Prediction of translation initiation sites on the genome of Synechocystis sp. strain PCC6803 by Hidden Markov model.

Abstract

We developed a computer program, GeneHackerTL, which predicts the most probable translation initiation site for a given nucleotide sequence. The program requires that information be extracted from the nucleotide sequence data surrounding the translation initiation sites according to the framework of the Hidden Markov Model. Since the translation initiation sites of 72 highly abundant proteins have already been assigned on the genome of Synechocystis sp. strain PCC6803 by amino-terminal analysis, we extracted necessary information for GeneHackerTL from the nucleotide sequence data. The prediction rate of the GeneHackerTL for these proteins was estimated to be 86.1%. We then used GeneHackerTL for prediction of the translation initiation sites of 24 other proteins, of which the initiation sites were not assigned experimentally, because of the lack of a potential initiation codon at the amino-terminal position. For 20 out of the 24 proteins, the initiation sites were predicted in the upstream of their amino-terminal positions. According to this assignment, the processed regions represent a typical feature of signal peptides. We could also predict multiple translation initiation sites for a particular gene for which at least two initiation sites were experimentally detected. This program would be effective for the prediction of translation initiation sites of other proteins, not only in this species but also in other prokaryotes as well.