Global importance of RNA secondary structures in protein-coding sequences

Genetic polymorphism in untranslated regions of PRKCZ influences mRNA structure, stability and binding sites

BACKGROUND

Variations in untranslated regions (UTR) alter regulatory pathways impacting phenotype, disease onset, and course of disease. Protein kinase C Zeta (PRKCZ), a serine-threonine kinase, is implicated in cardiovascular, neurological and oncological disorders. Due to limited research on PRKCZ, this study aimed to investigate the impact of UTR genetic variants' on binding sites for transcription factors and miRNA. RNA secondary structure, eQTLs, and variation tolerance analysis were also part of the study.

METHODS

The data related to PRKCZ gene variants was downloaded from the Ensembl genome browser, COSMIC and gnomAD. The RegulomeDB database was used to assess the functional impact of 5' UTR and 3'UTR variants. The analysis of the transcription binding sites (TFBS) was done through the Alibaba tool, and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) was employed to identify pathways associated with PRKCZ. To predict the effect of variants on microRNA binding sites, PolymiRTS was utilized for 3' UTR variants, and the SNPinfo tool was used for 5' UTR variants.

RESULTS

The results obtained indicated that a total of 24 variants present in the 3' UTR and 25 variants present in the 5' UTR were most detrimental. TFBS analysis revealed that 5' UTR variants added YY1, repressor, and Oct1, whereas 3' UTR variants added AP-2alpha, AhR, Da, GR, and USF binding sites. The study predicted TFs that influenced PRKCZ expression. RNA secondary structure analysis showed that eight 5' UTR and six 3' UTR altered the RNA structure by either removal or addition of the stem-loop. The microRNA binding site analysis highlighted that seven 3' UTR and one 5' UTR variant altered the conserved site and also created new binding sites. eQTLs analysis showed that one variant was associated with PRKCZ expression in the lung and thyroid. The variation tolerance analysis revealed that PRKCZ was an intolerant gene.

CONCLUSION

This study laid the groundwork for future studies aimed at targeting PRKCZ as a therapeutic target.

Comprehensive survey of conserved RNA secondary structures in full-genome alignment of Hepatitis C virus

Hepatitis C virus (HCV) is a plus-stranded RNA virus that often chronically infects liver hepatocytes and causes liver cirrhosis and cancer. These viruses replicate their genomes employing error-prone replicases. Thereby, they routinely generate a large 'cloud' of RNA genomes (quasispecies) which-by trial and error-comprehensively explore the sequence space available for functional RNA genomes that maintain the ability for efficient replication and immune escape. In this context, it is important to identify which RNA secondary structures in the sequence space of the HCV genome are conserved, likely due to functional requirements. Here, we provide the first genome-wide multiple sequence alignment (MSA) with the prediction of RNA secondary structures throughout all representative full-length HCV genomes. We selected 57 representative genomes by clustering all complete HCV genomes from the BV-BRC database based on k-mer distributions and dimension reduction and adding RefSeq sequences. We include annotations of previously recognized features for easy comparison to other studies. Our results indicate that mainly the core coding region, the C-terminal NS5A region, and the NS5B region contain secondary structure elements that are conserved beyond coding sequence requirements, indicating functionality on the RNA level. In contrast, the genome regions in between contain less highly conserved structures. The results provide a complete description of all conserved RNA secondary structures and make clear that functionally important RNA secondary structures are present in certain HCV genome regions but are largely absent from other regions. Full-genome alignments of all branches of Hepacivirus C are provided in the supplement.

Bioinformatic analysis of the effect of SNPs in the pig TERT gene on the structural and functional characteristics of the enzyme to develop new genetic markers of productivity traits

BACKGROUND

Telomerase reverse transcriptase (TERT) plays a crucial role in synthesizing telomeric repeats that safeguard chromosomes from damage and fusion, thereby maintaining genome stability. Mutations in the TERT gene can lead to a deviation in gene expression, impaired enzyme activity, and, as a result, abnormal telomere shortening. Genetic markers of productivity traits in livestock can be developed based on the TERT gene polymorphism for use in marker-associated selection (MAS). In this study, a bioinformatic-based approach is proposed to evaluate the effect of missense single-nucleotide polymorphisms (SNPs) in the pig TERT gene on enzyme function and structure, with the prospect of developing genetic markers.

