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Raj S, Peela SCM, Kumar H, Ramaiah S, Sistla S. Comparative genomic analysis of paired clinical isolates from a patient with recurrent melioidosis reveals a low within-host mutation rate. J Med Microbiol 2025; 74. [PMID: 40232806 DOI: 10.1099/jmm.0.002003] [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: 04/16/2025] Open
Abstract
Introduction. Relapse of melioidosis is not uncommon and can occur due to shorter oral antibiotic therapy in the first episode. In such isolates, low mutation rates were identified amongst paired clinical isolates during relapse, but large-scale structural variants were also common.Hypothesis. Using pair-wise comparison, a low number of mutations, especially amongst the virulence and antibiotic resistance genes, may be present amongst the paired isolates obtained during the study period.Aim. A pair of clinical isolates obtained from a patient with recurrent melioidosis during the study period (January 2018 to June 2021) was analysed for identifying the genomic relatedness and DNA changes that may have caused the relapse.Methodology. Using paired-end Illumina sequencing, following appropriate data quality checks, the genomes were assembled using Shovill pipeline, whilst the variants were called using Snippy. Structural variants were detected using TIDDIT, and functional associations were identified using the STRING database searches.Results. One of the isolates (from the second episode) had a highly fragmented genome, but very few structural variants and SNPs were identified. Both the isolates had similar virulence and antibiotic resistance genes; however, owing to the few structural changes, a slightly lower number of virulence genes were observed. Together, they shared 99.8% of the proteomes, and most variants identified spanned either hypothetical proteins or un-annotated regions.Conclusions. Based on comprehensive genome analysis the two strains were genetically similar, with a few structural variants, implying the second episode to be a relapse rather than a re-infection. There was no difference in the antibiotic resistance or virulence genes that may have explained the relapse.
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Affiliation(s)
- Sruthi Raj
- Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
- Present address: Department of Microbiology, Sukh Sagar Medical College, Jabalpur, Madhya Pradesh, India
| | - Sreeram Chandra Murthy Peela
- Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | - Hithesh Kumar
- Department of Biosciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Sudha Ramaiah
- Department of Biosciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Sujatha Sistla
- Department of Microbiology, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
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Chen X, Wei S, Sun C, Yi Z, Wang Z, Wu Y, Xu J, Tao J, Chen H, Zhang M, Jiang Y, Lv H, Huang C. Computational Tools for Studying Genome Structural Variation. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2025; 29:36-48. [PMID: 39905890 DOI: 10.1089/omi.2024.0200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2025]
Abstract
Structural variation (SV) typically refers to alterations in DNA fragments at least 50 base pairs long in the human genome. It can alter thousands of DNA nucleotides and thus significantly influence human health, disease, and clinical phenotypes. There is a shared and growing recognition that the emergence of effective computational tools and high-throughput technologies such as short-read sequencing and long-read sequencing offers novel insight into SV and, by extension, diseases affecting planetary health. However, numerous available SV tools exist with varying strengths and weaknesses. This is currently hampering the abilities of scholars to select the optimal tools to study SVs. Here, we reviewed 175 tools developed in the past two decades for SV detection, annotation, visualization, and downstream analysis of human genomics. In this expert review, we provide a comprehensive catalog of SV-related tools across different technology platforms and summarize their features, strengths, and limitations with an eye to accelerate systems science and planetary health innovations.
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Affiliation(s)
- Xingyu Chen
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Kay Laboratory of Quality Research in Chinese Medicine & Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, China
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Siyu Wei
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Chen Sun
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Zelin Yi
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Kay Laboratory of Quality Research in Chinese Medicine & Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, China
| | - Zihan Wang
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Kay Laboratory of Quality Research in Chinese Medicine & Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, China
| | - Yingyi Wu
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Kay Laboratory of Quality Research in Chinese Medicine & Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, China
| | - Jing Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Junxian Tao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Haiyan Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Mingming Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yongshuai Jiang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Hongchao Lv
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Chen Huang
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Kay Laboratory of Quality Research in Chinese Medicine & Faculty of Chinese Medicine, Macau University of Science and Technology, Taipa, China
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Karpman D, Lindström ML, Möller M, Ivarsson S, Kristoffersson AC, Bekassy Z, Fogo AB, Elfving M. Hypoaldosteronism due to a novel SEC61A1 variant successfully treated with fludrocortisone. Clin Kidney J 2024; 17:sfae213. [PMID: 39135939 PMCID: PMC11317836 DOI: 10.1093/ckj/sfae213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Indexed: 08/15/2024] Open
Abstract
Background Genetic variants in SEC61A1 are associated with autosomal dominant tubulointerstitial kidney disease. SEC61A1 is a translocon in the endoplasmic reticulum membrane and variants affect biosynthesis of renin and uromodulin. Methods A patient is described that presented at 1 year of age with failure-to-thrive, kidney failure (glomerular filtration rate, GFR, 18 ml/min/1.73m2), hyperkalemia and acidosis. Genetic evaluation was performed by whole genome sequencing. Results The patient has a novel de novo heterozygous SEC61A1 variant, Phe458Val. Plasma renin was low or normal, aldosterone was low or undetectable and uromodulin was low. Kidney biopsy at 2 years exhibited subtle changes suggestive of tubular dysgenesis without tubulocystic or glomerulocystic lesions and with renin staining of the juxtaglomerular cells. The patient experienced extreme fatigue due to severe hypotension attributed to hypoaldosteronism and at 8 years of age fludrocortisone treatment was initiated with marked improvement in her well-being. Blood pressure and potassium normalized. Biopsy at 9 years showed extensive glomerulosclerosis and mild tubulointerstitial fibrosis, as well as tubular mitochondrial abnormalities, without specific diagnostic changes. Her GFR improved to 54 ml/min/1.73m2. Conclusions As the renin-angiotensin system promotes aldosterone release, and the patient had repeatedly undetectable aldosterone levels, the SEC61A1 variant presumably contributed to severe hypotension. Treatment with a mineralocorticoid had a beneficial effect and corrected the electrolyte and acid-base disorder. We suggest that the increased blood pressure hemodynamically improved the patient's kidney function.
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Affiliation(s)
- Diana Karpman
- Department of Pediatrics, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Martin L Lindström
- Department of Pathology, Skåne University Hospital and Regional Laboratories, Malmö, Sweden
| | - Mattias Möller
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden
- Department of Clinical Genetics and Pathology, Region Skåne, Lund, Sweden
| | - Sofie Ivarsson
- Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden
- Department of Clinical Genetics and Pathology, Region Skåne, Lund, Sweden
| | | | - Zivile Bekassy
- Department of Pediatrics, Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Agnes B Fogo
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Maria Elfving
- Department of Pediatrics, Clinical Sciences Lund, Lund University, Lund, Sweden
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4
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Lysenkova Wiklander M, Arvidsson G, Bunikis I, Lundmark A, Raine A, Marincevic-Zuniga Y, Gezelius H, Bremer A, Feuk L, Ameur A, Nordlund J. A multiomic characterization of the leukemia cell line REH using short- and long-read sequencing. Life Sci Alliance 2024; 7:e202302481. [PMID: 38777370 PMCID: PMC11111970 DOI: 10.26508/lsa.202302481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 05/02/2024] [Accepted: 05/02/2024] [Indexed: 05/25/2024] Open
Abstract
The B-cell acute lymphoblastic leukemia (ALL) cell line REH, with the t(12;21) ETV6::RUNX1 translocation, is known to have a complex karyotype defined by a series of large-scale chromosomal rearrangements. Taken from a 15-yr-old at relapse, the cell line offers a practical model for the study of pediatric B-ALL. In recent years, short- and long-read DNA and RNA sequencing have emerged as a complement to karyotyping techniques in the resolution of structural variants in an oncological context. Here, we explore the integration of long-read PacBio and Oxford Nanopore whole-genome sequencing, IsoSeq RNA sequencing, and short-read Illumina sequencing to create a detailed genomic and transcriptomic characterization of the REH cell line. Whole-genome sequencing clarified the molecular traits of disrupted ALL-associated genes including CDKN2A, PAX5, BTG1, VPREB1, and TBL1XR1, as well as the glucocorticoid receptor NR3C1 Meanwhile, transcriptome sequencing identified seven fusion genes within the genomic breakpoints. Together, our extensive whole-genome investigation makes high-quality open-source data available to the leukemia genomics community.
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Affiliation(s)
- Mariya Lysenkova Wiklander
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- SciLifeLab, Uppsala University, Uppsala, Sweden
| | - Gustav Arvidsson
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- SciLifeLab, Uppsala University, Uppsala, Sweden
| | - Ignas Bunikis
- SciLifeLab, Uppsala University, Uppsala, Sweden
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- National Genomics Infrastructure, Uppsala University, Uppsala, Sweden
| | - Anders Lundmark
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- SciLifeLab, Uppsala University, Uppsala, Sweden
| | - Amanda Raine
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- SciLifeLab, Uppsala University, Uppsala, Sweden
- National Genomics Infrastructure, Uppsala University, Uppsala, Sweden
| | - Yanara Marincevic-Zuniga
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- SciLifeLab, Uppsala University, Uppsala, Sweden
- National Genomics Infrastructure, Uppsala University, Uppsala, Sweden
| | - Henrik Gezelius
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- SciLifeLab, Uppsala University, Uppsala, Sweden
- National Genomics Infrastructure, Uppsala University, Uppsala, Sweden
| | - Anna Bremer
- SciLifeLab, Uppsala University, Uppsala, Sweden
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- Department of Clinical Genetics, Uppsala University Hospital, Uppsala, Sweden
| | - Lars Feuk
- SciLifeLab, Uppsala University, Uppsala, Sweden
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- National Genomics Infrastructure, Uppsala University, Uppsala, Sweden
| | - Adam Ameur
- SciLifeLab, Uppsala University, Uppsala, Sweden
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- National Genomics Infrastructure, Uppsala University, Uppsala, Sweden
| | - Jessica Nordlund
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- SciLifeLab, Uppsala University, Uppsala, Sweden
- National Genomics Infrastructure, Uppsala University, Uppsala, Sweden
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5
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Yuan T, Dong J, Jia B, Jiang H, Zhao Z, Zhou M. DTDHM: detection of tandem duplications based on hybrid methods using next-generation sequencing data. PeerJ 2024; 12:e17748. [PMID: 39076774 PMCID: PMC11285389 DOI: 10.7717/peerj.17748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 06/24/2024] [Indexed: 07/31/2024] Open
Abstract
Background Tandem duplication (TD) is a common and important type of structural variation in the human genome. TDs have been shown to play an essential role in many diseases, including cancer. However, it is difficult to accurately detect TDs due to the uneven distribution of reads and the inherent complexity of next-generation sequencing (NGS) data. Methods This article proposes a method called DTDHM (detection of tandem duplications based on hybrid methods), which utilizes NGS data to detect TDs in a single sample. DTDHM builds a pipeline that integrates read depth (RD), split read (SR), and paired-end mapping (PEM) signals. To solve the problem of uneven distribution of normal and abnormal samples, DTDHM uses the K-nearest neighbor (KNN) algorithm for multi-feature classification prediction. Then, the qualified split reads and discordant reads are extracted and analyzed to achieve accurate localization of variation sites. This article compares DTDHM with three other methods on 450 simulated datasets and five real datasets. Results In 450 simulated data samples, DTDHM consistently maintained the highest F1-score. The average F1-score of DTDHM, SVIM, TARDIS, and TIDDIT were 80.0%, 56.2%, 43.4%, and 67.1%, respectively. The F1-score of DTDHM had a small variation range and its detection effect was the most stable and 1.2 times that of the suboptimal method. Most of the boundary biases of DTDHM fluctuated around 20 bp, and its boundary deviation detection ability was better than TARDIS and TIDDIT. In real data experiments, five real sequencing samples (NA19238, NA19239, NA19240, HG00266, and NA12891) were used to test DTDHM. The results showed that DTDHM had the highest overlap density score (ODS) and F1-score of the four methods. Conclusions Compared with the other three methods, DTDHM achieved excellent results in terms of sensitivity, precision, F1-score, and boundary bias. These results indicate that DTDHM can be used as a reliable tool for detecting TDs from NGS data, especially in the case of low coverage depth and tumor purity samples.
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Affiliation(s)
- Tianting Yuan
- School of Computer Science and Technology, Liaocheng University, Liaocheng, China
| | - Jinxin Dong
- School of Computer Science and Technology, Liaocheng University, Liaocheng, China
| | - Baoxian Jia
- School of Computer Science and Technology, Liaocheng University, Liaocheng, China
| | - Hua Jiang
- School of Computer Science and Technology, Liaocheng University, Liaocheng, China
| | - Zuyao Zhao
- Orthopedics Department, Liaocheng People’s Hospital, Liaocheng, China
| | - Mengjiao Zhou
- School of Computer Science and Technology, Liaocheng University, Liaocheng, China
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Jugas R, Vitkova H. ProcaryaSV: structural variation detection pipeline for bacterial genomes using short-read sequencing. BMC Bioinformatics 2024; 25:233. [PMID: 38982375 PMCID: PMC11234778 DOI: 10.1186/s12859-024-05843-1] [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: 01/31/2024] [Accepted: 06/13/2024] [Indexed: 07/11/2024] Open
Abstract
BACKGROUND Structural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results. RESULTS We developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool. CONCLUSIONS The ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly available on GitHub at https://github.com/robinjugas/ProcaryaSV .
