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Zhang Z, Zhang J, Kang L, Qiu X, Xu S, Xu J, Guo Y, Niu Z, Niu B, Bi A, Zhao X, Xu D, Wang J, Yin C, Lu F. Structural variation discovery in wheat using PacBio high-fidelity sequencing. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2024; 120:687-698. [PMID: 39239888 DOI: 10.1111/tpj.17011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2024] [Revised: 08/09/2024] [Accepted: 08/22/2024] [Indexed: 09/07/2024]
Abstract
Structural variations (SVs) pervade plant genomes and contribute substantially to the phenotypic diversity. However, most SVs were ineffectively assayed due to their complex nature and the limitations of early genomic technologies. By applying the PacBio high-fidelity (HiFi) sequencing for wheat genomes, we performed a comprehensive evaluation of mainstream long-read aligners and SV callers in SV detection. The results indicated that the accuracy of deletion discovery is markedly influenced by callers, accounting for 87.73% of the variance, whereas both aligners (38.25%) and callers (49.32%) contributed substantially to the accuracy variance for insertions. Among the aligners, Winnowmap2 and NGMLR excelled in detecting deletions and insertions, respectively. For SV callers, SVIM achieved the best performance. We demonstrated that combining the aligners and callers mentioned above is optimal for SV detection. Furthermore, we evaluated the effect of sequencing depth on the accuracy of SV detection, revealing that low-coverage HiFi sequencing is sufficiently robust for high-quality SV discovery. This study thoroughly evaluated SV discovery approaches and established optimal workflows for investigating structural variations using low-coverage HiFi sequencing in the wheat genome, which will advance SV discovery and decipher the biological functions of SVs in wheat and many other plants.
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Affiliation(s)
- Zhiliang Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jijin Zhang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Lipeng Kang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xuebing Qiu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Song Xu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jun Xu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yafei Guo
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Zelin Niu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Beirui Niu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Aoyue Bi
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xuebo Zhao
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Daxing Xu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Jing Wang
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Changbin Yin
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
| | - Fei Lu
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- CAS-JIC Centre of Excellence for Plant and Microbial Science (CEPAMS), Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
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2
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Teboul L, Amos-Landgraf J, Benavides FJ, Birling MC, Brown SDM, Bryda E, Bunton-Stasyshyn R, Chin HJ, Crispo M, Delerue F, Dobbie M, Franklin CL, Fuchtbauer EM, Gao X, Golzio C, Haffner R, Hérault Y, Hrabe de Angelis M, Lloyd KCK, Magnuson TR, Montoliu L, Murray SA, Nam KH, Nutter LMJ, Pailhoux E, Pardo Manuel de Villena F, Peterson K, Reinholdt L, Sedlacek R, Seong JK, Shiroishi T, Smith C, Takeo T, Tinsley L, Vilotte JL, Warming S, Wells S, Whitelaw CB, Yoshiki A, Pavlovic G. Improving laboratory animal genetic reporting: LAG-R guidelines. Nat Commun 2024; 15:5574. [PMID: 38956430 PMCID: PMC11220107 DOI: 10.1038/s41467-024-49439-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 06/05/2024] [Indexed: 07/04/2024] Open
Abstract
The biomedical research community addresses reproducibility challenges in animal studies through standardized nomenclature, improved experimental design, transparent reporting, data sharing, and centralized repositories. The ARRIVE guidelines outline documentation standards for laboratory animals in experiments, but genetic information is often incomplete. To remedy this, we propose the Laboratory Animal Genetic Reporting (LAG-R) framework. LAG-R aims to document animals' genetic makeup in scientific publications, providing essential details for replication and appropriate model use. While verifying complete genetic compositions may be impractical, better reporting and validation efforts enhance reliability of research. LAG-R standardization will bolster reproducibility, peer review, and overall scientific rigor.
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Affiliation(s)
- Lydia Teboul
- The Mary Lyon Centre at MRC Harwell, Harwell Campus, Didcot, OX11 0RD, Oxon, UK.
| | - James Amos-Landgraf
- University of Missouri School of Medicine, Columbia, MO, USA
- University of Missouri College of Veterinary Medicine, Columbia, MO, USA
- Rat Resource and Research Center, University of Missouri, Columbia, MO, USA
| | - Fernando J Benavides
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Marie-Christine Birling
- PHENOMIN-Institut Clinique de la Souris, CELPHEDIA, CNRS, INSERM, Université de Strasbourg, Illkirch-Grafenstaden, 67404, Strasbourg, France
| | - Steve D M Brown
- Visiting Scientist, Institut Clinique de la Souris, Université de Strasbourg, Illkirch-Grafenstaden, 67404, Strasbourg, France
| | - Elizabeth Bryda
- Rat Resource and Research Center, University of Missouri, Columbia, MO, 65201, USA
| | | | - Hsian-Jean Chin
- National Laboratory Animal Center (NLAC), NARLabs, Taipei, Taiwan
| | - Martina Crispo
- Laboratory Animal Biotechnology Unit, Institut Pasteur de Montevideo, Mataojo 2020, CP 1400, Montevideo, Uruguay
| | - Fabien Delerue
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Michael Dobbie
- Phenomics Australia, Australian National University, 131 Garran Road, Canberra, ACT 2601, Australia
| | - Craig L Franklin
- University of Missouri Mutant Mouse Resource and Research Center (MU MMRRC), University of Missouri, Columbia, MO, 65201, USA
| | | | - Xiang Gao
- National Resource Center of Mutant Mice (NRCMM), Nanjing Biomedical Research Institute, Nanjing University, Nanjing, China
| | - Christelle Golzio
- Université de Strasbourg, CNRS, Inserm, IGBMC UMR 7104- UMR-S 1258, F-67400, Illkirch, France
| | - Rebecca Haffner
- Department Veterinary Resources, Weizmann Institute of Science, Rehovot, Israel
| | - Yann Hérault
- PHENOMIN-Institut Clinique de la Souris, CELPHEDIA, CNRS, INSERM, Université de Strasbourg, Illkirch-Grafenstaden, 67404, Strasbourg, France
- Université de Strasbourg, CNRS, Inserm, IGBMC UMR 7104- UMR-S 1258, F-67400, Illkirch, France
| | - Martin Hrabe de Angelis
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Chair of Experimental Genetics, TUM School of Life Sciences, Technische Universität München, Alte Akademie 8, 85354, Freising, Germany
- German Center for Diabetes Research (DZD), Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
| | | | - Terry R Magnuson
- Department of Genetics, and Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7264, USA
| | - Lluis Montoliu
- Department of Molecular and Cellular Biology, National Centre for Biotechnology (CNB-CSIC), 28049, Madrid, Spain
- Centre for Biomedical Network Research on Rare Diseases (CIBERER-ISCIII), 28029, Madrid, Spain
| | | | - Ki-Hoan Nam
- Laboratory Animal Resource Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Korea
| | - Lauryl M J Nutter
- Genetics and Genome Biology, The Hospital for Sick Children and The Centre for Phenogenomics, Toronto, ON, M5T 3H7, Canada
| | - Eric Pailhoux
- Université Paris-Saclay, UVSQ, INRAE, BREED, 78350, Jouy-en-Josas, France
| | - Fernando Pardo Manuel de Villena
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, 27599, USA
| | | | | | - Radislav Sedlacek
- Czech Centre for Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czech Republic
| | - Je Kyung Seong
- Laboratory of Developmental Biology and Genomics, BK21 PLUS Program for Creative Veterinary Science Research, Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University, and Korea Mouse Phenotyping Center, Seoul, 08826, Republic of Korea
| | | | - Cynthia Smith
- Mouse Genome Informatics (MGI), Jackson Laboratory, Bar Harbor, ME, USA
| | - Toru Takeo
- Center for Animal Resources and Development (CARD), Institute of Resource Development and Analysis, Kumamoto University, Kumamoto, Japan
| | - Louise Tinsley
- The Mary Lyon Centre at MRC Harwell, Harwell Campus, Didcot, OX11 0RD, Oxon, UK
| | - Jean-Luc Vilotte
- Université Paris-Saclay, INRAE, AgroParisTech, GABI, Jouy-en-Josas, France
| | - Søren Warming
- Genentech, Inc., a member of the Roche group, South San Francisco, CA, USA
| | - Sara Wells
- The Mary Lyon Centre at MRC Harwell, Harwell Campus, Didcot, OX11 0RD, Oxon, UK
- Francis Crick Institute, London, NW1 1AT, UK
| | - C Bruce Whitelaw
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush, EH25 9RG, UK
| | - Atsushi Yoshiki
- Experimental Animal Division, RIKEN BioResource Research Center, Tsukuba, Ibaraki, 305-0074, Japan
| | - Guillaume Pavlovic
- PHENOMIN-Institut Clinique de la Souris, CELPHEDIA, CNRS, INSERM, Université de Strasbourg, Illkirch-Grafenstaden, 67404, Strasbourg, France.
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3
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Liang H, Sedillo JC, Schrodi SJ, Ikeda A. Structural variants in linkage disequilibrium with GWAS-significant SNPs. Heliyon 2024; 10:e32053. [PMID: 38882374 PMCID: PMC11177133 DOI: 10.1016/j.heliyon.2024.e32053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 05/17/2024] [Accepted: 05/28/2024] [Indexed: 06/18/2024] Open
Abstract
With the recent expansion of structural variant identification in the human genome, understanding the role of these impactful variants in disease architecture is critically important. Currently, a large proportion of genome-wide-significant genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) are functionally unresolved, raising the possibility that some of these SNPs are associated with disease through linkage disequilibrium with causal structural variants. Hence, understanding the linkage disequilibrium between newly discovered structural variants and statistically significant SNPs may provide a resource for further investigation into disease-associated regions in the genome. Here we present a resource cataloging structural variant-significant SNP pairs in high linkage disequilibrium. The database is composed of (i) SNPs that have exhibited genome-wide significant association with traits, primarily disease phenotypes, (ii) newly released structural variants (SVs), and (iii) linkage disequilibrium values calculated from unphased data. All data files including those detailing SV and GWAS SNP associations and results of GWAS-SNP-SV pairs are available at the SV-SNP LD Database and can be accessed at 'https://github.com/hliang-SchrodiLab/SV_SNPs. Our analysis results represent a useful fine mapping tool for interrogating SVs in linkage disequilibrium with disease-associated SNPs. We anticipate that this resource may play an important role in subsequent studies which investigate incorporating disease causing SVs into disease risk prediction models.
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Affiliation(s)
- Hao Liang
- Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI, USA
| | - Joni C Sedillo
- Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI, USA
- Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Steven J Schrodi
- Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI, USA
- Computation and Informatics in Biology and Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Akihiro Ikeda
- Department of Medical Genetics, University of Wisconsin-Madison, Madison, WI, USA
- McPherson Eye Research Institute, University of Wisconsin-Madison, Madison, WI, USA
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4
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Nodari R, Arghittu M, Bailo P, Cattaneo C, Creti R, D’Aleo F, Saegeman V, Franceschetti L, Novati S, Fernández-Rodríguez A, Verzeletti A, Farina C, Bandi C. Forensic Microbiology: When, Where and How. Microorganisms 2024; 12:988. [PMID: 38792818 PMCID: PMC11123702 DOI: 10.3390/microorganisms12050988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 04/30/2024] [Accepted: 05/08/2024] [Indexed: 05/26/2024] Open
Abstract
Forensic microbiology is a relatively new discipline, born in part thanks to the development of advanced methodologies for the detection, identification and characterization of microorganisms, and also in relation to the growing impact of infectious diseases of iatrogenic origin. Indeed, the increased application of medical practices, such as transplants, which require immunosuppressive treatments, and the growing demand for prosthetic installations, associated with an increasing threat of antimicrobial resistance, have led to a rise in the number of infections of iatrogenic origin, which entails important medico-legal issues. On the other hand, the possibility of detecting minimal amounts of microorganisms, even in the form of residual traces (e.g., their nucleic acids), and of obtaining gene and genomic sequences at contained costs, has made it possible to ask new questions of whether cases of death or illness might have a microbiological origin, with the possibility of also tracing the origin of the microorganisms involved and reconstructing the chain of contagion. In addition to the more obvious applications, such as those mentioned above related to the origin of iatrogenic infections, or to possible cases of infections not properly diagnosed and treated, a less obvious application of forensic microbiology concerns its use in cases of violence or violent death, where the characterization of the microorganisms can contribute to the reconstruction of the case. Finally, paleomicrobiology, e.g., the reconstruction and characterization of microorganisms in historical or even archaeological remnants, can be considered as a sister discipline of forensic microbiology. In this article, we will review these different aspects and applications of forensic microbiology.
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Affiliation(s)
- Riccardo Nodari
- Department of Pharmacological and Biomolecular Sciences (DiSFeB), University of Milan, 20133 Milan, Italy
| | - Milena Arghittu
- Analysis Laboratory, ASST Melegnano e Martesana, 20077 Vizzolo Predabissi, Italy
| | - Paolo Bailo
- Section of Legal Medicine, School of Law, University of Camerino, 62032 Camerino, Italy
| | - Cristina Cattaneo
- LABANOF, Laboratory of Forensic Anthropology and Odontology, Section of Forensic Medicine, Department of Biomedical Sciences for Health, University of Milan, 20133 Milan, Italy
| | - Roberta Creti
- Antibiotic Resistance and Special Pathogens Unit, Department of Infectious Diseases, Istituto Superiore di Sanità, 00161 Rome, Italy
| | - Francesco D’Aleo
- Microbiology and Virology Laboratory, GOM—Grande Ospedale Metropolitano, 89124 Reggio Calabria, Italy
| | - Veroniek Saegeman
- Microbiology and Infection Control, Vitaz Hospital, 9100 Sint-Niklaas, Belgium
| | - Lorenzo Franceschetti
- LABANOF, Laboratory of Forensic Anthropology and Odontology, Section of Forensic Medicine, Department of Biomedical Sciences for Health, University of Milan, 20133 Milan, Italy
| | - Stefano Novati
- Department of Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, University of Pavia, 27100 Pavia, Italy
| | - Amparo Fernández-Rodríguez
- Microbiology Department, Biology Service, Instituto Nacional de Toxicología y Ciencias Forenses, 41009 Madrid, Spain
| | - Andrea Verzeletti
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health University of Brescia, 25123 Brescia, Italy
| | - Claudio Farina
- Microbiology and Virology Laboratory, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy
| | - Claudio Bandi
- Romeo ed Enrica Invernizzi Paediatric Research Centre, Department of Biosciences, University of Milan, 20133 Milan, Italy
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5
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Huang S, Shi W, Li S, Fan Q, Yang C, Cao J, Wu L. Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis. LAB ON A CHIP 2024; 24:2601-2621. [PMID: 38669201 DOI: 10.1039/d4lc00105b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
Cells are the fundamental building blocks of living systems, exhibiting significant heterogeneity. The transcriptome connects the cellular genotype and phenotype, and profiling single-cell transcriptomes is critical for uncovering distinct cell types, states, and the interplay between cells in development, health, and disease. Nevertheless, single-cell transcriptome analysis faces daunting challenges due to the low abundance and diverse nature of RNAs in individual cells, as well as their heterogeneous expression. The advent and continuous advancements of next-generation sequencing (NGS) and third-generation sequencing (TGS) technologies have solved these problems and facilitated the high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs. In this review, we provide a broad introduction to current methodologies for single-cell transcriptome sequencing. First, state-of-the-art advancements in high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms using NGS are reviewed. Next, TGS-based long-read scRNA-seq methods are summarized. Finally, a brief conclusion and perspectives for comprehensive single-cell transcriptome analysis are discussed.
