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Achieving high-sensitivity for clinical applications using augmented exome sequencing
BACKGROUND: Whole exome sequencing is increasingly used for the clinical evaluation of genetic disease, yet the variation of coverage and sensitivity over medically relevant parts of the genome remains poorly understood. Several sequencing-based assays continue to provide coverage that is inadequate...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4534066/ https://www.ncbi.nlm.nih.gov/pubmed/26269718 http://dx.doi.org/10.1186/s13073-015-0197-4 |
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author | Patwardhan, Anil Harris, Jason Leng, Nan Bartha, Gabor Church, Deanna M. Luo, Shujun Haudenschild, Christian Pratt, Mark Zook, Justin Salit, Marc Tirch, Jeanie Morra, Massimo Chervitz, Stephen Li, Ming Clark, Michael Garcia, Sarah Chandratillake, Gemma Kirk, Scott Ashley, Euan Snyder, Michael Altman, Russ Bustamante, Carlos Butte, Atul J. West, John Chen, Richard |
author_facet | Patwardhan, Anil Harris, Jason Leng, Nan Bartha, Gabor Church, Deanna M. Luo, Shujun Haudenschild, Christian Pratt, Mark Zook, Justin Salit, Marc Tirch, Jeanie Morra, Massimo Chervitz, Stephen Li, Ming Clark, Michael Garcia, Sarah Chandratillake, Gemma Kirk, Scott Ashley, Euan Snyder, Michael Altman, Russ Bustamante, Carlos Butte, Atul J. West, John Chen, Richard |
author_sort | Patwardhan, Anil |
collection | PubMed |
description | BACKGROUND: Whole exome sequencing is increasingly used for the clinical evaluation of genetic disease, yet the variation of coverage and sensitivity over medically relevant parts of the genome remains poorly understood. Several sequencing-based assays continue to provide coverage that is inadequate for clinical assessment. METHODS: Using sequence data obtained from the NA12878 reference sample and pre-defined lists of medically-relevant protein-coding and noncoding sequences, we compared the breadth and depth of coverage obtained among four commercial exome capture platforms and whole genome sequencing. In addition, we evaluated the performance of an augmented exome strategy, ACE, that extends coverage in medically relevant regions and enhances coverage in areas that are challenging to sequence. Leveraging reference call-sets, we also examined the effects of improved coverage on variant detection sensitivity. RESULTS: We observed coverage shortfalls with each of the conventional exome-capture and whole-genome platforms across several medically interpretable genes. These gaps included areas of the genome required for reporting recently established secondary findings (ACMG) and known disease-associated loci. The augmented exome strategy recovered many of these gaps, resulting in improved coverage in these areas. At clinically-relevant coverage levels (100 % bases covered at ≥20×), ACE improved coverage among genes in the medically interpretable genome (>90 % covered relative to 10-78 % with other platforms), the set of ACMG secondary finding genes (91 % covered relative to 4-75 % with other platforms) and a subset of variants known to be associated with human disease (99 % covered relative to 52-95 % with other platforms). Improved coverage translated into improvements in sensitivity, with ACE variant detection sensitivities (>97.5 % SNVs, >92.5 % InDels) exceeding that observed with conventional whole-exome and whole-genome platforms. CONCLUSIONS: Clinicians should consider analytical performance when making clinical assessments, given that even a few missed variants can lead to reporting false negative results. An augmented exome strategy provides a level of coverage not achievable with other platforms, thus addressing concerns regarding the lack of sensitivity in clinically important regions. In clinical applications where comprehensive coverage of medically interpretable areas of the genome requires higher localized sequencing depth, an augmented exome approach offers both cost and performance advantages over other sequencing-based tests. