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SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples
Accurate detection of low frequency mutations from plasma cell-free DNA in blood using targeted next generation sequencing technology has shown promising benefits in clinical settings. Duplex sequencing technology is the most commonly used approach in liquid biopsies. Unique molecular identifiers ar...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393544/ https://www.ncbi.nlm.nih.gov/pubmed/32428603 http://dx.doi.org/10.1016/j.gpb.2020.02.003 |
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author | Ren, Yongzhe Zhang, Yang Wang, Dandan Liu, Fengying Fu, Ying Xiang, Shaohua Su, Li Li, Jiancheng Dai, Heng Huang, Bingding |
author_facet | Ren, Yongzhe Zhang, Yang Wang, Dandan Liu, Fengying Fu, Ying Xiang, Shaohua Su, Li Li, Jiancheng Dai, Heng Huang, Bingding |
author_sort | Ren, Yongzhe |
collection | PubMed |
description | Accurate detection of low frequency mutations from plasma cell-free DNA in blood using targeted next generation sequencing technology has shown promising benefits in clinical settings. Duplex sequencing technology is the most commonly used approach in liquid biopsies. Unique molecular identifiers are attached to each double-stranded DNA template, followed by production of low-error consensus sequences to detect low frequency variants. However, high sequencing costs have hindered application of this approach in clinical practice. Here, we have developed an improved duplex sequencing approach called SinoDuplex, which utilizes a pool of adapters containing pre-defined barcode sequences to generate far fewer barcode combinations than with random sequences, and implemented a novel computational analysis algorithm to generate duplex consensus sequences more precisely. SinoDuplex increased the output of duplex sequencing technology, making it more cost-effective. We evaluated our approach using reference standard samples and cell-free DNA samples from lung cancer patients. Our results showed that SinoDuplex has high sensitivity and specificity in detecting very low allele frequency mutations. The source code for SinoDuplex is freely available at https://github.com/SinOncology/sinoduplex. |
format | Online Article Text |
id | pubmed-7393544 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-73935442020-08-04 SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples Ren, Yongzhe Zhang, Yang Wang, Dandan Liu, Fengying Fu, Ying Xiang, Shaohua Su, Li Li, Jiancheng Dai, Heng Huang, Bingding Genomics Proteomics Bioinformatics Application Note Accurate detection of low frequency mutations from plasma cell-free DNA in blood using targeted next generation sequencing technology has shown promising benefits in clinical settings. Duplex sequencing technology is the most commonly used approach in liquid biopsies. Unique molecular identifiers are attached to each double-stranded DNA template, followed by production of low-error consensus sequences to detect low frequency variants. However, high sequencing costs have hindered application of this approach in clinical practice. Here, we have developed an improved duplex sequencing approach called SinoDuplex, which utilizes a pool of adapters containing pre-defined barcode sequences to generate far fewer barcode combinations than with random sequences, and implemented a novel computational analysis algorithm to generate duplex consensus sequences more precisely. SinoDuplex increased the output of duplex sequencing technology, making it more cost-effective. We evaluated our approach using reference standard samples and cell-free DNA samples from lung cancer patients. Our results showed that SinoDuplex has high sensitivity and specificity in detecting very low allele frequency mutations. The source code for SinoDuplex is freely available at https://github.com/SinOncology/sinoduplex. Elsevier 2020-02 2020-05-16 /pmc/articles/PMC7393544/ /pubmed/32428603 http://dx.doi.org/10.1016/j.gpb.2020.02.003 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Application Note Ren, Yongzhe Zhang, Yang Wang, Dandan Liu, Fengying Fu, Ying Xiang, Shaohua Su, Li Li, Jiancheng Dai, Heng Huang, Bingding SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples |
title | SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples |
title_full | SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples |
title_fullStr | SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples |
title_full_unstemmed | SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples |
title_short | SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples |
title_sort | sinoduplex: an improved duplex sequencing approach to detect low-frequency variants in plasma cfdna samples |
topic | Application Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7393544/ https://www.ncbi.nlm.nih.gov/pubmed/32428603 http://dx.doi.org/10.1016/j.gpb.2020.02.003 |
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