Non-polio enteroviruses are a ubiquitous and divergent group of non-enveloped RNA viruses. Novel types are reported regularly in addition to over 100 known types; however, mechanisms of emergence of novel types remain obscure. Here, the 33 most common types represented by 35-629 non-redundant partial VP1 sequences in GenBank were studied in parallel using Bayesian coalescent molecular clock analysis to investigate common evolutionary trends among enterovirus types. Inferred substitution rates were in the range of 0.41×10 to 3.07×10 substitutions per site per year. The most recent common ancestors of known isolates of each type presumably existed between 55 and 200 years ago. Phylogenetic analysis results suggested that global type populations underwent bottlenecks that could repeatedly reset the common ancestor dates. Nevertheless, species-level analysis suggested that the contemporary enterovirus types emerged within the last millennium. Analysis of 2657 complete VP1 sequences of the 24 most common types indicated that the type criterion based upon 75 % nucleotide sequence identity remains generally valid, despite exponential growth of the number of known sequences and a high rate of mutation fixation. However, in few types there was evidence that enteroviruses can drift slightly beyond the type threshold, up to 73 % identity, and both amino acid and nucleotide sequences should be considered for type identification. Analysis of sequence distances within types implied that sequence-identity-based identification of genotypes is rational within some, but not all, types and distinct genotype cut-offs (9-20 %) may be useful for different types.

Tick-borne encephalitis (TBE) is one of the most important viral zoonosis transmitted by the bite of infected ticks. In this study, all tick-borne encephalitis virus (TBEV) E gene sequences available in GenBank as of June 2019 with known date of isolation (n = 551) were analyzed. Simulation studies showed that a sample bias could significantly affect earlier studies, because small TBEV datasets (n = 50) produced non-overlapping intervals for evolutionary rate estimates. An apparent lack of a temporal signal in TBEV, in general, was found, precluding molecular clock analysis of all TBEV subtypes in one dataset. Within all subtypes and most of the smaller groups in these subtypes, there was evidence of many medium- and long-distance virus transfers. These multiple random events may play a key role in the virus spreading. For some groups, virus diversity within one territory was similar to diversity over the whole geographic range. This is best exemplified by the virus diversity observed in Switzerland or Czech Republic. These two countries yielded most of the known European subtype Eu3 subgroup sequences, and the diversity of viruses found within each of these small countries is comparable to that of the whole Eu3 subgroup, which is prevalent all over Central and Eastern Europe. Most of the deep tree nodes within all three established TBEV subtypes dated less than 300 years back. This could be explained by the recent emergence of most of the known TBEV diversity. Results of bioinformatics analysis presented here, together with multiple field findings, suggest that TBEV may be regarded as an emerging disease.

The viral family Coronaviridae comprises four genera, termed Alpha-, Beta-, Gamma-, and Deltacoronavirus. Recombination events have been described in many coronaviruses infecting humans and other animals. However, formal analysis of the recombination patterns, both in terms of the involved genome regions and the extent of genetic divergence between partners, are scarce. Common methods of recombination detection based on phylogenetic incongruences (e.g., a phylogenetic compatibility matrix) may fail in cases where too many events diminish the phylogenetic signal. Thus, an approach comparing genetic distances in distinct genome regions (pairwise distance deviation matrix) was set up. In alpha, beta, and delta-coronaviruses, a low incidence of recombination between closely related viruses was evident in all genome regions, but it was more extensive between the spike gene and other genome regions. In contrast, avian gammacoronaviruses recombined extensively and exist as a global cloud of genes with poorly corresponding genetic distances in different parts of the genome. Spike, but not other structural proteins, was most commonly exchanged between coronaviruses. Recombination patterns differed between coronavirus genera and corresponded to the modular structure of the spike: recombination traces were more pronounced between spike domains (N-terminal and C-terminal parts of S1 and S2) than within domains. The variability of possible recombination events and their uneven distribution over the genome suggest that compatibility of genes, rather than mechanistic or ecological limitations, shapes recombination patterns in coronaviruses.