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Affiliation(s)
- Shanqing Huang
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Weixiong Shi
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Shiyu Li
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Qian Fan
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
| | - Chaoyong Yang
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
- Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
| | - Jiao Cao
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
| | - Lingling Wu
- Institute of Molecular Medicine, Shanghai Key Laboratory for Nucleic Acid Chemistry and Nanomedicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
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6
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Gunasekaran D, Ardell DH, Nobile CJ. SNP-SVant: A Computational Workflow to Predict and Annotate Genomic Variants in Organisms Lacking Benchmarked Variants. Curr Protoc 2024; 4:e1046. [PMID: 38717471 PMCID: PMC11081530 DOI: 10.1002/cpz1.1046] [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] [Indexed: 05/12/2024]
Abstract
Whole-genome sequencing is widely used to investigate population genomic variation in organisms of interest. Assorted tools have been independently developed to call variants from short-read sequencing data aligned to a reference genome, including single nucleotide polymorphisms (SNPs) and structural variations (SVs). We developed SNP-SVant, an integrated, flexible, and computationally efficient bioinformatic workflow that predicts high-confidence SNPs and SVs in organisms without benchmarked variants, which are traditionally used for distinguishing sequencing errors from real variants. In the absence of these benchmarked datasets, we leverage multiple rounds of statistical recalibration to increase the precision of variant prediction. The SNP-SVant workflow is flexible, with user options to tradeoff accuracy for sensitivity. The workflow predicts SNPs and small insertions and deletions using the Genome Analysis ToolKit (GATK) and predicts SVs using the Genome Rearrangement IDentification Software Suite (GRIDSS), and it culminates in variant annotation using custom scripts. A key utility of SNP-SVant is its scalability. Variant calling is a computationally expensive procedure, and thus, SNP-SVant uses a workflow management system with intermediary checkpoint steps to ensure efficient use of resources by minimizing redundant computations and omitting steps where dependent files are available. SNP-SVant also provides metrics to assess the quality of called variants and converts between VCF and aligned FASTA format outputs to ensure compatibility with downstream tools to calculate selection statistics, which are commonplace in population genomics studies. By accounting for both small and large structural variants, users of this workflow can obtain a wide-ranging view of genomic alterations in an organism of interest. Overall, this workflow advances our capabilities in assessing the functional consequences of different types of genomic alterations, ultimately improving our ability to associate genotypes with phenotypes. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Predicting single nucleotide polymorphisms and structural variations Support Protocol 1: Downloading publicly available sequencing data Support Protocol 2: Visualizing variant loci using Integrated Genome Viewer Support Protocol 3: Converting between VCF and aligned FASTA formats.
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Affiliation(s)
- Deepika Gunasekaran
- Quantitative and Systems Biology Graduate Program, University of California, Merced, CA, USA
- Department of Molecular and Cell Biology, School of Natural Sciences, University of California, Merced, CA, USA
| | - David H. Ardell
- Department of Molecular and Cell Biology, School of Natural Sciences, University of California, Merced, CA, USA
| | - Clarissa J. Nobile
- Department of Molecular and Cell Biology, School of Natural Sciences, University of California, Merced, CA, USA
- Health Science Research Institute, University of California, Merced, CA, USA
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7
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Kwon D, Park N, Wy S, Lee D, Park W, Chai HH, Cho IC, Lee J, Kwon K, Kim H, Moon Y, Kim J, Kim J. Identification and characterization of structural variants related to meat quality in pigs using chromosome-level genome assemblies. BMC Genomics 2024; 25:299. [PMID: 38515031 PMCID: PMC10956321 DOI: 10.1186/s12864-024-10225-1] [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: 01/19/2024] [Accepted: 03/14/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Many studies have been performed to identify various genomic loci and genes associated with the meat quality in pigs. However, the full genetic architecture of the trait still remains unclear in part because of the lack of accurate identification of related structural variations (SVs) which resulted from the shortage of target breeds, the limitations of sequencing data, and the incompleteness of genome assemblies. The recent generation of a new pig breed with superior meat quality, called Nanchukmacdon, and its chromosome-level genome assembly (the NCMD assembly) has provided new opportunities. RESULTS By applying assembly-based SV calling approaches to various genome assemblies of pigs including Nanchukmacdon, the impact of SVs on meat quality was investigated. Especially, by checking the commonality of SVs with other pig breeds, a total of 13,819 Nanchukmacdon-specific SVs (NSVs) were identified, which have a potential effect on the unique meat quality of Nanchukmacdon. The regulatory potentials of NSVs for the expression of nearby genes were further examined using transcriptome- and epigenome-based analyses in different tissues. CONCLUSIONS Whole-genome comparisons based on chromosome-level genome assemblies have led to the discovery of SVs affecting meat quality in pigs, and their regulatory potentials were analyzed. The identified NSVs will provide new insights regarding genetic architectures underlying the meat quality in pigs. Finally, this study confirms the utility of chromosome-level genome assemblies and multi-omics analysis to enhance the understanding of unique phenotypes.
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Affiliation(s)
- Daehong Kwon
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Nayoung Park
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Suyeon Wy
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Daehwan Lee
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Woncheoul Park
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju, 55365, Republic of Korea
| | - Han-Ha Chai
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju, 55365, Republic of Korea
| | - In-Cheol Cho
- Subtropical Livestock Research Institute, National Institute of Animal Science, RDA, Jeju, 63242, Republic of Korea
| | - Jongin Lee
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Kisang Kwon
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Heesun Kim
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Youngbeen Moon
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Juyeon Kim
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Jaebum Kim
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea.
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8
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Tian L, Chen CJ, Song YN, Xu K, Li NE, Zhang XH, Xie Y, Jin ZB, Li Y. Comprehensive genetic analysis reveals the mutational landscape of ABCA4-associated retinal dystrophy in a Chinese cohort. Gene 2024; 891:147832. [PMID: 37774808 DOI: 10.1016/j.gene.2023.147832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Revised: 09/15/2023] [Accepted: 09/25/2023] [Indexed: 10/01/2023]
Abstract
PURPOSE To depict the variant profiles of the ABCA4 gene in a large Chinese cohort of patients with ABCA4-associated retinal dystrophy (ABCA4-RD). METHODS We recruited 290 unrelated Chinese patients with ABCA4-RD and did ABCA4 mutational screening by a combination of Sanger sequencing, targeted exome sequencing, entire ABCA4 locus sequencing, and whole genome sequencing (WGS). The pathogenicity of variants was assessed using in silico tools or in vitro splicing assays following the American College of Medical Genetics and Genomics guidelines. RESULTS Two hundred sixty-eight distinct pathogenic variants were identified, and 57 were novel. In 580 alleles, 22 noncoding region variants outside canonical splice sites and 4 structural variations were found in 44 alleles accounting for 7.6% of all alleles. Bioinformatics analysis showed the complex mechanism of aberrant splicing productsnatural splice site disruption, branch point destruction, and cryptic splice site activation. Correspondingly, minigene assays validated the various abnormal splicing products, including exon skipping, exon elongation, partial exon deletion, and pseudoexon insertion. WGS identified the first inversion variation in ABCA4. CONCLUSIONS This study systematically depicted the variant profiles of ABCA4 and revealed the missing alleles of patients with ABCA4-RD in a large Chinese cohort. Our findings demonstrated the complexity of molecular diagnosis of Mendelian diseases and the efficiency of WGS for detecting structural variants.
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Affiliation(s)
- Lu Tian
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing, China; Department of Ophthalmology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Chun-Jie Chen
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing, China
| | - Yu-Ning Song
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing, China
| | - Ke Xu
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing, China
| | - Ni-En Li
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing, China
| | - Xiao-Hui Zhang
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing, China
| | - Yue Xie
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing, China
| | - Zi-Bing Jin
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing, China
| | - Yang Li
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing Ophthalmology & Visual Sciences Key Lab, Beijing, China.
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9
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Yu SY, Xi YL, Xu FQ, Zhang J, Liu YS. Application of long read sequencing in rare diseases: The longer, the better? Eur J Med Genet 2023; 66:104871. [PMID: 38832911 DOI: 10.1016/j.ejmg.2023.104871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/11/2023] [Accepted: 10/22/2023] [Indexed: 06/06/2024]
Abstract
Rare diseases encompass a diverse group of genetic disorders that affect a small proportion of the population. Identifying the underlying genetic causes of these conditions presents significant challenges due to their genetic heterogeneity and complexity. Conventional short-read sequencing (SRS) techniques have been widely used in diagnosing and investigating of rare diseases, with limitations due to the nature of short-read lengths. In recent years, long read sequencing (LRS) technologies have emerged as a valuable tool in overcoming these limitations. This minireview provides a concise overview of the applications of LRS in rare disease research and diagnosis, including the identification of disease-causing tandem repeat expansions, structural variations, and comprehensive analysis of pathogenic variants with LRS.
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Affiliation(s)
- Si-Yan Yu
- Department of Pediatric Laboratory, Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi, Jiangsu, China; The First School of Clinical Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yu-Lin Xi
- Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, China
| | - Fu-Qiang Xu
- Department of Gynecology, Beijing Youan Hospital, Capital Medical University, Beijing, China
| | - Jian Zhang
- Department of Medical Laboratory, Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi, Jiangsu, China.
| | - Yan-Shan Liu
- Department of Pediatric Laboratory, Affiliated Children's Hospital of Jiangnan University (Wuxi Children's Hospital), Wuxi, Jiangsu, China; Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, China.
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10
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Gu J, Li S, Zhu B, Liang Q, Chen B, Tang X, Chen C, Wu DD, Li Y. Genetic variation and domestication of horses revealed by 10 chromosome-level genomes and whole-genome resequencing. Mol Ecol Resour 2023; 23:1656-1672. [PMID: 37259205 DOI: 10.1111/1755-0998.13818] [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: 11/03/2022] [Revised: 03/07/2023] [Accepted: 05/12/2023] [Indexed: 06/02/2023]
Abstract
Understanding the genetic variations of the horse (Equus caballus) genome will improve breeding conservation and welfare. However, genetic variations in long segments, such as structural variants (SVs), remain understudied. We de novo assembled 10 chromosome-level three-dimensional horse genomes, each representing a distinct breed, and analysed horse SVs using a multi-assembly approach. Our findings suggest that SVs with the accumulation of mammalian-wide interspersed repeats related to long interspersed nuclear elements might be a horse-specific mechanism to modulate genome-wide gene regulatory networks. We found that olfactory receptors were commonly loss and accumulated deleterious mutations, but no purge of deleterious mutations occurred during horse domestication. We examined the potential effects of SVs on the spatial structure of chromatin via topologically associating domains (TADs). Breed-specific TADs were significantly enriched by breed-specific SVs. We identified 4199 unique breakpoint-resolved novel insertions across all chromosomes that account for 2.84 Mb sequences missing from the reference genome. Several novel insertions might have potential functional consequences, as 519 appeared to reside within 449 gene bodies. These genes are primarily involved in pathogen recognition, innate immune responses and drug metabolism. Moreover, 37 diverse horses were resequenced. Combining this with public data, we analysed 97 horses through a comparative population genomics approach to identify the genetic basis underlying breed characteristics using Thoroughbreds as a case study. We provide new scientific evidence for horse domestication, an understanding of the genetic mechanism underlying the phenotypic evolution of horses, and a comprehensive genetic variation resource for further genetic studies of horses.
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Affiliation(s)
- Jingjing Gu
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, China
- Hunan Provincial Key Laboratory for Genetic Improvement of Domestic Animal, Changsha, China
| | - Sheng Li
- Maxun Biotechnology Institute, Changsha, China
| | - Bo Zhu
- Novogene Bioinformatics Institute, Beijing, China
| | - Qiqi Liang
- Key Laboratory of Pig Genetics and Breeding of Ministry of Agriculture & Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan, China
| | - Bin Chen
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, China
- Hunan Provincial Key Laboratory for Genetic Improvement of Domestic Animal, Changsha, China
| | - Xiangwei Tang
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, China
- Hunan Provincial Key Laboratory for Genetic Improvement of Domestic Animal, Changsha, China
| | - Chujie Chen
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, China
- Hunan Provincial Key Laboratory for Genetic Improvement of Domestic Animal, Changsha, China
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yan Li
- State Key Laboratory for Conservation and Utilization of Bio-Resource, Yunnan University, Kunming, China
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11
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Xia X, Zhang F, Li S, Luo X, Peng L, Dong Z, Pausch H, Leonard AS, Crysnanto D, Wang S, Tong B, Lenstra JA, Han J, Li F, Xu T, Gu L, Jin L, Dang R, Huang Y, Lan X, Ren G, Wang Y, Gao Y, Ma Z, Cheng H, Ma Y, Chen H, Pang W, Lei C, Chen N. Structural variation and introgression from wild populations in East Asian cattle genomes confer adaptation to local environment. Genome Biol 2023; 24:211. [PMID: 37723525 PMCID: PMC10507960 DOI: 10.1186/s13059-023-03052-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 09/07/2023] [Indexed: 09/20/2023] Open
Abstract
BACKGROUND Structural variations (SVs) in individual genomes are major determinants of complex traits, including adaptability to environmental variables. The Mongolian and Hainan cattle breeds in East Asia are of taurine and indicine origins that have evolved to adapt to cold and hot environments, respectively. However, few studies have investigated SVs in East Asian cattle genomes and their roles in environmental adaptation, and little is known about adaptively introgressed SVs in East Asian cattle. RESULTS In this study, we examine the roles of SVs in the climate adaptation of these two cattle lineages by generating highly contiguous chromosome-scale genome assemblies. Comparison of the two assemblies along with 18 Mongolian and Hainan cattle genomes obtained by long-read sequencing data provides a catalog of 123,898 nonredundant SVs. Several SVs detected from long reads are in exons of genes associated with epidermal differentiation, skin barrier, and bovine tuberculosis resistance. Functional investigations show that a 108-bp exonic insertion in SPN may affect the uptake of Mycobacterium tuberculosis by macrophages, which might contribute to the low susceptibility of Hainan cattle to bovine tuberculosis. Genotyping of 373 whole genomes from 39 breeds identifies 2610 SVs that are differentiated along a "north-south" gradient in China and overlap with 862 related genes that are enriched in pathways related to environmental adaptation. We identify 1457 Chinese indicine-stratified SVs that possibly originate from banteng and are frequent in Chinese indicine cattle. CONCLUSIONS Our findings highlight the unique contribution of SVs in East Asian cattle to environmental adaptation and disease resistance.
