How independent are the appearances of n-mers in different genomes?
Yuriy Fofanov,* 1 Yi Luo,1 Charles Katili,1 Jim Wang,1 Yuri Belosludtsev,3 Thomas Powdrill,3 Chetan Belapurkar,1 Viacheslav Fofanov,1 Tong-Bin Li,1 Sergey Chumakov,1,4 and B. Montgomery Pettitt1,2
1Department
of Computer Science,
2Department of
3Vitruvius Biosciences, The
Woodlands,
4Department of Physics,
* To whom correspondence should be addressed
Department of Computer Science
The
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Email: yfofanov@uh.edu
Running title:
Keywords: genome fingerprints, subsequence, primers, probes, genomes, microbial, virus, microarrays
Motivation: Analysis of statistical properties of DNA sequences is important for evolutional biology as well as for DNA probe and PCR technologies. These technologies, in turn, can be used for organism identification which implies applications in diagnosis of infectious diseases, environmental studies, etc.
Results: We present results of the correlation analysis of distributions of the presence/absence of short nucleotide subsequences of different length (“n-mers”, n = 5 – 20) in more than 1500 microbial and virus genomes, together with five genomes of multicellular organisms (including human). We calculate whether a given n-mer is present or absent (frequency of presence) in a given genome, which is not the usually calculated number of appearances of n-mers in one or more genomes (frequency of appearance). For organisms that are not close relatives of each other, the presence/absence of different 7–20-mers in their genomes are not correlated. For close biological relatives, some correlation of the presence of n-mers in this range appears, but is not as strong as expected. Suppressed correlations among the n-mers present in different genomes leads to the possibility of using random sets of n-mers (with appropriately chosen n) to discriminate genomes of different organisms and possibly individual genomes of the same species including human with a low probability of error.
Contact: yfofanov@uh.edu