Use of phylogenetics in the molecular epidemiology and evolutionary studies of viral infections

Abstract

Since DNA sequencing techniques first became available almost 30 years ago, the amount of nucleic acid sequence data has increased enormously. Phylogenetics, which is widely applied to compare and analyze such data, is particularly useful for the analysis of genes from rapidly evolving viruses. It has been used extensively to describe the molecular epidemiology and transmission of the human immunodeficiency virus (HIV), the origins and subsequent evolution of the severe acute respiratory syndrome (SARS)-associated coronavirus (SCoV), and, more recently, the evolving epidemiology of avian influenza as well as seasonal and pandemic human influenza viruses.

Recent advances in phylogenetic methods can infer more in-depth information about the patterns of virus emergence, adding to the conventional approaches in viral epidemiology. Examples of this information include estimations (with confidence limits) of the actual time of the origin of a new viral strain or its emergence in a new species, viral recombination and reassortment events, the rate of population size change in a viral epidemic, and how the virus spreads and evolves within a specific population and geographical region.

Such sequence-derived information obtained from the phylogenetic tree can assist in the design and implementation of public health and therapeutic interventions. However, application of many of these advanced phylogenetic methods are currently limited to specialized phylogeneticists and statisticians, mainly because of their mathematical basis and their dependence on the use of a large number of computer programs.

This review attempts to bridge this gap by presenting conceptual, technical, and practical aspects of applying phylogenetic methods in studies of influenza, HIV, and SCoV. It aims to provide, with minimal mathematics and statistics, a practical overview of how phylogenetic methods can be incorporated into virological studies by clinical and laboratory specialists.

Keywords::

• Alignment
• Bayesian
• coalescent
• discrete character methods
• distance-based methods
• epidemics
• evolutionary rate
• HIV
• influenza
• maximum likelihood
• maximum parsimony
• molecular clock
• mutation
• natural selection
• neighbor-joining
• pandemics
• phylogeny
• phylogeography
• population dynamics
• reassortment
• recombination
• SARS
• sequence
• tree
• virus
• zoonotic