Reconciling the debate on deamination on viral RNA

Unveiling RNA Editing by ADAR and APOBEC Protein Gene Families

RNA editing is a crucial post-transcriptional modification that alters the transcriptome and proteome and affects many cellular processes, including splicing, microRNA specificity, stability of RNA molecules, and protein structure. Enzymes from the adenosine deaminase acting on RNA (ADAR) and apolipoprotein B mRNA editing catalytic polypeptide-like (APOBEC) protein families mediate RNA editing and can alter a variety of non-coding and coding RNAs, including all regions of mRNA molecules, leading to tumor development and progression. This review provides novel insights into the potential use of RNA editing parameters, such as editing levels, expression of ADAR and APOBEC genes, and specifically edited genes, as biomarkers for cancer progression, distinguishing it from previous studies that focused on isolated aspects of RNA editing mechanisms. The methodological section offers clues to accelerate high-throughput analysis of RNA or DNA sequencing data for the identification of RNA editing events.

Analysis of the abundance and diversity of RNA secondary structure elements in RNA viruses using the RNAsselem Python package

Recent advancements in experimental and computational methods for RNA secondary structure detection have revealed the crucial role of RNA structural elements in diverse molecular processes within living cells. It has been demonstrated that the secondary structure of the entire viral genome is often responsible for performing crucial functions in the viral life cycle and also influences virus evolution. To investigate the role of viral RNA secondary structure, alongside experimental techniques, the use of bioinformatics tools is important for analyzing various secondary structure patterns, including hairpin loops, internal loops, multifurcations, external loops, bulges, stems, and pseudoknots. Here, we have introduced a Python package for analyzing RNA secondary structure elements in viral genomes, which includes the recognition of common secondary structure patterns, the generation of descriptive statistics for these structural elements, and the provision of their basic properties. We applied the developed package to analyze the secondary structures of complete viral genomes collected from the literature, aiming to gain insights into viral function and evolution. Both the package and the collection of secondary structures of viral genomes are available at http://github.com/KazanovLab/RNAsselem .

Convergent evolution of allele-specific gene expression that leads to non-small cell lung cancer in different human populations

Phenotypical innovations during evolution are caused by novel mutations, which are usually heterozygous at the beginning. The gene expressions on two alleles of these mutation sites are not necessarily identical, leading to flexible allele-specific regulation in cell systems. We retrieve the transcriptome data of normal and non-small cell lung cancer (NSCLC) tissues from 47 African Americans (AA) and 50 European Americans (EA). We analyze the differentially expressed genes (DEGs) in NSCLC as well as the tumor-specific mutations. Expression and mutation profiles show convergent evolution in AA and EA populations. The tumor-specific mutations are poorly overlapped, but many of them are located in the same genes, mainly oncogenes and tumor suppressor genes. The DEGs in tumors are majorly caused by the mutated alleles rather than normal alleles. The relative expressions of mutated alleles are highly correlated between AA and EA. The differential expression in NSCLC is predominantly mediated by the mutated alleles on heterozygous sites. This molecular mechanism underlying NSCLC oncogenesis is conserved across different human populations, exhibiting convergent evolution. We present this novel angle that differential expression analysis should be performed separately for different alleles. Our ideas should greatly benefit the cancer community.

In silico and experimental approaches for validating RNA editing events in transcriptomes

As a typical RNA virus, SARS-CoV-2 is subjected to RNA editing in host cells. While some researchers believe that a traditional variant calling pipeline retrieves all true-positive RNA editing events from the transcriptome, others argue that conventional methods identify many false-positive sites. Here, I describe several additional in silico and experimental approaches to validate the authenticity of RNA editing in SARS-CoV-2. These approaches include requiring strand-specific sequencing, analysis of hyperedited reads, linkage analysis, orthogonal methods like mass spectrometry, and the use of ADAR-deficient host cells. These findings may improve future analyses on the identification of RNA editing, especially in RNA viruses.

An orthology-based methodology as a complementary approach to retrieve evolutionarily conserved A-to-I RNA editing sites

Adar-mediated adenosine-to-inosine (A-to-I) mRNA editing is a conserved mechanism that exerts diverse regulatory functions during the development, evolution, and adaptation of metazoans. The accurate detection of RNA editing sites helps us understand their biological significance. In this work, with an improved genome assembly of honeybee (Apis mellifera), we used a new orthology-based methodology to complement the traditional pipeline of (de novo) RNA editing detection. Compared to the outcome of traditional pipeline, we retrieved many novel editing sites in CDS that are deeply conserved between honeybee and other distantly related insects. The newly retrieved sites were missed by the traditional de novo identification due to the stringent criteria for controlling false-positive rate. Caste-specific editing sites are identified, including an Ile>Met auto-recoding site in Adar. This recoding was even conserved between honeybee and bumblebee, suggesting its putative regulatory role in shaping the phenotypic plasticity of eusocial Hymenoptera. In summary, we proposed a complementary approach to the traditional pipeline and retrieved several previously unnoticed CDS editing sites. From both technical and biological aspects, our works facilitate future researches on finding the functional editing sites and advance our understanding on the connection between RNA editing and the great phenotypic diversity of organisms.

