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Synonymous Codon Usage Bias of E2 Genes of Classical Swine Fever Virus
Cao, H.W., # Zhang, H.#* and Cui, Y.D.
College of Biological Science and Technology, HeiLongJiang BaYi Agricultural University, DaQing 163319, China # Both authors contributed equally to this work.
* Corresponding author: Zhang, H., College of Bioscience and Technology, HeiLongJiang BaYi Agricultural University, 1 Xinyang road, Daqing 163319, PR China. E-mail: huazi8541@sina.com, tel.: +86 459 681 9299; fax: +86 459 681 9299.
AB ST RAC T
In this study, synonymous codon usage bias in 44 E2 genes of classical swine fever virus (CSFV) was analyzed. The relative synonymous codon usage (RSCU) and effective number of codons (ENC) values were used to estimate codon usage variation in each gene. Correspondence analysis (COA) was used to study the major trend in codon usage variation. The plot of ENC values against GC3s (at synonymous third codon position) revealed that mutational pressure rather than translational selection was the main factor determining the codon usage bias in CSFV E2 genes. Moreover, correlation analysis indicated that aromaticity of E2 genes also influenced the codon usage variation in a minor way. This study represents a comprehensive analysis to date of CSFV E2 genes’ codon usage patterns and provides a basic understanding of the mechanisms for codon usage bias. Key words: Classical swine fever virus, Envelope glycoprotein E2, Relative synonymous codon usage, Effective number of codons, Correspondence analysis.
Synonymous codons are not used randomly as has been previously shown in many prokaryotes and some lower eukaryotes (1, 2, 3). Studies of the synonymous codon usage can reveal information about the molecular evolution of individual genes and provide data to prepare genome-specific gene recognition algorithms (4), which detect protein coding regions in uncharacterized genomic DNA (5). In addition to mutational pressure, translational selection is also influenced by non-random codon usage (6). To date, codon usage bias and nucleotide composition has been studied in great detail for many organisms such as bacteria (7), yeast (8), Drosophila (9, 10), and mammals (1). However, there are only a few reports on factors determining synonymous codon usage bias and nucleotide composition in viruses, especially in animal viruses.
Israel Journal of Veterinary Medicine Vol. 67 (4) December 2012
INTRODUCTION
Classical swine fever virus (CSFV) an enveloped positive-stranded RNA virus belongs to the Pestivirus genus of the Flaviviridae family. The genome contains a large open reading frame (ORF) which encodes for a unique polyprotein of about 3898 amino acids that give rise to 12 final cleavage proteins (11). Envelope protein E2 is the major envelope glycoprotein exposed on the outer surface of the virion and represents an important target for induction of the immune response during infection (12). Furthermore, the E2 gene is extensively used for evolutionary analysis (13, 14). Phylogenetic analysis indicates CSFV could be classified into 3 groups (Group 1, 2 and 3) and 10 subgroups (15). Recently, Tao et al. have analyzed the positive selection pressure acting on the CSFV envelope protein genes, and identified several specific codons subject to diversifying positive selection (16, 17). In order to better understand the characteristics of the
Synonymous Codon Usage of Classical Swine Fever Virus
253
Research Articles
E2 gene of CSFV and to reveal more information about its evolution, we have analyzed the synonymous codon usage of E2 genes. MATERIALS AND METHODS
AA Phe Leu Tyr ter ter Leu
Codon UUU UUC UUA UUG UAU UAC UAA UAG CUU CUC CUA CUG CAU CAC CAA CAG AUU AUC AUA AUG AAU AAC AAA AAG GUU GUC GUA GUG GAU GAC GAA GAG
Table 1: Synonymous codon usage in CSFV E2 gene N RSCU
0.92 0.53
AA
Codon
N
RSCU
0.40 1.37
Virus sequences
The available 44 complete coding sequence (CDS) of E2 gene of CSFV were downloaded from GeneBank website (http://www.ncbi.nlm.nih. gov/) and European Molecular Biology Library (EMBL) website (http://www.ebi.ac.uk/embl/). Sequences with > 99% sequence identities were excluded. All information are listed in Table 1.
Codon usage indices analysis
His Gln Ile
Relative synonymous codon usage (RSCU) values of each codon in each genes were used to measure the synonymous codon usage (3). The preferred codon usage for each gene was analyzed using GCUA software package (version 1.0) (http:// bioinf.may.ie/downloads.html) (18). The effective number of codons (ENC) was used to quantify the codon usage bias of each gene (19). The GC index (G+C content) was used to calculate the overall GC content in each genes, while the index GC3’s (at synonymous third codon position) was used to calculate the fraction of GC nucleotides at the synonymous third codon position (excluding Met (Methionine), Trp (Tryptophan), and the termination codons) (20). The general average hydrophobicity (GRAVY) score and the frequency of aromatic amino acids (AROMO) in the hypothetical translated gene product were also computed (21).
