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Analysis of synonymous codon usage in 11 Human Bocavirus isolates

机译:11种人类博卡病毒分离株的同义密码子使用情况分析

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Human Bocavirus (HBoV) is a novel virus which can cause respiratory tract disease in infants or children. In this study, the codon usage bias and the base composition variations in the available 11 complete HBoV genome sequences have been investigated. Although, there is a significant variation in codon usage bias among different HBoV genes, codon usage bias in HBoV is a little slight, which is mainly determined by the base compositions on the third codon position and the effective number of codons (ENC) value. The results of correspondence analysis (COA) and Spearman's rank correlation analysis reveals that the G + C compositional constraint is the main factor that determines the codon usage bias in HBoV and the gene's function also contributes to the codon usage in this virus. Moreover, it was found that the hydrophobicity of each protein and the gene length are also critical in affecting these viruses’ codon usage, although they were less important than that of the mutational bias and the genes’ function. At last, the relative synonymous codon usage (RSCU) of 44 genes from these 11 HBoV isolates is analyzed using a hierarchical cluster method. The result suggests that genes with same function yet from different isolates are classified into the same lineage and it does not depend on geographical location. These conclusions not only can offer an insight into the codon usage patterns and gene classification of HBoV, but also may help in increasing the efficiency of gene delivery/expression systems.
机译:人Bocavirus(HBoV)是一种新型病毒,可​​引起婴儿或儿童的呼吸道疾病。在这项研究中,已经对可用的11个完整HBoV基因组序列中的密码子使用偏倚和碱基组成变化进行了研究。尽管不同的HBoV基因之间的密码子使用偏好存在显着差异,但是HBoV中的密码子使用偏好略有变化,这主要取决于第三个密码子位置的碱基组成和有效密码子数(ENC)值。对应分析(COA)和Spearman秩相关分析的结果表明,G + C组成限制是决定HBoV中密码子使用偏倚的主要因素,该基因的功能也有助于该病毒的密码子使用。此外,发现每种蛋白质的疏水性和基因长度对于影响这些病毒的密码子使用也至关重要,尽管它们的重要性不如突变偏倚和基因功能重要。最后,使用分层聚类法分析了来自这11个HBoV分离株的44个基因的相对同义密码子使用(RSCU)。结果表明,来自不同菌株的具有相同功能的基因被归为同一谱系,并且不取决于地理位置。这些结论不仅可以提供对HBoV密码子使用方式和基因分类的深入了解,还可以帮助提高基因传递/表达系统的效率。

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