Analysis and classification of RNA tertiary structures

Structural Landscape of nsp Coding Genomic Regions of SARS-CoV-2-ssRNA Genome: A Structural Genomics Approach Toward Identification of Druggable Genome, Ligand-Binding Pockets, and Structure-Based Druggability

SARS-CoV-2 has a single-stranded RNA genome (+ssRNA), and synthesizes structural and non-structural proteins (nsps). All 16 nsp are synthesized from the ORF1a, and ORF1b regions associated with different life cycle preprocesses, including replication. The regions of ORF1a synthesizes nsp1 to 11, and ORF1b synthesizes nsp12 to 16. In this paper, we have predicted the secondary structure conformations, entropy & mountain plots, RNA secondary structure in a linear fashion, and 3D structure of nsp coding genes of the SARS-CoV-2 genome. We have also analyzed the A, T, G, C, A+T, and G+C contents, GC-profiling of these genes, showing the range of the GC content from 34.23 to 48.52%. We have observed that the GC-profile value of the nsp coding genomic regions was less (about 0.375) compared to the whole genome (about 0.38). Additionally, druggable pockets were identified from the secondary structure-guided 3D structural conformations. For secondary structure generation of all the nsp coding genes (nsp 1-16), we used a recent algorithm-based tool (deep learning-based) along with the conventional algorithms (centroid and MFE-based) to develop secondary structural conformations, and we found stem-loop, multi-branch loop, pseudoknot, and the bulge structural components, etc. The 3D model shows bound and unbound forms, branched structures, duplex structures, three-way junctions, four-way junctions, etc. Finally, we identified binding pockets of nsp coding genes which will help as a fundamental resource for future researchers to develop RNA-targeted therapeutics using the druggable genome.

RNA-NRD: a non-redundant RNA structural dataset for benchmarking and functional analysis

The significance of RNA functions and their role in evolution and disease control have remarkably increased the research scope in the field of RNA science. Though the availability of RNA structure data in PBD has been growing tremendously, maintaining their quality and integrity has become the greater challenge. Since the data available in PDB are results of different independent research, they might contain redundancy. As a result, there remains a possibility of data bias for both protein and RNA chains. Quite a few studies have been conducted to remove the redundancy of protein structures by introducing high-quality representatives. However, the amount of research done to remove the redundancy of RNA structures is still very low. To remove RNA chain redundancy in PDB, we have introduced RNA-NRD, a non-redundant dataset of RNA chains based on sequence and 3D structural similarity. We compared RNA-NRD with the existing non-redundant RNA structure dataset RS-RNA and showed that it has better-formed clusters of redundant RNA chains with lower average RMSD and higher average PSI, thus improving the overall quality of the dataset.

Vernal: a tool for mining fuzzy network motifs in RNA

MOTIVATION

RNA 3D motifs are recurrent substructures, modeled as networks of base pair interactions, which are crucial for understanding structure-function relationships. The task of automatically identifying such motifs is computationally hard, and remains a key challenge in the field of RNA structural biology and network analysis. State-of-the-art methods solve special cases of the motif problem by constraining the structural variability in occurrences of a motif, and narrowing the substructure search space.

RESULTS

Here, we relax these constraints by posing the motif finding problem as a graph representation learning and clustering task. This framing takes advantage of the continuous nature of graph representations to model the flexibility and variability of RNA motifs in an efficient manner. We propose a set of node similarity functions, clustering methods and motif construction algorithms to recover flexible RNA motifs. Our tool, Vernal can be easily customized by users to desired levels of motif flexibility, abundance and size. We show that Vernal is able to retrieve and expand known classes of motifs, as well as to propose novel motifs.

AVAILABILITY AND IMPLEMENTATION

The source code, data and a webserver are available at vernal.cs.mcgill.ca. We also provide a flexible interface and a user-friendly webserver to browse and download our results.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Underestimated Aspects in Male Infertility: Epigenetics is A New Approach in Men with Obesity or Diabetes: A Review

Infertility is a complex multifactorial problem that affects about 7% of men and 15% of couples worldwide. Many molecular mechanisms involved in male infertility. Destructive effects of infertility on the next generations are not well understood. Approximately 60-75% of male infertility cases have idiopathic causes, and there is a need for additional investigations other than routine examinations. Molecular factors that surround DNA, which are mitotically stable and independently regulate genome activity of DNA sequences, are known as epigenetics. The known epigenetic mechanisms are DNA methylation, histone modifications and non-coding RNAs. Prevalence of metabolic diseases has been increased dramatically because of changes in lifestyle and the current levels of inactivity. Metabolic disorders, such<br />as obesity and diabetes, are prevalent reasons for male infertility; despite the association between metabolic diseases and male infertility, few studies have been conducted on the effects of epigenetic alterations associated with these diseases and sperm abnormalities. Diabetes can affect the reproductive system and testicular function at multiple levels;<br />however, there are very few molecular and epigenetic studies related to sperm from males with diabetes. On the other hand, obesity has similar conditions, while male obesity is linked to notable alterations in the sperm molecular architecture affecting both function and embryo quality. Therefore, in this review article, we presented new and developed technologies to study different patterns of epigenetic changes, and explained the exact mechanisms of epigenetic changes linked to metabolic diseases and their relationship with male infertility.

