Bioinformatics analysis of rabbit haemorrhagic disease virus genome

The 30 available complete RNA sequences of RHDV were obtained from GenBank randomly in January 2011. The serial number (SN), collection dates, isolated areas and GenBank accession numbers are listed in Table 1.

To investigate the characteristics of synonymous codon usage without the influence of amino acid composition, RSCU values of each codon in a ORF of RHDV were calculated according to previous reports (2 Sharp, Tuohy et al. 1986) as the followed formula:

Where g_ij is the observed number of the i th codon for j th amino acid which has n_i type of synonymous codons. The codons with RSCU value higher than 1.0 have positive codon usage bias, while codons with value lower than 1.0 has relative negative codon usage bias. As RSCU values of some codons are nearly equal to 1.0, it means that these codons are chosen equally and randomly.

The index GC3s means the fraction of the nucleotides G+C at the synonymous third codon position, excluding Met, Trp, and the termination codons.

The ENC, as the best estimator of absolute synonymous codon usage bias [16], was calculated for the quantification of the codon usage bias of each ORF [17]. The predicted values of ENC were calculated as

where s represents the given (G+C)₃% value. The values of ENC can also be obtained by EMBOSS CHIPS program [18].

Analyses were conducted with the Nei-Gojobori model [19], involving 30 nucleotide sequences. All positions containing gaps and missing data were eliminated. The values of dn, ds and ω (dn/ds) were calculated in MEGA4.0 [20].

Multivariate statistical analysis can be used to explore the relationships between variables and samples. In this study, correspondence analysis was used to investigate the major trend in codon usage variation among ORFs. In this study, the complete coding region of each ORF was represented as a 59 dimensional vector, and each dimension corresponds to the RSCU value of one sense codon (excluding Met, Trp, and the termination codons) [21].

Correlation analysis was used to identify the relationship between nucleotide composition and synonymous codon usage pattern [22]. This analysis was implemented based on the Spearman's rank correlation analysis way.

All statistical processes were carried out by with statistical software SPSS 17.0 for windows.

The values of nucleotide contents in complete coding region of all 30 RHDV genomes were analyzed and listed in Table 2 and Table 3. Evidently, (C+G)% content of the ORF1 fluctuated from 50.889 to 51.557 with a mean value of 51.14557, and (C+G)% content of the ORF2 were ranged from 35.593 to 40.113 with a mean value of 37.6624, which were indicating that nucleotides A and U were the major elements of ORF2 against ORF1. Comparing the values of A₃%, U₃%, C₃% and G₃%, it is clear that C₃% was distinctly high and A₃% was the lowest of all in ORF1 of RHDV, while U₃% was distinctly high and C₃% was the lowest of all in ORF2 of RHDV. The (C₃+G₃) % in ORF1 fluctuated from 57.014 to 58.977 with a mean value of 57.68287 and (C₃+G₃)% were range from 31.356 to 39.831 with a mean value of 34.8337. And the ENC values of ORF1 fluctuated from 54.192 to 55.491 with a mean value of 54.95 and ENC values of ORF2 displayed a far-ranging distribution from 39.771 to 51.964 with a mean value of 44.46. The ENC values of ORF1 were a little high indicating that there is a particular extent of codon preference in ORF1, but the codon usage is relatively randomly selected in ORF2 on the base of ENC values. The details of the overall relative synonymous codon usage (RSCU) values of 59 codons for each ORF in 30 RHDV genomes were listed in Table 4. Most preferentially used codons in ORF1 were C-ended or G-ended codons except Ala, Pro and Ser, however, A-ended or G-ended codons were preferred as the content of ORF2.

In addition, the dn, ds and ω(dN/dS) values of ORF1 were separately 0.014, 0.338 and 0.041, and the values of ORF2 were 0.034, 0.103 and 0.034, respectively. The ω values of two ORFs in RHDV genome are generally low, indicating that the RHDV whole genome is subject to relatively strong selective constraints.

COA was used to investigate the major trend in codon usage variation between two ORFs of all 30 RHDV selected for this study. After COA for RHDV Genome, one major trend in the first axis (f'₁) which accounted for 42.967% of the total variation, and another major trend in the second axis (f'₂) which accounted for 3.632% of the total variation. The coordinate of the complete coding region of each ORF was plotted in Figure 1 defining by the first and second principal axes. It is clear that coordinate of each ORF is relatively isolated. Interestingly, we found that relatively isolated spots from ORF2 tend to cluster into two groups: the ordinate value of one group (marked as Group 1) is positive value and the other one (marked as Group 2) is negative value. Interestingly, all of those strains isolated before 2000 belonged to Group 2.

