Thermodynamic contribution and nearest-neighbor parameters of pseudouridine-adenosine base pairs in oligoribonucleotides

RNA modification: A contemporary review of pseudouridine (Ψ) and its role in functional plant biology

Pseudouridine (Ψ) is a modified nucleoside present in diverse RNA species, including mRNA (messenger RNA), snRNA (small nuclear RNA), rRNA (ribosomal RNA) and tRNA (transfer RNA). In plants, Ψ serves a critical function in RNA modification, supporting the stability, structural integrity, and functionality of RNA molecules. This review provides the various roles that Ψ fulfils in the modification of plant RNA biology, encompassing effects on biosynthesis pathways, regulatory mechanisms, stability, and translation efficiency. Additionally, we discuss recent advancements in the dynamic regulation of Ψ deposition in response to environmental stimuli and stressors. Elucidating Ψ's roles contributes to the comprehension of plant biology and may facilitate developments in biotechnology and crop improvement.

Functions and therapeutic applications of pseudouridylation

The success of using pseudouridine (Ψ) and its methylation derivative in mRNA vaccines against SARS-CoV-2 has sparked a renewed interest in this RNA modification, known as the 'fifth nucleotide' of RNA. In this Review, we discuss the emerging functions of pseudouridylation in gene regulation, focusing on how pseudouridine in mRNA, tRNA and ribosomal RNA (rRNA) regulates translation. We also discuss the effects of pseudouridylation on RNA secondary structure, pre-mRNA splicing, and in vitro mRNA stability. In addition to nuclear-genome-encoded RNAs, pseudouridine is also present in mitochondria-encoded rRNA, mRNA and tRNA, where it has different distributions and functions compared with their nuclear counterparts. We then discuss the therapeutic potential of programmable pseudouridylation and mRNA vaccine optimization through pseudouridylation. Lastly, we briefly describe the latest quantitative pseudouridine detection methods. We posit that pseudouridine is a highly promising modification that merits further epitranscriptomics investigation and therapeutic application.

Kinetics and dynamics of oligonucleotide hybridization

The hybridization of short nucleic acid strands is a remarkable spontaneous process that is foundational to biotechnology and nanotechnology and plays a crucial role in gene expression, editing and DNA repair. Decades of research into the mechanism of hybridization have resulted in a deep understanding of its thermodynamics, but many questions remain regarding its kinetics and dynamics. Recent advances in experiments and molecular dynamics simulations of nucleic acids are enabling more direct insight into the structural dynamics of hybridization, which can test long-standing assumptions regarding its mechanism. In this Review, we summarize the current state of knowledge of hybridization kinetics, discuss the barriers to a molecular description of hybridization dynamics, and highlight the new approaches that have begun uncovering the dynamics of hybridization and the duplex ensemble. The kinetics and dynamics of hybridization are highly sensitive to the composition of nucleic acids, and we emphasize recent discoveries and open questions on the role of nucleobase sequence and chemical modifications.

Schizosaccharomyces pombe pus1 mutants are temperature sensitive due to decay of tRNAIle(UAU) by the 5'-3' exonuclease Dhp1, primarily targeting the unspliced pre-tRNA

The pseudouridylase Pus1 catalyzes pseudouridine (Ψ) formation at multiple uridine residues in tRNAs, and in some snRNAs and mRNAs. Although Pus1 is highly conserved, and mutations are associated with human disease, little is known about eukaryotic Pus1 biology. Here, we show that Schizosaccharomyces pombe pus1Δ mutants are temperature sensitive due to decay of tRNAIle(UAU), as tRNAIle(UAU) levels are reduced, and its overexpression suppresses the defect. We show that tRNAIle(UAU) is degraded by the 5'-3' exonuclease Dhp1 (ortholog of Saccharomyces cerevisiae Rat1), as each of four spontaneous pus1Δ suppressors had dhp1 mutations and restored tRNAIle(UAU) levels, and two suppressors that also restored tRNAIle(UAU) levels had mutations in tol1 (S. cerevisiae MET22 ortholog), predicted to inhibit Dhp1. We show that Pus1 modifies U27, U34, and U36 of tRNAIle(UAU), raising the question about how these modifications prevent decay. Our results suggest that Dhp1 targets unspliced pre-tRNAIle(UAU), as a pus1Δ strain in which the only copy of tRNAIle(UAU) has no intron [tI(UAU)-iΔ] is temperature resistant and undergoes no detectable decay, and the corresponding pus1Δ tI(UAU)-WT strain accumulates unspliced pre-tRNAIle(UAU) Moreover, the predicted exon-intron structure of pre-tRNAIle(UAU) differs from the canonical bulge-helix-loop structure compatible with tRNA splicing, and a pus1Δ tI(UAU)i-var strain with intron mutations predicted to improve exon-intron structure is temperature resistant and undergoes little decay. These results suggest that decay of tRNAIle(UAU) by Dhp1 in pus1Δ strains occurs at the level of unspliced pre-tRNAIle(UAU), implying a substantial role for one or more of the Ψ residues in stabilizing the pre-tRNA structure for splicing.

RNA modifications: emerging players in the regulation of reproduction and development

The intricate world of RNA modifications, collectively termed the epitranscriptome, covers over 170 identified modifications and impacts RNA metabolism and, consequently, almost all biological processes. In this review, we focus on the regulatory roles and biological functions of a panel of dominant RNA modifications (including m 6A, m 5C, Ψ, ac 4C, m 1A, and m 7G) on three RNA types-mRNA, tRNA, and rRNA-in mammalian development, particularly in the context of reproduction as well as embryonic development. We discuss in detail how those modifications, along with their regulatory proteins, affect RNA processing, structure, localization, stability, and translation efficiency. We also highlight the associations among dysfunctions in RNA modification-related proteins, abnormal modification deposition and various diseases, emphasizing the roles of RNA modifications in critical developmental processes such as stem cell self-renewal and cell fate transition. Elucidating the molecular mechanisms by which RNA modifications influence diverse developmental processes holds promise for developing innovative strategies to manage developmental disorders. Finally, we outline several unexplored areas in the field of RNA modification that warrant further investigation.

RluA is the major mRNA pseudouridine synthase in Escherichia coli

Pseudouridine (Ψ) is an ubiquitous RNA modification, present in the tRNAs and rRNAs of species across all domains of life. Conserved pseudouridine synthases modify the mRNAs of diverse eukaryotes, but the modification has yet to be identified in bacterial mRNAs. Here, we report the discovery of pseudouridines in mRNA from E. coli. By testing the mRNA modification capacity of all 11 known pseudouridine synthases, we identify RluA as the predominant mRNA-modifying enzyme. RluA, a known tRNA and 23S rRNA pseudouridine synthase, modifies at least 31 of the 44 high-confidence sites we identified in E. coli mRNAs. Using RNA structure probing data to inform secondary structures, we show that the target sites of RluA occur in a common sequence and structural motif comprised of a ΨURAA sequence located in the loop of a short hairpin. This recognition element is shared with previously identified target sites of RluA in tRNAs and rRNA. Overall, our work identifies pseudouridine in key mRNAs and suggests the capacity of Ψ to regulate the transcripts that contain it.

