Local RNA Secondary Structure Research Articles

Evaluation of the effect of RNA secondary structure on Cas13d-mediated target RNA cleavage

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas13d system was adapted as a powerful tool for targeting viral RNA sequences, making it a promising approach for antiviral strategies. Understanding the influence of template RNA structure on Cas13d binding and cleavage efficiency is crucial for optimizing its therapeutic potential. In this study, we investigated the effect of local RNA secondary structure on Cas13d activity. To do so, we varied the stability of a hairpin structure containing the SARS-CoV-2 target sequence, allowing us to determine the threshold RNA stability at which Cas13d activity is affected. Our results demonstrate that Cas13d possesses the ability to effectively bind and cleave highly stable RNA structures. Notably, we only observed a decrease in Cas13d activity in the case of exceptionally stable RNA hairpins with completely base-paired stems, which are rarely encountered in natural RNA molecules. Comparison of Cas13d and RNA interference (RNAi)-mediated cleavage of the same RNA targets demonstrated that RNAi is more sensitive for local target RNA structure than Cas13d. These results underscore the suitability of the CRISPR-Cas13d system for targeting viruses with highly structured RNA genomes.

RNA Secondary Structure Alteration Caused by Single Nucleotide Variants.

A point mutation in coding RNA can cause not only an amino acid substitution but also a dynamic change of RNA secondary structure, leading to a dysfunctional RNA. Although in silico structure prediction has been used to detect structure-disrupting point mutations known as riboSNitches, exhaustive simulation of long RNAs is needed to detect a significant enrichment or depletion of riboSNitches in functional RNAs. Here, we have developed a novel algorithm Radiam (RNA secondary structure Analysis with Deletion, Insertion, And substitution Mutations) for a comprehensive riboSNitch analysis of long RNAs. Radiam is based on the ParasoR framework, which efficiently computes local RNA secondary structures for long RNAs. ParasoR can compute a variety of structure scores over globally consistent structures with maximal span constraints for the base pair distance. Using the reusable structure database made by ParasoR, Radiam performs an efficient recomputation of the secondary structures for mutated sequences. An exhaustive simulation of Radiam is expected to find reliable riboSNitch candidates on long RNAs by evaluating their statistical significance in terms of the change of local structure stability.

In silico analysis of local RNA secondary structure in influenza virus A, B and C finds evidence of widespread ordered stability but little evidence of significant covariation

Influenza virus is a persistent threat to human health; indeed, the deadliest modern pandemic was in 1918 when an H1N1 virus killed an estimated 50 million people globally. The intent of this work is to better understand influenza from an RNA-centric perspective to provide local, structural motifs with likely significance to the influenza infectious cycle for therapeutic targeting. To accomplish this, we analyzed over four hundred thousand RNA sequences spanning three major clades: influenza A, B and C. We scanned influenza segments for local secondary structure, identified/modeled motifs of likely functionality, and coupled the results to an analysis of evolutionary conservation. We discovered 185 significant regions of predicted ordered stability, yet evidence of sequence covariation was limited to 7 motifs, where 3—found in influenza C—had higher than expected amounts of sequence covariation.

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.

Large-Scale Synonymous Substitutions in Cucumber Mosaic Virus RNA 3 Facilitate Amino Acid Mutations in the Coat Protein.

