Codon Usage and Phenotypic Divergences of SARS-CoV-2 Genes.
Maddalena DiluccaSergio ForcelloniAlexandros G GeorgakilasAndrea GiansantiAthanasia PavlopoulouPublished in: Viruses (2020)
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.
Keyphrases
- sars cov
- respiratory syndrome coronavirus
- genome wide
- genome wide identification
- bioinformatics analysis
- coronavirus disease
- endothelial cells
- type diabetes
- genome wide analysis
- cardiovascular disease
- gene expression
- respiratory tract
- gold nanoparticles
- quantum dots
- sensitive detection
- cardiovascular events
- clinical evaluation