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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2020-02-01
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| Series: | Genomics, Proteomics & Bioinformatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1672022920300541 |
| _version_ | 1797369799064420352 |
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| author | Yongzhe Ren Yang Zhang Dandan Wang Fengying Liu Ying Fu Shaohua Xiang Li Su Jiancheng Li Heng Dai Bingding Huang |
| author_facet | Yongzhe Ren Yang Zhang Dandan Wang Fengying Liu Ying Fu Shaohua Xiang Li Su Jiancheng Li Heng Dai Bingding Huang |
| author_sort | Yongzhe Ren |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-08T17:52:07Z |
| format | Article |
| id | doaj.art-5d52f997dbb74c6d96f96497049d0b86 |
| institution | Directory Open Access Journal |
| issn | 1672-0229 |
| language | English |
| last_indexed | 2024-03-08T17:52:07Z |
| publishDate | 2020-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Genomics, Proteomics & Bioinformatics |
| spelling | doaj.art-5d52f997dbb74c6d96f96497049d0b862024-01-02T07:14:28ZengElsevierGenomics, Proteomics & Bioinformatics1672-02292020-02-011818190SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA SamplesYongzhe Ren0Yang Zhang1Dandan Wang2Fengying Liu3Ying Fu4Shaohua Xiang5Li Su6Jiancheng Li7Heng Dai8Bingding Huang91College of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China; 2Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China2Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China2Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China2Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China2Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China1College of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China3Department of Integrated Traditional and Western Medicine In Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China4Department of Radiation Oncology, Fujian Medical University Cancer Hospital and Fujian Cancer Hospital, Fuzhou 350014, China2Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China1College of Big Data and Internet, Shenzhen Technology University, Shenzhen 518118, China; 2Department of Research and Development, Sinotech Genomics Inc., Kanxing Road 3399, Shanghai 201314, China; Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Science, Shenzhen 518005, China; Corresponding author.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.http://www.sciencedirect.com/science/article/pii/S1672022920300541Next generation sequencingLiquid biopsyCirculating tumor DNADuplex sequencingLow frequency variant |
| spellingShingle | Yongzhe Ren Yang Zhang Dandan Wang Fengying Liu Ying Fu Shaohua Xiang Li Su Jiancheng Li Heng Dai Bingding Huang SinoDuplex: An Improved Duplex Sequencing Approach to Detect Low-frequency Variants in Plasma cfDNA Samples Genomics, Proteomics & Bioinformatics Next generation sequencing Liquid biopsy Circulating tumor DNA Duplex sequencing Low frequency variant |
| 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 | Next generation sequencing Liquid biopsy Circulating tumor DNA Duplex sequencing Low frequency variant |
| url | http://www.sciencedirect.com/science/article/pii/S1672022920300541 |
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