The effect of large-scale synonymous substitutions in a small icosahedral, single-stranded RNA viral genome on virulence, viral titer, and protein evolution were analyzed. The coat protein (CP) gene of the Fny stain of cucumber mosaic virus (CMV) was modified. We created four CP mutants in which all the codons of nine amino acids in the 5' or 3' half of the CP gene were replaced by either the most frequently or the least frequently used synonymous codons in monocot plants. When the dicot host (Nicotiana benthamiana) was inoculated with these four CP mutants, viral RNA titers in uninoculated symptomatic leaves decreased, while all mutants eventually showed mosaic symptoms similar to those for the wild type. The codon adaptation index of these four CP mutants against dicot genes was similar to those of the wild-type CP gene, indicating that the reduction of viral RNA titer was due to deleterious changes of the secondary structure of RNAs 3 and 4. When two 5' mutants were serially passaged in N. benthamiana, viral RNA titers were rapidly restored but competitive fitness remained decreased. Although no nucleic acid changes were observed in the passaged wild-type CMV, one to three amino acid changes were observed in the synonymously mutated CP of each passaged virus, which were involved in recovery of viral RNA titer of 5' mutants. Thus, we demonstrated that deleterious effects of the large-scale synonymous substitutions in the RNA viral genome facilitated the rapid amino acid mutation(s) in the CP to restore the viral RNA titer.IMPORTANCE Recently, it has been known that synonymous substitutions in RNA virus genes affect viral pathogenicity and competitive fitness by alteration of global or local RNA secondary structure of the viral genome. We confirmed that large-scale synonymous substitutions in the CP gene of CMV resulted in decreased viral RNA titer. Importantly, when viral evolution was stimulated by serial-passage inoculation, viral RNA titer was rapidly restored, concurrent with a few amino acid changes in the CP. This novel finding indicates that the deleterious effects of large-scale nucleic acid mutations on viral RNA secondary structure are readily tolerated by structural changes in the CP, demonstrating a novel part of the adaptive evolution of an RNA viral genome. In addition, our experimental system for serial inoculation of large-scale synonymous mutants could uncover a role for new amino acid residues in the viral protein that have not been observed in the wild-type virus strains.

Genome wide analyses uncover allele-specific RNA editing in human and mouse.

RNA editing is one of the most common RNA level modifications that potentially generate amino acid changes similar to those resulting from genomic nonsynonymous mutations. However, unlike DNA level allele-specific modifications such as DNA methylation, it is currently unknown whether RNA editing displays allele-specificity across tissues and species. Here, we analyzed allele-specific RNA editing in human tissues and from brain tissues of heterozygous mice generated by crosses between divergent mouse strains and found a high proportion of overlap of allele-specific RNA editing sites between different samples. We identified three allele-specific RNA editing sites cause amino acid changes in coding regions of human and mouse genes, whereas their associated SNPs yielded synonymous differences. In vitro cellular experiments confirmed that sequences differing at a synonymous SNP can have differences in a linked allele-specific RNA editing site with nonsynonymous implications. Further, we demonstrate that allele-specific RNA editing is influenced by differences in local RNA secondary structure generated by SNPs. Our study provides new insights towards a better comprehension of the molecular mechanism that link SNPs with human diseases and traits.

In vivo probing of nascent RNA structures reveals principles of cotranscriptional folding.

Defining the in vivo folding pathway of cellular RNAs is essential to understand how they reach their final native conformation. We here introduce a novel method, named Structural Probing of Elongating Transcripts (SPET-seq), that permits single-base resolution analysis of transcription intermediates’ secondary structures on a transcriptome-wide scale, enabling base-resolution analysis of the RNA folding events. Our results suggest that cotranscriptional RNA folding in vivo is a mixture of cooperative folding events, in which local RNA secondary structure elements are formed as they get transcribed, and non-cooperative events, in which 5′-halves of long-range helices get sequestered into transient non-native interactions until their 3′ counterparts have been transcribed. Together our work provides the first transcriptome-scale overview of RNA cotranscriptional folding in a living organism.

The impact of RNA secondary structure on read start locations on the Illumina sequencing platform.

High-throughput sequencing is subject to sequence dependent bias, which must be accounted for if researchers are to make precise measurements and draw accurate conclusions from their data. A widely studied source of bias in sequencing is the GC content bias, in which levels of GC content in a genomic region effect the number of reads produced during sequencing. Although some research has been performed on methods to correct for GC bias, there has been little effort to understand the underlying mechanism. The availability of sequencing protocols that target the specific location of structure in nucleic acid molecules enables us to investigate the underlying molecular origin of observed GC bias in sequencing. By applying a parallel analysis of RNA structure (PARS) protocol to bacterial genomes of varying GC content, we are able to observe the relationship between local RNA secondary structure and sequencing outcome, and to establish RNA secondary structure as the significant contributing factor to observed GC bias.

Global analysis of regulatory divergence in the evolution of mouse alternative polyadenylation.