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Affiliation(s)
- Robin Jugas
- Department of Biomedical Engineering, Brno University of Technology, Brno, Czech Republic
| | - Helena Vitkova
- Department of Biomedical Engineering, Brno University of Technology, Brno, Czech Republic.
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7
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Schuy J, Sæther KB, Lisfeld J, Ek M, Grochowski CM, Lun MY, Hastie A, Rudolph S, Fuchs S, Neveling K, Hempel M, Hoischen A, Pettersson M, Carvalho CM, Eisfeldt J, Lindstrand A. A combination of long- and short-read genomics reveals frequent p-arm breakpoints within chromosome 21 complex genomic rearrangements. GENETICS IN MEDICINE OPEN 2024; 2:101863. [PMID: 39669604 PMCID: PMC11613786 DOI: 10.1016/j.gimo.2024.101863] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 06/18/2024] [Accepted: 06/20/2024] [Indexed: 12/14/2024]
Abstract
Purpose Although chromosome 21 is the smallest human chromosome, it is highly relevant in the pathogenicity of both cancer and congenital diseases, including Alzheimer disease and trisomy 21 (Down syndrome). In addition, cases with rare structural variants (SVs) of chromosome 21 have been reported. These events vary in size and include large chromosomal events, such as ring chromosomes and small partial aneuploidies. The p-arm of the acrocentric chromosome 21 was devoid of reference genomic sequence in GRCh37 and GRCh38, which hampered our ability to solve genomic rearrangements and find the mechanism of formation of disease-causing SVs. We hypothesize that conserved satellite structures and segmental duplications located on the p-arm play an important role in the formation of complex SVs involving chromosome 21. Methods Three cases with complex chromosome 21 rearrangements were studied with a combination of short-read and long-read genome sequencing, as well as optical genome mapping. The data were aligned to the T2T-CHM13 assembly. Results We were able to resolve all 3 complex chromosome 21 rearrangements in which 15, 8, and 26 breakpoints were identified, respectively. By comparing the identified SV breakpoints, we were able to pinpoint a region between 21p13 and 21p12 that appears to be frequently involved in chromosome 21 rearrangements. Importantly, we observed acrocentric satellite DNA at several breakpoint junctions suggesting an important role for those elements in the formation of complex SVs. Conclusion Taken together, our results provide further insights into the architecture and underlying mechanisms of complex rearrangements on acrocentric chromosomes.
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Affiliation(s)
- Jakob Schuy
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Kristine Bilgrav Sæther
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Jasmin Lisfeld
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marlene Ek
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Ming Yin Lun
- Pacific Northwest Research Institute, Seattle, WA
| | | | - Susanne Rudolph
- Gemeinschaftspraxis für Humangenetik und Genetische Labore, Hamburg, Germany
| | - Sigrid Fuchs
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kornelia Neveling
- Department of Human Genetics, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maja Hempel
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- University Heidelberg, Institute of Human Genetics, Heidelberg, Germany
| | - Alexander Hoischen
- Department of Human Genetics, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Internal Medicine, Radboud Expertise Center for Immunodeficiency and Autoinflammation and Radboud Center for Infectious Disease (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maria Pettersson
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
- Genomic Medicine Center Karolinska, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
- Genomic Medicine Center Karolinska, Karolinska University Hospital, Stockholm, Sweden
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8
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Hanssen F, Garcia MU, Folkersen L, Pedersen A, Lescai F, Jodoin S, Miller E, Seybold M, Wacker O, Smith N, Gabernet G, Nahnsen S. Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery. NAR Genom Bioinform 2024; 6:lqae031. [PMID: 38666213 PMCID: PMC11044436 DOI: 10.1093/nargab/lqae031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 03/23/2024] [Indexed: 04/28/2024] Open
Abstract
DNA variation analysis has become indispensable in many aspects of modern biomedicine, most prominently in the comparison of normal and tumor samples. Thousands of samples are collected in local sequencing efforts and public databases requiring highly scalable, portable, and automated workflows for streamlined processing. Here, we present nf-core/sarek 3, a well-established, comprehensive variant calling and annotation pipeline for germline and somatic samples. It is suitable for any genome with a known reference. We present a full rewrite of the original pipeline showing a significant reduction of storage requirements by using the CRAM format and runtime by increasing intra-sample parallelization. Both are leading to a 70% cost reduction in commercial clouds enabling users to do large-scale and cross-platform data analysis while keeping costs and CO2 emissions low. The code is available at https://nf-co.re/sarek.
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Affiliation(s)
- Friederike Hanssen
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
- Department of Computer Science, Eberhard-Karls University of Tübingen, 72076 Baden-Württemberg, Germany
- M3 Research Center, University Hospital, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
- Cluster of Excellence iFIT (EXC 2180) ‘Image-Guided and Functionally Instructed Tumor Therapies’, Eberhard-Karls University of Tübingen, Tübingen 72076, Baden-Württemberg, Germany
| | - Maxime U Garcia
- Seqera Labs, Carrer de Marià Aguilò, 28, Barcelona 08005, Spain
- Barntumörbanken, Department of Oncology-Pathology, Karolinska Institutet, BioClinicum, Visionsgatan 4, Solna 17164, Sweden
- National Genomics Infrastructure, SciLifeLab, SciLifeLab, Tomtebodavägen 23, Solna 17165, Sweden
| | | | | | - Francesco Lescai
- Department of Biology and Biotechnology ”L. Spallanzani”, University of Pavia, via Ferrata, 9, Pavia, 27100 PV, Italy
| | - Susanne Jodoin
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
- M3 Research Center, University Hospital, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
| | - Edmund Miller
- Department of Biological Sciences and Center for Systems Biology, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX 75080, USA
| | - Matthias Seybold
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
| | - Oskar Wacker
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
- M3 Research Center, University Hospital, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
| | - Nicholas Smith
- Department of Informatics, Technical University of Munich, Boltzmannstr. 3, Garching, 85748 Bavaria, Germany
| | - Gisela Gabernet
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
- Department of Pathology, Yale School of Medicine, 300 George, New Haven, CT 06510, USA
| | - Sven Nahnsen
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
- Department of Computer Science, Eberhard-Karls University of Tübingen, 72076 Baden-Württemberg, Germany
- M3 Research Center, University Hospital, Otfried-Müller Str. 37, Tübingen 72076, Baden-Württemberg, Germany
- Cluster of Excellence iFIT (EXC 2180) ‘Image-Guided and Functionally Instructed Tumor Therapies’, Eberhard-Karls University of Tübingen, Tübingen 72076, Baden-Württemberg, Germany
- Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard-Karls University of Tübingen, Tübingen 72076, Baden-Württemberg, Germany
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9
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Bilgrav Saether K, Eisfeldt J, Bengtsson J, Lun MY, Grochowski CM, Mahmoud M, Chao HT, Rosenfeld JA, Liu P, Schuy J, Ameur A, Hwang JP, Sedlazeck FJ, Bi W, Marom R, Nordgren A, Carvalho CMB, Lindstrand A. Mind the gap: the relevance of the genome reference to resolve rare and pathogenic inversions. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.22.24305780. [PMID: 38712270 PMCID: PMC11071548 DOI: 10.1101/2024.04.22.24305780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Both long-read genome sequencing (lrGS) and the recently published Telomere to Telomere (T2T) reference genome provide increased coverage and resolution across repetitive regions promising heightened structural variant detection and improved mapping. Inversions (INV), intrachromosomal segments which are rotated 180° and inserted back into the same chromosome, are a class of structural variants particularly challenging to detect due to their copy-number neutral state and association with repetitive regions. Inversions represent about 1/20 of all balanced structural chromosome aberrations and can lead to disease by gene disruption or altering regulatory regions of dosage sensitive genes in cis . Here we remapped the genome data from six individuals carrying unsolved cytogenetically detected inversions. An INV6 and INV10 were resolved using GRCh38 and T2T-CHM13. Finally, an INV9 required optical genome mapping, de novo assembly of lrGS data and T2T-CHM13. This inversion disrupted intron 25 of EHMT1, confirming a diagnosis of Kleefstra syndrome 1 (MIM#610253). These three inversions, only mappable in specific references, prompted us to investigate the presence and population frequencies of differential reference regions (DRRs) between T2T-CHM13, GRCh37, GRCh38, the chimpanzee and bonobo, and hundreds of megabases of DRRs were identified. Our results emphasize the significance of the chosen reference genome and the added benefits of lrGS and optical genome mapping in solving rearrangements in challenging regions of the genome. This is particularly important for inversions and may impact clinical diagnostics.
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10
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Dharanipragada P, Zhang X, Liu S, Lomeli SH, Hong A, Wang Y, Yang Z, Lo KZ, Vega-Crespo A, Ribas A, Moschos SJ, Moriceau G, Lo RS. Blocking Genomic Instability Prevents Acquired Resistance to MAPK Inhibitor Therapy in Melanoma. Cancer Discov 2023; 13:880-909. [PMID: 36700848 PMCID: PMC10068459 DOI: 10.1158/2159-8290.cd-22-0787] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 11/27/2022] [Accepted: 01/23/2023] [Indexed: 01/27/2023]
Abstract
Blocking cancer genomic instability may prevent tumor diversification and escape from therapies. We show that, after MAPK inhibitor (MAPKi) therapy in patients and mice bearing patient-derived xenografts (PDX), acquired resistant genomes of metastatic cutaneous melanoma specifically amplify resistance-driver, nonhomologous end-joining (NHEJ), and homologous recombination repair (HRR) genes via complex genomic rearrangements (CGR) and extrachromosomal DNAs (ecDNA). Almost all sensitive and acquired-resistant genomes harbor pervasive chromothriptic regions with disproportionately high mutational burdens and significant overlaps with ecDNA and CGR spans. Recurrently, somatic mutations within ecDNA and CGR amplicons enrich for HRR signatures, particularly within acquired resistant tumors. Regardless of sensitivity or resistance, breakpoint-junctional sequence analysis suggests NHEJ as critical to double-stranded DNA break repair underlying CGR and ecDNA formation. In human melanoma cell lines and PDXs, NHEJ targeting by a DNA-PKCS inhibitor prevents/delays acquired MAPKi resistance by reducing the size of ecDNAs and CGRs early on combination treatment. Thus, targeting the causes of genomic instability prevents acquired resistance. SIGNIFICANCE Acquired resistance often results in heterogeneous, redundant survival mechanisms, which challenge strategies aimed at reversing resistance. Acquired-resistant melanomas recurrently evolve resistance-driving and resistance-specific amplicons via ecDNAs and CGRs, thereby nominating chromothripsis-ecDNA-CGR biogenesis as a resistance-preventive target. Specifically, targeting DNA-PKCS/NHEJ prevents resistance by suppressing ecDNA/CGR rearrangements in MAPKi-treated melanomas. This article is highlighted in the In This Issue feature, p. 799.
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Affiliation(s)
- Prashanthi Dharanipragada
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Xiao Zhang
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Sixue Liu
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Shirley H. Lomeli
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Aayoung Hong
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Yan Wang
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Zhentao Yang
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Kara Z. Lo
- Division of Hematology/Oncology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Agustin Vega-Crespo
- Division of Hematology/Oncology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Antoni Ribas
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
- Division of Hematology/Oncology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
- Division of Surgical Oncology, Department of Surgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Stergios J. Moschos
- Division of Medical Oncology, Department of Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Gatien Moriceau
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - Roger S. Lo
- Division of Dermatology, Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
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11
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Hasegawa T, Kakuta M, Yamaguchi R, Sato N, Mikami T, Murashita K, Nakaji S, Itoh K, Imoto S. Impact of salivary and pancreatic amylase gene copy numbers on diabetes, obesity, and functional profiles of microbiome in Northern Japanese population. Sci Rep 2022; 12:7628. [PMID: 35538098 PMCID: PMC9090785 DOI: 10.1038/s41598-022-11730-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 04/18/2022] [Indexed: 11/25/2022] Open
Abstract
Amylase genes reside in a structurally complex locus, and their copy numbers vary greatly, and several studies have reported their association with obesity. The mechanism of this effect was partially explained by changes in the oral and gut microbiome compositions; however, a detailed mechanism has been unclarified. In this study, we showed their association with diabetes in addition to obesity, and further discovered a plausible mechanism of this association based on the function of commensal bacteria. First, we confirmed that the amylase copy number in the population tends to be larger than that reported in other studies and that there is a positive association between obesity and diabetes (p = 1.89E-2 and 8.63E-3). Second, we identified that relative abundance of some genus level microbiome, Capnocytophaga, Dialister, and previously reported bacteria, were significantly associated with amylase copy numbers. Finally, through functional gene-set analysis using shotgun sequencing, we observed that the abundance of genes in the Acarbose pathway in the gut microbiome was significantly decreased with an increase in the amylase copy number (p-value = 5.80E-4). Our findings can partly explain the mechanism underlying obesity and diabetes in populations with high amylase copy numbers.
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Affiliation(s)
- Takanori Hasegawa
- Health Intelligence Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan.
| | - Masanori Kakuta
- Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan
| | - Rui Yamaguchi
- Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan
| | - Noriaki Sato
- Department of Biomedical Data Intelligence, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Tatsuya Mikami
- Innovation Center for Health Promotion, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki, Aomori, 036-8562, Japan
| | - Koichi Murashita
- COI Research Initiatives Organization, Hirosaki University, 5 Zaifu-cho, Hirosaki, Aomori, Japan
| | - Shigeyuki Nakaji
- Department of Social Medicine, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki, Aomori, 036-8562, Japan
| | - Ken Itoh
- Department of Stress Response Science, Hirosaki University Graduate School of Medicine, 5 Zaifu-cho, Hirosaki, Aomori, 036-8562, Japan
| | - Seiya Imoto
- Health Intelligence Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan.
