Discovering relationships among dispersed repeats using spatial association rule mining

Abstract

DNA in eukaryotic genomes is characterized, and often dominated, by repetitive, non-genic DNA sequences. Initially thought to be non-functional, repeats have been found to influence gene expression and provide diversity to the genome via mutation. Mobile repeat sequences (transposons) have played a prominent role in the evolutionary histories of eukaryotic genomes, and their persistence in eukaryotic DNA indicates that they have, on the whole, been evolutionarily advantageous. While there are an increasing number of algorithms that have been developed for discovering novel dispersed repeats, significant analysis of the repeats and their relationships to other genome features will be required before we can truly understand the complex ways in which dispersed repeat sequences contribute to evolutionary fitness. We propose a spatial proximity rule based data mining technique to discover highly fragmented repeat regions for which only the conserved parts are reported by a computational repeat finder.