Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels
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 conside...
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description | 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.
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.
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.
Results from this in silico analysis suggest that exome sequencing may achieve a diagnostic yield similar to panel-based testing for Mendelian diseases. |
doi_str_mv | 10.1371/journal.pone.0170843 |
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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.
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.
Results from this in silico analysis suggest that exome sequencing may achieve a diagnostic yield similar to panel-based testing for Mendelian diseases.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0170843</identifier><identifier>PMID: 28152038</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Aorta ; Biology and life sciences ; Cancer ; Care and treatment ; Clinical medicine ; Computer Simulation ; Consortia ; Diagnostic systems ; DNA Mutational Analysis - methods ; DNA Mutational Analysis - statistics & numerical data ; DNA sequencing ; Dyskinesia ; Exome ; Female ; Gene mutation ; Gene sequencing ; Genes ; Genetic Diseases, Inborn - diagnosis ; Genetic Diseases, Inborn - genetics ; Genetic screening ; Genetic Testing - methods ; Genetic Testing - statistics & numerical data ; Genetics ; Genome, Human ; Genomes ; Genomics ; High-Throughput Nucleotide Sequencing - methods ; High-Throughput Nucleotide Sequencing - statistics & numerical data ; Homology ; Humans ; Intellectual disabilities ; Male ; Marfan syndrome ; Marfan's syndrome ; Medical diagnosis ; Medicine and Health Sciences ; Mutation ; Panels ; Physical Sciences ; Primary ciliary dyskinesia ; Research and analysis methods ; Risk assessment ; Risk factors ; Sensitivity analysis ; Sequence Analysis, DNA - methods ; Sequence Analysis, DNA - statistics & numerical data</subject><ispartof>PloS one, 2017-02, Vol.12 (2), p.e0170843-e0170843</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 LaDuca et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2017 LaDuca et al 2017 LaDuca et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c725t-66b63dee3f79aa648b595b43d3ba3127e6d983512582ce6c44b51cc9e2a8f0b33</citedby><cites>FETCH-LOGICAL-c725t-66b63dee3f79aa648b595b43d3ba3127e6d983512582ce6c44b51cc9e2a8f0b33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289469/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289469/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28152038$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Shomron, Noam</contributor><creatorcontrib>LaDuca, Holly</creatorcontrib><creatorcontrib>Farwell, Kelly D</creatorcontrib><creatorcontrib>Vuong, Huy</creatorcontrib><creatorcontrib>Lu, Hsiao-Mei</creatorcontrib><creatorcontrib>Mu, Wenbo</creatorcontrib><creatorcontrib>Shahmirzadi, Layla</creatorcontrib><creatorcontrib>Tang, Sha</creatorcontrib><creatorcontrib>Chen, Jefferey</creatorcontrib><creatorcontrib>Bhide, Shruti</creatorcontrib><creatorcontrib>Chao, Elizabeth C</creatorcontrib><title>Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>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.
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.
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.
Results from this in silico analysis suggest that exome sequencing may achieve a diagnostic yield similar to panel-based testing for Mendelian diseases.</description><subject>Analysis</subject><subject>Aorta</subject><subject>Biology and life sciences</subject><subject>Cancer</subject><subject>Care and treatment</subject><subject>Clinical medicine</subject><subject>Computer Simulation</subject><subject>Consortia</subject><subject>Diagnostic systems</subject><subject>DNA Mutational Analysis - methods</subject><subject>DNA Mutational Analysis - statistics & numerical data</subject><subject>DNA sequencing</subject><subject>Dyskinesia</subject><subject>Exome</subject><subject>Female</subject><subject>Gene mutation</subject><subject>Gene sequencing</subject><subject>Genes</subject><subject>Genetic Diseases, Inborn - diagnosis</subject><subject>Genetic Diseases, Inborn - genetics</subject><subject>Genetic screening</subject><subject>Genetic Testing - methods</subject><subject>Genetic Testing - statistics & numerical data</subject><subject>Genetics</subject><subject>Genome, Human</subject><subject>Genomes</subject><subject>Genomics</subject><subject>High-Throughput Nucleotide Sequencing - methods</subject><subject>High-Throughput Nucleotide Sequencing - statistics & numerical data</subject><subject>Homology</subject><subject>Humans</subject><subject>Intellectual disabilities</subject><subject>Male</subject><subject>Marfan syndrome</subject><subject>Marfan's syndrome</subject><subject>Medical diagnosis</subject><subject>Medicine and Health Sciences</subject><subject>Mutation</subject><subject>Panels</subject><subject>Physical Sciences</subject><subject>Primary ciliary dyskinesia</subject><subject>Research and analysis methods</subject><subject>Risk assessment</subject><subject>Risk factors</subject><subject>Sensitivity analysis</subject><subject>Sequence Analysis, DNA - methods</subject><subject>Sequence Analysis, DNA - statistics & numerical data</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNk01r3DAQhk1padK0_6C0htLSHnYrWR-WLoEQ0nYhEOjXVcjy2KtgS1vJDum_r3bXCeuSQ_DBYvzMO-NXM1n2GqMlJiX-fO3H4HS33HgHS4RLJCh5kh1jSYoFLxB5enA-yl7EeI0QI4Lz59lRITBLYXGcVRe3voc8wp8RnLGuzY2_gRDzUyne577J-3HQg_Uu5rYGN9jGQp17lw86tDCks4PbIW_BQdhxh1Ib7aCLL7Nnje4ivJreJ9mvLxc_z78tLq--rs7PLhemLNiw4LzipAYgTSm15lRUTLKKkppUmuCiBF5LQRgumCgMcENpxbAxEgotGlQRcpK93etuOh_VZE9UWHBKEUOFTMRqT9ReX6tNsL0Of5XXVu0CPrRKh8GaDpQGDE2qhhkBWpVGylogiiVjnHGM66R1OlUbqx5qk7wJupuJzr84u1atv1GsEJLybTMfJ4Hgk2NxUL2NBroumebHXd-CUIw4fwzKGBZIooS--w992IiJanX6V-san1o0W1F1RktZJufxtuzyASo9NfTWpLFrbIrPEj7NEhIzpOlo9RijWv34_nj26vec_XDArkF3wzr6btzN5Ryke9AEH2OA5v4-MFLbrblzQ223Rk1bk9LeHN7lfdLdmpB_vtkRNw</recordid><startdate>20170202</startdate><enddate>20170202</enddate><creator>LaDuca, Holly</creator><creator>Farwell, Kelly D</creator><creator>Vuong, Huy</creator><creator>Lu, Hsiao-Mei</creator><creator>Mu, Wenbo</creator><creator>Shahmirzadi, Layla</creator><creator>Tang, Sha</creator><creator>Chen, Jefferey</creator><creator>Bhide, Shruti</creator><creator>Chao, Elizabeth C</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20170202</creationdate><title>Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels</title><author>LaDuca, Holly ; Farwell, Kelly D ; Vuong, Huy ; Lu, Hsiao-Mei ; Mu, Wenbo ; Shahmirzadi, Layla ; Tang, Sha ; Chen, Jefferey ; Bhide, Shruti ; Chao, Elizabeth C</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c725t-66b63dee3f79aa648b595b43d3ba3127e6d983512582ce6c44b51cc9e2a8f0b33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Analysis</topic><topic>Aorta</topic><topic>Biology and life sciences</topic><topic>Cancer</topic><topic>Care and treatment</topic><topic>Clinical medicine</topic><topic>Computer Simulation</topic><topic>Consortia</topic><topic>Diagnostic systems</topic><topic>DNA Mutational Analysis - methods</topic><topic>DNA Mutational Analysis - statistics & numerical data</topic><topic>DNA sequencing</topic><topic>Dyskinesia</topic><topic>Exome</topic><topic>Female</topic><topic>Gene mutation</topic><topic>Gene sequencing</topic><topic>Genes</topic><topic>Genetic Diseases, Inborn - diagnosis</topic><topic>Genetic Diseases, Inborn - genetics</topic><topic>Genetic screening</topic><topic>Genetic Testing - methods</topic><topic>Genetic Testing - statistics & numerical data</topic><topic>Genetics</topic><topic>Genome, Human</topic><topic>Genomes</topic><topic>Genomics</topic><topic>High-Throughput Nucleotide Sequencing - methods</topic><topic>High-Throughput Nucleotide Sequencing - statistics & numerical data</topic><topic>Homology</topic><topic>Humans</topic><topic>Intellectual disabilities</topic><topic>Male</topic><topic>Marfan syndrome</topic><topic>Marfan's syndrome</topic><topic>Medical diagnosis</topic><topic>Medicine and Health Sciences</topic><topic>Mutation</topic><topic>Panels</topic><topic>Physical Sciences</topic><topic>Primary ciliary dyskinesia</topic><topic>Research and analysis methods</topic><topic>Risk assessment</topic><topic>Risk factors</topic><topic>Sensitivity analysis</topic><topic>Sequence Analysis, DNA - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>LaDuca, Holly</au><au>Farwell, Kelly D</au><au>Vuong, Huy</au><au>Lu, Hsiao-Mei</au><au>Mu, Wenbo</au><au>Shahmirzadi, Layla</au><au>Tang, Sha</au><au>Chen, Jefferey</au><au>Bhide, Shruti</au><au>Chao, Elizabeth C</au><au>Shomron, Noam</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2017-02-02</date><risdate>2017</risdate><volume>12</volume><issue>2</issue><spage>e0170843</spage><epage>e0170843</epage><pages>e0170843-e0170843</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>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.
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.
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.
Results from this in silico analysis suggest that exome sequencing may achieve a diagnostic yield similar to panel-based testing for Mendelian diseases.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28152038</pmid><doi>10.1371/journal.pone.0170843</doi><tpages>e0170843</tpages><oa>free_for_read</oa></addata></record> |
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recordid | cdi_plos_journals_1864405029 |
source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
subjects | Analysis Aorta Biology and life sciences Cancer Care and treatment Clinical medicine Computer Simulation Consortia Diagnostic systems DNA Mutational Analysis - methods DNA Mutational Analysis - statistics & numerical data DNA sequencing Dyskinesia Exome Female Gene mutation Gene sequencing Genes Genetic Diseases, Inborn - diagnosis Genetic Diseases, Inborn - genetics Genetic screening Genetic Testing - methods Genetic Testing - statistics & numerical data Genetics Genome, Human Genomes Genomics High-Throughput Nucleotide Sequencing - methods High-Throughput Nucleotide Sequencing - statistics & numerical data Homology Humans Intellectual disabilities Male Marfan syndrome Marfan's syndrome Medical diagnosis Medicine and Health Sciences Mutation Panels Physical Sciences Primary ciliary dyskinesia Research and analysis methods Risk assessment Risk factors Sensitivity analysis Sequence Analysis, DNA - methods Sequence Analysis, DNA - statistics & numerical data |
title | Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels |
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