd., 841 04 Bratislava, Slovakia.
| | - Jaroslav Budis
- Geneton Ltd., 841 04 Bratislava, Slovakia.
- Comenius University Science Park, 841 04 Bratislava, Slovakia.
- Slovak Center of Scientific and Technical Information, 811 04 Bratislava, Slovakia.
| | - Zuzana Kubiritova
- Faculty of Natural Sciences, Comenius University, 841 04 Bratislava, Slovakia.
- Institute for Clinical and Translational Research, Biomedical Research Center, Slovak Academy of Sciences, 845 05 Bratislava, Slovakia.
| | | | - Frantisek Duris
- Geneton Ltd., 841 04 Bratislava, Slovakia.
- Slovak Center of Scientific and Technical Information, 811 04 Bratislava, Slovakia.
| | - Jan Radvanszky
- Faculty of Natural Sciences, Comenius University, 841 04 Bratislava, Slovakia.
- Institute for Clinical and Translational Research, Biomedical Research Center, Slovak Academy of Sciences, 845 05 Bratislava, Slovakia.
| | - Tomas Szemes
- Faculty of Natural Sciences, Comenius University, 841 04 Bratislava, Slovakia.
- Geneton Ltd., 841 04 Bratislava, Slovakia.
- Comenius University Science Park, 841 04 Bratislava, Slovakia.
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17
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Abstract
PURPOSE OF REVIEW DNA copy number variations (CNVs) are large-scale mutations that include deletions and duplications larger than 50 bp in size. In the era when single-nucleotide variations were the major focus of genetic technology and research, CNVs were largely overlooked. However, CNVs clearly underlie a substantial proportion of clinical disorders. Here, we update recent progress in identifying CNVs in dyslipidemias. RECENT FINDINGS Until last year, only the LDLR and LPA genes were appreciated as loci within which clinically relevant CNVs contributed to familial hypercholesterolemia and variation in Lp(a) levels, respectively. Since 2017, next-generation sequencing panels have identified pathogenic CNVs in at least five more genes underlying dyslipidemias, including a PCSK9 whole-gene duplication in familial hypercholesterolemia; LPL, GPIHBP1, and APOC2 deletions in hypertriglyceridemia; and ABCA1 deletions in hypoalphalipoproteinemia. SUMMARY CNVs are an important class of mutation that contribute to the molecular genetic heterogeneity underlying dyslipidemias. Clinical applications of next-generation sequencing technologies need to consider CNVs concurrently with familiar small-scale genetic variation, given the likely implications for improved diagnosis and treatment.
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Affiliation(s)
- Michael A Iacocca
- Robarts Research Institute, and Department of Biochemistry, Schulich School of Medicine and Dentistry
| | - Jacqueline S Dron
- Robarts Research Institute, and Department of Biochemistry, Schulich School of Medicine and Dentistry
| | - Robert A Hegele
- Robarts Research Institute, and Department of Biochemistry, Schulich School of Medicine and Dentistry
- Department of Medicine, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
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18
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Tai AS, Peng CH, Peng SC, Hsieh WP. Decomposing the subclonal structure of tumors with two-way mixture models on copy number aberrations. PLoS One 2018; 13:e0206579. [PMID: 30540749 PMCID: PMC6291075 DOI: 10.1371/journal.pone.0206579] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 10/16/2018] [Indexed: 12/02/2022] Open
Abstract
Multistage tumorigenesis is a dynamic process characterized by the accumulation of mutations. Thus, a tumor mass is composed of genetically divergent cell subclones. With the advancement of next-generation sequencing (NGS), mathematical models have been recently developed to decompose tumor subclonal architecture from a collective genome sequencing data. Most of the methods focused on single-nucleotide variants (SNVs). However, somatic copy number aberrations (CNAs) also play critical roles in carcinogenesis. Therefore, further modeling subclonal CNAs composition would hold the promise to improve the analysis of tumor heterogeneity and cancer evolution. To address this issue, we developed a two-way mixture Poisson model, named CloneDeMix for the deconvolution of read-depth information. It can infer the subclonal copy number, mutational cellular prevalence (MCP), subclone composition, and the order in which mutations occurred in the evolutionary hierarchy. The performance of CloneDeMix was systematically assessed in simulations. As a result, the accuracy of CNA inference was nearly 93% and the MCP was also accurately restored. Furthermore, we also demonstrated its applicability using head and neck cancer samples from TCGA. Our results inform about the extent of subclonal CNA diversity, and a group of candidate genes that probably initiate lymph node metastasis during tumor evolution was also discovered. Most importantly, these driver genes are located at 11q13.3 which is highly susceptible to copy number change in head and neck cancer genomes. This study successfully estimates subclonal CNAs and exhibit the evolutionary relationships of mutation events. By doing so, we can track tumor heterogeneity and identify crucial mutations during evolution process. Hence, it facilitates not only understanding the cancer development but finding potential therapeutic targets. Briefly, this framework has implications for improved modeling of tumor evolution and the importance of inclusion of subclonal CNAs.
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Affiliation(s)
- An-Shun Tai
- Institute of Statistics, National Tsing Hua University, Hsinchu, Taiwan, R.O.C
| | - Chien-Hua Peng
- Institute of Statistics, National Tsing Hua University, Hsinchu, Taiwan, R.O.C
- * E-mail: (WPH); (CHP)
| | - Shih-Chi Peng
- Institute of Statistics, National Tsing Hua University, Hsinchu, Taiwan, R.O.C
| | - Wen-Ping Hsieh
- Institute of Statistics, National Tsing Hua University, Hsinchu, Taiwan, R.O.C
- * E-mail: (WPH); (CHP)
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19
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Sgardioli IC, Lustosa-Mendes E, dos Santos AP, Vieira TP, Gil-da-Silva-Lopes VL. A Rare Case of Concomitant Deletions in 15q11.2 and 19p13.3. Cytogenet Genome Res 2018; 156:80-86. [DOI: 10.1159/000493283] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/02/2018] [Indexed: 01/29/2023] Open
Abstract
A female individual with concomitant deletions in 15q11.2 and 19p13.3 is reported. She presents facial dysmorphisms, motor delay, learning difficulties, and mild behavioral impairment. After chromosomal microarray analysis, the final karyotype was established as 46,XX.arr[GRCh37] 15q11.2 (22770421_23282798)×1,19p13.3(3793904_4816330)×1. The deletion in 15q11.2 is 507 kb in size involving 7 non-imprinted genes, 4 of which are registered in the OMIM database and are implicated in neuropsychiatric or neurodevelopmental disorders. The deletion in 19p13.3 is 1,022 kb in size and encompasses 47 genes, most of which do not have a well-known function. The genotype-phenotype correlation is discussed, and most of the features could be related to the 19p13.3 deletion, except for velopharyngeal insufficiency. Other genes encompassed in the deleted region, as well as unrecognized epistatic factors could also be involved. Nevertheless, the two-hit model related to the 15q11.2 deletion would be an important hypothesis to be considered.