Plant RNA-mediated gene regulatory network

Not all transcribed RNAs are protein-coding RNAs. Many of them are non-protein-coding RNAs in diverse eukaryotes. However, some of them seem to be non-functional and are resulted from spurious transcription. A lot of non-protein-coding transcripts have a significant function in the translation process. Gene expressions depend on complex networks of diverse gene regulatory pathways. Several non-protein-coding RNAs regulate gene expression in a sequence-specific system either at the transcriptional level or post-transcriptional level. They include a significant part of the gene expression regulatory network. RNA-mediated gene regulation machinery is evolutionarily ancient. They well-evolved during the evolutionary time and are becoming much more complex than had been expected. In this review, we are trying to summarizing the current knowledge in the field of RNA-mediated gene silencing.

RR3DD: an RNA global structure-based RNA three-dimensional structural classification database

The three-dimensional (3D) structure of RNA usually plays an important role in the recognition with RNA-binding protein. Along with the discovering of RNAs, several RNA databases are developed to study the functions of RNA based on sequence, secondary structure, local 3D structural motif and global structure. Based on RNA function and structure, different RNAs are classified and stored in SCOR and DARTS, respectively. The classification of RNA structures is useful in RNA structure prediction and function annotation. However, the SCOR and DARTS are not updated any more. In this study, we present an RNA classification database RR3DD based on RNA fold with the global 3D structural similarity. The RR3DD includes 13,601 RNA chains from PDB and mmCIF format structures which are classified into 780 RNA folds. The RNA chains from PDB and mmCIF format structures are aligned and clustered into 675 and 220 RNA folds, respectively. By analysing the RNA structure in RR3DD, we find that there are 11 clusters with more than 50 members. These clusters include rRNAs, riboswitches, tRNAs and so on. By mapping RR3DD into Rfam, we found that some RNAs without annotation by Rfam can be annotated through structural alignment. For example, we analysed tRNAs and found that tRNA were successfully grouped in RR3DD for which Rfam did not classify them into one family. Finally, we provide a web interface of RR3DD offering functions of browsing RR3DD, annotating RNA 3D structure and finding templates for RNA homology modelling.

Thermostability, Tunability, and Tenacity of RNA as Rubbery Anionic Polymeric Materials in Nanotechnology and Nanomedicine-Specific Cancer Targeting with Undetectable Toxicity

RNA nanotechnology is the bottom-up self-assembly of nanometer-scale architectures, resembling LEGOs, composed mainly of RNA. The ideal building material should be (1) versatile and controllable in shape and stoichiometry, (2) spontaneously self-assemble, and (3) thermodynamically, chemically, and enzymatically stable with a long shelf life. RNA building blocks exhibit each of the above. RNA is a polynucleic acid, making it a polymer, and its negative-charge prevents nonspecific binding to negatively charged cell membranes. The thermostability makes it suitable for logic gates, resistive memory, sensor set-ups, and NEM devices. RNA can be designed and manipulated with a level of simplicity of DNA while displaying versatile structure and enzyme activity of proteins. RNA can fold into single-stranded loops or bulges to serve as mounting dovetails for intermolecular or domain interactions without external linking dowels. RNA nanoparticles display rubber- and amoeba-like properties and are stretchable and shrinkable through multiple repeats, leading to enhanced tumor targeting and fast renal excretion to reduce toxicities. It was predicted in 2014 that RNA would be the third milestone in pharmaceutical drug development. The recent approval of several RNA drugs and COVID-19 mRNA vaccines by FDA suggests that this milestone is being realized. Here, we review the unique properties of RNA nanotechnology, summarize its recent advancements, describe its distinct attributes inside or outside the body and discuss potential applications in nanotechnology, medicine, and material science.

Responsive self-assembly of tectoRNAs with loop-receptor interactions from the tetrahydrofolate (THF) riboswitch

Naturally occurring RNAs are known to exhibit a high degree of modularity, whereby specific structural modules (or motifs) can be mixed and matched to create new molecular architectures. The modular nature of RNA also affords researchers the ability to characterize individual structural elements in controlled synthetic contexts in order to gain new and critical insights into their particular structural features and overall performance. Here, we characterized the binding affinity of a unique loop–receptor interaction found in the tetrahydrofolate (THF) riboswitch using rationally designed self-assembling tectoRNAs. Our work suggests that the THF loop–receptor interaction has been fine-tuned for its particular role as a riboswitch component. We also demonstrate that the thermodynamic stability of this interaction can be modulated by the presence of folinic acid, which induces a local structural change at the level of the loop–receptor. This corroborates the existence of a THF binding site within this tertiary module and paves the way for its potential use as a THF responsive module for RNA nanotechnology and synthetic biology.

