Analysis of Codon Usage and Nucleotide Bias in Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2) Genes

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Research Paper 01/07/2021
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Analysis of Codon Usage and Nucleotide Bias in Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2) Genes

Abstract

SARS-CoV-2 has recently emerged as a virus that poses a significant public health concern. The genetic features concerning the codon usage of SARS-CoV-2 genes were analyzed by the relative synonymous codon usage, the relative strength of codon bias, the effective number of codons (ENC), the codon adaptation index, and neutrality plot. Compositional analysis indicated that G and C at the first and second codon positions significantly affect synonymous codon choices. The mutational bias toward A/U may confer a selective advantage. The results suggest that mutation, together with selection dynamics, may play an essential role in shaping the pattern of codon usages in SARS-CoV-2 genomes. Turning to the codon usage preference and codon pair association in the viral genome, some of the most preferentially used codon observed across the genome did not occur at similar magnitudes in all genes. The possible co-evolution of the virus and its adaptation to the animal host has been discussed based on the codon adaptation index and codon de-optimization index.

VIEWS 21

Wu F, Zhao S, Yu B. 2020.A new coronavirus associated with human respiratory disease in China. Nature 579, 265–269. https://doi.org/10.1038/s41586-020-2008-3

Chan JFW, Kok KH, Zhu Z,Chu H, To KKW, Yuan S, Yuen KY. 2020. Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan. Emerging Microbes & Infections 9(1), 221–236. https://doi.org/10.1080/22221751.2020.1719902

Wu A, Peng Y, Huang B. 2020a. Genome composition and divergence of the novel coronavirus (2019-nCoV) originating in China, Cell Host & Microbe 27, 325-328. https://doi.org/10.1016/j.chom.2020.02.001.

Liu Y. 2020. A code within the genetic code: codon usage regulates co-translational protein folding, Cell Communication and Signaling 18, 145. https://doi.org/10.1186/s12964-020-00642-66.

Coleman JR, Papamichail D, Skiena S, Futcher B, Wimmer E, Mueller S. 2008. Virus attenuation by genome-scale changes in codon pair bias. Science 320(5884), 1784-1787. https://doi.org/10.1126/science.1155761.

Baker SF, Nogales A, Martínez-Sobrido L. 2015. Downregulating viral gene expression: codon usage bias manipulation for the generation of novel influenza A virus vaccines: Future Virology 10(6), 715–730. https://doi.org/10.2217/fvl.1531.

Lytras S, Hughes J. 2020. Synonymous Dinucleotide Usage: A Codon-Aware Metric for Quantifying Dinucleotide Representation in Viruses. Viruses 12, 462. https://doi.org/10.3390/ v12040462.

Sharp PM, Wen-Hsiung L. 1986. An evolutionary perspective on synonymous codon usage in unicellular organisms. Journal of Molecular Evolution 24, 28–38. https://doi.org/10.1007/BF02099948.

Sahoo S, Das S. 2014. Analyzing gene expression and codon usage bias in diverse genomes using a variety of models. Current Bioinformatics 9, 102-112. https://doi.org/10.2174/1574893608999140109114247.

Rakshit R, Sahoo S. 2017. In Silico Prediction of Gene Expression Based on Codon Usage: A Mini Review. Journal of Investigative Genomics 4(2), 42-45. https://doi.org/10.15406/jig.2017.04.00063.

Wright F. 1990.The ‘effective number of codons’ used in a gene. Gene 87, 23–29. https://doi.org/10.1016/0378-1119(90)90491-9.

Khandia R, Singhal S,Kumar U, Ansari A, Tiwari R, Dhama K, Das J, Munjal A, Singh RK. 2019. Analysis of Nipah Virus Codon Usage and Adaptation to Hosts. Frontiers in Microbiology 10, 886. https://doi.org/10.3389 /fmicb.2019.00.886

Chen Y. 2013. A comparison of synonymous codon usage bias patterns in DNA and RNA virus genomes: quantifying the relative importance of mutational pressure and natural selection. BioMed Research International 2013, Article Id 406342. https://doi.org/ 10.1155/2013/406342.

Sharp PM, Li WH. 1987. The codon adaptation index– a measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Research 15, 1281– 1295. https://doi.org/10.1093/nar/15.3.1281.

Mueller S, Papamichail D, Coleman JR, Skiena S, Wimmer E. 2006. Reduction of the rate of poliovirus protein synthesis through large-scale codon deoptimization causes attenuation of viral virulence by lowering specific infectivity. J. Virology 80, 9687–9696. https://doi.org/10.1128/JVI.0073.8-06.

Butt AM, Nasrullah I, Qamar R, Tong Y.  2016. Evolution of codon usage in Zika virus genomes is host and vector specific. Emerging Microbes Infection 5, e107.  https://doi.org/10.1038/emi.2016.106

Belalov IS, Lukashev AN. 2013.Causes and implications of codon usage bias in RNA viruses. PLoS One 8, e56642. https://doi.org/10.1371/journal.pone.0056642.

Simmonds P, Xia W, Baillie JK, McKinnon K. 2013. Modelling mutational and selection pressures on dinucleotides in eukaryotic phyla –selection against CpG and UpA in cytoplasmically expressed RNA and in RNA viruses. BMC Genomics 14, 610. https://doi.org/10.1186/1471-2164-14-610.

Jang HS, Shin WJ, Lee JE, Do JT. 2017. CpG and Non-CpG Methylation in Epigenetic Gene Regulation and Brain Function. Genes (Basel) 8(6), 148. https://doi.org/10.3390/genes 8060148.

Vetsigian K, Goldenfeld N. 2009. Genome rhetoric and the emergence of compositional bias. PNAS 106, 215–220. https://doi.org/10.1073/pnas.0810122106.

Zhao F, Yu CH, Liu Y. 2017. Codon usage regulates protein structure and function by affecting translation elongation speed in Drosophila cells. Nucleic Acids Research 45(14), 8484–8492. https://doi.org/10.1093/nar/gkx501.

Puigbo P, Aragones L, Garcia-Vallve S. 2010. RCDI/eRCDI: a web-server to estimate codon usage deoptimization. BMC Research Notes 3, 87. https://doi.org/10.1186/1756-0500-3-87