Analysis of the codon usage pattern in Middle East Respiratory Syndrome Coronavirus

Chen, Ye; Xu, Quanming; Yuan, Xianjun; Li, Xinxin; Zhu, Tao; Ma, Yanmei; Chen, Ji‐Long

doi:10.18632/oncotarget.22738

Cited by 23 publications

(26 citation statements)

References 54 publications

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“…(Pro) and GUU (Val) the least and most frequently used codons (Chen et al, 2017). The same results were found in this work for SARS-CoV-2 ORFs, since CCG y GUU resulted to be the least and most frequently hydrophobic codons (11 and 352 times, respectively).…”

Section: Mers-cov Codon Usage Revealed a Bias Among Hydrophobic Aminosupporting

confidence: 88%

“…These codons were also the least and most frequently hydrophilic codons used in SARS-CoV-2 ORF's (11 and 310 times, respectively). Similarly, CpG and UpU dinucleotide frequencies resulted to be the lowest and highest frequencies found in MERS-CoV (Chen et al, 2017). The same results were obtained in these studies on SARS-CoV-2, since CpG and UpU were the lowest and highest dinucleotide frequencies found (0.22 and 1.96, respectively) (see Supplementary Material Table 2).…”

Section: Mers-cov Codon Usage Revealed a Bias Among Hydrophobic Aminosupporting

confidence: 80%

“…These results indicate that the composition of dinucleotides also determines the variation in synonymous codon usage among SARS-CoV-2 strains. Comparison of SARS-CoV-2 RSCU values with the ones of SARS-CoV (Gu et al, 2004) and MERS-CoV (Chen et al, 2017) revealed a similar pattern for most of the codons (Table 1). Highly underrepresented codons ACG (Thr), GCG (Ala) and GGG (Gly) were observed in all three viruses in relation to human cells (Table 1).…”

Section: Codon Usage Preferences In Sars-cov-2mentioning

confidence: 74%

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A comprehensive analysis of genome composition and codon usage patterns of emerging coronaviruses

2020

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1 These authors contributed equally to this work. Highlights• A comprehensive genome and codon usage analysis of SARS-CoV-2 was performed.• SARS-CoV-2 has a distinct genome composition in relation to other βCoV strains.• The overall codon usage in SARS-CoV-2 is slightly biased.• Most of the highly frequent codons are A-and U-ending codons.• Different codon preferences in SARS-CoV-2 genes in relation to human ones were found.• These differences are due to codon usage preferences. J o u r n a l P r e -p r o o f Abstract An outbreak of atypical pneumonia caused by a novel Betacoronavirus (βCoV), named SARS-CoV-2 has been declared a public health emergency of international concern bythe World Health Organization. In order to gain insight into the emergence, evolution and adaptation of SARS-CoV-2 viruses, a comprehensive analysis of genome composition and codon usage of βCoV circulating in China was performed. A biased nucleotide composition was found for SARS-CoV-2 genome. This bias in genomic composition is reflected in its codon and amino acid usage patterns. The overall codon usage in SARS-CoV-2 is similar among themselves and slightly biased. Most of the highly frequent codons are A-and U-ending, which strongly suggests that mutational bias is the main force shaping codon usage in this virus. Significant differences in relative synonymous codon usage frequencies among SARS-CoV-2 and human cells were found. These differences are due to codon usage preferences.

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Section: Mers-cov Codon Usage Revealed a Bias Among Hydrophobic Aminosupporting

confidence: 88%

Section: Mers-cov Codon Usage Revealed a Bias Among Hydrophobic Aminosupporting

confidence: 80%

Section: Codon Usage Preferences In Sars-cov-2mentioning

confidence: 74%

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A comprehensive analysis of genome composition and codon usage patterns of emerging coronaviruses

2020

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“…In SARS-CoV-2, the most frequently used codons are CGU (arginine, 2.34 times) and GGU (glycine, 2.42), whereas the least used codons are GGG (glycine) and UCG (serine). Of note, the most frequently used codons for each amino acid end with either U or A [18]. Heatmap was drawn with the CIMminer software [20], which uses Euclidean distances and the average linkage algorithm.…”