Met Asn Lys Val
Asp Glu
402 342 125 295 269 611 0 1 91 178 383 387 55 294 220 85 137 132 368 182 280 218 322 575 162 425 344 614 363 511 450 510
1.08
Ser
0.61 0.00 0.00 0.39
0.76 1.63 1.39
1.26
Cys ter Trp Pro
0.32
1.68 1.44 0.56 0.62 1.00 0.88
1.44
Arg
0.65
1.73
Thr
1.12 0.72 0.42
1.10 0.89 1.28
Ser Arg Ala
0.83
1.17 0.94 1.06
1.59
Gly
UCU UCC UCA UCG UGU UGC UGA UGG CCU CCC CCA CCG CGU CGC CGA CGG ACU ACC ACA ACG AGU AGC AGA AGG GCU GCC GCA GCG GGU GGC GGA GGG
50 171 179 4 142 516 0 301 202 248 219 123 1 6 1 46 362 628 446 138 99 246 341 427 204 117 294 155 350 311 274 530
0.03
0.43 1.57
1.43
0.00 1.00
1.02 1.25
0.62 0.04 0.34
0.92 1.60 0.01 0.01
1.11
1.13 0.35
0.79 1.97 2.49 1.06 0.61 1.53 0.96 0.75 1.45 3.12
0.81 0.85
Correspondence analysis
The relationships between variables and samples were explored using multivariate statistical analysis. Correspondence analysis (COA) was used to study the major trend in codon usage variation (22). Each dimension corresponded to the RSCU value of one sense codon (excluding AUG, UGG, and termination codons). Major trends within this dataset were determined using measures of relative inertia and genes ordered according to their positions along the axis of major inertia (23).
The preferentially used codons (RSCU>1.2) for each amino acid are displayed in bold. AA, amino acids; N, number of codons; RSCU, cumulative relative synonymous codon usage; ter, termination codon.
Statistical analysis
Correlation analysis was carried out using Spearman’s rank ried out using the statistical analysis software SPSS Statistics p≤0.05. correlation analysis method. All statistical analyses were car(Version 17.0). Statistical significance was considered at
Israel Journal of Veterinary Medicine Vol. 67 (4) December 2012
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Table 2: Data information of classical swine fever virus E2 genes used in this study CSFV strains
gi|311990282|
gi|219964344| gi|219964342| gi|152032049| gi|238627772| gi|152032077| gi|152032082| gi|152032059| gi|219964322| gi|152032063| gi|152032069| gi|219964324| gi|152032079| gi|152032075| gi|219964326| gi|219964332| gi|219964334| gi|219964330| gi|152032065| gi|219964328| gi|219964336| gi|152032073| gi|223049419| gi|223049417| gi|221063259| gi|221063257| gi|221063263| gi|221063261| gi|221063255| gi|152032084| gi|152032080| gi|152032051| gi|152032061| gi|219964340| gi|152032057| gi|152032055| gi|152032053| gi|152032067| gi|219964338| gi|152032071| gi|15283988| gi|15283986| gi|221063267| gi|221063265|
HQ317681 FJ456876 FJ456875 EF683605 FJ977628 EF683619 EF683622 EF683610 FJ456865 EF683612 EF683615 FJ456866 EF683620 EF683618 FJ456867 FJ456870 FJ456871 FJ456869 EF683613 FJ456868 FJ456872 EF683617 FJ607780 FJ607779 FJ582644 FJ582643 FJ598610 FJ598609 FJ582642 EF683623 EF683621 EF683606 EF683611 FJ456874 EF683609 EF683608 EF683607 EF683614 FJ456873 EF683616 AY027673 AY027672 FJ598612 FJ598611
Accession No.