Retrospect of the Two-Year Debate: What Fuels the Evolution of SARS-CoV-2: RNA Editing or Replication Error?

Mutation is one of the mechanisms of the evolutionary divergence of an organism. Under this global COVID-19 pandemic, the fast evolution of SARS-CoV-2 became one of the most worrying issues. Some researchers believed that the hosts' RNA deamination systems (APOBECs and ADARs) are the major source of mutations and have driven the evolution of SARS-CoV-2. However, apart from RNA editing, the RDRP (RNA-dependent RNA polymerase)-mediated replication errors may also contribute to the mutation of SARS-CoV-2 (just like the single-nucleotide polymorphisms/variations in eukaryotes caused by DNA replication errors). Unfortunately, it is technically unable to distinguish RNA editing and replication errors (SNPs) in this RNA virus. Here comes a fundamental question: we indeed observed the fast evolution of SARS-CoV-2, but what exactly fuels its evolution: RNA editing or replication errors? This debate lasts for 2 years. In this piece, we will retrospect the 2-year debate on RNA editing versus SNPs.

Evidence Supporting That C-to-U RNA Editing Is the Major Force That Drives SARS-CoV-2 Evolution

Mutations of DNA organisms are introduced by replication errors. However, SARS-CoV-2, as an RNA virus, is additionally subjected to rampant RNA editing by hosts. Both resources contributed to SARS-CoV-2 mutation and evolution, but the relative prevalence of the two origins is unknown. We performed comparative genomic analyses at intra-species (world-wide SARS-CoV-2 strains) and inter-species (SARS-CoV-2 and RaTG13 divergence) levels. We made prior predictions of the proportion of each mutation type (nucleotide substitution) under different scenarios and compared the observed versus the expected. C-to-T alteration, representing C-to-U editing, is far more abundant that all other mutation types. Derived allele frequency (DAF) as well as novel mutation rate of C-to-T are the highest in SARS-CoV-2 population, and C-T substitution dominates the divergence sites between SARS-CoV-2 and RaTG13. This is compelling evidence suggesting that C-to-U RNA editing is the major source of SARS-CoV-2 mutation. While replication errors serve as a baseline of novel mutation rate, the C-to-U editing has elevated the mutation rate for orders of magnitudes and accelerates the evolution of the virus.

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.

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.

The Sponge Interaction Between Circular RNA and microRNA Serves as a Fast-Evolving Mechanism That Suppresses Non-small Cell Lung Cancer (NSCLC) in Humans

Non-small cell lung cancer (NSCLC) is one of the most lethal cancer types in the world. Currently, the molecular mechanisms and pathways underlying NSCLC oncogenesis are poorly understood. Using multiple Omics data, we systematically explored the differentially expressed circular RNAs (circRNAs) in NSCLC. We also investigated potential microRNA sponges (that absorb circRNAs) in NSCLC and downstream target genes with experimental verifications. hsa_circ_0003497 was down-regulated in NSCLC and played an inhibitory role in tumorigenesis. In contrast, miR-197-3p was up-regulated in NSCLC. hsa_circ_0003497 directly interacts with miR-197-3p and releases a target gene of miR-197-3p termed CTNND1 (a known tumor suppressor gene). Evolutionary analysis reveals fast evolution of this hsa_circ_0003497-miR-197-3p-CTNND1-NSCLC axis in mammals. This work clarified the biological functions and molecular mechanisms of how hsa_circ_0003497 suppresses NSCLC through miR-197-3p and CTNND1. We discovered molecular markers for the prognosis of NSCLC and provided potential intervention targets for its treatment.

uORF-Mediated Translational Regulation of ATF4 Serves as an Evolutionarily Conserved Mechanism Contributing to Non-Small-Cell Lung Cancer (NSCLC) and Stress Response

Diseases and environmental stresses are two distinct challenges for virtually all living organisms. In light of evolution, cellular responses to diseases and stresses might share similar molecular mechanisms, but the detailed regulation pathway is not reported yet.

We obtained the transcriptomes and translatomes from several NSCLC (non-small-cell lung cancer) patients as well as from different species under normal or stress conditions. We found that the translation level of gene ATF4 is remarkably enhanced in NSCLC due to the reduced number of ribosomes binding to its upstream open reading frames (uORFs). We also showed the evolutionary conservation of this uORF-ATF4 regulation in the stress response of other species. Molecular experiments showed that knockdown of ATF4 reduced the cell growth rate while overexpression of ATF4 enhanced cell growth, especially for the ATF4 allele with mutated uORFs. Population genetics analyses in multiple species verified that the mutations that abolish uATGs (start codon of uORFs) are highly deleterious, suggesting the functional importance of uORFs.

Our study proposes an evolutionarily conserved pattern that enhances the ATF4 translation by uORFs upon stress or disease. We generalized the concept of cellular response to diseases and stresses. These two biological processes may share similar molecular mechanisms.

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.