Title :
Study of the Paired Change Points in Bacterial Genes
Author :
Suvorova, Yulia M. ; Korotkova, Maria A. ; Korotkov, Eugene V.
Author_Institution :
Bioinf. Lab., Centre of Bioeng., Moscow, Russia
fDate :
Sept.-Oct. 1 2014
Abstract :
It is known that nucleotide sequences are not totally homogeneous and this heterogeneity could not be due to random fluctuations only. Such heterogeneity poses a problem of making sequence segmentation into a set of homogeneous parts divided by the points called “change points”. In this work we investigated a special case of change points-paired change points (PCP). We used a well-known property of coding sequences-triplet periodicity (TP). The sequences that we are especially interested in consist of three successive parts: the first and the last parts have similar TP while the middle part has different TP type. We aimed to find the genes with PCP and provide explanation for this phenomenon. We developed a mathematical method for the PCP detection based on the new measure of similarity between TP matrices. We investigated 66,936 bacterial genes from 17 bacterial genomes and revealed 2,700 genes with PCP and 6,459 genes with single change point (SCP). We developed a mathematical approach to visualize the PCP cases. We suppose that PCP could be associated with double fusion or insertion events. The results of investigating the sequences with artificial insertions/fusions and distribution of TP inside the genome support the idea that the real number of genes formed by insertion/ fusion events could be 5-7 times greater than the number of genes revealed in the present work.
Keywords :
DNA; RNA; fluctuations; genetics; genomics; microorganisms; molecular biophysics; molecular configurations; PCP detection; artificial insertions-fusions; bacterial genes; bacterial genomes; coding sequences; double fusion; insertion events; mathematical method; nucleotide sequences; paired change points; random fluctuations; sequence segmentation; single change point; triplet periodicity; Bioinformatics; DNA; Encoding; Equations; Genomics; Mathematical model; Microorganisms; Biology and genetics Triplet periodicity; change points; genes; sequence analysis;
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
DOI :
10.1109/TCBB.2014.2321154