Discovering Patterns in Microsatellite Flanks with Evolutionary Computation by Evolving Discriminatory DNA Motifs

Microsatellites are repetitive regions of DNA which account for a highly significant amount of eukaryotic genomes. They are used as genetic markers and have various uses in the study of natural evolution and phylogeny. However, very little is known about the molecular biology mechanisms which produce microsatellites and even less is known about how and why different kinds of microsatellites occur with different length distributions in the genome. In this study we use a vast amount of microsatellite data from the human genome, and use an evolutionary algorithm to search for DNA patterns which might yield clues about their generation and perhaps their inhibition too. We find that the evolutionary algorithm uncovers several significant patterns which indicate preferences for microsatellites to appear nearby, and other patterns which seem to inhibit microsatellite production. The results show that both attracters and inhibitors to microsatellite production seem to exist, and are motifdependent. We feel this represents a nice example of using evolutionary algorithms to find previously unimagined fuel for molecular biology hypothesis making,