Structure and sequence at an RNA template 5' end influence insertion of transgenes by an R2 retrotransposon protein

R2 non-long terminal repeat retrotransposons insert site-specifically into ribosomal RNA genes (rDNA) in a broad range of multicellular eukaryotes. R2-encoded proteins can be leveraged to mediate transgene insertion at 28S rDNA loci in cultured human cells. This strategy, precise RNA-mediated insertion of transgenes (PRINT), relies on the codelivery of an mRNA encoding R2 protein and an RNA template encoding a transgene cassette of choice. Here, we demonstrate that the PRINT RNA template 5' module, which as a complementary DNA 3' end will generate the transgene 5' junction with rDNA, influences the efficiency and mechanism of gene insertion. Iterative design and testing identified optimal 5' modules consisting of a hepatitis delta virus-like ribozyme fold with high thermodynamic stability, suggesting that RNA template degradation from its 5' end may limit transgene insertion efficiency. We also demonstrate that transgene 5' junction formation can be either precise, formed by annealing the 3' end of first-strand complementary DNA with the upstream target site, or imprecise, by end-joining, but this difference in junction formation mechanism is not a major determinant of insertion efficiency. Sequence characterization of imprecise end-joining events indicates surprisingly minimal reliance on microhomology. Our findings expand the current understanding of the role of R2 retrotransposon transcript sequence and structure, and especially the 5' ribozyme fold, for retrotransposon mobility and RNA-templated gene synthesis in cells.

Exploring the challenges of RNAi-based strategies for crop protection

RNA silencing (or RNA interference, RNAi) initiated by double-stranded RNAs is a conserved mechanism for regulating gene expression in eukaryotes. RNAi-based crop protection strategies, including host-induced gene silencing (HIGS), spray-induced gene silencing (SIGS) and microbe-induced gene silencing (MIGS), have been successfully used against various pests and pathogens. Here, we highlight the challenges surrounding dsRNA design, large-scale production of dsRNA and dsRNA delivery systems. Addressing these questions will accelerate the lab-to-field transition of RNAi-based strategies. Moreover, based on studies of exogenous dsRNA-induced RNAi inheritance in Caenorhabditis elegans, we speculate that RNAi-based strategies would confer longer-lasting protection for crops against pests or fungal pathogens.

Decoding the 'Fifth' Nucleotide: Impact of RNA Pseudouridylation on Gene Expression and Human Disease

Cellular RNAs, both coding and noncoding are adorned by > 100 chemical modifications, which impact various facets of RNA metabolism and gene expression. Very often derailments in these modifications are associated with a plethora of human diseases. One of the most oldest of such modification is pseudouridylation of RNA, wherein uridine is converted to a pseudouridine (Ψ) via an isomerization reaction. When discovered, Ψ was referred to as the 'fifth nucleotide' and is chemically distinct from uridine and any other known nucleotides. Experimental evidence accumulated over the past six decades, coupled together with the recent technological advances in pseudouridine detection, suggest the presence of pseudouridine on messenger RNA, as well as on diverse classes of non-coding RNA in human cells. RNA pseudouridylation has widespread effects on cellular RNA metabolism and gene expression, primarily via stabilizing RNA conformations and destabilizing interactions with RNA-binding proteins. However, much remains to be understood about the RNA targets and their recognition by the pseudouridylation machinery, the regulation of RNA pseudouridylation, and its crosstalk with other RNA modifications and gene regulatory processes. In this review, we summarize the mechanism and molecular machinery involved in depositing pseudouridine on target RNAs, molecular functions of RNA pseudouridylation, tools to detect pseudouridines, the role of RNA pseudouridylation in human diseases like cancer, and finally, the potential of pseudouridine to serve as a biomarker and as an attractive therapeutic target.

Non‐m6A RNA modifications in haematological malignancies

Dysregulated RNA modifications, stemming from the aberrant expression and/or malfunction of RNA modification regulators operating through various pathways, play pivotal roles in driving the progression of haematological malignancies. Among RNA modifications, N6-methyladenosine (m6A) RNA modification, the most abundant internal mRNA modification, stands out as the most extensively studied modification. This prominence underscores the crucial role of the layer of epitranscriptomic regulation in controlling haematopoietic cell fate and therefore the development of haematological malignancies. Additionally, other RNA modifications (non-m6A RNA modifications) have gained increasing attention for their essential roles in haematological malignancies. Although the roles of the m6A modification machinery in haematopoietic malignancies have been well reviewed thus far, such reviews are lacking for non-m6A RNA modifications. In this review, we mainly focus on the roles and implications of non-m6A RNA modifications, including N4-acetylcytidine, pseudouridylation, 5-methylcytosine, adenosine to inosine editing, 2'-O-methylation, N1-methyladenosine and N7-methylguanosine in haematopoietic malignancies. We summarise the regulatory enzymes and cellular functions of non-m6A RNA modifications, followed by the discussions of the recent studies on the biological roles and underlying mechanisms of non-m6A RNA modifications in haematological malignancies. We also highlight the potential of therapeutically targeting dysregulated non-m6A modifiers in blood cancer.

Exploring the role of ribosomal RNA modifications in cancer

Recent advances have highlighted the significant roles of post-transcriptional modifications in rRNA in various cancers. Evidence suggests that dysregulation of rRNA modifications acts as a common denominator in cancer development, with alterations in these modifications conferring competitive advantages to cancer cells. Specifically, rRNA modifications modulate protein synthesis and favor the specialized translation of oncogenic programs, thereby contributing to the formation of a protumorigenic proteome in cancer cells. These findings reveal a novel regulatory layer mediated by changes in the deposition of rRNA chemical modifications. Moreover, inhibition of these modifications in vitro and in preclinical studies demonstrates potential therapeutic applications. The recurrence of altered rRNA modification patterns across different types of cancer underscores their importance in cancer progression, proposing them as potential biomarkers and novel therapeutic targets. This review will highlight the latest insights into how post-transcriptional rRNA modifications contribute to cancer progression and summarize the main developments and ongoing challenges in this research area.

