Literature DB >> 32001386

High-throughput sequencing (HTS) for the analysis of viral populations.

Marcos Pérez-Losada1, Miguel Arenas2, Juan Carlos Galán3, Mª Alma Bracho4, Julia Hillung5, Neris García-González6, Fernando González-Candelas7.   

Abstract

The development of High-Throughput Sequencing (HTS) technologies is having a major impact on the genomic analysis of viral populations. Current HTS platforms can capture nucleic acid variation across millions of genes for both selected amplicons and full viral genomes. HTS has already facilitated the discovery of new viruses, hinted new taxonomic classifications and provided a deeper and broader understanding of their diversity, population and genetic structure. Hence, HTS has already replaced standard Sanger sequencing in basic and applied research fields, but the next step is its implementation as a routine technology for the analysis of viruses in clinical settings. The most likely application of this implementation will be the analysis of viral genomics, because the huge population sizes, high mutation rates and very fast replacement of viral populations have demonstrated the limited information obtained with Sanger technology. In this review, we describe new technologies and provide guidelines for the high-throughput sequencing and genetic and evolutionary analyses of viral populations and metaviromes, including software applications. With the development of new HTS technologies, new and refurbished molecular and bioinformatic tools are also constantly being developed to process and integrate HTS data. These allow assembling viral genomes and inferring viral population diversity and dynamics. Finally, we also present several applications of these approaches to the analysis of viral clinical samples including transmission clusters and outbreak characterization.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Clinical virology; Complete genome sequences; Molecular evolution; Nanopore sequencing; Outbreaks; Population genomics; SMRT sequencing; Short-reads; Transmission clusters

Mesh:

Year:  2020        PMID: 32001386     DOI: 10.1016/j.meegid.2020.104208

Source DB:  PubMed          Journal:  Infect Genet Evol        ISSN: 1567-1348            Impact factor:   3.342


  12 in total

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