Discriminating Clonotypes of Influenza A Virus Genes by Nanopore Sequencing

Influenza viruses still pose a serious threat to humans, and we have not yet been able to effectively predict future pandemic strains and prepare vaccines in advance. One of the main reasons is the high genetic diversity of influenza viruses. We do not know the individual clonotypes of a virus popul...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of molecular sciences 2021-09, Vol.22 (18), p.10069
Hauptverfasser: Cao, Ying, Liu, Haizhou, Yan, Yi, Liu, Wenjun, Liu, Di, Li, Jing
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 18
container_start_page 10069
container_title International journal of molecular sciences
container_volume 22
creator Cao, Ying
Liu, Haizhou
Yan, Yi
Liu, Wenjun
Liu, Di
Li, Jing
description Influenza viruses still pose a serious threat to humans, and we have not yet been able to effectively predict future pandemic strains and prepare vaccines in advance. One of the main reasons is the high genetic diversity of influenza viruses. We do not know the individual clonotypes of a virus population because some are the majority and others make up only a small fraction of the population. First-generation (FGS) and next-generation sequencing (NGS) technologies have inherent limitations that are unable to resolve a minority clonotype’s information in the virus population. Third-generation sequencing (TGS) technologies with ultra-long reads have the potential to solve this problem but have a high error rate. Here, we evaluated emerging direct RNA sequencing and cDNA sequencing with the MinION platform and established a novel approach that combines the high accuracy of Illumina sequencing technology and long reads of nanopore sequencing technology to resolve both variants and clonotypes of influenza virus. Furthermore, a new program was written to eliminate the effect of nanopore sequencing errors for the analysis of the results. By using this pipeline, we identified 47 clonotypes in our experiment. We conclude that this approach can quickly discriminate the clonotypes of virus genes, allowing researchers to understand virus adaptation and evolution at the population level.
doi_str_mv 10.3390/ijms221810069
format Article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8468007</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2577451573</sourcerecordid><originalsourceid>FETCH-LOGICAL-c392t-734a9d7dd5d300b7c4d28546e3419c24fe5f477a6fb62d22feb2c53a1b6edd523</originalsourceid><addsrcrecordid>eNpdkc1Lw0AQxRdRbK0evQe8eIluZr-Si1Cq1mLRgx_XZZNsakqyW3cTof71bmkR62kG5jePefMQOk_wFSEZvq6XrQdI0gRjnh2gYUIB4tCLwz_9AJ14v8QYCLDsGA0IZYIDwUP0eFv7wtVtbVRXm0U0aayx3XqlfWSraGaqptfmW0Xj6L12vY-m2oRRvo6elLEr63T0oj8DUoTlU3RUqcbrs10dobf7u9fJQzx_ns4m43lckAy6WBCqslKUJSsJxrkoaAkpo1wTmmQF0EqzigqheJVzKAEqnUPBiEpyrsMSkBG62equ-rzVZaFN51QjV8GGcmtpVS33J6b-kAv7JVPKU4xFELjcCTgbjvedbMMXdNMoo23vJTAhKEuYIAG9-Icube9MsLehOCWQ0jRQ8ZYqnPXe6er3mATLTUxyLybyA4UihPw</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2576432848</pqid></control><display><type>article</type><title>Discriminating Clonotypes of Influenza A Virus Genes by Nanopore Sequencing</title><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><creator>Cao, Ying ; Liu, Haizhou ; Yan, Yi ; Liu, Wenjun ; Liu, Di ; Li, Jing</creator><creatorcontrib>Cao, Ying ; Liu, Haizhou ; Yan, Yi ; Liu, Wenjun ; Liu, Di ; Li, Jing</creatorcontrib><description>Influenza viruses still pose a serious threat to humans, and we have not yet been able to effectively predict future pandemic strains and prepare vaccines in advance. One of the main reasons is the high genetic diversity of influenza viruses. We do not know the individual clonotypes of a virus population because some are the majority and others make up only a small fraction of the population. First-generation (FGS) and next-generation sequencing (NGS) technologies have inherent limitations that are unable to resolve a minority clonotype’s information in the virus population. Third-generation sequencing (TGS) technologies with ultra-long reads have the potential to solve this problem but have a high error rate. Here, we evaluated emerging direct RNA sequencing and cDNA sequencing with the MinION platform and established a novel approach that combines the high accuracy of Illumina sequencing technology and long reads of nanopore sequencing technology to resolve both variants and clonotypes of influenza virus. Furthermore, a new program was written to eliminate the effect of nanopore sequencing errors for the analysis of the results. By using this pipeline, we identified 47 clonotypes in our experiment. We conclude that this approach can quickly discriminate the clonotypes of virus genes, allowing researchers to understand virus adaptation and evolution at the population level.