Pseudouridine and N1-methylpseudouridine as potent nucleotide analogues for RNA therapy and vaccine development

Modified nucleosides are integral to modern drug development, serving as crucial building blocks for creating safer, more potent, and more precisely targeted therapeutic interventions. Nucleobase modifications often confer antiviral and anti-cancer activity as monomers. When incorporated into nucleic acid oligomers, they increase stability against degradation by enzymes, enhancing the drugs' lifespan within the body. Moreover, modification strategies can mitigate potential toxic effects and reduce immunogenicity, making drugs safer and better tolerated. Particularly, N1-methylpseudouridine modification improved the efficacy of the mRNA coding for spike protein of COVID-19. This became a crucial step for developing COVID-19 vaccine applied during the 2020 pandemic. This makes N1-methylpseudouridine, and its "parent" analogue pseudouridine, potent nucleotide analogues for future RNA therapy and vaccine development. This review focuses on the structure and properties of pseudouridine and N1-methylpseudouridine. RNA has a greater structural versatility, different conformation, and chemical reactivity than DNA. Watson-Crick pairing is not strictly followed by RNA that has more unusual base pairs and base-triplets. This requires detailed structural studies and structure-activity relationship analyses for RNA, also when modifications are incorporated. Recent successes in this direction are revised in this review. We describe recent successes with using pseudouridine and N1-methylpseudouridine in mRNA drug candidates. We also highlight remaining challenges that need to be solved to develop new mRNA vaccines and therapies.

RNA oligomers at atomic resolution containing 1-methylpseudouridine, an essential building block of mRNA vaccines

All widely used mRNA vaccines against COVID-19 contain in their sequence 1-methylpseudouridine (m1Ψ) instead of uridine. In this publication, we report two high resolution crystal structures (at up to 1.01 and 1.32 Å, respectively) of one such double-stranded 12-mer RNA sequence crystallized in two crystal forms. The structures are compared with similar structures which do not contain this modification. Additionally, the X-ray structure of 1-methyl-pseudouridine itself was determined.

Research progress of RNA pseudouridine modification in nervous system

Recent advances of pseudouridine (Ψ, 5-ribosyluracil) modification highlight its crucial role as a post-transcriptional regulator in gene expression and its impact on various RNA processes. Ψ synthase (PUS), a category of RNA-modifying enzymes, orchestrates the pseudouridylation reaction. It can specifically recognize conserved sequences or structural motifs within substrates, thereby regulating the biological function of various RNA molecules accurately. Our comprehensive review underscored the close association of PUS1, PUS3, PUS7, PUS10, and dyskerin PUS1 with various nervous system disorders, including neurodevelopmental disorders, nervous system tumors, mitochondrial myopathy, lactic acidosis and sideroblastic anaemia (MLASA) syndrome, peripheral nervous system disorders, and type II myotonic dystrophy. In light of these findings, this study elucidated how Ψ strengthened RNA structures and contributed to RNA function, thereby providing valuable insights into the intricate molecular mechanisms underlying nervous system diseases. However, the detailed effects and mechanisms of PUS on neuron remain elusive. This lack of mechanistic understanding poses a substantial obstacle to the development of therapeutic approaches for various neurological disorders based on Ψ modification.

Predicting nearest neighbor free energies of modified RNA with LIE: results for pseudouridine and N1-methylpseudouridine within RNA duplexes

Pseudouridine (Ψ) and N1-methylpseudouridine (m1Ψ) are among the key modifications in the field of mRNA therapeutics and vaccine research. The accuracy of the design and development of therapeutic RNAs containing such modifications depends on the accuracy of the secondary structure prediction, which in turn depends on the nearest neighbor (NN) thermodynamic parameters for the standard and modified residues. Here, we propose a simple approach based on molecular dynamics simulations and linear interaction energy (LIE) approximation that is able to predict the NN free energy parameters for U-A, Ψ-A and m1Ψ-A pairs in reasonable agreement with the recent experimental reports. We report the NN thermodynamic parameters for different U, Ψ and m1Ψ base pairs, which might be helpful for a deeper understanding of the effect of these modifications in RNA. The predicted NN free energy parameters in this study are able to closely reproduce the folding free energies of duplexes containing internal Ψ for which the thermodynamic data were available. Additionally, we report the predicted folding free energies for the duplexes containing internal m1Ψ.

Why U matters: detection and functions of pseudouridine modifications in mRNAs

The uridine modifications pseudouridine (Ψ), dihydrouridine, and 5-methyluridine are present in eukaryotic mRNAs. Many uridine-modifying enzymes are associated with human disease, underscoring the importance of uncovering the functions of uridine modifications in mRNAs. These modified uridines have chemical properties distinct from those of canonical uridines, which impact RNA structure and RNA-protein interactions. Ψ, the most abundant of these uridine modifications, is present across (pre-)mRNAs. Recent work has shown that many Ψs are present at intermediate to high stoichiometries that are likely conducive to function and at locations that are poised to influence pre-/mRNA processing. Technological innovations and mechanistic investigations are unveiling the functions of uridine modifications in pre-mRNA splicing, translation, and mRNA stability, which are discussed in this review.

Global RNA modifications to the MALAT1 triple helix differentially affect thermostability and weaken binding to METTL16

Therapeutic mRNAs are generated using modified nucleotides, namely N1-methylpseudouridine (m1Ψ) triphosphate, so that the mRNA evades detection by the immune system. RNA modifications, even at a single-nucleotide position, perturb RNA structure, although it is not well understood how structure and function is impacted by globally modified RNAs. Therefore, we examined the metastasis-associated lung adenocarcinoma transcript 1 triple helix, a highly structured stability element that includes single-, double-, and triple-stranded RNA, globally modified with N6-methyladenosine (m6A), pseudouridine (Ψ), or m1Ψ. UV thermal denaturation assays showed that m6A destabilizes both the Hoogsteen and Watson-Crick faces of the RNA by ∼20 °C, Ψ stabilizes the Hoogsteen and Watson-Crick faces of the RNA by ∼12 °C, and m1Ψ has minimal effect on the stability of the Hoogsteen face of the RNA but increases the stability of the Watson-Crick face by ∼9 °C. Native gel-shift assays revealed that binding of the methyltransferase-like protein 16 to the metastasis-associated lung adenocarcinoma transcript 1 triple helix was weakened by at least 8-, 99-, and 23-fold, respectively, when RNA is globally modified with m6A, Ψ, or m1Ψ. These results demonstrate that a more thermostable RNA structure does not lead to tighter RNA-protein interactions, thereby highlighting the regulatory power of RNA modifications by multiple means.

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).

RNA pseudouridine modification in plants

Pseudouridine is one of the well-known chemical modifications in various RNA species. Current advances to detect pseudouridine show that the pseudouridine landscape is dynamic and affects multiple cellular processes. Although our understanding of this post-transcriptional modification mainly depends on yeast and human models, the recent findings provide strong evidence for the critical role of pseudouridine in plants. Here, we review the current knowledge of pseudouridine in plant RNAs, including its synthesis, degradation, regulatory mechanisms, and functions. Moreover, we propose future areas of research on pseudouridine modification in plants.