52.22 52.68 52.84 52.73 53.14 52.16 51.63 51.05 51.84 51.83 52.13 52.08 51.45 52.24 51.39 52.09 51.46 51.41 51.84 51.60 52.51 53.44 51.08 50.48 51.74 50.12 50.83 51.61 51.26 52.15 51.75 52.85 52.02 52.17 52.02 52.34 52.21 52.29 52.05 51.78 51.48 51.64 50.49 54.69
ENC
0.533 0.537 0.539 0.539 0.562 0.564 0.564 0.566 0.566 0.566 0.564 0.565 0.568 0.564 0.564 0.561 0.557 0.564 0.555 0.558 0.554 0.552 0.552 0.552 0.558 0.558 0.552 0.552 0.547 0.550 0.541 0.536 0.546 0.551 0.552 0.547 0.541 0.550 0.547 0.543 0.554 0.545 0.523 0.530
GC3s
0.487 0.492 0.492 0.494 0.508 0.505 0.502 0.506 0.503 0.507 0.503 0.505 0.504 0.501 0.503 0.502 0.502 0.502 0.499 0.499 0.498 0.498 0.498 0.496 0.502 0.501 0.495 0.497 0.493 0.500 0.497 0.492 0.496 0.497 0.497 0.496 0.492 0.496 0.495 0.495 0.493 0.491 0.485 0.488
GC
-0.165416 -0.141019 -0.140751 -0.110724 -0.135389 -0.164611 -0.117426 -0.159786 -0.142359 -0.139410 -0.152011 -0.135389 -0.122312 -0.132976 -0.122252 -0.135657 -0.151206 -0.141555 -0.141555 -0.149866 -0.148526 -0.160322 -0.152279 -0.139142 -0.146649 -0.131904 -0.186595 -0.171314 -0.141019 -0.121716 -0.130027 -0.146381 -0.152011 -0.149062 -0.150402 -0.148526 -0.151475 -0.150402 -0.127614 -0.151207 -0.128418 -0.100536 -0.129759 -0.164879
GRAVY
0.120643 0.117962
0.117962 0.115281 0.117962 0.117962 0.115281 0.117962 0.117962 0.117962 0.117962 0.115281 0.115281 0.117962 0.118280
AROMO
0.112601
0.117962 0.112601 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.115281 0.117962 0.117962 0.117962 0.117962 0.120643 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.115281 0.115281 0.112601 0.117962
Israel Journal of Veterinary Medicine Vol. 67 (4) December 2012
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Research Articles
Fig 1: A plot of value of the first and second axis of each CSFV E2 gene in COA. The first axis accounts for 24.11% of all variation and the second axis accounts for 18.26% of total vibrations.
RESULTS AND DISCUSSION
Correspondence analysis of codon usage
Synonymous codon usage variation in E2 genes
In order to investigate the extent of codon bias in CSFV E2 genes, the (Relative Synonymous Codon Usage) RSCU values of different codon in E2 genes were calculated. The details of cumulative codon usage of 59 codons in 44 CSFV E2 genes are displayed in Table 1. The preferentially used codons were A-ended, C-ended, and G-ended codons. It was interesting to note that no U-ended codons were used as preferential codons. Effective number of codons (ENC) values range from 20 to 61; the larger the extent of codon preference in a gene, the smaller the corresponding ENC value. In a highly biased gene where only one codon was used for each amino acid, the ENC value equalled 20. Conversely, in a gene exhibiting no bias, the value was 61 (19). Our data showed that the ENC values of different CSFV genes vary from 50.12 to 54.69, with a mean of 51.93 and S.D. of 0.8031, which indicated that the codon usage bias in CSFV E2 genes was small. Moreover, GC and GC3s values were calculated and are listed in Table 2. The average GC content of CSFV E2 genes was 0.4978 (mean values varying from 0.485 to 0.508, with a S.D. of 0.0054), while average GC3s content was 0.552 (mean values varying from 0.523 to 0.568, with a S.D. of 0.011). This results are consistent with previous observations that CSFV are not GC-poor genomes (17).
To investigate synonymous codon usage variation, Correspondence analysis (COA) was studied for 44 CSFV E2 genes selected for this study. Figure 1 depicts the position of each E2 gene on the plane defined by the first and second principal axes generated by COA on RSCU values. The first principal axis accounted for 24.11% of the total variation, and the next three axes accounted for 18.26%, 13.45%, and 11.34% of the variation, respectively. This observation indicated that although the first major axis could explains a substantial amount of variation in trends in codon usage, the second major axis also had an appreciable impact on total variation in synonymous codon usage.
Mutational bias as the main factor determining codon usage variation
Mutational pressure and translational selection are thought to be the main factors accounting for codon usage variation in genes (24). In order to investigate whether codon usage variation of different genes is determined by mutational bias, correlation analysis was employed to correlate the first two axes of COA with codon usage indices. Correlation analysis showed that axis 1 of COA and axis 2 were both correlated with GC (r = -0.62, P<0.001), GC3s (r = -0.653, P<0.001), GC (r = -0.312, P<0.05), GC3s (r = -0.307, P<0.05), respectively, which indicated that the patterns of base composiIsrael Journal of Veterinary Medicine Vol. 67 (4) December 2012
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Cao, H.W.
