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      Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels

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          Abstract

          Background

          With the expanded availability of next generation sequencing (NGS)-based clinical genetic tests, clinicians seeking to test patients with Mendelian diseases must weigh the superior coverage of targeted gene panels with the greater number of genes included in whole exome sequencing (WES) when considering their first-tier testing approach. Here, we use an in silico analysis to predict the analytic sensitivity of WES using pathogenic variants identified on targeted NGS panels as a reference.

          Methods

          Corresponding nucleotide positions for 1533 different alterations classified as pathogenic or likely pathogenic identified on targeted NGS multi-gene panel tests in our laboratory were interrogated in data from 100 randomly-selected clinical WES samples to quantify the sequence coverage at each position. Pathogenic variants represented 91 genes implicated in hereditary cancer, X-linked intellectual disability, primary ciliary dyskinesia, Marfan syndrome/aortic aneurysms, cardiomyopathies and arrhythmias.

          Results

          When assessing coverage among 100 individual WES samples for each pathogenic variant (153,300 individual assessments), 99.7% (n = 152,798) would likely have been detected on WES. All pathogenic variants had at least some coverage on exome sequencing, with a total of 97.3% (n = 1491) detectable across all 100 individuals. For the remaining 42 pathogenic variants, the number of WES samples with adequate coverage ranged from 35 to 99. Factors such as location in GC-rich, repetitive, or homologous regions likely explain why some of these alterations were not detected across all samples. To validate study findings, a similar analysis was performed against coverage data from 60,706 exomes available through the Exome Aggregation Consortium (ExAC). Results from this validation confirmed that 98.6% (91,743,296/93,062,298) of pathogenic variants demonstrated adequate depth for detection.

          Conclusions

          Results from this in silico analysis suggest that exome sequencing may achieve a diagnostic yield similar to panel-based testing for Mendelian diseases.

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          Most cited references15

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          Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results.

          Genetic testing of cancer susceptibility genes is now widely applied in clinical practice to predict risk of developing cancer. In general, sequence-based testing of germline DNA is used to determine whether an individual carries a change that is clearly likely to disrupt normal gene function. Genetic testing may detect changes that are clearly pathogenic, clearly neutral, or variants of unclear clinical significance. Such variants present a considerable challenge to the diagnostic laboratory and the receiving clinician in terms of interpretation and clear presentation of the implications of the result to the patient. There does not appear to be a consistent approach to interpreting and reporting the clinical significance of variants either among genes or among laboratories. The potential for confusion among clinicians and patients is considerable and misinterpretation may lead to inappropriate clinical consequences. In this article we review the current state of sequence-based genetic testing, describe other standardized reporting systems used in oncology, and propose a standardized classification system for application to sequence-based results for cancer predisposition genes. We suggest a system of five classes of variants based on the degree of likelihood of pathogenicity. Each class is associated with specific recommendations for clinical management of at-risk relatives that will depend on the syndrome. We propose that panels of experts on each cancer predisposition syndrome facilitate the classification scheme and designate appropriate surveillance and cancer management guidelines. The international adoption of a standardized reporting system should improve the clinical utility of sequence-based genetic tests to predict cancer risk. (c) 2008 Wiley-Liss, Inc.
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            Performance comparison of exome DNA sequencing technologies.

            Whole exome sequencing by high-throughput sequencing of target-enriched genomic DNA (exome-seq) has become common in basic and translational research as a means of interrogating the interpretable part of the human genome at relatively low cost. We present a comparison of three major commercial exome sequencing platforms from Agilent, Illumina and Nimblegen applied to the same human blood sample. Our results suggest that the Nimblegen platform, which is the only one to use high-density overlapping baits, covers fewer genomic regions than the other platforms but requires the least amount of sequencing to sensitively detect small variants. Agilent and Illumina are able to detect a greater total number of variants with additional sequencing. Illumina captures untranslated regions, which are not targeted by the Nimblegen and Agilent platforms. We also compare exome sequencing and whole genome sequencing (WGS) of the same sample, demonstrating that exome sequencing can detect additional small variants missed by WGS.
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              Actionable, pathogenic incidental findings in 1,000 participants' exomes.