Modified RNAs and predictions with the ViennaRNA Package

MOTIVATION

In living organisms, many RNA molecules are modified post-transcriptionally. This turns the widely known four-letter RNA alphabet ACGU into a much larger one with currently more than 300 known distinct modified bases. The roles for the majority of modified bases remain uncertain, but many are already well-known for their ability to influence the preferred structures that an RNA may adopt. In fact, tRNAs sometimes require certain modifications to fold into their cloverleaf shaped structure. However, predicting the structure of RNAs with base modifications is still difficult due to the lack of efficient algorithms that can deal with the extended sequence alphabet, as well as missing parameter sets that account for the changes in stability induced by the modified bases.

RESULTS

We present an approach to include sparse energy parameter data for modified bases into the ViennaRNA Package. Our method does not require any changes to the underlying efficient algorithms but instead uses a set of plug-in constraints that adapt the predictions in terms of loop evaluation at runtime. These adaptations are efficient in the sense that they are only performed for loops where additional parameters are actually available for. In addition, our approach also facilitates the inclusion of more modified bases as soon as further parameters become available.

AVAILABILITY AND IMPLEMENTATION

Source code and documentation are available at https://www.tbi.univie.ac.at/RNA.

RNA folding studies inside peptide-rich droplets reveal roles of modified nucleosides at the origin of life

Compartmentalization of RNA in biopolymer-rich membraneless organelles is now understood to be pervasive and critical for the function of extant biology and has been proposed as a prebiotically plausible way to accumulate RNA. However, compartment-RNA interactions that drive encapsulation have the potential to influence RNA structure and function in compartment- and RNA sequence-dependent ways. Here, we detail next-generation sequencing (NGS) experiments performed in membraneless compartments called complex coacervates to characterize the fold of many different transfer RNAs (tRNAs) simultaneously under the potentially denaturing conditions of these compartments. Notably, we find that natural modifications favor the native fold of tRNAs in these compartments. This suggests that covalent RNA modifications could have played a critical role in metabolic processes at the origin of life.

The diverse structural modes of tRNA binding and recognition

tRNAs are short noncoding RNAs responsible for decoding mRNA codon triplets, delivering correct amino acids to the ribosome, and mediating polypeptide chain formation. Due to their key roles during translation, tRNAs have a highly conserved shape and large sets of tRNAs are present in all living organisms. Regardless of sequence variability, all tRNAs fold into a relatively rigid three-dimensional L-shaped structure. The conserved tertiary organization of canonical tRNA arises through the formation of two orthogonal helices, consisting of the acceptor and anticodon domains. Both elements fold independently to stabilize the overall structure of tRNAs through intramolecular interactions between the D- and T-arm. During tRNA maturation, different modifying enzymes posttranscriptionally attach chemical groups to specific nucleotides, which not only affect translation elongation rates but also restrict local folding processes and confer local flexibility when required. The characteristic structural features of tRNAs are also employed by various maturation factors and modification enzymes to assure the selection, recognition, and positioning of specific sites within the substrate tRNAs. The cellular functional repertoire of tRNAs continues to extend well beyond their role in translation, partly, due to the expanding pool of tRNA-derived fragments. Here, we aim to summarize the most recent developments in the field to understand how three-dimensional structure affects the canonical and noncanonical functions of tRNA.

Measuring intramolecular connectivity in long RNA molecules using two-dimensional DNA patch-probe arrays

We describe a simple method to infer intramolecular connections in a population of long RNA molecules in vitro. First we add DNA oligonucleotide "patches" that perturb the RNA connections, then we use a microarray containing a complete set of DNA oligonucleotide "probes" to record where perturbations occur. The pattern of perturbations reveals couplings between different regions of the RNA sequence, from which we infer connections as well as their prevalences in the population. We validate this patch-probe method using the 1,058-nucleotide RNA genome of satellite tobacco mosaic virus (STMV), which has previously been shown to have multiple long-range connections. Our results not only indicate long duplexes that agree with previous structures but also reveal the prevalence of competing connections. Together, these results suggest that globally-folded and locally-folded structures coexist in solution. We show that the prevalence of connections changes when pseudouridine, an important component of natural and synthetic RNA molecules, is substituted for uridine in STMV RNA.

RNA folding studies inside peptide-rich droplets reveal roles of modified nucleosides at the origin of life

Compartmentalization of RNA in biopolymer-rich membraneless organelles is now understood to be pervasive and critical for the function of extant biology and has been proposed as a prebiotically-plausible way to accumulate RNA. However, compartment-RNA interactions that drive encapsulation have the potential to influence RNA structure and function in compartment- and RNA sequence-dependent ways. Herein, we detail Next-Generation Sequencing (NGS) experiments performed for the first time in membraneless compartments called complex coacervates to characterize the fold of many different transfer RNAs (tRNAs) simultaneously under the potentially denaturing conditions of these compartments. Strikingly, we find that natural modifications favor the native fold of tRNAs in these compartments. This suggests that covalent RNA modifications could have played a critical role in metabolic processes at the origin of life.

One Sentence Summary

We demonstrate that RNA folds into native secondary and tertiary structures in protocell models and that this is favored by covalent modifications, which is critical for the origins of life.

Translation of in vitro-transcribed RNA therapeutics

In vitro transcribed, modified messenger RNAs (IVTmRNAs) have been used to vaccinate billions of individuals against the SARS-CoV-2 virus, and are currently being developed for many additional therapeutic applications. IVTmRNAs must be translated into proteins with therapeutic activity by the same cellular machinery that also translates native endogenous transcripts. However, different genesis pathways and routes of entry into target cells as well as the presence of modified nucleotides mean that the way in which IVTmRNAs engage with the translational machinery, and the efficiency with which they are being translated, differs from native mRNAs. This review summarises our current knowledge of commonalities and differences in translation between IVTmRNAs and cellular mRNAs, which is key for the development of future design strategies that can generate IVTmRNAs with improved activity in therapeutic applications.

N1-methylpseudouridine found within COVID-19 mRNA vaccines produces faithful protein products

Synthetic mRNA technology is a promising avenue for treating and preventing disease. Key to the technology is the incorporation of modified nucleotides such as N1-methylpseudouridine (m1Ψ) to decrease immunogenicity of the RNA. However, relatively few studies have addressed the effects of modified nucleotides on the decoding process. Here, we investigate the effect of m1Ψ and the related modification pseudouridine (Ψ) on translation. In a reconstituted system, we find that m1Ψ does not significantly alter decoding accuracy. More importantly, we do not detect an increase in miscoded peptides when mRNA containing m1Ψ is translated in cell culture, compared with unmodified mRNA. We also find that m1Ψ does not stabilize mismatched RNA-duplex formation and only marginally promotes errors during reverse transcription. Overall, our results suggest that m1Ψ does not significantly impact translational fidelity, a welcome sign for future RNA therapeutics.

