Genome-Wide Analysis of RNA Secondary Structure

Targeting RNA with small molecules, from RNA structures to precision medicines: IUPHAR review: 40

RNA plays important roles in regulating both health and disease biology in all kingdoms of life. Notably, RNA can form intricate three-dimensional structures, and their biological functions are dependent on these structures. Targeting the structured regions of RNA with small molecules has gained increasing attention over the past decade, because it provides both chemical probes to study fundamental biology processes and lead medicines for diseases with unmet medical needs. Recent advances in RNA structure prediction and determination and RNA biology have accelerated the rational design and development of RNA-targeted small molecules to modulate disease pathology. However, challenges remain in advancing RNA-targeted small molecules towards clinical applications. This review summarizes strategies to study RNA structures, to identify small molecules recognizing these structures, and to augment the functionality of RNA-binding small molecules. We focus on recent advances in developing RNA-targeted small molecules as potential therapeutics in a variety of diseases, encompassing different modes of actions and targeting strategies. Furthermore, we present the current gaps between early-stage discovery of RNA-binding small molecules and their clinical applications, as well as a roadmap to overcome these challenges in the near future.

Nuclear PKM2 binds pre-mRNA at folded G-quadruplexes and reveals their gene regulatory role

Nuclear localization of the metabolic enzyme PKM2 is widely observed in various cancer types. We identify nuclear PKM2 as a non-canonical RNA-binding protein (RBP) that specifically interacts with folded RNA G-quadruplex (rG4) structures in precursor mRNAs (pre-mRNAs). PKM2 occupancy at rG4s prevents the binding of repressive RBPs, such as HNRNPF, and promotes the expression of rG4-containing pre-mRNAs (the "rG4ome"). We observe an upregulation of the rG4ome during epithelial-to-mesenchymal transition and a negative correlation of rG4 abundance with patient survival in different cancer types. By preventing the nuclear accumulation of PKM2, we could repress the rG4ome in triple-negative breast cancer cells and reduce migration and invasion of cancer cells in vitro and in xenograft mouse models. Our data suggest that the balance of folded and unfolded rG4s controlled by RBPs impacts gene expression during tumor progression.

Selective and non-selective evolutionary signatures found in the simplest replicative biological entities

Mitoviruses, which are considered evolutionary relics of extinct alpha-proteobacteria RNA phages, represent one of the simplest self-replicating biological systems. This study aims to quantitatively describe genomes and identify potential genomic signatures that support the protein phylogenetic-based classification criterion. Genomic variables, such as mononucleotide and dinucleotide composition, codon usage bias, and minimal free energy derived from optimized predicted RNA secondary structure, were analyzed. From the values obtained, the main evolutionary pressures were discussed, indicating that natural selection plays a significant role in shaping mitovirus genomes. However, neutral evolution also makes a significant contribution. This study reveals a significant discovery of structural divergence in Kvaramitovirus. The energy minimization approach employed to study 2D folding in this study reveals a distinct spatial organization of their genomes, providing evidence for the hypothesis of a single evolutionary event of circularization in the most recent common ancestor of the lineage. This hypothesis was discussed in light of recent discoveries by other researchers that partially support the existence of mitoviruses with circular genomes. Finally, this study represents a significant advancement in the understanding of mitoviruses, as it quantitatively describes the nucleotide sequence at the family and genus taxonomic levels. Additionally, we provide hypotheses that can be experimentally validated to inspire new research and address the gaps in knowledge of this fascinating, basally divergent RNA virus lineage.

Direct testing of natural twister ribozymes from over a thousand organisms reveals a broad tolerance for structural imperfections

Twister ribozymes are an extensively studied class of nucleolytic RNAs. Thousands of natural twisters have been proposed using sequence homology and structural descriptors. Yet, most of these candidates have not been validated experimentally. To address this gap, we developed CHiTA (Cleavage High-Throughput Assay), a high-throughput pipeline utilizing massively parallel oligonucleotide synthesis and next-generation sequencing to test putative ribozymes en masse in a scarless fashion. As proof of principle, we applied CHiTA to a small set of known active and mutant ribozymes. We then used CHiTA to test two large sets of naturally occurring twister ribozymes: over 1, 600 previously reported putative twisters and ∼1, 000 new candidate twisters. The new candidates were identified computationally in ∼1, 000 organisms, representing a massive increase in the number of ribozyme-harboring organisms. Approximately 94% of the twisters we tested were active and cleaved site-specifically. Analysis of their structural features revealed that many substitutions and helical imperfections can be tolerated. We repeated our computational search with structural descriptors updated from this analysis, whereupon we identified and confirmed the first intrinsically active twister ribozyme in mammals. CHiTA broadly expands the number of active twister ribozymes found in nature and provides a powerful method for functional analyses of other RNAs.

GRAPHICAL ABSTRACT

Identification of RNA structures and their roles in RNA functions

The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.

Synthetic Peptides: Promising Modalities for the Targeting of Disease-Related Nucleic Acids

DNA and RNA play pivotal roles in life processes by storing and transferring genetic information, modulating gene expression, and contributing to essential cellular machinery such as ribosomes. Dysregulation and mutations in nucleic acid-related processes are implicated in numerous diseases. Despite the critical impact on health of nucleic acid mutations or dysregulation, therapeutic compounds addressing these biomolecules remain limited. Peptides have emerged as a promising class of molecules for biomedical research, offering potential solutions for challenging drug targets. This review focuses on the use of synthetic peptides to target disease-related nucleic acids. We discuss examples of peptides targeting double-stranded DNA, including the clinical candidate Omomyc, and compounds designed for regulatory G-quadruplexes. Further, we provide insights into both library-based screenings and the rational design of peptides to target regulatory human RNA scaffolds and viral RNAs, emphasizing the potential of peptides in addressing nucleic acid-related diseases.

Heterobifunctional small molecules to modulate RNA function

RNA has diverse cellular functionality, including regulating gene expression, protein translation, and cellular response to stimuli, due to its intricate structures. Over the past decade, small molecules have been discovered that target functional structures within cellular RNAs and modulate their function. Simple binding, however, is often insufficient, resulting in low or even no biological activity. To overcome this challenge, heterobifunctional compounds have been developed that can covalently bind to the RNA target, alter RNA sequence, or induce its cleavage. Herein, we review the recent progress in the field of RNA-targeted heterobifunctional compounds using representative case studies. We identify critical gaps and limitations and propose a strategic pathway for future developments of RNA-targeted molecules with augmented functionalities.

