Abstract

The Local Shannon Entropy (LSE) in blocks is used as a complexity measure to study the information fluctuations along DNA sequences. The LSE of a DNA block maps the local base arrangement information to a single numerical value. It is shown that despite this reduction of information, LSE allows to extract meaningful information related to the detection of repetitive sequences in whole chromosomes and is useful in finding evolutionary differences between organisms. More specifically, large regions of tandem repeats, such as centromeres, can be detected based on their low LSE fluctuations along the chromosome. Furthermore, an empirical investigation of the appropriate block sizes is provided and the relationship of LSE properties with the structure of the underlying repetitive units is revealed by using both computational and mathematical methods. Sequence similarity between the genomic DNA of closely related species also leads to similar LSE values at the orthologous regions. As an application, the LSE covariance function is used to measure the evolutionary distance between several primate genomes.