Looking into the genome of Thermosynechococcus elongatus (thermophilic cyanobacteria) with codon selection and usage perspective.

Q4 Health Professions
Ratna Prabha, Dhananjaya P Singh, Anil Rai
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引用次数: 0

Abstract

Genome analysis of thermophilic cyanobacterium, Thermosynechococcus elongatus BP-1 revealed factors ruling choices of codons in this organism. Multiple parameters like Nc, GC3s, RSCU, Codon Adaptation Index (CAI), optimal and rare codons, codon-pair context and amino acid usage were analysed and compositional constraint was identified as major factor. Wide range of Nc values for the same GC3 content suggested the role of translational selection. Mutational bias is suggested at synonymous position. Among optimal codons for translation, most were GC-ending. Seven codons (AGA, AGG, AUA, UAA, UAG, UCA and UGA) were found to have least occurrence in the entire genome and except stop codons all were A-ending (exception AGG). Most widely used codon-pair in the genome are G-ending or C-ending and A-ending or U-ending codons make pair with G-ending or C-ending codons. Amino acids which are largely distributed in T. elongatus tend to use G-ending or C-ending codons most frequently. Findings showed cumulative role of translational selection, translational accuracy and gene expression levels with mutational bias as key player in codon selection pattern of this organism.

从密码子选择和使用的角度研究嗜热蓝藻热聚球菌的基因组。
对嗜热蓝藻热共生球菌(Thermosynechococcus elongatus BP-1)的基因组分析揭示了决定该生物密码子选择的因素。分析了Nc、GC3s、RSCU、密码子适应指数(CAI)、最优和罕见密码子、密码子对上下文和氨基酸使用等参数,并确定了组成约束是主要因素。相同GC3含量的Nc值范围较宽,说明了平移选择的作用。同义位置提示突变偏倚。在翻译的最优密码子中,大多数是gc末端的。AGA、AGG、AUA、UAA、UAG、UCA和UGA 7个密码子在整个基因组中出现最少,除终止密码子外均为a端(AGG除外)。基因组中最常用的密码子对是g端或c端,a端或u端密码子与g端或c端密码子配对。氨基酸主要分布在长形霉中,它们往往使用g端或c端密码子。结果表明,翻译选择、翻译准确性和基因表达水平与突变偏倚在该生物密码子选择模式中起着重要作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Bioinformatics Research and Applications
International Journal of Bioinformatics Research and Applications Health Professions-Health Information Management
CiteScore
0.60
自引率
0.00%
发文量
26
期刊介绍: Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.
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