ZayyuNet - A Unified Deep Learning Model for the Identification of Epigenetic Modifications Using Raw Genomic Sequences

Epigenetic modifications have a vital role in gene expression and are linked to cellular processes such as differentiation, development, and tumorigenesis. Thus, the availability of reliable and accurate methods for identifying and defining these changes facilitates greater insights into the regulatory mechanisms that rely on epigenetic modifications. The current experimental methods provide a genome-wide identification of epigenetic modifications; however, they are expensive and time-consuming. To date, several machine learning methods have been proposed for identifying modifications such as DNA N6-Methyladenine (6mA), RNA N6-Methyladenosine (m6A), DNA N4-methylcytosine (4mC), and RNA pseudouridine ( Ψ). However, these methods are task-specific computational tools and require different encoding representations of DNA/RNA sequences. In this study, we propose a unified deep learning model, called ZayyuNet, for the identification of various epigenetic modifications. The proposed model is based on an architecture called, SpinalNet, inspired by the human somatosensory system that can efficiently receive large inputs and achieve better performance. The proposed model has been evaluated on various epigenetic modifications such as 6mA, m6A, 4mC, and Ψ and the results achieved outperform current state-of-the-art models. A user-friendly web server has been built and made freely available at http://nsclbio.jbnu.ac.kr/tools/ZayyuNet/.

Inhaled siRNA Formulations for Respiratory Diseases: From Basic Research to Clinical Application

The development of siRNA technology has provided new opportunities for gene-specific inhibition and knockdown, as well as new ideas for the treatment of disease. Four siRNA drugs have already been approved for marketing. However, the instability of siRNA in vivo makes systemic delivery ineffective. Inhaled siRNA formulations can deliver drugs directly to the lung, showing great potential for treating respiratory diseases. The clinical applications of inhaled siRNA formulations still face challenges because effective delivery of siRNA to the lung requires overcoming the pulmonary and cellular barriers. This paper reviews the research progress for siRNA inhalation formulations for the treatment of various respiratory diseases and summarizes the chemical structural modifications and the various delivery systems for siRNA. Finally, we conclude the latest clinical application research for inhaled siRNA formulations and discuss the potential difficulty in efficient clinical application.

Nuclear magnetic resonance reveals a two hairpin equilibrium near the 3'-splice site of influenza A segment 7 mRNA that can be shifted by oligonucleotides

Influenza A kills hundreds of thousands of people globally every year and has the potential to generate more severe pandemics. Influenza A's RNA genome and transcriptome provide many potential therapeutic targets. Here, nuclear magnetic resonance (NMR) experiments suggest that one such target could be a hairpin loop of 8 nucleotides in a pseudoknot that sequesters a 3' splice site in canonical pairs until a conformational change releases it into a dynamic 2 × 2-nt internal loop. NMR experiments reveal that the hairpin loop is dynamic and able to bind oligonucleotides as short as pentamers. A 3D NMR structure of the complex contains 4 and likely 5 bp between pentamer and loop. Moreover, a hairpin sequence was discovered that mimics the equilibrium of the influenza hairpin between its structure in the pseudoknot and upon release of the splice site. Oligonucleotide binding shifts the equilibrium completely to the hairpin secondary structure required for pseudoknot folding. The results suggest this hairpin can be used to screen for compounds that stabilize the pseudoknot and potentially reduce splicing.

Data-informed reparameterization of modified RNA and the effect of explicit water models: application to pseudouridine and derivatives

Pseudouridine is one of the most abundant post-transcriptional modifications in RNA. We have previously shown that the FF99-derived parameters for pseudouridine and some of its naturally occurring derivatives in the AMBER distribution either alone or in combination with the revised γ torsion parameters (parmbsc0) failed to reproduce their conformational characteristics observed experimentally (Deb et al. in J Chem Inf Model 54:1129–1142, 2014; Deb et al. in J Comput Chem 37:1576–1588, 2016; Dutta et al. in J Chem Inf Model 60:4995–5002, 2020). However, the application of the recommended bsc0 correction did lead to an improvement in the description not only of the distribution in the γ torsional space but also of the sugar pucker distributions. In an earlier study, we examined the transferability of the revised glycosidic torsion parameters (χ_IDRP) for Ψ to its derivatives. We noticed that although these parameters in combination with the AMBER FF99-derived parameters and the revised γ torsional parameters resulted in conformational properties of these residues that were in better agreement with experimental observations, the sugar pucker distributions were still not reproduced accurately. Here we report a new set of partial atomic charges for pseudouridine, 1-methylpseudouridine, 3-methylpseudouridine and 2′-O-methylpseudouridine and a new set of glycosidic torsional parameters (χ_ND) based on chosen glycosidic torsional profiles that most closely corresponded to the NMR data for conformational propensities and studied their effect on the conformational distributions using REMD simulations at the individual nucleoside level. We have also studied the effect of the choice of water model on the conformational characteristics of these modified nucleosides. Our observations suggest that the current revised set of parameters and partial atomic charges describe the sugar pucker distributions for these residues more accurately and that the choice of a suitable water model is important for the accurate description of their conformational properties. We have further validated the revised sets of parameters by studying the effect of substitution of uridine with pseudouridine within single stranded RNA oligonucleotides on their conformational and hydration characteristics.

Secondary structure prediction for RNA sequences including N6-methyladenosine

There is increasing interest in the roles of covalently modified nucleotides in RNA. There has been, however, an inability to account for modifications in secondary structure prediction because of a lack of software and thermodynamic parameters. We report the solution for these issues for N⁶-methyladenosine (m⁶A), allowing secondary structure prediction for an alphabet of A, C, G, U, and m⁶A. The RNAstructure software now works with user-defined nucleotide alphabets of any size. We also report a set of nearest neighbor parameters for helices and loops containing m⁶A, using experiments. Interestingly, N⁶-methylation decreases folding stability for adenosines in the middle of a helix, has little effect on folding stability for adenosines at the ends of helices, and increases folding stability for unpaired adenosines stacked on a helix. We demonstrate predictions for an N⁶-methylation-activated protein recognition site from MALAT1 and human transcriptome-wide effects of N⁶-methylation on the probability of adenosine being buried in a helix.

RNA folding free energy nearest neighbor parameters were determined for sequences with the nucleotide m⁶A. The RNAstructure software package can accommodate modified nucleotides, enabling secondary structure prediction of sequences with m⁶A.

