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Do Tag-generated RT-PCR products from RNA viruses accurately reflect viral genetic heterogeneity?

  • B. Mullan
  • , P. Sheehy
  • , F. Shanahan
  • , L. Fanning

Research output: Contribution to journalReview articlepeer-review

Abstract

Since the first report of genetically heterogeneous, or quasispecies, populations of RNA viruses, the genetic heterogeneity of the RNA genomes of major viral pathogens has been extensively studied. These studies aim to provide insights into the evolutionary pressures that act upon viruses, in order to define windows where anti-viral therapies will be most effective, to take prognostic values from viral genetic distributions at a given time, and to aid the development of novel therapeutic compounds that may tilt viral replication towards information loss. Many methodologies are employed to analyse genetic distributions of a virus in a given sample, but all involve the generation, and subsequent analysis, of the sequence information contained in a reverse-transcription-polymerase chain reaction (RT-PCR) product. Despite the fact that the aim of these RT-PCRs is to obtain sequence information from viral genomes, their application to this task is approached without adequate consideration of this end-goal. The establishment of an RT-PCR for a specific viral target genome generally proceeds in the same fashion as one would apply to establishing a PCR to determine the presence or absence of a specific target sequence in a given sample. However, it is becoming increasingly apparent that RT-PCR products generated by amplification with the ubiquitous thermostable DNA polymerase Taq, coupled with standard cloning and sequencing methodologies, has the potential to yield inaccurate and misleading data as pertains to the information content of populations of RNA viral genomes. This review discusses varying approaches employed to analyse heterogeneous populations of hepatitis C virus RNA genomes.

Original languageEnglish
Pages (from-to)108-114
Number of pages7
JournalJournal of Viral Hepatitis
Volume11
Issue number2
DOIs
Publication statusPublished - Mar 2004

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Error rate
  • Hepatitis C virus
  • Mismatch
  • Quasispecies
  • Reverse-transcribed polymerase chain reaction

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