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Statistical Applications in Genetics and Molecular Biology

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Volume 14, Issue 2

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Study of triplet periodicity differences inside and between genomes

Yulia M. Suvorova
  • Corresponding author
  • Bioinformatics Laboratory, Centre of Bioengineering of the Russian Academy of Sciences, 117312, Prospect 60-tya Oktyabrya, Moscow, Russian Federation
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
 / Eugene V. Korotkov
  • Bioinformatics Laboratory, Centre of Bioengineering of the Russian Academy of Sciences, 117312, Prospect 60-tya Oktyabrya, Moscow, Russian Federation
  • Department of Applied Mathematics, National Nuclear Investigational University (MIFI), 115522, Kashirskoe Shosse, 31, Moscow, Russian Federation
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2015-02-24 | DOI: https://doi.org/10.1515/sagmb-2013-0063

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Abstract

Triplet periodicity (TP) is a distinctive feature of the protein coding sequences of both prokaryotic and eukaryotic genomes. In this work, we explored the TP difference inside and between 45 prokaryotic genomes. We constructed two hypotheses of TP distribution on a set of coding sequences and generated artificial datasets that correspond to the hypotheses. We found that TP is more similar inside a genome than between genomes and that TP distribution inside a real genome dataset corresponds to the hypothesis which implies that a common TP pattern exists for the majority of sequences inside a genome. Additionally, we performed gene classification based on TP matrixes. This classification showed that TP allows identification of the genome to which a given gene belongs with more than 85% accuracy.

Keywords: gene classification; genomes comparison; protein coding genes; triplet periodicity

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About the article

Corresponding author: Yulia M. Suvorova, Bioinformatics Laboratory, Centre of Bioengineering of the Russian Academy of Sciences, 117312, Prospect 60-tya Oktyabrya, Moscow, Russian Federation, e-mail:

Published Online: 2015-02-24

Published in Print: 2015-04-01

Citation Information: Statistical Applications in Genetics and Molecular Biology, Volume 14, Issue 2, Pages 113–123, ISSN (Online) 1544-6115, ISSN (Print) 2194-6302, DOI: https://doi.org/10.1515/sagmb-2013-0063.

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