RSV-GenoScan:用于全基因组人类呼吸道合胞病毒 (RSV) 序列分析的自动流水线

IF 2.2 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS Journal of virological methods Pub Date : 2024-04-06 DOI:10.1016/j.jviromet.2024.114938
Alexandre Dosbaa , Romane Guilbaud , Anna-Maria Franco Yusti , Valentine Marie Ferré , Charlotte Charpentier , Diane Descamps , Quentin Le Hingrat , Romain Coppée
{"title":"RSV-GenoScan:用于全基因组人类呼吸道合胞病毒 (RSV) 序列分析的自动流水线","authors":"Alexandre Dosbaa ,&nbsp;Romane Guilbaud ,&nbsp;Anna-Maria Franco Yusti ,&nbsp;Valentine Marie Ferré ,&nbsp;Charlotte Charpentier ,&nbsp;Diane Descamps ,&nbsp;Quentin Le Hingrat ,&nbsp;Romain Coppée","doi":"10.1016/j.jviromet.2024.114938","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Advances in high-throughput sequencing (HTS) technologies and reductions in sequencing costs have revolutionised the study of genomics and molecular biology by making whole-genome sequencing (WGS) accessible to many laboratories. However, the analysis of WGS data requires significant computational effort, which is the major drawback in implementing WGS as a routine laboratory technique.</p></div><div><h3>Objective</h3><p>Automated pipelines have been developed to overcome this issue, but they do not exist for all organisms. This is the case for human respiratory syncytial virus (RSV), which is a leading cause of lower respiratory tract infections in infants, the elderly, and immunocompromised adults.</p></div><div><h3>Results</h3><p>We present RSV-GenoScan, a fast and easy-to-use pipeline for WGS analysis of RSV generated by HTS on Illumina or Nanopore platforms. RSV-GenoScan automates the WGS analysis steps directly from the raw sequence data. The pipeline filters the sequence data, maps the reads to the RSV reference genomes, generates a consensus sequence, identifies the RSV subgroup, and lists amino acid mutations, insertions and deletions in the F and G viral genes. This enables the rapid identification of mutations in these coding genes that are known to confer resistance to monoclonal antibodies.</p></div><div><h3>Availability</h3><p>RSV-GenoScan is freely available at <span>https://github.com/AlexandreD-bio/RSV-GenoScan</span><svg><path></path></svg>.</p></div>","PeriodicalId":17663,"journal":{"name":"Journal of virological methods","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0166093424000624/pdfft?md5=f24cdd06dbedfd40bbdb57ad56f718a0&pid=1-s2.0-S0166093424000624-main.pdf","citationCount":"0","resultStr":"{\"title\":\"RSV-GenoScan: An automated pipeline for whole-genome human respiratory syncytial virus (RSV) sequence analysis\",\"authors\":\"Alexandre Dosbaa ,&nbsp;Romane Guilbaud ,&nbsp;Anna-Maria Franco Yusti ,&nbsp;Valentine Marie Ferré ,&nbsp;Charlotte Charpentier ,&nbsp;Diane Descamps ,&nbsp;Quentin Le Hingrat ,&nbsp;Romain Coppée\",\"doi\":\"10.1016/j.jviromet.2024.114938\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Advances in high-throughput sequencing (HTS) technologies and reductions in sequencing costs have revolutionised the study of genomics and molecular biology by making whole-genome sequencing (WGS) accessible to many laboratories. However, the analysis of WGS data requires significant computational effort, which is the major drawback in implementing WGS as a routine laboratory technique.</p></div><div><h3>Objective</h3><p>Automated pipelines have been developed to overcome this issue, but they do not exist for all organisms. This is the case for human respiratory syncytial virus (RSV), which is a leading cause of lower respiratory tract infections in infants, the elderly, and immunocompromised adults.</p></div><div><h3>Results</h3><p>We present RSV-GenoScan, a fast and easy-to-use pipeline for WGS analysis of RSV generated by HTS on Illumina or Nanopore platforms. RSV-GenoScan automates the WGS analysis steps directly from the raw sequence data. The pipeline filters the sequence data, maps the reads to the RSV reference genomes, generates a consensus sequence, identifies the RSV subgroup, and lists amino acid mutations, insertions and deletions in the F and G viral genes. This enables the rapid identification of mutations in these coding genes that are known to confer resistance to monoclonal antibodies.</p></div><div><h3>Availability</h3><p>RSV-GenoScan is freely available at <span>https://github.com/AlexandreD-bio/RSV-GenoScan</span><svg><path></path></svg>.</p></div>\",\"PeriodicalId\":17663,\"journal\":{\"name\":\"Journal of virological methods\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0166093424000624/pdfft?md5=f24cdd06dbedfd40bbdb57ad56f718a0&pid=1-s2.0-S0166093424000624-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of virological methods\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0166093424000624\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of virological methods","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0166093424000624","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