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Affiliation(s)
- Xiaoting Xia
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Fengwei Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Shuang Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Xiaoyu Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Lixin Peng
- National Engineering Research Center for Non-Food Biorefinery, Guangxi Academy of Sciences, 98 Daling Road, Nanning, China
| | - Zheng Dong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Hubert Pausch
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, 8006, Zurich, Switzerland
| | - Alexander S Leonard
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, 8006, Zurich, Switzerland
| | - Danang Crysnanto
- Animal Genomics, ETH Zurich, Universitaetstrasse 2, 8006, Zurich, Switzerland
| | - Shikang Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Bin Tong
- The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, School of Life Sciences, Inner Mongolia University, Hohhot, China
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Jianlin Han
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
- CAAS-ILRI Joint Laboratory On Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agriculture Sciences (CAAS), Beijing, China
| | - Fuyong Li
- Department of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR, China
| | - Tieshan Xu
- Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Lihong Gu
- Institute of Animal Science & Veterinary Medicine, Hainan Academy of Agricultural Sciences, Haikou, China
| | - Liangliang Jin
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Ruihua Dang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Yongzhen Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Xianyong Lan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Gang Ren
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Yuanpeng Gao
- College of Veterinary Medicine, Northwest A&F University, Xianyang, Yangling, China
| | - Zhijie Ma
- Qinghai Academy of Animal Science and Veterinary Medicine, Qinghai University, Xining, China
| | - Haijian Cheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
- Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Shandong Key Lab of Animal Disease Control and Breeding, Jinan, China
| | - Yun Ma
- Key Laboratory of Ruminant Molecular and Cellular Breeding of Ningxia Hui Autonomous Region, School of Agriculture, Ningxia University, Yinchuan, China
| | - Hong Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China
| | - Weijun Pang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China.
| | - Chuzhao Lei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China.
| | - Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang, China.
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12
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Karikari B, Lemay MA, Belzile F. k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives. Genes (Basel) 2023; 14:1439. [PMID: 37510343 PMCID: PMC10379394 DOI: 10.3390/genes14071439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/04/2023] [Accepted: 07/07/2023] [Indexed: 07/30/2023] Open
Abstract
Genome-wide association studies (GWAS) have allowed the discovery of marker-trait associations in crops over recent decades. However, their power is hampered by a number of limitations, with the key one among them being an overreliance on single-nucleotide polymorphisms (SNPs) as molecular markers. Indeed, SNPs represent only one type of genetic variation and are usually derived from alignment to a single genome assembly that may be poorly representative of the population under study. To overcome this, k-mer-based GWAS approaches have recently been developed. k-mer-based GWAS provide a universal way to assess variation due to SNPs, insertions/deletions, and structural variations without having to specifically detect and genotype these variants. In addition, k-mer-based analyses can be used in species that lack a reference genome. However, the use of k-mers for GWAS presents challenges such as data size and complexity, lack of standard tools, and potential detection of false associations. Nevertheless, efforts are being made to overcome these challenges and a general analysis workflow has started to emerge. We identify the priorities for k-mer-based GWAS in years to come, notably in the development of user-friendly programs for their analysis and approaches for linking significant k-mers to sequence variation.
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Affiliation(s)
- Benjamin Karikari
- Département de Phytologie, Université Laval, Quebec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada
- Department of Agricultural Biotechnology, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale P.O. Box TL 1882, Ghana
| | - Marc-André Lemay
- Département de Phytologie, Université Laval, Quebec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada
| | - François Belzile
- Département de Phytologie, Université Laval, Quebec City, QC G1V 0A6, Canada
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC G1V 0A6, Canada
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13
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Damián A, Núñez-Moreno G, Jubin C, Tamayo A, de Alba MR, Villaverde C, Fund C, Delépine M, Leduc A, Deleuze JF, Mínguez P, Ayuso C, Corton M. Long-read genome sequencing identifies cryptic structural variants in congenital aniridia cases. Hum Genomics 2023; 17:45. [PMID: 37269011 DOI: 10.1186/s40246-023-00490-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/08/2023] [Indexed: 06/04/2023] Open
Abstract
BACKGROUND Haploinsufficiency of the transcription factor PAX6 is the main cause of congenital aniridia, a genetic disorder characterized by iris and foveal hypoplasia. 11p13 microdeletions altering PAX6 or its downstream regulatory region (DRR) are present in about 25% of patients; however, only a few complex rearrangements have been described to date. Here, we performed nanopore-based whole-genome sequencing to assess the presence of cryptic structural variants (SVs) on the only two unsolved "PAX6-negative" cases from a cohort of 110 patients with congenital aniridia after unsuccessfully short-read sequencing approaches. RESULTS Long-read sequencing (LRS) unveiled balanced chromosomal rearrangements affecting the PAX6 locus at 11p13 in these two patients and allowed nucleotide-level breakpoint analysis. First, we identified a cryptic 4.9 Mb de novo inversion disrupting intron 7 of PAX6, further verified by targeted polymerase chain reaction amplification and sequencing and FISH-based cytogenetic analysis. Furthermore, LRS was decisive in correctly mapping a t(6;11) balanced translocation cytogenetically detected in a second proband with congenital aniridia and considered non-causal 15 years ago. LRS resolved that the breakpoint on chromosome 11 was indeed located at 11p13, disrupting the DNase I hypersensitive site 2 enhancer within the DRR of PAX6, 161 Kb from the causal gene. Patient-derived RNA expression analysis demonstrated PAX6 haploinsufficiency, thus supporting that the 11p13 breakpoint led to a positional effect by cleaving crucial enhancers for PAX6 transactivation. LRS analysis was also critical for mapping the exact breakpoint on chromosome 6 to the highly repetitive centromeric region at 6p11.1. CONCLUSIONS In both cases, the LRS-based identified SVs have been deemed the hidden pathogenic cause of congenital aniridia. Our study underscores the limitations of traditional short-read sequencing in uncovering pathogenic SVs affecting low-complexity regions of the genome and the value of LRS in providing insight into hidden sources of variation in rare genetic diseases.
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Affiliation(s)
- Alejandra Damián
- Department of Genetics & Genomics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain
- Centre for Biomedical Network Research On Rare Diseases (CIBERER), 28029, Madrid, Spain
| | - Gonzalo Núñez-Moreno
- Department of Genetics & Genomics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain
- Centre for Biomedical Network Research On Rare Diseases (CIBERER), 28029, Madrid, Spain
- Bioinformatics Unit, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain
| | - Claire Jubin
- Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, 91057, Evry, France
| | - Alejandra Tamayo
- Department of Genetics & Genomics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain
- Centre for Biomedical Network Research On Rare Diseases (CIBERER), 28029, Madrid, Spain
- Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, Science and Technology Campus, University of Alcalá, 28871, Alcalá de Henares, Spain
| | - Marta Rodríguez de Alba
- Department of Genetics & Genomics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain
- Centre for Biomedical Network Research On Rare Diseases (CIBERER), 28029, Madrid, Spain
| | - Cristina Villaverde
- Department of Genetics & Genomics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain
- Centre for Biomedical Network Research On Rare Diseases (CIBERER), 28029, Madrid, Spain
| | - Cédric Fund
- Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, 91057, Evry, France
| | - Marc Delépine
- Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, 91057, Evry, France
| | - Aurélie Leduc
- Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, 91057, Evry, France
| | - Jean François Deleuze
- Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, 91057, Evry, France
| | - Pablo Mínguez
- Department of Genetics & Genomics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain
- Centre for Biomedical Network Research On Rare Diseases (CIBERER), 28029, Madrid, Spain
- Bioinformatics Unit, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain
| | - Carmen Ayuso
- Department of Genetics & Genomics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain
- Centre for Biomedical Network Research On Rare Diseases (CIBERER), 28029, Madrid, Spain
| | - Marta Corton
- Department of Genetics & Genomics, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), 28040, Madrid, Spain.
- Centre for Biomedical Network Research On Rare Diseases (CIBERER), 28029, Madrid, Spain.
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14
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Kim JH, Kim GH, Yoo HW, Choi JH. Molecular basis and genetic testing strategies for diagnosing 21-hydroxylase deficiency, including CAH-X syndrome. Ann Pediatr Endocrinol Metab 2023; 28:77-86. [PMID: 37401054 DOI: 10.6065/apem.2346108.054] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 05/22/2022] [Indexed: 07/05/2023] Open
Abstract
Congenital adrenal hyperplasia (CAH) is a group of autosomally recessive disorders that result from impaired synthesis of glucocorticoid and mineralocorticoid. Most cases (~95%) are caused by mutations in the CYP21A2 gene, which encodes steroid 21-hydroxylase. CAH patients manifest a wide phenotypic spectrum according to their degree of residual enzyme activity. CYP21A2 and its pseudogene (CYP21A1P) are located 30 kb apart in the 6q21.3 region and share approximately 98% of their sequences in the coding region. Both genes are aligned in tandem with the C4, SKT19, and TNX genes, forming 2 segments of the RCCX modules that are arranged as STK19-C4A-CYP21A1P-TNXA-STK19B-C4B-CYP21A2-TNXB. The high sequence homology between the active gene and pseudogene leads to frequent microconversions and large rearrangements through intergenic recombination. The TNXB gene encodes an extracellular matrix glycoprotein, tenascin-X (TNX), and defects in TNXB cause Ehlers-Danlos syndrome. Deletions affecting both CYP21A2 and TNXB result in a contiguous gene deletion syndrome known as CAH-X syndrome. Because of the high homology between CYP21A2 and CYP21A1P, genetic testing for CAH should include an evaluation of copy number variations, as well as Sanger sequencing. Although it poses challenges for genetic testing, a large number of mutations and their associated phenotypes have been identified, which has helped to establish genotype-phenotype correlations. The genotype is helpful for guiding early treatment, predicting the clinical phenotype and prognosis, and providing genetic counseling. In particular, it can help ensure proper management of the potential complications of CAH-X syndrome, such as musculoskeletal and cardiac defects. This review focuses on the molecular pathophysiology and genetic diagnosis of 21-hydroxylase deficiency and highlights genetic testing strategies for CAH-X syndrome.
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Affiliation(s)
- Ja Hye Kim
- Department of Pediatrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Gu-Hwan Kim
- Medical Genetics Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Han-Wook Yoo
- Department of Pediatrics, Bundang CHA Medical Center, CHA University, Seongnam, Korea
| | - Jin-Ho Choi
- Department of Pediatrics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
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15
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Jiang R, Yang M, Zhang S, Huang M. Advances in sequencing-based studies of microDNA and ecDNA: Databases, identification methods, and integration with single-cell analysis. Comput Struct Biotechnol J 2023; 21:3073-3080. [PMID: 37273851 PMCID: PMC10238454 DOI: 10.1016/j.csbj.2023.05.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 05/17/2023] [Accepted: 05/17/2023] [Indexed: 06/06/2023] Open
Abstract
Extrachromosomal circular DNA (eccDNA) is a class of circular DNA molecules that originate from genomic DNA but are separate from chromosomes. They are common in various organisms, with sizes ranging from a few hundred to millions of base pairs. A special type of large extrachromosomal DNA (ecDNA) is prevalent in cancer cells. Research on ecDNA has significantly contributed to our comprehension of cancer development, progression, evolution, and drug resistance. The use of next-generation (NGS) and third-generation sequencing (TGS) techniques to identify eccDNAs throughout the genome has become a trend in current research. Here, we briefly review current advances in the biological mechanisms and applications of two distinct types of eccDNAs: microDNA and ecDNA. In addition to presenting available identification tools based on sequencing data, we summarize the most recent efforts to integrate ecDNA with single-cell analysis and put forth suggestions to promote the process.
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Affiliation(s)
| | | | - Shufan Zhang
- School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Moli Huang
- School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
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16
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Rau S, Huynh T, Larsen A, Kounovsky-Shafer KL. Concentration of lambda concatemers using a 3D printed device. Electrophoresis 2023; 44:744-751. [PMID: 36799437 PMCID: PMC10121831 DOI: 10.1002/elps.202200200] [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: 08/05/2022] [Revised: 11/18/2022] [Accepted: 02/15/2023] [Indexed: 02/18/2023]
Abstract
Identifying significant variations in genomes can be cumbersome, as the variations span a multitude of base pairs and can make genome assembly difficult. However, large DNA molecules that span the variation aid in assembly. Due to the DNA molecule's large size, routine molecular biology techniques can break DNA. Therefore, a method is required to concentrate large DNA. A bis-acrylamide roadblock was cured in a proof-of-principle 3D printed device to concentrate DNA at the interface between the roadblock and solution. Lambda concatemer DNA was stained with YOYO-1 and loaded into the 3D printed device. A dynamic range of voltages and acrylamide concentrations were tested to determine how much DNA was concentrated and recovered. The fluorescence of the original solution and the concentrated solution was measured, the recovery was 37% of the original sample, and the volume decreased by a factor of 3 of the original volume.
