Stability Of RNA Secondary Structure Research Articles

Biomolecular condensates can enhance pathological RNA clustering.

Intracellular aggregation of repeat expanded RNA has been implicated in many neurological disorders. Here, we study the role of biomolecular condensates on irreversible RNA clustering. We find that physiologically relevant and disease-associated repeat RNAs spontaneously undergo an age-dependent percolation transition inside multi-component protein-nucleic acid condensates to form nanoscale clusters. Homotypic RNA clusters drive the emergence of multiphasic condensate structures with an RNA-rich solid core surrounded by an RNA-depleted fluid shell. The timescale of the RNA clustering, which drives a liquid-to-solid transition of biomolecular condensates, is determined by the sequence features, stability of RNA secondary structure, and repeat length. Importantly, G3BP1, the core scaffold of stress granules, introduces heterotypic buffering to homotypic RNA-RNA interactions and impedes intra-condensate RNA clustering in an ATP-independent manner. Our work suggests that biomolecular condensates can act as sites for RNA aggregation. It also highlights the functional role of RNA-binding proteins in suppressing aberrant RNA phase transitions.

Biomolecular Condensates Can Enhance Pathological RNA Clustering.

Intracellular aggregation of repeat expanded RNA has been implicated in many neurological disorders. Here, we study the role of biomolecular condensates on irreversible RNA clustering. We find that physiologically relevant and disease-associated repeat RNAs spontaneously undergo an age-dependent percolation transition inside multi-component protein-nucleic acid condensates to form nanoscale clusters. Homotypic RNA clusters drive the emergence of multiphasic condensate structures with an RNA-rich solid core surrounded by an RNA-depleted fluid shell. The timescale of the RNA clustering, which drives a liquid-to-solid transition of biomolecular condensates, is determined by the sequence features, stability of RNA secondary structure, and repeat length. Importantly, G3BP1, the core scaffold of stress granules, introduces heterotypic buffering to homotypic RNA-RNA interactions and impedes intra-condensate RNA clustering in an ATP-independent manner. Our work suggests that biomolecular condensates can act as sites for RNA aggregation. It also highlights the functional role of RNA-binding proteins in suppressing aberrant RNA phase transitions.

High frequency of transition to transversion ratio in the stem region of RNA secondary structure of untranslated region of SARS-CoV-2.

The propensity of nucleotide bases to form pairs, causes folding and the formation of secondary structure in the RNA. Therefore, purine (R): pyrimidine (Y) base-pairing is vital to maintain uniform lateral dimension in RNA secondary structure. Transversions or base substitutions between R and Y bases, are more detrimental to the stability of RNA secondary structure, than transitions derived from substitutions between A and G or C and T. The study of transversion and transition base substitutions is important to understand evolutionary mechanisms of RNA secondary structure in the 5' and 3' untranslated (UTR) regions of SARS-CoV-2. In this work, we carried out comparative analysis of transition and transversion base substitutions in the stem and loop regions of RNA secondary structure of SARS-CoV-2. We have considered the experimentally determined and well documented stem and loop regions of 5' and 3' UTR regions of SARS-CoV-2 for base substitution analysis. The secondary structure comprising of stem and loop regions were visualized using the RNAfold web server. The GISAID repository was used to extract base sequence alignment of the UTR regions. Python scripts were developed for comparative analysis of transversion and transition frequencies in the stem and the loop regions. The results of base substitution analysis revealed a higher transition (ti) to transversion (tv) ratio (ti/tv) in the stem region of UTR of RNA secondary structure of SARS-CoV-2 reported during the early stage of the pandemic. The higher ti/tv ratio in the stem region suggested the influence of secondary structure in selecting the pattern of base substitutions. This differential pattern of ti/tv values between stem and loop regions was not observed among the Delta and Omicron variants that dominated the later stage of the pandemic. It is noteworthy that the ti/tv values in the stem and loop regions were similar among the later dominant Delta and Omicron variant strains which is to be investigated to understand the rapid evolution and global adaptation of SARS-CoV-2. Our findings implicate the lower frequency of transversions than the transitions in the stem regions of UTRs of SARS-CoV-2. The RNA secondary structures are associated with replication, translation, and packaging, further investigations are needed to understand these base substitutions across different variants of SARS-CoV-2.

Stem Region of tRNA Genes Favors Transition Substitution Towards Keto Bases in Bacteria.