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12
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Maroilley T, Li X, Oldach M, Jean F, Stasiuk SJ, Tarailo-Graovac M. Deciphering complex genome rearrangements in C. elegans using short-read whole genome sequencing. Sci Rep 2021; 11:18258. [PMID: 34521941 PMCID: PMC8440550 DOI: 10.1038/s41598-021-97764-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 08/30/2021] [Indexed: 12/14/2022] Open
Abstract
Genomic rearrangements cause congenital disorders, cancer, and complex diseases in human. Yet, they are still understudied in rare diseases because their detection is challenging, despite the advent of whole genome sequencing (WGS) technologies. Short-read (srWGS) and long-read WGS approaches are regularly compared, and the latter is commonly recommended in studies focusing on genomic rearrangements. However, srWGS is currently the most economical, accurate, and widely supported technology. In Caenorhabditis elegans (C. elegans), such variants, induced by various mutagenesis processes, have been used for decades to balance large genomic regions by preventing chromosomal crossover events and allowing the maintenance of lethal mutations. Interestingly, those chromosomal rearrangements have rarely been characterized on a molecular level. To evaluate the ability of srWGS to detect various types of complex genomic rearrangements, we sequenced three balancer strains using short-read Illumina technology. As we experimentally validated the breakpoints uncovered by srWGS, we showed that, by combining several types of analyses, srWGS enables the detection of a reciprocal translocation (eT1), a free duplication (sDp3), a large deletion (sC4), and chromoanagenesis events. Thus, applying srWGS to decipher real complex genomic rearrangements in model organisms may help designing efficient bioinformatics pipelines with systematic detection of complex rearrangements in human genomes.
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Affiliation(s)
- Tatiana Maroilley
- Departments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Xiao Li
- Departments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Matthew Oldach
- Departments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Francesca Jean
- Departments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Susan J Stasiuk
- Departments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada
| | - Maja Tarailo-Graovac
- Departments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, T2N 4N1, Canada. .,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, AB, T2N 4N1, Canada.
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13
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Grochowski CM, Krepischi ACV, Eisfeldt J, Du H, Bertola DR, Oliveira D, Costa SS, Lupski JR, Lindstrand A, Carvalho CMB. Chromoanagenesis Event Underlies a de novo Pericentric and Multiple Paracentric Inversions in a Single Chromosome Causing Coffin-Siris Syndrome. Front Genet 2021; 12:708348. [PMID: 34512724 PMCID: PMC8427664 DOI: 10.3389/fgene.2021.708348] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 07/23/2021] [Indexed: 02/02/2023] Open
Abstract
Chromoanagenesis is a descriptive term that encompasses classes of catastrophic mutagenic processes that generate localized and complex chromosome rearrangements in both somatic and germline genomes. Herein, we describe a 5-year-old female presenting with a constellation of clinical features consistent with a clinical diagnosis of Coffin–Siris syndrome 1 (CSS1). Initial G-banded karyotyping detected a 90-Mb pericentric and a 47-Mb paracentric inversion on a single chromosome. Subsequent analysis of short-read whole-genome sequencing data and genomic optical mapping revealed additional inversions, all clustered on chromosome 6, one of them disrupting ARID1B for which haploinsufficiency leads to the CSS1 disease trait (MIM:135900). The aggregate structural variant data show that the resolved, the resolved derivative chromosome architecture presents four de novo inversions, one pericentric and three paracentric, involving six breakpoint junctions in what appears to be a shuffling of genomic material on this chromosome. Each junction was resolved to nucleotide-level resolution with mutational signatures suggestive of non-homologous end joining. The disruption of the gene ARID1B is shown to occur between the fourth and fifth exon of the canonical transcript with subsequent qPCR studies confirming a decrease in ARID1B expression in the patient versus healthy controls. Deciphering the underlying genomic architecture of chromosomal rearrangements and complex structural variants may require multiple technologies and can be critical to elucidating the molecular etiology of a patient’s clinical phenotype or resolving unsolved Mendelian disease cases.
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Affiliation(s)
- Christopher M Grochowski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
| | - Ana C V Krepischi
- Department of Genetics and Evolutionary Biology, Human Genome and Stem Cell Research Center, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Haowei Du
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
| | - Debora R Bertola
- Department of Genetics and Evolutionary Biology, Human Genome and Stem Cell Research Center, Institute of Biosciences, University of São Paulo, São Paulo, Brazil.,Clinical Genetics Unit, Instituto da Criança do Hospital das Clínicas, University of São Paulo, São Paulo, Brazil
| | - Danyllo Oliveira
- Department of Genetics and Evolutionary Biology, Human Genome and Stem Cell Research Center, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | - Silvia S Costa
- Department of Genetics and Evolutionary Biology, Human Genome and Stem Cell Research Center, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | - James R Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States.,Department of Pediatrics, Baylor College of Medicine, Houston, TX, United States.,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, United States.,Texas Children's Hospital, Houston, TX, United States
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Claudia M B Carvalho
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States.,Pacific Northwest Research Institute, Seattle, WA, United States
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14
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Abstract
Mycobacterium tuberculosis complex (MTBC) species are classic examples of genetically monomorphic microorganisms due to their low genetic variability. Whole-genome sequencing made it possible to describe both the main species within the complex and M. tuberculosis lineages and sublineages. This differentiation is based on single nucleotide polymorphisms (SNPs) and large sequence polymorphisms in the so-called regions of difference (RDs). Although a number of studies have been performed to elucidate RD localizations, their distribution among MTBC species, and their role in the bacterial life cycle, there are some inconsistencies and ambiguities in the localization of RDs in different members of the complex. To address this issue, we conducted a thorough search for all possible deletions in the WGS data collection comprising 721 samples representing the full MTBC diversity. Discovered deletions were compared with a list of all previously described RDs. As with the SNP-based analysis, we confirmed the specificities of 79 regions at the species, lineage, or sublineage level, 17 of which are described for the first time. We also present RDscan (https://github.com/dbespiatykh/RDscan), an open-source workflow, which detects deletions from short-read sequencing data and correlates the results with high-specificity RDs, curated in this study. Testing of the workflow on a collection comprising ∼7,000 samples showed a high specificity of the found RDs. This study provides novel details that can contribute to a better understanding of the species differentiation within the MTBC and can help to determine how individual clusters evolve within various MTBC species. IMPORTANCE Reductive genome evolution is one of the most important and intriguing adaptation strategies of different living organisms to their environment. Mycobacterium offers several notorious examples of either naturally reduced (Mycobacterium leprae) or laboratory-reduced (Mycobacterium bovis BCG) genomes. Mycobacterium tuberculosis complex has its phylogeny unambiguously framed by large sequence polymorphisms that present unidirectional unique event changes. In the present study, we curated all known regions of difference and analyzed both Mycobacterium tuberculosis and animal-adapted MTBC species. For 79 loci, we have shown a relationship with phylogenetic units, which can serve as a marker for diagnosing or studying biological effects. Moreover, intersections were found for some loci, which may indicate the nonrandomness of these processes and the involvement of these regions in the adaptation of bacteria to external conditions.
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15
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Gong T, Hayes VM, Chan EKF. Detection of somatic structural variants from short-read next-generation sequencing data. Brief Bioinform 2021; 22:bbaa056. [PMID: 32379294 PMCID: PMC8138798 DOI: 10.1093/bib/bbaa056] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Revised: 03/05/2020] [Accepted: 03/29/2020] [Indexed: 01/09/2023] Open
Abstract
Somatic structural variants (SVs), which are variants that typically impact >50 nucleotides, play a significant role in cancer development and evolution but are notoriously more difficult to detect than small variants from short-read next-generation sequencing (NGS) data. This is due to a combination of challenges attributed to the purity of tumour samples, tumour heterogeneity, limitations of short-read information from NGS and sequence alignment ambiguities. In spite of active development of SV detection tools (callers) over the past few years, each method has inherent advantages and limitations. In this review, we highlight some of the important factors affecting somatic SV detection and compared the performance of seven commonly used SV callers. In particular, we focus on the extent of change in sensitivity and precision for detecting different SV types and size ranges from samples with differing variant allele frequencies and sequencing depths of coverage. We highlight the reasons for why some SV callers perform well in some settings but not others, allowing our evaluation findings to be extended beyond the seven SV callers examined in this paper. As the importance of large SVs become increasingly recognized in cancer genomics, this paper provides a timely review on some of the most impactful factors influencing somatic SV detection that should be considered when choosing SV callers.
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Affiliation(s)
| | - Vanessa M Hayes
- Corresponding authors: Eva K.F. Chan, New South Wales Health Pathology, Newcastle, NSW 2300, Australia. E-mail: ; Vanessa M. Hayes, Garvan Institute of Medical Research, Sydney, NSW 2010, Australia. Tel.: +61-2-9355-5841; Fax: +61 2-2-9295-8151; E-mail:
| | - Eva K F Chan
- Corresponding authors: Eva K.F. Chan, New South Wales Health Pathology, Newcastle, NSW 2300, Australia. E-mail: ; Vanessa M. Hayes, Garvan Institute of Medical Research, Sydney, NSW 2010, Australia. Tel.: +61-2-9355-5841; Fax: +61 2-2-9295-8151; E-mail:
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16
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Stranneheim H, Lagerstedt-Robinson K, Magnusson M, Kvarnung M, Nilsson D, Lesko N, Engvall M, Anderlid BM, Arnell H, Johansson CB, Barbaro M, Björck E, Bruhn H, Eisfeldt J, Freyer C, Grigelioniene G, Gustavsson P, Hammarsjö A, Hellström-Pigg M, Iwarsson E, Jemt A, Laaksonen M, Enoksson SL, Malmgren H, Naess K, Nordenskjöld M, Oscarson M, Pettersson M, Rasi C, Rosenbaum A, Sahlin E, Sardh E, Stödberg T, Tesi B, Tham E, Thonberg H, Töhönen V, von Döbeln U, Vassiliou D, Vonlanthen S, Wikström AC, Wincent J, Winqvist O, Wredenberg A, Ygberg S, Zetterström RH, Marits P, Soller MJ, Nordgren A, Wirta V, Lindstrand A, Wedell A. Integration of whole genome sequencing into a healthcare setting: high diagnostic rates across multiple clinical entities in 3219 rare disease patients. Genome Med 2021; 13:40. [PMID: 33726816 PMCID: PMC7968334 DOI: 10.1186/s13073-021-00855-5] [Citation(s) in RCA: 152] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 02/11/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND We report the findings from 4437 individuals (3219 patients and 1218 relatives) who have been analyzed by whole genome sequencing (WGS) at the Genomic Medicine Center Karolinska-Rare Diseases (GMCK-RD) since mid-2015. GMCK-RD represents a long-term collaborative initiative between Karolinska University Hospital and Science for Life Laboratory to establish advanced, genomics-based diagnostics in the Stockholm healthcare setting. METHODS Our analysis covers detection and interpretation of SNVs, INDELs, uniparental disomy, CNVs, balanced structural variants, and short tandem repeat expansions. Visualization of results for clinical interpretation is carried out in Scout-a custom-developed decision support system. Results from both singleton (84%) and trio/family (16%) analyses are reported. Variant interpretation is done by 15 expert teams at the hospital involving staff from three clinics. For patients with complex phenotypes, data is shared between the teams. RESULTS Overall, 40% of the patients received a molecular diagnosis ranging from 19 to 54% for specific disease groups. There was heterogeneity regarding causative genes (n = 754) with some of the most common ones being COL2A1 (n = 12; skeletal dysplasia), SCN1A (n = 8; epilepsy), and TNFRSF13B (n = 4; inborn errors of immunity). Some causative variants were recurrent, including previously known founder mutations, some novel mutations, and recurrent de novo mutations. Overall, GMCK-RD has resulted in a large number of patients receiving specific molecular diagnoses. Furthermore, negative cases have been included in research studies that have resulted in the discovery of 17 published, novel disease-causing genes. To facilitate the discovery of new disease genes, GMCK-RD has joined international data sharing initiatives, including ClinVar, UDNI, Beacon, and MatchMaker Exchange. CONCLUSIONS Clinical WGS at GMCK-RD has provided molecular diagnoses to over 1200 individuals with a broad range of rare diseases. Consolidation and spread of this clinical-academic partnership will enable large-scale national collaboration.
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Affiliation(s)
- Henrik Stranneheim
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
- Science for Life Laboratory, Department of Microbiology, Tumour and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Kristina Lagerstedt-Robinson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Måns Magnusson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Department of Microbiology, Tumour and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Malin Kvarnung
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Daniel Nilsson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Nicole Lesko
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Martin Engvall
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Britt-Marie Anderlid
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Henrik Arnell
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | | | - Michela Barbaro
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Erik Björck
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Helene Bruhn
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Christoph Freyer
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Giedre Grigelioniene
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Peter Gustavsson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Hammarsjö
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Maritta Hellström-Pigg
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Erik Iwarsson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Anders Jemt
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Mikael Laaksonen
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institutet of Technology, Stockholm, Sweden
| | - Sara Lind Enoksson
- Department of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Helena Malmgren
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Karin Naess
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Magnus Nordenskjöld
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Mikael Oscarson
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Maria Pettersson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Chiara Rasi
- Science for Life Laboratory, Department of Microbiology, Tumour and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Adam Rosenbaum
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institutet of Technology, Stockholm, Sweden
| | - Ellika Sahlin
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Eliane Sardh
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Tommy Stödberg
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Bianca Tesi
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Emma Tham
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Håkan Thonberg
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Virpi Töhönen
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Ulrika von Döbeln
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Daphne Vassiliou
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Sofie Vonlanthen
- Department of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Ann-Charlotte Wikström
- Department of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Josephine Wincent
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Ola Winqvist
- Department of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Wredenberg
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Sofia Ygberg
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Rolf H Zetterström
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Per Marits
- Department of Clinical Immunology and Transfusion Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Maria Johansson Soller
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Valtteri Wirta
- Science for Life Laboratory, Department of Microbiology, Tumour and Cell Biology, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institutet of Technology, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.
| | - Anna Wedell
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.
- Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden.
- Science for Life Laboratory, Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.
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17
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Ethnic-specific association of amylase gene copy number with adiposity traits in a large Middle Eastern biobank. NPJ Genom Med 2021; 6:8. [PMID: 33563995 PMCID: PMC7873199 DOI: 10.1038/s41525-021-00170-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 12/24/2020] [Indexed: 02/07/2023] Open
Abstract
Studies assessing the impact of amylase genes copy number (CN) on adiposity report conflicting findings in different global populations, likely reflecting the impact of ancestral and ethnic-specific environment and lifestyle on selection at the amylase loci. Here, we leverage population size and detailed adiposity measures from a large population biobank to resolve confounding effects and determine the relationship between salivary (AMY1) and pancreatic (AMY2A) amylase genes CN and adiposity in 2935 Qatari individuals who underwent whole-genome sequencing (WGS) as part of the Qatar Genome Programme. We observe a negative association between AMY1 CNs and trunk fat percentage in the Qatari population (P = 7.50 × 10-3) and show that Qataris of Arab descent have significantly lower CN at AMY1 (P = 1.32 × 10-10) as well as less favorable adiposity and metabolic profiles (P < 1.34 × 10-8) than Qataris with Persian ancestry. Indeed, lower AMY1 CN was associated with increased total and trunk fat percentages in Arabs (P < 4.60 × 10-3) but not in Persians. Notably, overweight and obese Persians reported a significant trend towards dietary restraint following weight gain compared to Arabs (P = 4.29 × 10-5), with AMY1 CN showing negative association with dietary self-restraint (P = 3.22 × 10-3). This study reports an association between amylase gene CN and adiposity traits in a large Middle Eastern population. Importantly, we leverage rich biobank data to demonstrate that the strength of this association varies with ethnicity, and may be influenced by population-specific behaviors that also contribute to adiposity traits.
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18
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Eisfeldt J, Pettersson M, Petri A, Nilsson D, Feuk L, Lindstrand A. Hybrid sequencing resolves two germline ultra-complex chromosomal rearrangements consisting of 137 breakpoint junctions in a single carrier. Hum Genet 2020; 140:775-790. [PMID: 33315133 PMCID: PMC8052244 DOI: 10.1007/s00439-020-02242-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 11/18/2020] [Indexed: 12/16/2022]
Abstract
Chromoanagenesis is a genomic event responsible for the formation of complex structural chromosomal rearrangements (CCRs). Germline chromoanagenesis is rare and the majority of reported cases are associated with an affected phenotype. Here, we report a healthy female carrying two de novo CCRs involving chromosomes 4, 19, 21 and X and chromosomes 7 and 11, respectively, with a total of 137 breakpoint junctions (BPJs). We characterized the CCRs using a hybrid-sequencing approach, combining short-read sequencing, nanopore sequencing, and optical mapping. The results were validated using multiple cytogenetic methods, including fluorescence in situ hybridization, spectral karyotyping, and Sanger sequencing. We identified 137 BPJs, which to our knowledge is the highest number of reported breakpoint junctions in germline chromoanagenesis. We also performed a statistical assessment of the positioning of the breakpoints, revealing a significant enrichment of BPJ-affecting genes (96 intragenic BPJs, 26 genes, p < 0.0001), indicating that the CCRs formed during active transcription of these genes. In addition, we find that the DNA fragments are unevenly and non-randomly distributed across the derivative chromosomes indicating a multistep process of scattering and re-joining of DNA fragments. In summary, we report a new maximum number of BPJs (137) in germline chromoanagenesis. We also show that a hybrid sequencing approach is necessary for the correct characterization of complex CCRs. Through in-depth statistical assessment, it was found that the CCRs most likely was formed through an event resembling chromoplexy—a catastrophic event caused by erroneous transcription factor binding.
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Affiliation(s)
- Jesper Eisfeldt
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Karolinska University Hospital Solna, 171 76, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Maria Pettersson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Karolinska University Hospital Solna, 171 76, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Petri
- Science for Life Laboratory Uppsala, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Daniel Nilsson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Karolinska University Hospital Solna, 171 76, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Lars Feuk
- Science for Life Laboratory Uppsala, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Karolinska University Hospital Solna, 171 76, Stockholm, Sweden. .,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.
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19
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Subudhi PK, Garcia RS, Coronejo S, De Leon TB. A Novel Mutation of the NARROW LEAF 1 Gene Adversely Affects Plant Architecture in Rice ( Oryza sativa L.). Int J Mol Sci 2020; 21:ijms21218106. [PMID: 33143090 PMCID: PMC7672626 DOI: 10.3390/ijms21218106] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 09/25/2020] [Accepted: 10/26/2020] [Indexed: 11/17/2022] Open
Abstract
Plant architecture is critical for enhancing the adaptability and productivity of crop plants. Mutants with an altered plant architecture allow researchers to elucidate the genetic network and the underlying mechanisms. In this study, we characterized a novel nal1 rice mutant with short height, small panicle, and narrow and thick deep green leaves that was identified from a cross between a rice cultivar and a weedy rice accession. Bulked segregant analysis coupled with genome re-sequencing and cosegregation analysis revealed that the overall mutant phenotype was caused by a 1395-bp deletion spanning over the last two exons including the transcriptional end site of the nal1 gene. This deletion resulted in chimeric transcripts involving nal1 and the adjacent gene, which were validated by a reference-guided assembly of transcripts followed by PCR amplification. A comparative transcriptome analysis of the mutant and the wild-type rice revealed 263 differentially expressed genes involved in cell division, cell expansion, photosynthesis, reproduction, and gibberellin (GA) and brassinosteroids (BR) signaling pathways, suggesting the important regulatory role of nal1. Our study indicated that nal1 controls plant architecture through the regulation of genes involved in the photosynthetic apparatus, cell cycle, and GA and BR signaling pathways.
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Affiliation(s)
- Prasanta K. Subudhi
- School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA; (R.S.G.); (S.C.)
- Correspondence: ; Tel.: +1-225-578-1303
| | - Richard S. Garcia
- School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA; (R.S.G.); (S.C.)
| | - Sapphire Coronejo
- School of Plant, Environmental, and Soil Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA; (R.S.G.); (S.C.)
| | - Teresa B. De Leon
- California Cooperative Rice Research Foundation, Inc., Biggs, CA 95917, USA;
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20
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Pettersson M, Grochowski CM, Wincent J, Eisfeldt J, Breman AM, Cheung SW, Krepischi ACV, Rosenberg C, Lupski JR, Ottosson J, Lovmar L, Gacic J, Lundberg ES, Nilsson D, Carvalho CMB, Lindstrand A. Cytogenetically visible inversions are formed by multiple molecular mechanisms. Hum Mutat 2020; 41:1979-1998. [PMID: 32906200 PMCID: PMC7702065 DOI: 10.1002/humu.24106] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 08/10/2020] [Accepted: 08/28/2020] [Indexed: 01/25/2023]
Abstract
Cytogenetically detected inversions are generally assumed to be copy number and phenotypically neutral events. While nonallelic homologous recombination is thought to play a major role, recent data suggest the involvement of other molecular mechanisms in inversion formation. Using a combination of short-read whole-genome sequencing (WGS), 10X Genomics Chromium WGS, droplet digital polymerase chain reaction and array comparative genomic hybridization we investigated the genomic structure of 18 large unique cytogenetically detected chromosomal inversions and achieved nucleotide resolution of at least one chromosomal inversion junction for 13/18 (72%). Surprisingly, we observed that seemingly copy number neutral inversions can be accompanied by a copy-number gain of up to 350 kb and local genomic complexities (3/18, 17%). In the resolved inversions, the mutational signatures are consistent with nonhomologous end-joining (8/13, 62%) or microhomology-mediated break-induced replication (5/13, 38%). Our study indicates that short-read 30x coverage WGS can detect a substantial fraction of chromosomal inversions. Moreover, replication-based mechanisms are responsible for approximately 38% of those events leading to a significant proportion of inversions that are actually accompanied by additional copy-number variation potentially contributing to the overall phenotypic presentation of those patients.
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Affiliation(s)
- Maria Pettersson
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | | | - Josephine Wincent
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet, Solna, Sweden
| | - Amy M Breman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Sau W Cheung
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Ana C V Krepischi
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | - Carla Rosenberg
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil
| | - James R Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA.,Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA.,Department of Pediatrics, Texas Children's Hospital, Houston, Texas, USA
| | - Jesper Ottosson
- Department of Clinical Genetics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Lovisa Lovmar
- Department of Clinical Genetics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jelena Gacic
- Department of Clinical Genetics, Linköping University Hospital, Linköping, Sweden
| | - Elisabeth S Lundberg
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Daniel Nilsson
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet, Solna, Sweden
| | - Claudia M B Carvalho
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA.,Pacific Northwest Research Institute, Seattle, Washington, USA
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
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21
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Dong J, Qi M, Wang S, Yuan X. DINTD: Detection and Inference of Tandem Duplications From Short Sequencing Reads. Front Genet 2020; 11:924. [PMID: 32849857 PMCID: PMC7433346 DOI: 10.3389/fgene.2020.00924] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 07/24/2020] [Indexed: 11/21/2022] Open
Abstract
Tandem duplication (TD) is an important type of structural variation (SV) in the human genome and has biological significance for human cancer evolution and tumor genesis. Accurate and reliable detection of TDs plays an important role in advancing early detection, diagnosis, and treatment of disease. The advent of next-generation sequencing technologies has made it possible for the study of TDs. However, detection is still challenging due to the uneven distribution of reads and the uncertain amplitude of TD regions. In this paper, we present a new method, DINTD (Detection and INference of Tandem Duplications), to detect and infer TDs using short sequencing reads. The major principle of the proposed method is that it first extracts read depth and mapping quality signals, then uses the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm to find the possible TD regions. The total variation penalized least squares model is fitted with read depth and mapping quality signals to denoise signals. A 2D binary search tree is used to search the neighbor points effectively. To further identify the exact breakpoints of the TD regions, split-read signals are integrated into DINTD. The experimental results of DINTD on simulated data sets showed that DINTD can outperform other methods for sensitivity, precision, F1-score, and boundary bias. DINTD is further validated on real samples, and the experiment results indicate that it is consistent with other methods. This study indicates that DINTD can be used as an effective tool for detecting TDs.
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Affiliation(s)
- Jinxin Dong
- School of Computer Science and Technology, Xidian University, Xi'an, China.,School of Computer Science and Technology, Liaocheng University, Liaocheng, China
| | - Minyong Qi
- School of Computer Science and Technology, Xidian University, Xi'an, China.,School of Computer Science and Technology, Liaocheng University, Liaocheng, China
| | - Shaoqiang Wang
- School of Computer Science and Technology, Xidian University, Xi'an, China
| | - Xiguo Yuan
- School of Computer Science and Technology, Xidian University, Xi'an, China
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22
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Soylev A, Le TM, Amini H, Alkan C, Hormozdiari F. Discovery of tandem and interspersed segmental duplications using high-throughput sequencing. Bioinformatics 2020; 35:3923-3930. [PMID: 30937433 DOI: 10.1093/bioinformatics/btz237] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 01/20/2019] [Accepted: 03/29/2019] [Indexed: 01/01/2023] Open
Abstract
MOTIVATION Several algorithms have been developed that use high-throughput sequencing technology to characterize structural variations (SVs). Most of the existing approaches focus on detecting relatively simple types of SVs such as insertions, deletions and short inversions. In fact, complex SVs are of crucial importance and several have been associated with genomic disorders. To better understand the contribution of complex SVs to human disease, we need new algorithms to accurately discover and genotype such variants. Additionally, due to similar sequencing signatures, inverted duplications or gene conversion events that include inverted segmental duplications are often characterized as simple inversions, likewise, duplications and gene conversions in direct orientation may be called as simple deletions. Therefore, there is still a need for accurate algorithms to fully characterize complex SVs and thus improve calling accuracy of more simple variants. RESULTS We developed novel algorithms to accurately characterize tandem, direct and inverted interspersed segmental duplications using short read whole genome sequencing datasets. We integrated these methods to our TARDIS tool, which is now capable of detecting various types of SVs using multiple sequence signatures such as read pair, read depth and split read. We evaluated the prediction performance of our algorithms through several experiments using both simulated and real datasets. In the simulation experiments, using a 30× coverage TARDIS achieved 96% sensitivity with only 4% false discovery rate. For experiments that involve real data, we used two haploid genomes (CHM1 and CHM13) and one human genome (NA12878) from the Illumina Platinum Genomes set. Comparison of our results with orthogonal PacBio call sets from the same genomes revealed higher accuracy for TARDIS than state-of-the-art methods. Furthermore, we showed a surprisingly low false discovery rate of our approach for discovery of tandem, direct and inverted interspersed segmental duplications prediction on CHM1 (<5% for the top 50 predictions). AVAILABILITY AND IMPLEMENTATION TARDIS source code is available at https://github.com/BilkentCompGen/tardis, and a corresponding Docker image is available at https://hub.docker.com/r/alkanlab/tardis/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Arda Soylev
- Department of Computer Engineering, Bilkent University, Ankara.,Department of Computer Engineering, Konya Food and Agriculture University, Konya, Turkey
| | - Thong Minh Le
- UC-Davis Genome Center, University of California, Davis, CA, USA.,Department of Computer Science, University of California, Davis, CA, USA
| | - Hajar Amini
- Department of Neurology, School of Medicine, University of California, Davis, CA, USA
| | - Can Alkan
- Department of Computer Engineering, Bilkent University, Ankara.,Bilkent-Hacettepe Health Sciences and Technologies Program, Ankara, Turkey.,Department of Computer Science, ETH Zürich, Zurich, Switzerland
| | - Fereydoun Hormozdiari
- UC-Davis Genome Center, University of California, Davis, CA, USA.,Department of Biochemistry and Molecular Medicine, University of California, Davis, CA, USA.,MIND Institute, University of California, Davis, CA, USA
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23
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Klar J, Engstrand-Lilja H, Maqbool K, Mattisson J, Feuk L, Dahl N. Whole genome sequencing of familial isolated oesophagus atresia uncover shared structural variants. BMC Med Genomics 2020; 13:85. [PMID: 32586322 PMCID: PMC7318369 DOI: 10.1186/s12920-020-00737-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 06/08/2020] [Indexed: 12/15/2022] Open
Abstract
Background Oesophageal atresia (OA) is a life-threatening developmental defect characterized by a lost continuity between the upper and lower oesophagus. The most common form is a distal connection between the trachea and the oesophagus, i.e. a tracheoesophageal fistula (TEF). The condition may be part of a syndrome or occurs as an isolated feature. The recurrence risk in affected families is increased compared to the population-based incidence suggesting contributing genetic factors. Methods To gain insight into gene variants and genes associated with isolated OA we conducted whole genome sequencing on samples from three families with recurrent cases affected by congenital and isolated TEF. Results We identified a combination of single nucleotide variants (SNVs), splice site variants (SSV) and structural variants (SV) annotated to altogether 100 coding genes in the six affected individuals. Conclusion This study highlights rare SVs among candidate gene variants in our individuals with OA and provides a gene framework for further investigations of genetic factors behind this malformation.