The genome sequence of 'Kurodagosun', a major carrot variety in Japan and China, reveals insights into biological research and carrot breeding

Carrot (Daucus carota L.) is one of the most economically important root vegetables in the world, providing numerous nutrients for human health. China is the largest country of carrot production in the world, and 'Kurodagosun' has been a major carrot variety in China. Carrot material used in this study was the inbred line 'DC-27', which was derived by forced selfing from 'Kurodagosun'. To understand the genetic system and plant-specific genes of 'Kurodagosun', we report the draft genome sequence of carrot 'DC-27' assembled using a combination of Roche454 and HiSeq 2000 sequencing technologies to achieve 32-fold genome coverage. A total of 31,891 predicted genes were identified. These assembled sequences provide candidate genes involved in biological processes including stress response and carotenoid biosynthesis. Genomic sequences corresponding to 371.6 Mb was less than 473 Mb, which is the estimated genome size. The availability of a draft sequence of the 'DC-27' genome advances knowledge on the biological research and breeding of carrot, as well as other Apiaceae plants. The 'DC-27' genome sequence data also provide a new resource to explore the evolution of other higher plants.

Favorable biodistribution, specific targeting and conditional endosomal escape of RNA nanoparticles in cancer therapy

The past decades have witnessed the successful transition of several nanotechnology platforms into the clinical trials. However, specific delivery of therapeutics to tumors is hindered by several barriers including cancer recognition and tissue penetration, particle heterogeneity and aggregation, and unfavorable pharmacokinetic profiles such as fast clearance and organ accumulation. With the advent of RNA nanotechnology, a series of RNA nanoparticles have been successfully constructed to overcome many of the aforementioned challenges for in vivo cancer targeting with favorable biodistribution profiles. Compared to other nanodelivery platforms, the physiochemical properties of RNA nanoparticles can be tuned with relative ease for investigating the in vivo behavior of nanoparticles upon systemic injection. The size, shape, and surface chemistry, especially hydrophobic modifications, exert significant impacts on the in vivo fate of RNA nanoparticles. Rationally designed RNA nanoparticles with defined stoichiometry and high homogeneity have been demonstrated to specifically target tumor cells while avoiding accumulation in healthy vital organs after systemic injection. RNA nanoparticles were proven to deliver therapeutics such as siRNA and anti-miRNA to block tumor growth in several animal models. Although the release of anti-miRNA from the RNA nanoparticles has achieved high efficiency of tumor regression in multiple animal models, the efficiency of endosomal escape for siRNA delivery needs further improvement. This review focuses on the advances and perspectives of this promising RNA nanotechnology platform for cancer targeting and therapy.

Advancement of the Emerging Field of RNA Nanotechnology

The field of RNA nanotechnology has advanced rapidly during the past decade. A variety of programmable RNA nanoparticles with defined shape, size, and stoichiometry have been developed for diverse applications in nanobiotechnology. The rising popularity of RNA nanoparticles is due to a number of factors: (1) removing the concern of RNA degradation in vitro and in vivo by introducing chemical modification into nucleotides without significant alteration of the RNA property in folding and self-assembly; (2) confirming the concept that RNA displays very high thermodynamic stability and is suitable for in vivo trafficking and other applications; (3) obtaining the knowledge to tune the immunogenic properties of synthetic RNA constructs for in vivo applications; (4) increased understanding of the 4D structure and intermolecular interaction of RNA molecules; (5) developing methods to control shape, size, and stoichiometry of RNA nanoparticles; (6) increasing knowledge of regulation and processing functions of RNA in cells; (7) decreasing cost of RNA production by biological and chemical synthesis; and (8) proving the concept that RNA is a safe and specific therapeutic modality for cancer and other diseases with little or no accumulation in vital organs. Other applications of RNA nanotechnology, such as adapting them to construct 2D, 3D, and 4D structures for use in tissue engineering, biosensing, resistive biomemory, and potential computer logic gate modules, have stimulated the interest of the scientific community. This review aims to outline the current state of the art of RNA nanoparticles as programmable smart complexes and offers perspectives on the promising avenues of research in this fast-growing field.