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Affiliation(s)
- Samantha Rau
- Department of Chemistry, University of Nebraska - Kearney, Kearney, NE, USA
| | - Thi Huynh
- Department of Chemistry, University of Nebraska - Kearney, Kearney, NE, USA
| | - Alex Larsen
- Department of Chemistry, University of Nebraska - Kearney, Kearney, NE, USA
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17
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Li R, Gong M, Zhang X, Wang F, Liu Z, Zhang L, Yang Q, Xu Y, Xu M, Zhang H, Zhang Y, Dai X, Gao Y, Zhang Z, Fang W, Yang Y, Fu W, Cao C, Yang P, Ghanatsaman ZA, Negari NJ, Nanaei HA, Yue X, Song Y, Lan X, Deng W, Wang X, Pan C, Xiang R, Ibeagha-Awemu EM, Heslop-Harrison PJS, Rosen BD, Lenstra JA, Gan S, Jiang Y. A sheep pangenome reveals the spectrum of structural variations and their effects on tail phenotypes. Genome Res 2023; 33:463-477. [PMID: 37310928 PMCID: PMC10078295 DOI: 10.1101/gr.277372.122] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 02/21/2023] [Indexed: 03/29/2023]
Abstract
Structural variations (SVs) are a major contributor to genetic diversity and phenotypic variations, but their prevalence and functions in domestic animals are largely unexplored. Here we generated high-quality genome assemblies for 15 individuals from genetically diverse sheep breeds using Pacific Biosciences (PacBio) high-fidelity sequencing, discovering 130.3 Mb nonreference sequences, from which 588 genes were annotated. A total of 149,158 biallelic insertions/deletions, 6531 divergent alleles, and 14,707 multiallelic variations with precise breakpoints were discovered. The SV spectrum is characterized by an excess of derived insertions compared to deletions (94,422 vs. 33,571), suggesting recent active LINE expansions in sheep. Nearly half of the SVs display low to moderate linkage disequilibrium with surrounding single-nucleotide polymorphisms (SNPs) and most SVs cannot be tagged by SNP probes from the widely used ovine 50K SNP chip. We identified 865 population-stratified SVs including 122 SVs possibly derived in the domestication process among 690 individuals from sheep breeds worldwide. A novel 168-bp insertion in the 5' untranslated region (5' UTR) of HOXB13 is found at high frequency in long-tailed sheep. Further genome-wide association study and gene expression analyses suggest that this mutation is causative for the long-tail trait. In summary, we have developed a panel of high-quality de novo assemblies and present a catalog of structural variations in sheep. Our data capture abundant candidate functional variations that were previously unexplored and provide a fundamental resource for understanding trait biology in sheep.
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Affiliation(s)
- Ran Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mian Gong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xinmiao Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Fei Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zhenyu Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Lei Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Qimeng Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yuan Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mengsi Xu
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, Xinjiang 832000, China
| | - Huanhuan Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yunfeng Zhang
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, Xinjiang 832000, China
| | - Xuelei Dai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yuanpeng Gao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zhuangbiao Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Wenwen Fang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yuta Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Weiwei Fu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chunna Cao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Peng Yang
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, Xinjiang 832000, China
| | - Zeinab Amiri Ghanatsaman
- Department of Animal Science, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education & Extension Organization (AREEO), Shiraz 7155863511, Iran
| | | | | | - Xiangpeng Yue
- State Key Laboratory of Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China
| | - Yuxuan Song
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xianyong Lan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Weidong Deng
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Xihong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chuanying Pan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Ruidong Xiang
- Faculty of Veterinary & Agricultural Science, The University of Melbourne, Parkville, 3052 Victoria, Australia
| | - Eveline M Ibeagha-Awemu
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, Quebec J1M 0C8, Canada
| | - Pat J S Heslop-Harrison
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, United Kingdom
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht 3508 TD, The Netherlands
| | - Shangquan Gan
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, Xinjiang 832000, China;
- College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang 524088, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China;
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
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18
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Malekshoar M, Azimi SA, Kaki A, Mousazadeh L, Motaei J, Vatankhah M. CRISPR-Cas9 Targeted Enrichment and Next-Generation Sequencing for Mutation Detection. J Mol Diagn 2023; 25:249-262. [PMID: 36841425 DOI: 10.1016/j.jmoldx.2023.01.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 01/08/2023] [Accepted: 01/27/2023] [Indexed: 02/27/2023] Open
Abstract
Despite the rapid application of next-generation sequencing (NGS) technologies, target sequencing in regions of the genome is often required to diagnose many genetic diseases. Target enrichment can be an effective factor in reducing the cost of sequencing and the duration of sequencing. Recently, several clustered system regularly interspaced short palindromic repeats (CRISPR)-based methods (amplification-free sequencing) have been developed to target enrichment in combination with one of the NGS platforms. CRISPR-based target enrichment strategies act as an auxiliary tool to improve NGS analytical performance, thereby indirectly facilitating nucleic acid detection. The direct DNA cleavage approach by CRISPR-Cas at genome-specific sites enhances the possibility of separating native large fragments from disease-related genomic regions. The CRISPR-Cas can isolate the target region without any amplification; subsequently, long-read sequencing technologies were also implemented. These methods, as promising tools, have the ability to assess genetic and epigenetic composition for clinical application and treatment responses in cancer precision medicine. By modifying CRISPR-based enrichment protocols, it was possible to identify different types of mutations, including structural variants, short tandem repeats, fusion genes, and mobile elements. The Cas9 can specifically eliminate wild-type sequences, and it also enables the enrichment and detection of small amounts of tumor DNA fragments among the highly heterogeneous fragments of wild-type DNA.
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Affiliation(s)
- Mehrdad Malekshoar
- Anesthesiology, Critical Care and Pain Management Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Sajad Ataei Azimi
- Department of Hematology-Oncology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Arastoo Kaki
- Department of Medical Genetics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Leila Mousazadeh
- Department of Medical Biotechnology, School of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Jamshid Motaei
- Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Majid Vatankhah
- Anesthesiology, Critical Care and Pain Management Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
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19
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Wang H, Wang LS, Schellenberg G, Lee WP. The role of structural variations in Alzheimer's disease and other neurodegenerative diseases. Front Aging Neurosci 2023; 14:1073905. [PMID: 36846102 PMCID: PMC9944073 DOI: 10.3389/fnagi.2022.1073905] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/31/2022] [Indexed: 02/10/2023] Open
Abstract
Dozens of single nucleotide polymorphisms (SNPs) related to Alzheimer's disease (AD) have been discovered by large scale genome-wide association studies (GWASs). However, only a small portion of the genetic component of AD can be explained by SNPs observed from GWAS. Structural variation (SV) can be a major contributor to the missing heritability of AD; while SV in AD remains largely unexplored as the accurate detection of SVs from the widely used array-based and short-read technology are still far from perfect. Here, we briefly summarized the strengths and weaknesses of available SV detection methods. We reviewed the current landscape of SV analysis in AD and SVs that have been found associated with AD. Particularly, the importance of currently less explored SVs, including insertions, inversions, short tandem repeats, and transposable elements in neurodegenerative diseases were highlighted.
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Affiliation(s)
- Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Gerard Schellenberg
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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20
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Lesack K, Mariene GM, Andersen EC, Wasmuth JD. Different structural variant prediction tools yield considerably different results in Caenorhabditis elegans. PLoS One 2022; 17:e0278424. [PMID: 36584177 PMCID: PMC9803319 DOI: 10.1371/journal.pone.0278424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 11/15/2022] [Indexed: 01/01/2023] Open
Abstract
The accurate characterization of structural variation is crucial for our understanding of how large chromosomal alterations affect phenotypic differences and contribute to genome evolution. Whole-genome sequencing is a popular approach for identifying structural variants, but the accuracy of popular tools remains unclear due to the limitations of existing benchmarks. Moreover, the performance of these tools for predicting variants in non-human genomes is less certain, as most tools were developed and benchmarked using data from the human genome. To evaluate the use of long-read data for the validation of short-read structural variant calls, the agreement between predictions from a short-read ensemble learning method and long-read tools were compared using real and simulated data from Caenorhabditis elegans. The results obtained from simulated data indicate that the best performing tool is contingent on the type and size of the variant, as well as the sequencing depth of coverage. These results also highlight the need for reference datasets generated from real data that can be used as 'ground truth' in benchmarks.
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Affiliation(s)
- Kyle Lesack
- Faculty of Veterinary Medicine, University of Calgary, Alberta, Canada
- Host-Parasite Interactions Research Training Network, University of Calgary, Alberta, Canada
| | - Grace M. Mariene
- Faculty of Veterinary Medicine, University of Calgary, Alberta, Canada
- Host-Parasite Interactions Research Training Network, University of Calgary, Alberta, Canada
| | - Erik C. Andersen
- Department of Molecular Biosciences, Northwestern University, Evanston, IL, United States of America
| | - James D. Wasmuth
- Faculty of Veterinary Medicine, University of Calgary, Alberta, Canada
- Host-Parasite Interactions Research Training Network, University of Calgary, Alberta, Canada
- * E-mail:
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21
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Abdelhalim H, Berber A, Lodi M, Jain R, Nair A, Pappu A, Patel K, Venkat V, Venkatesan C, Wable R, Dinatale M, Fu A, Iyer V, Kalove I, Kleyman M, Koutsoutis J, Menna D, Paliwal M, Patel N, Patel T, Rafique Z, Samadi R, Varadhan R, Bolla S, Vadapalli S, Ahmed Z. Artificial Intelligence, Healthcare, Clinical Genomics, and Pharmacogenomics Approaches in Precision Medicine. Front Genet 2022; 13:929736. [PMID: 35873469 PMCID: PMC9299079 DOI: 10.3389/fgene.2022.929736] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 05/25/2022] [Indexed: 12/13/2022] Open
Abstract
Precision medicine has greatly aided in improving health outcomes using earlier diagnosis and better prognosis for chronic diseases. It makes use of clinical data associated with the patient as well as their multi-omics/genomic data to reach a conclusion regarding how a physician should proceed with a specific treatment. Compared to the symptom-driven approach in medicine, precision medicine considers the critical fact that all patients do not react to the same treatment or medication in the same way. When considering the intersection of traditionally distinct arenas of medicine, that is, artificial intelligence, healthcare, clinical genomics, and pharmacogenomics—what ties them together is their impact on the development of precision medicine as a field and how they each contribute to patient-specific, rather than symptom-specific patient outcomes. This study discusses the impact and integration of these different fields in the scope of precision medicine and how they can be used in preventing and predicting acute or chronic diseases. Additionally, this study also discusses the advantages as well as the current challenges associated with artificial intelligence, healthcare, clinical genomics, and pharmacogenomics.
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Affiliation(s)
- Habiba Abdelhalim
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Asude Berber
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Mudassir Lodi
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Rihi Jain
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Achuth Nair
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Anirudh Pappu
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Kush Patel
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Vignesh Venkat
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Cynthia Venkatesan
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Raghu Wable
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Matthew Dinatale
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Allyson Fu
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Vikram Iyer
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Ishan Kalove
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Marc Kleyman
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Joseph Koutsoutis
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - David Menna
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Mayank Paliwal
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Nishi Patel
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Thirth Patel
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Zara Rafique
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Rothela Samadi
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Roshan Varadhan
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Shreyas Bolla
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Sreya Vadapalli
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
| | - Zeeshan Ahmed
- Rutgers Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States.,Department of Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers Biomedical and Health Sciences, New Brunswick, NJ, United States
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22
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Hamdan A, Ewing A. Unravelling the tumour genome: The evolutionary and clinical impacts of structural variants in tumourigenesis. J Pathol 2022; 257:479-493. [PMID: 35355264 PMCID: PMC9321913 DOI: 10.1002/path.5901] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/16/2022] [Accepted: 03/28/2022] [Indexed: 11/15/2022]
Abstract
Structural variants (SVs) represent a major source of aberration in tumour genomes. Given the diversity in the size and type of SVs present in tumours, the accurate detection and interpretation of SVs in tumours is challenging. New classes of complex structural events in tumours are discovered frequently, and the definitions of the genomic consequences of complex events are constantly being refined. Detailed analyses of short-read whole-genome sequencing (WGS) data from large tumour cohorts facilitate the interrogation of SVs at orders of magnitude greater scale and depth. However, the inherent technical limitations of short-read WGS prevent us from accurately detecting and investigating the impact of all the SVs present in tumours. The expanded use of long-read WGS will be critical for improving the accuracy of SV detection, and in fully resolving complex SV events, both of which are crucial for determining the impact of SVs on tumour progression and clinical outcome. Despite the present limitations, we demonstrate that SVs play an important role in tumourigenesis. In particular, SVs contribute significantly to late-stage tumour development and to intratumoural heterogeneity. The evolutionary trajectories of SVs represent a window into the clonal dynamics in tumours, a comprehensive understanding of which will be vital for influencing patient outcomes in the future. Recent findings have highlighted many clinical applications of SVs in cancer, from early detection to biomarkers for treatment response and prognosis. As the methods to detect and interpret SVs improve, elucidating the full breadth of the complex SV landscape and determining how these events modulate tumour evolution will improve our understanding of cancer biology and our ability to capitalise on the utility of SVs in the clinical management of cancer patients. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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Affiliation(s)
- Alhafidz Hamdan
- MRC Human Genetics Unit, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
- Cancer Research UK Edinburgh Centre, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
| | - Ailith Ewing
- MRC Human Genetics Unit, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
- Cancer Research UK Edinburgh Centre, Institute of Genetics and CancerUniversity of EdinburghEdinburghUK
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23
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Quan C, Lu H, Lu Y, Zhou G. Population-scale genotyping of structural variation in the era of long-read sequencing. Comput Struct Biotechnol J 2022; 20:2639-2647. [PMID: 35685364 PMCID: PMC9163579 DOI: 10.1016/j.csbj.2022.05.047] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/24/2022] [Accepted: 05/24/2022] [Indexed: 11/29/2022] Open
Abstract
Population-scale studies of structural variation (SV) are growing rapidly worldwide with the development of long-read sequencing technology, yielding a considerable number of novel SVs and complete gap-closed genome assemblies. Herein, we highlight recent studies using a hybrid sequencing strategy and present the challenges toward large-scale genotyping for SVs due to the reference bias. Genotyping SVs at a population scale remains challenging, which severely impacts genotype-based population genetic studies or genome-wide association studies of complex diseases. We summarize academic efforts to improve genotype quality through linear or graph representations of reference and alternative alleles. Graph-based genotypers capable of integrating diverse genetic information are effectively applied to large and diverse cohorts, contributing to unbiased downstream analysis. Meanwhile, there is still an urgent need in this field for efficient tools to construct complex graphs and perform sequence-to-graph alignments.