Pseudouridine synthases modify human pre-mRNA co-transcriptionally and affect pre-mRNA processing

Pseudouridine is a modified nucleotide that is prevalent in human mRNAs and is dynamically regulated. Here, we investigate when in their life cycle mRNAs become pseudouridylated to illuminate the potential regulatory functions of endogenous mRNA pseudouridylation. Using single-nucleotide resolution pseudouridine profiling on chromatin-associated RNA from human cells, we identified pseudouridines in nascent pre-mRNA at locations associated with alternatively spliced regions, enriched near splice sites, and overlapping hundreds of binding sites for RNA-binding proteins. In vitro splicing assays establish a direct effect of individual endogenous pre-mRNA pseudouridines on splicing efficiency. We validate hundreds of pre-mRNA sites as direct targets of distinct pseudouridine synthases and show that PUS1, PUS7, and RPUSD4-three pre-mRNA-modifying pseudouridine synthases with tissue-specific expression-control widespread changes in alternative pre-mRNA splicing and 3' end processing. Our results establish a vast potential for cotranscriptional pre-mRNA pseudouridylation to regulate human gene expression via alternative pre-mRNA processing.

The uridine to pseudouridine modification at the wobble position of eukaryotic isoleucine tRNA species is unlikely to induce mistranslation

Replacement of a U in an RNA duplex with a pseudouridine (Ψ), in general, stabilize the duplex because of the stronger stacking interaction, even concerning the wobble pair with G. The tRNA species specific to the AUA isoleucine codon in many eukaryotes have a Ψ at the first position of the anticodon. This tRNA^Ile would cause mistranslation if it could recognize the AUG codon through formation of a Ψ-G base pair. Here, I propose rationales for the minimal promotive effect of the U to Ψ modification on the mistranslation of the AUG codon.

A Feature Fusion Predictor for RNA Pseudouridine Sites with Particle Swarm Optimizer Based Feature Selection and Ensemble Learning Approach

RNA pseudouridine modification is particularly important in a variety of cellular biological and physiological processes. It plays a significant role in understanding RNA functions, RNA structure stabilization, translation processes, etc. To understand its functional mechanisms, it is necessary to accurately identify pseudouridine sites in RNA sequences. Although some computational methods have been proposed for the identification of pseudouridine sites, it is still a challenge to improve the identification accuracy and generalization ability. To address this challenge, a novel feature fusion predictor, named PsoEL-PseU, is proposed for the prediction of pseudouridine sites. Firstly, this study systematically and comprehensively explored different types of feature descriptors and determined six feature descriptors with various properties. To improve the feature representation ability, a binary particle swarm optimizer was used to capture the optimal feature subset for six feature descriptors. Secondly, six individual predictors were trained by using the six optimal feature subsets. Finally, to fuse the effects of all six features, six individual predictors were fused into an ensemble predictor by a parallel fusion strategy. Ten-fold cross-validation on three benchmark datasets indicated that the PsoEL-PseU predictor significantly outperformed the current state-of-the-art predictors. Additionally, the new predictor achieved better accuracy in the independent dataset evaluation-accuracy which is significantly higher than that of its existing counterparts-and the user-friendly webserver developed by the PsoEL-PseU predictor has been made freely accessible.

Identification of RNA pseudouridine sites using deep learning approaches

Pseudouridine(Ψ) is widely popular among various RNA modifications which have been confirmed to occur in rRNA, mRNA, tRNA, and nuclear/nucleolar RNA. Hence, identifying them has vital significance in academic research, drug development and gene therapies. Several laboratory techniques for Ψ identification have been introduced over the years. Although these techniques produce satisfactory results, they are costly, time-consuming and requires skilled experience. As the lengths of RNA sequences are getting longer day by day, an efficient method for identifying pseudouridine sites using computational approaches is very important. In this paper, we proposed a multi-channel convolution neural network using binary encoding. We employed k-fold cross-validation and grid search to tune the hyperparameters. We evaluated its performance in the independent datasets and found promising results. The results proved that our method can be used to identify pseudouridine sites for associated purposes. We have also implemented an easily accessible web server at http://103.99.176.239/ipseumulticnn/.

Molecular Dynamics Simulation of the Conformational Preferences of Pseudouridine Derivatives: Improving the Distribution in the Glycosidic Torsion Space

There are only four derivatives of pseudouridine (Ψ) that are known to occur naturally in RNA as post-transcriptional modifications. We have studied the conformational consequences of pseudouridylation and further modifications using replica exchange molecular dynamics simulations at the nucleoside level, and the simulated conformational preferences were compared with the available experimental (NMR) data. We found that the existing AMBER FF99-derived parameters for these nucleosides did not reproduce the observed experimental features and while the recommended bsc0 correction could be combined with these parameters leading to an improvement in the description of sugar pucker distributions, the χ_OL3 correction could not be applied to these nucleosides as such because of base isomerization. On the other hand, the revised χ torsion parameters (χ_IDRP) for Ψ developed earlier by us (Deb, I., J. Comput. Chem., 2016, 37, 1576-1588) in combination with the AMBER provided parameters and the revised γ torsion parameters generated conformational distributions, which generally were in better agreement with the experimental data. A significant shift of the distribution of base orientation toward the syn conformation was observed with our revised parameter sets compared to the large excess of anti conformation predicted by the FF99 parameters. Overall, our observations indicated that our revised set of parameters (χ_IDRP) for Ψ were also able to generate conformational distributions for all of the derivatives of Ψ in better agreement with the experimental data.

Regulation and Function of RNA Pseudouridylation in Human Cells

Recent advances in pseudouridine detection reveal a complex pseudouridine landscape that includes messenger RNA and diverse classes of noncoding RNA in human cells. The known molecular functions of pseudouridine, which include stabilizing RNA conformations and destabilizing interactions with varied RNA-binding proteins, suggest that RNA pseudouridylation could have widespread effects on RNA metabolism and gene expression. Here, we emphasize how much remains to be learned about the RNA targets of human pseudouridine synthases, their basis for recognizing distinct RNA sequences, and the mechanisms responsible for regulated RNA pseudouridylation. We also examine the roles of noncoding RNA pseudouridylation in splicing and translation and point out the potential effects of mRNA pseudouridylation on protein production, including in the context of therapeutic mRNAs.