CHSalign: A Web Server That Builds upon Junction-Explorer and RNAJAG for Pairwise Alignment of RNA Secondary Structures with Coaxial Helical Stacking

RNA junctions are important structural elements of RNA molecules. They are formed when three or more helices come together in three-dimensional space. Recent studies have focused on the annotation and prediction of coaxial helical stacking (CHS) motifs within junctions. Here we exploit such predictions to develop an efficient alignment tool to handle RNA secondary structures with CHS motifs. Specifically, we build upon our Junction-Explorer software for predicting coaxial stacking and RNAJAG for modelling junction topologies as tree graphs to incorporate constrained tree matching and dynamic programming algorithms into a new method, called CHSalign, for aligning the secondary structures of RNA molecules containing CHS motifs. Thus, CHSalign is intended to be an efficient alignment tool for RNAs containing similar junctions. Experimental results based on thousands of alignments demonstrate that CHSalign can align two RNA secondary structures containing CHS motifs more accurately than other RNA secondary structure alignment tools. CHSalign yields a high score when aligning two RNA secondary structures with similar CHS motifs or helical arrangement patterns, and a low score otherwise. This new method has been implemented in a web server, and the program is also made freely available, at http://bioinformatics.njit.edu/CHSalign/.

RAG-3D: a search tool for RNA 3D substructures

To address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding.

SARA-Coffee web server, a tool for the computation of RNA sequence and structure multiple alignments

This article introduces the SARA-Coffee web server; a service allowing the online computation of 3D structure based multiple RNA sequence alignments. The server makes it possible to combine sequences with and without known 3D structures. Given a set of sequences SARA-Coffee outputs a multiple sequence alignment along with a reliability index for every sequence, column and aligned residue. SARA-Coffee combines SARA, a pairwise structural RNA aligner with the R-Coffee multiple RNA aligner in a way that has been shown to improve alignment accuracy over most sequence aligners when enough structural data is available. The server can be accessed from http://tcoffee.crg.cat/apps/tcoffee/do:saracoffee.

RASS: a web server for RNA alignment in the joint sequence-structure space

Comparison of ribonucleic acid (RNA) molecules is important for revealing their evolutionary relationships, predicting their functions and predicting their structures. Many methods have been developed for comparing RNAs using either sequence or three-dimensional (3D) structure (backbone geometry) information. Sequences and 3D structures contain non-overlapping sets of information that both determine RNA functions. When comparing RNA 3D structures, both types of information need to be taken into account. However, few methods compare RNA structures using both sequence and 3D structure information. Recently, we have developed a new method based on elastic shape analysis (ESA) that compares RNA molecules by combining both sequence and 3D structure information. ESA treats RNA structures as 3D curves with sequence information encoded on additional coordinates so that the alignment can be performed in the joint sequence-structure space. The similarity between two RNA molecules is quantified by a formal distance, geodesic distance. In this study, we implement a web server for the method, called RASS, to make it publicly available to research community. The web server is located at http://cloud.stat.fsu.edu/RASS/.

RNA Bricks--a database of RNA 3D motifs and their interactions

The RNA Bricks database (http://iimcb.genesilico.pl/rnabricks), stores information about recurrent RNA 3D motifs and their interactions, found in experimentally determined RNA structures and in RNA–protein complexes. In contrast to other similar tools (RNA 3D Motif Atlas, RNA Frabase, Rloom) RNA motifs, i.e. ‘RNA bricks’ are presented in the molecular environment, in which they were determined, including RNA, protein, metal ions, water molecules and ligands. All nucleotide residues in RNA bricks are annotated with structural quality scores that describe real-space correlation coefficients with the electron density data (if available), backbone geometry and possible steric conflicts, which can be used to identify poorly modeled residues. The database is also equipped with an algorithm for 3D motif search and comparison. The algorithm compares spatial positions of backbone atoms of the user-provided query structure and of stored RNA motifs, without relying on sequence or secondary structure information. This enables the identification of local structural similarities among evolutionarily related and unrelated RNA molecules. Besides, the search utility enables searching ‘RNA bricks’ according to sequence similarity, and makes it possible to identify motifs with modified ribonucleotide residues at specific positions.