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20
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Affiliation(s)
| | - Philip Erhart
- Department of Vascular and Endovascular Surgery, University Hospital Heidelberg, Heidelberg, Germany
| | - Bowang Chen
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Manja Kloss
- Department of Neurology, University Hospital Heidelberg, Heidelberg, Germany
| | - Stefan T. Engelter
- Neurorehabilitation Unit, University of Basel and University Center for Medicine of Aging, Felix Platter Hospital, Basel, Switzerland
- Department of Neurology and Stroke Center, University Hospital Basel, Basel, Switzerland
| | - John W. Cole
- Department of Neurology, Veterans Affairs Medical Center and University of Maryland School of Medicine, Baltimore, USA
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21
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Fernández Asensio A, Iglesias T, Cotarelo A, Espina M, Blanco-González E, Sierra L, Montes-Bayón M. Multiplex polymerase chain reaction in combination with gel electrophoresis-inductively coupled plasma mass spectrometry: A powerful tool for the determination of gene copy number variations and gene expression changes. Anal Chim Acta 2018; 1023:64-73. [DOI: 10.1016/j.aca.2018.03.047] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Revised: 03/09/2018] [Accepted: 03/10/2018] [Indexed: 12/14/2022]
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22
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Cosemans N, Claes P, Brison N, Vermeesch JR, Peeters H. Noise-robust assessment of SNP array based CNV calls through local noise estimation of log R ratios. Stat Appl Genet Mol Biol 2018; 17:sagmb-2017-0026. [PMID: 29708886 DOI: 10.1515/sagmb-2017-0026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Arrays based on single nucleotide polymorphisms (SNPs) have been successful for the large scale discovery of copy number variants (CNVs). However, current CNV calling algorithms still have limitations in detecting CNVs with high specificity and sensitivity, especially in case of small (<100 kb) CNVs. Therefore, this study presents a simple statistical analysis to evaluate CNV calls from SNP arrays in order to improve the noise-robustness of existing CNV calling algorithms. The proposed approach estimates local noise of log R ratios and returns the probability that a certain observation is different from this log R ratio noise level. This probability can be triggered at different thresholds to tailor specificity and/or sensitivity in a flexible way. Moreover, a comparison based on qPCR experiments showed that the proposed noise-robust CNV calls outperformed original ones for multiple threshold values.
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Affiliation(s)
- Nele Cosemans
- Center for Human Genetics, University Hospital Leuven, KU Leuven, Leuven, Belgium
| | - Peter Claes
- Medical Image Computing, ESAT/PSI, Department of Electrical Engineering, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium
| | - Nathalie Brison
- Center for Human Genetics, University Hospital Leuven, KU Leuven, Leuven, Belgium
| | | | - Hilde Peeters
- Center for Human Genetics, University Hospital Leuven, KU Leuven, Leuven, Belgium
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23
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Abstract
Differences between genomes can be due to single nucleotide variants (SNPs), translocations, inversions and copy number variants (CNVs, gain or loss of DNA). The latter can range from sub-microscopic events to complete chromosomal aneuploidies. Small CNVs are often benign but those larger than 250 kb are strongly associated with morbid consequences such as developmental disorders and cancer. Detecting CNVs within and between populations is essential to better understand the plasticity of our genome and to elucidate its possible contribution to disease or phenotypic traits.While the link between SNPs and disease susceptibility has been well studied, to date there are still very few published CNV genome-wide association studies; probably owing to the fact that CNV analysis remains a slightly more complex task than SNP analysis (both in term of bioinformatics workflow and uncertainty in the CNV calling leading to high false positive rates and unknown false negative rates). This chapter aims at explaining computational methods for the analysis of CNVs, ranging from study design, data processing and quality control, up to genome-wide association study with clinical traits.
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Affiliation(s)
- Aurélien Macé
- Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland.,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Zoltán Kutalik
- Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
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24
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Letaief R, Rebours E, Grohs C, Meersseman C, Fritz S, Trouilh L, Esquerré D, Barbieri J, Klopp C, Philippe R, Blanquet V, Boichard D, Rocha D, Boussaha M. Identification of copy number variation in French dairy and beef breeds using next-generation sequencing. Genet Sel Evol 2017; 49:77. [PMID: 29065859 PMCID: PMC5655909 DOI: 10.1186/s12711-017-0352-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2017] [Accepted: 10/17/2017] [Indexed: 11/15/2022] Open
Abstract
Background Copy number variations (CNV) are known to play a major role in genetic variability and disease pathogenesis in several species including cattle. In this study, we report the identification and characterization of CNV in eight French beef and dairy breeds using whole-genome sequence data from 200 animals. Bioinformatics analyses to search for CNV were carried out using four different but complementary tools and we validated a subset of the CNV by both in silico and experimental approaches.
Results We report the identification and localization of 4178 putative deletion-only, duplication-only and CNV regions, which cover 6% of the bovine autosomal genome; they were validated by two in silico approaches and/or experimentally validated using array-based comparative genomic hybridization and single nucleotide polymorphism genotyping arrays. The size of these variants ranged from 334 bp to 7.7 Mb, with an average size of ~ 54 kb. Of these 4178 variants, 3940 were deletions, 67 were duplications and 171 corresponded to both deletions and duplications, which were defined as potential CNV regions. Gene content analysis revealed that, among these variants, 1100 deletions and duplications encompassed 1803 known genes, which affect a wide spectrum of molecular functions, and 1095 overlapped with known QTL regions. Conclusions Our study is a large-scale survey of CNV in eight French dairy and beef breeds. These CNV will be useful to study the link between genetic variability and economically important traits, and to improve our knowledge on the genomic architecture of cattle. Electronic supplementary material The online version of this article (doi:10.1186/s12711-017-0352-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Rabia Letaief
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78352, Jouy-en-Josas, France.
