Nothing in SARS-CoV-2 makes sense except in the light of RNA modification?

The expression pattern of RNA deaminases determines the mutation and evolution of SARS-CoV-2.

C-to-U RNA deamination is the driving force accelerating SARS-CoV-2 evolution.

Understanding the molecular mechanism underlying the rampant mutation of SARS-CoV-2 would help us control the COVID-19 pandemic. The APOBEC-mediated C-to-U deamination is a major mutation type in the SARS-CoV-2 genome. However, it is unclear whether the novel mutation rate u is higher for C-to-U than for other mutation types, and what the detailed driving force is. By analyzing the time course SARS-CoV-2 global population data, we found that C-to-U has the highest novel mutation rate u among all mutation types and that this u is still increasing with time (du/dt > 0). Novel C-to-U events, rather than other mutation types, have a preference over particular genomic regions. A less local RNA structure is correlated with a high novel C-to-U mutation rate. A cascade model nicely explains the du/dt > 0 for C-to-U deamination. In SARS-CoV-2, the RNA structure serves as the molecular basis of the extremely high and continuously accelerating C-to-U deamination rate. This mechanism is the driving force of the mutation, adaptation, and evolution of SARS-CoV-2. Our findings help us understand the dynamic evolution of the virus mutation rate.

Nothing in SARS-CoV-2 makes sense except in the light of RNA modification?

Tweetable The expression pattern of RNA deaminases determines the mutation and evolution of SARS-CoV-2.

Rampant C-to-U deamination accounts for the intrinsically high mutation rate in SARS-CoV-2 spike gene.

The high mutation rate of SARS-CoV-2 largely complicates our control of the pandemic. In particular, it is currently unclear why the spike (S) gene has an extraordinarily high mutation rate among all SARS-CoV-2 genes. By analyzing the occurrence of fixed synonymous mutations between SARS-CoV-2 and RaTG13, and profiling the DAF (derived allele frequency) of polymorphic synonymous sites among millions of worldwide SARS-CoV-2 strains, we found that both fixed and polymorphic mutations show higher mutation rates in the S gene than other genes. The majority of mutations are C-to-T, representing the APOBEC-mediated C-to-U deamination instead of the previously proposed A-to-I deamination. Both in silico and in vivo evidence indicated that the S gene is more likely to be single-stranded compared to other SARS-CoV-2 genes, agreeing with the APOBEC preference of ssRNA. We conclude that the single-stranded property of the S gene makes it a favorable target for C-to-U deamination, leading to its excessively high mutation rate compared to other non-S genes. In conclusion, APOBEC, rather than ADAR, is the "editor-in-chief" of SARS-CoV-2 RNAs. This work helps us to understand the molecular mechanism underlying the mutation and evolution of SARS-CoV-2, and we believe it will contribute to the control of the pandemic.

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.

Fast evolution of SARS-CoV-2 driven by deamination systems in hosts.

As an RNA virus, the fast evolution of SARS-CoV-2 is driven by the extensive RNA deamination by the host cells.

SNPs or RNA modifications? Concerns on mutation-based evolutionary studies of SARS-CoV-2.

SARS-CoV-2 is still rampaging throughout the world while the many evolutionary studies on it are simultaneously springing up. Researchers have simply utilized the public RNA-seq data to find out the so-called SNPs in the virus genome. The evolutionary analyses were largely based on these mutations. Here, we claim that we reliably detected A-to-G RNA modifications in the RNA-seq data of SARS-CoV-2 with high signal to noise ratios, presumably caused by the host's deamination enzymes. Intriguingly, since SARS-CoV-2 is an RNA virus, it is technically impossible to distinguish SNPs and RNA modifications from the RNA-seq data alone without solid evidence, making it difficult to tell the evolutionary patterns behind the mutation spectrum. Researchers should clarify their biological significance before they automatically regard the mutations as SNPs or RNA modifications. This is not a problem for DNA organisms but should be seriously considered when we are investigating the RNA viruses.

The divergence between SARS-CoV-2 and RaTG13 might be overestimated due to the extensive RNA modification

Aim: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread throughout the world. There is urgent need to understand the phylogeny, divergence and origin of SARS-CoV-2. Materials & methods: A recent study claimed that there was 17% divergence between SARS-CoV-2 and RaTG13 (a SARS-related coronaviruses) on synonymous sites by using sequence alignment. We re-analyzed the sequences of the two coronaviruses with the same methodology. Results: We found that 87% of the synonymous substitutions between the two coronaviruses could be potentially explained by the RNA modification system in hosts, with 65% contributed by deamination on cytidines (C-T mismatches) and 22% contributed by deamination on adenosines (A-G mismatches). Conclusion: Our results demonstrate that the divergence between SARS-CoV-2 and RaTG13 has been overestimated.

Mutation profile of over 4500 SARS-CoV-2 isolations reveals prevalent cytosine-to-uridine deamination on viral RNAs.

Aim: The inference of coronavirus evolution is largely based on mutations in SARS-CoV-2 genome. Misinterpretation of these mutations would mislead people about the evolution of SARS-CoV-2. Materials & methods: With 4521 lines of SARS-CoV-2, we obtained 3169 unique point mutation sites. We counted the numbers and calculated the minor allele frequency (MAF) of each mutation type. Results: Nearly half of the point mutations are C-T mismatches and 20% are A-G mismatches. The MAF of C-T and A-G mismatches is significantly higher than MAF of other mutation types. Conclusion: The excessive C-T mismatches do not resemble the random mutation profile. They are likely to be caused by the cytosine-to-uridine deamination system in hosts.

GC usage of SARS-CoV-2 genes might adapt to the environment of human lung expressed genes.

Understanding how SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) efficiently reproduces itself by taking resources from the human host could facilitate the development of drugs against the virus. SARS-CoV-2 translates its own proteins by using the host tRNAs, so that its GC or codon usage should fit that of the host cells. It is necessary to study both the virus and human genomes in the light of evolution and adaptation. The SARS-CoV-2 virus has significantly lower GC content and GC3 as compared to human. However, when we selected a set of human genes that have similar GC properties to SARS-CoV-2, we found that these genes were enriched in particular pathways. Moreover, these human genes have the codon composition perfectly correlated with the SARS-CoV-2, and were extraordinarily highly expressed in human lung tissues, demonstrating that the SARS-CoV-2 genes have similar GC usage as compared to the lung expressed human genes. RSCU (relative synonymous codon usage) and CAI (codon adaptation index) profiles further support the matching between SARS-CoV-2 and lungs. Our study indicates that SARS-CoV-2 might have adapted to the human lung environment by observing the high correlation between GC usage of SARS-CoV-2 and human lung genes, which suggests the GC content of SARS-CoV-2 is optimized to take advantage of human lung tissues.