Evolution of the structure of lipid nanoparticles for nucleic acid delivery: From in situ studies of formulation to colloidal stability

The development of lipid nanoparticle (LNP) based therapeutics for delivery of RNA has triggered the advance of new strategies for formulation, such as high throughput microfluidics for precise mixing of components into well-defined particles. In this study, we have characterised the structure of LNPs throughout the formulation process using in situ small angle x-ray scattering in the microfluidic chip, then by sampling in the subsequent dialysis process. The final formulation was investigated with small angle x-ray (SAXS) and neutron (SANS) scattering, dynamic light scattering (DLS) and cryo-TEM. The effect on structure was investigated for LNPs with a benchmark lipid composition and containing different cargos: calf thymus DNA (DNA) and two model mRNAs, polyadenylic acid (polyA) and polyuridylic acid (polyU). The LNP structure evolved during mixing in the microfluidic channel, however was only fully developed during the dialysis. The colloidal stability of the final formulation was affected by the type of incorporated nucleic acids (NAs) and decreased with the degree of base-pairing, as polyU induced extensive particle aggregation. The main NA LNP peak in the SAXS data for the final formulation were similar, with the repeat distance increasing from polyU Collapse

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MESH Headings

• Scattering, Small Angle
• Lipids/chemistry
• X-Ray Diffraction
• Nanoparticles/chemistry
• DNA
• RNA, Messenger
• RNA, Small Interfering/chemistry
• Liposomes

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Grants Collapse

Affiliation(s)

Jennifer Gilbert Division of Physical Chemistry, Department of Chemistry, Lund University, 221 00 Lund, Sweden; NanoLund, Lund University, Professorsgatan 1, 223 63 Lund, Sweden
Federica Sebastiani Division of Physical Chemistry, Department of Chemistry, Lund University, 221 00 Lund, Sweden; Department of Pharmacy, University of Copenhagen, Universitetsparken 2, 2100 København Ø, Denmark
Marianna Yanez Arteta Advanced Drug Delivery, Pharmaceutical Sciences, R&D, AstraZeneca, 431 83, Gothenburg, Sweden
Ann Terry MAX IV Laboratory, Lund University, Fotongatan 2, 224 84 Lund, Sweden
Anna Fornell MAX IV Laboratory, Lund University, Fotongatan 2, 224 84 Lund, Sweden
Robert Russell National Deuteration Facility (NDF), Australian Nuclear Science and Technology Organisation (ANSTO), Lucas Heights, 2232 Sydney, NSW, Australia
Najet Mahmoudi ISIS Neutron and Muon Source, Harwell Science and Innovation Campus, Didcot OX11 0QX, UK
Tommy Nylander Division of Physical Chemistry, Department of Chemistry, Lund University, 221 00 Lund, Sweden; NanoLund, Lund University, Professorsgatan 1, 223 63 Lund, Sweden; LINXS Institute of Advanced Neutron and X-Ray Science, Lund, Sweden; School of Chemical Engineering and Translational Nanobioscience Research Center, Sungkyunkwan University, Suwon, Republic of Korea.

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Small molecule approaches to targeting RNA

The development of innovative methodologies to identify RNA binders has attracted enormous attention in chemical biology and drug discovery. Although antibiotics targeting bacterial ribosomal RNA have been on the market for decades, the renewed interest in RNA targeting reflects the need to better understand complex intracellular processes involving RNA. In this context, small molecules are privileged tools used to explore the biological functions of RNA and to validate RNAs as therapeutic targets, and they eventually are to become new drugs. Despite recent progress, the rational design of specific RNA binders requires a better understanding of the interactions which occur with the RNA target to reach the desired biological response. In this Review, we discuss the challenges to approaching this underexplored chemical space, together with recent strategies to bind, interact and affect biologically relevant RNAs.

On the interactions between RNA and titrateable lipid layers: implications for RNA delivery with lipid nanoparticles

Characterising the interaction between cationic ionisable lipids (CIL) and nucleic acids (NAs) is key to understanding the process of RNA lipid nanoparticle (LNP) formation and release of NAs from LNPs. Here, we have used different surface techniques to reveal the effect of pH and NA type on the interaction with a model system of DOPC and the CIL DLin-MC3-DMA (MC3). At only 5% MC3, differences in the structure and dynamics of the lipid layer were observed. Both pH and %MC3 were shown to affect the absorption behaviour of erythropoietin mRNA, polyadenylic acid (polyA) and polyuridylic acid (polyU). The adsorbed amount of all studied NAs was found to increase with decreasing pH and increasing %MC3 but with different effects on the lipid layer, which could be linked to the NA secondary structure. For polyA at pH 6, adsorption to the surface of the layer was observed, whereas for other conditions and NAs, penetration of the NA into the layer resulted in the formation of a multilayer structure. By comparison to simulations excluding the secondary structure, differences in adsorption behaviours between polyA and polyU could be observed, indicating that the NA's secondary structure also affected the MC3-NA interactions.

Flanking Sequence Cotranscriptionally Regulates Twister Ribozyme Activity

Small nucleolytic ribozymes are RNAs that cleave their own phosphodiester backbone. While proteinaceous enzymes are regulated by a variety of known mechanisms, methods of regulation for ribozymes remain unclear. Twister is one ribozyme class for which many structural and catalytic properties have been elucidated. However, few studies have analyzed the activity of twister ribozymes in the context of a native flanking sequence, even though ribozymes as transcribed in nature do not exist in isolation. Interactions between the ribozyme and its neighboring sequences can induce conformational changes that inhibit self-cleavage, providing a regulatory mechanism that could naturally determine ribozyme activity in vivo and in synthetic applications. To date, eight twister ribozymes have been identified within the staple crop rice (Oryza sativa). Herein, we select several twister ribozymes from rice and show that they are differentially regulated by their flanking sequence using published RNA-seq data sets, structure probing, and cotranscriptional cleavage assays. We found that the Osa 1-2 ribozyme does not interact with its flanking sequences. However, sequences flanking the Osa 1-3 and Osa 1-8 ribozymes form inactive conformations, referred to here as "ribozymogens", that attenuate ribozyme self-cleavage activity. For the Osa 1-3 ribozyme, we show that activity can be rescued upon addition of a complementary antisense oligonucleotide, suggesting ribozymogens can be controlled via external signals. In all, our data provide a plausible mechanism wherein flanking sequence differentially regulates ribozyme activity in vivo. More broadly, the ability to regulate ribozyme behavior locally has potential applications in control of gene expression and synthetic biology.

RNA Folding, Mutation, and Detection

The structure of RNA molecules is absolutely critical to their functions in a biological system. RNA structure is dynamic and changes in response to cellular needs. Within the last few decades, there has been an increased interest in studying the structure of RNA molecules and how they change to support the needs of the cell in different conditions. Selective 2'-hydroxyl acylation-based mutational profiling using high-throughput sequencing is a powerful method to predict the secondary structure of RNA molecules both in vivo and in immunopurified samples. Selective 2'-hydroxyl acylation-based mutational profiling using high-throughput sequencing works by adding bulky groups onto accessible "flexible" bases in an RNA molecule that are not involved in any base-pairing or RNA-protein interactions. When the RNA is reverse transcribed into cDNA, the bulky groups are incorporated as base mutations, which can be compared to an unmodified control to identify the locations of flexible bases. The comparison of sequence data between modified and unmodified samples allows the computer software program (developed to generate reactivity profiles) to generate RNA secondary structure models. These models can be compared in a variety of conditions to determine how specific stimuli influence RNA secondary structures.

