Using statistical properties of short subsequences in microbial identification

The comparative analysis of distributions of the presence/absence of short subsequences of different length ("n-mers", n = 5 - 20) in more than 100 microbial genomes has been performed. Our results show that for organisms, which are not close relatives of each other, the presence/absence of different 10-20-mers in their genomes are not correlated. For close biological relatives, some correlation of the presence of n-mers appears, but is not as strong as expected. Suppressed correlations among the n-mers present in different genomes lead to the possibility of using random sets of n-mers (with appropriately chosen n) to discriminate genomes of different organisms with a low probability of error. We have performed in silico experiments to demonstrate that the presence/absence pattern of 1000 random oligomers of length 12-13 in a bacterial genome is sufficiently characteristic to readily and unambiguously distinguish any known bacterial genome from any other.