Transversion and transition mutations have variable effects on the stability of RNA secondary structure considering that the former destabilizes the double helix geometry to a greater extent by introducing purine:purine (R:R) or pyrimidine:pyrimidine (Y:Y) base pairs. Therefore, transversion frequency is likely to be lower than that of transition in the secondary structure regions of RNA genes. Here, we performed an analysis of transition and transversion frequencies in tRNA genes defined well with secondary structure and compared with the intergenic regions in five bacterial species namely Escherichia coli, Klebsiella pneumoniae, Salmonella enterica, Staphylococcus aureus and Streptococcus pneumoniae using a large genome sequence data set. In general, the transversion frequency was observed to be lower than that of transition in both tRNA genes and intergenic regions. The transition to transversion ratio was observed to be greater in tRNA genes than that in the intergenic regions in all the five bacteria that we studied. Interestingly, the intraspecies base substitution analysis in tRNA genes revealed that non-compensatory substitutions were more frequent than compensatory substitutions in the stem region. Further, transition to transversion ratio in the loop region was observed to be significantly lesser than that among the non-compensatory substitutions in the stem region. This indicated that the transversion is more deleterious than transition in the stem regions. In addition, substitutions from amino bases (A/C) to keto bases (G/T) were also observed to be more than the reverse substitutions in the stem region. Substitution from amino bases to keto bases are likely to facilitate the stable G:U pairing unlike the reverse substitution that facilitates the unstable A:C pairing in the stem region of tRNA. This work provides additional support that the secondary structure of tRNA molecule is what drives the different substitutions in its gene sequence.

N6-Methyladenosine Modification in a Long Noncoding RNA Hairpin Predisposes Its Conformation to Protein Binding

N6-Methyladenosine (m6A) is a reversible and abundant internal modification of messenger RNA (mRNA) and long noncoding RNA (lncRNA) with roles in RNA processing, transport, and stability. Although m6A does not preclude Watson–Crick base pairing, the N6-methyl group alters the stability of RNA secondary structure. Since changes in RNA structure can affect diverse cellular processes, the influence of m6A on mRNA and lncRNA structure has the potential to be an important mechanism for m6A function in the cell. Indeed, an m6A site in the lncRNA metastasis associated lung adenocarcinoma transcript 1 (MALAT1) was recently shown to induce a local change in structure that increases the accessibility of a U5-tract for recognition and binding by heterogeneous nuclear ribonucleoprotein C (HNRNPC). This m6A-dependent regulation of protein binding through a change in RNA structure, termed “m6A-switch”, affects transcriptome-wide mRNA abundance and alternative splicing. To further characterize this first example of an m6A-switch in a cellular RNA, we used nuclear magnetic resonance and Förster resonance energy transfer to demonstrate the effect of m6A on a 32-nucleotide RNA hairpin derived from the m6A-switch in MALAT1. The observed imino proton nuclear magnetic resonance resonances and Förster resonance energy transfer efficiencies suggest that m6A selectively destabilizes the portion of the hairpin stem where the U5-tract is located, increasing the solvent accessibility of the neighboring bases while maintaining the overall hairpin structure. The m6A-modified hairpin has a predisposed conformation that resembles the hairpin conformation in the RNA–HNRNPC complex more closely than the unmodified hairpin. The m6A-induced structural changes in the MALAT1 hairpin can serve as a model for a large family of m6A-switches that mediate the influence of m6A on cellular processes.

Rational Design and Tuning of Functional RNA Switch to Control an Allosteric Intermolecular Interaction.

Conformational transitions of biomolecules in response to specific stimuli control many biological processes. In natural functional RNA switches, often called riboswitches, a particular RNA structure that has a suppressive or facilitative effect on gene expression transitions to an alternative structure with the opposite effect upon binding of a specific metabolite to the aptamer region. Stability of RNA secondary structure (-ΔG°) can be predicted based on thermodynamic parameters and is easily tuned by changes in nucleobases. We envisioned that tuning of a functional RNA switch that causes an allosteric interaction between an RNA and a peptide would be possible based on a predicted switching energy (ΔΔG°) that corresponds to the energy difference between the RNA secondary structure before (-ΔG°before) and after (-ΔG°after) the RNA conformational transition. We first selected functional RNA switches responsive to neomycin with predicted ΔΔG° values ranging from 5.6 to 12.2 kcal mol(-1). We then demonstrated a simple strategy to rationally convert the functional RNA switch to switches responsive to natural metabolites thiamine pyrophosphate, S-adenosyl methionine, and adenine based on the predicted ΔΔG° values. The ΔΔG° values of the designed RNA switches proportionally correlated with interaction energy (ΔG°interaction) between the RNA and peptide, and we were able to tune the sensitivity of the RNA switches for the trigger molecule. The strategy demonstrated here will be generally applicable for construction of functional RNA switches and biosensors in which mechanisms are based on conformational transition of nucleic acids.

MBNL1-RNA Interactions: Binding-Induced Rna Conformational Changes

The muscleblind-like protein 1 (MBNL1) is an RNA binding protein that regulates mRNA alternative splicing. It is implicated to be involved in myotonic dystrophy, an inherited multisystem disease, through interacting with poly(CUG) or poly(CCUG) RNA. In the disease state, MBNL1 is abnormally expressed and translocated, which leads to many mis-splicing events. MBNL1 can bind various RNA substrates, most of which share a stem-loop structure containing 5’YGCY3’(Y=U or C) motifs. Using FRET together with a combination of stopped-flow kinetic fluorescence measurements and gel shift assays, we have investigated the relationship between MBNL1-RNA interactions and RNA secondary structure. This work suggested that binding of MBNL1 destabilizes the RNA secondary structure and leads to a partial melting of the stem loop RNA. The RNA secondary structure stability is directly correlated with the kinetic and thermodynamic properties of the MBNL1-RNA complex. The data presented here provides insight into the role of RNA secondary structure in regulation of alternative splicing by MBNL1 and suggests new perspectives for drug development for myotonic dystrophy.