Modified Nucleotides and RNA Structure Prediction

Nucleotide modifications are occurrent in all types of RNA and play an important role in RNA structure formation and stability. Modified bases not only possess the ability to shift the RNA structure ensemble towards desired functional confirmations. By changes in the base pairing partner preference, they may even enlarge or reduce the conformational space, i.e., the number and types of structures the RNA molecule can adopt. However, most methods to predict RNA secondary structure do not provide the means to include the effect of modifications on the result. With the help of a heavily modified transfer RNA (tRNA) molecule, this chapter demonstrates how to include the effect of different base modifications into secondary structure prediction using the ViennaRNA Package. The constructive approach demonstrated here allows for the calculation of minimum free energy structure and suboptimal structures at different levels of modified base support. In particular we, show how to incorporate the isomerization of uridine to pseudouridine ( Ψ ) and the reduction of uridine to dihydrouridine (D).

Effective Antiviral Application of Antisense in Plants by Exploiting Accessible Sites in the Target RNA

Antisense oligodeoxynucleotides (ASOs) have long been used to selectively inhibit or modulate gene expression at the RNA level, and some ASOs are approved for clinical use. However, the practicability of antisense technologies remains limited by the difficulty of reliably predicting the sites accessible to ASOs in complex folded RNAs. Recently, we applied a plant-based method that reproduces RNA-induced RNA silencing in vitro to reliably identify sites in target RNAs that are accessible to small interfering RNA (siRNA)-guided Argonaute endonucleases. Here, we show that this method is also suitable for identifying ASOs that are effective in DNA-induced RNA silencing by RNases H. We show that ASOs identified in this way that target a viral genome are comparably effective in protecting plants from infection as siRNAs with the corresponding sequence. The antiviral activity of the ASOs could be further enhanced by chemical modification. This led to two important conclusions: siRNAs and ASOs that can effectively knock down complex RNA molecules can be identified using the same approach, and ASOs optimized in this way could find application in crop protection. The technology developed here could be useful not only for effective RNA silencing in plants but also in other organisms.

miRNA-like secondary structures in maize (Zea mays) genes and transposable elements correlate with small RNAs, methylation, and expression

RNA molecules carry information in their primary sequence and also their secondary structure. Secondary structure can confer important functional information, but it is also a signal for an RNAi-like host epigenetic response mediated by small RNAs (smRNAs). In this study, we used two bioinformatic methods to predict local secondary structures across features of the maize genome, focusing on small regions that had similar folding properties to pre-miRNA loci. We found miRNA-like secondary structures to be common in genes and most, but not all, superfamilies of RNA and DNA transposable elements (TEs). The miRNA-like regions map to a higher diversity of smRNAs than regions without miRNA-like structure, explaining up to 27% of variation in smRNA mapping for some TE superfamilies. This mapping bias is more pronounced among putatively autonomous TEs relative to nonautonomous TEs. Genome-wide, miRNA-like regions are also associated with elevated methylation levels, particularly in the CHH context. Among genes, those with miRNA-like secondary structure are 1.5-fold more highly expressed, on average, than other genes. However, these genes are also more variably expressed across the 26 nested association mapping founder lines, and this variability positively correlates with the number of mapping smRNAs. We conclude that local miRNA-like structures are a nearly ubiquitous feature of expressed regions of the maize genome, that they correlate with higher smRNA mapping and methylation, and that they may represent a trade-off between functional requirements and the potentially negative consequences of smRNA production.

In vivo-like nearest neighbor parameters improve prediction of fractional RNA base-pairing in cells

We conducted a thermodynamic analysis of RNA stability in Eco80 artificial cytoplasm, which mimics in vivo conditions, and compared it to transcriptome-wide probing of mRNA. Eco80 contains 80% of Escherichia coli metabolites, with biological concentrations of metal ions, including 2 mM free Mg2+ and 29 mM metabolite-chelated Mg2+. Fluorescence-detected binding isotherms (FDBI) were used to conduct a thermodynamic analysis of 24 RNA helices and found that these helices, which have an average stability of -12.3 kcal/mol, are less stable by ΔΔGo37 ∼1 kcal/mol. The FDBI data was used to determine a set of Watson-Crick free energy nearest neighbor parameters (NNPs), which revealed that Eco80 reduces the stability of three NNPs. This information was used to adjust the NN model using the RNAstructure package. The in vivo-like adjustments have minimal effects on the prediction of RNA secondary structures determined in vitro and in silico, but markedly improve prediction of fractional RNA base pairing in E. coli, as benchmarked with our in vivo DMS and EDC RNA chemical probing data. In summary, our thermodynamic and chemical probing analyses of RNA helices indicate that RNA secondary structures are less stable in cells than in artificially stable in vitro buffer conditions.

Exploring the adaptability of the secondary structure of mRNA to temperature in intertidal snails based on SHAPE experiments

RNA-based thermal regulation is an important strategy for organisms to cope with temperature changes. Inhabiting the intertidal rocky shore, a key interface of the ocean, atmosphere and terrestrial environments, intertidal species have developed variable thermal adaptation mechanisms; however, adaptions at the RNA level remain largely uninvestigated. To examine the relationship between mRNA structural stability and species distribution, in the present study, the secondary structure of cytosolic malate dehydrogenase (cMDH) mRNA of Echinolittorina malaccana, Echinolittorina radiata and Littorina brevicula was determined using selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE), and the change in folding free energy of formation (ΔGfold) was calculated. The results showed that ΔGfold increased as the temperature increased. The difference in ΔGfold (ΔΔGfold) between two specific temperatures (25 versus 0°C, 37 versus 0°C and 57 versus 0°C) differed among the three species, and the ΔΔGfold value of E. malaccana was significantly lower than those of E. radiata and L. brevicula. The number of stems of cMDH mRNA of the snails decreased with increasing temperature, and the breakpoint temperature of E. malaccana was the highest among these. The number of loops was also reduced with increasing temperature, while the length of the loop structure increased accordingly. Consequently, these structural changes can potentially affect the translational efficiency of mRNA. These results imply that there were interspecific differences in the thermal stability of RNA secondary structures in intertidal snails, and these differences may be related to snail distribution.

StemP: A Fast and Deterministic Stem-Graph Approach for RNA Secondary Structure Prediction

We propose a new deterministic methodology to predict the secondary structure of RNA sequences. What information of stem is important for structure prediction, and is it enough ? The proposed simple deterministic algorithm uses minimum stem length, Stem-Loop score, and co-existence of stems, to give good structure predictions for short RNA and tRNA sequences. The main idea is to consider all possible stem with certain stem loop energy and strength to predict RNA secondary structure. We use graph notation, where stems are represented as vertexes, and co-existence between stems as edges. This full Stem-graph presents all possible folding structure, and we pick sub-graph(s) which give the best matching energy for structure prediction. Stem-Loop score adds structure information and speeds up the computation. The proposed method can predict secondary structure even with pseudo knots. One of the strengths of this approach is the simplicity and flexibility of the algorithm, and it gives a deterministic answer. Numerical experiments are done on various sequences from Protein Data Bank and the Gutell Lab using a laptop and results take only a few seconds.

