The RNA Ontology Consortium: an open invitation to the RNA community

Beyond DAD: proposing a one-letter code for nucleobase-mediated molecular recognition

Nucleobase binding is a fundamental molecular recognition event central to modern biological and bioinspired supramolecular research. Underpinning this recognition is a deceptively simple hydrogen-bonding code, primarily based on the canonical nucleobases in DNA and RNA. Inspired by these biotic structures, chemists and biologists have designed abiotic hydrogen-bonding motifs that can interact with, augment, and reshape native molecular recognition, for applications ranging from genetic code expansion and nucleic acid recognition to supramolecular materials utilizing mono- and bifacial nucleobases. However, as the number of nucleobase-inspired motifs expands, the absence of a standard vocabulary to describe hydrogen bond (HB) patterns has led to a haphazard mixture of shorthand descriptors that are confusing and inconsistent. Alternative notations that specify individual HB sites (such as DAD for donor-acceptor-donor) are cumbersome for biological and supramolecular constructs that contain many such patterns. This situation creates a barrier to sharing and interpreting nucleobase-related research across sub-disciplines, hindering collaboration and innovation. In this perspective, we aim to initiate discourse on this issue by considering what would be needed to formulate a concise one-letter code for the HB patterns associated with synthetic nucleobases. We first summarize some of the issues caused by the current absence of a consistent naming scheme. Subsequently, we discuss some key considerations in designing a coherent naming system. Finally, we leverage chemical rationale and pedagogical mnemonic considerations to propose a succinct and intuitive one-letter code for supramolecular two- and three-HB motifs. We hope that this discussion will spark conversations within our interdisciplinary community, thereby facilitating collaboration and easing communication among researchers engaged in synthetic nucleobase design.

Lone Pair…π Contacts and Structure Signatures of r(UNCG) Tetraloops, Z-Turns, and Z-Steps: A WebFR3D Survey

Z-DNA and Z-RNA have long appeared as oddities to nucleic acid scientists. However, their Z-step constituents are recurrently observed in all types of nucleic acid systems including ribosomes. Z-steps are NpN steps that are isostructural to Z-DNA CpG steps. Among their structural features, Z-steps are characterized by the presence of a lone pair…π contact that involves the stacking of the ribose O4′ atom of the first nucleotide with the 3′-face of the second nucleotide. Recently, it has been documented that the CpG step of the ubiquitous r(UNCG) tetraloops is a Z-step. Accordingly, such r(UNCG) conformations were called Z-turns. It has also been recognized that an r(GAAA) tetraloop in appropriate conditions can shapeshift to an unusual Z-turn conformation embedding an ApA Z-step. In this report, we explore the multiplicity of RNA motifs based on Z-steps by using the WebFR3D tool to which we added functionalities to be able to retrieve motifs containing lone pair…π contacts. Many examples that underscore the diversity and universality of these motifs are provided as well as tutorial guidance on using WebFR3D. In addition, this study provides an extensive survey of crystallographic, cryo-EM, NMR, and molecular dynamics studies on r(UNCG) tetraloops with a critical view on how to conduct database searches and exploit their results.

UUCG RNA Tetraloop as a Formidable Force-Field Challenge for MD Simulations

Explicit solvent atomistic molecular dynamics (MD) simulations represent an established technique to study structural dynamics of RNA molecules and an important complement for diverse experimental methods. However, performance of molecular mechanical (MM) force fields (ff's) remains far from satisfactory even after decades of development, as apparent from a problematic structural description of some important RNA motifs. Actually, some of the smallest RNA molecules belong to the most challenging systems for MD simulations and, among them, the UUCG tetraloop is saliently difficult. We report a detailed analysis of UUCG MD simulations, depicting the sequence of events leading to the loss of the UUCG native state during MD simulations. The total amount of MD simulation data analyzed in this work is close to 1.3 ms. We identify molecular interactions, backbone conformations, and substates that are involved in the process. Then, we unravel specific ff deficiencies using diverse quantum mechanical/molecular mechanical (QM/MM) and QM calculations. Comparison between the MM and QM methods shows discrepancies in the description of the 5'-flanking phosphate moiety and both signature sugar-base interactions. Our work indicates that poor behavior of the UUCG tetraloop in simulations is a complex issue that cannot be attributed to one dominant and straightforwardly correctable factor. Instead, there is a concerted effect of multiple ff inaccuracies that are coupled and amplifying each other. We attempted to improve the simulation behavior by some carefully tailored interventions, but the results were still far from satisfactory, underlying the difficulties in development of accurate nucleic acid ff's.

