Background: Phylogenetic analyses are an essential part in the exploratory assessment of nucleic acid and amino acid sequences. Particularly in virology, they are able to delineate the evolution and epidemiology of disease etiologic agents and/or the evolutionary path of their hosts. The objective of this review is to help researchers who want to use phylogenetic analyses as a tool in virology and molecular epidemiology studies, presenting the most commonly used methodologies, describing the importance of the different techniques, their peculiar vocabulary and some examples of their use in virology.Review: This article starts presenting basic concepts of molecular epidemiology and molecular evolution, emphasizing their relevance in the context of viral infectious diseases. It presents a session on the vocabulary relevant to the subject, bringing readers to a minimum level of knowledge needed throughout this literature review. Within its main subject, the text explains what a molecular phylogenetic analysis is, starting from a multiple alignment of nucleotide or amino acid sequences. The different software used to perform multiple alignments may apply different algorithms. To build a phylogeny based on amino acid or nucleotide sequences it is necessary to produce a data matrix based on a model for nucleotide or amino acid replacement, also called evolutionary model. There are a number of evolutionary models available, varying in complexity according to the number of parameters (transition, transversion, GC content, nucleotide position in the codon, among others). Some papers presented herein provide techniques that can be used to choose evolutionary models. After the model is chosen, the next step is to opt for a phylogenetic reconstruction method that best fits the available data and the selected model. Here we present the most common reconstruction methods currently used, describing their principles, advantages and disadvantages. Distance methods, for example, are simpler and faster, however, they do not provide reliable estimations when the sequences are highly divergent. The accuracy of the analysis with probabilistic models (neighbour joining, maximum likelihood and bayesian inference) strongly depends on the adherence of the actual data to the chosen development model. Finally, we also explore topology confidence tests, especially the most used one, the bootstrap. To assist the reader, this review presents figures to explain specific situations discussed in the text and numerous examples of previously published scientific articles in virology that demonstrate the importance of the techniques discussed herein, as well as their judicious use.Conclusion: The DNA sequence is not only a record of phylogeny and divergence times, but also keeps signs of how the evolutionary process has shaped its history and also the elapsed time in the evolutionary process of the population. Analyses of genomic sequences by molecular phylogeny have demonstrated a broad spectrum of applications. It is important to note that for the different available data and different purposes of phylogenies, reconstruction methods and evolutionary models should be wisely chosen. This review provides theoretical basis for the choice of evolutionary models and phylogenetic reconstruction methods best suited to each situation. In addition, it presents examples of diverse applications of molecular phylogeny in virology.
An experimentally informed evolutionary model improves phylogenetic fit to divergent lactamase homologs
