Abstract

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.

Keywords: HBoV; Complete genome; Synonymous codon usage; Mutational bias; Selection pressure; Hierarchical cluster analysis

Abbreviations: bp, base pair; HBoV, Human Bocavirus; RSCU, relative synonymous codon usage; ENC, effective number of codons; COA, correspondence analysis; GC_3S, the frequency of G + C at the synonymous third position of sense codons; A_3S, T_3S, G_3S and C_3S, the adenine, thymine, guanine and cytosine content at synonymous third positions; S.D., standard deviation

Article Outline

1. Introduction

2. Materials and methods

2.1. Datasets

2.2. Statistical analysis

2.3. Measures of synonymous codon usage bias

2.4. Correspondence analysis (COA)

2.5. Analysis tools

3. Results

3.1. Synonymous codon usage in HBoV

3.2. Correspondence analysis on codon usage

3.3. Effect of mutational bias on the codon usage variation in HBoV

3.4. Gene function also drives the codon usage variation among different viruses

3.5. Effect of other factors on codon usage

3.6. Cluster analysis

4. Discussion

Appendix A. Supplementary data

References