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Affiliation(s)
- Joakim Klar
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden. .,Department of Women's and Children's Health, Section of Pediatric Surgery, Uppsala University, SE-75185, Uppsala, Sweden.
| | - Helene Engstrand-Lilja
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.,Department of Women's and Children's Health, Section of Pediatric Surgery, Uppsala University, SE-75185, Uppsala, Sweden
| | - Khurram Maqbool
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.,Department of Women's and Children's Health, Section of Pediatric Surgery, Uppsala University, SE-75185, Uppsala, Sweden
| | - Jonas Mattisson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.,Department of Women's and Children's Health, Section of Pediatric Surgery, Uppsala University, SE-75185, Uppsala, Sweden
| | - Lars Feuk
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.,Department of Women's and Children's Health, Section of Pediatric Surgery, Uppsala University, SE-75185, Uppsala, Sweden
| | - Niklas Dahl
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala, Sweden.,Department of Women's and Children's Health, Section of Pediatric Surgery, Uppsala University, SE-75185, Uppsala, Sweden
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24
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Saba KH, Cornmark L, Hofvander J, Magnusson L, Nilsson J, van den Bos H, Spierings DC, Foijer F, Staaf J, Brosjö O, Sumathi VP, Lam SW, Szuhai K, Bovée JV, Kovac M, Baumhoer D, Styring E, Nord KH. Loss of NF2 defines a genetic subgroup of non-FOS-rearranged osteoblastoma. JOURNAL OF PATHOLOGY CLINICAL RESEARCH 2020; 6:231-237. [PMID: 32542935 PMCID: PMC7578308 DOI: 10.1002/cjp2.172] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 05/05/2020] [Accepted: 05/11/2020] [Indexed: 12/18/2022]
Abstract
Osteoblastoma is a locally aggressive tumour of bone. Until recently, its underlying genetic features were largely unknown. During the past two years, reports have demonstrated that acquired structural variations affect the transcription factor FOS in a high proportion of cases. These rearrangements modify the terminal exon of the gene and are believed to stabilise both the FOS transcript and the encoded protein, resulting in high expression levels. Here, we applied in‐depth genetic analyses to a series of 29 osteoblastomas, including five classified as epithelioid osteoblastoma. We found recurrent homozygous deletions of the NF2 gene in three of the five epithelioid cases and in one conventional osteoblastoma. These events were mutually exclusive from FOS mutations. Structural variations were determined by deep whole genome sequencing and the number of FOS‐rearranged cases was less than previously reported (10/23, 43%). One conventional osteoblastoma displayed a novel mechanism of FOS upregulation; bringing the entire FOS gene under the control of the WNT5A enhancer that is itself activated by FOS. Taken together, we show that NF2 loss characterises a subgroup of osteoblastomas, distinct from FOS‐rearranged cases. Both NF2 and FOS are involved in regulating bone homeostasis, thereby providing a mechanistic link to the excessive bone growth of osteoblastoma.
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Affiliation(s)
- Karim H Saba
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
| | - Louise Cornmark
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
| | - Jakob Hofvander
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
| | - Linda Magnusson
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
| | - Jenny Nilsson
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
| | - Hilda van den Bos
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Diana Cj Spierings
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Floris Foijer
- European Research Institute for the Biology of Ageing, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Johan Staaf
- Department of Clinical Sciences, Division of Oncology and Pathology, Lund University, Lund, Sweden
| | - Otte Brosjö
- Department of Orthopedics, Karolinska University Hospital, Stockholm, Sweden
| | - Vaiyapuri P Sumathi
- Department of Musculoskeletal Pathology, Royal Orthopaedic Hospital, Birmingham, UK
| | - Suk Wai Lam
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
| | - Karoly Szuhai
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, The Netherlands
| | - Judith Vmg Bovée
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
| | - Michal Kovac
- Bone Tumour Reference Centre at the Institute of Pathology, University Hospital and University of Basel, Basel, Switzerland
| | - Daniel Baumhoer
- Bone Tumour Reference Centre at the Institute of Pathology, University Hospital and University of Basel, Basel, Switzerland
| | - Emelie Styring
- Department of Orthopedics, Lund University, Skåne University Hospital, Lund, Sweden
| | - Karolin H Nord
- Department of Laboratory Medicine, Division of Clinical Genetics, Lund University, Lund, Sweden
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25
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Khalil AIS, Khyriem C, Chattopadhyay A, Sanyal A. Hierarchical discovery of large-scale and focal copy number alterations in low-coverage cancer genomes. BMC Bioinformatics 2020; 21:147. [PMID: 32299346 PMCID: PMC7160937 DOI: 10.1186/s12859-020-3480-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Accepted: 04/01/2020] [Indexed: 12/15/2022] Open
Abstract
Background Detection of DNA copy number alterations (CNAs) is critical to understand genetic diversity, genome evolution and pathological conditions such as cancer. Cancer genomes are plagued with widespread multi-level structural aberrations of chromosomes that pose challenges to discover CNAs of different length scales, and distinct biological origins and functions. Although several computational tools are available to identify CNAs using read depth (RD) signal, they fail to distinguish between large-scale and focal alterations due to inaccurate modeling of the RD signal of cancer genomes. Additionally, RD signal is affected by overdispersion-driven biases at low coverage, which significantly inflate false detection of CNA regions. Results We have developed CNAtra framework to hierarchically discover and classify ‘large-scale’ and ‘focal’ copy number gain/loss from a single whole-genome sequencing (WGS) sample. CNAtra first utilizes a multimodal-based distribution to estimate the copy number (CN) reference from the complex RD profile of the cancer genome. We implemented Savitzky-Golay smoothing filter and Modified Varri segmentation to capture the change points of the RD signal. We then developed a CN state-driven merging algorithm to identify the large segments with distinct copy numbers. Next, we identified focal alterations in each large segment using coverage-based thresholding to mitigate the adverse effects of signal variations. Using cancer cell lines and patient datasets, we confirmed CNAtra’s ability to detect and distinguish the segmental aneuploidies and focal alterations. We used realistic simulated data for benchmarking the performance of CNAtra against other single-sample detection tools, where we artificially introduced CNAs in the original cancer profiles. We found that CNAtra is superior in terms of precision, recall and f-measure. CNAtra shows the highest sensitivity of 93 and 97% for detecting large-scale and focal alterations respectively. Visual inspection of CNAs revealed that CNAtra is the most robust detection tool for low-coverage cancer data. Conclusions CNAtra is a single-sample CNA detection tool that provides an analytical and visualization framework for CNA profiling without relying on any reference control. It can detect chromosome-level segmental aneuploidies and high-confidence focal alterations, even from low-coverage data. CNAtra is an open-source software implemented in MATLAB®. It is freely available at https://github.com/AISKhalil/CNAtra.
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Affiliation(s)
- Ahmed Ibrahim Samir Khalil
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Costerwell Khyriem
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore
| | - Anupam Chattopadhyay
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.
| | - Amartya Sanyal
- School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore, 637551, Singapore.
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26
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pyCancerSig: subclassifying human cancer with comprehensive single nucleotide, structural and microsatellite mutational signature deconstruction from whole genome sequencing. BMC Bioinformatics 2020; 21:128. [PMID: 32245405 PMCID: PMC7118897 DOI: 10.1186/s12859-020-3451-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 03/10/2020] [Indexed: 12/28/2022] Open
Abstract
Background DNA damage accumulates over the course of cancer development. The often-substantial amount of somatic mutations in cancer poses a challenge to traditional methods to characterize tumors based on driver mutations. However, advances in machine learning technology can take advantage of this substantial amount of data. Results We developed a command line interface python package, pyCancerSig, to perform sample profiling by integrating single nucleotide variation (SNV), structural variation (SV) and microsatellite instability (MSI) profiles into a unified profile. It also provides a command to decipher underlying cancer processes, employing an unsupervised learning technique, Non-negative Matrix Factorization, and a command to visualize the results. The package accepts common standard file formats (vcf, bam). The program was evaluated using a cohort of breast- and colorectal cancer from The Cancer Genome Atlas project (TCGA). The result showed that by integrating multiple mutations modes, the tool can correctly identify cases with known clear mutational signatures and can strengthen signatures in cases with unclear signal from an SNV-only profile. The software package is available at https://github.com/jessada/pyCancerSig. Conclusions pyCancerSig has demonstrated its capability in identifying known and unknown cancer processes, and at the same time, illuminates the association within and between the mutation modes.
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27
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Andersson K, Malmgren B, Åström E, Nordgren A, Taylan F, Dahllöf G. Mutations in COL1A1/A2 and CREB3L1 are associated with oligodontia in osteogenesis imperfecta. Orphanet J Rare Dis 2020; 15:80. [PMID: 32234057 PMCID: PMC7110904 DOI: 10.1186/s13023-020-01361-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 03/17/2020] [Indexed: 02/07/2023] Open
Abstract
Background Osteogenesis imperfecta (OI) is a heterogeneous connective tissue disorder characterized by an increased tendency for fractures throughout life. Autosomal dominant (AD) mutations in COL1A1 and COL1A2 are causative in approximately 85% of cases. In recent years, recessive variants in genes involved in collagen processing have been found. Hypodontia (< 6 missing permanent teeth) and oligodontia (≥ 6 missing permanent teeth) have previously been reported in individuals with OI. The aim of the present cross-sectional study was to investigate whether children and adolescents with OI and oligodontia and hypodontia also present with variants in other genes with potential effects on tooth development. The cohort comprised 10 individuals (7.7–19.9 years of age) with known COL1A1/A2 variants who we clinically and radiographically examined and further genetically evaluated by whole-genome sequencing. All study participants were treated at the Astrid Lindgren Children’s Hospital at Karolinska University Hospital, Stockholm (Sweden’s national multidisciplinary pediatric OI team). We evaluated a panel of genes that were associated with nonsyndromic and syndromic hypodontia or oligodontia as well as that had been found to be involved in tooth development in animal models. Results We detected a homozygous nonsense variant in CREB3L1, p.Tyr428*, c.1284C > A in one boy previously diagnosed with OI type III. COL1A1 and COL1A2 were the only two genes among 9 individuals which carried a pathogenic mutation. We found rare variants with unknown significance in several other genes related to tooth development. Conclusions Our findings suggest that mutations in COL1A1, COL1A2, and CREB3L1 may cause hypodontia and oligodontia in OI. The findings cannot exclude additive effects from other modifying or interacting genes that may contribute to the severity of the expressed phenotype. Larger cohorts and further functional studies are needed.