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Affiliation(s)
- Cheng Quan
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
| | - Hao Lu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
| | - Yiming Lu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
- Hebei University, Baoding, Hebei Province 071002, PR China
| | - Gangqiao Zhou
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province 211166, PR China
- Medical College of Guizhou University, Guiyang, Guizhou Province 550025, PR China
- Hebei University, Baoding, Hebei Province 071002, PR China
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24
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Danis D, Jacobsen JOB, Balachandran P, Zhu Q, Yilmaz F, Reese J, Haimel M, Lyon GJ, Helbig I, Mungall CJ, Beck CR, Lee C, Smedley D, Robinson PN. SvAnna: efficient and accurate pathogenicity prediction of coding and regulatory structural variants in long-read genome sequencing. Genome Med 2022; 14:44. [PMID: 35484572 PMCID: PMC9047340 DOI: 10.1186/s13073-022-01046-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 04/12/2022] [Indexed: 01/18/2023] Open
Abstract
Structural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to sequencing technology limitations. Long-read sequencing enables comprehensive detection of SVs, but approaches for prioritization of candidate SVs are needed. Structural variant Annotation and analysis (SvAnna) assesses all classes of SVs and their intersection with transcripts and regulatory sequences, relating predicted effects on gene function with clinical phenotype data. SvAnna places 87% of deleterious SVs in the top ten ranks. The interpretable prioritizations offered by SvAnna will facilitate the widespread adoption of long-read sequencing in diagnostic genomics. SvAnna is available at https://github.com/TheJacksonLaboratory/SvAnn a .
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Affiliation(s)
- Daniel Danis
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Julius O B Jacobsen
- William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | | | - Qihui Zhu
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Feyza Yilmaz
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Justin Reese
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Matthias Haimel
- Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases, Vienna, Austria
- St. Anna Children's Cancer Research Institute, Vienna, Austria
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
- Present address: Global Computational Biology and Digital Sciences, Boehringer Ingelheim Regional Center Vienna GmbH & Co KG, 1120, Vienna, Austria
| | - Gholson J Lyon
- Department of Human Genetics, New York State Institute for Basic Research in Developmental Disabilities, Staten Island, New York, USA
- Biology PhD Program, The Graduate Center, The City University of New York, New York, USA
| | - Ingo Helbig
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The Epilepsy NeuroGenetics Initiative (ENGIN), Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher J Mungall
- Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Christine R Beck
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, 06032, USA
- Institute for Systems Genomics, University of Connecticut, Storrs, CT, 06269, USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA
| | - Damian Smedley
- William Harvey Research Institute, Charterhouse Square, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
| | - Peter N Robinson
- The Jackson Laboratory for Genomic Medicine, Farmington, CT, 06032, USA.
- Department of Genetics and Genome Sciences, University of Connecticut Health Center, Farmington, CT, 06032, USA.
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25
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Uppuluri L, Wang Y, Young E, Wong JS, Abid HZ, Xiao M. Multiplex structural variant detection by whole-genome mapping and nanopore sequencing. Sci Rep 2022; 12:6512. [PMID: 35444207 PMCID: PMC9021263 DOI: 10.1038/s41598-022-10483-7] [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: 10/25/2021] [Accepted: 04/08/2022] [Indexed: 11/26/2022] Open
Abstract
Identification of structural variants (SVs) breakpoints is important in studying mutations, mutagenic causes, and functional impacts. Next-generation sequencing and whole-genome optical mapping are extensively used in SV discovery and characterization. However, multiple platforms and computational approaches are needed for comprehensive analysis, making it resource-intensive and expensive. Here, we propose a strategy combining optical mapping and cas9-assisted targeted nanopore sequencing to analyze SVs. Optical mapping can economically and quickly detect SVs across a whole genome but does not provide sequence-level information or precisely resolve breakpoints. Furthermore, since only a subset of all SVs is known to affect biology, we attempted to type a subset of all SVs using targeted nanopore sequencing. Using our approach, we resolved the breakpoints of five deletions, five insertions, and an inversion, in a single experiment.
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Affiliation(s)
- Lahari Uppuluri
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA.,Department of Mechanical Engineering and Mechanics, Drexel University, Philadelphia, PA, USA
| | - Yilin Wang
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA
| | - Eleanor Young
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA
| | - Jessica S Wong
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA
| | - Heba Z Abid
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA
| | - Ming Xiao
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA. .,Center for Genomic Sciences, Institute of Molecular Medicine and Infectious Disease, Drexel University, Philadelphia, PA, USA.
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26
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Rech GE, Radío S, Guirao-Rico S, Aguilera L, Horvath V, Green L, Lindstadt H, Jamilloux V, Quesneville H, González J. Population-scale long-read sequencing uncovers transposable elements associated with gene expression variation and adaptive signatures in Drosophila. Nat Commun 2022; 13:1948. [PMID: 35413957 PMCID: PMC9005704 DOI: 10.1038/s41467-022-29518-8] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 03/15/2022] [Indexed: 12/16/2022] Open
Abstract
High quality reference genomes are crucial to understanding genome function, structure and evolution. The availability of reference genomes has allowed us to start inferring the role of genetic variation in biology, disease, and biodiversity conservation. However, analyses across organisms demonstrate that a single reference genome is not enough to capture the global genetic diversity present in populations. In this work, we generate 32 high-quality reference genomes for the well-known model species D. melanogaster and focus on the identification and analysis of transposable element variation as they are the most common type of structural variant. We show that integrating the genetic variation across natural populations from five climatic regions increases the number of detected insertions by 58%. Moreover, 26% to 57% of the insertions identified using long-reads were missed by short-reads methods. We also identify hundreds of transposable elements associated with gene expression variation and new TE variants likely to contribute to adaptive evolution in this species. Our results highlight the importance of incorporating the genetic variation present in natural populations to genomic studies, which is essential if we are to understand how genomes function and evolve.
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Affiliation(s)
- Gabriel E Rech
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Santiago Radío
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Sara Guirao-Rico
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Laura Aguilera
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Vivien Horvath
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Llewellyn Green
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | - Hannah Lindstadt
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain
| | | | | | - Josefa González
- Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), 08003, Barcelona, Spain.
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27
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Liu Z, Roberts R, Mercer TR, Xu J, Sedlazeck FJ, Tong W. Towards accurate and reliable resolution of structural variants for clinical diagnosis. Genome Biol 2022; 23:68. [PMID: 35241127 PMCID: PMC8892125 DOI: 10.1186/s13059-022-02636-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 02/15/2022] [Indexed: 12/17/2022] Open
Abstract
Structural variants (SVs) are a major source of human genetic diversity and have been associated with different diseases and phenotypes. The detection of SVs is difficult, and a diverse range of detection methods and data analysis protocols has been developed. This difficulty and diversity make the detection of SVs for clinical applications challenging and requires a framework to ensure accuracy and reproducibility. Here, we discuss current developments in the diagnosis of SVs and propose a roadmap for the accurate and reproducible detection of SVs that includes case studies provided from the FDA-led SEquencing Quality Control Phase II (SEQC-II) and other consortium efforts.
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Affiliation(s)
- Zhichao Liu
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Ruth Roberts
- ApconiX, BioHub at Alderley Park, Alderley Edge, SK10 4TG, UK
- University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Timothy R Mercer
- Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, QLD, Australia
- Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Joshua Xu
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA.
| | - Weida Tong
- National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR, 72079, USA.
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28
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Nanodevices for Biological and Medical Applications: Development of Single-Molecule Electrical Measurement Method. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12031539] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
A comprehensive detection of a wide variety of diagnostic markers is required for the realization of personalized medicine. As a sensor to realize such personalized medicine, a single molecule electrical measurement method using nanodevices is currently attracting interest for its comprehensive simultaneous detection of various target markers for use in biological and medical application. Single-molecule electrical measurement using nanodevices, such as nanopore, nanogap, or nanopipette devices, has the following features:; high sensitivity, low-cost, high-throughput detection, easy-portability, low-cost availability by mass production technologies, and the possibility of integration of various functions and multiple sensors. In this review, I focus on the medical applications of single- molecule electrical measurement using nanodevices. This review provides information on the current status and future prospects of nanodevice-based single-molecule electrical measurement technology, which is making a full-scale contribution to realizing personalized medicine in the future. Future prospects include some discussion on of the current issues on the expansion of the application requirements for single-mole-cule measurement.
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29
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Mohammed Salih M, Carpenter S. What sequencing technologies can teach us about innate immunity. Immunol Rev 2022; 305:9-28. [PMID: 34747035 PMCID: PMC8865538 DOI: 10.1111/imr.13033] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 09/22/2021] [Accepted: 10/16/2021] [Indexed: 01/03/2023]
Abstract
For years, we have taken a reductionist approach to understanding gene regulation through the study of one gene in one cell at a time. While this approach has been fruitful it is laborious and fails to provide a global picture of what is occurring in complex situations involving tightly coordinated immune responses. The emergence of whole-genome techniques provides a system-level view of a response and can provide a plethora of information on events occurring in a cell from gene expression changes to splicing changes and chemical modifications. As with any technology, this often results in more questions than answers, but this wealth of knowledge is providing us with an unprecedented view of what occurs inside our cells during an immune response. In this review, we will discuss the current RNA-sequencing technologies and what they are helping us learn about the innate immune system.
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Affiliation(s)
- Mays Mohammed Salih
- Department of Molecular Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, California, USA
| | - Susan Carpenter
- Department of Molecular Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, California, USA
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30
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Bartalucci N, Romagnoli S, Vannucchi AM. A blood drop through the pore: nanopore sequencing in hematology. Trends Genet 2021; 38:572-586. [PMID: 34906378 DOI: 10.1016/j.tig.2021.11.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/09/2021] [Accepted: 11/15/2021] [Indexed: 10/19/2022]
Abstract
The development of new sequencing platforms, technologies, and bioinformatics tools in the past decade fostered key discoveries in human genomics. Among the most recent sequencing technologies, nanopore sequencing (NS) has caught the interest of researchers for its intriguing potential and flexibility. This up-to-date review highlights the recent application of NS in the hematology field, focusing on progress and challenges of the technological approaches employed for the identification of pathologic alterations. The molecular and analytic pipelines developed for the analysis of the whole-genome, target regions, and transcriptomics provide a proof of evidence of the unparalleled amount of information that could be retrieved by an innovative approach based on long-read sequencing.
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Affiliation(s)
- Niccolò Bartalucci
- CRIMM, Center of Research and Innovation of Myeloproliferative Neoplasms, Careggi University Hospital and Department of Experimental and Clinical Medicine, University of Florence, DENOTHE Excellence Center, Florence, Italy
| | - Simone Romagnoli
- CRIMM, Center of Research and Innovation of Myeloproliferative Neoplasms, Careggi University Hospital and Department of Experimental and Clinical Medicine, University of Florence, DENOTHE Excellence Center, Florence, Italy
| | - Alessandro Maria Vannucchi
- CRIMM, Center of Research and Innovation of Myeloproliferative Neoplasms, Careggi University Hospital and Department of Experimental and Clinical Medicine, University of Florence, DENOTHE Excellence Center, Florence, Italy.
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31
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Lüth T, Wasner K, Klein C, Schaake S, Tse R, Pereira SL, Laß J, Sinkkonen L, Grünewald A, Trinh J. Nanopore Single-Molecule Sequencing for Mitochondrial DNA Methylation Analysis: Investigating Parkin-Associated Parkinsonism as a Proof of Concept. Front Aging Neurosci 2021; 13:713084. [PMID: 34650424 PMCID: PMC8506010 DOI: 10.3389/fnagi.2021.713084] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 09/01/2021] [Indexed: 01/08/2023] Open
Abstract
Objective: To establish a workflow for mitochondrial DNA (mtDNA) CpG methylation using Nanopore whole-genome sequencing and perform first pilot experiments on affected Parkin biallelic mutation carriers (Parkin-PD) and healthy controls. Background: Mitochondria, including mtDNA, are established key players in Parkinson's disease (PD) pathogenesis. Mutations in Parkin, essential for degradation of damaged mitochondria, cause early-onset PD. However, mtDNA methylation and its implication in PD is understudied. Herein, we establish a workflow using Nanopore sequencing to directly detect mtDNA CpG methylation and compare mtDNA methylation between Parkin-related PD and healthy individuals. Methods: To obtain mtDNA, whole-genome Nanopore sequencing was performed on blood-derived from five Parkin-PD and three control subjects. In addition, induced pluripotent stem cell (iPSC)-derived midbrain neurons from four of these patients with PD and the three control subjects were investigated. The workflow was validated, using methylated and unmethylated 897 bp synthetic DNA samples at different dilution ratios (0, 50, 100% methylation) and mtDNA without methylation. MtDNA CpG methylation frequency (MF) was detected using Nanopolish and Megalodon. Results: Across all blood-derived samples, we obtained a mean coverage of 250.3X (SD ± 80.5X) and across all neuron-derived samples 830X (SD ± 465X) of the mitochondrial genome. We detected overall low-level CpG methylation from the blood-derived DNA (mean MF ± SD = 0.029 ± 0.041) and neuron-derived DNA (mean MF ± SD = 0.019 ± 0.035). Validation of the workflow, using synthetic DNA samples showed that highly methylated DNA molecules were prone to lower Guppy Phred quality scores and thereby more likely to fail Guppy base-calling. CpG methylation in blood- and neuron-derived DNA was significantly lower in Parkin-PD compared to controls (Mann-Whitney U-test p < 0.05). Conclusion: Nanopore sequencing is a useful method to investigate mtDNA methylation architecture, including Guppy-failed reads is of importance when investigating highly methylated sites. We present a mtDNA methylation workflow and suggest methylation variability across different tissues and between Parkin-PD patients and controls as an initial model to investigate.