Alternative polyadenylation (APA), which is regulated by both cis‐elements and trans‐factors, plays an important role in post‐transcriptional regulation of eukaryotic gene expression. However, comparing to the extensively studied transcription and alternative splicing, the extent of APA divergence during evolution and the relative cis‐ and trans‐contribution remain largely unexplored. To directly address these questions for the first time in mammals, by using deep sequencing‐based methods, we measured APA divergence between C57BL/6J and SPRET/EiJ mouse strains as well as allele‐specific APA pattern in their F1 hybrids. Among the 24,721 polyadenylation sites (pAs) from 7,271 genes expressing multiple pAs, we identified 3,747 pAs showing significant divergence between the two strains. After integrating the allele‐specific data from F1 hybrids, we demonstrated that these events could be predominately attributed to cis‐regulatory effects. Further systematic sequence analysis of the regions in proximity to cis‐divergent pAs revealed that the local RNA secondary structure and a poly(U) tract in the upstream region could negatively modulate the pAs usage.

RNA Sequence Context Effects Measured In Vitro Predict In Vivo Protein Binding and Regulation

Many RNA binding proteins (RBPs) bind specific RNA sequence motifs, but only a small fraction (∼15%-40%) of RBP motif occurrences are occupied invivo. To determine which contextual features discriminate between bound and unbound motifs, we performed an invitro binding assay using 12,000 mouse RNA sequences with the RBPs MBNL1 and RBFOX2. Surprisingly, the strength of binding to motif occurrences invitro was significantly correlated with invivo binding, developmental regulation, and evolutionary age of alternative splicing. Multiple lines of evidence indicate that the primary context effect that affects binding invitro and invivo is RNA secondary structure. Large-scale combinatorial mutagenesis of unfavorable sequence contexts revealed a consistent pattern whereby mutations that increased motif accessibility improved protein binding and regulatory activity. Our results indicate widespread inhibition of motif binding by local RNA secondary structure and suggest that mutations that alter sequence context commonly affect RBP binding and regulation.

MicroRNA-122 target sites in the hepatitis C virus RNA NS5B coding region and 3' untranslated region: function in replication and influence of RNA secondary structure.

We have analyzed the binding of the liver-specific microRNA-122 (miR-122) to three conserved target sites of hepatitis C virus (HCV) RNA, two in the non-structural protein 5B (NS5B) coding region and one in the 3' untranslated region (3'UTR). miR-122 binding efficiency strongly depends on target site accessibility under conditions when the range of flanking sequences available for the formation of local RNA secondary structures changes. Our results indicate that the particular sequence feature that contributes most to the correlation between target site accessibility and binding strength varies between different target sites. This suggests that the dynamics of miRNA/Ago2 binding not only depends on the target site itself but also on flanking sequence context to a considerable extent, in particular in a small viral genome in which strong selection constraints act on coding sequence and overlapping cis-signals and model the accessibility of cis-signals. In full-length genomes, single and combination mutations in the miR-122 target sites reveal that site 5B.2 is positively involved in regulating overall genome replication efficiency, whereas mutation of site 5B.3 showed a weaker effect. Mutation of the 3'UTR site and double or triple mutants showed no significant overall effect on genome replication, whereas in a translation reporter RNA, the 3'UTR target site inhibits translation directed by the HCV 5'UTR. Thus, the miR-122 target sites in the 3'-region of the HCV genome are involved in a complex interplay in regulating different steps of the HCV replication cycle.

COME: a robust coding potential calculation tool for lncRNA identification and characterization based on multiple features.

Recent genomic studies suggest that novel long non-coding RNAs (lncRNAs) are specifically expressed and far outnumber annotated lncRNA sequences. To identify and characterize novel lncRNAs in RNA sequencing data from new samples, we have developed COME, a coding potential calculation tool based on multiple features. It integrates multiple sequence-derived and experiment-based features using a decompose–compose method, which makes it more accurate and robust than other well-known tools. We also showed that COME was able to substantially improve the consistency of predication results from other coding potential calculators. Moreover, COME annotates and characterizes each predicted lncRNA transcript with multiple lines of supporting evidence, which are not provided by other tools. Remarkably, we found that one subgroup of lncRNAs classified by such supporting features (i.e. conserved local RNA secondary structure) was highly enriched in a well-validated database (lncRNAdb). We further found that the conserved structural domains on lncRNAs had better chance than other RNA regions to interact with RNA binding proteins, based on the recent eCLIP-seq data in human, indicating their potential regulatory roles. Overall, we present COME as an accurate, robust and multiple-feature supported method for the identification and characterization of novel lncRNAs. The software implementation is available at https://github.com/lulab/COME.

Diverse regulation of 3' splice site usage.