摘要

背景高通量测序(HTS)技术的发展和测序成本的降低使许多实验室都能进行全基因组测序(WGS),从而彻底改变了基因组学和分子生物学研究。然而,WGS 数据的分析需要大量的计算工作,这是将 WGS 作为实验室常规技术的主要缺点。人类呼吸道合胞病毒(RSV)就是这种情况,它是婴儿、老人和免疫力低下的成年人下呼吸道感染的主要病因。结果我们介绍了 RSV-GenoScan,这是一种快速、易用的管道,用于在 Illumina 或 Nanopore 平台上对 HTS 产生的 RSV 进行 WGS 分析。RSV-GenoScan 可直接根据原始序列数据自动执行 WGS 分析步骤。该管道过滤序列数据,将读数映射到 RSV 参考基因组,生成共识序列,识别 RSV 亚群,并列出 F 和 G 病毒基因中的氨基酸突变、插入和缺失。这样就能快速识别这些编码基因中已知会对单克隆抗体产生抗性的突变。RSV-GenoScan 可在 https://github.com/AlexandreD-bio/RSV-GenoScan 免费获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
RSV-GenoScan: An automated pipeline for whole-genome human respiratory syncytial virus (RSV) sequence analysis

Background

Advances in high-throughput sequencing (HTS) technologies and reductions in sequencing costs have revolutionised the study of genomics and molecular biology by making whole-genome sequencing (WGS) accessible to many laboratories. However, the analysis of WGS data requires significant computational effort, which is the major drawback in implementing WGS as a routine laboratory technique.

Objective

Automated pipelines have been developed to overcome this issue, but they do not exist for all organisms. This is the case for human respiratory syncytial virus (RSV), which is a leading cause of lower respiratory tract infections in infants, the elderly, and immunocompromised adults.

Results

We present RSV-GenoScan, a fast and easy-to-use pipeline for WGS analysis of RSV generated by HTS on Illumina or Nanopore platforms. RSV-GenoScan automates the WGS analysis steps directly from the raw sequence data. The pipeline filters the sequence data, maps the reads to the RSV reference genomes, generates a consensus sequence, identifies the RSV subgroup, and lists amino acid mutations, insertions and deletions in the F and G viral genes. This enables the rapid identification of mutations in these coding genes that are known to confer resistance to monoclonal antibodies.

Availability

RSV-GenoScan is freely available at https://github.com/AlexandreD-bio/RSV-GenoScan.

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
CiteScore
5.80
自引率
0.00%
发文量
209
审稿时长
41 days
期刊介绍: The Journal of Virological Methods focuses on original, high quality research papers that describe novel and comprehensively tested methods which enhance human, animal, plant, bacterial or environmental virology and prions research and discovery. The methods may include, but not limited to, the study of: Viral components and morphology- Virus isolation, propagation and development of viral vectors- Viral pathogenesis, oncogenesis, vaccines and antivirals- Virus replication, host-pathogen interactions and responses- Virus transmission, prevention, control and treatment- Viral metagenomics and virome- Virus ecology, adaption and evolution- Applied virology such as nanotechnology- Viral diagnosis with novelty and comprehensive evaluation. We seek articles, systematic reviews, meta-analyses and laboratory protocols that include comprehensive technical details with statistical confirmations that provide validations against current best practice, international standards or quality assurance programs and which advance knowledge in virology leading to improved medical, veterinary or agricultural practices and management.
期刊最新文献
Rapid detection of bat coronaviruses from fecal samples using loop-mediated isothermal amplification assay in the field Establishment of a reverse genetics system for virulent systemic feline calicivirus using circular polymerase extension reaction Real-time quantitative reverse transcription PCR assay for the detection of Nuomin virus – An emerging tick-borne virus Efficient and accurate BmNPV bacmid editing system by two-step golden gate assembly Carboxy-PEG-thiol functionalized gold nanoparticle conjugates for the detection of SARS-CoV-2: Detection tools and analytical method development
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1