Prediction and characterization of noncoding RNAs in C. elegans by integrating conservation, secondary structure, and high-throughput sequencing and array data

We present an integrative machine learning method, incRNA, for whole-genome identification of noncoding RNAs (ncRNAs). It combines a large amount of expression data, RNA secondary-structure stability, and evolutionary conservation at the protein and nucleic-acid level. Using the incRNA model and data from the modENCODE consortium, we are able to separate known C. elegans ncRNAs from coding sequences and other genomic elements with a high level of accuracy (97% AUC on an independent validation set), and find more than 7000 novel ncRNA candidates, among which more than 1000 are located in the intergenic regions of C. elegans genome. Based on the validation set, we estimate that 91% of the approximately 7000 novel ncRNA candidates are true positives. We then analyze 15 novel ncRNA candidates by RT-PCR, detecting the expression for 14. In addition, we characterize the properties of all the novel ncRNA candidates and find that they have distinct expression patterns across developmental stages and tend to use novel RNA structural families. We also find that they are often targeted by specific transcription factors (∼59% of intergenic novel ncRNA candidates). Overall, our study identifies many new potential ncRNAs in C. elegans and provides a method that can be adapted to other organisms.

Single feature polymorphisms between two rice cultivars detected using a median polish method

Expression levels measured in microarrays of oligonucleotide probes have now been adapted as a high throughput approach for identifying DNA sequence variation between genotypes, referred to as single feature polymorphisms (SFPs). Although there have been increasing interests in this approach, there is still need for improving the algorithm in order to achieve high sensitivity and specificity especially with complex genome and large datasets, while maintaining optimal computational performance. We obtained microarray datasets for expression profiles of two rice cultivars and adapted a median polish method to detect SFPs. The analysis identified 6,655 SFPs between two the rice varieties representing 3,131 rice unique genes. We showed that the median polish method has the advantage of avoiding fitting complex linear models thus can be used to analyze complex transcriptome datasets like the ones in this study. The method is also superior in sensitivity, accuracy and computing time requirement compared with two previously used methods. A comparison with data from a resequencing project indicated that 75.6% of the SFPs had SNP supports in the probe regions. Further comparison revealed that SNPs in sequences immediately flanking the probes also had contributions to the detection of SFPs in cases where the probes and the targets had perfectly matched sequences. It was shown that differences in minimum free energies caused by flanking SNPs, which may change the stability of RNA secondary structure, may partly explain the SFPs as detected. These SFPs may facilitate gene discovery in future studies.

No evidence that mRNAs have lower folding free energies than random sequences with the same dinucleotide distribution.

This work investigates whether mRNA has a lower estimated folding free energy than random sequences. The free energy estimates are calculated by the mfold program for prediction of RNA secondary structures. For a set of 46 mRNAs it is shown that the predicted free energy is not significantly different from random sequences with the same dinucleotide distribution. For random sequences with the same mononucleotide distribution it has previously been shown that the native mRNA sequences have a lower predicted free energy, which indicates a more stable structure than random sequences. However, dinucleotide content is important when assessing the significance of predicted free energy as the physical stability of RNA secondary structure is known to depend on dinucleotide base stacking energies. Even known RNA secondary structures, like tRNAs, can be shown to have predicted free energies indistinguishable from randomized sequences. This suggests that the predicted free energy is not always a good determinant for RNA folding.

Free energy of imperfect nucleic acid helices: III. Small internal loops resulting from mismatches

Physical studies of enzymioally synthesized oligoribonucleotides of defined sequence are used to evaluate quantitatively the destabilizing influence of mismatched bases in a double helix. The series (A-) 4G(-C) n (-U) 4, N = 1 to 6, exist as imperfect dimer helices when N is equal to or less than 4, and as monomolecular hairpin helices when N is 5 and 6. Internal loops become progressively more destabilizing as their size increases from 2 to 4 to 6 nucleotides resulting from 1, 2 and 3 consecutive mismatched base pairs. However, the stability of a helix will generally be greater if a given number of mismatched pairs occur consecutively rather than in isolation from one another. These data may be used for improved calculations of stability of RNA secondary structure, to estimate the frequency of structural fluctuations in a double helix and to assess the stability of modified polynucleotide helices. An unmodified double helix of one million randomly arranged base pairs should contain on the time average approximately 10 G.C and 500 A.U pairs in non-hydrogen bonded, unstacked conformations at 25 °C. Our estimate of the effect of mismatching on T m values of high polymers is less precise because of the long temperature extrapolation required. However, we estimate that DNA or RNA treated with mutagens which interrupt up to 20% of the nucleotide pairs will show a drop of about 1.2 deg. C in melting temperature with each unit per cent of modification.