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First published online April 11, 2008
Experimental Biology and Medicine 233:665-673 (2008)
doi: 10.3181/0704-MR-97
© 2008 by the Society for Experimental Biology and Medicine
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MINIREVIEW

The Computational Detection of Functional Nucleotide Sequence Motifs in the Coding Regions of Organisms

Harlan Robins*,1, Michael Krasnitz{dagger} and Arnold J. Levine{dagger}

* Computational Biology Group, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109; and {dagger} Institute for Advanced Study, Princeton, New Jersey 08540

To whom requests for reprints should be addressed at 1 Computational Biology Group, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N, Seattle, WA 98109. E-mail: hrobins{at}fhcrc.org

A new algorithm has been constructed for finding under- and overrepresented oligonucleotide motifs in the protein coding regions of genomes that have been normalized for G/C content, codon usage, and amino acid order. This Robins-Krasnitz algorithm has been employed to compare the oligonucleotide frequencies between many different prokaryotic genomes. Evidence is presented demonstrating that at least some of these sequence motifs are functionally important and selected for or against during the evolution of these prokaryotes. The applications of this method include the optimization of protein expression for synthetic genes in foreign organisms, identification of novel oligonucleotide signals used by the organism and the examination of evolutionary relationships not dependent upon different gene sequence trees.

Key Words: motifs • codon usage • relative entropy






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