Base Composition and Host Adaptation of the SARS-CoV-2: Insight From the Codon Usage Perspective

Codon usage bias of goose circovirus and its adaptation to host

Goose circovirus (GoCV), a potential immunosuppressive virus possessing a circular single-stranded DNA genome, is widely distributed in both domesticated and wild geese. This virus infection causes significant economic losses in the waterfowl industry. The codon usage patterns of viruses reflect the evolutionary history and genetic architecture, allowing them to adapt quickly to changes in the external environment, particularly to their hosts. In this study, we retrieved the coding sequences (Rep and Cap) and the genome of GoCV from GenBank, conducting comprehensive research to explore the codon usage patterns in 144 GoCV strains. The overall codon usage of the GoCV strains was relatively similar and exhibited a slight bias. The effective number of codons (ENC) indicated a low overall extent of codon usage bias (CUB) in GoCV. Combined with the base composition and relative synonymous codon usage (RSCU) analysis, the results revealed a bias toward A- and G-ending codons in the overall codon usage. Analysis of the ENC-GC3s plot and neutrality plot suggested that natural selection plays an important role in shaping the codon usage pattern of GoCV, with mutation pressure having a minor influence. Furthermore, the correlations between ENC and relative indices, as well as correspondence analysis (COA), showed that hydrophobicity and geographical distribution also contribute to codon usage variation in GoCV, suggesting the possible involvement of natural selection. In conclusion, GoCV exhibits comparatively slight CUB, with natural selection being the major factor shaping the codon usage pattern of GoCV. Our research contributes to a deeper understanding of GoCV evolution and its host adaptation, providing valuable insights for future basic studies and vaccine design related to GoCV.

Systematic analysis of the codon usage patterns of African swine fever virus genome coding sequences reveals its host adaptation phenotype

African swine fever (ASF) is a severe haemorrhagic disease caused by the African swine fever virus (ASFV), transmitted by ticks, resulting in high mortality among domestic pigs and wild boars. The global spread of ASFV poses significant economic threats to the swine industry. This study employs diverse analytical methods to explore ASFV's evolution and host adaptation, focusing on codon usage patterns and associated factors. Utilizing phylogenetic analysis methods including neighbour-joining and maximum-likelihood, 64 ASFV strains were categorized into four clades. Codon usage bias (CUB) is modest in ASFV coding sequences. This research identifies multiple factors - such as nucleotide composition, mutational pressures, natural selection and geographical diversity - contributing to the formation of CUB in ASFV. Analysis of relative synonymous codon usage reveals CUB variations within clades and among ASFVs and their hosts. Both Codon Adaptation Index and Similarity Index analyses confirm that ASFV strains are highly adapted to soft ticks (Ornithodoros moubata) but less so to domestic pigs, which could be a result of the long-term co-evolution of ASFV with ticks. This study sheds light on the factors influencing ASFV's codon usage and fitness dynamics, enriching our understanding of its evolution, adaptation and host interactions.

Base composition, adaptation, and evolution of goose astroviruses: codon-based investigation

Goose astroviruses (GoAstVs) are causative agents that account for fatal infection of goslings characterized by visceral urate deposition, resulting in severe economic losses in major goose-producing regions in China since 2017. In this study, we sought to unravel the intrinsic properties associated with adaptation and evolution in the host environment of GoAstVs. Consistent results from phylogenetic analysis and correspondence analysis performed on the codon usage patterns (CUPs) reveal 2 clusters of GoAstVs, namely, GoAstV-1 and GoAstV-2. However, multiple similar compositional characteristics were found, despite the high divergence between GoAstV-1 and GoAstV-2. Studies on the base composition of GoAstVs reveal an A/U bias, indicating a compositional constraint, while natural selection prevailed in determining the CUPs in the virus genome based on our neutrality plot analysis, reflecting high adaptive pressure to fit the host environment. Codon adaptation index (CAI) analysis revealed a higher degree of fitness to the CUPs of the corresponding host for GoAstVs than avian influenza virus and betacoronaviruses, which may be a favorable factor contributing to the high pathogenicity and wide distribution of GoAstVs in goslings. In addition, GoAstVs were less adapted to ducks and chickens, with significantly lower CAI values than to geese, which may be a reason for the different prevalence of GoAstVs among these species. Extensive investigations on dinucleotide distribution revealed a significant suppression of the CpG and UpA motifs in the virus genome, which may facilitate adaptation to the host's innate immune system by evading surveillance. In addition, our study reported the trends of increasing fitness to the host's microenvironment for GoAstVs through increasing adaptation to host CUPs and ongoing reduction of CpG motifs in the virus genome. The present analysis deepens our understanding of the basic biology, pathogenesis, adaptation and evolutionary pattern of GoAstVs, and contributes to the development of novel antiviral strategies.