RESULTS

A comparative analysis of the coding and amino acid sequences of the pig TERT was performed with corresponding sequences of other species. The distribution of polymorphisms in the pig TERT gene, with respect to the enzyme's structural-functional domains, was established. A three-dimensional model of the pig TERT structure was obtained through homological modeling. The potential impact of each of the 23 missense SNPs in the pig TERT gene on telomerase function and stability was assessed using predictive bioinformatic tools utilizing data on the amino acid sequence and structure of pig TERT.

CONCLUSIONS

According to bioinformatic analysis of 23 missense SNPs of the pig TERT gene, a predictive effect of rs789641834 (TEN domain), rs706045634 (TEN domain), rs325294961 (TRBD domain) and rs705602819 (RTD domain) on the structural and functional parameters of the enzyme was established. These SNPs hold the potential to serve as genetic markers of productivity traits. Therefore, the possibility of their application in MAS should be further evaluated in associative analysis studies.

Machine learning modeling of RNA structures: methods, challenges and future perspectives

The three-dimensional structure of RNA molecules plays a critical role in a wide range of cellular processes encompassing functions from riboswitches to epigenetic regulation. These RNA structures are incredibly dynamic and can indeed be described aptly as an ensemble of structures that shifts in distribution depending on different cellular conditions. Thus, the computational prediction of RNA structure poses a unique challenge, even as computational protein folding has seen great advances. In this review, we focus on a variety of machine learning-based methods that have been developed to predict RNA molecules' secondary structure, as well as more complex tertiary structures. We survey commonly used modeling strategies, and how many are inspired by or incorporate thermodynamic principles. We discuss the shortcomings that various design decisions entail and propose future directions that could build off these methods to yield more robust, accurate RNA structure predictions.

Sulfonylation of RNA 2'-OH groups

The nucleophilic reactivity of RNA 2'-OH groups in water has proven broadly useful in probing, labeling, and conjugating RNA. To date, reactions selective to ribose 2'-OH have been limited to bond formation with short-lived carbonyl electrophiles. Here we report that many activated small-molecule sulfonyl species can exhibit extended lifetimes in water and retain 2'-OH reactivity. The data establish favorable aqueous solubility for selected reagents and successful RNA-selective reactions at stoichiometric and superstoichiometric yields, particularly for aryl sulfonyltriazole species. We report that the latter are considerably more stable than most prior carbon electrophiles in aqueous environments and tolerate silica chromatography. Furthermore, an azide-substituted sulfonyltriazole reagent is developed to introduce labels into RNA via click chemistry. In addition to high-yield reactions, we find that RNA sulfonylation can also be performed under conditions that give trace yields necessary for structure mapping. Like acylation, the reaction occurs with selectivity for unpaired nucleotides over those in the duplex structure, and a sulfonate adduct causes reverse transcriptase stops, suggesting potential use in RNA structure analysis. Probing of rRNA is demonstrated in human cells, indicating possible cell permeability. The sulfonyl reagent class enables a new level of control, selectivity, versatility, and ease of preparation for RNA applications.

Reorganization of the Landscape of Translated mRNAs in NSUN2-Deficient Cells and Specific Features of NSUN2 Target mRNAs