Alu RNA fold links splicing with signal recognition particle proteins

Transcriptomic diversity in primates was considerably expanded by exonizations of intronic Alu elements. To better understand their cellular mechanisms we have used structure-based mutagenesis coupled with functional and proteomic assays to study the impact of successive primate mutations and their combinations on inclusion of a sense-oriented AluJ exon in the human F8 gene. We show that the splicing outcome was better predicted by consecutive RNA conformation changes than by computationally derived splicing regulatory motifs. We also demonstrate an involvement of SRP9/14 (signal recognition particle) heterodimer in splicing regulation of Alu-derived exons. Nucleotide substitutions that accumulated during primate evolution relaxed the conserved left-arm AluJ structure including helix H1 and reduced the capacity of SRP9/14 to stabilize the closed Alu conformation. RNA secondary structure-constrained mutations that promoted open Y-shaped conformations of the Alu made the Alu exon inclusion reliant on DHX9. Finally, we identified additional SRP9/14 sensitive Alu exons and predicted their functional roles in the cell. Together, these results provide unique insights into architectural elements required for sense Alu exonization, identify conserved pre-mRNA structures involved in exon selection and point to a possible chaperone activity of SRP9/14 outside the mammalian signal recognition particle.

Natural variation in codon bias and mRNA folding strength interact synergistically to modify protein expression in Saccharomyces cerevisiae

Codon bias and mRNA folding strength (mF) are hypothesized molecular mechanisms by which polymorphisms in genes modify protein expression. Natural patterns of codon bias and mF across genes as well as effects of altering codon bias and mF suggest that the influence of these 2 mechanisms may vary depending on the specific location of polymorphisms within a transcript. Despite the central role codon bias and mF may play in natural trait variation within populations, systematic studies of how polymorphic codon bias and mF relate to protein expression variation are lacking. To address this need, we analyzed genomic, transcriptomic, and proteomic data for 22 Saccharomyces cerevisiae isolates, estimated protein accumulation for each allele of 1,620 genes as the log of protein molecules per RNA molecule (logPPR), and built linear mixed-effects models associating allelic variation in codon bias and mF with allelic variation in logPPR. We found that codon bias and mF interact synergistically in a positive association with logPPR, and this interaction explains almost all the effects of codon bias and mF. We examined how the locations of polymorphisms within transcripts influence their effects and found that codon bias primarily acts through polymorphisms in domain-encoding and 3' coding sequences, while mF acts most significantly through coding sequences with weaker effects from untranslated regions. Our results present the most comprehensive characterization to date of how polymorphisms in transcripts influence protein expression.

An overview on nucleic-acid G-quadruplex prediction: from rule-based methods to deep neural networks

Nucleic-acid G-quadruplexes (G4s) play vital roles in many cellular processes. Due to their importance, researchers have developed experimental assays to measure nucleic-acid G4s in high throughput. The generated high-throughput datasets gave rise to unique opportunities to develop machine-learning-based methods, and in particular deep neural networks, to predict G4s in any given nucleic-acid sequence and any species. In this paper, we review the success stories of deep-neural-network applications for G4 prediction. We first cover the experimental technologies that generated the most comprehensive nucleic-acid G4 high-throughput datasets in recent years. We then review classic rule-based methods for G4 prediction. We proceed by reviewing the major machine-learning and deep-neural-network applications to nucleic-acid G4 datasets and report a novel comparison between them. Next, we present the interpretability techniques used on the trained neural networks to learn key molecular principles underlying nucleic-acid G4 folding. As a new result, we calculate the overlap between measured DNA and RNA G4s and compare the performance of DNA- and RNA-G4 predictors on RNA- and DNA-G4 datasets, respectively, to demonstrate the potential of transfer learning from DNA G4s to RNA G4s. Last, we conclude with open questions in the field of nucleic-acid G4 prediction and computational modeling.

RNA Polymerase III-Dependent BoNR8 and AtR8 lncRNAs Contribute to Hypocotyl Elongation in Response to Light and Abscisic Acid

Hypocotyl elongation is inhibited by light and promoted by darkness. The plant hormone abscisic acid (ABA) also inhibits hypocotyl elongation. However, details of the molecular mechanism that regulates the integrated effects of light and ABA signaling on hypocotyl elongation remain unclear. Long non-coding RNAs (lncRNAs; >200 nt) do not encode proteins but play many physiological roles in organisms. Until now, only a few lncRNAs related to hypocotyl elongation have been reported. The lncRNAs BoNR8 (272 nt) and AtR8 (259 nt), both of which are transcribed by RNA polymerase III, are homologous lncRNAs that are abundantly present in cabbage and Arabidopsis, respectively. These lncRNAs shared 77% sequence identity, and their predicted RNA secondary structures were similar; the non-conserved nucleotides in both sequences were positioned mainly in the stem-loop regions of the secondary structures. A previous study showed that BoNR8 regulated seed germination along with ABA and that AtR8 may be involved in innate immune function in Arabidopsis. Our results show that the expression levels of BoNR8 and AtR8 were differentially affected by light and ABA and that overexpression (OX) of both BoNR8 and AtR8 in Arabidopsis regulated hypocotyl elongation depending on light and ABA.. The expression levels of light-related genes PHYB, COP1, HY5 and PIF4 and ABA-related genes ABI3 and ABI5 were altered in the AtR8-OX and BoNR8-OX lines, and, in an ABI3-defective mutant, hypocotyl elongation was greatly increased under dark condition with the addition of ABA. These results indicate that BoNR8 and AtR8 regulate hypocotyl elongation together with ABI3 and key downstream light signaling genes.

Sequence similarity governs generalizability of de novo deep learning models for RNA secondary structure prediction

Making no use of physical laws or co-evolutionary information, de novo deep learning (DL) models for RNA secondary structure prediction have achieved far superior performances than traditional algorithms. However, their statistical underpinning raises the crucial question of generalizability. We present a quantitative study of the performance and generalizability of a series of de novo DL models, with a minimal two-module architecture and no post-processing, under varied similarities between seen and unseen sequences. Our models demonstrate excellent expressive capacities and outperform existing methods on common benchmark datasets. However, model generalizability, i.e., the performance gap between the seen and unseen sets, degrades rapidly as the sequence similarity decreases. The same trends are observed from several recent DL and machine learning models. And an inverse correlation between performance and generalizability is revealed collectively across all learning-based models with wide-ranging architectures and sizes. We further quantitate how generalizability depends on sequence and structure identity scores via pairwise alignment, providing unique quantitative insights into the limitations of statistical learning. Generalizability thus poses a major hurdle for deploying de novo DL models in practice and various pathways for future advances are discussed.

