Determining Difference in Evolutionary Variation of Bacterial RecA proteins vs 16SrRNA Genes by using 16s_Toxonomy Tree

Authors

  • Fahimi, Hossein Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Branch, Islamic Azad University, Tehran, Iran
  • Maleki, Avisa Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Branch, Islamic Azad University, Tehran, Iran
  • Taghizadeh, Mohammad Department of Biotechnology, Faculty of Advanced Science and Technology, Tehran Medical Branch, Islamic Azad University, Tehran, Iran
Abstract:

Background and Aims: The rate of variation in various genes of a bacterial species is different during evolution. Therefore, in systematic bacterial studies many researchers compare the phylogenetic tree of a particular gene to the standard tree of an rRNA gene. Regarding the importance of 16SrRNA gene and the evolutional process of RecA protein family, we investigated the changes in the selected phylum of bacterial RecA family in comparing with the 16SrRNA gene. Materials and Methods: For this purpose, sequences of the RecA protein family were extracted from Uniprot database and categorized by using CD-hit algorithm. One species was selected from each category. Then we found 16SrRNA complete sequences for same species. After determining the index, based on the Average Alignment Score (AAS), the 16s-taxonomic tree was obtained. Furthermore, Similar calculations were considered for corresponding RecA proteins phylums. Results: By comparing amount of AAS in 16srRNA phylums and RecA phylums, we observed that the Actinobacteria phylum is the closest to the header phylum in the 16s-taxonomic tree, but the same phylum in the RecA is the most distant to the header phylum; and the position of the cyanobacteria phylum remains the same in both trees, which indicates the least amount of changes in the genus and species of this phylum. Conclusion: The 16s-taxonomic tree which is presented in this study for the first time is different from the available bioinformatics algorithms for tree drawing. Finding the species with the highest and lowest rates of changes, can be a type of prediction method for indicating the reasons why bacteria become resistant to drugs over a long period of time.

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Journal title

volume 13  issue 1

pages  32- 43

publication date 2019-03

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