Section: Codon Usage Of Sars-cov-2mentioning

confidence: 99%

Codon Usage and Phenotypic Divergences of SARS-CoV-2 Genes

Dilucca

Forcelloni

Georgakilas

et al. 2020

Viruses

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first occurred in Wuhan (China) in December of 2019, causes a severe acute respiratory illness with a high mortality rate, and has spread around the world. To gain an understanding of the evolution of the newly emerging SARS-CoV-2, we herein analyzed the codon usage pattern of SARS-CoV-2. For this purpose, we compared the codon usage of SARS-CoV-2 with that of other viruses belonging to the subfamily of Orthocoronavirinae. We found that SARS-CoV-2 has a high AU content that strongly influences its codon usage, which appears to be better adapted to the human host. We also studied the evolutionary pressures that influence the codon usage of five conserved coronavirus genes encoding the viral replicase, spike, envelope, membrane and nucleocapsid proteins. We found different patterns of both mutational bias and natural selection that affect the codon usage of these genes. Moreover, we show here that the two integral membrane proteins (matrix and envelope) tend to evolve slowly by accumulating nucleotide mutations on their corresponding genes. Conversely, genes encoding nucleocapsid (N), viral replicase and spike proteins (S), although they are regarded as are important targets for the development of vaccines and antiviral drugs, tend to evolve faster in comparison to the two genes mentioned above. Overall, our results suggest that the higher divergence observed for the latter three genes could represent a significant barrier in the development of antiviral therapeutics against SARS-CoV-2.

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“…We also note the most frequently used codons for each amino acid, ended in either U or A. [5] 2.4 The codon usage of 2019-nCoV is not optimized to the host.…”

Section: Codon Usage Of 2019-ncov Genome Strainsmentioning

confidence: 99%

Codon usage and evolutionary rates of the 2019-nCoV genes

Dilucca

Forcelloni

Pavlopoulou

et al. 2020

Preprint

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Severe acute respiratory syndrome coronavirus 2 (2019-nCoV), which first broke out in 1 Wuhan (China) in December of 2019, causes a severe acute respiratory illness with a mortality 2 ranging from 3% to 6%. To better understand the evolution of the newly emerging 2019-nCoV, in this 3 paper, we analyze the codon usage pattern of 2019-nCoV. For this purpose, we compare the codon 4 usage of 2019-nCoV with that of other 30 viruses belonging to the subfamily of orthocoronavirinae. 5 We found that 2019-nCoV shows a rich composition of AT nucleotides that strongly influences its 6 codon usage, which appears to be not optimized to human host. Then, we study the evolutionary 7 pressures influencing the codon usage and evolutionary rates of the sequences of five conserved 8 genes that encode the corresponding proteins (viral replicase, spike, envelope, membrane and 9 nucleocapsid) characteristic of coronaviruses. We found different patterns of both mutational bias 10 and nature selection that affect the codon usage of these genes at different extents. Moreover, we 11 show that the two integral membrane proteins proteins (matrix and envelope) tend to evolve slowly 12 by accumulating nucleotide mutations on their genes. Conversely, genes encoding nucleocapsid 13 (N), viral replicase and spike proteins are important targets for the development of vaccines and 14 antiviral drugs, tend to evolve faster as compared to other ones. Taken together, our results suggest 15 that the higher evolutionary rate observed for these two genes could represent a major barrier in the 16 development of antiviral therapeutics 2019-nCoV.

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Analysis of the codon usage pattern in Middle East Respiratory Syndrome Coronavirus

Cited by 23 publications

References 54 publications

A comprehensive analysis of genome composition and codon usage patterns of emerging coronaviruses

A comprehensive analysis of genome composition and codon usage patterns of emerging coronaviruses

Codon Usage and Phenotypic Divergences of SARS-CoV-2 Genes

Codon usage and evolutionary rates of the 2019-nCoV genes

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