Intrinsic Regulatory Role of RNA Structural Arrangement in Alternative Splicing Control

Alternative splicing is a highly sophisticated process, playing a significant role in posttranscriptional gene expression and underlying the diversity and complexity of organisms. Its regulation is multilayered, including an intrinsic role of RNA structural arrangement which undergoes time- and tissue-specific alterations. In this review, we describe the principles of RNA structural arrangement and briefly decipher its cis- and trans-acting cellular modulators which serve as crucial determinants of biological functionality of the RNA structure. Subsequently, we engage in a discussion about the RNA structure-mediated mechanisms of alternative splicing regulation. On one hand, the impairment of formation of optimal RNA structures may have critical consequences for the splicing outcome and further contribute to understanding the pathomechanism of severe disorders. On the other hand, the structural aspects of RNA became significant features taken into consideration in the endeavor of finding potential therapeutic treatments. Both aspects have been addressed by us emphasizing the importance of ongoing studies in both fields.

iPseU-Layer: Identifying RNA Pseudouridine Sites Using Layered Ensemble Model

Pseudouridine represents one of the most prevalent post-transcriptional RNA modifications. The identification of pseudouridine sites is an essential step toward understanding RNA functions, RNA structure stabilization, translation process, and RNA stability; however, high-throughput experimental techniques remain expensive and time-consuming in lab explorations and biochemical processes. Thus, how to develop an efficient pseudouridine site identification method based on machine learning is very important both in academic research and drug development. Motived by this, we present an effective layered ensemble model designated as iPseU-Layer for identification of RNA pseudouridine sites. The proposed iPseU-Layer approach is essentially based on three different machine learning layers including: feature selection layer, feature extraction and fusion layer, and prediction layer. The feature selection layer reduces the dimensionality, which can be regarded as a data pre-processing stage. The feature extraction and fusion layer utilizes an ensemble method which is implemented through various machine learning algorithms to generate some outputs. The prediction layer applies classic random forest to identify the final results. Furthermore, we systematically conduct the validation experiments using cross-validation tests and independent test with the current state-of-the-art models. The proposed iPseU-Layer provides a promising predictive performance in terms of sensitivity, specificity, accuracy and Matthews correlation coefficient. Collectively, these findings indicate that the framework of iPseU-Layer is a feasible and effective strategy for the prediction of RNA pseudouridine sites.

Is There Any Sequence Feature in the RNA Pseudouridine Modification Prediction Problem?

Pseudouridine (Ψ) is the most abundant RNA modification and has been found in many kinds of RNAs, including snRNA, rRNA, tRNA, mRNA, and snoRNA. Thus, Ψ sites play a significant role in basic research and drug development. Although some experimental techniques have been developed to identify Ψ sites, they are expensive and time consuming, especially in the post-genomic era with the explosive growth of known RNA sequences. Thus, highly accurate computational methods are urgently required to quickly detect the Ψ sites on uncharacterized RNA sequences. Several predictors have been proposed using multifarious features, but their evaluated performances are still unsatisfactory. In this study, we first identified Ψ sites for H. sapiens, S. cerevisiae, and M. musculus using the sequence features from the bi-profile Bayes (BPB) method based on the random forest (RF) and support vector machine (SVM) algorithms, where the performances were evaluated using 5-fold cross-validation and independent tests. It was found that the SVM-based accuracies were 3.55% and 5.09% lower than the iPseU-CUU predictor for the H_990 and S_628 datasets, respectively. Almost the same-level results were obtained for M_994 and an independent H_200 dataset, even showing a 5.0% improvement for S_200. Then, three different kinds of features, including basic Kmer, general parallel correlation pseudo-dinucleotide composition (PC-PseDNC-General), and nucleotide chemical property (NCP) and nucleotide density (ND) from the iRNA-PseU method, were combined with BPB to show their comprehensive performances, where the effective features are selected by the max-relevance-max-distance (MRMD) method. The best evaluated accuracies of the combined features for the S_628 and M_994 datasets were achieved at 70.54% and 72.45%, which were 2.39% and 0.65% higher than iPseU-CUU. For the S_200 dataset, it was also improved 8% from 69% to 77%. However, there was no obvious improvement for H. sapiens, which was evaluated as approximately 63.23% and 72.0% for the H_990 and H_200 datasets, respectively. The overall performances for Ψ identification using BPB features as well as the combined features were not obviously improved. Although some kinds of feature extraction methods based on the RNA sequence information have been applied to construct the predictors in previous studies, the corresponding accuracies are generally in the range of 60%-70%. Thus, researchers need to reconsider whether there is any sequence feature in the RNA Ψ modification prediction problem.

Stability prediction of canonical and non-canonical structures of nucleic acids in various molecular environments and cells

This review provides the biophysicochemical background and recent advances in stability prediction of canonical and non-canonical structures of nucleic acids in various molecular environments and cells.

iPseU-NCP: Identifying RNA pseudouridine sites using random forest and NCP-encoded features

Background

Pseudouridine modification is most commonly found among various kinds of RNA modification occurred in both prokaryotes and eukaryotes. This biochemical event has been proved to occur in multiple types of RNAs, including rRNA, mRNA, tRNA, and nuclear/nucleolar RNA. Hence, gaining a holistic understanding of pseudouridine modification can contribute to the development of drug discovery and gene therapies. Although some laboratory techniques have come up with moderately good outcomes in pseudouridine identification, they are costly and required skilled work experience. We propose iPseU-NCP – an efficient computational framework to predict pseudouridine sites using the Random Forest (RF) algorithm combined with nucleotide chemical properties (NCP) generated from RNA sequences. The benchmark dataset collected from Chen et al. (2016) was used to develop iPseU-NCP and fairly compare its performances with other methods.

Results

Under the same experimental settings, comparing with three state-of-the-art methods including iPseU-CNN, PseUI, and iRNA-PseU, the Matthew’s correlation coefficient (MCC) of our model increased by about 20.0%, 55.0%, and 109.0% when tested on the H. sapiens (H_200) dataset and by about 6.5%, 35.0%, and 150.0% when tested on the S. cerevisiae (S_200) dataset, respectively. This significant growth in MCC is very important since it ensures the stability and performance of our model. With those two independent test datasets, our model also presented higher accuracy with a success rate boosted by 7.0%, 13.0%, and 20.0% and 2.0%, 9.5%, and 25.0% when compared to iPseU-CNN, PseUI, and iRNA-PseU, respectively. For majority of other evaluation metrics, iPseU-NCP demonstrated superior performance as well.

Conclusions

iPseU-NCP combining the RF and NPC-encoded features showed better performances than other existing state-of-the-art methods in the identification of pseudouridine sites. This also shows an optimistic view in addressing biological issues related to human diseases.

mRNA structure regulates protein expression through changes in functional half-life

Despite widespread recognition that RNA is inherently structured, the interplay between local and global mRNA secondary structure (particularly in the coding region) and overall protein expression has not been thoroughly explored. Our work uses 2 approaches to disentangle the regulatory roles of mRNA primary sequence and secondary structure: global substitution with modified nucleotides and computational sequence design. By fitting detailed kinetic expression data to mathematical models, we show that secondary structure can increase mRNA half-life independent of codon usage. These findings have significant implications for both translational regulation of endogenous mRNAs and the emerging field of mRNA therapeutics.