| | - Emmanuelle Rebours
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78352, Jouy-en-Josas, France
| | - Cécile Grohs
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78352, Jouy-en-Josas, France
| | - Cédric Meersseman
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78352, Jouy-en-Josas, France.,GMA, INRA, Université de Limoges, UMR1061, Unité Génétique Moléculaire Animale, 123 avenue Albert Thomas, 87060, Limoges Cedex, France
| | - Sébastien Fritz
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78352, Jouy-en-Josas, France.,Allice, Maison Nationale des Eleveurs, 75012, Paris, France
| | - Lidwine Trouilh
- LISBP, CNRS, INRA, INSA, Université de Toulouse, Toulouse, France
| | - Diane Esquerré
- GenPhySE, INRA, Université de Toulouse INPT ENSAT, Université de Toulouse INPT ENVT, 52627, Castanet-Tolosan, France
| | - Johanna Barbieri
- GenPhySE, INRA, Université de Toulouse INPT ENSAT, Université de Toulouse INPT ENVT, 52627, Castanet-Tolosan, France
| | | | - Romain Philippe
- GMA, INRA, Université de Limoges, UMR1061, Unité Génétique Moléculaire Animale, 123 avenue Albert Thomas, 87060, Limoges Cedex, France
| | - Véronique Blanquet
- GMA, INRA, Université de Limoges, UMR1061, Unité Génétique Moléculaire Animale, 123 avenue Albert Thomas, 87060, Limoges Cedex, France
| | - Didier Boichard
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78352, Jouy-en-Josas, France
| | - Dominique Rocha
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78352, Jouy-en-Josas, France
| | - Mekki Boussaha
- GABI, INRA, AgroParisTech, Université Paris-Saclay, 78352, Jouy-en-Josas, France
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25
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Nowakowska B. Clinical interpretation of copy number variants in the human genome. J Appl Genet 2017; 58:449-457. [PMID: 28963714 PMCID: PMC5655614 DOI: 10.1007/s13353-017-0407-4] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 08/31/2017] [Accepted: 09/05/2017] [Indexed: 12/15/2022]
Abstract
Molecular methods, by which copy number variants (CNVs) detection is available, have been gradually introduced into routine diagnostics over the last 15 years. Despite this, some CNVs continue to be a huge challenge when it comes to clinical interpretation. CNVs are an important source of normal and pathogenic variants, but, in many cases, their impact on human health depends on factors that are not yet known. Therefore, perception of their clinical consequences can change over time, as our knowledge grows. This review summarises guidelines that facilitate correct classification of identified changes and discusses difficulties with the interpretation of rare, small CNVs.
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Affiliation(s)
- Beata Nowakowska
- Department of Medical Genetics, Institute of Mother and Child, Kasprzaka 17a, 01-211, Warsaw, Poland.
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26
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Ivanov M, Laktionov K, Breder V, Chernenko P, Novikova E, Telysheva E, Musienko S, Baranova A, Mileyko V. Towards standardization of next-generation sequencing of FFPE samples for clinical oncology: intrinsic obstacles and possible solutions. J Transl Med 2017; 15:22. [PMID: 28137276 PMCID: PMC5282851 DOI: 10.1186/s12967-017-1125-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 01/19/2017] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Next generation sequencing has a potential to revolutionize the management of cancer patients within the framework of precision oncology. Nevertheless, lack of standardization decelerated entering of the technology into the clinical testing space. Here we dissected a number of common problems of NGS diagnostics in oncology and introduced ways they can be resolved. METHODS DNA was extracted from 26 formalin fixed paraffin embedded (FFPE) specimens and processed with the TrueSeq Amplicon Cancer Panel (Illumina Inc, San Diego, California) targeting 48 cancer-related genes and sequenced in single run. Sequencing data were comparatively analyzed by several bioinformatics pipelines. RESULTS Libraries yielded sufficient coverage to detect even low prevalent mutations. We found that the number of FFPE sequence artifacts significantly correlates with pre-normalization concentration of libraries (rank correlation -0.81; p < 1e-10), thus, contributing to sample-specific variant detection cut-offs. Surprisingly, extensive validation of EGFR mutation calls by a combination of aligners and variant callers resulted in identification of two false negatives and one false positive that were due to complexity of underlying genomic change, confirmed by Sanger sequencing. Additionally, the study of the non-EGFR amplicons revealed 33 confirmed unique mutations in 17 genes, with TP53 being the most frequently mutated. Clinical relevance of these finding is discussed. CONCLUSIONS Reporting of entire mutational spectrum revealed by targeted sequencing is questionable, at least until the clinically-driven guidelines on reporting of somatic mutations are established. The standardization of sequencing protocols, especially their data analysis components, requires assay-, disease-, and, in many cases, even sample-specific customization that could be performed only in cooperation with clinicians.