The RNA cytosine C5 methyltransferase NSUN2 has a variety of RNA substrates and plays an important role in mRNA metabolism. NSUN2 binds to specific sequences enriched in exosomal mRNAs, suggesting its possible involvement in the sorting of mRNAs into exosomes. We applied the photoactivatable.4-thiouridine-enhanced cross-linking and immunoprecipitation assay involving high-throughput RNA sequencing (RNA-seq) to HEK293T cells to determine NSUN2 mRNA targets. NSUN2 cross-linking sites were found in more than one hundred relatively abundant mRNAs with a high GC content and a pronounced secondary structure. Then, utilizing RNA-seq for the total and polysome-associated mRNA from HEK293T cells with and without the knockdown of NSUN2, we identified differentially expressed genes, as well as genes with altered translational efficiency (GATEs). It turned out that the up-regulated GATE mRNAs were much shorter on average than the down-regulated ones, and their GC content was higher; moreover, they contained motifs with C residues located in GC-rich environments. Our findings reveal the specific features of mRNAs that make them potential targets for NSUN2 and expand our understanding of the role of NSUN2 in controlling translation and, possibly, in mRNA sorting into exosomes implemented through the methylation of cytosine residues.

sRNARFTarget: a fast machine-learning-based approach for transcriptome-wide sRNA target prediction

Bacterial small regulatory RNAs (sRNAs) are key regulators of gene expression in many processes related to adaptive responses. A multitude of sRNAs have been identified in many bacterial species; however, their function has yet to be elucidated. A key step to understand sRNAs function is to identify the mRNAs these sRNAs bind to. There are several computational methods for sRNA target prediction, and the most accurate one is CopraRNA which is based on comparative-genomics. However, species-specific sRNAs are quite common and CopraRNA cannot be used for these sRNAs. The most commonly used transcriptome-wide sRNA target prediction method and second-most-accurate method is IntaRNA. However, IntaRNA can take hours to run on a bacterial transcriptome. Here we present sRNARFTarget, a machine-learning-based method for transcriptome-wide sRNA target prediction applicable to any sRNA. We comparatively assessed the performance of sRNARFTarget, CopraRNA and IntaRNA in three bacterial species. Our results show that sRNARFTarget outperforms IntaRNA in terms of accuracy, ranking of true interacting pairs, and running time. However, CopraRNA substantially outperforms the other two programsin terms of accuracy. Thus, we suggest using CopraRNA when homolog sequences of the sRNA are available, and sRNARFTarget for transcriptome-wide prediction or for species-specific sRNAs. sRNARFTarget is available at https://github.com/BioinformaticsLabAtMUN/sRNARFTarget.

HCV Genetic Diversity Can Be Used to Infer Infection Recency and Time since Infection

HIV-1 genetic diversity can be used to infer time since infection (TSI) and infection recency. We adapted this approach for HCV and identified genomic regions with informative diversity. We included 72 HCV/HIV-1 coinfected participants of the Swiss HIV Cohort Study, for whom reliable estimates of infection date and viral sequences were available. Average pairwise diversity (APD) was calculated over each codon position for the entire open reading frame of HCV. Utilizing cross validation, we evaluated the correlation of APD with TSI, and its ability to infer TSI via a linear model. We additionally studied the ability of diversity to classify infections as recent (infected for <1 year) or chronic, using receiver-operator-characteristic area under the curve (ROC-AUC) in 50 patients whose infection could be unambiguously classified as either recent or chronic. Measuring HCV diversity over third or all codon positions gave similar performances, and notable improvement over first or second codon positions. APD calculated over the entire genome enabled classification of infection recency (ROC-AUC = 0.76). Additionally, APD correlated with TSI (R² = 0.33) and could predict TSI (mean absolute error = 1.67 years). Restricting the region over which APD was calculated to E2-NS2 further improved accuracy (ROC-AUC = 0.85, R² = 0.54, mean absolute error = 1.38 years). Genetic diversity in HCV correlates with TSI and is a proxy for infection recency and TSI, even several years post-infection.