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tion were most likely the results of mutational pressure, and not natural selection, since the effects were present at all codon positions. Moreover, ENC-plot (ENC plotted against GC3’s) was used as part of a general strategy to investigate patterns of synonymous codon usage (22). Genes, whose codon choice is constrained only by a G + C mutation bias, should lie on or just below the curve of the predicted values (5, 19). All of the spots were located below the expected curve as in Figure 2, indicating that the codon usage bias Fig 2:. Effective number of codons used in each gene plotted against the GC3s. The in these 44 CSFV E2 genes was greatcontinuous curve plots the relationship between GC3’s and ENC in the absence of selection. All of spots lie below the expected curve. ly influenced by the GC compositional constraints. In addition, a significantly negative correlation (r = -0.327, P<0.05) cated that the degree of hydrophobicity was not associated between GC3s and ENC values was observed, which indiwith condon usage variation, whereas, the aromatic amino cated the patterns of condon usage also appear to be closely acids (Phe, Tyr, Trp) were associated with the codon usage related to the GC content on the third codon position. These variation to some extent. results indicated that most of the codon usage bias among genes was directly related to the nucleotide composition. CONCLUSION Therefore, it is concluded that the compositional constraint (caused by mutation bias) is the main determinant of the Synonymous codon usage biases in 44 CSFV E2 genes were variation in synonymous codon usage. analyzed, and the results showed that CSFV E2 genes had low codon usage bias. Mutational pressure is the main factor Aromaticity and hydrophobicity affect codon usage determining the codon usage biases. In addition, aromaticity To test whether selection pressure contributes to the codon could partially account for the codon usage variation. usage variation among E2 genes, we performed a correlation analysis to evaluate whether GRAVY and AROMO values ACKNOWLED GEMENT were related to first two axes of COA, ENC and GC3s (25). The study was supported by the Technology Research Foundation Our results showed that only AROMO was correlated with of Education Department of HeiLongJiang Province, China axis 1 (r =-0.306, P<0.05) (Table 3), while GRAVY was not (12511352). correlated with two axes, ENC and GC3s. The results indiTable 3: Summary of correlation analysis between GRAVY, AROMO, ENC, and the first two axes in COA GRAVY AROMO 1. Marin, A., Bertranpetit, J., Oliver, J.L. and Medina, J.R.: Variation in G+C content and codon choice: differences among synonymous codon groups in vertebrate genes. Nucleic Acids Res. 17: 6181-6189, 1989. 2. Aota, S. and Ikemura, T.: Diversity in G+C content at the third position of codons in vertebrate genes and its cause. Nucleic Acids Res. 14: 6345-6355, 1986. 3. Sharp, P.M., Tuohy, T.M.F. and Mosurski, K.R.: Codon usage in yeast cluster-analysis clearly differentiates highly and lowly expressed genes. Nucleic Acids Res. 14: 5125-5143, 1986. Synonymous Codon Usage of Classical Swine Fever Virus
REFERENCES
r r
Axis 1
P P
0.092
-0.257 -0.306
Axis2
0.381 0.745
-0.135 0.050
ENC
0.389 0.684 -0.63
-0.133
0.098 0.13
GC3s
0.528
0.043*
0.402
r - correlation coefficient; *P-value ≤0.05.
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4. Bulmer, M.: The selection-mutation-drift theory of synonymous codon usage. Genetics. 129: 897-907, 1991. 5. Zhong, J.C., Li, Y.M., Zhao, S., Liu, S.G. and Zhang, Z.D.: Mutation pressure shapes codon usage in the GC-Rich genome of foot-and-mouth disease virus. Virus Genes. 35: 767-776, 2007. 6. Zhou, T., Gu, W.J., Ma, J.M., Sun, X. and Lu, Z.H.: Analysis of synonymous codon usage in H5N1 virus and other influenza A viruses. BioSystems. 81: 77-86, 2005. 7. Wright, F. and Bibb, M.J.: Codon usage in the G+C rich Streptomyces genome. Gene 113: 55-65, 1992. 8. Sharp, P.M. and Lloyd, A.T.: Regional base composition variation along yeast chromosome III evolution of chromosome primary structure. Nucleic Acids Res. 21: 179-183, 1993. 9. Rubin, G.M.: The Drosophila genome project: a progress report. Trends in Genetics. 14: 340-343, 1998. 10. Hiroshi, A., Richard, M.K. and Adam, E.W.: Mutation pressure, natural selection, and the evolution of base composition in Drosophila. Genetica. 102: 49-60, 1998. 11. Fan, Y.F., Zhao, Q., Zhao, Y., Wang, Q., Ning, Y.B. and Zhang, Z.Q.: Complete genome sequence of attenuated low-temperature Thiverval strain of classical swine fever virus. Virus Genes. 36: 531-538, 2008. 12. Montesino, R., Toledo, J.R., Sanchez, B., Zamora, Y., Barrera, M., Royle, L., Rudd, P.M., Dwek, R.A., Harvey, D.J. and Cremata, J.A.: N-Glycosylation Pattern of E2 Glycoprotein from classical swine fever virus. J. Proteo. Res. 8: 546-555, 2009. 13. Paton, D.J., McGoldrick, A., Greiser-Wilke, I., Parchariyanon, S., Song, J.Y., Liou, P.P., Stadejek, T., Lowings, J.P., Bjorklund, H. and Belak, S.: Genetic typing of classical swine fever virus. Vet. Micr. 73: 137-157, 2000. 14. Chen, N., Hu, H.X., Zhang, Z.F., Shuai, J.B., Jiang, L.L. and Fang, W.H.: Genetic diversity of the envelope glycoprotein E2
15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25.