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Affiliation(s)
- Maxim Ivanov
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region, 141700 Russia
- Atlas Biomed Group, Moscow, 121069 Russia
- Institute of Chemical Biology and Fundamental Medicine of SB RAS, Novosibirsk, 630090 Russia
| | - Konstantin Laktionov
- N.N. Blokhin Russian Cancer Research Center, Ministry of Health of the Russian Federation, Kashirskoe sh. 24, Moscow, 115478 Russia
| | - Valery Breder
- N.N. Blokhin Russian Cancer Research Center, Ministry of Health of the Russian Federation, Kashirskoe sh. 24, Moscow, 115478 Russia
| | - Polina Chernenko
- N.N. Blokhin Russian Cancer Research Center, Ministry of Health of the Russian Federation, Kashirskoe sh. 24, Moscow, 115478 Russia
| | - Ekaterina Novikova
- Federal State Budgetary Institution Russian Scientific Center of Roentgenoradiology (RSCRR) of the Ministry of Healthcare of the Russian Federation (Russian Scientific Center of Roentgenoradiology), Moscow, 117485 Russia
| | - Ekaterina Telysheva
- Federal State Budgetary Institution Russian Scientific Center of Roentgenoradiology (RSCRR) of the Ministry of Healthcare of the Russian Federation (Russian Scientific Center of Roentgenoradiology), Moscow, 117485 Russia
| | | | - Ancha Baranova
- Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow Region, 141700 Russia
- Atlas Biomed Group, Moscow, 121069 Russia
- Research Centre for Medical Genetics, Moscow, 115478 Russia
- Center for the Study of Chronic Metabolic and Rare Diseases, School of System Biology, George Mason University, Fairfax, VA USA
| | - Vladislav Mileyko
- Atlas Biomed Group, Moscow, 121069 Russia
- Institute of Chemical Biology and Fundamental Medicine of SB RAS, Novosibirsk, 630090 Russia
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27
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Noll AC, Miller NA, Smith LD, Yoo B, Fiedler S, Cooley LD, Willig LK, Petrikin JE, Cakici J, Lesko J, Newton A, Detherage K, Thiffault I, Saunders CJ, Farrow EG, Kingsmore SF. Clinical detection of deletion structural variants in whole-genome sequences. NPJ Genom Med 2016; 1:16026. [PMID: 29263817 PMCID: PMC5685307 DOI: 10.1038/npjgenmed.2016.26] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2016] [Revised: 06/22/2016] [Accepted: 06/22/2016] [Indexed: 12/13/2022] Open
Abstract
Optimal management of acutely ill infants with monogenetic diseases requires rapid identification of causative haplotypes. Whole-genome sequencing (WGS) has been shown to identify pathogenic nucleotide variants in such infants. Deletion structural variants (DSVs, >50 nt) are implicated in many genetic diseases, and tools have been designed to identify DSVs using short-read WGS. Optimisation and integration of these tools into a WGS pipeline could improve diagnostic sensitivity and specificity of WGS. In addition, it may improve turnaround time when compared with current CNV assays, enhancing utility in acute settings. Here we describe DSV detection methods for use in WGS for rapid diagnosis in acutely ill infants: SKALD (Screening Konsensus and Annotation of Large Deletions) combines calls from two tools (Breakdancer and GenomeStrip) with calibrated filters and clinical interpretation rules. In four WGS runs, the average analytic precision (positive predictive value) of SKALD was 78%, and recall (sensitivity) was 27%, when compared with validated reference DSV calls. When retrospectively applied to a cohort of 36 families with acutely ill infants SKALD identified causative DSVs in two. The first was heterozygous deletion of exons 1–3 of MMP21 in trans with a heterozygous frame-shift deletion in two siblings with transposition of the great arteries and heterotaxy. In a newborn female with dysmorphic features, ventricular septal defect and persistent pulmonary hypertension, SKALD identified the breakpoints of a heterozygous, de novo 1p36.32p36.13 deletion. In summary, consensus DSV calling, implemented in an 8-h computational pipeline with parameterised filtering, has the potential to increase the diagnostic yield of WGS in acutely ill neonates and discover novel disease genes.
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Affiliation(s)
- Aaron C Noll
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA.,Heartland Institute for Clinical and Translational Research, University of Kansas Medical Center, Kansas City, KS, USA.,Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Neil A Miller
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Laurie D Smith
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA.,Heartland Institute for Clinical and Translational Research, University of Kansas Medical Center, Kansas City, KS, USA.,Department of Pediatrics, University of Missouri-Kansas City, Kansas City, MO, USA
| | - Byunggil Yoo
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Stephanie Fiedler
- Department of Pathology, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Linda D Cooley
- Department of Pediatrics, University of Missouri-Kansas City, Kansas City, MO, USA.,Department of Pathology, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Laurel K Willig
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA.,Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO, USA.,Department of Pediatrics, University of Missouri-Kansas City, Kansas City, MO, USA
| | - Josh E Petrikin
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA.,Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO, USA.,Department of Pediatrics, University of Missouri-Kansas City, Kansas City, MO, USA
| | - Julie Cakici
- Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
| | - John Lesko
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Angela Newton
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Kali Detherage
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Isabelle Thiffault
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA.,Department of Pediatrics, University of Missouri-Kansas City, Kansas City, MO, USA.,Department of Pathology, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Carol J Saunders
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA.,Department of Pediatrics, University of Missouri-Kansas City, Kansas City, MO, USA.,Department of Pathology, Children's Mercy Kansas City, Kansas City, MO, USA
| | - Emily G Farrow
- Center for Pediatric Genomic Medicine, Children's Mercy Kansas City, Kansas City, MO, USA.,Department of Pediatrics, Children's Mercy Kansas City, Kansas City, MO, USA.,Department of Pediatrics, University of Missouri-Kansas City, Kansas City, MO, USA
| | - Stephen F Kingsmore
- Heartland Institute for Clinical and Translational Research, University of Kansas Medical Center, Kansas City, KS, USA.,Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
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28
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Tracking Cancer Genetic Evolution using OncoTrack. Sci Rep 2016; 6:29647. [PMID: 27412732 PMCID: PMC4944131 DOI: 10.1038/srep29647] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2015] [Accepted: 06/20/2016] [Indexed: 02/07/2023] Open
Abstract
It is difficult for existing methods to quantify, and track the constant evolution of cancers due to high heterogeneity of mutations. However, structural variations associated with nucleotide number changes show repeatable patterns in localized regions of the genome. Here we introduce SPKMG, which generalizes nucleotide number based properties of genes, in statistical terms, at the genome-wide scale. It is measured from the normalized amount of aligned NGS reads in exonic regions of a gene. SPKMG values are calculated within OncoTrack. SPKMG values being continuous numeric variables provide a statistical metric to track DNA level changes. We show that SPKMG measures of cancer DNA show a normative pattern at the genome-wide scale. The analysis leads to the discovery of core cancer genes and also provides novel dynamic insights into the stage of cancer, including cancer development, progression, and metastasis. This technique will allow exome data to also be used for quantitative LOH/CNV analysis for tracking tumour progression and evolution with a higher efficiency.
