Deep sequencing analysis of viral infection and evolution allows rapid and detailed characterization of viral mutant spectrum. Academic Article uri icon

Overview

abstract

  • MOTIVATION: The study of RNA virus populations is a challenging task. Each population of RNA virus is composed of a collection of different, yet related genomes often referred to as mutant spectra or quasispecies. Virologists using deep sequencing technologies face major obstacles when studying virus population dynamics, both experimentally and in natural settings due to the relatively high error rates of these technologies and the lack of high performance pipelines. In order to overcome these hurdles we developed a computational pipeline, termed ViVan (Viral Variance Analysis). ViVan is a complete pipeline facilitating the identification, characterization and comparison of sequence variance in deep sequenced virus populations. RESULTS: Applying ViVan on deep sequenced data obtained from samples that were previously characterized by more classical approaches, we uncovered novel and potentially crucial aspects of virus populations. With our experimental work, we illustrate how ViVan can be used for studies ranging from the more practical, detection of resistant mutations and effects of antiviral treatments, to the more theoretical temporal characterization of the population in evolutionary studies. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://www.vivanbioinfo.org CONTACT: : nshomron@post.tau.ac.il SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

publication date

  • February 19, 2015

Research

keywords

  • Biological Evolution
  • Genetic Variation
  • High-Throughput Nucleotide Sequencing
  • Mutation
  • Virus Diseases
  • Viruses

Identity

PubMed Central ID

  • PMC4481840

Scopus Document Identifier

  • 84936797457

Digital Object Identifier (DOI)

  • 10.1093/bioinformatics/btv101

PubMed ID

  • 25701575

Additional Document Info

volume

  • 31

issue

  • 13