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PLoS One. 2012;7(9):e45103. doi: 10.1371/journal.pone.0045103. Epub 2012 Sep 24.

Predicting statistical properties of open reading frames in bacterial genomes.

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1
Institute of Communications Engineering, Ulm University, Ulm, Germany. katharina.mir@uni-ulm.de

Abstract

An analytical model based on the statistical properties of Open Reading Frames (ORFs) of eubacterial genomes such as codon composition and sequence length of all reading frames was developed. This new model predicts the average length, maximum length as well as the length distribution of the ORFs of 70 species with GC contents varying between 21% and 74%. Furthermore, the number of annotated genes is predicted with high accordance. However, the ORF length distribution in the five alternative reading frames shows interesting deviations from the predicted distribution. In particular, long ORFs appear more often than expected statistically. The unexpected depletion of stop codons in these alternative open reading frames cannot completely be explained by a biased codon usage in the +1 frame. While it is unknown if the stop codon depletion has a biological function, it could be due to a protein coding capacity of alternative ORFs exerting a selection pressure which prevents the fixation of stop codon mutations. The comparison of the analytical model with bacterial genomes, therefore, leads to a hypothesis suggesting novel gene candidates which can now be investigated in subsequent wet lab experiments.

PMID:
23028785
PMCID:
PMC3454372
DOI:
10.1371/journal.pone.0045103
[Indexed for MEDLINE]
Free PMC Article
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