Ribosome Pausing at Inefficient Codons at the End of the Replicase Coding Region Is Important for Hepatitis C Virus Genome Replication

Hepatitis C virus (HCV) infects liver cells and often causes chronic infection, also leading to liver cirrhosis and cancer. In the cytoplasm, the viral structural and non-structural (NS) proteins are directly translated from the plus strand HCV RNA genome. The viral proteins NS3 to NS5B proteins constitute the replication complex that is required for RNA genome replication via a minus strand antigenome. The most C-terminal protein in the genome is the NS5B replicase, which needs to initiate antigenome RNA synthesis at the very 3′-end of the plus strand. Using ribosome profiling of cells replicating full-length infectious HCV genomes, we uncovered that ribosomes accumulate at the HCV stop codon and about 30 nucleotides upstream of it. This pausing is due to the presence of conserved rare, inefficient Wobble codons upstream of the termination site. Synonymous substitution of these inefficient codons to efficient codons has negative consequences for viral RNA replication but not for viral protein synthesis. This pausing may allow the enzymatically active replicase core to find its genuine RNA template in cis, while the protein is still held in place by being stuck with its C-terminus in the exit tunnel of the paused ribosome.

Widespread non-modular overlapping codes in the coding regions

Messenger RNAs (mRNAs) consist of a coding region (open reading frame (ORF)) and two untranslated regions (UTRs), 5'UTR and 3'UTR. Ribosomes travel along the coding region, translating nucleotide triplets (called codons) to a chain of amino acids. The coding region was long believed to mainly encode the amino acid content of proteins, whereas regulatory signals reside in the UTRs and in other genomic regions. However, in recent years we have learned that the ORF is expansively populated with various regulatory signals, or codes, which are related to all gene expression steps and additional intracellular aspects. In this paper, we review the current knowledge related to overlapping codes inside the coding regions, such as the influence of synonymous codon usage on translation speed (and, in turn, the effect of translation speed on protein folding), ribosomal frameshifting, mRNA stability, methylation, splicing, transcription and more. All these codes come together and overlap in the ORF sequence, ensuring production of the right protein at the right time.

Hepatitis C Virus Translation Regulation

Translation of the hepatitis C virus (HCV) RNA genome is regulated by the internal ribosome entry site (IRES), located in the 5’-untranslated region (5′UTR) and part of the core protein coding sequence, and by the 3′UTR. The 5′UTR has some highly conserved structural regions, while others can assume different conformations. The IRES can bind to the ribosomal 40S subunit with high affinity without any other factors. Nevertheless, IRES activity is modulated by additional cis sequences in the viral genome, including the 3′UTR and the cis-acting replication element (CRE). Canonical translation initiation factors (eIFs) are involved in HCV translation initiation, including eIF3, eIF2, eIF1A, eIF5, and eIF5B. Alternatively, under stress conditions and limited eIF2-Met-tRNA_i^Met availability, alternative initiation factors such as eIF2D, eIF2A, and eIF5B can substitute for eIF2 to allow HCV translation even when cellular mRNA translation is downregulated. In addition, several IRES trans-acting factors (ITAFs) modulate IRES activity by building large networks of RNA-protein and protein–protein interactions, also connecting 5′- and 3′-ends of the viral RNA. Moreover, some ITAFs can act as RNA chaperones that help to position the viral AUG start codon in the ribosomal 40S subunit entry channel. Finally, the liver-specific microRNA-122 (miR-122) stimulates HCV IRES-dependent translation, most likely by stabilizing a certain structure of the IRES that is required for initiation.

Hepatitis C Virus Downregulates Core Subunits of Oxidative Phosphorylation, Reminiscent of the Warburg Effect in Cancer Cells

Hepatitis C Virus (HCV) mainly infects liver hepatocytes and replicates its single-stranded plus strand RNA genome exclusively in the cytoplasm. Viral proteins and RNA interfere with the host cell immune response, allowing the virus to continue replication. Therefore, in about 70% of cases, the viral infection cannot be cleared by the immune system, but a chronic infection is established, often resulting in liver fibrosis, cirrhosis and hepatocellular carcinoma (HCC). Induction of cancer in the host cells can be regarded to provide further advantages for ongoing virus replication. One adaptation in cancer cells is the enhancement of cellular carbohydrate flux in glycolysis with a reduction of the activity of the citric acid cycle and aerobic oxidative phosphorylation. To this end, HCV downregulates the expression of mitochondrial oxidative phosphorylation complex core subunits quite early after infection. This so-called aerobic glycolysis is known as the “Warburg Effect” and serves to provide more anabolic metabolites upstream of the citric acid cycle, such as amino acids, pentoses and NADPH for cancer cell growth. In addition, HCV deregulates signaling pathways like those of TNF-β and MAPK by direct and indirect mechanisms, which can lead to fibrosis and HCC.