An Ontology for Facilitating Discussion of Catalytic Strategies of RNA-Cleaving Enzymes

A predictive understanding of the mechanisms of RNA cleavage is important for the design of emerging technology built from biological and synthetic molecules that have promise for new biochemical and medicinal applications. Over the past 15 years, RNA cleavage reactions involving 2'-O-transphosphorylation have been discussed using a simplified framework introduced by Breaker that consists of four fundamental catalytic strategies (designated α, β, γ, and δ) that contribute to rate enhancement. As more detailed mechanistic data emerge, there is need for the framework to evolve and keep pace. We develop an ontology for discussion of strategies of enzymes that catalyze RNA cleavage via 2'-O-transphosphorylation that stratifies Breaker's framework into primary (1°), secondary (2°), and tertiary (3°) contributions to enable more precise interpretation of mechanism in the context of structure and bonding. Further, we point out instances where atomic-level changes give rise to changes in more than one catalytic contribution, a phenomenon we refer to as "functional blurring". We hope that this ontology will help clarify our conversations and pave the path forward toward a consensus view of these fundamental and fascinating mechanisms. The insight gained will deepen our understanding of RNA cleavage reactions catalyzed by natural protein and RNA enzymes, as well as aid in the design of new engineered DNA and synthetic enzymes.

The comparison of thesaurus and ontology

Purpose

The purpose of this paper is to investigate indexers’ evaluation on the usability of ontology vs thesaurus in representation of concepts and semantic relations. To do so, “searching” category of ASIS&T thesaurus was selected and ASIS&TOnto was built based on it.

Design/methodology/approach

The usability examination method is used in order to compare the two semantic tools. Nine indexers were recruited as participants, who were proficient in English language, had experience in using the thesaurus and all had successfully passed the course of “information representation.” They were asked to think aloud while working with the tools and to answer a semi-structured interview. The data gathering was continued until it reached its saturation point.

Findings

The results of this study revealed that the definitions and scope notes represented in indexing tools such as thesauri and ontologies have an important role in improvement of indexers’ understanding. On comparing the hierarchical relations, results show that converting the structure of hierarchical relationships of ASIS&T thesaurus can enhance the indexers understanding of them, and also enriching the associative relations of ASIS&T thesaurus can cause indexers to have a better understanding and evaluation of the presented concepts and relations.

Originality/value

This study shares our findings on the usability of ASIS&T thesaurus as a core set of vocabulary for building a “searching” domain as a prototype ontology in the area of library and information science and provides the indexers viewpoints of the two semantic tools in this area.

It's a loop world - single strands in RNA as structural and functional elements

Unpaired regions in RNA molecules - loops - are centrally involved in defining the characteristic three-dimensional (3D) architecture of RNAs and are of high interest in RNA engineering and design. Loops adopt diverse, but specific conformations stabilised by complex tertiary structural interactions that provide structural flexibility to RNA structures that would otherwise not be possible if they only consisted of the rigid A-helical shapes usually formed by canonical base pairing. By participating in sequence-non-local contacts, they furthermore contribute to stabilising the overall fold of RNA molecules. Interactions between RNAs and other nucleic acids, proteins, or small molecules are also generally mediated by RNA loop structures. Therefore, the function of an RNA molecule is generally dependent on its loops. Examples include intermolecular interactions between RNAs as part of the microRNA processing pathways, ribozymatic activity, or riboswitch-ligand interactions. Bioinformatics approaches have been successfully applied to the identification of novel RNA structural motifs including loops, local and global RNA 3D structure prediction, and structural and conformational analysis of RNAs and have contributed to a better understanding of the sequence-structure-function relationships in RNA loops.

Drawing and editing the secondary structure(s) of RNA

Secondary structure diagrams are essential, in RNA biology, to communicate functional hypotheses and summarize structural data, and communicate them visually as drafts or finalized publication-ready figures. While many tools are currently available to automate the production of such diagrams, their capacities are usually partial, making it hard for a user to decide which to use in a given context. In this chapter, we guide the reader through the steps involved in the production of expressive publication-quality illustrations featuring the RNA secondary structure. We present major existing representations and layouts, and give precise instructions to produce them using available free software, including jViz.RNA, the PseudoViewer, RILogo, R-chie, RNAplot, R2R, and VARNA. We describe the file formats and structural descriptions accepted by popular RNA visualization tools. We also provide command lines and Python scripts to ease the user's access to advanced features. Finally, we discuss and illustrate alternative approaches to visualize the secondary structure in the presence of probing data, pseudoknots, RNA-RNA interactions, and comparative data.

The Nucleic Acid Database: new features and capabilities

The Nucleic Acid Database (NDB) (http://ndbserver.rutgers.edu) is a web portal providing access to information about 3D nucleic acid structures and their complexes. In addition to primary data, the NDB contains derived geometric data, classifications of structures and motifs, standards for describing nucleic acid features, as well as tools and software for the analysis of nucleic acids. A variety of search capabilities are available, as are many different types of reports. This article describes the recent redesign of the NDB Web site with special emphasis on new RNA-derived data and annotations and their implementation and integration into the search capabilities.