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29
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Macé A, Tuke MA, Beckmann JS, Lin L, Jacquemont S, Weedon MN, Reymond A, Kutalik Z. New quality measure for SNP array based CNV detection. Bioinformatics 2016; 32:3298-3305. [PMID: 27402902 DOI: 10.1093/bioinformatics/btw477] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Accepted: 07/03/2016] [Indexed: 12/25/2022] Open
Abstract
MOTIVATION Only a few large systematic studies have evaluated the impact of copy number variants (CNVs) on common diseases. Several million individuals have been genotyped on single nucleotide variation arrays, which could be used for genome-wide CNVs association studies. However, CNV calls remain prone to false positives and only empirical filtering strategies exist in the literature. To overcome this issue, we defined a new quality score (QS) estimating the probability of a CNV called by PennCNV to be confirmed by other software. RESULTS Out-of-sample comparison showed that the correlation between the consensus CNV status and the QS is twice as high as it is for any previously proposed CNV filters. ROC curves displayed an AUC higher than 0.8 and simulations showed an increase up to 20% in statistical power when using QS in comparison to other filtering strategies. Superior performance was confirmed also for alternative consensus CNV definition and through improving known CNV-trait associations. AVAILABILITY AND IMPLEMENTATION http://goo.gl/T6yuFM CONTACT: zoltan.kutalik@unil.ch or aurelien@mace@unil.chSupplementary information: Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- A Macé
- Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland Department of Computational Biology, University of Lausanne, Lausanne, Switzerland Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - M A Tuke
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - J S Beckmann
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - L Lin
- Division of Cardiology, Geneva University Hospital, Geneva, Switzerland
| | - S Jacquemont
- Service de Génétique Médicale, Centre Universitaire Hospitalier Vaudois, Lausanne, Switzerland
| | - M N Weedon
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - A Reymond
- Center for Integrative Genomics, University for Lausanne, Lausanne, Switzerland
| | - Z Kutalik
- Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland Swiss Institute of Bioinformatics, Lausanne, Switzerland
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30
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Olgiati S, Quadri M, Bonifati V. Genetics of movement disorders in the next-generation sequencing era. Mov Disord 2016; 31:458-70. [DOI: 10.1002/mds.26521] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Accepted: 11/29/2015] [Indexed: 12/15/2022] Open
Affiliation(s)
- Simone Olgiati
- Department of Clinical Genetics; Erasmus MC; Rotterdam The Netherlands
| | - Marialuisa Quadri
- Department of Clinical Genetics; Erasmus MC; Rotterdam The Netherlands
| | - Vincenzo Bonifati
- Department of Clinical Genetics; Erasmus MC; Rotterdam The Netherlands
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31
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Nagasaki M, Yasuda J, Katsuoka F, Nariai N, Kojima K, Kawai Y, Yamaguchi-Kabata Y, Yokozawa J, Danjoh I, Saito S, Sato Y, Mimori T, Tsuda K, Saito R, Pan X, Nishikawa S, Ito S, Kuroki Y, Tanabe O, Fuse N, Kuriyama S, Kiyomoto H, Hozawa A, Minegishi N, Douglas Engel J, Kinoshita K, Kure S, Yaegashi N, Yamamoto M. Rare variant discovery by deep whole-genome sequencing of 1,070 Japanese individuals. Nat Commun 2015; 6:8018. [PMID: 26292667 PMCID: PMC4560751 DOI: 10.1038/ncomms9018] [Citation(s) in RCA: 297] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2014] [Accepted: 07/07/2015] [Indexed: 12/19/2022] Open
Abstract
The Tohoku Medical Megabank Organization reports the whole-genome sequences of 1,070 healthy Japanese individuals and construction of a Japanese population reference panel (1KJPN). Here we identify through this high-coverage sequencing (32.4 × on average), 21.2 million, including 12 million novel, single-nucleotide variants (SNVs) at an estimated false discovery rate of <1.0%. This detailed analysis detected signatures for purifying selection on regulatory elements as well as coding regions. We also catalogue structural variants, including 3.4 million insertions and deletions, and 25,923 genic copy-number variants. The 1KJPN was effective for imputing genotypes of the Japanese population genome wide. These data demonstrate the value of high-coverage sequencing for constructing population-specific variant panels, which covers 99.0% SNVs of minor allele frequency ≥0.1%, and its value for identifying causal rare variants of complex human disease phenotypes in genetic association studies. The Tohoku Medical Megabank Organization establishes a biobank with detailed patient health care and genome information. Here the authors analyse whole-genome sequences of 1,070 Japanese individuals, allowing them to catalogue 21 million single-nucleotide variants including 12 million novel ones.
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Affiliation(s)
- Masao Nagasaki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan.,Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8579, Japan
| | - Jun Yasuda
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Fumiki Katsuoka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Naoki Nariai
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Kaname Kojima
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Yosuke Kawai
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Yumi Yamaguchi-Kabata
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Junji Yokozawa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Inaho Danjoh
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Sakae Saito
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Yukuto Sato
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Takahiro Mimori
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Kaoru Tsuda
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Rumiko Saito
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Xiaoqing Pan
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Satoshi Nishikawa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Shin Ito
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Yoko Kuroki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Osamu Tanabe
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan.,International Research Institute of Disaster Science, Tohoku University, 468-1, Aramaki Aza-Aoba, Aoba-ku, Sendai 980-0845, Japan
| | - Hideyasu Kiyomoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Naoko Minegishi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - James Douglas Engel
- Department of Cell and Developmental Biology, University of Michigan Medical School, 109 Zina Pitcher Place, Ann Arbor, Michigan 48109-2200, USA
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8579, Japan.,Institute of Development, Aging and Cancer, Tohoku University, 4-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Shigeo Kure
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Nobuo Yaegashi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | | | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan.,Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
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32
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Locke MEO, Milojevic M, Eitutis ST, Patel N, Wishart AE, Daley M, Hill KA. Genomic copy number variation in Mus musculus. BMC Genomics 2015; 16:497. [PMID: 26141061 PMCID: PMC4490682 DOI: 10.1186/s12864-015-1713-z] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2014] [Accepted: 06/22/2015] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Copy number variation is an important dimension of genetic diversity and has implications in development and disease. As an important model organism, the mouse is a prime candidate for copy number variant (CNV) characterization, but this has yet to be completed for a large sample size. Here we report CNV analysis of publicly available, high-density microarray data files for 351 mouse tail samples, including 290 mice that had not been characterized for CNVs previously. RESULTS We found 9634 putative autosomal CNVs across the samples affecting 6.87% of the mouse reference genome. We find significant differences in the degree of CNV uniqueness (single sample occurrence) and the nature of CNV-gene overlap between wild-caught mice and classical laboratory strains. CNV-gene overlap was associated with lipid metabolism, pheromone response and olfaction compared to immunity, carbohydrate metabolism and amino-acid metabolism for wild-caught mice and classical laboratory strains, respectively. Using two subspecies of wild-caught Mus musculus, we identified putative CNVs unique to those subspecies and show this diversity is better captured by wild-derived laboratory strains than by the classical laboratory strains. A total of 9 genic copy number variable regions (CNVRs) were selected for experimental confirmation by droplet digital PCR (ddPCR). CONCLUSION The analysis we present is a comprehensive, genome-wide analysis of CNVs in Mus musculus, which increases the number of known variants in the species and will accelerate the identification of novel variants in future studies.