of classical swine fever virus: Recent isolates branched away from historical and vaccine strains. Vet. Micr. 127: 286-299, 2008. Paton, D.J. and Greiser-Wilke, I.: Classical swine fever - an update. Res.Vet. Sci. 75: 169-178, 2003. Zhang, H., Wang, Y.H., Cao, H.W. and Cui, Y.D.: Phylogenetic analysis of E2 genes of classical swine fever virus in China. Isr. J. Vet. Med. 65: 151-155, 2010. Tao, P., Dai, L., Luo, M.C., Tang, F.Q., Tien, P. and Pan, Z.S.: Analysis of synonymous codon usage in classical swine fever virus. Virus Genes. 38: 104-112, 2009. Sharp, P.M. and Li, W.H.: Codon usage in regulatory genes in Escherichia coli does not reflect selection for rare codons. Nucleic Acids Res. 14: 7737-7749, 1986. Wright, F.: The effective number of codons used in a gene. Gene. 87: 23-29, 1990. Richard, J.E., Lin, K. and Tan, T.: A functional significance for codon third bases. Gene. 245: 291-298, 2000. Kyte, J. and Doolittle, R.: A simple method for displaying the hydropathic character of a protein. J. Mol. Biol. 157: 105-132, 1982. Gupta, S.K. and Ghosh, T.C.: Expressivity is the main factor in dictating the codon usage variation among the genes in Pseudomonas aeruginosa. Gene. 273: 63-70, 2001. Grantham, R., Gautier, C., Gouy, M., Jacobzone, M. and Mercier, R.: Codon catalogue usage is a genome strategy for genome expressivity. Nucleic Acids Res. 9: 43-75, 1981. Gareth, M.J. and Edward, C.H.: The extent of codon usage bias in human RNA viruses and its evolutionary origin. Virus Res. 92: 1-7, 2003. Lobry, J.R. and Gautier, C.: Hydrophobicity, expressivity and aromaticity are the major trends of amino acid usage in 999 Escherichia coli chromosome encoded genes. Nucleic Acid Res. 22: 3174-3180, 1994.
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Israel Journal of Veterinary Medicine Vol. 67 (4) December 2012
Synonymous Codon Usage Bias of E2 Genes of Classical Swine Fever Virus
Cao, H.W., # Zhang, H.#* and Cui, Y.D.
College of Biological Science and Technology, HeiLongJiang BaYi Agricultural University, DaQing 163319, China # Both authors contributed equally to this work.
* Corresponding author: Zhang, H., College of Bioscience and Technology, HeiLongJiang BaYi Agricultural University, 1 Xinyang road, Daqing 163319, PR China. E-mail: huazi8541@sina.com, tel.: +86 459 681 9299; fax: +86 459 681 9299.
AB ST RAC T
In this study, synonymous codon usage bias in 44 E2 genes of classical swine fever virus (CSFV) was analyzed. The relative synonymous codon usage (RSCU) and effective number of codons (ENC) values were used to estimate codon usage variation in each gene. Correspondence analysis (COA) was used to study the major trend in codon usage variation. The plot of ENC values against GC3s (at synonymous third codon position) revealed that mutational pressure rather than translational selection was the main factor determining the codon usage bias in CSFV E2 genes. Moreover, correlation analysis indicated that aromaticity of E2 genes also influenced the codon usage variation in a minor way. This study represents a comprehensive analysis to date of CSFV E2 genes’ codon usage patterns and provides a basic understanding of the mechanisms for codon usage bias. Key words: Classical swine fever virus, Envelope glycoprotein E2, Relative synonymous codon usage, Effective number of codons, Correspondence analysis.
Synonymous codons are not used randomly as has been previously shown in many prokaryotes and some lower eukaryotes (1, 2, 3). Studies of the synonymous codon usage can reveal information about the molecular evolution of individual genes and provide data to prepare genome-specific gene recognition algorithms (4), which detect protein coding regions in uncharacterized genomic DNA (5). In addition to mutational pressure, translational selection is also influenced by non-random codon usage (6). To date, codon usage bias and nucleotide composition has been studied in great detail for many organisms such as bacteria (7), yeast (8), Drosophila (9, 10), and mammals (1). However, there are only a few reports on factors determining synonymous codon usage bias and nucleotide composition in viruses, especially in animal viruses.
