In the search for the low-complexity sequences in prokaryotic and eukaryotic genomes: how to derive a coherent picture from global and local entropy measures

We investigate on a possible way to connect the presence of low-complexity sequences (LCS) in DNA genomes and the non-stationary properties of base correlations. Under the hypothesis that these variations signal a change in the DNA function, we use a new technique, called non-stationarity entropic index (NSEI) method, and we prove that this technique is an efficient way to detect functional changes with respect to a random baseline. The remarkable aspect is that NSEI does not imply any training data or fitting parameter, the only arbitrarity being the choice of a marker in the sequence. We make this choice on the basis of biological information about LCS distributions in genomes. We show that there exists a correlation between changing the amount in LCS and the ratio of long- to short-range correlation.