RNA nanotechnology for computer design and in vivo computation

Molecular-scale computing has been explored since 1989 owing to the foreseeable limitation of Moore's law for silicon-based computation devices. With the potential of massive parallelism, low energy consumption and capability of working in vivo, molecular-scale computing promises a new computational paradigm. Inspired by the concepts from the electronic computer, DNA computing has realized basic Boolean functions and has progressed into multi-layered circuits. Recently, RNA nanotechnology has emerged as an alternative approach. Owing to the newly discovered thermodynamic stability of a special RNA motif (Shu et al. 2011 Nat. Nanotechnol. 6, 658-667 (doi:10.1038/nnano.2011.105)), RNA nanoparticles are emerging as another promising medium for nanodevice and nanomedicine as well as molecular-scale computing. Like DNA, RNA sequences can be designed to form desired secondary structures in a straightforward manner, but RNA is structurally more versatile and more thermodynamically stable owing to its non-canonical base-pairing, tertiary interactions and base-stacking property. A 90-nucleotide RNA can exhibit 4⁹⁰ nanostructures, and its loops and tertiary architecture can serve as a mounting dovetail that eliminates the need for external linking dowels. Its enzymatic and fluorogenic activity creates diversity in computational design. Varieties of small RNA can work cooperatively, synergistically or antagonistically to carry out computational logic circuits. The riboswitch and enzymatic ribozyme activities and its special in vivo attributes offer a great potential for in vivo computation. Unique features in transcription, termination, self-assembly, self-processing and acid resistance enable in vivo production of RNA nanoparticles that harbour various regulators for intracellular manipulation. With all these advantages, RNA computation is promising, but it is still in its infancy. Many challenges still exist. Collaborations between RNA nanotechnologists and computer scientists are necessary to advance this nascent technology.

Fabrication of pRNA nanoparticles to deliver therapeutic RNAs and bioactive compounds into tumor cells

RNA nanotechnology is a term that refers to the design, fabrication and use of nanoparticles that are mainly composed of RNAs via bottom-up self-assembly. The packaging RNA (pRNA) of the bacteriophage phi29 DNA packaging motor has been developed into a nanodelivery platform. This protocol describes the synthesis, assembly and functionalization of pRNA nanoparticles on the basis of three 'toolkits' derived from pRNA structural features: interlocking loops for hand-in-hand interactions, palindrome sequences for foot-to-foot interactions and an RNA three-way junction for branch extension. siRNAs, ribozymes, aptamers, chemical ligands, fluorophores and other functionalities can also be fused to the pRNA before the assembly of the nanoparticles, so as to ensure the production of homogeneous nanoparticles and the retention of appropriate folding and function of the incorporated modules. The resulting self-assembled multivalent pRNA nanoparticles are thermodynamically and chemically stable, and they remain intact at ultralow concentrations. Gene-silencing effects are progressively enhanced with increasing numbers of siRNAs in each pRNA nanoparticle. Systemic injection of the pRNA nanoparticles into xenograft-bearing mice has revealed strong binding to tumors without accumulation in vital organs or tissues. The pRNA-based nanodelivery scaffold paves a new way for nanotechnological application of pRNA-based nanoparticles for disease detection and treatment. The time required for completing one round of this protocol is 3-4 weeks when including in vitro functional assays, or 2-3 months when including in vivo studies.

Using tertiary structure for the computation of highly accurate multiple RNA alignments with the SARA-Coffee package

MOTIVATION

Aligning RNAs is useful to search for homologous genes, study evolutionary relationships, detect conserved regions and identify any patterns that may be of biological relevance. Poor levels of conservation among homologs, however, make it difficult to compare RNA sequences, even when considering closely evolutionary related sequences.

RESULTS

We describe SARA-Coffee, a tertiary structure-based multiple RNA aligner, which has been validated using BRAliDARTS, a new benchmark framework designed for evaluating tertiary structure-based multiple RNA aligners. We provide two methods to measure the capacity of alignments to match corresponding secondary and tertiary structure features. On this benchmark, SARA-Coffee outperforms both regular aligners and those using secondary structure information. Furthermore, we show that on sequences in which <60% of the nucleotides form base pairs, primary sequence methods usually perform better than secondary-structure aware aligners.

AVAILABILITY AND IMPLEMENTATION

The package and the datasets are available from http://www.tcoffee.org/Projects/saracoffee and http://structure.biofold.org/sara/.

SETTER: web server for RNA structure comparison

The recent discoveries of regulatory non-coding RNAs changed our view of RNA as a simple information transfer molecule. Understanding the architecture and function of active RNA molecules requires methods for comparing and analyzing their 3D structures. While structural alignment of short RNAs is achievable in a reasonable amount of time, large structures represent much bigger challenge. Here, we present the SETTER web server for the RNA structure pairwise comparison utilizing the SETTER (SEcondary sTructure-based TERtiary Structure Similarity Algorithm) algorithm. The SETTER method divides an RNA structure into the set of non-overlapping structural elements called generalized secondary structure units (GSSUs). The SETTER algorithm scales as O(n²) with the size of a GSSUs and as O(n) with the number of GSSUs in the structure. This scaling gives SETTER its high speed as the average size of the GSSU remains constant irrespective of the size of the structure. However, the favorable speed of the algorithm does not compromise its accuracy. The SETTER web server together with the stand-alone implementation of the SETTER algorithm are freely accessible at http://siret.cz/setter.