The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions

Background

The practice and research of medicine generates considerable quantities of data and model resources (DMRs). Although in principle biomedical resources are re-usable, in practice few can currently be shared. In particular, the clinical communities in physiology and pharmacology research, as well as medical education, (i.e. PPME communities) are facing considerable operational and technical obstacles in sharing data and models.

Findings

We outline the efforts of the PPME communities to achieve automated semantic interoperability for clinical resource documentation in collaboration with the RICORDO project. Current community practices in resource documentation and knowledge management are overviewed. Furthermore, requirements and improvements sought by the PPME communities to current documentation practices are discussed. The RICORDO plan and effort in creating a representational framework and associated open software toolkit for the automated management of PPME metadata resources is also described.

Conclusions

RICORDO is providing the PPME community with tools to effect, share and reason over clinical resource annotations. This work is contributing to the semantic interoperability of DMRs through ontology-based annotation by (i) supporting more effective navigation and re-use of clinical DMRs, as well as (ii) sustaining interoperability operations based on the criterion of biological similarity. Operations facilitated by RICORDO will range from automated dataset matching to model merging and managing complex simulation workflows. In effect, RICORDO is contributing to community standards for resource sharing and interoperability.

Sharing and archiving nucleic acid structure mapping data

Nucleic acids are particularly amenable to structural characterization using chemical and enzymatic probes. Each individual structure mapping experiment reveals specific information about the structure and/or dynamics of the nucleic acid. Currently, there is no simple approach for making these data publically available in a standardized format. We therefore developed a standard for reporting the results of single nucleotide resolution nucleic acid structure mapping experiments, or SNRNASMs. We propose a schema for sharing nucleic acid chemical probing data that uses generic public servers for storing, retrieving, and searching the data. We have also developed a consistent nomenclature (ontology) within the Ontology of Biomedical Investigations (OBI), which provides unique identifiers (termed persistent URLs, or PURLs) for classifying the data. Links to standardized data sets shared using our proposed format along with a tutorial and links to templates can be found at http://snrnasm.bio.unc.edu.

Structural characterization of naturally occurring RNA single mismatches

RNA is known to be involved in several cellular processes; however, it is only active when it is folded into its correct 3D conformation. The folding, bending and twisting of an RNA molecule is dependent upon the multitude of canonical and non-canonical secondary structure motifs. These motifs contribute to the structural complexity of RNA but also serve important integral biological functions, such as serving as recognition and binding sites for other biomolecules or small ligands. One of the most prevalent types of RNA secondary structure motifs are single mismatches, which occur when two canonical pairs are separated by a single non-canonical pair. To determine sequence–structure relationships and to identify structural patterns, we have systematically located, annotated and compared all available occurrences of the 30 most frequently occurring single mismatch-nearest neighbor sequence combinations found in experimentally determined 3D structures of RNA-containing molecules deposited into the Protein Data Bank. Hydrogen bonding, stacking and interaction of nucleotide edges for the mismatched and nearest neighbor base pairs are described and compared, allowing for the identification of several structural patterns. Such a database and comparison will allow researchers to gain insight into the structural features of unstudied sequences and to quickly look-up studied sequences.

RKB: a Semantic Web knowledge base for RNA

Increasingly sophisticated knowledge about RNA structure and function requires an inclusive knowledge representation that facilitates the integration of independently -generated information arising from such efforts as genome sequencing projects, microarray analyses, structure determination and RNA SELEX experiments. While RNAML, an XML-based representation, has been proposed as an exchange format for a select subset of information, it lacks domain-specific semantics that are essential for answering questions that require expert knowledge. Here, we describe an RNA knowledge base (RKB) for structure-based knowledge using RDF/OWL Semantic Web technologies. RKB extends a number of ontologies and contains basic terminology for nucleic acid composition along with context/model-specific structural features such as sugar conformations, base pairings and base stackings. RKB (available at http://semanticscience.org/projects/rkb) is populated with PDB entries and MC-Annotate structural annotation. We show queries to the RKB using description logic reasoning, thus opening the door to question answering over independently-published RNA knowledge using Semantic Web technologies.

Evolution of the Sequence Ontology terms and relationships

The Sequence Ontology is an established ontology, with a large user community, for the purpose of genomic annotation. We are reforming the ontology to provide better terms and relationships to describe the features of biological sequence, for both genomic and derived sequence. The SO is working within the guidelines of the OBO Foundry to provide interoperability between SO and the other related OBO ontologies. Here, we report changes and improvements made to SO including new relationships to better define the mereological, spatial and temporal aspects of biological sequence.