Effects of the Expressions and Variants of the CAST Gene on the Fatty Acid Composition of the Longissimus Thoracis Muscle of Grazing Sonid Sheep

Fatty acid (FA) composition has an important impact on the nutrition and flavor of meat, and on consumer health, and is receiving more attention in the sheep industry. This study aimed to evaluate the relationship between the expression levels of the CAST gene and the FA composition in the longissimus thoracis (LL) muscle, to identify novel variants of CAST, and to perform association analysis with the FA composition in grazing Sonid lambs. The correlation results showed that high expression levels of CAST are correlated with better FA compositions and classes in LL. For association studies, the results showed that c.1210C>T and c.1437G>A in LD-M, and c.2097C>T mutations are associated with some compositions and classes of FA in the LL of grazing Sonid sheep. Two missense c.646G>C (G216R) and c.1210C>T (R404C) mutations were predicted to influence the Calpain_inhib domains of CAST. Thus, the correlation results and associated mutations are expected to be genetic selection markers for the FA composition and meat quality of grazing Sonid lamb muscle and provide new insights into sheep meat quality traits influenced by the ovine CAST gene.

Targeting RNA structures with small molecules

RNA adopts 3D structures that confer varied functional roles in human biology and dysfunction in disease. Approaches to therapeutically target RNA structures with small molecules are being actively pursued, aided by key advances in the field including the development of computational tools that predict evolutionarily conserved RNA structures, as well as strategies that expand mode of action and facilitate interactions with cellular machinery. Existing RNA-targeted small molecules use a range of mechanisms including directing splicing - by acting as molecular glues with cellular proteins (such as branaplam and the FDA-approved risdiplam), inhibition of translation of undruggable proteins and deactivation of functional structures in noncoding RNAs. Here, we describe strategies to identify, validate and optimize small molecules that target the functional transcriptome, laying out a roadmap to advance these agents into the next decade.

Widespread autogenous mRNA-protein interactions detected by CLIP-seq

Autogenous interactions between mRNAs and the proteins they encode are implicated in cellular feedback-loop regulation, but their extent and mechanistic foundation are unclear. It was recently hypothesized that such interactions may be common, reflecting the role of intrinsic nucleobase-amino acid affinities in shaping the genetic code's structure. Here we analyze a comprehensive set of CLIP-seq experiments involving multiple protocols and report on widespread autogenous interactions across different organisms. Specifically, 230 of 341 (67%) studied RNA-binding proteins (RBPs) interact with their own mRNAs, with a heavy enrichment among high-confidence hits and a preference for coding sequence binding. We account for different confounding variables, including physical (overexpression and proximity during translation), methodological (difference in CLIP protocols, peak callers and cell types) and statistical (treatment of null backgrounds). In particular, we demonstrate a high statistical significance of autogenous interactions by sampling null distributions of fixed-margin interaction matrices. Furthermore, we study the dependence of autogenous binding on the presence of RNA-binding motifs and structured domains in RBPs. Finally, we show that intrinsic nucleobase-amino acid affinities favor co-aligned binding between mRNA coding regions and the proteins they encode. Our results suggest a central role for autogenous interactions in RBP regulation and support the possibility of a fundamental connection between coding and binding.

RNA biology takes root in plant systems

Advances in RNA biology such as RNAi, CRISPR, and the first mRNA vaccine represent the enormous potential of RNA research to address current problems. Additionally, plants are a diverse and undeniably essential resource for life threatened by climate change, loss of arable land, and pollution. Different aspects of RNA such as its processing, modification and structure are intertwined with plant development, physiology and stress response. This report details the findings of researchers around the world during the 23rd Penn State Symposium in Plant Biology with a focus in RNA biology.

Large scale screening of CRISPR guide RNAs using an optimized high throughput robotics system

All CRISPR/CAS systems utilize CRISPR guide RNAs (crRNAs), the design of which depend on the type of CAS protein, genetic target and the environment/matrix. While machine learning approaches have recently been developed to optimize some crRNA designs, candidate crRNAs must still be screened for efficacy under relevant conditions. Here, we demonstrate a high-throughput method to screen hundreds of candidate crRNAs for activation of Cas13a collateral RNA cleavage. Entire regions of a model gene transcript (Y. pestis lcrV gene) were tiled to produce overlapping crRNA sets. We tested for possible effects that included crRNA/target sequence, size and secondary structures, and the commercial source of DNA oligomers used to generate crRNAs. Detection of a 981 nt target RNA was initially successful with 271 out of 296 tested guide RNAs, and that was improved to 287 out of 296 (97%) after protocol optimizations. For this specific example, we determined that crRNA efficacy did not strongly depend on the target region or crRNA physical properties, but was dependent on the source of DNA oligomers used for RNA preparation. Our high-throughput methods for screening crRNAs has general applicability to the optimization of Cas12 and Cas13 guide RNA designs.

Recent advances in RNA structurome

RNA structures are essential to support RNA functions and regulation in various biological processes. Recently, a range of novel technologies have been developed to decode genome-wide RNA structures and novel modes of functionality across a wide range of species. In this review, we summarize key strategies for probing the RNA structurome and discuss the pros and cons of representative technologies. In particular, these new technologies have been applied to dissect the structural landscape of the SARS-CoV-2 RNA genome. We also summarize the functionalities of RNA structures discovered in different regulatory layers-including RNA processing, transport, localization, and mRNA translation-across viruses, bacteria, animals, and plants. We review many versatile RNA structural elements in the context of different physiological and pathological processes (e.g., cell differentiation, stress response, and viral replication). Finally, we discuss future prospects for RNA structural studies to map the RNA structurome at higher resolution and at the single-molecule and single-cell level, and to decipher novel modes of RNA structures and functions for innovative applications.

The intersection between circadian and heat-responsive regulatory networks controls plant responses to increasing temperatures

Increasing temperatures impact plant biochemistry, but the effects can be highly variable. Both external and internal factors modulate how plants respond to rising temperatures. One such factor is the time of day or season the temperature increase occurs. This timing significantly affects plant responses to higher temperatures altering the signaling networks and affecting tolerance levels. Increasing overlaps between circadian signaling and high temperature responses have been identified that could explain this sensitivity to the timing of heat stress. ELF3, a circadian clock component, functions as a thermosensor. ELF3 regulates thermoresponsive hypocotyl elongation in part through its cellular localization. The temperature sensitivity of ELF3 depends on the length of a polyglutamine region, explaining how plant temperature responses vary between species. However, the intersection between the circadian system and increased temperature stress responses is pervasive and extends beyond this overlap in thermosensing. Here, we review the network responses to increased temperatures, heat stress, and the impacts on the mechanisms of gene expression from transcription to translation, highlighting the intersections between the elevated temperature and heat stress response pathways and circadian signaling, focusing on the role of ELF3 as a thermosensor.