To estimate whether the evolution of RHDV genome on codon usage was regulated by mutation pressure or natural selection, the A%, U%, C%, G% and (C+G)% were compared with A₃%, U₃%, C₃%, G₃% and (C₃+G₃)%, respectively (Table 5). There is a complex correlation among nucleotide compositions. In detail, A₃%, U₃%, C₃% and G₃% have a significant negative correlation with G%, C%, U% and A% and positive correlation with A%, U%, C% and G%, respectively. It suggests that nucleotide constraint may influence synonymous codon usage patterns. However, A₃% has non-correlation with U% and C%, and U₃% has non-correlation with A% and G%, respectively, which haven't indicated any peculiarity about synonymous codon usage. Furthermore, C₃% and G₃% have non-correlation with A%, G% and U%, C%, respectively, indicating these data don't reflect the true feature of synonymous codon usage as well. Therefore, linear regression analysis was implemented to analyze the correlation between synonymous codon usage bias and nucleotide compositions. Details of correlation analysis between the first two principle axes (f'₁ and f'₂) of each RHDV genome in COA and nucleotide contents were listed in Table 6. In surprise, only f2 values are closely related to base nucleotide A and G content on the third codon position only, suggesting that nucleotide A and G is a factor influencing the synonymous codon usage pattern of RHDV genome. However, f'₁ value has non-correlation with base nucleotide contents on the third codon position; it is observably suggest that codon usage patterns in RHDV were probably influenced by other factors, such as the second structure of viral genome and limits of host. In spite of that, compositional constraint is a factor shaping the pattern of synonymous codon usage in RHDV genome.

ENC-plot, as a general strategy, was utilized to investigate patterns of synonymous codon usage. The ENC-plots of ORFs constrained only by a C₃+G₃ composition will lie on or just below the curve of the predicted values [18]. ENC values of RHDV genomes were plotted against its corresponding (C₃+G₃) %. All of the spots lie below the curve of the predicted values, as shown in Figure 2, suggesting that the codon usage bias in all these 30 RHDV genomes is principally influenced by the mutational bias.

As we know, the efficiency of gene expression is influenced by regulator sequences or elements and codon usage bias. It reported that the RNA sequence of the 3-terminal 84 nucleotides of ORF1were found to be crucial for VP10 expression instead of the encoded peptide. VP10 coding by ORF2 has been reported as a low expressive structural protein against VP60 coding by ORF1 [5]. And its efficiency of translation is only 20% of VP60. According to results showed by Table 4, it revealed the differences in codon usage patterns of two ORFs, which is a possible factor reducing the expression of VP10.

Although VP10 encoded by ORF2, as a minor structural protein with unknown functions, has been described by LIU as a nonessential protein for virus infectivity, the ω value of ORF2 suggests VP10 plays an important role in the certain stage of whole RHDV lifecycle. After combining with low expression and ω value of VP10, we conjectured that VP10 might be beneficial for the replication, release or both of virus by inducing infected cell apoptosis initiate by RHDV. This mechanism has been confirmed in various positive-chain RNA viruses, including coxsackievirus, dengue virus, equine arterivirus, foot-and-mouth disease virus, hepatitis C virus, poliovirus, rhinovirus, and severe acute respiratory syndrome [23‐29], although the details remain elusive.

As preceding description, ENC reflects the evolution of codon usage variation and nucleotide composition to some degree. After the correlation analysis of ENC values between ORF1 and ORF2 (Table 7), the related coefficient of ENC values of two ORFs is 0.230, and p value is 0.222 more than 0.05. These data revealed that no correlation existed in ENC values of two ORFs, indicating that codon usage patterns and evolution of two ORFs are separated each other. Further, this information maybe helps us well understand why RSCU and ENC between two ORFs are quite different.

Interestingly, we found that relatively isolated spots from ORF2 tend to cluster into two groups: the ordinate value of one group (marked as Group 1) is positive value and the other one (marked as Group 2) is negative value. And all of those strains isolated before 2000 belonged to Group 2, including Italy-90, RHDV-V351, RHDV-FRG, BS89, RHDV-SD and M67473.1. Although RHDV has been reported as only one type, this may be a reference on dividing into two genotypes.