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Affiliation(s)
- M Elizabeth O Locke
- Department of Computer Science, The University of Western Ontario, London, ON, N6A 5B7, Canada.
| | - Maja Milojevic
- Department of Biology, The University of Western Ontario, Biological and Geological Sciences Building 1151 Richmond St. N, London, ON, N6A 5B7, Canada.
| | - Susan T Eitutis
- Department of Biology, The University of Western Ontario, Biological and Geological Sciences Building 1151 Richmond St. N, London, ON, N6A 5B7, Canada.
| | - Nisha Patel
- Department of Biology, The University of Western Ontario, Biological and Geological Sciences Building 1151 Richmond St. N, London, ON, N6A 5B7, Canada.
| | - Andrea E Wishart
- Department of Biology, The University of Western Ontario, Biological and Geological Sciences Building 1151 Richmond St. N, London, ON, N6A 5B7, Canada.
| | - Mark Daley
- Department of Computer Science, The University of Western Ontario, London, ON, N6A 5B7, Canada.
- Department of Biology, The University of Western Ontario, Biological and Geological Sciences Building 1151 Richmond St. N, London, ON, N6A 5B7, Canada.
| | - Kathleen A Hill
- Department of Computer Science, The University of Western Ontario, London, ON, N6A 5B7, Canada.
- Department of Biology, The University of Western Ontario, Biological and Geological Sciences Building 1151 Richmond St. N, London, ON, N6A 5B7, Canada.
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Gorfine M, Goldstein B, Fishman A, Heller R, Heller Y, Lamm AT. Function of cancer associated genes revealed by modern univariate and multivariate association tests. PLoS One 2015; 10:e0126544. [PMID: 25965968 PMCID: PMC4429101 DOI: 10.1371/journal.pone.0126544] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2014] [Accepted: 04/03/2015] [Indexed: 11/24/2022] Open
Abstract
Copy number variation (CNV) plays a role in pathogenesis of many human diseases, especially cancer. Several whole genome CNV association studies have been performed for the purpose of identifying cancer associated CNVs. Here we undertook a novel approach to whole genome CNV analysis, with the goal being identification of associations between CNV of different genes (CNV-CNV) across 60 human cancer cell lines. We hypothesize that these associations point to the roles of the associated genes in cancer, and can be indicators of their position in gene networks of cancer-driving processes. Recent studies show that gene associations are often non-linear and non-monotone. In order to obtain a more complete picture of all CNV associations, we performed omnibus univariate analysis by utilizing dCov, MIC, and HHG association tests, which are capable of detecting any type of association, including non-monotone relationships. For comparison we used Spearman and Pearson association tests, which detect only linear or monotone relationships. Application of dCov, MIC and HHG tests resulted in identification of twice as many associations compared to those found by Spearman and Pearson alone. Interestingly, most of the new associations were detected by the HHG test. Next, we utilized dCov's and HHG's ability to perform multivariate analysis. We tested for association between genes of unknown function and known cancer-related pathways. Our results indicate that multivariate analysis is much more effective than univariate analysis for the purpose of ascribing biological roles to genes of unknown function. We conclude that a combination of multivariate and univariate omnibus association tests can reveal significant information about gene networks of disease-driving processes. These methods can be applied to any large gene or pathway dataset, allowing more comprehensive analysis of biological processes.
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Affiliation(s)
- Malka Gorfine
- Faculty of Industrial Engineering and Management, Technion- Israel Institute of Technology, Technion City, Haifa 3200003, Israel
| | - Boaz Goldstein
- Faculty of Biology, Technion- Israel Institute of Technology, Technion City, Haifa 3200003, Israel
| | - Alla Fishman
- Faculty of Biology, Technion- Israel Institute of Technology, Technion City, Haifa 3200003, Israel
| | - Ruth Heller
- Department of Statistics and Operations Research, Tel Aviv University, Ramat Aviv, Tel Aviv 6997801, Israel
| | | | - Ayelet T. Lamm
- Faculty of Biology, Technion- Israel Institute of Technology, Technion City, Haifa 3200003, Israel
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Cooper NJ, Shtir CJ, Smyth DJ, Guo H, Swafford AD, Zanda M, Hurles ME, Walker NM, Plagnol V, Cooper JD, Howson JMM, Burren OS, Onengut-Gumuscu S, Rich SS, Todd JA. Detection and correction of artefacts in estimation of rare copy number variants and analysis of rare deletions in type 1 diabetes. Hum Mol Genet 2014; 24:1774-90. [PMID: 25424174 PMCID: PMC4381751 DOI: 10.1093/hmg/ddu581] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
Copy number variants (CNVs) have been proposed as a possible source of ‘missing heritability’ in complex human diseases. Two studies of type 1 diabetes (T1D) found null associations with common copy number polymorphisms, but CNVs of low frequency and high penetrance could still play a role. We used the Log-R-ratio intensity data from a dense single nucleotide polymorphism (SNP) array, ImmunoChip, to detect rare CNV deletions (rDELs) and duplications (rDUPs) in 6808 T1D cases, 9954 controls and 2206 families with T1D-affected offspring. Initial analyses detected CNV associations. However, these were shown to be false-positive findings, failing replication with polymerase chain reaction. We developed a pipeline of quality control (QC) tests that were calibrated using systematic testing of sensitivity and specificity. The case–control odds ratios (OR) of CNV burden on T1D risk resulting from this QC pipeline converged on unity, suggesting no global frequency difference in rDELs or rDUPs. There was evidence that deletions could impact T1D risk for a small minority of cases, with enrichment for rDELs longer than 400 kb (OR = 1.57, P = 0.005). There were also 18 de novo rDELs detected in affected offspring but none for unaffected siblings (P = 0.03). No specific CNV regions showed robust evidence for association with T1D, although frequencies were lower than expected (most less than 0.1%), substantially reducing statistical power, which was examined in detail. We present an R-package, plumbCNV, which provides an automated approach for QC and detection of rare CNVs that can facilitate equivalent analyses of large-scale SNP array datasets.
