Analysis of 3.5 million SARS-CoV-2 sequences reveals unique mutational trends with consistent nucleotide and codon frequencies.

BACKGROUND: Since the onset of the SARS-CoV-2 pandemic, bioinformatic analyses have been performed to understand the nucleotide and synonymous codon usage features and mutational patterns of the virus. However, comparatively few have attempted to perform such analyses on a considerably large cohort of viral genomes while organizing the plethora of available sequence data for a month-by-month analysis to observe changes over time. Here, we aimed to perform sequence composition and mutation analysis of SARS-CoV-2, separating sequences by gene, clade, and timepoints, and contrast the mutational profile of SARS-CoV-2 to other comparable RNA viruses. METHODS: Using a cleaned, filtered, and pre-aligned dataset of over 3.5 million sequences downloaded from the GISAID database, we computed nucleotide and codon usage statistics, including calculation of relative synonymous codon usage values. We then calculated codon adaptation index (CAI) changes and a nonsynonymous/synonymous mutation ratio (dN/dS) over time for our dataset. Finally, we compiled information on the types of mutations occurring for SARS-CoV-2 and other comparable RNA viruses, and generated heatmaps showing codon and nucleotide composition at high entropy positions along the Spike sequence. RESULTS: We show that nucleotide and codon usage metrics remain relatively consistent over the 32-month span, though there are significant differences between clades within each gene at various timepoints. CAI and dN/dS values vary substantially between different timepoints and different genes, with Spike gene on average showing both the highest CAI and dN/dS values. Mutational analysis showed that SARS-CoV-2 Spike has a higher proportion of nonsynonymous mutations than analogous genes in other RNA viruses, with nonsynonymous mutations outnumbering synonymous ones by up to 20:1. However, at several specific positions, synonymous mutations were overwhelmingly predominant. CONCLUSIONS: Our multifaceted analysis covering both the composition and mutation signature of SARS-CoV-2 gives valuable insight into the nucleotide frequency and codon usage heterogeneity of SARS-CoV-2 over time, and its unique mutational profile compared to other RNA viruses.

Hepatitis B virus (HBV) codon adapts well to the gene expression profile of liver cancer: an evolutionary explanation for HBV's oncogenic role.

Due to the evolutionary arms race between hosts and viruses, viruses must adapt to host translation systems to rapidly synthesize viral proteins. Highly expressed genes in hosts have a codon bias related to tRNA abundance, the primary RNA translation rate determinant. We calculated the relative synonymous codon usage (RSCU) of three hepatitis viruses (HAV, HBV, and HCV), SARS-CoV-2, 30 human tissues, and hepatocellular carcinoma (HCC). After comparing RSCU between viruses and human tissues, we calculated the codon adaptation index (CAI) of viral and human genes. HBV and HCV showed the highest correlations with HCC and the normal liver, while SARS-CoV-2 had the strongest association with lungs. In addition, based on HCC RSCU, the CAI of HBV and HCV genes was the highest. HBV and HCV preferentially adapt to the tRNA pool in HCC, facilitating viral RNA translation. After an initial trigger, rapid HBV/HCV translation and replication may change normal liver cells into HCC cells. Our findings reveal a novel perspective on virus-mediated oncogenesis.

Relative synonymous codon usage of ORF1ab in SARS-CoV-2 and SARS-CoV.