Optimization and Deoptimization of Codons in SARS-CoV-2 and Related Implications for Vaccine Development

The spread of coronavirus disease 2019 (COVID-19), caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), has progressed into a global pandemic. To date, thousands of genetic variants have been identified among SARS-CoV-2 isolates collected from patients. Sequence analysis reveals that the codon adaptation index (CAI) values of viral sequences have decreased over time but with occasional fluctuations. Through evolution modeling, it is found that this phenomenon may result from the virus's mutation preference during transmission. Using dual-luciferase assays, it is further discovered that the deoptimization of codons in the viral sequence may weaken protein expression during virus evolution, indicating that codon usage may play an important role in virus fitness. Finally, given the importance of codon usage in protein expression and particularly for mRNA vaccines, it is designed several codon-optimized Omicron BA.2.12.1, BA.4/5, and XBB.1.5 spike mRNA vaccine candidates and experimentally validated their high levels of expression. This study highlights the importance of codon usage in virus evolution and provides guidelines for codon optimization in mRNA and DNA vaccine development.

Insights into the Evolution and Host Adaptation of the Monkeypox Virus from a Codon Usage Perspective: Focus on the Ongoing 2022 Outbreak

The exceptionally widespread outbreak of human monkeypox, an emerging zoonosis caused by the monkeypox virus (MPXV), with more than 69,000 confirmed cases in 100 non-endemic countries since 2022, is a major public health concern. Codon usage patterns reflect genetic variation and adaptation to new hosts and ecological niches. However, detailed analyses of codon usage bias in MPXV based on large-scale genomic data, especially for strains responsible for the 2022 outbreak, are lacking. In this study, we analyzed codon usage in MPXV and its relationship with host adaptation. We confirmed the ongoing outbreak of MPXVs belonging to the West Africa (WA) lineage by principal component analysis based on their codon usage patterns. The 2022 outbreak strains had a relatively low codon usage bias. Codon usage of MPXVs was shaped by mutation and natural selection; however, different from past strains, codon usage in the 2022 outbreak strains was predominantly determined by mutation pressure. Additionally, as revealed by the codon adaptation index (CAI), relative codon deoptimization index (RCDI), and similarity index (SiD) analyses, the codon usage patterns of MPXVs were also affected by their hosts. In particular, the 2022 outbreak strains showed slightly but significantly greater adaptation to many primates, including humans, and were subjected to stronger selection pressure induced by hosts. Our results suggest that MPXVs contributing to the 2022 outbreak have unique evolutionary features, emphasizing the importance of sustained monitoring of their transmission and evolution.

Codon usage bias of Venezuelan equine encephalitis virus and its host adaption

Venezuelan equine encephalitis virus (VEEV) is an emerging zoonotic virus in the alphavirus genus. It can be transmitted to humans due to spillover from equid-mosquito cycles. The symptoms caused by VEEV include fever, headache, myalgia, nausea, and vomiting. It can also cause encephalitis in severe cases. The evolutionary features of VEEV are largely unknown. In this study, we comprehensively analyzed the codon usage pattern of VEEV by computing a variety of indicators, such as effective number of codons (ENc), codon adaptation index (CAI), relative synonymous codon usage (RSCU), on 130 VEEV coding sequences retrieved from GenBank. The results showed that the codon usage bias of VEEV is relatively low. ENc-GC3s plot, neutrality plot, and CAI-ENc correlation analyses supported that translational selection plays an important role in shaping the codon usage pattern of VEEV whereas the mutation pressure has a minor influence. Analysis of RSCU values showed that most of the preferred codons in VEEV are C/G-ended. Analysis of dinucleotide composition found that all CG- and UA-containing codons are not preferentially used. Phylogenetic analysis showed that VEEV isolates can be clustered into three genera and evolutionary force affects the codon usage pattern. Furthermore, a correspondence analysis (COA) showed that aromaticity and hydrophobicity as well as geographical distribution also have certain effects on the codon usage variation of VEEV, suggesting the possible involvement of translational selection. Overall, the codon usage of VEEV is comparatively slight and translational selection might be the main factor that shapes the codon usage pattern of VEEV. This study will promote our understanding about the evolution of VEEV and its host adaption, and might provide some clues for preventing the cross-species transmission of VEEV.