              The incorporation of genomics into medicine is stimulating interest on the return of incidental findings (IFs) from exome and genome sequencing. However, no large-scale study has yet estimated the number of expected actionable findings per individual; therefore, we classified actionable pathogenic single-nucleotide variants in 500 European- and 500 African-descent participants randomly selected from the National Heart, Lung, and Blood Institute Exome Sequencing Project. The 1,000 individuals were screened for variants in 114 genes selected by an expert panel for their association with medically actionable genetic conditions possibly undiagnosed in adults. Among the 1,000 participants, 585 instances of 239 unique variants were identified as disease causing in the Human Gene Mutation Database (HGMD). The primary literature supporting the variants' pathogenicity was reviewed. Of the identified IFs, only 16 unique autosomal-dominant variants in 17 individuals were assessed to be pathogenic or likely pathogenic, and one participant had two pathogenic variants for an autosomal-recessive disease. Furthermore, one pathogenic and four likely pathogenic variants not listed as disease causing in HGMD were identified. These data can provide an estimate of the frequency (∼3.4% for European descent and ∼1.2% for African descent) of the high-penetrance actionable pathogenic or likely pathogenic variants in adults. The 23 participants with pathogenic or likely pathogenic variants were disproportionately of European (17) versus African (6) descent. The process of classifying these variants underscores the need for a more comprehensive and diverse centralized resource to provide curated information on pathogenicity for clinical use to minimize health disparities in genomic medicine. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2 February 2017
                2017
                : 12
                : 2
                : e0170843
                Affiliations
                [1 ]Department of Clinical Diagnostics, Ambry Genetics, Aliso Viejo, California, United States of America
                [2 ]Department of Pediatrics, Division of Genetics and Genomic Medicine, University of California Irvine, Irvine, California, United States of America
                Tel Aviv University, ISRAEL
                Author notes

                Competing Interests: All authors were full time paid employees of Ambry Genetics at the time the study was conducted. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                • Conceptualization: HL.

                • Formal analysis: HL H-ML JC HV.

                • Investigation: JC WM HV.

                • Methodology: HL KDF LS ST SB ECC.

                • Software: WM JC H-ML.

                • Writing – original draft: HL KDF LS ST ECC.

                • Writing – review & editing: HL KDF HV H-ML WM LS ST JC SB ECC.

                Article
                PONE-D-16-35058
                10.1371/journal.pone.0170843
                5289469
                28152038
                3dea02b5-95ec-45be-b9e4-d9287dd13597
                © 2017 LaDuca et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 1 September 2016
                : 11 January 2017
                Page count
                Figures: 0, Tables: 2, Pages: 11
                Funding
                Ambry Genetics provided support in the form of salaries for all authors, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and life sciences
                Molecular biology
                Molecular biology techniques
                Sequencing techniques
                DNA sequencing
                Next-Generation Sequencing
                Research and analysis methods
                Molecular biology techniques
                Sequencing techniques
                DNA sequencing
                Next-Generation Sequencing
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Next-Generation Sequencing
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Transcriptome Analysis
                Next-Generation Sequencing
                Biology and Life Sciences
                Computational Biology
                Genome Complexity
                Introns
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Complexity
                Introns
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Physical Sciences
                Chemistry
                Polymer Chemistry
                Macromolecules
                Polymers
                Physical Sciences
                Materials Science
                Materials by Structure
                Polymers
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Sequencing Techniques
                Nucleotide Sequencing
                Research and Analysis Methods
                Molecular Biology Techniques
                Sequencing Techniques
                Nucleotide Sequencing
                Biology and life sciences
                Molecular biology
                Molecular biology techniques
                Sequencing techniques
                DNA sequencing
                Gene Sequencing
                Research and analysis methods
                Molecular biology techniques
                Sequencing techniques
                DNA sequencing
                Gene Sequencing
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Sequence Alignment
                Medicine and Health Sciences
                Diagnostic Medicine
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

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