BACKGROUND: COVID-19, as a novel coronavirus disease caused by new coronavirus SARS-CoV-2, spreads all over the world, and brings harm to human in many countries. Humans suffered a lot from both SARS-CoV-2 now and by SARS-CoV in the year 2003. It is important to understand the differences and the relationships between these two types of viruses. OBJECTIVE: To compare relative synonymous codon usage of ORF1ab gene in SARS-CoV-2 and SARS-CoV, relative synonymous codon usage of their genomes are studied in this paper from the bioinformatics perspective. METHODS: The ORF1ab gene, which is an important non-structural polyprotein coding gene and now used for nucleic acid detection markers in many measurement method, in both SARS-CoV-2 (30 strains) and SARS-CoV (20 strains) are considered to be the research object in the present paper. The relative synonymous codon usage values of the ORF1ab gene are calculated to characterize the differences and the evolutionary characteristics among 50 strains. RESULTS: There is a significant difference between SARS-CoV and SARS-CoV-2 when the relative synonymous codon usage value of ORF1ab genes is concerned. The results suggest that codon usage pattern of SARS-CoV is more similar to human than that of the SARS-CoV-2, and that the inner difference in SARS-CoV-2 strains is larger than that of SARS-CoV, which denote the larger diversity exits in the SARS-CoV-2 virus. CONCLUSION: These results show that the relative synonymous codon usage values in the coronavirus could be used for further research on their evolutionary phenomenon.

A scheme for inferring viral-host associations based on codon usage patterns identifies the most affected signaling pathways during COVID-19.

Understanding the molecular mechanism of COVID-19 pathogenesis helps in the rapid therapeutic target identification. Usually, viral protein targets host proteins in an organized fashion. The expression of any viral gene depends mostly on the host translational machinery. Recent studies report the great significance of codon usage biases in establishing host-viral protein-protein interactions (PPI). Exploring the codon usage patterns between a pair of co-evolved host and viral proteins may present novel insight into the host-viral protein interactomes during disease pathogenesis. Leveraging the similarity in codon usage patterns, we propose a computational scheme to recreate the host-viral protein-protein interaction network. We use host proteins from seventeen (17) essential signaling pathways for our current work towards understanding the possible targeting mechanism of SARS-CoV-2 proteins. We infer both negatively and positively interacting edges in the network. Further, extensive analysis is performed to understand the host PPI network topologically and the attacking behavior of the viral proteins. Our study reveals that viral proteins mostly utilize codons, rare in the targeted host proteins (negatively correlated interaction). Among them, non-structural proteins, NSP3 and structural protein, Spike (S), are the most influential proteins in interacting with multiple host proteins. While ranking the most affected pathways, MAPK pathways observe to be the worst affected during the SARS-CoV-2 infection. Several proteins participating in multiple pathways are highly central in host PPI and mostly targeted by multiple viral proteins. We observe many potential targets (host proteins) from the affected pathways associated with the various drug molecules, including Arsenic trioxide, Dexamethasone, Hydroxychloroquine, Ritonavir, and Interferon beta, which are either under clinical trial or in use during COVID-19.

A comparative genomics-based study of positive strand RNA viruses emphasizing on SARS-CoV-2 utilizing dinucleotide signature, codon usage and codon context analyses.

The novel corona virus disease or COVID-19 caused by a positive strand RNA virus (PRV) called SARS-CoV-2 is plaguing the entire planet as we conduct this study. In this study a multifaceted analysis was carried out employing dinucleotide signature, codon usage and codon context to compare and unravel the genomic as well as genic characteristics of the SARS-CoV-2 isolates and how they compare to other PRVs which represents some of the most pathogenic human viruses. The main emphasis of this study was to comprehend the codon biology of the SARS-CoV-2 in the backdrop of the other PRVs like Poliovirus, Japanese encephalitis virus, Hepatitis C virus, Norovirus, Rubella virus, Semliki Forest virus, Zika virus, Dengue virus, Human rhinoviruses and the Betacoronaviruses since codon usage pattern along with the nucleotide composition prevalent within the viral genome helps to understand the biology and evolution of viruses. Our results suggest discrete genomic dinucleotide signature within the PRVs. Some of the genes from the different SARS-CoV-2 isolates were also found to demonstrate heterogeneity in terms of their dinucleotide signature. The SARS-CoV-2 isolates also demonstrated a codon context trend characteristically dissimilar to the other PRVs. The findings of this study are expected to contribute to the developing global knowledge base in countering COVID-19.