Evolution of codon and amino acid usage in bacterial protein toxins

Toxin proteins are secreted by most pathogens as an integral part of pathogenic mechanism(s). The toxins act by either damaging the host cell membrane (for example, pore-forming toxins and RTX toxins) or by modulation of important cellular pathways (for example, inhibition of protein translation by ribosome-inactivating proteins). The mechanism of action of these toxins provides the pathogen with strategies for adaptation in the unfavorable host environment. Though, secreted by different pathogenic species, the protein toxins seem to share common features that allow the protein to bind to specific molecules and enter the host cell. Earlier studies have suggested role of several events like horizontal gene transfer and insertion-deletion mutations in evolution of protein toxins. The present study involving 125 bacterial protein toxins secreted by 49 pathogenic bacteria focuses on the role and constraints of the bacterial genome on evolution of codon and amino acid usage in respective bacterial protein toxins. We compare the nucleotide composition, codon and dinucleotide usage trends between different classes of bacterial protein toxins and between individual toxins and the parent bacterial genome expressing the toxin(s).

Variation in synonymous evolutionary rates in the SARS-CoV-2 genome

Introduction

Coronavirus disease 2019 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Influential variants and mutants of this virus continue to emerge, and more effective virus-related information is urgently required for identifying and predicting new mutants. According to earlier reports, synonymous substitutions were considered phenotypically silent; thus, such mutations were frequently ignored in studies of viral mutations because they did not directly cause amino acid changes. However, recent studies have shown that synonymous substitutions are not completely silent, and their patterns and potential functional correlations should thus be delineated for better control of the pandemic.

Methods

In this study, we estimated the synonymous evolutionary rate (SER) across the SARS-CoV-2 genome and used it to infer the relationship between the viral RNA and host protein. We also assessed the patterns of characteristic mutations found in different viral lineages.

Results

We found that the SER varies across the genome and that the variation is primarily influenced by codon-related factors. Moreover, the conserved motifs identified based on the SER were found to be related to host RNA transport and regulation. Importantly, the majority of the existing fixed-characteristic mutations for five important virus lineages (Alpha, Beta, Gamma, Delta, and Omicron) were significantly enriched in partially constrained regions.

Discussion

Taken together, our results provide unique information on the evolutionary and functional dynamics of SARS-CoV-2 based on synonymous mutations and offer potentially useful information for better control of the SARS-CoV-2 pandemic.

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.

Recombination in sarbecovirus lineage and mutations/insertions in spike protein are linked to the emergence and adaptation of SARS-CoV-2

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan city, China in December 2019 and thereafter its spillover across the world has created a global pandemic and public health crisis. Right after, there has been intense interest in understanding how the SARS-CoV-2 originated and evolved. This paper also aims to shed light on the origin and evolution of SARS-CoV- 2. A consensus result based on whole genome phylogeny, gene tree analysis, and genetic similarity study revealed that SARS-CoV-2 evolved from Bat-CoV-RaTG13. Furthermore, recombination analysis indicated that probable origin of SARS-CoV-2 is the results of ancestral intra-species recombination events between bat coronaviruses belonging to Sarbecovirus sub-genus. Multiple sequence alignment (MSA) revealed the insertion of four amino acid residues "PRRA" (Proline-Arginine-Arginine-Alanine) to the S1/S2 site in the spike protein of SARS-CoV-2, and structural modeling of spike protein of bat-CoV-RaTG13 also shows a high number of mutations at one of the receptor binding domains (RBD). Acquisition of the furin cleavage sites ("PRRA") along with high number of mutations at one of its RBD is probably responsible for the adaptation of SARS-CoV-2 into human systems. Furthermore, the codon adaptation index (CAI) was used to quantify the magnitude of adaptive efficacy of SARS-CoV-2 in human host in comparison with SARS-CoV. The CAI result showed a relatively less adaptive efficacy of the newly emerged SARS-CoV-2 to the human systems, which might be an indication of its mild clinical severity and progression compared to SARS-CoVs.