Predicting kissing interactions in microRNA-target complex and assessment of microRNA activity

MicroRNAs (miRNAs) are a class of short RNA molecules that play an important role in post-transcriptional gene regulation. Computational prediction of the miRNA target sites in mRNA is crucial for understanding the mechanism of miRNA-mRNA interactions. We here develop a new computational model that allows us to treat a variety of miRNA-mRNA kissing interactions, which have been ignored in the currently existing miRNA target prediction algorithms. By including all the different inter- and intra-molecular base pairs, this new model can predict both the structural accessibility of the target sites and the binding affinity (free energy). Applications of the model to a test set of 105 miRNA-gene systems show a notably improved success rate of 83/105. We found that although the binding affinity alone predicts the miRNA repression efficiency with a high success rate of 73/105, the structure in the seed region can significantly influence the miRNA activity. The method also allows us to efficiently search for the potent miRNA from a pool of miRNA candidates for any given gene target. Furthermore, extension of the method may enable predictions of the three-dimensional (3D) structures of miRNA/mRNA complexes.

Lost in folding space? Comparing four variants of the thermodynamic model for RNA secondary structure prediction

BACKGROUND

Many bioinformatics tools for RNA secondary structure analysis are based on a thermodynamic model of RNA folding. They predict a single, "optimal" structure by free energy minimization, they enumerate near-optimal structures, they compute base pair probabilities and dot plots, representative structures of different abstract shapes, or Boltzmann probabilities of structures and shapes. Although all programs refer to the same physical model, they implement it with considerable variation for different tasks, and little is known about the effects of heuristic assumptions and model simplifications used by the programs on the outcome of the analysis.

RESULTS

We extract four different models of the thermodynamic folding space which underlie the programs RNAFOLD, RNASHAPES, and RNASUBOPT. Their differences lie within the details of the energy model and the granularity of the folding space. We implement probabilistic shape analysis for all models, and introduce the shape probability shift as a robust measure of model similarity. Using four data sets derived from experimentally solved structures, we provide a quantitative evaluation of the model differences.

CONCLUSIONS

We find that search space granularity affects the computed shape probabilities less than the over- or underapproximation of free energy by a simplified energy model. Still, the approximations perform similar enough to implementations of the full model to justify their continued use in settings where computational constraints call for simpler algorithms. On the side, we observe that the rarely used level 2 shapes, which predict the complete arrangement of helices, multiloops, internal loops and bulges, include the "true" shape in a rather small number of predicted high probability shapes. This calls for an investigation of new strategies to extract high probability members from the (very large) level 2 shape space of an RNA sequence. We provide implementations of all four models, written in a declarative style that makes them easy to be modified. Based on our study, future work on thermodynamic RNA folding may make a choice of model based on our empirical data. It can take our implementations as a starting point for further program development.

A conditional random fields method for RNA sequence-structure relationship modeling and conformation sampling

Accurate tertiary structures are very important for the functional study of non-coding RNA molecules. However, predicting RNA tertiary structures is extremely challenging, because of a large conformation space to be explored and lack of an accurate scoring function differentiating the native structure from decoys. The fragment-based conformation sampling method (e.g. FARNA) bears shortcomings that the limited size of a fragment library makes it infeasible to represent all possible conformations well. A recent dynamic Bayesian network method, BARNACLE, overcomes the issue of fragment assembly. In addition, neither of these methods makes use of sequence information in sampling conformations. Here, we present a new probabilistic graphical model, conditional random fields (CRFs), to model RNA sequence–structure relationship, which enables us to accurately estimate the probability of an RNA conformation from sequence. Coupled with a novel tree-guided sampling scheme, our CRF model is then applied to RNA conformation sampling. Experimental results show that our CRF method can model RNA sequence–structure relationship well and sequence information is important for conformation sampling. Our method, named as TreeFolder, generates a much higher percentage of native-like decoys than FARNA and BARNACLE, although we use the same simple energy function as BARNACLE.

Contact:zywang@ttic.edu; j3xu@ttic.edu

Supplementary Information:Supplementary data are available at Bioinformatics online.

Hydration sites of unpaired RNA bases: a statistical analysis of the PDB structures

BACKGROUND

Hydration is crucial for RNA structure and function. X-ray crystallography is the most commonly used method to determine RNA structures and hydration and, therefore, statistical surveys are based on crystallographic results, the number of which is quickly increasing.

RESULTS

A statistical analysis of the water molecule distribution in high-resolution X-ray structures of unpaired RNA nucleotides showed that: different bases have the same penchant to be surrounded by water molecules; clusters of water molecules indicate possible hydration sites, which, in some cases, match those of the major and minor grooves of RNA and DNA double helices; complex hydrogen bond networks characterize the solvation of the nucleotides, resulting in a significant rigidity of the base and its surrounding water molecules. Interestingly, the hydration sites around unpaired RNA bases do not match, in general, the positions that are occupied by the second nucleotide when the base-pair is formed.

CONCLUSIONS

The hydration sites around unpaired RNA bases were found. They do not replicate the atom positions of complementary bases in the Watson-Crick pairs.