Experimental and computational determination of tRNA dynamics

As the molecular representation of the genetic code, tRNA plays a central role in the translational machinery where it interacts with several proteins and other RNAs during the course of protein synthesis. These interactions exploit the dynamic flexibility of tRNA. In this minireview, we discuss the effects of modified bases, ions, and proteins on tRNA structure and dynamics and the challenges of observing its motions over the cycle of translation.

The RNA structure alignment ontology

Multiple sequence alignments are powerful tools for understanding the structures, functions, and evolutionary histories of linear biological macromolecules (DNA, RNA, and proteins), and for finding homologs in sequence databases. We address several ontological issues related to RNA sequence alignments that are informed by structure. Multiple sequence alignments are usually shown as two-dimensional (2D) matrices, with rows representing individual sequences, and columns identifying nucleotides from different sequences that correspond structurally, functionally, and/or evolutionarily. However, the requirement that sequences and structures correspond nucleotide-by-nucleotide is unrealistic and hinders representation of important biological relationships. High-throughput sequencing efforts are also rapidly making 2D alignments unmanageable because of vertical and horizontal expansion as more sequences are added. Solving the shortcomings of traditional RNA sequence alignments requires explicit annotation of the meaning of each relationship within the alignment. We introduce the notion of "correspondence," which is an equivalence relation between RNA elements in sets of sequences as the basis of an RNA alignment ontology. The purpose of this ontology is twofold: first, to enable the development of new representations of RNA data and of software tools that resolve the expansion problems with current RNA sequence alignments, and second, to facilitate the integration of sequence data with secondary and three-dimensional structural information, as well as other experimental information, to create simultaneously more accurate and more exploitable RNA alignments.

Initial implementation of a comparative data analysis ontology

Comparative analysis is used throughout biology. When entities under comparison (e.g. proteins, genomes, species) are related by descent, evolutionary theory provides a framework that, in principle, allows N-ary comparisons of entities, while controlling for non-independence due to relatedness. Powerful software tools exist for specialized applications of this approach, yet it remains under-utilized in the absence of a unifying informatics infrastructure. A key step in developing such an infrastructure is the definition of a formal ontology. The analysis of use cases and existing formalisms suggests that a significant component of evolutionary analysis involves a core problem of inferring a character history, relying on key concepts: “Operational Taxonomic Units” (OTUs), representing the entities to be compared; “character-state data” representing the observations compared among OTUs; “phylogenetic tree”, representing the historical path of evolution among the entities; and “transitions”, the inferred evolutionary changes in states of characters that account for observations. Using the Web Ontology Language (OWL), we have defined these and other fundamental concepts in a Comparative Data Analysis Ontology (CDAO). CDAO has been evaluated for its ability to represent token data sets and to support simple forms of reasoning. With further development, CDAO will provide a basis for tools (for semantic transformation, data retrieval, validation, integration, etc.) that make it easier for software developers and biomedical researchers to apply evolutionary methods of inference to diverse types of data, so as to integrate this powerful framework for reasoning into their research.

Analysis of four-way junctions in RNA structures

RNA secondary structures can be divided into helical regions composed of canonical Watson-Crick and related base pairs, as well as single-stranded regions such as hairpin loops, internal loops, and junctions. These elements function as building blocks in the design of diverse RNA molecules with various fundamental functions in the cell. To better understand the intricate architecture of three-dimensional (3D) RNAs, we analyze existing RNA four-way junctions in terms of base-pair interactions and 3D configurations. Specifically, we identify nine broad junction families according to coaxial stacking patterns and helical configurations. We find that helices within junctions tend to arrange in roughly parallel and perpendicular patterns and stabilize their conformations using common tertiary motifs such as coaxial stacking, loop-helix interaction, and helix packing interaction. Our analysis also reveals a number of highly conserved base-pair interaction patterns and novel tertiary motifs such as A-minor-coaxial stacking combinations and sarcin/ricin motif variants. Such analyses of RNA building blocks can ultimately help in the difficult task of RNA 3D structure prediction.

Frequency and isostericity of RNA base pairs

Most of the hairpin, internal and junction loops that appear single-stranded in standard RNA secondary structures form recurrent 3D motifs, where non-Watson-Crick base pairs play a central role. Non-Watson-Crick base pairs also play crucial roles in tertiary contacts in structured RNA molecules. We previously classified RNA base pairs geometrically so as to group together those base pairs that are structurally similar (isosteric) and therefore able to substitute for each other by mutation without disrupting the 3D structure. Here, we introduce a quantitative measure of base pair isostericity, the IsoDiscrepancy Index (IDI), to more accurately determine which base pair substitutions can potentially occur in conserved motifs. We extract and classify base pairs from a reduced-redundancy set of RNA 3D structures from the Protein Data Bank (PDB) and calculate centroids (exemplars) for each base combination and geometric base pair type (family). We use the exemplars and IDI values to update our online Basepair Catalog and the Isostericity Matrices (IM) for each base pair family. From the database of base pairs observed in 3D structures we derive base pair occurrence frequencies for each of the 12 geometric base pair families. In order to improve the statistics from the 3D structures, we also derive base pair occurrence frequencies from rRNA sequence alignments.