Componential usage patterns in dengue 4 viruses reveal their better evolutionary adaptation to humans

There have been at least four types of dengue outbreaks in the past few years. The evolutionary characteristics of dengue viruses have aroused great concerns. The evolutionary characteristics of dengue 4 viruses are studied in the present study based on their base usage patterns and codon usage patterns. The effective number of codons and relative synonymous codon usage (RSCU) values of four types of dengue viruses were counted or calculated. The Kullback–Leibler (K–L) divergences of relative synonymous codon usage from dengue viruses to humans and the Kullback–Leibler divergences of amino acid usage patterns from dengue viruses to humans were calculated to explore the adaptation levels of dengue viruses. The results suggested that: (1) codon adaptation in dengue 4 viruses occurred through an evolutionary process from 1956 to 2021, (2) overall relative synonymous codon usage values of dengue 4 viruses showed more similarities to humans than those of other subtypes of dengue viruses, and (3) the smaller Kullback–Leibler divergence of amino acid usage and relative synonymous codon usage from dengue viruses to humans indicated that the dengue 4 viruses adapted to human hosts better. All results indicated that both mutation pressure and natural selection pressure contributed to the codon usage pattern of dengue 4 viruses more obvious than to other subtypes of dengue viruses and that the dengue 4 viruses adapted to human hosts better than other types of dengue viruses during their evolutionary process.

Natural selection plays a significant role in governing the codon usage bias in the novel SARS-CoV-2 variants of concern (VOC)

The ongoing prevailing COVID-19 pandemic caused by SARS-CoV-2 is becoming one of the major global health concerns worldwide. The SARS-CoV-2 genome encodes spike (S) glycoprotein that plays a very crucial role in viral entry into the host cell via binding of its receptor binding domain (RBD) to the host angiotensin converting enzyme 2 (ACE2) receptor. The continuously evolving SARS-CoV-2 genome results in more severe and transmissible variants characterized by the emergence of novel mutations called 'variants of concern' (VOC). The currently designated alpha, beta, gamma, delta and omicron VOC are the focus of this study due to their high transmissibility, increased virulence, and concerns for decreased effectiveness of the available vaccines. In VOC, the spike (S) gene and other non-structural protein mutations may affect the efficacies of the approved COVID-19 vaccines. To understand the diversity of SARS-CoV-2, several studies have been performed on a limited number of sequences. However, only a few studies have focused on codon usage bias (CUBs) pattern analysis of all the VOC strains. Therefore, to evaluate the evolutionary divergence of all VOC S-genes, we performed CUBs analysis on 300,354 sequences to understand the evolutionary relationship with its adaptation in different hosts, i.e., humans, bats, and pangolins. Base composition and RSCU analysis revealed the presence of 20 preferred AU-ended and 10 under-preferred GC-ended codons. In addition, CpG was found to be depleted, which may be attributable to the adaptive response by viruses to escape from the host defense process. Moreover, the ENC values revealed a higher bias in codon usage in the VOC S-gene. Further, the neutrality plot analysis demonstrated that S-genes analyzed in this study are under 83.93% influence of natural selection, suggesting its pivotal role in shaping the CUBs. The CUBs pattern of S-genes was found to be very similar among all the VOC strains. Interestingly, we observed that VOC strains followed a trend of antagonistic codon usage with respect to the human host. The identified CUBs divergence would help to understand the virus evolution and its host adaptation, thus help design novel vaccine strategies against the emerging VOC strains. To the best of our knowledge, this is the first report for identifying the evolution of CUBs pattern in all the currently identified VOC.

Translational Control of COVID-19 and Its Therapeutic Implication

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of COVID-19, which has broken out worldwide for more than two years. However, due to limited treatment, new cases of infection are still rising. Therefore, there is an urgent need to understand the basic molecular biology of SARS-CoV-2 to control this virus. SARS-CoV-2 replication and spread depend on the recruitment of host ribosomes to translate viral messenger RNA (mRNA). To ensure the translation of their own mRNAs, the SARS-CoV-2 has developed multiple strategies to globally inhibit the translation of host mRNAs and block the cellular innate immune response. This review provides a comprehensive picture of recent advancements in our understanding of the molecular basis and complexity of SARS-CoV-2 protein translation. Specifically, we summarize how this viral infection inhibits host mRNA translation to better utilize translation elements for translation of its own mRNA. Finally, we discuss the potential of translational components as targets for therapeutic interventions.

