Evolutionary analysis and modeling of coronavirus genomes

Studies have shown that novel coronavirus (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) most likely was transmitted to humans by animal carriers. It is therefore interesting to ask how the virus has evolved in organisms of different hosts. Mathematical tools allow analysis of genomic diversity of coronaviruses in the context of its past, present and projected co-evolution with host populations. Especially phylogenetic methods are useful in inferring patterns of evolutionary changes from nucleotide sequence variation. Using available genome sequence data, we compared mutation site frequency spectra of SARS-CoV-2 derived from human hosts with theoretical models, with results indicating influence of natural selection. In addition, we analyzed sequences of previous coronavirus strains (SARS-CoV, MERS-CoV) sampled from human and animal hosts. Specifically, using the Bayesian Evolutionary Analysis by Sampling Trees 2 (BEAST 2) software package we performed evolutionary analysis of parts of coronavirus genomes, estimating their pace of evolution, most recent common ancestor (MRCA) age and topology of phylogenetic tree. Preliminary results showed significant differences in estimated evolutionary rates, population size changes and MRCA age between coronavirus strains isolated from different hosts, bringing us closer to the estimation of future evolution rates of coronavirus strains and building reliable phylodynamic models. One model which we are currently exploring with respect to its applicability in the endemic phase of coronavirus evolution is the tug-of-war model, which seems to predict irregular fluctuations of fitness in bat coronaviruses.

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