用于快速DNA片段计数和基因分型的模糊测序仪

IF 26.8 1区 医学 Q1 ENGINEERING, BIOMEDICAL
Wenxiong Zhou, Li Kang, Shuo Qiao, Haifeng Duan, Chenghong Yin, Chao Liu, Zhizhao Liao, Mingchuan Tang, Ruiying Zhang, Lei Li, Lei Shi, Meijie Du, Yipeng Wang, Wentao Yue, Yan Xiao, Lin Di, Xiannian Zhang, Yuhong Pang, Mingkun Li, Lili Ren, Jianbin Wang, Zitian Chen, Yanyi Huang
{"title":"用于快速DNA片段计数和基因分型的模糊测序仪","authors":"Wenxiong Zhou, Li Kang, Shuo Qiao, Haifeng Duan, Chenghong Yin, Chao Liu, Zhizhao Liao, Mingchuan Tang, Ruiying Zhang, Lei Li, Lei Shi, Meijie Du, Yipeng Wang, Wentao Yue, Yan Xiao, Lin Di, Xiannian Zhang, Yuhong Pang, Mingkun Li, Lili Ren, Jianbin Wang, Zitian Chen, Yanyi Huang","doi":"10.1038/s41551-025-01430-8","DOIUrl":null,"url":null,"abstract":"<p>High-throughput sequencing technologies generate a vast number of DNA sequence reads simultaneously, which are subsequently analysed using the information contained within these fragmented reads. The assessment of sequencing technology relies on information efficiency, which measures the amount of information entropy produced per sequencing reaction cycle. Here we propose a fuzzy sequencing strategy that exhibits information efficiency more than twice that of currently prevailing cyclic reversible terminator sequencing methods. To validate our approach, we develop a fully functional and high-throughput fuzzy sequencer. This sequencer implements an efficient fluorogenic sequencing-by-synthesis chemistry and we test it across various application scenarios, including copy-number variation detection, non-invasive prenatal testing, transcriptome profiling, mutation genotyping and metagenomic profiling. Our findings demonstrate that the fuzzy sequencing strategy outperforms existing methods in terms of information efficiency and delivers accurate resequencing results with faster turnaround times.</p>","PeriodicalId":19063,"journal":{"name":"Nature Biomedical Engineering","volume":"280 1","pages":""},"PeriodicalIF":26.8000,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A fuzzy sequencer for rapid DNA fragment counting and genotyping\",\"authors\":\"Wenxiong Zhou, Li Kang, Shuo Qiao, Haifeng Duan, Chenghong Yin, Chao Liu, Zhizhao Liao, Mingchuan Tang, Ruiying Zhang, Lei Li, Lei Shi, Meijie Du, Yipeng Wang, Wentao Yue, Yan Xiao, Lin Di, Xiannian Zhang, Yuhong Pang, Mingkun Li, Lili Ren, Jianbin Wang, Zitian Chen, Yanyi Huang\",\"doi\":\"10.1038/s41551-025-01430-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>High-throughput sequencing technologies generate a vast number of DNA sequence reads simultaneously, which are subsequently analysed using the information contained within these fragmented reads. The assessment of sequencing technology relies on information efficiency, which measures the amount of information entropy produced per sequencing reaction cycle. Here we propose a fuzzy sequencing strategy that exhibits information efficiency more than twice that of currently prevailing cyclic reversible terminator sequencing methods. To validate our approach, we develop a fully functional and high-throughput fuzzy sequencer. This sequencer implements an efficient fluorogenic sequencing-by-synthesis chemistry and we test it across various application scenarios, including copy-number variation detection, non-invasive prenatal testing, transcriptome profiling, mutation genotyping and metagenomic profiling. Our findings demonstrate that the fuzzy sequencing strategy outperforms existing methods in terms of information efficiency and delivers accurate resequencing results with faster turnaround times.</p>\",\"PeriodicalId\":19063,\"journal\":{\"name\":\"Nature Biomedical Engineering\",\"volume\":\"280 1\",\"pages\":\"\"},\"PeriodicalIF\":26.8000,\"publicationDate\":\"2025-07-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Biomedical Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1038/s41551-025-01430-8\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Biomedical Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1038/s41551-025-01430-8","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0

摘要

高通量测序技术同时产生大量的DNA序列读取,随后使用这些片段读取中包含的信息对其进行分析。对测序技术的评价依赖于信息效率,它衡量每个测序反应周期产生的信息熵的数量。在这里,我们提出了一种模糊测序策略,其信息效率是目前流行的循环可逆终止序列方法的两倍以上。为了验证我们的方法,我们开发了一个功能齐全,高通量的模糊测序器。该测序仪实现了高效的荧光合成化学测序,我们在各种应用场景中对其进行了测试,包括拷贝数变异检测、无创产前检测、转录组分析、突变基因分型和宏基因组分析。我们的研究结果表明,模糊排序策略在信息效率方面优于现有的方法,并以更快的周转时间提供准确的重排序结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A fuzzy sequencer for rapid DNA fragment counting and genotyping

A fuzzy sequencer for rapid DNA fragment counting and genotyping

High-throughput sequencing technologies generate a vast number of DNA sequence reads simultaneously, which are subsequently analysed using the information contained within these fragmented reads. The assessment of sequencing technology relies on information efficiency, which measures the amount of information entropy produced per sequencing reaction cycle. Here we propose a fuzzy sequencing strategy that exhibits information efficiency more than twice that of currently prevailing cyclic reversible terminator sequencing methods. To validate our approach, we develop a fully functional and high-throughput fuzzy sequencer. This sequencer implements an efficient fluorogenic sequencing-by-synthesis chemistry and we test it across various application scenarios, including copy-number variation detection, non-invasive prenatal testing, transcriptome profiling, mutation genotyping and metagenomic profiling. Our findings demonstrate that the fuzzy sequencing strategy outperforms existing methods in terms of information efficiency and delivers accurate resequencing results with faster turnaround times.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Nature Biomedical Engineering
Nature Biomedical Engineering Medicine-Medicine (miscellaneous)
CiteScore
45.30
自引率
1.10%
发文量
138
期刊介绍: Nature Biomedical Engineering is an online-only monthly journal that was launched in January 2017. It aims to publish original research, reviews, and commentary focusing on applied biomedicine and health technology. The journal targets a diverse audience, including life scientists who are involved in developing experimental or computational systems and methods to enhance our understanding of human physiology. It also covers biomedical researchers and engineers who are engaged in designing or optimizing therapies, assays, devices, or procedures for diagnosing or treating diseases. Additionally, clinicians, who make use of research outputs to evaluate patient health or administer therapy in various clinical settings and healthcare contexts, are also part of the target audience.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信