M. I. Bogachev - Ph.D. (Eng.), Associate Professor, Saint-Petersburg State Electrotechnical University «LETI» n. a. V. I. Ulyanov (Lenin). E-mail: rogex@mail333.com
A.R. Kayumov - Ph.D. (Biol.), Kazan (Volga region) Federal University. E-mail: kairatr@yandex.ru
O.A. Markelov - Saint-Petersburg State Electrotechnical University «LETI» n. a. V. I. Ulyanov (Lenin). E-mail: omarkelov@yandex.ru
V.A. Mironov - Junior Research Scientist, RAS Institute of Physical Chemical and Biological Problems in Soil Science. E-mail: Vasiliy.A.Mironov@gmail.com

Statistical analysis of the genome structure is a powerful tool to better understand and quantitatively describe various genetic processes. For example, Arneodo and coworkers have shown recently that the strand asymmetry in the human genome, which is known to be related to the replication timing and thus also may be used as an indicator of increased mutational pressure, can be evaluated by the statistical analysis of the nonlinear dependencies in the genome. To perform this analysis, various fluctuation analysis methods like those based on wavelet transformation or detrended fluctuation analysis have been applied. We have recently suggested that instead of the indirect fluctuation analysis of the DNA walk or similar artificial mathematical constructions, similar properties can be effectively extracted using the statistics of the return intervals between single nucleotides or their combination in the primary DNA structure. Here we show how far the interval statistics can be extrapolated when performing mutagenic tests on different bioindicator organisms, ranging from S. cerevisiae to H. sapiens. We suggest a universal functional fit for the distribution of the return intervals based on a q-exponential function which is valid for various organisms at different evolutionary levels. We also show that suggested instruments are sensitive in detecting TA-GC strand-asymmetry and thus can be used as a powerful and universal marker for increased mutagenic pressure.