Widespread selection for extremely high and low levels of secondary structure in coding sequences across all domains of life

Codon composition, GC content and local RNA secondary structures can have a profound effect on gene expression, and mutations affecting these parameters, even though they do not alter the protein sequence, are not neutral in terms of selection. Although evidence exists that, in some cases, selection favours more stable RNA secondary structures, we currently lack a concrete idea of how many genes are affected within a species, and whether this is a universal phenomenon in nature. We searched for signs of structural selection in a global manner, analysing a set of 1 million coding sequences from 73 species representing all domains of life, as well as viruses, by means of our newly developed software PACKEIS. We show that codon composition and amino acid identity are main determinants of RNA secondary structure. In addition, we show that the arrangement of synonymous codons within coding sequences is non-random, yielding extremely high, but also extremely low, RNA structuredness significantly more often than expected by chance. Taken together, we demonstrate that selection for high and low levels of secondary structure is a widespread phenomenon. Our results provide another line of evidence that synonymous mutations are less neutral than commonly thought, which is of importance for many evolutionary models.

Conserved Secondary Structures in Viral mRNAs

RNA secondary structure in untranslated and protein coding regions has been shown to play an important role in regulatory processes and the viral replication cycle. While structures in non-coding regions have been investigated extensively, a thorough overview of the structural repertoire of protein coding mRNAs, especially for viruses, is lacking. Secondary structure prediction of large molecules, such as long mRNAs remains a challenging task, as the contingent of structures a sequence can theoretically fold into grows exponentially with sequence length. We applied a structure prediction pipeline to Viral Orthologous Groups that first identifies the local boundaries of potentially structured regions and subsequently predicts their functional importance. Using this procedure, the orthologous groups were split into structurally homogenous subgroups, which we call subVOGs. This is the first compilation of potentially functional conserved RNA structures in viral coding regions, covering the complete RefSeq viral database. We were able to recover structural elements from previous studies and discovered a variety of novel structured regions. The subVOGs are available through our web resource RNASIV (RNA structure in viruses; http://rnasiv.bio.wzw.tum.de).

Cellular Gene Expression during Hepatitis C Virus Replication as Revealed by Ribosome Profiling

Background: Hepatitis C virus (HCV) infects human liver hepatocytes, often leading to liver cirrhosis and hepatocellular carcinoma (HCC). It is believed that chronic infection alters host gene expression and favors HCC development. In particular, HCV replication in Endoplasmic Reticulum (ER) derived membranes induces chronic ER stress. How HCV replication affects host mRNA translation and transcription at a genome wide level is not yet known. Methods: We used Riboseq (Ribosome Profiling) to analyze transcriptome and translatome changes in the Huh-7.5 hepatocarcinoma cell line replicating HCV for 6 days. Results: Established viral replication does not cause global changes in host gene expression—only around 30 genes are significantly differentially expressed. Upregulated genes are related to ER stress and HCV replication, and several regulated genes are known to be involved in HCC development. Some mRNAs (PPP1R15A/GADD34, DDIT3/CHOP, and TRIB3) may be subject to upstream open reading frame (uORF) mediated translation control. Transcriptional downregulation mainly affects mitochondrial respiratory chain complex core subunit genes. Conclusion: After establishing HCV replication, the lack of global changes in cellular gene expression indicates an adaptation to chronic infection, while the downregulation of mitochondrial respiratory chain genes indicates how a virus may further contribute to cancer cell-like metabolic reprogramming (“Warburg effect”) even in the hepatocellular carcinoma cells used here.