</description><identifier>ISSN: 1422-0067</identifier><identifier>ISSN: 1661-6596</identifier><identifier>EISSN: 1422-0067</identifier><identifier>DOI: 10.3390/ijms221810069</identifier><identifier>PMID: 34576230</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Ebola virus ; Epidemics ; Evolutionary genetics ; Genes ; Genetic diversity ; Genomes ; Influenza ; Influenza A ; Next-generation sequencing ; Pandemics ; Poultry ; Public health ; Viruses ; Zika virus</subject><ispartof>International journal of molecular sciences, 2021-09, Vol.22 (18), p.10069</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 by the authors. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c392t-734a9d7dd5d300b7c4d28546e3419c24fe5f477a6fb62d22feb2c53a1b6edd523</citedby><cites>FETCH-LOGICAL-c392t-734a9d7dd5d300b7c4d28546e3419c24fe5f477a6fb62d22feb2c53a1b6edd523</cites><orcidid>0000-0002-4289-452X ; 0000-0002-4727-088X ; 0000-0001-8195-3628 ; 0000-0001-9588-5291</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468007/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468007/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27923,27924,53790,53792</link.rule.ids></links><search><creatorcontrib>Cao, Ying</creatorcontrib><creatorcontrib>Liu, Haizhou</creatorcontrib><creatorcontrib>Yan, Yi</creatorcontrib><creatorcontrib>Liu, Wenjun</creatorcontrib><creatorcontrib>Liu, Di</creatorcontrib><creatorcontrib>Li, Jing</creatorcontrib><title>Discriminating Clonotypes of Influenza A Virus Genes by Nanopore Sequencing</title><title>International journal of molecular sciences</title><description>Influenza viruses still pose a serious threat to humans, and we have not yet been able to effectively predict future pandemic strains and prepare vaccines in advance. One of the main reasons is the high genetic diversity of influenza viruses. We do not know the individual clonotypes of a virus population because some are the majority and others make up only a small fraction of the population. First-generation (FGS) and next-generation sequencing (NGS) technologies have inherent limitations that are unable to resolve a minority clonotype’s information in the virus population. Third-generation sequencing (TGS) technologies with ultra-long reads have the potential to solve this problem but have a high error rate. Here, we evaluated emerging direct RNA sequencing and cDNA sequencing with the MinION platform and established a novel approach that combines the high accuracy of Illumina sequencing technology and long reads of nanopore sequencing technology to resolve both variants and clonotypes of influenza virus. Furthermore, a new program was written to eliminate the effect of nanopore sequencing errors for the analysis of the results. By using this pipeline, we identified 47 clonotypes in our experiment. We conclude that this approach can quickly discriminate the clonotypes of virus genes, allowing researchers to understand virus adaptation and evolution at the population level.</description><subject>Ebola virus</subject><subject>Epidemics</subject><subject>Evolutionary genetics</subject><subject>Genes</subject><subject>Genetic diversity</subject><subject>Genomes</subject><subject>Influenza</subject><subject>Influenza A</subject><subject>Next-generation sequencing</subject><subject>Pandemics</subject><subject>Poultry</subject><subject>Public health</subject><subject>Viruses</subject><subject>Zika virus</subject><issn>1422-0067</issn><issn>1661-6596</issn><issn>1422-0067</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpdkc1Lw0AQxRdRbK0evQe8eIluZr-Si1Cq1mLRgx_XZZNsakqyW3cTof71bmkR62kG5jePefMQOk_wFSEZvq6XrQdI0gRjnh2gYUIB4tCLwz_9AJ14v8QYCLDsGA0IZYIDwUP0eFv7wtVtbVRXm0U0aayx3XqlfWSraGaqptfmW0Xj6L12vY-m2oRRvo6elLEr63T0oj8DUoTlU3RUqcbrs10dobf7u9fJQzx_ns4m43lckAy6WBCqslKUJSsJxrkoaAkpo1wTmmQF0EqzigqheJVzKAEqnUPBiEpyrsMSkBG62equ-rzVZaFN51QjV8GGcmtpVS33J6b-kAv7JVPKU4xFELjcCTgbjvedbMMXdNMoo23vJTAhKEuYIAG9-Icube9MsLehOCWQ0jRQ8ZYqnPXe6er3mATLTUxyLybyA4UihPw</recordid><startdate>20210917</startdate><enddate>20210917</enddate><creator>Cao, Ying</creator><creator>Liu, Haizhou</creator><creator>Yan, Yi</creator><creator>Liu, Wenjun</creator><creator>Liu, Di</creator><creator>Li, Jing</creator><general>MDPI AG</general><general>MDPI</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-4289-452X</orcidid><orcidid>https://orcid.org/0000-0002-4727-088X</orcidid><orcidid>https://orcid.org/0000-0001-8195-3628</orcidid><orcidid>https://orcid.org/0000-0001-9588-5291</orcidid></search><sort><creationdate>20210917</creationdate><title>Discriminating