Robust and generic RNA modeling using inferred constraints: a structure for the hepatitis C virus IRES pseudoknot domain

SHAPE Directed Discovery of New Functions in Large RNAs

RNA lies upstream of nearly all biology and functions as the central conduit of information exchange in all cells. RNA molecules encode information both in their primary sequences and in complex structures that form when an RNA folds back on itself. From the time of discovery of mRNA in the late 1950s until quite recently, we had only a rudimentary understanding of RNA structure across vast regions of most messenger and noncoding RNAs. This deficit is now rapidly being addressed, especially by selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistry, mutational profiling (MaP), and closely related platform technologies that, collectively, create chemical microscopes for RNA. These technologies make it possible to interrogate RNA structure, quantitatively, at nucleotide resolution, and at large scales, for entire mRNAs, noncoding RNAs, and viral RNA genomes. By applying comprehensive structure probing to diverse problems, we and others are showing that control of biological function mediated by RNA structure is ubiquitous across prokaryotic and eukaryotic organisms.Work over the past decade using SHAPE-based analyses has clarified key principles. First, the method of RNA structure probing matters. SHAPE-MaP, with its direct and one-step readout that probes nearly every nucleotide by reaction at the 2'-hydroxyl, gives a more detailed and accurate readout than alternatives. Second, comprehensive chemical probing is essential. Focusing on fragments of large RNAs or using meta-gene or statistical analyses to compensate for sparse data sets misses critical features and often yields structure models with poor predictive power. Finally, every RNA has its own internal structural personality. There are myriad ways in which RNA structure modulates sequence accessibility, protein binding, translation, splice-site choice, phase separation, and other fundamental biological processes. In essentially every instance where we have applied rigorous and quantitative SHAPE technologies to study RNA structure-function interrelationships, new insights regarding biological regulatory mechanisms have emerged. RNA elements with more complex higher-order structures appear more likely to contain high-information-content clefts and pockets that bind small molecules, broadly informing a vigorous field of RNA-targeted drug discovery.The broad implications of this collective work are twofold. First, it is long past time to abandon depiction of large RNAs as simple noodle-like or gently flowing molecules. Instead, we need to emphasize that nearly all RNAs are punctuated with distinctive internal structures, a subset of which modulate function in profound ways. Second, structure probing should be an integral component of any effort that seeks to understand the functional nexuses and biological roles of large RNAs.

Structures and Functions of the 3' Untranslated Regions of Positive-Sense Single-Stranded RNA Viruses Infecting Humans and Animals

The 3′ untranslated region (3′ UTR) of positive-sense single-stranded RNA [ssRNA(+)] viruses is highly structured. Multiple elements in the region interact with other nucleotides and proteins of viral and cellular origin to regulate various aspects of the virus life cycle such as replication, translation, and the host-cell response. This review attempts to summarize the primary and higher order structures identified in the 3′UTR of ssRNA(+) viruses and their functional roles.

Standing your ground to exoribonucleases: Function of Flavivirus long non-coding RNAs

Members of the Flaviviridae (e.g., Dengue virus, West Nile virus, and Hepatitis C virus) contain a positive-sense RNA genome that encodes a large polyprotein. It is now also clear most if not all of these viruses also produce an abundant subgenomic long non-coding RNA. These non-coding RNAs, which are called subgenomic flavivirus RNAs (sfRNAs) or Xrn1-resistant RNAs (xrRNAs), are stable decay intermediates generated from the viral genomic RNA through the stalling of the cellular exoribonuclease Xrn1 at highly structured regions. Several functions of these flavivirus long non-coding RNAs have been revealed in recent years. The generation of these sfRNAs/xrRNAs from viral transcripts results in the repression of Xrn1 and the dysregulation of cellular mRNA stability. The abundant sfRNAs also serve directly as a decoy for important cellular protein regulators of the interferon and RNA interference antiviral pathways. Thus the generation of long non-coding RNAs from flaviviruses, hepaciviruses and pestiviruses likely disrupts aspects of innate immunity and may directly contribute to viral replication, cytopathology and pathogenesis.