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Affiliation(s)
- Nicholas J Cooper
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Corina J Shtir
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Deborah J Smyth
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Hui Guo
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Austin D Swafford
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Manuela Zanda
- Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, University College London, Darwin Building, London WC1E 6BT, UK
| | - Matthew E Hurles
- Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK
| | - Neil M Walker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Vincent Plagnol
- University College London, Darwin Building, London WC1E 6BT, UK
| | - Jason D Cooper
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Joanna M M Howson
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK, Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge CB1 8RN, UK
| | - Oliver S Burren
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, West Complex, University of Virginia, Charlottesville, VA 22908, USA
| | - Stephen S Rich
- Center for Public Health Genomics, West Complex, University of Virginia, Charlottesville, VA 22908, USA
| | - John A Todd
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK,
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Campos CMR, Zanardo EA, Dutra RL, Kulikowski LD, Kim CA. Investigation of copy number variation in children with conotruncal heart defects. Arq Bras Cardiol 2014; 104:24-31. [PMID: 25387403 PMCID: PMC4387608 DOI: 10.5935/abc.20140169] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2014] [Accepted: 09/04/2014] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Congenital heart defects (CHD) are the most prevalent group of structural abnormalities at birth and one of the main causes of infant morbidity and mortality. Studies have shown a contribution of the copy number variation in the genesis of cardiac malformations. OBJECTIVES Investigate gene copy number variation (CNV) in children with conotruncal heart defect. METHODS Multiplex ligation-dependent probe amplification (MLPA) was performed in 39 patients with conotruncal heart defect. Clinical and laboratory assessments were conducted in all patients. The parents of the probands who presented abnormal findings were also investigated. RESULTS Gene copy number variation was detected in 7/39 patients: 22q11.2 deletion, 22q11.2 duplication, 15q11.2 duplication, 20p12.2 duplication, 19p deletion, 15q and 8p23.2 duplication with 10p12.31 duplication. The clinical characteristics were consistent with those reported in the literature associated with the encountered microdeletion/microduplication. None of these changes was inherited from the parents. CONCLUSIONS Our results demonstrate that the technique of MLPA is useful in the investigation of microdeletions and microduplications in conotruncal congenital heart defects. Early diagnosis of the copy number variation in patients with congenital heart defect assists in the prevention of morbidity and decreased mortality in these patients.
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Affiliation(s)
| | - Evelin Aline Zanardo
- Laboratório de Citogenômica - LIM 03, Departamento de Patologia, Universidade de São Paulo, São Paulo, SP, Brazil
| | - Roberta Lelis Dutra
- Laboratório de Citogenômica - LIM 03, Departamento de Patologia, Universidade de São Paulo, São Paulo, SP, Brazil
| | | | - Chong Ae Kim
- Universidade de São Paulo, São Paulo, SP, Brazil
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Waugh MG. Amplification of Chromosome 1q Genes Encoding the Phosphoinositide Signalling Enzymes PI4KB, AKT3, PIP5K1A and PI3KC2B in Breast Cancer. J Cancer 2014; 5:790-6. [PMID: 25368680 PMCID: PMC4216804 DOI: 10.7150/jca.9794] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2014] [Accepted: 09/11/2014] [Indexed: 01/08/2023] Open
Abstract
Little is known about the possible oncogenic roles of genes encoding for the phosphatidylinositol 4-kinases, a family of enzymes that regulate an early step in phosphoinositide signalling. To address this issue, the mutational status of all four human phosphatidylinositol 4-kinases genes was analyzed across 852 breast cancer samples using the COSMIC data resource. Point mutations in the phosphatidylinositol 4-kinase genes were uncommon and appeared in less than 1% of the patient samples however, 62% of the tumours had increases in gene copy number for PI4KB which encodes the phosphatidylinositol 4-kinase IIIbeta isozyme. Extending this analysis to subsequent enzymes in the phosphoinositide signalling cascades revealed that the only PIP5K1A, PI3KC2B and AKT3 genes exhibited similar patterns of gene copy number variation. By comparison, gene copy number increases for established oncogenes such as EGFR and HER2/Neu were only evident in 20% of the samples. The PI4KB, PIP5K1A, PI3KC2B and AKT3 genes are related in that they all localize to chromosome 1q which is often structurally and numerically abnormal in breast cancer. These results demonstrate that a gene quartet encoding a potential phosphoinositide signalling pathway is amplified in a subset of breast cancers.
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Affiliation(s)
- Mark G Waugh
- Lipid and Membrane Biology Group, Institute for Liver and Digestive Health, UCL, Royal Free Campus, Rowland Hill Street, London, NW3 2PF United Kingdom
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Köhler S, Schoeneberg U, Czeschik JC, Doelken SC, Hehir-Kwa JY, Ibn-Salem J, Mungall CJ, Smedley D, Haendel MA, Robinson PN. Clinical interpretation of CNVs with cross-species phenotype data. J Med Genet 2014; 51:766-772. [PMID: 25280750 DOI: 10.1136/jmedgenet-2014-102633] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
BACKGROUND Clinical evaluation of CNVs identified via techniques such as array comparative genome hybridisation (aCGH) involves the inspection of lists of known and unknown duplications and deletions with the goal of distinguishing pathogenic from benign CNVs. A key step in this process is the comparison of the individual's phenotypic abnormalities with those associated with Mendelian disorders of the genes affected by the CNV. However, because often there is not much known about these human genes, an additional source of data that could be used is model organism phenotype data. Currently, almost 6000 genes in mouse and zebrafish are, when knocked out, associated with a phenotype in the model organism, but no disease is known to be caused by mutations in the human ortholog. Yet, searching model organism databases and comparing model organism phenotypes with patient phenotypes for identifying novel disease genes and medical evaluation of CNVs is hindered by the difficulty in integrating phenotype information across species and the lack of appropriate software tools. METHODS Here, we present an integrated ranking scheme based on phenotypic matching, degree of overlap with known benign or pathogenic CNVs and the haploinsufficiency score for the prioritisation of CNVs responsible for a patient's clinical findings. RESULTS We show that this scheme leads to significant improvements compared with rankings that do not exploit phenotypic information. We provide a software tool called PhenogramViz, which supports phenotype-driven interpretation of aCGH findings based on multiple data sources, including the integrated cross-species phenotype ontology Uberpheno, in order to visualise gene-to-phenotype relations. CONCLUSIONS Integrating and visualising cross-species phenotype information on the affected genes may help in routine diagnostics of CNVs.