Israel Journal of Veterinary Medicine Vol. 67 (4) December 2012
INTRODUCTION
Classical swine fever virus (CSFV) an enveloped positive-stranded RNA virus belongs to the Pestivirus genus of the Flaviviridae family. The genome contains a large open reading frame (ORF) which encodes for a unique polyprotein of about 3898 amino acids that give rise to 12 final cleavage proteins (11). Envelope protein E2 is the major envelope glycoprotein exposed on the outer surface of the virion and represents an important target for induction of the immune response during infection (12). Furthermore, the E2 gene is extensively used for evolutionary analysis (13, 14). Phylogenetic analysis indicates CSFV could be classified into 3 groups (Group 1, 2 and 3) and 10 subgroups (15). Recently, Tao et al. have analyzed the positive selection pressure acting on the CSFV envelope protein genes, and identified several specific codons subject to diversifying positive selection (16, 17). In order to better understand the characteristics of the
Synonymous Codon Usage of Classical Swine Fever Virus
253
Research Articles
E2 gene of CSFV and to reveal more information about its evolution, we have analyzed the synonymous codon usage of E2 genes. MATERIALS AND METHODS
AA Phe Leu Tyr ter ter Leu
Codon UUU UUC UUA UUG UAU UAC UAA UAG CUU CUC CUA CUG CAU CAC CAA CAG AUU AUC AUA AUG AAU AAC AAA AAG GUU GUC GUA GUG GAU GAC GAA GAG
Table 1: Synonymous codon usage in CSFV E2 gene N RSCU
0.92 0.53
AA
Codon
N
RSCU
0.40 1.37
Virus sequences
The available 44 complete coding sequence (CDS) of E2 gene of CSFV were downloaded from GeneBank website (http://www.ncbi.nlm.nih. gov/) and European Molecular Biology Library (EMBL) website (http://www.ebi.ac.uk/embl/). Sequences with > 99% sequence identities were excluded. All information are listed in Table 1.
Codon usage indices analysis
His Gln Ile
Relative synonymous codon usage (RSCU) values of each codon in each genes were used to measure the synonymous codon usage (3). The preferred codon usage for each gene was analyzed using GCUA software package (version 1.0) (http:// bioinf.may.ie/downloads.html) (18). The effective number of codons (ENC) was used to quantify the codon usage bias of each gene (19). The GC index (G+C content) was used to calculate the overall GC content in each genes, while the index GC3’s (at synonymous third codon position) was used to calculate the fraction of GC nucleotides at the synonymous third codon position (excluding Met (Methionine), Trp (Tryptophan), and the termination codons) (20). The general average hydrophobicity (GRAVY) score and the frequency of aromatic amino acids (AROMO) in the hypothetical translated gene product were also computed (21).
Met Asn Lys Val
Asp Glu
402 342 125 295 269 611 0 1 91 178 383 387 55 294 220 85 137 132 368 182 280 218 322 575 162 425 344 614 363 511 450 510
1.08
Ser
0.61 0.00 0.00 0.39
0.76 1.63 1.39
1.26
Cys ter Trp Pro
0.32
1.68 1.44 0.56 0.62 1.00 0.88
1.44
Arg
0.65
1.73
Thr
1.12 0.72 0.42
1.10 0.89 1.28
Ser Arg Ala
0.83
1.17 0.94 1.06
1.59
Gly
UCU UCC UCA UCG UGU UGC UGA UGG CCU CCC CCA CCG CGU CGC CGA CGG ACU ACC ACA ACG AGU AGC AGA AGG GCU GCC GCA GCG GGU GGC GGA GGG
50 171 179 4 142 516 0 301 202 248 219 123 1 6 1 46 362 628 446 138 99 246 341 427 204 117 294 155 350 311 274 530
0.03
0.43 1.57
1.43
0.00 1.00
1.02 1.25
0.62 0.04 0.34
0.92 1.60 0.01 0.01
1.11
1.13 0.35
0.79 1.97 2.49 1.06 0.61 1.53 0.96 0.75 1.45 3.12
0.81 0.85
Correspondence analysis
The relationships between variables and samples were explored using multivariate statistical analysis. Correspondence analysis (COA) was used to study the major trend in codon usage variation (22). Each dimension corresponded to the RSCU value of one sense codon (excluding AUG, UGG, and termination codons). Major trends within this dataset were determined using measures of relative inertia and genes ordered according to their positions along the axis of major inertia (23).
The preferentially used codons (RSCU>1.2) for each amino acid are displayed in bold. AA, amino acids; N, number of codons; RSCU, cumulative relative synonymous codon usage; ter, termination codon.
Statistical analysis
Correlation analysis was carried out using Spearman’s rank ried out using the statistical analysis software SPSS Statistics p≤0.05. correlation analysis method. All statistical analyses were car(Version 17.0). Statistical significance was considered at
Israel Journal of Veterinary Medicine Vol. 67 (4) December 2012
254
Cao, H.W.