The regulation of splice site (SS) usage is important for alternative pre-mRNA splicing and thus proper expression of protein isoforms in cells; its disruption causes diseases. In recent years, an increasing number of novel regulatory elements have been found within or nearby the 3'SS in mammalian genes. The diverse elements recruit a repertoire of trans-acting factors or form secondary structures to regulate 3'SS usage, mostly at the early steps of spliceosome assembly. Their mechanisms of action mainly include: (1) competition between the factors for RNA elements, (2) steric hindrance between the factors, (3) direct interaction between the factors, (4) competition between two splice sites, or (5) local RNA secondary structures or longer range loops, according to the mode of protein/RNA interactions. Beyond the 3'SS, chromatin remodeling/transcription, posttranslational modifications of trans-acting factors and upstream signaling provide further layers of regulation. Evolutionarily, some of the 3'SS elements seem to have emerged in mammalian ancestors. Moreover, other possibilities of regulation such as that by non-coding RNA remain to be explored. It is thus likely that there are more diverse elements/factors and mechanisms that influence the choice of an intron end. The diverse regulation likely contributes to a more complex but refined transcriptome and proteome in mammals.

Extensive allele-specific translational regulation in hybrid mice.

Translational regulation is mediated through the interaction between diffusible trans-factors and cis-elements residing within mRNA transcripts. In contrast to extensively studied transcriptional regulation, cis-regulation on translation remains underexplored. Using deep sequencing-based transcriptome and polysome profiling, we globally profiled allele-specific translational efficiency for the first time in an F1 hybrid mouse. Out of 7,156 genes with reliable quantification of both alleles, we found 1,008 (14.1%) exhibiting significant allelic divergence in translational efficiency. Systematic analysis of sequence features of the genes with biased allelic translation revealed that local RNA secondary structure surrounding the start codon and proximal out-of-frame upstream AUGs could affect translational efficiency. Finally, we observed that the cis-effect was quantitatively comparable between transcriptional and translational regulation. Such effects in the two regulatory processes were more frequently compensatory, suggesting that the regulation at the two levels could be coordinated in maintaining robustness of protein expression.

APeg3: regulation of Peg3 through an evolutionarily conserved ncRNA

Mammalian APeg3 is an antisense gene that is localized within the 3'-untranslated region of the imprinted gene, Peg3. APeg3 is expressed only in the vasopressinergic neurons of the hypothalamus, thus is predicted to play significant roles in this specific area of the brain. In the current study, we investigate the functions of APeg3 with comparative genomics and cell line-based functional approaches. The transcribed region of APeg3 displays high levels of sequence conservation among placental mammals, but without any obvious open reading frame, suggesting that APeg3 may have been selected as a ncRNA gene during eutherian evolution. This has been further supported by the detection of a conserved local RNA secondary structure within APeg3. RNA secondary structure analyses indicate a single conserved hairpin-loop structure towards the 5' end of the transcript. The results from cell line-based transfection experiments demonstrate that APeg3 has the potential to down-regulate the transcription and protein levels of Peg3. The observed down-regulation by APeg3 is also somewhat orientation-independent. Overall, these results suggest that APeg3 has evolved as a ncRNA gene and controls the function of its sense gene Peg3 within specific neuronal cells.

Transcriptome-Wide Analysis of UTRs in Non-Small Cell Lung Cancer Reveals Cancer-Related Genes with SNV-Induced Changes on RNA Secondary Structure and miRNA Target Sites

Traditional mutation assessment methods generally focus on predicting disruptive changes in protein-coding regions rather than non-coding regulatory regions like untranslated regions (UTRs) of mRNAs. The UTRs, however, are known to have many sequence and structural motifs that can regulate translational and transcriptional efficiency and stability of mRNAs through interaction with RNA-binding proteins and other non-coding RNAs like microRNAs (miRNAs). In a recent study, transcriptomes of tumor cells harboring mutant and wild-type KRAS (V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog) genes in patients with non-small cell lung cancer (NSCLC) have been sequenced to identify single nucleotide variations (SNVs). About 40% of the total SNVs (73,717) identified were mapped to UTRs, but omitted in the previous analysis. To meet this obvious demand for analysis of the UTRs, we designed a comprehensive pipeline to predict the effect of SNVs on two major regulatory elements, secondary structure and miRNA target sites. Out of 29,290 SNVs in 6462 genes, we predict 472 SNVs (in 408 genes) affecting local RNA secondary structure, 490 SNVs (in 447 genes) affecting miRNA target sites and 48 that do both. Together these disruptive SNVs were present in 803 different genes, out of which 188 (23.4%) were previously known to be cancer-associated. Notably, this ratio is significantly higher (one-sided Fisher's exact test p-value = 0.032) than the ratio (20.8%) of known cancer-associated genes (n = 1347) in our initial data set (n = 6462). Network analysis shows that the genes harboring disruptive SNVs were involved in molecular mechanisms of cancer, and the signaling pathways of LPS-stimulated MAPK, IL-6, iNOS, EIF2 and mTOR. In conclusion, we have found hundreds of SNVs which are highly disruptive with respect to changes in the secondary structure and miRNA target sites within UTRs. These changes hold the potential to alter the expression of known cancer genes or genes linked to cancer-associated pathways.

Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico

The internal ribosomal entry site (IRES) functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES element. We have designed a viral IRES prediction system (VIPS) to perform the IRES secondary structure prediction. In order to obtain better results for the IRES prediction, the VIPS can evaluate and predict for all four different groups of IRESs with a higher accuracy. RNA secondary structure prediction, comparison, and pseudoknot prediction programs were implemented to form the three-stage procedure for the VIPS. The backbone of VIPS includes: the RNAL fold program, aimed to predict local RNA secondary structures by minimum free energy method; the RNA Align program, intended to compare predicted structures; and pknotsRG program, used to calculate the pseudoknot structure. VIPS was evaluated by using UTR database, IRES database and Virus database, and the accuracy rate of VIPS was assessed as 98.53%, 90.80%, 82.36% and 80.41% for IRES groups 1, 2, 3, and 4, respectively. This advance useful search approach for IRES structures will facilitate IRES related studies. The VIPS on-line website service is available at http://140.135.61.250/vips/.

Prediction of clustered RNA-binding protein motif sites in the mammalian genome.

Sequence-specific interactions of RNA-binding proteins (RBPs) with their target transcripts are essential for post-transcriptional gene expression regulation in mammals. However, accurate prediction of RBP motif sites has been difficult because many RBPs recognize short and degenerate sequences. Here we describe a hidden Markov model (HMM)-based algorithm mCarts to predict clustered functional RBP-binding sites by effectively integrating the number and spacing of individual motif sites, their accessibility in local RNA secondary structures and cross-species conservation. This algorithm learns and quantifies rules of these features, taking advantage of a large number of in vivo RBP-binding sites obtained from cross-linking and immunoprecipitation data. We applied this algorithm to study two representative RBP families, Nova and Mbnl, which regulate tissue-specific alternative splicing through interacting with clustered YCAY and YGCY elements, respectively, and predicted their binding sites in the mouse transcriptome. Despite the low information content in individual motif elements, our algorithm made specific predictions for successful experimental validation. Analysis of predicted sites also revealed cases of extensive and distal RBP-binding sites important for splicing regulation. This algorithm can be readily applied to other RBPs to infer their RNA-regulatory networks. The software is freely available at http://zhanglab.c2b2.columbia.edu/index.php/MCarts.

The RNAsnp web server: predicting SNP effects on local RNA secondary structure

The function of many non-coding RNA genes and cis-regulatory elements of messenger RNA largely depends on the structure, which is in turn determined by their sequence. Single nucleotide polymorphisms (SNPs) and other mutations may disrupt the RNA structure, interfere with the molecular function and hence cause a phenotypic effect. RNAsnp is an efficient method to predict the effect of SNPs on local RNA secondary structure based on the RNA folding algorithms implemented in the Vienna RNA package. The SNP effects are quantified in terms of empirical P-values, which, for computational efficiency, are derived from extensive pre-computed tables of distributions of substitution effects as a function of gene length and GC content. Here, we present a web service that not only provides an interface for RNAsnp but also features a graphical output representation. In addition, the web server is connected to a local mirror of the UCSC genome browser database that enables the users to select the genomic sequences for analysis and visualize the results directly in the UCSC genome browser. The RNAsnp web server is freely available at: http://rth.dk/resources/rnasnp/.

RNAsnp: Efficient Detection of Local RNA Secondary Structure Changes Induced by SNPs

RNAsnp: Efficient Detection of Local RNA Secondary Structure Changes Induced by SNPs