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Affiliation(s)
- Kristofer Andersson
- Department of Dental Medicine, Division of Orthodontics and Pediatric Dentistry, Karolinska Institutet, POB 4064, SE-141 04, Huddinge, Sweden. .,Center for Pediatric Oral Health Research, Stockholm, Sweden.
| | - Barbro Malmgren
- Department of Dental Medicine, Division of Orthodontics and Pediatric Dentistry, Karolinska Institutet, POB 4064, SE-141 04, Huddinge, Sweden.,Center for Pediatric Oral Health Research, Stockholm, Sweden
| | - Eva Åström
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.,Pediatric Neurology, Astrid Lindgren Children's Hospital at Karolinska University Hospital, Stockholm, Sweden
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Fulya Taylan
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Göran Dahllöf
- Department of Dental Medicine, Division of Orthodontics and Pediatric Dentistry, Karolinska Institutet, POB 4064, SE-141 04, Huddinge, Sweden.,Center for Pediatric Oral Health Research, Stockholm, Sweden.,Center for Oral Health Services and Research, Mid-Norway, TkMidt, Trondheim, Norway
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28
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SVXplorer: Three-tier approach to identification of structural variants via sequential recombination of discordant cluster signatures. PLoS Comput Biol 2020; 16:e1007737. [PMID: 32182236 PMCID: PMC7100977 DOI: 10.1371/journal.pcbi.1007737] [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: 06/24/2019] [Revised: 03/27/2020] [Accepted: 02/18/2020] [Indexed: 11/19/2022] Open
Abstract
The identification of structural variants using short-read data remains challenging. Most approaches that use discordant paired-end sequences ignore non-trivial signatures presented by variants containing 3 breakpoints, such as those generated by various copy-paste and cut-paste mechanisms. This can result in lower precision and sensitivity in the identification of the more common structural variants such as deletions and duplications. We present SVXplorer, which uses a graph-based clustering approach streamlined by the integration of non-trivial signatures from discordant paired-end alignments, split-reads and read depth information to improve upon existing methods. We show that SVXplorer is more sensitive and precise compared to several existing approaches on multiple real and simulated datasets. SVXplorer is available for download at https://github.com/kunalkathuria/SVXplorer.
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29
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Plesser Duvdevani M, Pettersson M, Eisfeldt J, Avraham O, Dagan J, Frumkin A, Lupski JR, Lindstrand A, Harel T. Whole-genome sequencing reveals complex chromosome rearrangement disrupting NIPBL in infant with Cornelia de Lange syndrome. Am J Med Genet A 2020; 182:1143-1151. [PMID: 32125084 DOI: 10.1002/ajmg.a.61539] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 01/29/2020] [Accepted: 02/05/2020] [Indexed: 02/05/2023]
Abstract
Clinical laboratory diagnostic evaluation of the genomes of children with suspected genetic disorders, including chromosomal microarray and exome sequencing, cannot detect copy number neutral genomic rearrangements such as inversions, balanced translocations, and complex chromosomal rearrangements (CCRs). We describe an infant with a clinical diagnosis of Cornelia de Lange syndrome (CdLS) in whom chromosome analysis revealed a de novo complex balanced translocation, 46,XY,t(5;7;6)(q11.2;q32;q13)dn. Subsequent molecular characterization by whole-genome sequencing (WGS) identified 23 breakpoints, delineating segments derived from four chromosomes (5;6;7;21) in ancestral or inverted orientation. One of the breakpoints disrupted a known CdLS gene, NIPBL. Further investigation revealed paternal origin of the CCR allele, clustering of the breakpoint junctions, and molecular repair signatures suggestive of a single catastrophic event. Notably, very short DNA segments (25 and 41 bp) were included in the reassembled chromosomes, lending additional support that the DNA repair machinery can detect and repair such segments. Interestingly, there was an independent paternally derived miniscule complex rearrangement, possibly predisposing to subsequent genomic instability. In conclusion, we report a CCR causing a monogenic Mendelian disorder, urging WGS analysis of similar unsolved cases with suspected Mendelian disorders. Breakpoint analysis allowed for identification of the underlying molecular diagnosis and implicated chromoanagenesis in CCR formation.
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Affiliation(s)
- Morasha Plesser Duvdevani
- Department of Genetic and Metabolic Diseases, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Maria Pettersson
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
| | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Ortal Avraham
- Department of Genetic and Metabolic Diseases, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Judith Dagan
- Department of Genetic and Metabolic Diseases, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Ayala Frumkin
- Department of Genetic and Metabolic Diseases, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - James R Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Baylor College of Medicine, Houston, Texas, USA
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Tamar Harel
- Department of Genetic and Metabolic Diseases, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
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30
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Whole genome sequencing unveils genetic heterogeneity in optic nerve hypoplasia. PLoS One 2020; 15:e0228622. [PMID: 32040484 PMCID: PMC7010252 DOI: 10.1371/journal.pone.0228622] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 01/20/2020] [Indexed: 12/21/2022] Open
Abstract
Optic nerve hypoplasia (ONH) is a congenital malformation with a reduced number of retinal ganglion cell axons in a thin optic nerve. It is a common cause of visual impairment in children and ONH is associated with neurodevelopmental disorders, pituitary hormone deficiencies, and brain malformations. In most cases, the aetiology is unknown, but both environmental factors and genetic causes have been described. This study aimed to identify genetic variants underlying ONH in a well-characterised cohort of individuals with ONH. We performed array comparative genomic hybridization and whole genome sequencing in 29 individuals with ONH. Rare variants were verified by Sanger sequencing and inheritance was assessed in parental samples. We identified 11 rare single nucleotide variants (SNVs) in ten individuals, including a homozygous variant in KIF7 (previously associated with Joubert syndrome), a heterozygous de novo variant in COL4A1 (previously described in an individual with porencephaly), and a homozygous variant in COL4A2. In addition, one individual harboured a heterozygous variant in OPA1 and a heterozygous variant in COL4A1, both were inherited and assessed as variants of unknown clinical significance. Finally, a heterozygous deletion of 341 kb involving exons 7-18 of SOX5 (associated with Lamb-Schaffer syndrome) was identified in one individual. The overall diagnostic yield of pathogenic or likely pathogenic variants in individuals with ONH using whole genome sequencing was 4/29 (14%). Our results show that there is a genetic heterogeneity in ONH and indicate that genetic causes of ONH are not rare. We conclude that genetic testing is valuable in a substantial proportion of the individuals with ONH, especially in cases with non-isolated ONH.
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31
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Eisfeldt J, Mårtensson G, Ameur A, Nilsson D, Lindstrand A. Discovery of Novel Sequences in 1,000 Swedish Genomes. Mol Biol Evol 2020; 37:18-30. [PMID: 31560401 PMCID: PMC6984370 DOI: 10.1093/molbev/msz176] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Novel sequences (NSs), not present in the human reference genome, are abundant and remain largely unexplored. Here, we utilize de novo assembly to study NS in 1,000 Swedish individuals first sequenced as part of the SweGen project revealing a total of 46 Mb in 61,044 distinct contigs of sequences not present in GRCh38. The contigs were aligned to recently published catalogs of Icelandic and Pan-African NSs, as well as the chimpanzee genome, revealing a great diversity of shared sequences. Analyzing the positioning of NS across the chimpanzee genome, we find that 2,807 NS align confidently within 143 chimpanzee orthologs of human genes. Aligning the whole genome sequencing data to the chimpanzee genome, we discover ancestral NS common throughout the Swedish population. The NSs were searched for repeats and repeat elements: revealing a majority of repetitive sequence (56%), and enrichment of simple repeats (28%) and satellites (15%). Lastly, we align the unmappable reads of a subset of the thousand genomes data to our collection of NS, as well as the previously published Pan-African NS: revealing that both the Swedish and Pan-African NS are widespread, and that the Swedish NSs are largely a subset of the Pan-African NS. Overall, these results highlight the importance of creating a more diverse reference genome and illustrate that significant amounts of the NS may be of ancestral origin.
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Affiliation(s)
- Jesper Eisfeldt
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Gustaf Mårtensson
- Division of Nanobiotechnology, Department of Protein Science, Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Adam Ameur
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Daniel Nilsson
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
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32
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Garcia M, Juhos S, Larsson M, Olason PI, Martin M, Eisfeldt J, DiLorenzo S, Sandgren J, Díaz De Ståhl T, Ewels P, Wirta V, Nistér M, Käller M, Nystedt B. Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants. F1000Res 2020; 9:63. [PMID: 32269765 PMCID: PMC7111497 DOI: 10.12688/f1000research.16665.2] [Citation(s) in RCA: 117] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/03/2020] [Indexed: 12/13/2022] Open
Abstract
Whole-genome sequencing (WGS) is a fundamental technology for research to advance precision medicine, but the limited availability of portable and user-friendly workflows for WGS analyses poses a major challenge for many research groups and hampers scientific progress. Here we present Sarek, an open-source workflow to detect germline variants and somatic mutations based on sequencing data from WGS, whole-exome sequencing (WES), or gene panels. Sarek features (i) easy installation, (ii) robust portability across different computer environments, (iii) comprehensive documentation, (iv) transparent and easy-to-read code, and (v) extensive quality metrics reporting. Sarek is implemented in the Nextflow workflow language and supports both Docker and Singularity containers as well as Conda environments, making it ideal for easy deployment on any POSIX-compatible computers and cloud compute environments. Sarek follows the GATK best-practice recommendations for read alignment and pre-processing, and includes a wide range of software for the identification and annotation of germline and somatic single-nucleotide variants, insertion and deletion variants, structural variants, tumour sample purity, and variations in ploidy and copy number. Sarek offers easy, efficient, and reproducible WGS analyses, and can readily be used both as a production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups. The Sarek source code, documentation and installation instructions are freely available at
https://github.com/nf-core/sarek and at
https://nf-co.re/sarek/.
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Affiliation(s)
- Maxime Garcia
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden
| | - Szilveszter Juhos
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden.,Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Box 1031, Solna, 17121, Sweden.,Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, Uppsala, 752 37, Sweden
| | - Malin Larsson
- Department of Physics, Chemistry and Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Linköping University, Linköping, 58183, Sweden
| | - Pall I Olason
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, Uppsala, 752 37, Sweden
| | - Marcel Martin
- Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Box 1031, Solna, 17121, Sweden
| | - Jesper Eisfeldt
- Clinical Genetics, Department of Molecular Medicine and Surgery, Karolinska Institutet, MMK L1:00, Karolinska University Hospital at Solna, Stockholm, 171 76, Sweden
| | - Sebastian DiLorenzo
- Department of Medical Sciences, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, Uppsala, 752 37, Sweden
| | - Johanna Sandgren
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden
| | - Teresita Díaz De Ståhl
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden
| | - Philip Ewels
- Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Box 1031, Solna, 17121, Sweden
| | - Valtteri Wirta
- Department of Microbiology, Tumor and Cell Biology, Clinical Genomics Facility, Science for Life Laboratory, Karolinska Institutet, Box 1031, Solna, 171 21, Sweden
| | - Monica Nistér
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden
| | - Max Käller
- School of Engineering Sciences in Chemistry, Biotechnology and Health, Science for Life Laboratory, KTH Royal Institute of Technology, Box 1031, Solna, 17121, Sweden
| | - Björn Nystedt
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, Uppsala, 752 37, Sweden
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33
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Garcia M, Juhos S, Larsson M, Olason PI, Martin M, Eisfeldt J, DiLorenzo S, Sandgren J, Díaz De Ståhl T, Ewels P, Wirta V, Nistér M, Käller M, Nystedt B. Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants. F1000Res 2020; 9:63. [PMID: 32269765 PMCID: PMC7111497 DOI: 10.12688/f1000research.16665.1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/03/2020] [Indexed: 06/22/2024] Open
Abstract
Whole-genome sequencing (WGS) is a fundamental technology for research to advance precision medicine, but the limited availability of portable and user-friendly workflows for WGS analyses poses a major challenge for many research groups and hampers scientific progress. Here we present Sarek, an open-source workflow to detect germline variants and somatic mutations based on sequencing data from WGS, whole-exome sequencing (WES), or gene panels. Sarek features (i) easy installation, (ii) robust portability across different computer environments, (iii) comprehensive documentation, (iv) transparent and easy-to-read code, and (v) extensive quality metrics reporting. Sarek is implemented in the Nextflow workflow language and supports both Docker and Singularity containers as well as Conda environments, making it ideal for easy deployment on any POSIX-compatible computers and cloud compute environments. Sarek follows the GATK best-practice recommendations for read alignment and pre-processing, and includes a wide range of software for the identification and annotation of germline and somatic single-nucleotide variants, insertion and deletion variants, structural variants, tumour sample purity, and variations in ploidy and copy number. Sarek offers easy, efficient, and reproducible WGS analyses, and can readily be used both as a production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups. The Sarek source code, documentation and installation instructions are freely available at https://github.com/nf-core/sarek and at https://nf-co.re/sarek/.