Semiautomated and rapid quantification of nucleic acid footprinting and structure mapping experiments

We have developed protocols for rapidly quantifying the band intensities from nucleic acid chemical mapping gels at single-nucleotide resolution. These protocols are implemented in the software SAFA (semi-automated footprinting analysis) that can be downloaded without charge from http://safa.stanford.edu. The protocols implemented in SAFA have five steps: (i) lane identification, (ii) gel rectification, (iii) band assignment, (iv) model fitting and (v) band-intensity normalization. SAFA enables the rapid quantitation of gel images containing thousands of discrete bands, thereby eliminating a bottleneck to the analysis of chemical mapping experiments. An experienced user of the software can quantify a gel image in approximately 20 min. Although SAFA was developed to analyze hydroxyl radical (*OH) footprints, it effectively quantifies the gel images obtained with other types of chemical mapping probes. We also present a series of tutorial movies that illustrate the best practices and different steps in the SAFA analysis as a supplement to this protocol.

MODOMICS: a database of RNA modification pathways. 2008 update

MODOMICS, a database devoted to the systems biology of RNA modification, has been subjected to substantial improvements. It provides comprehensive information on the chemical structure of modified nucleosides, pathways of their biosynthesis, sequences of RNAs containing these modifications and RNA-modifying enzymes. MODOMICS also provides cross-references to other databases and to literature. In addition to the previously available manually curated tRNA sequences from a few model organisms, we have now included additional tRNAs and rRNAs, and all RNAs with 3D structures in the Nucleic Acid Database, in which modified nucleosides are present. In total, 3460 modified bases in RNA sequences of different organisms have been annotated. New RNA-modifying enzymes have been also added. The current collection of enzymes includes mainly proteins for the model organisms Escherichia coli and Saccharomyces cerevisiae, and is currently being expanded to include proteins from other organisms, in particular Archaea and Homo sapiens. For enzymes with known structures, links are provided to the corresponding Protein Data Bank entries, while for many others homology models have been created. Many new options for database searching and querying have been included. MODOMICS can be accessed at http://genesilico.pl/modomics.

Toward predicting self-splicing and protein-facilitated splicing of group I introns

In the current era of massive discoveries of noncoding RNAs within genomes, being able to infer a function from a nucleotide sequence is of paramount interest. Although studies of individual group I introns have identified self-splicing and nonself-splicing examples, there is no overall understanding of the prevalence of self-splicing or the factors that determine it among the >2300 group I introns sequenced to date. Here, the self-splicing activities of 12 group I introns from various organisms were assayed under six reaction conditions that had been shown previously to promote RNA catalysis for different RNAs. Besides revealing that assessing self-splicing under only one condition can be misleading, this survey emphasizes that in vitro self-splicing efficiency is correlated with the GC content of the intron (>35% GC was generally conductive to self-splicing), and with the ability of the introns to form particular tertiary interactions. Addition of the Neurospora crassa CYT-18 protein activated splicing of two nonself-splicing introns, but inhibited the second step of self-splicing for two others. Together, correlations between sequence, predicted structure and splicing begin to establish rules that should facilitate our ability to predict the self-splicing activity of any group I intron from its sequence.

Riboswitches: emerging themes in RNA structure and function

Riboswitches are RNAs capable of binding cellular metabolites using a diverse array of secondary and tertiary structures to modulate gene expression. The recent determination of the three-dimensional structures of parts of six different riboswitches illuminates common features that allow riboswitches to be grouped into one of two types. Type I riboswitches, as exemplified by the purine riboswitch, are characterized by a single, localized binding pocket supported by a largely pre-established global fold. This arrangement limits ligand-induced conformational changes in the RNA to a small region. In contrast, Type II riboswitches, such as the thiamine pyrophosphate riboswitch, contain binding pockets split into at least two spatially distinct sites. As a result, binding induces both local changes to the binding pocket and global architecture. Similar organizational themes are found in other noncoding RNAs, making it possible to begin to build a hierarchical classification of RNA structure based on the spatial organization of their active sites and associated secondary structural elements.

