SDT: a virus classification tool based on pairwise sequence alignment and identity calculation

Abstract

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).

Figure 1. The SDT interface.

(A) Colour-coded pairwise identity matrix generated from 29 Chickpea chlorotic dwarf virus genomes. Each coloured cell represents a percentage identity score between two sequences (one indicated horizontally to the left and the other vertically at the bottom). A coloured key indicates the correspondence between pairwise identities and the colours displayed in the matrix. (B) Pairwise identity frequency distribution plot. The horizontal axis indicates percentage pairwise identities, and the vertical axis indicates proportions of these identities within the distribution. While peaks on the graph indicate pairwise sequence identity thresholds that would yield the most ambiguous classifications, troughs indicate thresholds that would yield the least ambiguous classifications and could therefore be tentatively used as relatively conflict free operational taxonomic unit demarcation cut-offs.

Figure 2. Distribution of pairwise genetic/evolutionary distances of the same set of 25 mastrevirus full genome sequences in the context of progressively larger sequence datasets.

The constant frequency distribution (represented by red graph) illustrates the consistency of pairwise distance calculation based on pairwise alignments while the changing frequency distributions (represented by blue and green graphs) indicate how pairwise distance scores based on multiple sequence alignment tend to become inflated as dataset sizes get larger.