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-015-0197-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4534066 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45340662015-08-13 Achieving high-sensitivity for clinical applications using augmented exome sequencing Patwardhan, Anil Harris, Jason Leng, Nan Bartha, Gabor Church, Deanna M. Luo, Shujun Haudenschild, Christian Pratt, Mark Zook, Justin Salit, Marc Tirch, Jeanie Morra, Massimo Chervitz, Stephen Li, Ming Clark, Michael Garcia, Sarah Chandratillake, Gemma Kirk, Scott Ashley, Euan Snyder, Michael Altman, Russ Bustamante, Carlos Butte, Atul J. West, John Chen, Richard Genome Med Research BACKGROUND: Whole exome sequencing is increasingly used for the clinical evaluation of genetic disease, yet the variation of coverage and sensitivity over medically relevant parts of the genome remains poorly understood. Several sequencing-based assays continue to provide coverage that is inadequate for clinical assessment. METHODS: Using sequence data obtained from the NA12878 reference sample and pre-defined lists of medically-relevant protein-coding and noncoding sequences, we compared the breadth and depth of coverage obtained among four commercial exome capture platforms and whole genome sequencing. In addition, we evaluated the performance of an augmented exome strategy, ACE, that extends coverage in medically relevant regions and enhances coverage in areas that are challenging to sequence. Leveraging reference call-sets, we also examined the effects of improved coverage on variant detection sensitivity. RESULTS: We observed coverage shortfalls with each of the conventional exome-capture and whole-genome platforms across several medically interpretable genes. These gaps included areas of the genome required for reporting recently established secondary findings (ACMG) and known disease-associated loci. The augmented exome strategy recovered many of these gaps, resulting in improved coverage in these areas. At clinically-relevant coverage levels (100 % bases covered at ≥20×), ACE improved coverage among genes in the medically interpretable genome (>90 % covered relative to 10-78 % with other platforms), the set of ACMG secondary finding genes (91 % covered relative to 4-75 % with other platforms) and a subset of variants known to be associated with human disease (99 % covered relative to 52-95 % with other platforms). Improved coverage translated into improvements in sensitivity, with ACE variant detection sensitivities (>97.5 % SNVs, >92.5 % InDels) exceeding that observed with conventional whole-exome and whole-genome platforms. CONCLUSIONS: Clinicians should consider analytical performance when making clinical assessments, given that even a few missed variants can lead to reporting false negative results. An augmented exome strategy provides a level of coverage not achievable with other platforms, thus addressing concerns regarding the lack of sensitivity in clinically important regions. In clinical applications where comprehensive coverage of medically interpretable areas of the genome requires higher localized sequencing depth, an augmented exome approach offers both cost and performance advantages over other sequencing-based tests. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13073-015-0197-4) contains supplementary material, which is available to authorized users. BioMed Central 2015-07-16 /pmc/articles/PMC4534066/ /pubmed/26269718 http://dx.doi.org/10.1186/s13073-015-0197-4 Text en © Patwardhan et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Patwardhan, Anil Harris, Jason Leng, Nan Bartha, Gabor Church, Deanna M. Luo, Shujun Haudenschild, Christian Pratt, Mark Zook, Justin Salit, Marc Tirch, Jeanie Morra, Massimo Chervitz, Stephen Li, Ming Clark, Michael Garcia, Sarah Chandratillake, Gemma Kirk, Scott Ashley, Euan Snyder, Michael Altman, Russ Bustamante, Carlos Butte, Atul J. West, John Chen, Richard Achieving high-sensitivity for clinical applications using augmented exome sequencing |
title | Achieving high-sensitivity for clinical applications using augmented exome sequencing |
title_full | Achieving high-sensitivity for clinical applications using augmented exome sequencing |
title_fullStr | Achieving high-sensitivity for clinical applications using augmented exome sequencing |
title_full_unstemmed | Achieving high-sensitivity for clinical applications using augmented exome sequencing |
title_short | Achieving high-sensitivity for clinical applications using augmented exome sequencing |
title_sort | achieving high-sensitivity for clinical applications using augmented exome sequencing |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4534066/ https://www.ncbi.nlm.nih.gov/pubmed/26269718 http://dx.doi.org/10.1186/s13073-015-0197-4 |
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