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Affiliation(s)
- Maxime Garcia
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden
| | - Szilveszter Juhos
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden
- Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Box 1031, Solna, 17121, Sweden
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, Uppsala, 752 37, Sweden
| | - Malin Larsson
- Department of Physics, Chemistry and Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Linköping University, Linköping, 58183, Sweden
| | - Pall I. Olason
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, Uppsala, 752 37, Sweden
| | - Marcel Martin
- Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Box 1031, Solna, 17121, Sweden
| | - Jesper Eisfeldt
- Clinical Genetics, Department of Molecular Medicine and Surgery, Karolinska Institutet, MMK L1:00, Karolinska University Hospital at Solna, Stockholm, 171 76, Sweden
| | - Sebastian DiLorenzo
- Department of Medical Sciences, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, Uppsala, 752 37, Sweden
| | - Johanna Sandgren
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden
| | - Teresita Díaz De Ståhl
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden
| | - Philip Ewels
- Department of Biochemistry and Biophysics, Science for Life Laboratory, Stockholm University, Box 1031, Solna, 17121, Sweden
| | - Valtteri Wirta
- Department of Microbiology, Tumor and Cell Biology, Clinical Genomics Facility, Science for Life Laboratory, Karolinska Institutet, Box 1031, Solna, 171 21, Sweden
| | - Monica Nistér
- Department of Oncology-Pathology, Karolinska Institutet, J5:30 BioClinicum, Visionsgatan 4, Karolinska University Hospital at Solna, Solna, 17164, Sweden
| | - Max Käller
- School of Engineering Sciences in Chemistry, Biotechnology and Health, Science for Life Laboratory, KTH Royal Institute of Technology, Box 1031, Solna, 17121, Sweden
| | - Björn Nystedt
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Husargatan 3, Uppsala, 752 37, Sweden
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34
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Lindstrand A, Eisfeldt J, Pettersson M, Carvalho CMB, Kvarnung M, Grigelioniene G, Anderlid BM, Bjerin O, Gustavsson P, Hammarsjö A, Georgii-Hemming P, Iwarsson E, Johansson-Soller M, Lagerstedt-Robinson K, Lieden A, Magnusson M, Martin M, Malmgren H, Nordenskjöld M, Norling A, Sahlin E, Stranneheim H, Tham E, Wincent J, Ygberg S, Wedell A, Wirta V, Nordgren A, Lundin J, Nilsson D. From cytogenetics to cytogenomics: whole-genome sequencing as a first-line test comprehensively captures the diverse spectrum of disease-causing genetic variation underlying intellectual disability. Genome Med 2019; 11:68. [PMID: 31694722 PMCID: PMC6836550 DOI: 10.1186/s13073-019-0675-1] [Citation(s) in RCA: 100] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Accepted: 10/09/2019] [Indexed: 12/30/2022] Open
Abstract
Background Since different types of genetic variants, from single nucleotide variants (SNVs) to large chromosomal rearrangements, underlie intellectual disability, we evaluated the use of whole-genome sequencing (WGS) rather than chromosomal microarray analysis (CMA) as a first-line genetic diagnostic test. Methods We analyzed three cohorts with short-read WGS: (i) a retrospective cohort with validated copy number variants (CNVs) (cohort 1, n = 68), (ii) individuals referred for monogenic multi-gene panels (cohort 2, n = 156), and (iii) 100 prospective, consecutive cases referred to our center for CMA (cohort 3). Bioinformatic tools developed include FindSV, SVDB, Rhocall, Rhoviz, and vcf2cytosure. Results First, we validated our structural variant (SV)-calling pipeline on cohort 1, consisting of three trisomies and 79 deletions and duplications with a median size of 850 kb (min 500 bp, max 155 Mb). All variants were detected. Second, we utilized the same pipeline in cohort 2 and analyzed with monogenic WGS panels, increasing the diagnostic yield to 8%. Next, cohort 3 was analyzed by both CMA and WGS. The WGS data was processed for large (> 10 kb) SVs genome-wide and for exonic SVs and SNVs in a panel of 887 genes linked to intellectual disability as well as genes matched to patient-specific Human Phenotype Ontology (HPO) phenotypes. This yielded a total of 25 pathogenic variants (SNVs or SVs), of which 12 were detected by CMA as well. We also applied short tandem repeat (STR) expansion detection and discovered one pathologic expansion in ATXN7. Finally, a case of Prader-Willi syndrome with uniparental disomy (UPD) was validated in the WGS data. Important positional information was obtained in all cohorts. Remarkably, 7% of the analyzed cases harbored complex structural variants, as exemplified by a ring chromosome and two duplications found to be an insertional translocation and part of a cryptic unbalanced translocation, respectively. Conclusion The overall diagnostic rate of 27% was more than doubled compared to clinical microarray (12%). Using WGS, we detected a wide range of SVs with high accuracy. Since the WGS data also allowed for analysis of SNVs, UPD, and STRs, it represents a powerful comprehensive genetic test in a clinical diagnostic laboratory setting.
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Affiliation(s)
- Anna Lindstrand
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden. .,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden. .,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
| | - Jesper Eisfeldt
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden
| | - Maria Pettersson
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Claudia M B Carvalho
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Malin Kvarnung
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Giedre Grigelioniene
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Britt-Marie Anderlid
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Olof Bjerin
- The Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Peter Gustavsson
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Anna Hammarsjö
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Erik Iwarsson
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Maria Johansson-Soller
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Kristina Lagerstedt-Robinson
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Agne Lieden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Måns Magnusson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden.,Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Marcel Martin
- Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Stockholm, Sweden
| | - Helena Malmgren
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Magnus Nordenskjöld
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ameli Norling
- The Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - Ellika Sahlin
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Henrik Stranneheim
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Emma Tham
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Josephine Wincent
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Sofia Ygberg
- The Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.,Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Wedell
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Centre for Inherited Metabolic Diseases, Karolinska University Hospital, Stockholm, Sweden
| | - Valtteri Wirta
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, Sweden.,Science for Life Laboratory, Department of Microbiology, Tumor and Cell biology, Karolinska Institutet, Stockholm, Sweden
| | - Ann Nordgren
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Johanna Lundin
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA
| | - Daniel Nilsson
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden
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35
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Järviaho T, Bang B, Zachariadis V, Taylan F, Moilanen J, Möttönen M, Smith CIE, Harila-Saari A, Niinimäki R, Nordgren A. Predisposition to childhood acute lymphoblastic leukemia caused by a constitutional translocation disrupting ETV6. Blood Adv 2019; 3:2722-2731. [PMID: 31519648 PMCID: PMC6759729 DOI: 10.1182/bloodadvances.2018028795] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 06/17/2019] [Indexed: 12/31/2022] Open
Abstract
Pathogenic germline variants in ETV6 have been associated with familial predisposition to thrombocytopenia and hematological malignancies, predominantly childhood B-cell precursor acute lymphoblastic leukemia (BCP-ALL). In addition, overrepresentation of a high hyperdiploid subtype and older age at diagnosis have been reported among sporadic BCP-ALL cases with germline variants in ETV6 We studied a family with 2 second-degree relatives who developed childhood high hyperdiploid BCP-ALL at ages 8 and 12 years, respectively. A constitutional balanced reciprocal translocation t(12;14)(p13.2;q23.1) was discovered in both patients by routine karyotyping at diagnosis and, subsequently, in 7 healthy family members who had not experienced hematological malignancies. No carriers had thrombocytopenia. Whole-genome sequencing confirmed the translocation, resulting in 2 actively transcribed but nonfunctional fusion genes, causing heterozygous loss and consequently monoallelic expression of ETV6 Whole-genome sequencing analysis of the affected female subjects' leukemia excluded additional somatic aberrations in ETV6 and RTN1 as well as shared somatic variants in other genes. Expression studies, performed to confirm decreased expression of ETV6, were not conclusive. We suggest that germline aberrations resulting in monoallelic expression of ETV6 contribute to leukemia susceptibility, whereas more severe functional deficiency of ETV6 is required for developing THC5. To our knowledge, this report is the first of a constitutional translocation disrupting ETV6 causing predisposition to childhood ALL.
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Affiliation(s)
- Tekla Järviaho
- PEDEGO Research Unit, University of Oulu, Oulu, Finland
- Medical Research Center, University of Oulu and Oulu University Hospital, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Benedicte Bang
- Department of Molecular Medicine and Surgery, Center of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Vasilios Zachariadis
- Department of Molecular Medicine and Surgery, Center of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Fulya Taylan
- Department of Molecular Medicine and Surgery, Center of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jukka Moilanen
- PEDEGO Research Unit, University of Oulu, Oulu, Finland
- Medical Research Center, University of Oulu and Oulu University Hospital, Oulu, Finland
- Department of Clinical Genetics and
| | - Merja Möttönen
- PEDEGO Research Unit, University of Oulu, Oulu, Finland
- Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - C I Edvard Smith
- Clinical Research Center, Department of Laboratory Medicine, Karolinska Institutet, Huddinge, Sweden; and
| | - Arja Harila-Saari
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Riitta Niinimäki
- PEDEGO Research Unit, University of Oulu, Oulu, Finland
- Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
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36
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Kosugi S, Momozawa Y, Liu X, Terao C, Kubo M, Kamatani Y. Comprehensive evaluation of structural variation detection algorithms for whole genome sequencing. Genome Biol 2019; 20:117. [PMID: 31159850 PMCID: PMC6547561 DOI: 10.1186/s13059-019-1720-5] [Citation(s) in RCA: 283] [Impact Index Per Article: 47.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Accepted: 05/20/2019] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Structural variations (SVs) or copy number variations (CNVs) greatly impact the functions of the genes encoded in the genome and are responsible for diverse human diseases. Although a number of existing SV detection algorithms can detect many types of SVs using whole genome sequencing (WGS) data, no single algorithm can call every type of SVs with high precision and high recall. RESULTS We comprehensively evaluate the performance of 69 existing SV detection algorithms using multiple simulated and real WGS datasets. The results highlight a subset of algorithms that accurately call SVs depending on specific types and size ranges of the SVs and that accurately determine breakpoints, sizes, and genotypes of the SVs. We enumerate potential good algorithms for each SV category, among which GRIDSS, Lumpy, SVseq2, SoftSV, Manta, and Wham are better algorithms in deletion or duplication categories. To improve the accuracy of SV calling, we systematically evaluate the accuracy of overlapping calls between possible combinations of algorithms for every type and size range of SVs. The results demonstrate that both the precision and recall for overlapping calls vary depending on the combinations of specific algorithms rather than the combinations of methods used in the algorithms. CONCLUSION These results suggest that careful selection of the algorithms for each type and size range of SVs is required for accurate calling of SVs. The selection of specific pairs of algorithms for overlapping calls promises to effectively improve the SV detection accuracy.
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Affiliation(s)
- Shunichi Kosugi
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
| | - Xiaoxi Liu
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
| | - Chikashi Terao
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045 Japan
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37
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Comprehensive structural variation genome map of individuals carrying complex chromosomal rearrangements. PLoS Genet 2019; 15:e1007858. [PMID: 30735495 PMCID: PMC6368290 DOI: 10.1371/journal.pgen.1007858] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 11/28/2018] [Indexed: 11/19/2022] Open
Abstract
Complex chromosomal rearrangements (CCRs) are rearrangements involving more than two chromosomes or more than two breakpoints. Whole genome sequencing (WGS) allows for outstanding high resolution characterization on the nucleotide level in unique sequences of such rearrangements, but problems remain for mapping breakpoints in repetitive regions of the genome, which are known to be prone to rearrangements. Hence, multiple complementary WGS experiments are sometimes needed to solve the structures of CCRs. We have studied three individuals with CCRs: Case 1 and Case 2 presented with de novo karyotypically balanced, complex interchromosomal rearrangements (46,XX,t(2;8;15)(q35;q24.1;q22) and 46,XY,t(1;10;5)(q32;p12;q31)), and Case 3 presented with a de novo, extremely complex intrachromosomal rearrangement on chromosome 1. Molecular cytogenetic investigation revealed cryptic deletions in the breakpoints of chromosome 2 and 8 in Case 1, and on chromosome 10 in Case 2, explaining their clinical symptoms. In Case 3, 26 breakpoints were identified using WGS, disrupting five known disease genes. All rearrangements were subsequently analyzed using optical maps, linked-read WGS, and short-read WGS. In conclusion, we present a case series of three unique de novo CCRs where we by combining the results from the different technologies fully solved the structure of each rearrangement. The power in combining short-read WGS with long-molecule sequencing or optical mapping in these unique de novo CCRs in a clinical setting is demonstrated.
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38
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Nazaryan-Petersen L, Eisfeldt J, Pettersson M, Lundin J, Nilsson D, Wincent J, Lieden A, Lovmar L, Ottosson J, Gacic J, Mäkitie O, Nordgren A, Vezzi F, Wirta V, Käller M, Hjortshøj TD, Jespersgaard C, Houssari R, Pignata L, Bak M, Tommerup N, Lundberg ES, Tümer Z, Lindstrand A. Replicative and non-replicative mechanisms in the formation of clustered CNVs are indicated by whole genome characterization. PLoS Genet 2018; 14:e1007780. [PMID: 30419018 PMCID: PMC6258378 DOI: 10.1371/journal.pgen.1007780] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2018] [Revised: 11/26/2018] [Accepted: 10/23/2018] [Indexed: 01/25/2023] Open
Abstract
Clustered copy number variants (CNVs) as detected by chromosomal microarray analysis (CMA) are often reported as germline chromothripsis. However, such cases might need further investigations by massive parallel whole genome sequencing (WGS) in order to accurately define the underlying complex rearrangement, predict the occurrence mechanisms and identify additional complexities. Here, we utilized WGS to delineate the rearrangement structure of 21 clustered CNV carriers first investigated by CMA and identified a total of 83 breakpoint junctions (BPJs). The rearrangements were further sub-classified depending on the patterns observed: I) Cases with only deletions (n = 8) often had additional structural rearrangements, such as insertions and inversions typical to chromothripsis; II) cases with only duplications (n = 7) or III) combinations of deletions and duplications (n = 6) demonstrated mostly interspersed duplications and BPJs enriched with microhomology. In two cases the rearrangement mutational signatures indicated both a breakage-fusion-bridge cycle process and haltered formation of a ring chromosome. Finally, we observed two cases with Alu- and LINE-mediated rearrangements as well as two unrelated individuals with seemingly identical clustered CNVs on 2p25.3, possibly a rare European founder rearrangement. In conclusion, through detailed characterization of the derivative chromosomes we show that multiple mechanisms are likely involved in the formation of clustered CNVs and add further evidence for chromoanagenesis mechanisms in both “simple” and highly complex chromosomal rearrangements. Finally, WGS characterization adds positional information, important for a correct clinical interpretation and deciphering mechanisms involved in the formation of these rearrangements. Clustered copy number variants (CNVs) as detected by chromosomal microarray are often reported as germline chromoanagenesis. However, such cases might need further investigation by whole genome sequencing (WGS) to accurately resolve the complexity of the structural rearrangement and predict underlying mutational mechanisms. Here, we used WGS to characterize 83 breakpoint-junctions (BPJs) from 21 clustered CNVs, and outlined the rearrangement connectivity pictures. Cases with only deletions often had additional structural rearrangements, such as insertions and inversions, which could be a result of multiple double-strand DNA breaks followed by non-homologous repair, typical to chromothripsis. In contrast, cases with only duplications or combinations of deletions and duplications, demonstrated mostly interspersed duplications and BPJs enriched with microhomology, consistent with serial template switching during DNA replication (chromoanasynthesis). Only two rearrangements were repeat mediated. In aggregate, our results suggest that multiple CNVs clustered on a single chromosome may arise through either chromothripsis or chromoanasynthesis.