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Affiliation(s)
- Theresa Lüth
- Institute of Neurogenetics BMF, University of Lübeck and University Hospital Schleswig-Holstein Campus Lübeck, Lübeck, Germany
| | - Kobi Wasner
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Christine Klein
- Institute of Neurogenetics BMF, University of Lübeck and University Hospital Schleswig-Holstein Campus Lübeck, Lübeck, Germany
| | - Susen Schaake
- Institute of Neurogenetics BMF, University of Lübeck and University Hospital Schleswig-Holstein Campus Lübeck, Lübeck, Germany
| | - Ronnie Tse
- Institute of Neurogenetics BMF, University of Lübeck and University Hospital Schleswig-Holstein Campus Lübeck, Lübeck, Germany
| | - Sandro L. Pereira
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Joshua Laß
- Institute of Neurogenetics BMF, University of Lübeck and University Hospital Schleswig-Holstein Campus Lübeck, Lübeck, Germany
| | - Lasse Sinkkonen
- Department of Life Sciences and Medicine, University of Luxembourg, Belvaux, Luxembourg
| | - Anne Grünewald
- Institute of Neurogenetics BMF, University of Lübeck and University Hospital Schleswig-Holstein Campus Lübeck, Lübeck, Germany
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
| | - Joanne Trinh
- Institute of Neurogenetics BMF, University of Lübeck and University Hospital Schleswig-Holstein Campus Lübeck, Lübeck, Germany
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32
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Abstract
Long-read sequencing technologies have now reached a level of accuracy and yield that allows their application to variant detection at a scale of tens to thousands of samples. Concomitant with the development of new computational tools, the first population-scale studies involving long-read sequencing have emerged over the past 2 years and, given the continuous advancement of the field, many more are likely to follow. In this Review, we survey recent developments in population-scale long-read sequencing, highlight potential challenges of a scaled-up approach and provide guidance regarding experimental design. We provide an overview of current long-read sequencing platforms, variant calling methodologies and approaches for de novo assemblies and reference-based mapping approaches. Furthermore, we summarize strategies for variant validation, genotyping and predicting functional impact and emphasize challenges remaining in achieving long-read sequencing at a population scale.
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Affiliation(s)
- Wouter De Coster
- Applied and Translational Neurogenomics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Applied and Translational Neurogenomics Group, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | | | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.
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33
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Gutierrez-Rodrigues F, Sahoo SS, Wlodarski MW, Young NS. Somatic mosaicism in inherited bone marrow failure syndromes. Best Pract Res Clin Haematol 2021; 34:101279. [PMID: 34404533 DOI: 10.1016/j.beha.2021.101279] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 06/01/2021] [Accepted: 06/12/2021] [Indexed: 12/20/2022]
Abstract
Inherited bone marrow failure syndromes (IBMFS) are a heterogenous group of diseases caused by pathogenic germline variants in key pathways associated with haematopoiesis and genomic stability. Germline variants in IBMFS-related genes are known to reduce the fitness of hematopoietic stem and progenitor cells (HSPC), which has been hypothesized to drive clonal selection in these diseases. In many IBMFS, somatic mosaicism predominantly impacts cells by two distinct mechanisms, with contrasting effects. An acquired variation can improve cell fitness towards baseline levels, providing rescue of a deleterious phenotype. Alternatively, somatic mosaicism may result in a fitness advantage that results in malignant transformation. This review will describe these phenomena in IBMFS and delineate their relevance for diagnosis and clinical management. In addition, we will discuss which samples and methods can be used for detection of mosaicism according to clinical phenotype, type of mosaicism, and sample availability.
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Affiliation(s)
| | - Sushree S Sahoo
- Department of Hematology, St. Jude Children's Research Hospital, TN, USA
| | - Marcin W Wlodarski
- Department of Hematology, St. Jude Children's Research Hospital, TN, USA; Division of Pediatric Hematology and Oncology, Department of Pediatrics and Adolescent Medicine, Medical Center, Faculty of Medicine, University of Freiburg, Germany
| | - Neal S Young
- Hematology Branch, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, MD, USA
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34
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Liu H, Yin H, Li G, Li J, Wang X. Aperture: alignment-free detection of structural variations and viral integrations in circulating tumor DNA. Brief Bioinform 2021; 22:6345221. [PMID: 34368852 DOI: 10.1093/bib/bbab290] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 06/18/2021] [Accepted: 07/06/2021] [Indexed: 01/23/2023] Open
Abstract
The identification of structural variations (SVs) and viral integrations in circulating tumor DNA (ctDNA) is a key step in precision oncology that may assist clinicians in treatment selection and monitoring. However, due to the short fragment size of ctDNA, it is challenging to accurately detect low-frequency SVs or SVs involving complex junctions in ctDNA sequencing data. Here, we describe Aperture, a new fast SV caller that applies a unique strategy of $k$-mer-based searching, binary label-based breakpoint detection and candidate clustering to detect SVs and viral integrations with high sensitivity, especially when junctions span repetitive regions. Aperture also employs a barcode-based filter to ensure specificity. Compared with existing methods, Aperture exhibits superior sensitivity and specificity in simulated, reference and real data tests, especially at low dilutions. Additionally, Aperture is able to predict sites of viral integration and identify complex SVs involving novel insertions and repetitive sequences in real patient data. Aperture is freely available at https://github.com/liuhc8/Aperture.
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Affiliation(s)
- Hongchao Liu
- State Key Laboratory of Medical Molecular Biology, Center for Bioinformatics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences,School of Basic Medicine Peking Union Medical College
| | - Huihui Yin
- State Key Laboratory of Molecular Oncology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Guangyu Li
- State Key Laboratory of Medical Molecular Biology, Center for Bioinformatics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences,School of Basic Medicine Peking Union Medical College
| | - Junling Li
- National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xiaoyue Wang
- State Key Laboratory of Medical Molecular Biology, Center for Bioinformatics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences,School of Basic Medicine Peking Union Medical College
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35
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Quan C, Li Y, Liu X, Wang Y, Ping J, Lu Y, Zhou G. Characterization of structural variation in Tibetans reveals new evidence of high-altitude adaptation and introgression. Genome Biol 2021; 22:159. [PMID: 34034800 PMCID: PMC8146648 DOI: 10.1186/s13059-021-02382-3] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/14/2021] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Structural variation (SV) acts as an essential mutational force shaping the evolution and function of the human genome. However, few studies have examined the role of SVs in high-altitude adaptation and little is known of adaptive introgressed SVs in Tibetans so far. RESULTS Here, we generate a comprehensive catalog of SVs in a Chinese Tibetan (n = 15) and Han (n = 10) population using nanopore sequencing technology. Among a total of 38,216 unique SVs in the catalog, 27% are sequence-resolved for the first time. We systematically assess the distribution of these SVs across repeat sequences and functional genomic regions. Through genotyping in additional 276 genomes, we identify 69 Tibetan-Han stratified SVs and 80 candidate adaptive genes. We also discover a few adaptive introgressed SV candidates and provide evidence for a deletion of 335 base pairs at 1p36.32. CONCLUSIONS Overall, our results highlight the important role of SVs in the evolutionary processes of Tibetans' adaptation to the Qinghai-Tibet Plateau and provide a valuable resource for future high-altitude adaptation studies.
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Affiliation(s)
- Cheng Quan
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Yuanfeng Li
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Xinyi Liu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Yahui Wang
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Jie Ping
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
| | - Yiming Lu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
- Hebei University, Baoding, Hebei Province 071002 People’s Republic of China
| | - Gangqiao Zhou
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850 People’s Republic of China
- Hebei University, Baoding, Hebei Province 071002 People’s Republic of China
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province 211166 People’s Republic of China
- Medical College of Guizhou University, Guiyang, Guizhou Province 550025 People’s Republic of China
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36
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Halliwell JA, Baker D, Judge K, Quail MA, Oliver K, Betteridge E, Skelton J, Andrews PW, Barbaric I. Nanopore Sequencing Indicates That Tandem Amplification of Chromosome 20q11.21 in Human Pluripotent Stem Cells Is Driven by Break-Induced Replication. Stem Cells Dev 2021; 30:578-586. [PMID: 33757297 PMCID: PMC8165465 DOI: 10.1089/scd.2021.0013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Copy number variants (CNVs) are genomic rearrangements implicated in numerous congenital and acquired diseases, including cancer. The appearance of culture-acquired CNVs in human pluripotent stem cells (PSCs) has prompted concerns for their use in regenerative medicine. A particular problem in PSC is the frequent occurrence of CNVs in the q11.21 region of chromosome 20. However, the exact mechanism of origin of this amplicon remains elusive due to the difficulty in delineating its sequence and breakpoints. Here, we have addressed this problem using long-read Nanopore sequencing of two examples of this CNV, present as duplication and as triplication. In both cases, the CNVs were arranged in a head-to-tail orientation, with microhomology sequences flanking or overlapping the proximal and distal breakpoints. These breakpoint signatures point to a mechanism of microhomology-mediated break-induced replication in CNV formation, with surrounding Alu sequences likely contributing to the instability of this genomic region.
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Affiliation(s)
- Jason A Halliwell
- Department of Biomedical Science, University of Sheffield, Sheffield, United Kingdom
| | - Duncan Baker
- Sheffield Diagnostic Genetic Services, Sheffield Children's Hospital, Sheffield, United Kingdom
| | - Kim Judge
- Department of Sequencing R & D, Wellcome Sanger Institute, Hinxton, United Kingdom
| | - Michael A Quail
- Department of Sequencing R & D, Wellcome Sanger Institute, Hinxton, United Kingdom
| | - Karen Oliver
- Department of Sequencing R & D, Wellcome Sanger Institute, Hinxton, United Kingdom
| | - Emma Betteridge
- Department of Sequencing R & D, Wellcome Sanger Institute, Hinxton, United Kingdom
| | - Jason Skelton
- Department of Sequencing R & D, Wellcome Sanger Institute, Hinxton, United Kingdom
| | - Peter W Andrews
- Department of Biomedical Science, University of Sheffield, Sheffield, United Kingdom
| | - Ivana Barbaric
- Department of Biomedical Science, University of Sheffield, Sheffield, United Kingdom
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37
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Kojima S, Kamada AJ, Parrish NF. Virus-derived variation in diverse human genomes. PLoS Genet 2021; 17:e1009324. [PMID: 33901175 PMCID: PMC8101998 DOI: 10.1371/journal.pgen.1009324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 05/06/2021] [Accepted: 03/25/2021] [Indexed: 11/19/2022] Open
Abstract
Acquisition of genetic material from viruses by their hosts can generate inter-host structural genome variation. We developed computational tools enabling us to study virus-derived structural variants (SVs) in population-scale whole genome sequencing (WGS) datasets and applied them to 3,332 humans. Although SVs had already been cataloged in these subjects, we found previously-overlooked virus-derived SVs. We detected non-germline SVs derived from squirrel monkey retrovirus (SMRV), human immunodeficiency virus 1 (HIV-1), and human T lymphotropic virus (HTLV-1); these variants are attributable to infection of the sequenced lymphoblastoid cell lines (LCLs) or their progenitor cells and may impact gene expression results and the biosafety of experiments using these cells. In addition, we detected new heritable SVs derived from human herpesvirus 6 (HHV-6) and human endogenous retrovirus-K (HERV-K). We report the first solo-direct repeat (DR) HHV-6 likely to reflect DR rearrangement of a known full-length endogenous HHV-6. We used linkage disequilibrium between single nucleotide variants (SNVs) and variants in reads that align to HERV-K, which often cannot be mapped uniquely using conventional short-read sequencing analysis methods, to locate previously-unknown polymorphic HERV-K loci. Some of these loci are tightly linked to trait-associated SNVs, some are in complex genome regions inaccessible by prior methods, and some contain novel HERV-K haplotypes likely derived from gene conversion from an unknown source or introgression. These tools and results broaden our perspective on the coevolution between viruses and humans, including ongoing virus-to-human gene transfer contributing to genetic variation between humans.
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Affiliation(s)
- Shohei Kojima
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Anselmo Jiro Kamada
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
| | - Nicholas F. Parrish
- Genome Immunobiology RIKEN Hakubi Research Team, RIKEN Center for Integrative Medical Sciences and RIKEN Cluster for Pioneering Research, Yokohama, Japan
- * E-mail:
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38
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Ascari G, Rendtorff ND, De Bruyne M, De Zaeytijd J, Van Lint M, Bauwens M, Van Heetvelde M, Arno G, Jacob J, Creytens D, Van Dorpe J, Van Laethem T, Rosseel T, De Pooter T, De Rijk P, De Coster W, Menten B, Rey AD, Strazisar M, Bertelsen M, Tranebjaerg L, De Baere E. Long-Read Sequencing to Unravel Complex Structural Variants of CEP78 Leading to Cone-Rod Dystrophy and Hearing Loss. Front Cell Dev Biol 2021; 9:664317. [PMID: 33968938 PMCID: PMC8097100 DOI: 10.3389/fcell.2021.664317] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 03/08/2021] [Indexed: 11/13/2022] Open
Abstract
Inactivating variants as well as a missense variant in the centrosomal CEP78 gene have been identified in autosomal recessive cone-rod dystrophy with hearing loss (CRDHL), a rare syndromic inherited retinal disease distinct from Usher syndrome. Apart from this, a complex structural variant (SV) implicating CEP78 has been reported in CRDHL. Here we aimed to expand the genetic architecture of typical CRDHL by the identification of complex SVs of the CEP78 region and characterization of their underlying mechanisms. Approaches used for the identification of the SVs are shallow whole-genome sequencing (sWGS) combined with quantitative polymerase chain reaction (PCR) and long-range PCR, or ExomeDepth analysis on whole-exome sequencing (WES) data. Targeted or whole-genome nanopore long-read sequencing (LRS) was used to delineate breakpoint junctions at the nucleotide level. For all SVs cases, the effect of the SVs on CEP78 expression was assessed using quantitative PCR on patient-derived RNA. Apart from two novel canonical CEP78 splice variants and a frameshifting single-nucleotide variant (SNV), two SVs affecting CEP78 were identified in three unrelated individuals with CRDHL: a heterozygous total gene deletion of 235 kb and a partial gene deletion of 15 kb in a heterozygous and homozygous state, respectively. Assessment of the molecular consequences of the SVs on patient's materials displayed a loss-of-function effect. Delineation and characterization of the 15-kb deletion using targeted LRS revealed the previously described complex CEP78 SV, suggestive of a recurrent genomic rearrangement. A founder haplotype was demonstrated for the latter SV in cases of Belgian and British origin, respectively. The novel 235-kb deletion was delineated using whole-genome LRS. Breakpoint analysis showed microhomology and pointed to a replication-based underlying mechanism. Moreover, data mining of bulk and single-cell human and mouse transcriptional datasets, together with CEP78 immunostaining on human retina, linked the CEP78 expression domain with its phenotypic manifestations. Overall, this study supports that the CEP78 locus is prone to distinct SVs and that SV analysis should be considered in a genetic workup of CRDHL. Finally, it demonstrated the power of sWGS and both targeted and whole-genome LRS in identifying and characterizing complex SVs in patients with ocular diseases.
