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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...

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Detalles Bibliográficos
Autores principales: Cao, Ying, Liu, Haizhou, Yan, Yi, Liu, Wenjun, Liu, Di, Li, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468007/
https://www.ncbi.nlm.nih.gov/pubmed/34576230
http://dx.doi.org/10.3390/ijms221810069
Descripción
Sumario: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.