Research Articles
Table 2: Data information of classical swine fever virus E2 genes used in this study CSFV strains
gi|311990282|
gi|219964344| gi|219964342| gi|152032049| gi|238627772| gi|152032077| gi|152032082| gi|152032059| gi|219964322| gi|152032063| gi|152032069| gi|219964324| gi|152032079| gi|152032075| gi|219964326| gi|219964332| gi|219964334| gi|219964330| gi|152032065| gi|219964328| gi|219964336| gi|152032073| gi|223049419| gi|223049417| gi|221063259| gi|221063257| gi|221063263| gi|221063261| gi|221063255| gi|152032084| gi|152032080| gi|152032051| gi|152032061| gi|219964340| gi|152032057| gi|152032055| gi|152032053| gi|152032067| gi|219964338| gi|152032071| gi|15283988| gi|15283986| gi|221063267| gi|221063265|
HQ317681 FJ456876 FJ456875 EF683605 FJ977628 EF683619 EF683622 EF683610 FJ456865 EF683612 EF683615 FJ456866 EF683620 EF683618 FJ456867 FJ456870 FJ456871 FJ456869 EF683613 FJ456868 FJ456872 EF683617 FJ607780 FJ607779 FJ582644 FJ582643 FJ598610 FJ598609 FJ582642 EF683623 EF683621 EF683606 EF683611 FJ456874 EF683609 EF683608 EF683607 EF683614 FJ456873 EF683616 AY027673 AY027672 FJ598612 FJ598611
Accession No.
52.22 52.68 52.84 52.73 53.14 52.16 51.63 51.05 51.84 51.83 52.13 52.08 51.45 52.24 51.39 52.09 51.46 51.41 51.84 51.60 52.51 53.44 51.08 50.48 51.74 50.12 50.83 51.61 51.26 52.15 51.75 52.85 52.02 52.17 52.02 52.34 52.21 52.29 52.05 51.78 51.48 51.64 50.49 54.69
ENC
0.533 0.537 0.539 0.539 0.562 0.564 0.564 0.566 0.566 0.566 0.564 0.565 0.568 0.564 0.564 0.561 0.557 0.564 0.555 0.558 0.554 0.552 0.552 0.552 0.558 0.558 0.552 0.552 0.547 0.550 0.541 0.536 0.546 0.551 0.552 0.547 0.541 0.550 0.547 0.543 0.554 0.545 0.523 0.530
GC3s
0.487 0.492 0.492 0.494 0.508 0.505 0.502 0.506 0.503 0.507 0.503 0.505 0.504 0.501 0.503 0.502 0.502 0.502 0.499 0.499 0.498 0.498 0.498 0.496 0.502 0.501 0.495 0.497 0.493 0.500 0.497 0.492 0.496 0.497 0.497 0.496 0.492 0.496 0.495 0.495 0.493 0.491 0.485 0.488
GC
-0.165416 -0.141019 -0.140751 -0.110724 -0.135389 -0.164611 -0.117426 -0.159786 -0.142359 -0.139410 -0.152011 -0.135389 -0.122312 -0.132976 -0.122252 -0.135657 -0.151206 -0.141555 -0.141555 -0.149866 -0.148526 -0.160322 -0.152279 -0.139142 -0.146649 -0.131904 -0.186595 -0.171314 -0.141019 -0.121716 -0.130027 -0.146381 -0.152011 -0.149062 -0.150402 -0.148526 -0.151475 -0.150402 -0.127614 -0.151207 -0.128418 -0.100536 -0.129759 -0.164879
GRAVY
0.120643 0.117962
0.117962 0.115281 0.117962 0.117962 0.115281 0.117962 0.117962 0.117962 0.117962 0.115281 0.115281 0.117962 0.118280
AROMO
0.112601
0.117962 0.112601 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.115281 0.117962 0.117962 0.117962 0.117962 0.120643 0.117962 0.117962 0.117962 0.117962 0.117962 0.117962 0.115281 0.115281 0.112601 0.117962
Israel Journal of Veterinary Medicine Vol. 67 (4) December 2012
Synonymous Codon Usage of Classical Swine Fever Virus
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Research Articles
Fig 1: A plot of value of the first and second axis of each CSFV E2 gene in COA. The first axis accounts for 24.11% of all variation and the second axis accounts for 18.26% of total vibrations.
RESULTS AND DISCUSSION
Correspondence analysis of codon usage
Synonymous codon usage variation in E2 genes
In order to investigate the extent of codon bias in CSFV E2 genes, the (Relative Synonymous Codon Usage) RSCU values of different codon in E2 genes were calculated. The details of cumulative codon usage of 59 codons in 44 CSFV E2 genes are displayed in Table 1. The preferentially used codons were A-ended, C-ended, and G-ended codons. It was interesting to note that no U-ended codons were used as preferential codons. Effective number of codons (ENC) values range from 20 to 61; the larger the extent of codon preference in a gene, the smaller the corresponding ENC value. In a highly biased gene where only one codon was used for each amino acid, the ENC value equalled 20. Conversely, in a gene exhibiting no bias, the value was 61 (19). Our data showed that the ENC values of different CSFV genes vary from 50.12 to 54.69, with a mean of 51.93 and S.D. of 0.8031, which indicated that the codon usage bias in CSFV E2 genes was small. Moreover, GC and GC3s values were calculated and are listed in Table 2. The average GC content of CSFV E2 genes was 0.4978 (mean values varying from 0.485 to 0.508, with a S.D. of 0.0054), while average GC3s content was 0.552 (mean values varying from 0.523 to 0.568, with a S.D. of 0.011). This results are consistent with previous observations that CSFV are not GC-poor genomes (17).