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Affiliation(s)
- Giulia Ascari
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Nanna D Rendtorff
- The Kennedy Center, Department of Clinical Genetics, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Marieke De Bruyne
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Julie De Zaeytijd
- Department of Ophthalmology, Ghent University Hospital, Ghent, Belgium
| | - Michel Van Lint
- Department of Ophthalmology, Antwerp University Hospital, Antwerp, Belgium
| | - Miriam Bauwens
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Mattias Van Heetvelde
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Gavin Arno
- Great Ormond Street Hospital, London, United Kingdom.,Moorfields Eye Hospital, London, United Kingdom.,UCL Institute of Ophthalmology, London, United Kingdom
| | - Julie Jacob
- Department of Ophthalmology, University Hospitals Leuven, Leuven, Belgium
| | - David Creytens
- Department of Pathology, Ghent University Hospital, Ghent, Belgium.,Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Jo Van Dorpe
- Department of Pathology, Ghent University Hospital, Ghent, Belgium.,Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Thalia Van Laethem
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Toon Rosseel
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Tim De Pooter
- Neuromics Support Facility, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium.,Neuromics Support Facility, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Peter De Rijk
- Neuromics Support Facility, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium.,Neuromics Support Facility, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Wouter De Coster
- Applied and Translational Neurogenomics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium.,Applied and Translational Neurogenomics Group, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Björn Menten
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Alfredo Dueñas Rey
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Mojca Strazisar
- Neuromics Support Facility, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium.,Neuromics Support Facility, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Mette Bertelsen
- The Kennedy Center, Department of Clinical Genetics, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.,Department of Ophthalmology, Rigshospitalet-Glostrup, University of Copenhagen, Glostrup, Denmark
| | - Lisbeth Tranebjaerg
- The Kennedy Center, Department of Clinical Genetics, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.,Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Elfride De Baere
- Center for Medical Genetics Ghent, Ghent University Hospital, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
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39
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Lyu R, Tsui V, McCarthy DJ, Crismani W. Personalized genome structure via single gamete sequencing. Genome Biol 2021; 22:112. [PMID: 33874978 PMCID: PMC8054432 DOI: 10.1186/s13059-021-02327-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Accepted: 03/25/2021] [Indexed: 12/13/2022] Open
Abstract
Genetic maps have been fundamental to building our understanding of disease genetics and evolutionary processes. The gametes of an individual contain all of the information required to perform a de novo chromosome-scale assembly of an individual's genome, which historically has been performed with populations and pedigrees. Here, we discuss how single-cell gamete sequencing offers the potential to merge the advantages of short-read sequencing with the ability to build personalized genetic maps and open up an entirely new space in personalized genetics.
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Affiliation(s)
- Ruqian Lyu
- Bioinformatics and Cellular Genomics, St. Vincent's Institute of Medical Research, Melbourne, Australia
- Melbourne Integrative Genomics, Faculty of Science, The University of Melbourne, Melbourne, Australia
| | - Vanessa Tsui
- DNA Repair and Recombination Laboratory, St. Vincent's Institute of Medical Research, Melbourne, Australia
- The Faculty of Medicine, Dentistry and Health Science, The University of Melbourne, Melbourne, Australia
| | - Davis J McCarthy
- Bioinformatics and Cellular Genomics, St. Vincent's Institute of Medical Research, Melbourne, Australia.
- Melbourne Integrative Genomics, Faculty of Science, The University of Melbourne, Melbourne, Australia.
| | - Wayne Crismani
- DNA Repair and Recombination Laboratory, St. Vincent's Institute of Medical Research, Melbourne, Australia.
- The Faculty of Medicine, Dentistry and Health Science, The University of Melbourne, Melbourne, Australia.
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40
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Oppenheimer J, Rosen BD, Heaton MP, Vander Ley BL, Shafer WR, Schuetze FT, Stroud B, Kuehn LA, McClure JC, Barfield JP, Blackburn HD, Kalbfleisch TS, Bickhart DM, Davenport KM, Kuhn KL, Green RE, Shapiro B, Smith TPL. A Reference Genome Assembly of American Bison, Bison bison bison. J Hered 2021; 112:174-183. [PMID: 33595645 PMCID: PMC8006816 DOI: 10.1093/jhered/esab003] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Accepted: 01/13/2021] [Indexed: 11/14/2022] Open
Abstract
Bison are an icon of the American West and an ecologically, commercially, and culturally important species. Despite numbering in the hundreds of thousands today, conservation concerns remain for the species, including the impact on genetic diversity of a severe bottleneck around the turn of the 20th century and genetic introgression from domestic cattle. Genetic diversity and admixture are best evaluated at genome-wide scale, for which a high-quality reference is necessary. Here, we use trio binning of long reads from a bison-Simmental cattle (Bos taurus taurus) male F1 hybrid to sequence and assemble the genome of the American plains bison (Bison bison bison). The male haplotype genome is chromosome-scale, with a total length of 2.65 Gb across 775 scaffolds (839 contigs) and a scaffold N50 of 87.8 Mb. Our bison genome is ~13× more contiguous overall and ~3400× more contiguous at the contig level than the current bison reference genome. The bison genome sequence presented here (ARS-UCSC_bison1.0) will enable new research into the evolutionary history of this iconic megafauna species and provide a new tool for the management of bison populations in federal and commercial herds.
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Affiliation(s)
- Jonas Oppenheimer
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Benjamin D Rosen
- USDA, ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD, USA
| | - Michael P Heaton
- USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Brian L Vander Ley
- Great Plains Veterinary Educational Center, University of Nebraska-Lincoln, Lincoln, NE, USA
| | | | | | - Brad Stroud
- Stroud Veterinary Embryo Services, Weatherford, TE, USA
| | - Larry A Kuehn
- USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | | | - Jennifer P Barfield
- College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO, USA
| | | | | | | | - Kimberly M Davenport
- Department of Animal, Veterinary, and Food Science, University of Idaho, Moscow, ID, USA
| | - Kristen L Kuhn
- USDA, ARS, U.S. Meat Animal Research Center, Clay Center, NE, USA
| | - Richard E Green
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, USA.,Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA, USA
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41
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van Belzen IAEM, Schönhuth A, Kemmeren P, Hehir-Kwa JY. Structural variant detection in cancer genomes: computational challenges and perspectives for precision oncology. NPJ Precis Oncol 2021; 5:15. [PMID: 33654267 PMCID: PMC7925608 DOI: 10.1038/s41698-021-00155-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 01/12/2021] [Indexed: 01/31/2023] Open
Abstract
Cancer is generally characterized by acquired genomic aberrations in a broad spectrum of types and sizes, ranging from single nucleotide variants to structural variants (SVs). At least 30% of cancers have a known pathogenic SV used in diagnosis or treatment stratification. However, research into the role of SVs in cancer has been limited due to difficulties in detection. Biological and computational challenges confound SV detection in cancer samples, including intratumor heterogeneity, polyploidy, and distinguishing tumor-specific SVs from germline and somatic variants present in healthy cells. Classification of tumor-specific SVs is challenging due to inconsistencies in detected breakpoints, derived variant types and biological complexity of some rearrangements. Full-spectrum SV detection with high recall and precision requires integration of multiple algorithms and sequencing technologies to rescue variants that are difficult to resolve through individual methods. Here, we explore current strategies for integrating SV callsets and to enable the use of tumor-specific SVs in precision oncology.
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Affiliation(s)
| | - Alexander Schönhuth
- Genome Data Science, Faculty of Technology, Bielefeld University, Bielefeld, Germany
| | - Patrick Kemmeren
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Jayne Y Hehir-Kwa
- Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands.
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42
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Begum G, Albanna A, Bankapur A, Nassir N, Tambi R, Berdiev BK, Akter H, Karuvantevida N, Kellam B, Alhashmi D, Sung WWL, Thiruvahindrapuram B, Alsheikh-Ali A, Scherer SW, Uddin M. Long-Read Sequencing Improves the Detection of Structural Variations Impacting Complex Non-Coding Elements of the Genome. Int J Mol Sci 2021; 22:2060. [PMID: 33669700 PMCID: PMC7923155 DOI: 10.3390/ijms22042060] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 01/21/2021] [Accepted: 01/27/2021] [Indexed: 12/17/2022] Open
Abstract
The advent of long-read sequencing offers a new assessment method of detecting genomic structural variation (SV) in numerous rare genetic diseases. For autism spectrum disorders (ASD) cases where pathogenic variants fail to be found in the protein-coding genic regions along chromosomes, we proposed a scalable workflow to characterize the risk factor of SVs impacting non-coding elements of the genome. We applied whole-genome sequencing on an Emirati family having three children with ASD using long and short-read sequencing technology. A series of analytical pipelines were established to identify a set of SVs with high sensitivity and specificity. At 15-fold coverage, we observed that long-read sequencing technology (987 variants) detected a significantly higher number of SVs when compared to variants detected using short-read technology (509 variants) (p-value < 1.1020 × 10-57). Further comparison showed 97.9% of long-read sequencing variants were spanning within the 1-100 kb size range (p-value < 9.080 × 10-67) and impacting over 5000 genes. Moreover, long-read variants detected 604 non-coding RNAs (p-value < 9.02 × 10-9), comprising 58% microRNA, 31.9% lncRNA, and 9.1% snoRNA. Even at low coverage, long-read sequencing has shown to be a reliable technology in detecting SVs impacting complex elements of the genome.
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Affiliation(s)
- Ghausia Begum
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
| | - Ammar Albanna
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
- Department of Psychiatry, Al Jalila Children’s Specialty Hospital, Dubai 7662, United Arab Emirates
| | - Asma Bankapur
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
| | - Nasna Nassir
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
| | - Richa Tambi
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
| | - Bakhrom K. Berdiev
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
| | - Hosneara Akter
- Genetics and Genomic Medicine Centre, NeuroGen Children’s Healthcare, Dhaka 1205, Bangladesh;
- Department of Biochemistry and Molecular Biology, Dhaka University, Dhaka 1000, Bangladesh
| | - Noushad Karuvantevida
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
- Department of Biotechnology, Bharathidasan University, Tiruchirappalli 620024, India
| | - Barbara Kellam
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5S 1A1, Canada; (B.K.); (W.W.L.S.); (B.T.)
| | - Deena Alhashmi
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
| | - Wilson W. L. Sung
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5S 1A1, Canada; (B.K.); (W.W.L.S.); (B.T.)
| | - Bhooma Thiruvahindrapuram
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5S 1A1, Canada; (B.K.); (W.W.L.S.); (B.T.)
| | - Alawi Alsheikh-Ali
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
| | - Stephen W. Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON M5S 1A1, Canada; (B.K.); (W.W.L.S.); (B.T.)
- Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
- McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, ON M5S, Canada
| | - Mohammed Uddin
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates; (G.B.); (A.A.); (A.B.); (N.N.); (R.T.); (B.K.B.); (N.K.); (D.A.); (A.A.-A.)
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43
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Interpreting the impact of noncoding structural variation in neurodevelopmental disorders. Genet Med 2020; 23:34-46. [PMID: 32973355 PMCID: PMC7790743 DOI: 10.1038/s41436-020-00974-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 09/03/2020] [Accepted: 09/14/2020] [Indexed: 12/21/2022] Open
Abstract
The emergence of novel sequencing technologies has greatly improved the identification of structural variation, revealing that a human genome harbors tens of thousands of structural variants (SVs). Since these SVs primarily impact noncoding DNA sequences, the next challenge is one of interpretation, not least to improve our understanding of human disease etiology. However, this task is severely complicated by the intricacy of the gene regulatory landscapes embedded within these noncoding regions, their incomplete annotation, as well as their dependence on the three-dimensional (3D) conformation of the genome. Also in the context of neurodevelopmental disorders (NDDs), reports of putatively causal, noncoding SVs are accumulating and understanding their impact on transcriptional regulation is presenting itself as the next step toward improved genetic diagnosis.
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44
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Zhao H, Chen Y, Shen C, Li L, Li Q, Tan K, Huang H, Hu G. Breakpoint mapping of a t(9;22;12) chronic myeloid leukaemia patient with e14a3 BCR-ABL1 transcript using Nanopore sequencing. J Gene Med 2020; 23:e3276. [PMID: 32949441 DOI: 10.1002/jgm.3276] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 09/03/2020] [Accepted: 09/14/2020] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND The genetic changes in chronic myeloid leukaemia (CML) have been well established, although challenges persist in cases with rare fusion transcripts or complex variant translocations. Here, we present a CML patient with e14a3 BCR-ABL1 transcript and t(9;22;12) variant Philadelphia (Ph) chromosome. METHODS Cytogenetic analysis and fluorescence in situ hybridization (FISH) was performed to identify the chromosomal aberrations and gene fusions. Rare fusion transcript was verified by a reverse transcription-polymerase chain reaction (RT-PCR). Breakpoints were characterized and validated using Oxford Nanopore Technologies (ONT) (Oxford, UK) and Sanger sequencing, respectively. RESULTS The karyotype showed the translocation t(9;22;12)(q34;q11.2;q24) [20] and FISH indicated 40% positive BCR-ABL1 fusion signals. The RT-PCR suggested e14a3 type fusion transcript. The ONT sequencing analysis identified specific positions of translocation breakpoints: chr22:23633040-chr9:133729579, chr12:121567595-chr22:24701405, which were confirmed using Sanger sequencing. The patient achieved molecular remission 3 months after imatinib therapy. CONCLUSIONS The present study indicates Nanopore sequencing as a valid strategy, which can characterize breakpoints precisely in special clinical cases with atypical structural variations. CML patients with e14a3 transcripts may have good clinical course in the tyrosine kinase inhibitor era, as reviewed here.