Progress and Current Challenges in Modeling Large RNAs

Recent breakthroughs in next-generation sequencing technologies have led to the discovery of several classes of non-coding RNAs (ncRNAs). It is now apparent that RNA molecules are not only just carriers of genetic information but also key players in many cellular processes. While there has been a rapid increase in the number of ncRNA sequences deposited in various databases over the past decade, the biological functions of these ncRNAs are largely not well understood. Similar to proteins, RNA molecules carry out a function by forming specific three-dimensional structures. Understanding the function of a particular RNA therefore requires a detailed knowledge of its structure. However, determining experimental structures of RNA is extremely challenging. In fact, RNA-only structures represent just 1% of the total structures deposited in the PDB. Thus, computational methods that predict three-dimensional RNA structures are in high demand. Computational models can provide valuable insights into structure-function relationships in ncRNAs and can aid in the development of functional hypotheses and experimental designs. In recent years, a set of diverse RNA structure prediction tools have become available, which differ in computational time, input data and accuracy. This review discusses the recent progress and challenges in RNA structure prediction methods.

Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction

Despite the biological importance of non-coding RNA, their structural characterization remains challenging. Making use of the rapidly growing sequence databases, we analyze nucleotide coevolution across homologous sequences via Direct-Coupling Analysis to detect nucleotide-nucleotide contacts. For a representative set of riboswitches, we show that the results of Direct-Coupling Analysis in combination with a generalized Nussinov algorithm systematically improve the results of RNA secondary structure prediction beyond traditional covariance approaches based on mutual information. Even more importantly, we show that the results of Direct-Coupling Analysis are enriched in tertiary structure contacts. By integrating these predictions into molecular modeling tools, systematically improved tertiary structure predictions can be obtained, as compared to using secondary structure information alone.

iFoldRNA v2: folding RNA with constraints

A key to understanding RNA function is to uncover its complex 3D structure. Experimental methods used for determining RNA 3D structures are technologically challenging and laborious, which makes the development of computational prediction methods of substantial interest. Previously, we developed the iFoldRNA server that allows accurate prediction of short (<50 nt) tertiary RNA structures starting from primary sequences. Here, we present a new version of the iFoldRNA server that permits the prediction of tertiary structure of RNAs as long as a few hundred nucleotides. This substantial increase in the server capacity is achieved by utilization of experimental information such as base-pairing and hydroxyl-radical probing. We demonstrate a significant benefit provided by integration of experimental data and computational methods.

AVAILABILITY AND IMPLEMENTATION

http://ifoldrna.dokhlab.org

CONTACT

dokh@unc.eu.

Messenger RNAs bearing tRNA-like features exemplified by interferon alfa 5 mRNA

The purpose of this work was to ascertain whether liver mRNA species share common structural features with hepatitis C virus (HCV) mRNA that allow them to support the RNase-P (pre-tRNA/processing enzyme) cleavage reaction in vitro. The presence of RNase-P competitive elements in the liver mRNA population was determined by means of biochemical techniques, and a set of sensitive mRNA species were identified through microarray screening. Cleavage specificity and substrate length requirement of around 200 nts, were determined for three mRNA species. One of these cleavage sites was found in interferon-alpha 5 (IFNA5) mRNA between specific base positions and with the characteristic RNase-P chemistry of cleavage. It was mapped within a cloverleaf-like structure revealed by a comparative structural analysis based on several direct enzymes and chemical probing methods of three RNA fragments of increasing size, and subsequently contrasted against site-directed mutants. The core region was coincident with the reported signal for the cytoplasmic accumulation region (CAR) in IFNAs. Striking similarities with the tRNA-like element of the antagonist HCV mRNA were found. In general, this study provides a new way of looking at a variety of viral tRNA-like motifs as this type of structural mimicry might be related to specific host mRNA species rather than, or in addition to, tRNA itself.

Computational methods toward accurate RNA structure prediction using coarse-grained and all-atom models

Computational methods can provide significant insights into RNA structure and dynamics, bridging the gap in our understanding of the relationship between structure and biological function. Simulations enrich and enhance our understanding of data derived on the bench, as well as provide feasible alternatives to costly or technically challenging experiments. Coarse-grained computational models of RNA are especially important in this regard, as they allow analysis of events occurring in timescales relevant to RNA biological function, which are inaccessible through experimental methods alone. We have developed a three-bead coarse-grained model of RNA for discrete molecular dynamics simulations. This model is efficient in de novo prediction of short RNA tertiary structure, starting from RNA primary sequences of less than 50 nucleotides. To complement this model, we have incorporated additional base-pairing constraints and have developed a bias potential reliant on data obtained from hydroxyl probing experiments that guide RNA folding to its correct state. By introducing experimentally derived constraints to our computer simulations, we are able to make reliable predictions of RNA tertiary structures up to a few hundred nucleotides. Our refined model exemplifies a valuable benefit achieved through integration of computation and experimental methods.