RNA backbone: consensus all-angle conformers and modular string nomenclature (an RNA Ontology Consortium contribution)

A consensus classification and nomenclature are defined for RNA backbone structure using all of the backbone torsion angles. By a consensus of several independent analysis methods, 46 discrete conformers are identified as suitably clustered in a quality-filtered, multidimensional dihedral angle distribution. Most of these conformers represent identifiable features or roles within RNA structures. The conformers are given two-character names that reflect the seven-angle delta epsilon zeta alpha beta gamma delta combinations empirically found favorable for the sugar-to-sugar "suite" unit within which the angle correlations are strongest (e.g., 1a for A-form, 5z for the start of S-motifs). Since the half-nucleotides are specified by a number for delta epsilon zeta and a lowercase letter for alpha beta gamma delta, this modular system can also be parsed to describe traditional nucleotide units (e.g., a1) or the dinucleotides (e.g., a1a1) that are especially useful at the level of crystallographic map fitting. This nomenclature can also be written as a string with two-character suite names between the uppercase letters of the base sequence (N1aG1gN1aR1aA1cN1a for a GNRA tetraloop), facilitating bioinformatic comparisons. Cluster means, standard deviations, coordinates, and examples are made available, as well as the Suitename software that assigns suite conformer names and conformer match quality (suiteness) from atomic coordinates. The RNA Ontology Consortium will combine this new backbone system with others that define base pairs, base-stacking, and hydrogen-bond relationships to provide a full description of RNA structural motifs.

From knotted to nested RNA structures: a variety of computational methods for pseudoknot removal

Pseudoknots are abundant in RNA structures. Many computational analyses require pseudoknot-free structures, which means that some of the base pairs in the knotted structure must be disregarded to obtain a nested structure. There is a surprising diversity of methods to perform this pseudoknot removal task, but these methods are often poorly described and studies can therefore be difficult to reproduce (in part, because different procedures may be intuitively obvious to different investigators). Here we provide a variety of algorithms for pseudoknot removal, some of which can incorporate sequence or alignment information in the removal process. We demonstrate that different methods lead to different results, which might affect structure-based analyses. This work thus provides a starting point for discussion of the extent to which these different methods recapture the underlying biological reality. We provide access to reference implementations through a web interface (at http://www.ibi.vu.nl/programs/k2nwww), and the source code is available in the PyCogent project.

The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration

The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or 'ontologies'. Unfortunately, the very success of this approach has led to a proliferation of ontologies, which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium is pursuing a strategy to overcome this problem. Existing OBO ontologies, including the Gene Ontology, are undergoing coordinated reform, and new ontologies are being created on the basis of an evolving set of shared principles governing ontology development. The result is an expanding family of ontologies designed to be interoperable and logically well formed and to incorporate accurate representations of biological reality. We describe this OBO Foundry initiative and provide guidelines for those who might wish to become involved.

A comparative analysis of the triloops in all high-resolution RNA structures reveals sequence structure relationships

Despite an increasing number of experimentally determined RNA structures, the gap between the number of structures and that of RNA families is still growing. To overcome this limitation, efficient and reliable RNA modeling methodologies must be developed. In order to reach this goal, here, we show how triloop sequence-structure relationships have been inferred through a systematic analysis of all triloops found in available high-resolution structures. The structural annotation of all triloops allowed us to define discrete states of the triloop's conformational space, and therefore an explicit sequence-to-structure relation. The sequence-structure relationships inferred from this explicit relation are presented in a convenient modeling table that provides a limited set of possible three-dimensional structures given any triloop sequence. The table is indexed by the two nucleotides that form the triloop's flanking base pair, since they are shown to provide the most information about the triloop three-dimensional structures. We also report the observations in the X-ray crystallographic structures of important conformational variations, which we believe might be the result of RNA dynamic.

FR3D: finding local and composite recurrent structural motifs in RNA 3D structures