Small and intermediate size structural RNAs in the unicellular parasite Cryptosporidium parvum as revealed by sRNA-seq and comparative genomics

Small and intermediate-size noncoding RNAs (sRNAs and is-ncRNAs) have been shown to play important regulatory roles in the development of several eukaryotic organisms. However, they have not been thoroughly explored in Cryptosporidium parvum, an obligate zoonotic protist parasite responsible for the diarrhoeal disease cryptosporidiosis. Using Illumina sequencing of a small RNA library, a systematic identification of novel small and is-ncRNAs was performed in C. parvum excysted sporozoites. A total of 79 novel is-ncRNA candidates, including antisense, intergenic and intronic is-ncRNAs, were identified, including 7 new small nucleolar RNAs (snoRNAs). Expression of select novel is-ncRNAs was confirmed by RT-PCR. Phylogenetic conservation was analysed using covariance models (CMs) in related Cryptosporidium and apicomplexan parasite genome sequences. A potential new type of small ncRNA derived from tRNA fragments was observed. Overall, a deep profiling analysis of novel is-ncRNAs in C. parvum and related species revealed structural features and conservation of these novel is-ncRNAs. Covariance models can be used to detect is-ncRNA genes in other closely related parasites. These findings provide important new sequences for additional functional characterization of novel is-ncRNAs in the protist pathogen C. parvum.

RNA-Binding Macrocyclic Peptides

Being able to effectively target RNA with potent ligands will open up a large number of potential therapeutic options. The knowledge on how to achieve this is ever expanding but an important question that remains open is what chemical matter is suitable to achieve this goal. The high flexibility of an RNA as well as its more limited chemical diversity and featureless binding sites can be difficult to target selectively but can be addressed by well-designed cyclic peptides. In this review we will provide an overview of reported cyclic peptide ligands for therapeutically relevant RNA targets and discuss the methods used to discover them. We will also provide critical insights into the properties required for potent and selective interaction and suggestions on how to assess these parameters. The use of cyclic peptides to target RNA is still in its infancy but the lessons learned from past examples can be adopted for the development of novel potent and selective ligands.

Alternative splicing modulation by G-quadruplexes

Alternative splicing is central to metazoan gene regulation, but the regulatory mechanisms are incompletely understood. Here, we show that G-quadruplex (G4) motifs are enriched ~3-fold near splice junctions. The importance of G4s in RNA is emphasised by a higher enrichment for the non-template strand. RNA-seq data from mouse and human neurons reveals an enrichment of G4s at exons that were skipped following depolarisation induced by potassium chloride. We validate the formation of stable RNA G4s for three candidate splice sites by circular dichroism spectroscopy, UV-melting and fluorescence measurements. Moreover, we find that sQTLs are enriched at G4s, and a minigene experiment provides further support for their role in promoting exon inclusion. Analysis of >1,800 high-throughput experiments reveals multiple RNA binding proteins associated with G4s. Finally, exploration of G4 motifs across eleven species shows strong enrichment at splice sites in mammals and birds, suggesting an evolutionary conserved splice regulatory mechanism.

Here the authors shows that G-quadruplexes, non-canonical DNA/RNA structures, can have a direct impact on alternative splicing and that binding of splicing regulators is affected by their presence.

The Potential Role of RNA Structure in Crop Molecular Breeding

The continually growing human population creates a concomitantly increasing demand for nutritious crops with high yields. Advances in high throughput sequencing technologies have revealed the genetic architecture of major crops. This includes extensive information enabling comprehensive genetic markers for breeding selection, new gene discoveries, and novel gene regulatory strategies for crop editing. RNA structure is an important type of genetic feature, essential for post-transcriptional regulation of gene expression. Here, we summarize recent advances in genome-wide RNA structure studies in crops and review the associated RNA structure-mediated regulation of gene expression. We also discuss the functional importance of those single nucleotide variations that induce large RNA structure disparities. Lastly, we discuss the potential role of RNA structure in crop molecular breeding.

Experimental demonstration and pan-structurome prediction of climate-associated riboSNitches in Arabidopsis

Background

Genome-wide association studies (GWAS) aim to correlate phenotypic changes with genotypic variation. Upon transcription, single nucleotide variants (SNVs) may alter mRNA structure, with potential impacts on transcript stability, macromolecular interactions, and translation. However, plant genomes have not been assessed for the presence of these structure-altering polymorphisms or “riboSNitches.”

Results

We experimentally demonstrate the presence of riboSNitches in transcripts of two Arabidopsis genes, ZINC RIBBON 3 (ZR3) and COTTON GOLGI-RELATED 3 (CGR3), which are associated with continentality and temperature variation in the natural environment. These riboSNitches are also associated with differences in the abundance of their respective transcripts, implying a role in regulating the gene's expression in adaptation to local climate conditions. We then computationally predict riboSNitches transcriptome-wide in mRNAs of 879 naturally inbred Arabidopsis accessions. We characterize correlations between SNPs/riboSNitches in these accessions and 434 climate descriptors of their local environments, suggesting a role of these variants in local adaptation. We integrate this information in CLIMtools V2.0 and provide a new web resource, T-CLIM, that reveals associations between transcript abundance variation and local environmental variation.

Conclusion

We functionally validate two plant riboSNitches and, for the first time, demonstrate riboSNitch conditionality dependent on temperature, coining the term “conditional riboSNitch.” We provide the first pan-genome-wide prediction of riboSNitches in plants. We expand our previous CLIMtools web resource with riboSNitch information and with 1868 additional Arabidopsis genomes and 269 additional climate conditions, which will greatly facilitate in silico studies of natural genetic variation, its phenotypic consequences, and its role in local adaptation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02656-4.

Probing in vivo RNA Structure With Optimized DMS-MaPseq in Rice

RNA transcripts form various secondary and tertiary structures that have a wide range of regulatory functions. Several methods have been developed to profile in vivo RNA secondary structure in prokaryotes and eukaryotes. These methods, such as dimethyl sulfate (DMS) mutational profiling with high-throughput sequencing (DMS-MaPseq), couple small chemical-mediated RNA modifications with next-generation sequencing. DMS-MaPseq, a powerful method for genome-wide and target-specific RNA secondary structure profiling, has been applied in yeast, mammals, Drosophila, and Arabidopsis thaliana, but not in crops. Here, we used DMS-MaPseq to conduct a target-specific and genome-wide profile of in vivo RNA secondary structure in rice (Oryza sativa). The DMS treatment conditions were optimized for rice leaf and root tissues. To increase the sequencing depth and coverage of low-abundance transcripts in genome-wide DMS-MaPseq, we used streptavidin-biotin depletion to reduce the abundance of highly expressed chloroplast transcripts during library construction. The resulting target-specific and genome-wide rice DMS-MaPseq data were of high quality and reproducibility. Furthermore, we used DMS-MaPseq to profile the in vivo RNA secondary structure of an OsmiR399 target region located at 5'UTR of OsPHO2, which participates in rice phosphate homeostasis. An unfolded RNA structure downstream of miRNA target site was observed in predicted in vivo RNA secondary structure, reminiscence of the TAM (Target Adjacent nucleotide Motif) involved in mRNA structure-mediated regulation in miRNA cleavage. Our study optimized DMS-MaPseq for probing in vivo RNA secondary structure in rice, facilitating the study of RNA structure-mediated regulations in crops.