Prevalence of syn nucleobases in the active sites of functional RNAs

Biological RNAs, like their DNA counterparts, contain helical stretches, which have standard Watson-Crick base pairs in the anti conformation. Most functional RNAs also adopt geometries with far greater complexity such as bulges, loops, and multihelical junctions. Occasionally, nucleobases in these regions populate the syn conformation wherein the base resides close to or over the ribose sugar, which leads to a more compact state. The importance of the syn conformation to RNA function is largely unknown. In this study, we analyze 51 RNAs with tertiary structure, including aptamers, riboswitches, ribozymes, and ribosomal RNAs, for number, location, and properties of syn nucleobases. These RNAs represent the set of nonoverlapping, moderate- to high-resolution structures available at present. We find that syn nucleobases are much more common among purines than pyrimidines, and that they favor C2'-endo-like conformations especially among those nucleobases in the intermediate syn conformation. Strikingly, most syn nucleobases participate in tertiary stacking and base-pairing interactions: Inspection of RNA structures revealed that the majority of the syn nucleobases are in regions assigned to function, with many syn nucleobases interacting directly with a ligand or ribozyme active site. These observations suggest that judicious placement of conformationally restricted nucleotides biased into the syn conformation could enhance RNA folding and catalysis. Such changes could also be useful for locking RNAs into functionally competent folds for use in X-ray crystallography and NMR.

The emerging field of RNA nanotechnology

Like DNA, RNA can be designed and manipulated to produce a variety of different nanostructures. Moreover, RNA has a flexible structure and possesses catalytic functions that are similar to proteins. Although RNA nanotechnology resembles DNA nanotechnology in many ways, the base-pairing rules for constructing nanoparticles are different. The large variety of loops and motifs found in RNA allows it to fold into numerous complicated structures, and this diversity provides a platform for identifying viable building blocks for various applications. The thermal stability of RNA also allows the production of multivalent nanostructures with defined stoichiometry. Here we review techniques for constructing RNA nanoparticles from different building blocks, we describe the distinct attributes of RNA inside the body, and discuss potential applications of RNA nanostructures in medicine. We also offer some perspectives on the yield and cost of RNA production.

Regulatory RNAs in brain function and disorders

Regulatory RNAs are being increasingly investigated in neurons, and important roles in brain function have been revealed. Regulatory RNAs are non-protein-coding RNAs (npcRNAs) that comprise a heterogeneous group of molecules, varying in size and mechanism of action. Regulatory RNAs often exert post-transcriptional control of gene expression, resulting in gene silencing or gene expression stimulation. Here, we review evidence that regulatory RNAs are implicated in neuronal development, differentiation, and plasticity. We will also discuss npcRNA dysregulation that may be involved in pathological states of the brain such as neurodevelopmental disorders, neurodegeneration, and epilepsy.

FRASS: the web-server for RNA structural comparison

Background

The impressive increase of novel RNA structures, during the past few years, demands automated methods for structure comparison. While many algorithms handle only small motifs, few techniques, developed in recent years, (ARTS, DIAL, SARA, SARSA, and LaJolla) are available for the structural comparison of large and intact RNA molecules.

Results

The FRASS web-server represents a RNA chain with its Gauss integrals and allows one to compare structures of RNA chains and to find similar entries in a database derived from the Protein Data Bank. We observed that FRASS scores correlate well with the ARTS and LaJolla similarity scores. Moreover, the-web server can also reproduce satisfactorily the DARTS classification of RNA 3D structures and the classification of the SCOR functions that was obtained by the SARA method.

Conclusions

The FRASS web-server can be easily used to detect relationships among RNA molecules and to scan efficiently the rapidly enlarging structural databases.

Quantifying the relationship between sequence and three-dimensional structure conservation in RNA

Background

In recent years, the number of available RNA structures has rapidly grown reflecting the increased interest on RNA biology. Similarly to the studies carried out two decades ago for proteins, which gave the fundamental grounds for developing comparative protein structure prediction methods, we are now able to quantify the relationship between sequence and structure conservation in RNA.

Results

Here we introduce an all-against-all sequence- and three-dimensional (3D) structure-based comparison of a representative set of RNA structures, which have allowed us to quantitatively confirm that: (i) there is a measurable relationship between sequence and structure conservation that weakens for alignments resulting in below 60% sequence identity, (ii) evolution tends to conserve more RNA structure than sequence, and (iii) there is a twilight zone for RNA homology detection.