New methods are described for finding recurrent three-dimensional (3D) motifs in RNA atomic-resolution structures. Recurrent RNA 3D motifs are sets of RNA nucleotides with similar spatial arrangements. They can be local or composite. Local motifs comprise nucleotides that occur in the same hairpin or internal loop. Composite motifs comprise nucleotides belonging to three or more different RNA strand segments or molecules. We use a base-centered approach to construct efficient, yet exhaustive search procedures using geometric, symbolic, or mixed representations of RNA structure that we implement in a suite of MATLAB programs, "Find RNA 3D" (FR3D). The first modules of FR3D preprocess structure files to classify base-pair and -stacking interactions. Each base is represented geometrically by the position of its glycosidic nitrogen in 3D space and by the rotation matrix that describes its orientation with respect to a common frame. Base-pairing and base-stacking interactions are calculated from the base geometries and are represented symbolically according to the Leontis/Westhof basepairing classification, extended to include base-stacking. These data are stored and used to organize motif searches. For geometric searches, the user supplies the 3D structure of a query motif which FR3D uses to find and score geometrically similar candidate motifs, without regard to the sequential position of their nucleotides in the RNA chain or the identity of their bases. To score and rank candidate motifs, FR3D calculates a geometric discrepancy by rigidly rotating candidates to align optimally with the query motif and then comparing the relative orientations of the corresponding bases in the query and candidate motifs. Given the growing size of the RNA structure database, it is impossible to explicitly compute the discrepancy for all conceivable candidate motifs, even for motifs with less than ten nucleotides. The screening algorithm that we describe finds all candidate motifs whose geometric discrepancy with respect to the query motif falls below a user-specified cutoff discrepancy. This technique can be applied to RMSD searches. Candidate motifs identified geometrically may be further screened symbolically to identify those that contain particular basepair types or base-stacking arrangements or that conform to sequence continuity or nucleotide identity constraints. Purely symbolic searches for motifs containing user-defined sequence, continuity and interaction constraints have also been implemented. We demonstrate that FR3D finds all occurrences, both local and composite and with nucleotide substitutions, of sarcin/ricin and kink-turn motifs in the 23S and 5S ribosomal RNA 3D structures of the H. marismortui 50S ribosomal subunit and assigns the lowest discrepancy scores to bona fide examples of these motifs. The search algorithms have been optimized for speed to allow users to search the non-redundant RNA 3D structure database on a personal computer in a matter of minutes.

RNA in brain disease: no longer just "the messenger in the middle"

RNA research has made great progress in recent years. A variety of unforeseen complexities have been identified, many with relevance to human brain disease. For example, neurologic illnesses may arise because of perturbations in distinct but interrelated tiers of RNA-based genetic regulation: pre-mRNA splicing; nonsplicing RNA modifications; and mRNA translational regulation. Furthermore, there is poor correlation between mRNA levels and protein levels in mammalian cells, due partly to complicated post-transcriptional regulation by hitherto unknown noncoding RNAs. Some noncoding RNAs have been shown to be involved in human brain diseases. Diseases potentially mediated by alterations in RNA processes include tauopathies, myotonic dystrophy, Alzheimer disease, brain cancer, and many others. Here we present an overview of new research highlighting functions for RNA that far surpass the "messenger in the middle" role and that identify RNA molecules as important agents in the human brain in health and in disease states.

Informatics challenges in structured RNA

The world of regulatory RNAs is fast expanding into mainstream molecular biology as both a subject of intense mechanistic study and as a tool for functional characterization. The RNA world is one of complex structures that carry out catalysis, sense metabolites and synthesize proteins. The dynamic and structural nature of RNAs presents a whole new set of informatics challenges to the computational community. The ability to relate structure and dynamics to function will be key to understanding this complex world. I review several important classes of structured RNAs that present our community with a series of biologically novel informatics challenges. I also review available informatics tools that have been recently developed in the field.

Mutational analysis of the ribosome

The ribosome is responsible for protein synthesis, the translation of the genetic code, in all living organisms. Ribosomes are composed of RNA (ribosomal RNA) and protein (ribosomal protein). Soluble protein factors bind to the ribosome and facilitate different phases of translation. Genetic approaches have proved useful for the identification and characterization of the structural and functional roles of specific nucleotides in ribosomal RNA and of specific amino acids in ribosomal proteins and in ribosomal factors. This chapter summarizes examples of mutations identified in ribosomal RNA, ribosomal proteins, and ribosomal factors.

RNA structure: bioinformatic analysis

The range of functions ascribed to RNA molecules has grown considerably during recent years. Consequently, the analysis and comparison of RNA sequences have become recurrent tasks in molecular biology. Because the biological function of an RNA is expressed more by its folded architecture than by its sequence, original computational tools adapted to the multifaceted RNA functions have to be developed. Such tools, recently published, enable a user to solve classical problems related to RNA research: constructing 'structural' multiple alignments, inferring complete structures and structural motifs from RNA alignments, or searching structural homology in genomic databases.

Coplanar and coaxial orientations of RNA bases and helices

Electrostatic interactions, base-pairing, and especially base-stacking dominate RNA three-dimensional structures. In an A-form RNA helix, base-stacking results in nearly perfect parallel orientations of all bases in the helix. Interestingly, when an RNA structure containing multiple helices is visualized at the atomic level, it is often possible to find an orientation such that only the edges of most bases are visible. This suggests that a general aspect of higher level RNA structure is a coplanar arrangement of base-normal vectors. We have analyzed all solved RNA crystal structures to determine the degree to which RNA base-normal vectors are globally coplanar. Using a statistical test based on the Watson-Girdle distribution, we determined that 330 out of 331 known RNA structures show statistically significant (p < 0.05; false discovery rate [FDR] = 0.05) coplanar normal vector orientations. Not surprisingly, 94% of the helices in RNA show bipolar arrangements of their base-normal vectors (p < 0.05). This allows us to compute a mean axis for each helix and compare their orientations within an RNA structure. This analysis revealed that 62% (208/331) of the RNA structures exhibit statistically significant coaxial packing of helices (p < 0.05, FDR = 0.08). Further analysis reveals that the bases in hairpin loops and junctions are also generally planar. This work demonstrates coplanar base orientation and coaxial helix packing as an emergent behavior of RNA structure and may be useful as a structural modeling constraint.