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Affiliation(s)
- Lusine Nazaryan-Petersen
- Wilhelm Johannsen Center for Functional Genome Research, Institute of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Maria Pettersson
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
| | - Johanna Lundin
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Daniel Nilsson
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Josephine Wincent
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Agne Lieden
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Lovisa Lovmar
- Department of Clinical Genetics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jesper Ottosson
- Department of Clinical Genetics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jelena Gacic
- Department of Clinical Genetics, Linköping University Hospital, Linköping, Sweden
| | - Outi Mäkitie
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
- Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Institute of Genetics, Helsinki, Finland
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Francesco Vezzi
- SciLifeLab, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Valtteri Wirta
- SciLifeLab, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, Sweden
- SciLifeLab, Department of Microbiology, Tumor and Cell biology, Karolinska Institutet, Stockholm, Sweden
| | - Max Käller
- SciLifeLab, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, Sweden
- SciLifeLab, Department of Microbiology, Tumor and Cell biology, Karolinska Institutet, Stockholm, Sweden
| | - Tina Duelund Hjortshøj
- Kennedy Center, Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, Glostrup, Denmark
| | - Cathrine Jespersgaard
- Kennedy Center, Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, Glostrup, Denmark
| | - Rayan Houssari
- Kennedy Center, Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, Glostrup, Denmark
| | - Laura Pignata
- Kennedy Center, Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, Glostrup, Denmark
| | - Mads Bak
- Wilhelm Johannsen Center for Functional Genome Research, Institute of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Niels Tommerup
- Wilhelm Johannsen Center for Functional Genome Research, Institute of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Elisabeth Syk Lundberg
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Zeynep Tümer
- Kennedy Center, Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
- * E-mail: (AL); (ZT)
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
- * E-mail: (AL); (ZT)
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Pettersson M, Eisfeldt J, Syk Lundberg E, Lundin J, Lindstrand A. Flanking complex copy number variants in the same family formed through unequal crossing-over during meiosis. Mutat Res 2018; 812:1-4. [PMID: 30384002 DOI: 10.1016/j.mrfmmm.2018.10.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Accepted: 10/08/2018] [Indexed: 05/22/2023]
Abstract
Two phenomena that have been described in germline complex genomic rearrangements (CGRs) formation are chromothripsis and chromoanasynthesis, characterized by distinct features such as the orientation and copy number of the involved fragments. Herein we present different CGRs on chromosome 5p in a mother and her daughter that through unequal crossing-over during meiosis has evolved from a chromothriptic rearrangement in the mother into another complex rearrangement in her daughter involving both deletions and duplications. Initially, both rearrangements were classified as simple copy number variants, but follow-up studies using whole-genome sequencing revealed a much more complex nature of both rearrangements and enabled us to decipher the biological process involved in the formation of the rearrangement found in the daughter. In conclusion, these two cases highlight the need of analyzing the inheritance patterns of CGRs, and provide an example of a disease-causing CGR formed through multiple genetic events.
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Affiliation(s)
- Maria Pettersson
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm and Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Elisabeth Syk Lundberg
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm and Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Johanna Lundin
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm and Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm and Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden.
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40
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Pettersson M, Vaz R, Hammarsjö A, Eisfeldt J, Carvalho CMB, Hofmeister W, Tham E, Horemuzova E, Voss U, Nishimura G, Klintberg B, Nordgren A, Nilsson D, Grigelioniene G, Lindstrand A. Alu-Alu mediated intragenic duplications in IFT81 and MATN3 are associated with skeletal dysplasias. Hum Mutat 2018; 39:1456-1467. [PMID: 30080953 DOI: 10.1002/humu.23605] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2018] [Revised: 07/09/2018] [Accepted: 08/02/2018] [Indexed: 01/22/2023]
Abstract
Skeletal dysplasias are a diverse group of rare Mendelian disorders with clinical and genetic heterogeneity. Here, we used targeted copy number variant (CNV) screening and identified intragenic exonic duplications, formed through Alu-Alu fusion events, in two individuals with skeletal dysplasia and negative exome sequencing results. First, we detected a homozygous tandem duplication of exon 9 and 10 in IFT81 in a boy with Jeune syndrome, or short-rib thoracic dysplasia (SRTD) (MIM# 208500). Western blot analysis did not detect any wild-type IFT81 protein in fibroblasts from the patient with the IFT81 duplication, but only a shorter isoform of IFT81 that was also present in the normal control samples. Complementary zebrafish studies suggested that loss of full-length IFT81 protein but expression of a shorter form of IFT81 protein affects the phenotype while being compatible with life. Second, a de novo tandem duplication of exons 2 to 5 in MATN3 was identified in a girl with multiple epiphyseal dysplasia (MED) type 5 (MIM# 607078). Our data highlights the importance of detection and careful characterization of intragenic duplication CNVs, presenting them as a novel and very rare genetic mechanism in IFT81-related Jeune syndrome and MATN3-related MED.
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Affiliation(s)
- Maria Pettersson
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet and Clinical Genetics, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Raquel Vaz
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Anna Hammarsjö
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet and Clinical Genetics, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Claudia M B Carvalho
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas
| | - Wolfgang Hofmeister
- Department of Molecular Medicine and Surgery and Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Emma Tham
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet and Clinical Genetics, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Eva Horemuzova
- Department of Women's and Children's Health, Karolinska Institutet and Paediatric Endocrinology Unit, Karolinska University Hospital, Stockholm, Sweden
| | - Ulrika Voss
- Department of Pediatric Radiology, Karolinska University Hospital, Stockholm, Sweden
| | - Gen Nishimura
- Intractable Disease Center, Saitama University Hospital, Saitama, Japan
| | - Bo Klintberg
- Department of Pediatrics, Visby Hospital, Visby, Sweden
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet and Clinical Genetics, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Daniel Nilsson
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet and Clinical Genetics, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Giedre Grigelioniene
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet and Clinical Genetics, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet and Clinical Genetics, Karolinska University Laboratory, Karolinska University Hospital, Stockholm, Sweden
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Tran AN, Taylan F, Zachariadis V, Ivanov Öfverholm I, Lindstrand A, Vezzi F, Lötstedt B, Nordenskjöld M, Nordgren A, Nilsson D, Barbany G. High-resolution detection of chromosomal rearrangements in leukemias through mate pair whole genome sequencing. PLoS One 2018. [PMID: 29529047 PMCID: PMC5846771 DOI: 10.1371/journal.pone.0193928] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
The detection of recurrent somatic chromosomal rearrangements is standard of care for most leukemia types. Even though karyotype analysis-a low-resolution genome-wide chromosome analysis-is still the gold standard, it often needs to be complemented with other methods to increase resolution. To evaluate the feasibility and applicability of mate pair whole genome sequencing (MP-WGS) to detect structural chromosomal rearrangements in the diagnostic setting, we sequenced ten bone marrow samples from leukemia patients with recurrent rearrangements. Samples were selected based on cytogenetic and FISH results at leukemia diagnosis to include common rearrangements of prognostic relevance. Using MP-WGS and in-house bioinformatic analysis all sought rearrangements were successfully detected. In addition, unexpected complexity or additional, previously undetected rearrangements was unraveled in three samples. Finally, the MP-WGS analysis pinpointed the location of chromosome junctions at high resolution and we were able to identify the exact exons involved in the resulting fusion genes in all samples and the specific junction at the nucleotide level in half of the samples. The results show that our approach combines the screening character from karyotype analysis with the specificity and resolution of cytogenetic and molecular methods. As a result of the straightforward analysis and high-resolution detection of clinically relevant rearrangements, we conclude that MP-WGS is a feasible method for routine leukemia diagnostics of structural chromosomal rearrangements.
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Affiliation(s)
- Anh Nhi Tran
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Laboratory Division Karolinska University Hospital, Clinical Genetics, Stockholm, Sweden
| | - Fulya Taylan
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Vasilios Zachariadis
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ingegerd Ivanov Öfverholm
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Laboratory Division Karolinska University Hospital, Clinical Genetics, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Laboratory Division Karolinska University Hospital, Clinical Genetics, Stockholm, Sweden
| | - Francesco Vezzi
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Britta Lötstedt
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Magnus Nordenskjöld
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Laboratory Division Karolinska University Hospital, Clinical Genetics, Stockholm, Sweden
| | - Ann Nordgren
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Laboratory Division Karolinska University Hospital, Clinical Genetics, Stockholm, Sweden
| | - Daniel Nilsson
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Gisela Barbany
- Department of Molecular Medicine and Surgery, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Laboratory Division Karolinska University Hospital, Clinical Genetics, Stockholm, Sweden
- * E-mail:
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Hofmeister W, Pettersson M, Kurtoglu D, Armenio M, Eisfeldt J, Papadogiannakis N, Gustavsson P, Lindstrand A. Targeted copy number screening highlights an intragenic deletion of WDR63 as the likely cause of human occipital encephalocele and abnormal CNS development in zebrafish. Hum Mutat 2018; 39:495-505. [PMID: 29285825 DOI: 10.1002/humu.23388] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2017] [Revised: 11/21/2017] [Accepted: 12/15/2017] [Indexed: 02/04/2023]
Abstract
Congenital malformations affecting the neural tube can present as isolated malformations or occur in association with other developmental abnormalities and syndromes. Using high-resolution copy number screening in 66 fetuses with neural tube defects, we identified six fetuses with likely pathogenic mutations, three aneuploidies (one trisomy 13 and two trisomy 18) and three deletions previously reported in NTDs (one 22q11.2 deletion and two 1p36 deletions) corresponding to 9% of the cohort. In addition, we identified five rare deletions and two duplications of uncertain significance including a rare intragenic heterozygous in-frame WDR63 deletion in a fetus with occipital encephalocele. Whole genome sequencing verified the deletion and excluded known pathogenic variants. The deletion spans exons 14-17 resulting in the expression of a protein missing the third and fourth WD-repeat domains. These findings were supported by CRISPR/Cas9-mediated somatic deletions in zebrafish. Injection of two different sgRNA-pairs targeting relevant intronic regions resulted in a deletion mimicking the human deletion and a concomitant increase of abnormal embryos with body and brain malformations (41%, n = 161 and 62%, n = 224, respectively), including a sac-like brain protrusion (7% and 9%, P < 0.01). Similar results were seen with overexpression of RNA encoding the deleted variant in zebrafish (total abnormal; 46%, n = 255, P < 0.001) compared with the overexpression of an equivalent amount of wild-type RNA (total abnormal; 3%, n = 177). We predict the in-frame WDR63 deletion to result in a dominant negative or gain-of-function form of WDR63. These are the first findings supporting a role for WDR63 in encephalocele formation.
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Affiliation(s)
- Wolfgang Hofmeister
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Centre of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Maria Pettersson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Centre of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Deniz Kurtoglu
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Centre of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Miriam Armenio
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Centre of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jesper Eisfeldt
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Centre of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Karolinska Institutet Science Park, Solna, Sweden
| | - Nikos Papadogiannakis
- Department of Laboratory Medicine, Division of Pathology, Karolinska Institutet, Huddinge, Sweden
| | - Peter Gustavsson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Centre of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Anna Lindstrand
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden.,Centre of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
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SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population. Eur J Hum Genet 2017; 25:1253-1260. [PMID: 28832569 PMCID: PMC5765326 DOI: 10.1038/ejhg.2017.130] [Citation(s) in RCA: 140] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2017] [Revised: 06/09/2017] [Accepted: 07/18/2017] [Indexed: 12/14/2022] Open
Abstract
Here we describe the SweGen data set, a comprehensive map of genetic variation in the Swedish population. These data represent a basic resource for clinical genetics laboratories as well as for sequencing-based association studies by providing information on genetic variant frequencies in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide cohort of over 10 000 Swedish-born individuals included in the Swedish Twin Registry. A total of 1000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole-genome sequencing. Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a genome-wide collection of aggregated variant frequencies in the Swedish population that we have made available to the scientific community through the website https://swefreq.nbis.se. A total of 29.2 million single-nucleotide variants and 3.8 million indels were detected in the 1000 samples, with 9.9 million of these variants not present in current databases. Each sample contributed with an average of 7199 individual-specific variants. In addition, an average of 8645 larger structural variants (SVs) were detected per individual, and we demonstrate that the population frequencies of these SVs can be used for efficient filtering analyses. Finally, our results show that the genetic diversity within Sweden is substantial compared with the diversity among continental European populations, underscoring the relevance of establishing a local reference data set.
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