title: Mapping the space of genomic signatures.
abstract: We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thousands 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 Molecular 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 corresponding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a genomic 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 distances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Dimensional Scaling (MDS) to obtain Molecular Distance Maps that visually display the sequence relatedness in various subsets, at different taxonomic levels. This general-purpose method does not require DNA sequence alignment and can thus be used to compare similar or vastly different DNA sequences, genomic or computer-generated, of the same or different lengths. We illustrate potential uses of this approach by applying it to several taxonomic subsets: phylum Vertebrata, (super)kingdom Protista, classes Amphibia-Insecta-Mammalia, class Amphibia, and order Primates. This analysis of an extensive dataset confirms that the oligomer composition of full mtDNA sequences can be a source of taxonomic information. This method also correctly finds the mtDNA sequences most closely related to that of the anatomically modern human (the Neanderthal, the Denisovan, and the chimp), and that the sequence most different from it in this dataset belongs to a cucumber.
authors.affiliation: Department of Computer Science, University of Western Ontario, London, Ontario, Canada.
authors.forename: Lila
authors.initials: L
authors.lastname: Kari
authors.affiliation: Department of Computer Science, University of Western Ontario, London, Ontario, Canada; Department of Biology, University of Western Ontario, London, Ontario, Canada.
authors.forename: Kathleen A
authors.initials: KA
authors.lastname: Hill
authors.affiliation: Department of Computer Science, University of Western Ontario, London, Ontario, Canada.
authors.forename: Abu S
authors.initials: AS
authors.lastname: Sayem
authors.affiliation: Department of Computer Science, University of Western Ontario, London, Ontario, Canada.
authors.forename: Rallis
authors.initials: R
authors.lastname: Karamichalis
authors.affiliation: Department of Computer Science, University of Western Ontario, London, Ontario, Canada.
authors.forename: Nathaniel
authors.initials: N
authors.lastname: Bryans
authors.affiliation: Department of Biology, University of Western Ontario, London, Ontario, Canada.
authors.forename: Katelyn
authors.initials: K
authors.lastname: Davis
authors.affiliation: Physical and Theoretical Chemistry Laboratory, Department of Chemistry, Oxford University, Oxford, United Kingdom.
authors.forename: Nikesh S
authors.initials: NS
authors.lastname: Dattani
mesh_terms: D000818:Animals; D004272:DNA, Mitochondrial / Q000235:genetics*; D008962:Models, Theoretical
chemical_list: D004272:DNA, Mitochondrial