MolProbity: all-atom contacts and structure validation for proteins and nucleic acids

MolProbity is a general-purpose web server offering quality validation for 3D structures of proteins, nucleic acids and complexes. It provides detailed all-atom contact analysis of any steric problems within the molecules as well as updated dihedral-angle diagnostics, and it can calculate and display the H-bond and van der Waals contacts in the interfaces between components. An integral step in the process is the addition and full optimization of all hydrogen atoms, both polar and nonpolar. New analysis functions have been added for RNA, for interfaces, and for NMR ensembles. Additionally, both the web site and major component programs have been rewritten to improve speed, convenience, clarity and integration with other resources. MolProbity results are reported in multiple forms: as overall numeric scores, as lists or charts of local problems, as downloadable PDB and graphics files, and most notably as informative, manipulable 3D kinemage graphics shown online in the KiNG viewer. This service is available free to all users at http://molprobity.biochem.duke.edu.

RNABC: forward kinematics to reduce all-atom steric clashes in RNA backbone

Although accurate details in RNA structure are of great importance for understanding RNA function, the backbone conformation is difficult to determine, and most existing RNA structures show serious steric clashes (>or= 0.4 A overlap) when hydrogen atoms are taken into account. We have developed a program called RNABC (RNA Backbone Correction) that performs local perturbations to search for alternative conformations that avoid those steric clashes or other local geometry problems. Its input is an all-atom coordinate file for an RNA crystal structure (usually from the MolProbity web service), with problem areas specified. RNABC rebuilds a suite (the unit from sugar to sugar) by anchoring the phosphorus and base positions, which are clearest in crystallographic electron density, and reconstructing the other atoms using forward kinematics. Geometric parameters are constrained within user-specified tolerance of canonical or original values, and torsion angles are constrained to ranges defined through empirical database analyses. Several optimizations reduce the time required to search the many possible conformations. The output results are clustered and presented to the user, who can choose whether to accept one of the alternative conformations. Two test evaluations show the effectiveness of RNABC, first on the S-motifs from 42 RNA structures, and second on the worst problem suites (clusters of bad clashes, or serious sugar pucker outliers) in 25 unrelated RNA structures. Among the 101 S-motifs, 88 had diagnosed problems, and RNABC produced clash-free conformations with acceptable geometry for 71 of those (about 80%). For the 154 worst problem suites, RNABC proposed alternative conformations for 72. All but 8 of those were judged acceptable after examining electron density (where available) and local conformation. Thus, even for these worst cases, nearly half the time RNABC suggested corrections suitable to initiate further crystallographic refinement. The program is available from http://kinemage.biochem.duke.edu .

The interaction networks of structured RNAs

All pairwise interactions occurring between bases which could be detected in three-dimensional structures of crystallized RNA molecules are annotated on new planar diagrams. The diagrams attempt to map the underlying complex networks of base–base interactions and, especially, they aim at conveying key relationships between helical domains: co-axial stacking, bending and all Watson–Crick as well as non-Watson–Crick base pairs. Although such wiring diagrams cannot replace full stereographic images for correct spatial understanding and representation, they reveal structural similarities as well as the conserved patterns and distances between motifs which are present within the interaction networks of folded RNAs of similar or unrelated functions. Finally, the diagrams could help devising methods for meaningfully transforming RNA structures into graphs amenable to network analysis.

The building blocks and motifs of RNA architecture

RNA motifs can be defined broadly as recurrent structural elements containing multiple intramolecular RNA-RNA interactions, as observed in atomic-resolution RNA structures. They constitute the modular building blocks of RNA architecture, which is organized hierarchically. Recent work has focused on analyzing RNA backbone conformations to identify, define and search for new instances of recurrent motifs in X-ray structures. One current view asserts that recurrent RNA strand segments with characteristic backbone configurations qualify as independent motifs. Other considerations indicate that, to characterize modular motifs, one must take into account the larger structural context of such strand segments. This follows the biologically relevant motivation, which is to identify RNA structural characteristics that are subject to sequence constraints and that thus relate RNA architectures to sequences.