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Affiliation(s)
- Sebastian Köhler
- Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin,Berlin, Germany.,Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany
| | - Uwe Schoeneberg
- Foundation Institute Molecular Biology and Bioinformatics, Freie Universitaet Berlin, Berlin, Germany
| | | | - Sandra C Doelken
- Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin,Berlin, Germany
| | - Jayne Y Hehir-Kwa
- Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Jonas Ibn-Salem
- Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin,Berlin, Germany
| | | | - Damian Smedley
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK
| | - Melissa A Haendel
- Department of Medical Informatics and Epidemiology and OHSU Library, Oregon Health & Science University, Portland, USA
| | - Peter N Robinson
- Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin,Berlin, Germany.,Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany.,Max Planck Institute for Molecular Genetics, Berlin, Germany.,Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitaet Berlin, Berlin, Germany
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Ding X, Tsang SY, Ng SK, Xue H. Application of Machine Learning to Development of Copy Number Variation-based Prediction of Cancer Risk. GENOMICS INSIGHTS 2014. [PMID: 26203258 PMCID: PMC4504076 DOI: 10.4137/gei.s15002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
In the present study, recurrent copy number variations (CNVs) from non-tumor blood cell DNAs of Caucasian non-cancer subjects and glioma, myeloma, and colorectal cancer-patients, and Korean non-cancer subjects and hepatocellular carcinoma, gastric cancer, and colorectal cancer patients, were found to reveal for each of the two ethnic cohorts highly significant differences between cancer patients and controls with respect to the number of CN-losses and size-distribution of CN-gains, suggesting the existence of recurrent constitutional CNV-features useful for prediction of predisposition to cancer. Upon identification by machine learning, such CNV-features could extensively discriminate between cancer-patient and control DNAs. When the CNV-features selected from a learning-group of Caucasian or Korean mixed DNAs consisting of both cancer-patient and control DNAs were employed to make predictions on the cancer predisposition of an unseen test group of mixed DNAs, the average prediction accuracy was 93.6% for the Caucasian cohort and 86.5% for the Korean cohort.
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Affiliation(s)
- Xiaofan Ding
- Applied Genomics Center and Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Shui-Ying Tsang
- Applied Genomics Center and Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Siu-Kin Ng
- Applied Genomics Center and Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
| | - Hong Xue
- Applied Genomics Center and Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
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Abstract
MOTIVATION Studies of genomic DNA copy number alteration can deal with datasets with several million probes and thousands of subjects. Analyzing these data with currently available software (e.g. as available from BioConductor) can be extremely slow and may not be feasible because of memory requirements. RESULTS We have developed a BioConductor package, ADaCGH2, that parallelizes the main segmentation algorithms (using forking on multicore computers or parallelization via message passing interface, etc., in clusters of computers) and uses ff objects for reading and data storage. We show examples of data with 6 million probes per array; we can analyze data that would otherwise not fit in memory, and compared with the non-parallelized versions we can achieve speedups of 25-40 times on a 64-cores machine. AVAILABILITY AND IMPLEMENTATION ADaCGH2 is an R package available from BioConductor. Version 2.3.11 or higher is available from the development branch: http://www.bioconductor.org/packages/devel/bioc/html/ADaCGH2.html.
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Affiliation(s)
- Ramon Diaz-Uriarte
- Department of Biochemistry, Universidad Autónoma de Madrid, Instituto de Investigaciones Biomédicas 'Alberto Sols' (UAM-CSIC), 28029 Madrid, Spain
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English AC, Salerno WJ, Reid JG. PBHoney: identifying genomic variants via long-read discordance and interrupted mapping. BMC Bioinformatics 2014; 15:180. [PMID: 24915764 PMCID: PMC4082283 DOI: 10.1186/1471-2105-15-180] [Citation(s) in RCA: 94] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2014] [Accepted: 06/04/2014] [Indexed: 11/25/2022] Open
Abstract
Background As resequencing projects become more prevalent across a larger number of species, accurate variant identification will further elucidate the nature of genetic diversity and become increasingly relevant in genomic studies. However, the identification of larger genomic variants via DNA sequencing is limited by both the incomplete information provided by sequencing reads and the nature of the genome itself. Long-read sequencing technologies provide high-resolution access to structural variants often inaccessible to shorter reads. Results We present PBHoney, software that considers both intra-read discordance and soft-clipped tails of long reads (>10,000 bp) to identify structural variants. As a proof of concept, we identify four structural variants and two genomic features in a strain of Escherichia coli with PBHoney and validate them via de novo assembly. PBHoney is available for download at http://sourceforge.net/projects/pb-jelly/. Conclusions Implementing two variant-identification approaches that exploit the high mappability of long reads, PBHoney is demonstrated as being effective at detecting larger structural variants using whole-genome Pacific Biosciences RS II Continuous Long Reads. Furthermore, PBHoney is able to discover two genomic features: the existence of Rac-Phage in isolate; evidence of E. coli’s circular genome.
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Affiliation(s)
- Adam C English
- Human Genome Sequencing Center at Baylor College of Medicine, One Baylor Plaza, Houston 77030, Texas, USA.
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Hammond P, McKee S, Suttie M, Allanson J, Cobben JM, Maas SM, Quarrell O, Smith ACM, Lewis S, Tassabehji M, Sisodiya S, Mattina T, Hennekam R. Opposite effects on facial morphology due to gene dosage sensitivity. Hum Genet 2014; 133:1117-25. [PMID: 24889830 PMCID: PMC4148161 DOI: 10.1007/s00439-014-1455-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2014] [Accepted: 05/19/2014] [Indexed: 02/01/2023]
Abstract
Sequencing technology is increasingly demonstrating the impact of genomic copy number variation (CNV) on phenotypes. Opposing variation in growth, head size, cognition and behaviour is known to result from deletions and reciprocal duplications of some genomic regions. We propose normative inversion of face shape, opposing difference from a matched norm, as a basis for investigating the effects of gene dosage on craniofacial development. We use dense surface modelling techniques to match any face (or part of a face) to a facial norm of unaffected individuals of matched age, sex and ethnicity and then we reverse the individual’s face shape differences from the matched norm to produce the normative inversion. We demonstrate for five genomic regions, 4p16.3, 7q11.23, 11p15, 16p13.3 and 17p11.2, that such inversion for individuals with a duplication or (epi)-mutation produces facial forms remarkably similar to those associated with a deletion or opposite (epi-)mutation of the same region, and vice versa. The ability to visualise and quantify face shape effects of gene dosage is of major benefit for determining whether a CNV is the cause of the phenotype of an individual and for predicting reciprocal consequences. It enables face shape to be used as a relatively simple and inexpensive functional analysis of the gene(s) involved.
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Affiliation(s)
- Peter Hammond
- Molecular Medicine Unit, UCL Institute of Child Health, 30 Guilford St, London, WC1N 1EH, UK,
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Onaivi ES, Ishiguro H, Sgro S, Leonard CM. Cannabinoid Receptor Gene Variations in Drug Addiction and Neuropsychiatric Disorders. ACTA ACUST UNITED AC 2013. [DOI: 10.4303/jdar/235714] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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