UFold: fast and accurate RNA secondary structure prediction with deep learning

For many RNA molecules, the secondary structure is essential for the correct function of the RNA. Predicting RNA secondary structure from nucleotide sequences is a long-standing problem in genomics, but the prediction performance has reached a plateau over time. Traditional RNA secondary structure prediction algorithms are primarily based on thermodynamic models through free energy minimization, which imposes strong prior assumptions and is slow to run. Here, we propose a deep learning-based method, called UFold, for RNA secondary structure prediction, trained directly on annotated data and base-pairing rules. UFold proposes a novel image-like representation of RNA sequences, which can be efficiently processed by Fully Convolutional Networks (FCNs). We benchmark the performance of UFold on both within- and cross-family RNA datasets. It significantly outperforms previous methods on within-family datasets, while achieving a similar performance as the traditional methods when trained and tested on distinct RNA families. UFold is also able to predict pseudoknots accurately. Its prediction is fast with an inference time of about 160 ms per sequence up to 1500 bp in length. An online web server running UFold is available at https://ufold.ics.uci.edu. Code is available at https://github.com/uci-cbcl/UFold.

Pull-down of Biotinylated RNA and Associated Proteins

Mapping networks of RNA-protein interactions in cells is essential for understanding the inner workings of many biological processes, including RNA processing, trafficking, and translation. Current in vivo methods for studying protein-RNA interactions rely mostly on purification of poly(A) transcripts, which represent only ~2-3% of total RNAs (Figure 1). Alternate robust methods for tagging RNA molecules with an RNA aptamer (e.g., MS2-, U1A- and biotin-RNA aptamer) and capturing the RNA-protein complex by the respective aptamer-specific partner are not extensively studied. Here, we describe a protocol (Figure 2) in which a biotin-RNA aptamer, referred to as the RNA mimic of biotin (RMB), was conjugated separately to two small RNA secondary structures that contribute to trafficking and translating HAC1 mRNA in the budding yeast Saccharomyces cerevisiae. The RMB-tagged RNA was expressed in yeast cells from a constitutive promoter. The biotinylated RNA bound to proteins was pulled down from the cell lysate by streptavidin agarose beads. RNA was detected by RT-PCR (Figure 3) and associated proteins by mass spectrometry (Figure 4). Our findings show that an RNA aptamer tag to RNA molecule is an effective method to explore the functional roles of RNA-protein networks in vivo.

The cap-proximal RNA secondary structure inhibits preinitiation complex formation on HAC1 mRNA

Translation of HAC1 mRNA in the budding yeast Saccharomyces cerevisiae is derepressed when RNase Ire1 removes its intron via nonconventional cytosolic splicing in response to accumulation of unfolded proteins inside the endoplasmic reticulum. The spliced HAC1 mRNA is translated into a transcription factor that changes the cellular gene expression patterns to increase the protein folding capacity of cells. Previously, we showed that a segment of the intronic sequence interacts with the 5′-UTR of the unspliced mRNA, resulting in repression of HAC1 translation at the initiation stage. However, the exact mechanism of translational derepression is not clear. Here, we show that at least 11-base-pairing interactions between the 5′-UTR and intron (UI) are sufficient to repress HAC1 translation. We also show that overexpression of the helicase eukaryotic initiation factor 4A derepressed translation of an unspliced HAC1 mRNA containing only 11-bp interactions between the 5′-UTR and intronic sequences. In addition, our genetic screen identifies that single mutations in the UI interaction site could derepress translation of the unspliced HAC1 mRNA. Furthermore, we show that the addition of 24 RNA bases between the mRNA 5′-cap and the UI interaction site derepressed translation of the unspliced HAC1 mRNA. Together, our data provide a mechanistic explanation for why the cap-proximal UI–RNA duplex inhibits the recruitment of translating ribosomes to HAC1 mRNA, thus keeping mRNA translationally repressed.

RNA Secondary Structurome Revealed Distinct Thermoregulation in Plasmodium falciparum

The development of Plasmodium parasites, a causative agent of malaria, requests two hosts and the completion of 11 different parasite stages during development. Therefore, an efficient and fast response of parasites to various complex environmental changes, such as ambient temperature, pH, ions, and nutrients, is essential for parasite development and survival. Among many of these environmental changes, temperature is a decisive factor for parasite development and pathogenesis, including the thermoregulation of rRNA expression, gametogenesis, and parasite sequestration in cerebral malaria. However, the exact mechanism of how Plasmodium parasites rapidly respond and adapt to temperature change remains elusive. As a fundamental and pervasive regulator of gene expression, RNA structure can be a specific mechanism for fine tuning various biological processes. For example, dynamic and temperature-dependent changes in RNA secondary structures can control the expression of different gene programs, as shown by RNA thermometers. In this study, we applied the in vitro and in vivo transcriptomic-wide secondary structurome approach icSHAPE to measure parasite RNA structure changes with temperature alteration at single-nucleotide resolution for ring and trophozoite stage parasites. Among 3,000 probed structures at different temperatures, our data showed structural changes in the global transcriptome, such as S-type rRNA, HRPII gene, and the erythrocyte membrane protein family. When the temperature drops from 37°C to 26°C, most of the genes in the trophozoite stage cause significantly more changes to the RNA structure than the genes in the ring stage. A multi-omics analysis of transcriptome data from RNA-seq and RNA structure data from icSHAPE reveals that the specific RNA secondary structure plays a significant role in the regulation of transcript expression for parasites in response to temperature changes. In addition, we identified several RNA thermometers (RNATs) that responded quickly to temperature changes. The possible thermo-responsive RNAs in Plasmodium falciparum were further mapped. To this end, we identified dynamic and temperature-dependent RNA structural changes in the P. falciparum transcriptome and performed a comprehensive characterization of RNA secondary structures over the course of temperature stress in blood stage development. These findings not only contribute to a better understanding of the function of the RNA secondary structure but may also provide novel targets for efficient vaccines or drugs.

An ultra low-input method for global RNA structure probing uncovers Regnase-1-mediated regulation in macrophages

To enable diverse functions and precise regulation, an RNA sequence often folds into complex yet distinct structures in different cellular states. Probing RNA in its native environment is essential to uncovering RNA structures of biological contexts. However, current methods generally require large amounts of input RNA and are challenging for physiologically relevant use. Here, we report smartSHAPE, a new RNA structure probing method that requires very low amounts of RNA input due to the largely reduced artefact of probing signals and increased efficiency of library construction. Using smartSHAPE, we showcased the profiling of the RNA structure landscape of mouse intestinal macrophages upon inflammation, and provided evidence that RNA conformational changes regulate immune responses. These results demonstrate that smartSHAPE can greatly expand the scope of RNA structure-based investigations in practical biological systems, and also provide a research paradigm for the study of post-transcriptional regulation.

lncRNA DDGC participates in premature ovarian insufficiency through regulating RAD51 and WT1

The list of long non-coding RNAs (lncRNAs) that participate in the function of ovarian granulosa cells (GCs) is rapidly expanding, but the mechanisms through which lncRNAs regulate GC function are not yet fully understood. Here, we recognized a minimally expressed lncRNA RP4-545C24.1 (which we named DDGC) in GCs from patients with biochemical premature ovarian insufficiency (bPOI). We further explored the role of lncRNA DDGC in GC function and its contribution to the development of bPOI. Mechanistically, silencing DDGC downregulated RAD51 by competitively binding with miR-589-5p, and this resulted in significant inhibition of DNA damage repair capacity. In addition, decreased expression of DDGC promoted ubiquitin-mediated degradation of Wilms tumor 1 (WT1) protein through interactions with heat shock protein 90 (HSP90), which led to aberrant differentiation of GCs. Moreover, DDGC was able to ameliorate the etoposide-induced DNA damage and apoptosis in vivo. Taken together, these findings provide new insights into the contribution of lncRNAs in POI pathogenesis.