Messenger RNAs (mRNAs) encode information in both their primary sequence and their higher order structure. The independent contributions of factors like codon usage and secondary structure to regulating protein expression are difficult to establish as they are often highly correlated in endogenous sequences. Here, we used 2 approaches, global inclusion of modified nucleotides and rational sequence design of exogenously delivered constructs, to understand the role of mRNA secondary structure independent from codon usage. Unexpectedly, highly expressed mRNAs contained a highly structured coding sequence (CDS). Modified nucleotides that stabilize mRNA secondary structure enabled high expression across a wide variety of primary sequences. Using a set of eGFP mRNAs with independently altered codon usage and CDS structure, we find that the structure of the CDS regulates protein expression through changes in functional mRNA half-life (i.e., mRNA being actively translated). This work highlights an underappreciated role of mRNA secondary structure in the regulation of mRNA stability.

Computational and NMR studies of RNA duplexes with an internal pseudouridine-adenosine base pair

Pseudouridine (Ψ) is the most common chemical modification present in RNA. In general, Ψ increases the thermodynamic stability of RNA. However, the degree of stabilization depends on the sequence and structural context. To explain experimentally observed sequence dependence of the effect of Ψ on the thermodynamic stability of RNA duplexes, we investigated the structure, dynamics and hydration of RNA duplexes with an internal Ψ-A base pair in different nearest-neighbor sequence contexts. The structures of two RNA duplexes containing 5′-GΨC/3′-CAG and 5′-CΨG/3′-GAC motifs were determined using NMR spectroscopy. To gain insight into the effect of Ψ on duplex dynamics and hydration, we performed molecular dynamics (MD) simulations of RNA duplexes with 5′-GΨC/3′-CAG, 5′-CΨG/3′-GAC, 5′-AΨU/3′-UAA and 5′-UΨA/3′-AAU motifs and their unmodified counterparts. Our results showed a subtle impact from Ψ modification on the structure and dynamics of the RNA duplexes studied. The MD simulations confirmed the change in hydration pattern when U is replaced with Ψ. Quantum chemical calculations showed that the replacement of U with Ψ affected the intrinsic stacking energies at the base pair steps depending on the sequence context. The calculated intrinsic stacking energies help to explain the experimentally observed sequence dependent changes in the duplex stability from Ψ modification.

Validation of the nearest-neighbor model for Watson-Crick self-complementary DNA duplexes in molecular crowding condition

Recent advancement in nucleic acid techniques inside cells demands the knowledge of the stability of nucleic acid structures in molecular crowding. The nearest-neighbor model has been successfully used to predict thermodynamic parameters for the formation of nucleic acid duplexes, with significant accuracy in a dilute solution. However, knowledge about the applicability of the model in molecular crowding is still limited. To determine and predict the stabilities of DNA duplexes in a cell-like crowded environment, we systematically investigated the validity of the nearest-neighbor model for Watson–Crick self-complementary DNA duplexes in molecular crowding. The thermodynamic parameters for the duplex formation were measured in the presence of 40 wt% poly(ethylene glycol)200 for different self-complementary DNA oligonucleotides consisting of identical nearest-neighbors in a physiological buffer containing 0.1 M NaCl. The thermodynamic parameters as well as the melting temperatures (T_m) obtained from the UV melting studies revealed similar values for the oligonucleotides having identical nearest-neighbors, suggesting the validity of the nearest-neighbor model in the crowding condition. Linear relationships between the measured ΔG°₃₇ and T_m in crowding condition and those predicted in dilute solutions allowed us to predict ΔG°₃₇, T_m and nearest-neighbor parameters in molecular crowding using existing parameters in the dilute condition, which provides useful information about the thermostability of the self-complementary DNA duplexes in molecular crowding.

Estimating Energy Parameters for RNA Secondary Structure Predictions Using Both Experimental and Computational Data

Computational RNA secondary structure prediction depends on a large number of nearest-neighbor free-energy parameters, including 10 parameters for Watson-Crick stacked base pairs that were estimated from experimental measurements of the free energies of 90 RNA duplexes. These experimental data are provided by time-consuming and cost-intensive experiments. In contrast, various modified nucleotides in RNAs, which would affect not only their structures but also functions, have been found, and rapid determination of energy parameters for a such modified nucleotides is needed. To reduce the high cost of determining energy parameters, we propose a novel method to estimate energy parameters from both experimental and computational data, where the computational data are provided by a recently developed molecular dynamics simulation protocol. We evaluate our method for Watson-Crick stacked base pairs, and show that parameters estimated from 10 experimental data items and 10 computational data items can predict RNA secondary structures with accuracy comparable to that using conventional parameters. The results indicate that the combination of experimental free-energy measurements and molecular dynamics simulations is capable of estimating the thermodynamic properties of RNA secondary structures at lower cost.

iRNA-m2G: Identifying N2-methylguanosine Sites Based on Sequence-Derived Information

RNA N²-methylguanosine (m2G) is one kind of posttranscriptional modification and plays crucial roles in the control and stabilization of tRNA. However, our knowledge about the biological functions of m2G is still limited. The key step of revealing its new function is to recognize the m2G sites in the transcriptome. Since there is no effective method for detecting m2G sites, it is desirable to develop new methods to identify m2G sites. In this study, a computational predictor called iRNA-m2G was proposed to identify m2G sites in eukaryotic transcriptomes. In iRNA-m2G, the RNA sequences were encoded by using nucleotide chemical property and accumulated nucleotide frequency. iRNA-m2G was not only validated by the rigorous jackknife test on the benchmark dataset but also examined by performing cross-species validations. In addition, iRNA-m2G was also tested on an independent dataset. It was found that the accuracies obtained by iRNA-m2G were all quite promising in these tests, indicating that the proposed method could become a powerful tool for identifying m2G sites. Finally, a user-friendly web server for iRNA-m2G is freely accessible at http://lin-group.cn/server/iRNA-m2G.php.

iPseU-CNN: Identifying RNA Pseudouridine Sites Using Convolutional Neural Networks

Pseudouridine is the most prevalent RNA modification and has been found in both eukaryotes and prokaryotes. Currently, pseudouridine has been demonstrated in several kinds of RNAs, such as small nuclear RNA, rRNA, tRNA, mRNA, and small nucleolar RNA. Therefore, its significance to academic research and drug development is understandable. Through biochemical experiments, the pseudouridine site identification has produced good outcomes, but these lab exploratory methods and biochemical processes are expensive and time consuming. Therefore, it is important to introduce efficient methods for identification of pseudouridine sites. In this study, an intelligent method for pseudouridine sites using the deep-learning approach was developed. The proposed prediction model is called iPseU-CNN (identifying pseudouridine by convolutional neural networks). The existing methods used handcrafted features and machine-learning approaches to identify pseudouridine sites. However, the proposed predictor extracts the features of the pseudouridine sites automatically using a convolution neural network model. The iPseU-CNN model yields better outcomes than the current state-of-the-art models in all evaluation parameters. It is thus highly projected that the iPseU-CNN predictor will become a helpful tool for academic research on pseudouridine site prediction of RNA, as well as in drug discovery.