Over time, natural selection molds every gene into a unique mosaic of sites evolving rapidly and resisting change – an “evolutionary fingerprint” of the gene. Using a conceptually new metric, called the evolutionary selection distance (ESD), one can identify similarities and idiosyncrasies in selection pressure between sequence alignments. Based upon a broad survey of viral genes, we apply a variety of computational techniques employing ESD to classify genes by the similarity of their evolutionary fingerprints, identify genes with distinctive evolutionary features, and correlate evolution with phylogenetic, functional, and taxonomic information. We demonstrate that genes within the same functional group tend to exhibit similar evolutionary patterns, both within a single viral genome and between different viruses; similarity in selection pressures mirrors phylogenetic relationships among hepatitis C virus subtypes, but not HIV-1 subtypes and that evolutionary patterns in the hemagglutinin gene of the Influenza A virus are largely determined by the host with a few notable exceptions. By comparing genes at the level of the evolutionary processes rather than the pattern of sequence variation, we can compare both closely and distantly related genes, potentially revealing the guiding principles underlying the evolution of genetic diversity. We also describe future extensions of the metric to take other aspects of the evolutionary process into account.
Dr Kosakovsky Pond’s research focus is on developing methods, algorithms and software for statistical analysis, inference and hypothesis testing on molecular sequence data. His work is strongly based on information drawn from the evolution of HIV. He and his colleagues have developed the powerful HYPHY (Hypothesis Testing Using Phylogenies) software package for analyses in phylogenetic and molecular evolutionary studies. http://www.hyphy.org/sergei/