Discussion

The computational analysis here presented quantitatively describes the relationship between sequence and structure for RNA molecules and defines a twilight zone region for detecting RNA homology. Our work could represent the theoretical basis and limitations for future developments in comparative RNA 3D structure prediction.

iPARTS: an improved tool of pairwise alignment of RNA tertiary structures

iPARTS is an improved web server for aligning two RNA 3D structures based on a structural alphabet (SA)-based approach. In particular, we first derive a Ramachandran-like diagram of RNAs by plotting nucleotides on a 2D axis using their two pseudo-torsion angles η and θ. Next, we apply the affinity propagation clustering algorithm to this η-θ plot to obtain an SA of 23-nt conformations. We finally use this SA to transform RNA 3D structures into 1D sequences of SA letters and continue to utilize classical sequence alignment methods to compare these 1D SA-encoded sequences and determine their structural similarities. iPARTS takes as input two RNA 3D structures in the PDB format and outputs their global alignment (for determining overall structural similarity), semiglobal alignments (for detecting structural motifs or substructures), local alignments (for finding locally similar substructures) and normalized local structural alignments (for identifying more similar local substructures without non-similar internal fragments), with graphical display that allows the user to visually view, rotate and enlarge the superposition of aligned RNA 3D structures. iPARTS is now available online at http://bioalgorithm.life.nctu.edu.tw/iPARTS/.

Exploring RNA structure by integrative molecular modelling

RNA molecular modelling is adequate to rapidly tackle the structure of RNA molecules. With new structured RNAs constituting a central class of cellular regulators discovered every year, the need for swift and reliable modelling methods is more crucial than ever. The pragmatic method based on interactive all-atom molecular modelling relies on the observation that specific structural motifs are recurrently found in RNA sequences. Once identified by a combination of comparative sequence analysis and biochemical data, the motifs composing the secondary structure of a given RNA can be extruded in three dimensions (3D) and used as building blocks assembled manually during a bioinformatic interactive process. Comparing the models to the corresponding crystal structures has validated the method as being powerful to predict the RNA topology and architecture while being less accurate regarding the prediction of base-base interactions. These aspects as well as the necessary steps towards automation will be discussed.

Sequence-structure relationships in RNA loops: establishing the basis for loop homology modeling

The specific function of RNA molecules frequently resides in their seemingly unstructured loop regions. We performed a systematic analysis of RNA loops extracted from experimentally determined three-dimensional structures of RNA molecules. A comprehensive loop-structure data set was created and organized into distinct clusters based on structural and sequence similarity. We detected clear evidence of the hallmark of homology present in the sequence-structure relationships in loops. Loops differing by <25% in sequence identity fold into very similar structures. Thus, our results support the application of homology modeling for RNA loop model building. We established a threshold that may guide the sequence divergence-based selection of template structures for RNA loop homology modeling. Of all possible sequences that are, under the assumption of isosteric relationships, theoretically compatible with actual sequences observed in RNA structures, only a small fraction is contained in the Rfam database of RNA sequences and classes implying that the actual RNA loop space may consist of a limited number of unique loop structures and conserved sequences. The loop-structure data sets are made available via an online database, RLooM. RLooM also offers functionalities for the modeling of RNA loop structures in support of RNA engineering and design efforts.

New metrics for comparing and assessing discrepancies between RNA 3D structures and models

To benchmark progress made in RNA three-dimensional modeling and assess newly developed techniques, reliable and meaningful comparison metrics and associated tools are necessary. Generally, the average root-mean-square deviations (RMSDs) are quoted. However, RMSD can be misleading since errors are spread over the whole molecule and do not account for the specificity of RNA base interactions. Here, we introduce two new metrics that are particularly suitable to RNAs: the deformation index and deformation profile. The deformation index is calibrated by the interaction network fidelity, which considers base-base-stacking and base-base-pairing interactions within the target structure. The deformation profile highlights dissimilarities between structures at the nucleotide scale for both intradomain and interdomain interactions. Our results show that there is little correlation between RMSD and interaction network fidelity. The deformation profile is a tool that allows for rapid assessment of the origins of discrepancies.

SARA: a server for function annotation of RNA structures

Recent interest in non-coding RNA transcripts has resulted in a rapid increase of deposited RNA structures in the Protein Data Bank. However, a characterization and functional classification of the RNA structure and function space have only been partially addressed. Here, we introduce the SARA program for pair-wise alignment of RNA structures as a web server for structure-based RNA function assignment. The SARA server relies on the SARA program, which aligns two RNA structures based on a unit-vector root-mean-square approach. The likely accuracy of the SARA alignments is assessed by three different P-values estimating the statistical significance of the sequence, secondary structure and tertiary structure identity scores, respectively. Our benchmarks, which relied on a set of 419 RNA structures with known SCOR structural class, indicate that at a negative logarithm of mean P-value higher or equal than 2.5, SARA can assign the correct or a similar SCOR class to 81.4% and 95.3% of the benchmark set, respectively. The SARA server is freely accessible via the World Wide Web at http://sgu.bioinfo.cipf.es/services/SARA/.