Deep learning based on biologically interpretable genome representation predicts two types of human adaptation of SARS-CoV-2 variants

Explosively emerging SARS-CoV-2 variants challenge current nomenclature schemes based on genetic diversity and biological significance. Genomic composition-based machine learning methods have recently performed well in identifying phenotype–genotype relationships. We introduced a framework involving dinucleotide (DNT) composition representation (DCR) to parse the general human adaptation of RNA viruses and applied a three-dimensional convolutional neural network (3D CNN) analysis to learn the human adaptation of other existing coronaviruses (CoVs) and predict the adaptation of SARS-CoV-2 variants of concern (VOCs). A markedly separable, linear DCR distribution was observed in two major genes—receptor-binding glycoprotein and RNA-dependent RNA polymerase (RdRp)—of six families of single-stranded (ssRNA) viruses. Additionally, there was a general host-specific distribution of both the spike proteins and RdRps of CoVs. The 3D CNN based on spike DCR predicted a dominant type II adaptation of most Beta, Delta and Omicron VOCs, with high transmissibility and low pathogenicity. Type I adaptation with opposite transmissibility and pathogenicity was predicted for SARS-CoV-2 Alpha VOCs (77%) and Kappa variants of interest (58%). The identified adaptive determinants included D1118H and A570D mutations and local DNTs. Thus, the 3D CNN model based on DCR features predicts SARS-CoV-2, a major type II human adaptation and is qualified to predict variant adaptation in real time, facilitating the risk-assessment of emerging SARS-CoV-2 variants and COVID-19 control.

Unheeded SARS-CoV-2 proteins? A deep look into negative-sense RNA

SARS-CoV-2 is a novel positive-sense single-stranded RNA virus from the Coronaviridae family (genus Betacoronavirus), which has been established as causing the COVID-19 pandemic. The genome of SARS-CoV-2 is one of the largest among known RNA viruses, comprising of at least 26 known protein-coding loci. Studies thus far have outlined the coding capacity of the positive-sense strand of the SARS-CoV-2 genome, which can be used directly for protein translation. However, it has been recently shown that transcribed negative-sense viral RNA intermediates that arise during viral genome replication from positive-sense viruses can also code for proteins. No studies have yet explored the potential for negative-sense SARS-CoV-2 RNA intermediates to contain protein-coding loci. Thus, using sequence and structure-based bioinformatics methodologies, we have investigated the presence and validity of putative negative-sense ORFs (nsORFs) in the SARS-CoV-2 genome. Nine nsORFs were discovered to contain strong eukaryotic translation initiation signals and high codon adaptability scores, and several of the nsORFs were predicted to interact with RNA-binding proteins. Evolutionary conservation analyses indicated that some of the nsORFs are deeply conserved among related coronaviruses. Three-dimensional protein modeling revealed the presence of higher order folding among all putative SARS-CoV-2 nsORFs, and subsequent structural mimicry analyses suggest similarity of the nsORFs to DNA/RNA-binding proteins and proteins involved in immune signaling pathways. Altogether, these results suggest the potential existence of still undescribed SARS-CoV-2 proteins, which may play an important role in the viral lifecycle and COVID-19 pathogenesis.

Codon usage, phylogeny and binding energy estimation predict the evolution of SARS-CoV-2

In the frames of a One Health strategy, i.e. a strategy should be able to predict susceptibility to infection in both humans and animals, developing a SARS-CoV-2 mutation tracking system is a goal. We observed that the phylogenetic proximity of vertebrate ACE2 receptors does not affect the binding energy for the viral spike protein. However, all viral variants seem to bind ACE2 better in many animals than in humans. Moreover, two observations highlight that the evolution of the virus started at the beginning of 2020 and culminated with the appearance of the variants. First, codon usage analysis shows that the B.1.1.7 (alpha), B.1.351 (beta) and B.1.617.2 (delta) variants, similar in the use of codons, are also similar to a virus sampled in January 2020. Second, the host-specific D614G mutation becomes prevalent starting from March 2020. Overall, we show that SARS-CoV-2 undergoes a process of molecular evolution that begins with the optimization of codons followed by the functional optimization of the spike protein.

