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Unique features of nucleotide and codon usage patterns in mycoplasmas revealed by information entropy.

Authors :
Wang, Yi-ning
Ji, Wen-heng
Li, Xue-rui
Liu, Yong-sheng
Zhou, Jian-hua
Source :
Biosystems. Mar2018, Vol. 165, p1-7. 7p.
Publication Year :
2018

Abstract

Currently, the comparison between GC usage pattern at the 3rd codon position and codon usage index is commonly used to estimate the roles of evolutionary forces in shaping synonymous codon usages, however, this kind of analysis often losses the information about the role of A/T usage bias in shaping synonymous codon usage bias. To overcome this limitation and better understand the interplay between nucleotide and codon usages for the evolution of bacteria at gene levels, in this study, we employed the information entropy method with some modification to estimate roles of nucleotide compositions in the overall codon usage bias for 18 mycoplasma species in combination with Davies-Bouldin index. At gene levels, the overall nucleotide usage bias represents A content as the highest, followed by T, G and C for mycoplasmas, resulting in a low GC content. This feature is universal across these species derived from different hosts, suggesting that the hosts have the limited impact on nucleotide usage bias of mycoplasmas. Information entropy and Davies-Bouldin index can better reveal that the nucleotide usage bias at the 3rd codon position is essential in shaping the overall nucleotide bias for all given mycoplasmas except M. pneumoniae M129. Davies-Bouldin index revealed that the 1st and 2nd codon position play more important role in synonymous codon usage bias than that of the 3rd position at gene levels. To our knowledge, this is the first comprehensive investigation into cooperation between nucleotide and codon usages for mycoplasma and extends our knowledge of the mechanisms that contribute to codon usage and evolution of this microorganism. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03032647
Volume :
165
Database :
Academic Search Index
Journal :
Biosystems
Publication Type :
Academic Journal
Accession number :
128286878
Full Text :
https://doi.org/10.1016/j.biosystems.2017.12.008