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High-throughput sequencing (HTS) for the analysis of viral populations.
Pérez-Losada, Marcos; Arenas, Miguel; Galán, Juan Carlos; Bracho, Mª Alma; Hillung, Julia; García-González, Neris; González-Candelas, Fernando.
Afiliação
  • Pérez-Losada M; Computational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, DC, USA; CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, Vairão 4485-661, Portugal.
  • Arenas M; Department of Biochemistry, Genetics and Immunology, University of Vigo, 36310 Vigo, Spain; Biomedical Research Center (CINBIO), University of Vigo, 36310 Vigo, Spain. Electronic address: marenas@uvigo.es.
  • Galán JC; Microbiology Service, Hospital Ramón y Cajal, Madrid, Spain; CIBER in Epidemiology and Public Health, Spain. Electronic address: juancarlos.galan@salud.madrid.org.
  • Bracho MA; CIBER in Epidemiology and Public Health, Spain; Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Valencia, Spain. Electronic address: bracho_alm@gva.es.
  • Hillung J; Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Valencia, Spain; Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Valencia, Spain. Electronic address: julia.hillung@uv.es.
  • García-González N; Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Valencia, Spain; Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Valencia, Spain. Electronic address: neris@uv.es.
  • González-Candelas F; CIBER in Epidemiology and Public Health, Spain; Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Valencia, Spain; Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Valencia, Spain. Electronic address: fernando.gonzalez@uv.es.
Infect Genet Evol ; 80: 104208, 2020 06.
Article em En | MEDLINE | ID: mdl-32001386
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Vírus / Metagenoma / Metagenômica / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Diagnostic_studies / Guideline Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Vírus / Metagenoma / Metagenômica / Sequenciamento de Nucleotídeos em Larga Escala Tipo de estudo: Diagnostic_studies / Guideline Limite: Animals / Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article