Thermal adaptation of mRNA secondary structure: stability versus lability

Macromolecular function commonly involves rapidly reversible alterations in three-dimensional structure (conformation). To allow these essential conformational changes, macromolecules must possess higher order structures that are appropriately balanced between rigidity and flexibility. Because of the low stabilization free energies (marginal stabilities) of macromolecule conformations, temperature changes have strong effects on conformation and, thereby, on function. As is well known for proteins, during evolution, temperature-adaptive changes in sequence foster retention of optimal marginal stability at a species' normal physiological temperatures. Here, we extend this type of analysis to messenger RNAs (mRNAs), a class of macromolecules for which the stability-lability balance has not been elucidated. We employ in silico methods to determine secondary structures and estimate changes in free energy of folding (ΔG_fold) for 25 orthologous mRNAs that encode the enzyme cytosolic malate dehydrogenase in marine mollusks with adaptation temperatures spanning an almost 60 °C range. The change in free energy that occurs during formation of the ensemble of mRNA secondary structures is significantly correlated with adaptation temperature: ΔG_fold values are all negative and their absolute values increase with adaptation temperature. A principal mechanism underlying these adaptations is a significant increase in synonymous guanine + cytosine substitutions with increasing temperature. These findings open up an avenue of exploration in molecular evolution and raise interesting questions about the interaction between temperature-adaptive changes in mRNA sequence and in the proteins they encode.

A roadmap for rRNA folding and assembly during transcription

Ribonucleoprotein (RNP) assembly typically begins during transcription when folding of the newly synthesized RNA is coupled with the recruitment of RNA-binding proteins (RBPs). Upon binding, the proteins induce structural rearrangements in the RNA that are crucial for the next steps of assembly. Focusing primarily on bacterial ribosome assembly, we discuss recent work showing that early RNA-protein interactions are more dynamic than previously supposed, and remain so, until sufficient proteins are recruited to each transcript to consolidate an entire domain of the RNP. We also review studies showing that stable assembly of an RNP competes against modification and processing of the RNA. Finally, we discuss how transcription sets the timeline for competing and cooperative RNA-RBP interactions that determine the fate of the nascent RNA. How this dance is coordinated is the focus of this review.

The Expression Level of HIV-1 Vif Is Optimized by Nucleotide Changes in the Genomic SA1D2prox Region during the Viral Adaptation Process

HIV-1 Vif plays an essential role in viral replication by antagonizing anti-viral cellular restriction factors, a family of APOBEC3 proteins. We have previously shown that naturally-occurring single-nucleotide mutations in the SA1D2prox region, which surrounds the splicing acceptor 1 and splicing donor 2 sites of the HIV-1 genome, dramatically alter the Vif expression level, resulting in variants with low or excessive Vif expression. In this study, we investigated how these HIV-1 variants with poor replication ability adapt and evolve under the pressure of APOBEC3 proteins. Adapted clones obtained through adaptation experiments exhibited an altered replication ability and Vif expression level compared to each parental clone. While various mutations were present throughout the viral genome, all replication-competent adapted clones with altered Vif expression levels were found to bear them within SA1D2prox, without exception. Indeed, the mutations identified within SA1D2prox were responsible for changes in the Vif expression levels and altered the splicing pattern. Moreover, for samples collected from HIV-1-infected patients, we showed that the nucleotide sequences of SA1D2prox can be chronologically changed and concomitantly affect the Vif expression levels. Taken together, these results demonstrated the importance of the SA1D2prox nucleotide sequence for modulating the Vif expression level during HIV-1 replication and adaptation.

Association between novel variants in BMPR1B gene and litter size in Mongolia and Ujimqin sheep breeds

Prolificacy is an important trait of animals, specifically for sheep. The Bone morphogenetic protein receptor 1B (BMPR1B) is a major gene affecting the litter size of many sheep breeds. The well-known FecB mutation (Q249R) was associated fully with the hyper prolific phenotype of Booroola Merino. However, the identification of variation in all exonic regions of BMPR1B was rare. In this study, we sequenced all exonic regions of BMPR1B gene of Mongolia sheep breed, and ten novel variants were detected by direct sequencing. Among them, the litter size of the Mongolia ewes with the CC genotype was significantly higher (0.34 additional lambs, p < .05) than those with the TT genotype of the g.29346567C>T single nucleotide polymorphism (SNP). The litter size of the Mongolia ewes with the TT genotype was significantly higher (0.19 additional lambs, p < .05 and .31 additional lambs, p < .01, respectively) than those with the GT and GG genotypes of the c.1470G>T SNP. The silent c.1470G>T mutation is predicted to increase the stability of the mRNA secondary structure through reducing minimum free energy and is predicted to change the mRNA secondary structure of BMPR1B. Our findings may give potentially useful genetic markers for increasing litter size in sheep.

Long Tracts of Guanines Drive Aggregation of RNA G-Quadruplexes in the Presence of Spermine

G-Quadruplexes (GQs) are compact, stable structures in DNA and RNA comprised of two or more tiers of quartets whose G-rich motif of tracts of two or more G's occurs commonly within genomes and transcriptomes. While thermodynamically stable in vitro, these structures remain difficult to study in vivo. One approach to understanding GQ in vivo behavior is to test whether conditions and molecules found in cells facilitate their folding. Polyamines are biogenic polycations that interact with RNA. Among common polyamines, spermine contains the highest charge and is found in eukaryotes, making it a good candidate for association with high-charge density nucleic acid structures like GQs. Using a variety of techniques, including ultraviolet-detected thermal denaturation, circular dichroism, size exclusion chromatography, and confocal microscopy, on an array of quadruplex sequence variants, we find that eukaryotic biological concentrations of spermine induce microaggregation of three-tiered G-rich sequences, but not of purely two-tiered structures, although higher spermine concentrations induce aggregation of even these. The formation of microaggregates can also be induced by addition of as little as a single G to a two-tiered structure; moreover, they form at biological temperatures, are sensitive to salt, and can form in the presence of at least some flanking sequence. Notably, GQ aggregation is not observed under prokaryotic-like conditions of no spermine and higher NaCl concentrations. The sequence, polyamine, and salt specificity of microaggregation reported herein have implications for the formation and stability of G-rich nucleic acid aggregates in vivo and for functional roles for understudied GQ sequences with only two quadruplex tiers.