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Dunn P, Albury CL, Maksemous N, Benton MC, Sutherland HG, Smith RA, Haupt LM, Griffiths LR. Next Generation Sequencing Methods for Diagnosis of Epilepsy Syndromes. Front Genet 2018; 9:20. [PMID: 29467791 PMCID: PMC5808353 DOI: 10.3389/fgene.2018.00020] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 01/16/2018] [Indexed: 12/28/2022] Open
Abstract
Epilepsy is a neurological disorder characterized by an increased predisposition for seizures. Although this definition suggests that it is a single disorder, epilepsy encompasses a group of disorders with diverse aetiologies and outcomes. A genetic basis for epilepsy syndromes has been postulated for several decades, with several mutations in specific genes identified that have increased our understanding of the genetic influence on epilepsies. With 70-80% of epilepsy cases identified to have a genetic cause, there are now hundreds of genes identified to be associated with epilepsy syndromes which can be analyzed using next generation sequencing (NGS) techniques such as targeted gene panels, whole exome sequencing (WES) and whole genome sequencing (WGS). For effective use of these methodologies, diagnostic laboratories and clinicians require information on the relevant workflows including analysis and sequencing depth to understand the specific clinical application and diagnostic capabilities of these gene sequencing techniques. As epilepsy is a complex disorder, the differences associated with each technique influence the ability to form a diagnosis along with an accurate detection of the genetic etiology of the disorder. In addition, for diagnostic testing, an important parameter is the cost-effectiveness and the specific diagnostic outcome of each technique. Here, we review these commonly used NGS techniques to determine their suitability for application to epilepsy genetic diagnostic testing.
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Affiliation(s)
- Paul Dunn
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Cassie L Albury
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Neven Maksemous
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Miles C Benton
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Heidi G Sutherland
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Robert A Smith
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Larisa M Haupt
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Lyn R Griffiths
- Genomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
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102
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Zhang W, Li Y, Chen Y, Xu S, Du G, Shi H, Zhou J, Chen J. Complete genome sequence and analysis of the industrial Saccharomyces cerevisiae strain N85 used in Chinese rice wine production. DNA Res 2018; 25:4838783. [PMID: 29415277 PMCID: PMC6014378 DOI: 10.1093/dnares/dsy002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2017] [Accepted: 01/10/2018] [Indexed: 12/17/2022] Open
Abstract
Chinese rice wine is a popular traditional alcoholic beverage in China, while its brewing processes have rarely been explored. We herein report the first gapless, near-finished genome sequence of the yeast strain Saccharomyces cerevisiae N85 for Chinese rice wine production. Several assembly methods were used to integrate Pacific Bioscience (PacBio) and Illumina sequencing data to achieve high-quality genome sequencing of the strain. The genome encodes more than 6,000 predicted proteins, and 238 long non-coding RNAs, which are validated by RNA-sequencing data. Moreover, our annotation predicts 171 novel genes that are not present in the reference S288c genome. We also identified 65,902 single nucleotide polymorphisms and small indels, many of which are located within genic regions. Dozens of larger copy-number variations and translocations were detected, mainly enriched in the subtelomeres, suggesting these regions may be related to genomic evolution. This study will serve as a milestone in studying of Chinese rice wine and related beverages in China and in other countries. It will help to develop more scientific and modern fermentation processes of Chinese rice wine, and explore metabolism pathways of desired and harmful components in Chinese rice wine to improve its taste and nutritional value.
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Affiliation(s)
- Weiping Zhang
- School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214443, China
| | - Yudong Li
- School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214443, China
- Department of Bioengineering, School of Food Sciences and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, China
| | - Yiwang Chen
- Department of Bioengineering, School of Food Sciences and Biotechnology, Zhejiang Gongshang University, Hangzhou 310018, China
| | - Sha Xu
- School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214443, China
| | - Guocheng Du
- School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214443, China
| | - Huidong Shi
- Georgia Cancer Center, Augusta University, Augusta, GA 30912, USA
| | - Jingwen Zhou
- School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214443, China
| | - Jian Chen
- School of Biotechnology, Jiangnan University, Wuxi, Jiangsu 214443, China
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103
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Gómez-Sánchez D, Schlötterer C. ReadTools: A universal toolkit for handling sequence data from different sequencing platforms. Mol Ecol Resour 2017; 18:676-680. [PMID: 29171165 DOI: 10.1111/1755-0998.12741] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 09/07/2017] [Accepted: 11/12/2017] [Indexed: 11/28/2022]
Abstract
Sequencing whole genomes has become a standard research tool in many disciplines including Molecular Ecology, but the rapid technological advances in combination with several competing platforms have resulted in a confusing diversity of formats. This lack of standard formats causes several problems, such as undocumented preprocessing steps or the loss of information in downstream software tools, which do not account for the specifics of the different available formats. ReadTools is an open-source Java toolkit designed to standardize and preprocess read data from different platforms. It manages FASTQ- and SAM-formatted inputs while dealing with platform-specific peculiarities and provides a standard SAM compliant output. The code and executable are available at https://github.com/magicDGS/ReadTools.
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Affiliation(s)
- Daniel Gómez-Sánchez
- Institut für Populationsgenetik, Vetmeduni Vienna, Wien, Austria.,Vienna Graduate School of Population Genetics, Wien, Vienna
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