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Affiliation(s)
- Hu Zhao
- Department of Haematology, The Affiliated Zhuzhou Hospital, XiangYa Medical College, Central South University, Zhuzhou, Hunan, China
| | - Yuan Chen
- Department of Haematology, The Affiliated Zhuzhou Hospital, XiangYa Medical College, Central South University, Zhuzhou, Hunan, China
| | - Chanjuan Shen
- Department of Haematology, The Affiliated Zhuzhou Hospital, XiangYa Medical College, Central South University, Zhuzhou, Hunan, China
| | - Lingshu Li
- Department of Haematology, The Affiliated Zhuzhou Hospital, XiangYa Medical College, Central South University, Zhuzhou, Hunan, China
| | - Qingzhao Li
- Department of Haematology, The Affiliated Zhuzhou Hospital, XiangYa Medical College, Central South University, Zhuzhou, Hunan, China
| | - Kui Tan
- Department of Haematology, The Affiliated Zhuzhou Hospital, XiangYa Medical College, Central South University, Zhuzhou, Hunan, China
| | - Huang Huang
- Department of Haematology, The Affiliated Zhuzhou Hospital, XiangYa Medical College, Central South University, Zhuzhou, Hunan, China
| | - Guoyu Hu
- Department of Haematology, The Affiliated Zhuzhou Hospital, XiangYa Medical College, Central South University, Zhuzhou, Hunan, China
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45
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López-Girona E, Davy MW, Albert NW, Hilario E, Smart MEM, Kirk C, Thomson SJ, Chagné D. CRISPR-Cas9 enrichment and long read sequencing for fine mapping in plants. PLANT METHODS 2020; 16:121. [PMID: 32884578 PMCID: PMC7465313 DOI: 10.1186/s13007-020-00661-x] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Accepted: 08/18/2020] [Indexed: 05/03/2023]
Abstract
BACKGROUND Genomic methods for identifying causative variants for trait loci applicable to a wide range of germplasm are required for plant biologists and breeders to understand the genetic control of trait variation. RESULTS We implemented Cas9-targeted sequencing for fine-mapping in apple, a method combining CRISPR-Cas9 targeted cleavage of a region of interest, followed by enrichment and long-read sequencing using the Oxford Nanopore Technology (ONT). We demonstrated the capability of this methodology to specifically cleave and enrich a plant genomic locus spanning 8 kb. The repeated mini-satellite motif located upstream of the Malus × domestica (apple) MYB10 transcription factor gene, causing red fruit colouration when present in a heterozygous state, was our exemplar to demonstrate the efficiency of this method: it contains a genomic region with a long structural variant normally ignored by short-read sequencing technologiesCleavage specificity of the guide RNAs was demonstrated using polymerase chain reaction products, before using them to specify cleavage of high molecular weight apple DNA. An enriched library was subsequently prepared and sequenced using an ONT MinION flow cell (R.9.4.1). Of the 7,056 ONT reads base-called using both Albacore2 (v2.3.4) and Guppy (v3.2.4), with a median length of 9.78 and 9.89 kb, respectively, 85.35 and 91.38%, aligned to the reference apple genome. Of the aligned reads, 2.98 and 3.04% were on-target with read depths of 180 × and 196 × for Albacore2 and Guppy, respectively, and only five genomic loci were off-target with read depth greater than 25 × , which demonstrated the efficiency of the enrichment method and specificity of the CRISPR-Cas9 cleavage. CONCLUSIONS We demonstrated that this method can isolate and resolve single-nucleotide and structural variants at the haplotype level in plant genomic regions. The combination of CRISPR-Cas9 target enrichment and ONT sequencing provides a more efficient technology for fine-mapping loci than genome-walking approaches.
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Affiliation(s)
- Elena López-Girona
- The New Zealand Institute for Plant and Food Research Limited (Plant & Food Research), Private Bag 11600, Palmerston North, 4442 New Zealand
| | | | - Nick W. Albert
- The New Zealand Institute for Plant and Food Research Limited (Plant & Food Research), Private Bag 11600, Palmerston North, 4442 New Zealand
| | | | - Maia E. M. Smart
- The New Zealand Institute for Plant and Food Research Limited (Plant & Food Research), Private Bag 11600, Palmerston North, 4442 New Zealand
| | - Chris Kirk
- The New Zealand Institute for Plant and Food Research Limited (Plant & Food Research), Private Bag 11600, Palmerston North, 4442 New Zealand
| | | | - David Chagné
- The New Zealand Institute for Plant and Food Research Limited (Plant & Food Research), Private Bag 11600, Palmerston North, 4442 New Zealand
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Alonge M, Wang X, Benoit M, Soyk S, Pereira L, Zhang L, Suresh H, Ramakrishnan S, Maumus F, Ciren D, Levy Y, Harel TH, Shalev-Schlosser G, Amsellem Z, Razifard H, Caicedo AL, Tieman DM, Klee H, Kirsche M, Aganezov S, Ranallo-Benavidez TR, Lemmon ZH, Kim J, Robitaille G, Kramer M, Goodwin S, McCombie WR, Hutton S, Van Eck J, Gillis J, Eshed Y, Sedlazeck FJ, van der Knaap E, Schatz MC, Lippman ZB. Major Impacts of Widespread Structural Variation on Gene Expression and Crop Improvement in Tomato. Cell 2020; 182:145-161.e23. [PMID: 32553272 PMCID: PMC7354227 DOI: 10.1016/j.cell.2020.05.021] [Citation(s) in RCA: 377] [Impact Index Per Article: 94.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 04/10/2020] [Accepted: 05/12/2020] [Indexed: 12/22/2022]
Abstract
Structural variants (SVs) underlie important crop improvement and domestication traits. However, resolving the extent, diversity, and quantitative impact of SVs has been challenging. We used long-read nanopore sequencing to capture 238,490 SVs in 100 diverse tomato lines. This panSV genome, along with 14 new reference assemblies, revealed large-scale intermixing of diverse genotypes, as well as thousands of SVs intersecting genes and cis-regulatory regions. Hundreds of SV-gene pairs exhibit subtle and significant expression changes, which could broadly influence quantitative trait variation. By combining quantitative genetics with genome editing, we show how multiple SVs that changed gene dosage and expression levels modified fruit flavor, size, and production. In the last example, higher order epistasis among four SVs affecting three related transcription factors allowed introduction of an important harvesting trait in modern tomato. Our findings highlight the underexplored role of SVs in genotype-to-phenotype relationships and their widespread importance and utility in crop improvement.
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Affiliation(s)
- Michael Alonge
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Xingang Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Matthias Benoit
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Sebastian Soyk
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Lara Pereira
- Center for Applied Genetic Technologies, Genetics & Genomics, University of Georgia, Athens, GA 30602, USA
| | - Lei Zhang
- Center for Applied Genetic Technologies, Genetics & Genomics, University of Georgia, Athens, GA 30602, USA
| | - Hamsini Suresh
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | | | - Florian Maumus
- URGI, INRA, Université Paris-Saclay, 78026 Versailles, France
| | - Danielle Ciren
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Yuval Levy
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Tom Hai Harel
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Gili Shalev-Schlosser
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Ziva Amsellem
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Hamid Razifard
- Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA; Department of Biology, University of Massachusetts Amherst, Amherst, MA 01003, USA
| | - Ana L Caicedo
- Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA; Department of Biology, University of Massachusetts Amherst, Amherst, MA 01003, USA
| | - Denise M Tieman
- Horticultural Sciences, Plant Innovation Center, University of Florida, Gainesville, FL 32611, USA
| | - Harry Klee
- Horticultural Sciences, Plant Innovation Center, University of Florida, Gainesville, FL 32611, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | | | - Zachary H Lemmon
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Jennifer Kim
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Gina Robitaille
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Melissa Kramer
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Sara Goodwin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - W Richard McCombie
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Samuel Hutton
- Gulf Coast Research and Education Center, University of Florida, Wimauma, FL 33598, USA
| | - Joyce Van Eck
- Boyce Thompson Institute, Ithaca, NY 14853, USA; Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA
| | - Jesse Gillis
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Yuval Eshed
- Department of Plant and Environmental Sciences, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Esther van der Knaap
- Center for Applied Genetic Technologies, Genetics & Genomics, University of Georgia, Athens, GA 30602, USA; Institute of Plant Breeding, Genetics and Genomics, University of Georgia, Athens, GA 30602, USA; Department of Horticulture, University of Georgia, Athens, GA 30602, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA; Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA.
| | - Zachary B Lippman
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.
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First interchromosomal insertion in a patient with cerebral and spinal cavernous malformations. Sci Rep 2020; 10:6306. [PMID: 32286434 PMCID: PMC7156631 DOI: 10.1038/s41598-020-63337-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 03/30/2020] [Indexed: 01/06/2023] Open
Abstract
Autosomal dominant cerebral cavernous malformations (CCM) are leaky vascular lesions that can cause epileptic seizures and stroke-like symptoms. Germline mutations in either CCM1, CCM2 or CCM3 are found in the majority of patients with multiple CCMs or a positive family history. Recently, the first copy number neutral inversion in CCM2 has been identified by whole genome sequencing in an apparently mutation-negative CCM family. We here asked the question whether further structural genomic rearrangements can be detected within NGS gene panel data of unsolved CCM cases. Hybrid capture NGS data of eight index patients without a pathogenic single nucleotide, indel or copy number variant were analyzed using two bioinformatics pipelines. In a 58-year-old male with multiple CCMs in his brain and spinal cord, we identified a 294 kb insertion within the coding sequence of CCM2. Fine mapping of the breakpoints, molecular cytogenetic studies, and multiplex ligation-dependent probe amplification verified that the structural variation was an inverted unbalanced insertion that originated from 1p12-p11.2. As this rearrangement disrupts exon 6 of CCM2 on 7p13, it was classified as pathogenic. Our study demonstrates that efforts to detect structural variations in known disease genes increase the diagnostic sensitivity of genetic analyses for well-defined Mendelian disorders.
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48
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Luan MW, Zhang XM, Zhu ZB, Chen Y, Xie SQ. Evaluating Structural Variation Detection Tools for Long-Read Sequencing Datasets in Saccharomyces cerevisiae. Front Genet 2020; 11:159. [PMID: 32211024 PMCID: PMC7075250 DOI: 10.3389/fgene.2020.00159] [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: 11/07/2019] [Accepted: 02/11/2020] [Indexed: 01/01/2023] Open
Abstract
Structural variation (SV) represents a major form of genetic variations that contribute to polymorphic variations, human diseases, and phenotypes in many organisms. Long-read sequencing has been successfully used to identify novel and complex SVs. However, comparison of SV detection tools for long-read sequencing datasets has not been reported. Therefore, we developed an analysis workflow that combined two alignment tools (NGMLR and minimap2) and five callers (Sniffles, Picky, smartie-sv, PBHoney, and NanoSV) to evaluate the SV detection in six datasets of Saccharomyces cerevisiae. The accuracy of SV regions was validated by re-aligning raw reads in diverse alignment tools, SV callers, experimental conditions, and sequencing platforms. The results showed that SV detection between NGMLR and minimap2 was not significant when using the same caller. The PBHoney was with the highest average accuracy (89.04%) and Picky has the lowest average accuracy (35.85%). The accuracy of NanoSV, Sniffles, and smartie-sv was 68.67%, 60.47%, and 57.67%, respectively. In addition, smartie-sv and NanoSV detected the most and least number of SVs, and SV detection from the PacBio sequencing platform was significantly more than that from ONT (p = 0.000173).
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Affiliation(s)
- Mei-Wei Luan
- Key Laboratory of Genetics and Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants (Ministry of Education), Hainan Key Laboratory for Biology of Tropical Ornamental Plant Germplasm, College of Forestry, Hainan University, Haikou, China
| | - Xiao-Ming Zhang
- College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Huhhot, China
| | - Zi-Bin Zhu
- Key Laboratory of Genetics and Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants (Ministry of Education), Hainan Key Laboratory for Biology of Tropical Ornamental Plant Germplasm, College of Forestry, Hainan University, Haikou, China
| | - Ying Chen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China
| | - Shang-Qian Xie
- Key Laboratory of Genetics and Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants (Ministry of Education), Hainan Key Laboratory for Biology of Tropical Ornamental Plant Germplasm, College of Forestry, Hainan University, Haikou, China
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49
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De Coster W, Strazisar M, De Rijk P. Critical length in long-read resequencing. NAR Genom Bioinform 2020; 2:lqz027. [PMID: 33575574 PMCID: PMC7671308 DOI: 10.1093/nargab/lqz027] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Revised: 12/06/2019] [Accepted: 01/02/2020] [Indexed: 12/25/2022] Open
Abstract
Long-read sequencing has substantial advantages for structural variant discovery and phasing of variants compared to short-read technologies, but the required and optimal read length has not been assessed. In this work, we used long reads simulated from human genomes and evaluated structural variant discovery and variant phasing using current best practice bioinformatics methods. We determined that optimal discovery of structural variants from human genomes can be obtained with reads of minimally 20 kb. Haplotyping variants across genes only reaches its optimum from reads of 100 kb. These findings are important for the design of future long-read sequencing projects.
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Affiliation(s)
- Wouter De Coster
- VIB-UAntwerp Center for Molecular Neurology, 2610 Antwerp, Belgium
| | - Mojca Strazisar
- VIB-UAntwerp Center for Molecular Neurology, 2610 Antwerp, Belgium
| | - Peter De Rijk
- VIB-UAntwerp Center for Molecular Neurology, 2610 Antwerp, Belgium
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50
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Minervini CF, Cumbo C, Orsini P, Anelli L, Zagaria A, Specchia G, Albano F. Nanopore Sequencing in Blood Diseases: A Wide Range of Opportunities. Front Genet 2020; 11:76. [PMID: 32140171 PMCID: PMC7043087 DOI: 10.3389/fgene.2020.00076] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 01/23/2020] [Indexed: 12/20/2022] Open
Abstract
The molecular pathogenesis of hematological diseases is often driven by genetic and epigenetic alterations. Next-generation sequencing has considerably increased our genomic knowledge of these disorders becoming ever more widespread in clinical practice. In 2012 Oxford Nanopore Technologies (ONT) released the MinION, the first long-read nanopore-based sequencer, overcoming the main limits of short-reads sequences generation. In the last years, several nanopore sequencing approaches have been performed in various "-omic" sciences; this review focuses on the challenge to introduce ONT devices in the hematological field, showing advantages, disadvantages and future perspectives of this technology in the precision medicine era.
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Affiliation(s)
| | | | | | | | | | | | - Francesco Albano
- Department of Emergency and Organ Transplantation (D.E.T.O.), Hematology Section, University of Bari, Bari, Italy
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