Clonotypes of Influenza A Virus Genes by Nanopore Sequencing</title><author>Cao, Ying ; Liu, Haizhou ; Yan, Yi ; Liu, Wenjun ; Liu, Di ; Li, Jing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c392t-734a9d7dd5d300b7c4d28546e3419c24fe5f477a6fb62d22feb2c53a1b6edd523</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Ebola virus</topic><topic>Epidemics</topic><topic>Evolutionary genetics</topic><topic>Genes</topic><topic>Genetic diversity</topic><topic>Genomes</topic><topic>Influenza</topic><topic>Influenza A</topic><topic>Next-generation sequencing</topic><topic>Pandemics</topic><topic>Poultry</topic><topic>Public health</topic><topic>Viruses</topic><topic>Zika virus</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cao, Ying</creatorcontrib><creatorcontrib>Liu, Haizhou</creatorcontrib><creatorcontrib>Yan, Yi</creatorcontrib><creatorcontrib>Liu, Wenjun</creatorcontrib><creatorcontrib>Liu, Di</creatorcontrib><creatorcontrib>Li, Jing</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>International journal of molecular sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cao, Ying</au><au>Liu, Haizhou</au><au>Yan, Yi</au><au>Liu, Wenjun</au><au>Liu, Di</au><au>Li, Jing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Discriminating Clonotypes of Influenza A Virus Genes by Nanopore Sequencing</atitle><jtitle>International journal of molecular sciences</jtitle><date>2021-09-17</date><risdate>2021</risdate><volume>22</volume><issue>18</issue><spage>10069</spage><pages>10069-</pages><issn>1422-0067</issn><issn>1661-6596</issn><eissn>1422-0067</eissn><abstract>Influenza viruses still pose a serious threat to humans, and we have not yet been able to effectively predict future pandemic strains and prepare vaccines in advance. One of the main reasons is the high genetic diversity of influenza viruses. We do not know the individual clonotypes of a virus population because some are the majority and others make up only a small fraction of the population. First-generation (FGS) and next-generation sequencing (NGS) technologies have inherent limitations that are unable to resolve a minority clonotype’s information in the virus population. Third-generation sequencing (TGS) technologies with ultra-long reads have the potential to solve this problem but have a high error rate. Here, we evaluated emerging direct RNA sequencing and cDNA sequencing with the MinION platform and established a novel approach that combines the high accuracy of Illumina sequencing technology and long reads of nanopore sequencing technology to resolve both variants and clonotypes of influenza virus. Furthermore, a new program was written to eliminate the effect of nanopore sequencing errors for the analysis of the results. By using this pipeline, we identified 47 clonotypes in our experiment. We conclude that this approach can quickly discriminate the clonotypes of virus genes, allowing researchers to understand virus adaptation and evolution at the population level.</abstract><cop>Basel</cop><pub>MDPI AG</pub><pmid>34576230</pmid><doi>10.3390/ijms221810069</doi><orcidid>https://orcid.org/0000-0002-4289-452X</orcidid><orcidid>https://orcid.org/0000-0002-4727-088X</orcidid><orcidid>https://orcid.org/0000-0001-8195-3628</orcidid><orcidid>https://orcid.org/0000-0001-9588-5291</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1422-0067
ispartof International journal of molecular sciences, 2021-09, Vol.22 (18), p.10069
issn 1422-0067
1661-6596
1422-0067
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8468007
source MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals; PubMed Central
subjects Ebola virus
Epidemics
Evolutionary genetics
Genes
Genetic diversity
Genomes
Influenza
Influenza A
Next-generation sequencing
Pandemics
Poultry
Public health
Viruses
Zika virus
title Discriminating Clonotypes of Influenza A Virus Genes by Nanopore Sequencing
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T11%3A46%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Discriminating%20Clonotypes%20of%20Influenza%20A%20Virus%20Genes%20by%20Nanopore%20Sequencing&rft.jtitle=International%20journal%20of%20molecular%20sciences&rft.au=Cao,%20Ying&rft.date=2021-09-17&rft.volume=22&rft.issue=18&rft.spage=10069&rft.pages=10069-&rft.issn=1422-0067&rft.eissn=1422-0067&rft_id=info:doi/10.3390/ijms221810069&rft_dat=%3Cproquest_pubme%3E2577451573%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2576432848&rft_id=info:pmid/34576230&rfr_iscdi=true