To investigate synonymous codon usage variation, Correspondence analysis (COA) was studied for 44 CSFV E2 genes selected for this study. Figure 1 depicts the position of each E2 gene on the plane defined by the first and second principal axes generated by COA on RSCU values. The first principal axis accounted for 24.11% of the total variation, and the next three axes accounted for 18.26%, 13.45%, and 11.34% of the variation, respectively. This observation indicated that although the first major axis could explains a substantial amount of variation in trends in codon usage, the second major axis also had an appreciable impact on total variation in synonymous codon usage.
Mutational bias as the main factor determining codon usage variation
Mutational pressure and translational selection are thought to be the main factors accounting for codon usage variation in genes (24). In order to investigate whether codon usage variation of different genes is determined by mutational bias, correlation analysis was employed to correlate the first two axes of COA with codon usage indices. Correlation analysis showed that axis 1 of COA and axis 2 were both correlated with GC (r = -0.62, P<0.001), GC3s (r = -0.653, P<0.001), GC (r = -0.312, P<0.05), GC3s (r = -0.307, P<0.05), respectively, which indicated that the patterns of base composiIsrael Journal of Veterinary Medicine Vol. 67 (4) December 2012
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Research Articles
tion were most likely the results of mutational pressure, and not natural selection, since the effects were present at all codon positions. Moreover, ENC-plot (ENC plotted against GC3’s) was used as part of a general strategy to investigate patterns of synonymous codon usage (22). Genes, whose codon choice is constrained only by a G + C mutation bias, should lie on or just below the curve of the predicted values (5, 19). All of the spots were located below the expected curve as in Figure 2, indicating that the codon usage bias Fig 2:. Effective number of codons used in each gene plotted against the GC3s. The in these 44 CSFV E2 genes was greatcontinuous curve plots the relationship between GC3’s and ENC in the absence of selection. All of spots lie below the expected curve. ly influenced by the GC compositional constraints. In addition, a significantly negative correlation (r = -0.327, P<0.05) cated that the degree of hydrophobicity was not associated between GC3s and ENC values was observed, which indiwith condon usage variation, whereas, the aromatic amino cated the patterns of condon usage also appear to be closely acids (Phe, Tyr, Trp) were associated with the codon usage related to the GC content on the third codon position. These variation to some extent. results indicated that most of the codon usage bias among genes was directly related to the nucleotide composition. CONCLUSION Therefore, it is concluded that the compositional constraint (caused by mutation bias) is the main determinant of the Synonymous codon usage biases in 44 CSFV E2 genes were variation in synonymous codon usage. analyzed, and the results showed that CSFV E2 genes had low codon usage bias. Mutational pressure is the main factor Aromaticity and hydrophobicity affect codon usage determining the codon usage biases. In addition, aromaticity To test whether selection pressure contributes to the codon could partially account for the codon usage variation. usage variation among E2 genes, we performed a correlation analysis to evaluate whether GRAVY and AROMO values ACKNOWLED GEMENT were related to first two axes of COA, ENC and GC3s (25). The study was supported by the Technology Research Foundation Our results showed that only AROMO was correlated with of Education Department of HeiLongJiang Province, China axis 1 (r =-0.306, P<0.05) (Table 3), while GRAVY was not (12511352). correlated with two axes, ENC and GC3s. The results indiTable 3: Summary of correlation analysis between GRAVY, AROMO, ENC, and the first two axes in COA GRAVY AROMO 1. Marin, A., Bertranpetit, J., Oliver, J.L. and Medina, J.R.: Variation in G+C content and codon choice: differences among synonymous codon groups in vertebrate genes. Nucleic Acids Res. 17: 6181-6189, 1989. 2. Aota, S. and Ikemura, T.: Diversity in G+C content at the third position of codons in vertebrate genes and its cause. Nucleic Acids Res. 14: 6345-6355, 1986. 3. Sharp, P.M., Tuohy, T.M.F. and Mosurski, K.R.: Codon usage in yeast cluster-analysis clearly differentiates highly and lowly expressed genes. Nucleic Acids Res. 14: 5125-5143, 1986. Synonymous Codon Usage of Classical Swine Fever Virus
REFERENCES
r r
Axis 1
P P
0.092
-0.257 -0.306
Axis2
0.381 0.745
-0.135 0.050
ENC
0.389 0.684 -0.63
-0.133
0.098 0.13
GC3s
0.528
0.043*
0.402
r - correlation coefficient; *P-value ≤0.05.
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