The perpetually increasing rate at which viral full-genome sequences are being determined is creating a pressing demand for computational tools that will aid the objective classification of these genome sequences. Taxonomic classification approaches that are based on pairwise genetic identity measures are potentially highly automatable and are progressively gaining favour with the International Committee on Taxonomy of Viruses (ICTV). There are, however, various issues with the calculation of such measures that could potentially undermine the accuracy and consistency with which they can be applied to virus classification. Firstly, pairwise sequence identities computed based on multiple sequence alignments rather than on multiple independent pairwise alignments can lead to the deflation of identity scores with increasing dataset sizes. Also, when gap-characters need to be introduced during sequence alignments to account for insertions and deletions, methodological variations in the way that these characters are introduced and handled during pairwise genetic identity calculations can cause high degrees of inconsistency in the way that different methods classify the same sets of sequences. Here we present Sequence Demarcation Tool (SDT), a free user-friendly computer program that aims to provide a robust and highly reproducible means of objectively using pairwise genetic identity calculations to classify any set of nucleotide or amino acid sequences. SDT can produce publication quality pairwise identity plots and colour-coded distance matrices to further aid the classification of sequences according to ICTV approved taxonomic demarcation criteria. Besides a graphical interface version of the program for Windows computers, command-line versions of the program are available for a variety of different operating systems (including a parallel version for cluster computing platforms).

Circoviruses are circular single-stranded DNA (ssDNA) viruses that infect a variety of animals, both domestic and wild. Circovirus infection in birds is associated with immunosuppression and this in turn predisposes the infected animals to secondary infections that can lead to mortality. Farmed geese (Anser anser) in many parts of the world are infected with circoviruses. The majority of the current genomic information for goose circoviruses (GoCVs) (n = 40) are from birds sampled in China and Taiwan, and only two genome sequences are available from Europe (Germany and Poland). In this study, we sampled 23 wild and 19 domestic geese from the Gopło Lake area in Poland. We determined the genomes of GoCV from 21 geese; 14 domestic Greylag geese (Anser anser), three wild Greylag geese (A. anser), three bean geese (A. fabalis), and one white fronted goose (A. albifrons). These genomes share 83–95% nucleotide pairwise identities with previously identified GoCV genomes, most are recombinants with exchanged fragment sizes up to 50% of the genome. Higher diversity levels can be seen within the genomes from domestic geese compared with those from wild geese. In the GoCV capsid protein (cp) and replication associated protein (rep) gene sequences we found that episodic positive selection appears to largely mirror those of beak and feather disease virus and pigeon circovirus. Analysis of the secondary structure of the ssDNA genome revealed a conserved stem-loop structure with the G-C rich stem having a high degree of negative selection on these nucleotides.

Annually, rubella virus (RV) still causes severe congenital defects in around 100 000 children globally. An attempt to eradicate RV is currently underway and analytical tools to monitor the global decline of the last remaining RV lineages will be useful for assessing the effectiveness of this endeavour. RV evolves rapidly enough that much of this information might be inferable from RV genomic sequence data. Using BEASTv1.8.0, we analysed publically available RV sequence data to estimate genome-wide and gene-specific nucleotide substitution rates to test whether current estimates of RV substitution rates are representative of the entire RV genome. We specifically accounted for possible confounders of nucleotide substitution rate estimates, such as temporally biased sampling, sporadic recombination, and natural selection favouring either increased or decreased genetic diversity (estimated by the PARRIS and FUBAR methods), at nucleotide sites within the genomic secondary structures (predicted by the NASP method). We determine that RV nucleotide substitution rates range from 1.19 × 10-3 substitutions/site/year in the E1 region to 7.52 × 10-4 substitutions/site/year in the P150 region. We find that differences between substitution rate estimates in different RV genome regions are largely attributable to temporal sampling biases such that datasets containing higher proportions of recently sampled sequences, will tend to have inflated estimates of mean substitution rates. Although there exists little evidence of positive selection or natural genetic recombination in RV, we show that RV genomes possess pervasive biologically functional nucleic acid secondary structure and that purifying selection acting to maintain this structure contributes substantially to variations in estimated nucleotide substitution rates across RV genomes. Both temporal sampling biases and purifying selection favouring the conservation of RV nucleic acid secondary structures have an appreciable impact on substitution rate estimates but do not preclude the use of RV sequence data to date ancestral sequences. The combination of uniformly high substitution rates across the RV genome and strong temporal structure within the available sequence data, suggests that such data should be suitable for tracking the demographic, epidemiological and movement dynamics of this virus during eradication attempts.