RESEARCH ARTICLE Mapping the Space of Genomic Signatures

We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thou-sands of complete mitochondrial genomes. An "image distance " is computed for each pair of graphical representations of DNA sequences, and the distances are visualized as a Mo-lecular Distance Map: Each point on the map represents a DNA sequence, and the spatial proximity between any two points reflects the degree of structural similarity between the cor-responding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a geno-mic signature. Consequently, Molecular Distance Maps could inform species identification, taxonomic classifications and, to a certain extent, evolutionary history. The image distance employed, Structural Dissimilarity Index (DSSIM), implicitly compares the occurrences of oligomers of length up to k (herein k = 9) in DNA sequences. We computed DSSIM dis-tances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Di-mensional Scaling (MDS) to obtain Molecular Distance Maps that visually display th