Study on the Characteristic Codon Usage Pattern in Porcine Epidemic Diarrhea Virus Genomes and Its Host Adaptation Phenotype

Porcine epidemic diarrhea virus (PEDV), which classified in the genus Alphacoronavirus, family Coronaviridae, is one of the most important pathogens that cause heavy economic losses in pig industry. Although intensive mutation and recombination analysis of PEDV strains were provided, systematic genome analysis were needed to elucidate the evolution mechanism and codon usage adaptation profiles of the pathogen. Here, a comprehensive investigation was carried out to reveal the systematic evolutionary processes of synonymous codon usage and host-adapted evolution phenotype of PEDV genome. We found a low codon usage bias (CUB) in PEDV genome and that nucleotide compositions, natural selection, mutation pressure and geographical diversity shapes the codon usage patterns of PEDV, with natural selection dominated the overall codon usage bias in PEDV than the others. By using the relative codon deoptimization index (RCDI) and similarity index (SiD) analysis, we observed that genotype II PEDV strains showed the highest level of adaptation phenotype to Sus scrofa than another divergent clade. To the best of our knowledge, this is the first comprehensive report elaborating the codon usage and host adaptation of PEDV. The findings offer an insight into our understanding of factors involved in PEDV evolution, adaptation and fitness toward their hosts.

SARS-CoV-2 competes with host mRNAs for efficient translation by maintaining the mutations favorable for translation initiation

During SARS-CoV-2 proliferation, the translation of viral RNAs is usually the rate-limiting step. Understanding the molecular details of this step is beneficial for uncovering the origin and evolution of SARS-CoV-2 and even for controlling the pandemic. To date, it is unclear how SARS-CoV-2 competes with host mRNAs for ribosome binding and efficient translation. We retrieved the coding sequences of all human genes and SARS-CoV-2 genes. We systematically profiled the GC content and folding energy of each CDS. Considering that some fixed or polymorphic mutations exist in SARS-CoV-2 and human genomes, all algorithms and analyses were applied to both pre-mutate and post-mutate versions. In SARS-CoV-2 but not human, the 5-prime end of CDS had lower GC content and less RNA structure than the 3-prime part, which was favorable for ribosome binding and efficient translation initiation. Globally, the fixed and polymorphic mutations in SARS-CoV-2 had created an even lower GC content at the 5-prime end of CDS. In contrast, no similar patterns were observed for the fixed and polymorphic mutations in human genome. Compared with human RNAs, the SARS-CoV-2 RNAs have less RNA structure in the 5-prime end and thus are more favorable of fast translation initiation. The fixed and polymorphic mutations in SARS-CoV-2 are further amplifying this advantage. This might serve as a strategy for SARS-CoV-2 to adapt to the human host.

Compelling Evidence Suggesting the Codon Usage of SARS-CoV-2 Adapts to Human After the Split From RaTG13

SARS-CoV-2 needs to efficiently make use of the resources from hosts in order to survive and propagate. Among the multiple layers of regulatory network, mRNA translation is the rate-limiting step in gene expression. Synonymous codon usage usually conforms with tRNA concentration to allow fast decoding during translation. It is acknowledged that SARS-CoV-2 has adapted to the codon usage of human lungs so that the virus could rapidly proliferate in the lung environment. While this notion seems to nicely explain the adaptation of SARS-CoV-2 to lungs, it is unable to tell why other viruses do not have this advantage. In this study, we retrieve the GTEx RNA-seq data for 30 tissues (belonging to over 17 000 individuals). We calculate the RSCU (relative synonymous codon usage) weighted by gene expression in each human sample, and investigate the correlation of RSCU between the human tissues and SARS-CoV-2 or RaTG13 (the closest coronavirus to SARS-CoV-2). Lung has the highest correlation of RSCU to SARS-CoV-2 among all tissues, suggesting that the lung environment is generally suitable for SARS-CoV-2. Interestingly, for most tissues, SARS-CoV-2 has higher correlations with the human samples compared with the RaTG13-human correlation. This difference is most significant for lungs. In conclusion, the codon usage of SARS-CoV-2 has adapted to human lungs to allow fast decoding and translation. This adaptation probably took place after SARS-CoV-2 split from RaTG13 because RaTG13 is less perfectly correlated with human. This finding depicts the trajectory of adaptive evolution from ancestral sequence to SARS-CoV-2, and also well explains why SARS-CoV-2 rather than other viruses could perfectly adapt to human lung environment.