Understanding the potential of hepatitis C virus internal ribosome entry site domains to modulate translation initiation via their structure and function

Translation initiation in the hepatitis C virus (HCV) occurs through a cap-independent mechanism that involves an internal ribosome entry site (IRES) capable of interacting with and utilizing the eukaryotic translational machinery. In this review, we focus on the structural configuration of the different HCV IRES domains and the impact of IRES primary sequence variations on secondary structure conservation and function. In some cases, multiple mutations, even those scattered across different domains, led to restoration of the translational activity of the HCV IRES, although the individual occurrences of these mutations were found to be deleterious. We propose that such observation may be attributed to probable long-range inter- and/or intra-domain functional interactions. The precise functioning of the HCV IRES requires the specific interaction of its domains with ribosomal subunits and a subset of eukaryotic translation initiation factors (eIFs). The structural conformation, sequence preservation and variability, and translational machinery association with the HCV IRES regions are also thoroughly discussed, along with other factors that can affect and influence the formation of translation initiation complexes. WIREs RNA 2015, 6:211–224. doi: 10.1002/wrna.1268

RNA tertiary structure analysis by 2'-hydroxyl molecular interference

We introduce a melded chemical and computational approach for probing and modeling higher-order intramolecular tertiary interactions in RNA. 2'-Hydroxyl molecular interference (HMX) identifies nucleotides in highly packed regions of an RNA by exploiting the ability of bulky adducts at the 2'-hydroxyl position to disrupt overall RNA structure. HMX was found to be exceptionally selective for quantitative detection of higher-order and tertiary interactions. When incorporated as experimental constraints in discrete molecular dynamics simulations, HMX information yielded accurate three-dimensional models, emphasizing the power of molecular interference to guide RNA tertiary structure analysis and fold refinement. In the case of a large, multidomain RNA, the Tetrahymena group I intron, HMX identified multiple distinct sets of tertiary structure interaction groups in a single, concise experiment.

Topological constraints are major determinants of tRNA tertiary structure and dynamics and provide basis for tertiary folding cooperativity

Recent studies have shown that basic steric and connectivity constraints encoded at the secondary structure level are key determinants of 3D structure and dynamics in simple two-way RNA junctions. However, the role of these topological constraints in higher order RNA junctions remains poorly understood. Here, we use a specialized coarse-grained molecular dynamics model to directly probe the thermodynamic contributions of topological constraints in defining the 3D architecture and dynamics of transfer RNA (tRNA). Topological constraints alone restrict tRNA's allowed conformational space by over an order of magnitude and strongly discriminate against formation of non-native tertiary contacts, providing a sequence independent source of folding specificity. Topological constraints also give rise to long-range correlations between the relative orientation of tRNA's helices, which in turn provides a mechanism for encoding thermodynamic cooperativity between distinct tertiary interactions. These aspects of topological constraints make it such that only several tertiary interactions are needed to confine tRNA to its native global structure and specify functionally important 3D dynamics. We further show that topological constraints are conserved across tRNA's different naturally occurring secondary structures. Taken together, our results emphasize the central role of secondary-structure-encoded topological constraints in defining RNA 3D structure, dynamics and folding.

Single-molecule correlated chemical probing of RNA

Complex higher-order RNA structures play critical roles in all facets of gene expression; however, the through-space interaction networks that define tertiary structures and govern sampling of multiple conformations are poorly understood. Here we describe single-molecule RNA structure analysis in which multiple sites of chemical modification are identified in single RNA strands by massively parallel sequencing and then analyzed for correlated and clustered interactions. The strategy thus identifies RNA interaction groups by mutational profiling (RING-MaP) and makes possible two expansive applications. First, we identify through-space interactions, create 3D models for RNAs spanning 80-265 nucleotides, and characterize broad classes of intramolecular interactions that stabilize RNA. Second, we distinguish distinct conformations in solution ensembles and reveal previously undetected hidden states and large-scale structural reconfigurations that occur in unfolded RNAs relative to native states. RING-MaP single-molecule nucleic acid structure interrogation enables concise and facile analysis of the global architectures and multiple conformations that govern function in RNA.

Computational modeling of RNA 3D structures, with the aid of experimental restraints

In addition to mRNAs whose primary function is transmission of genetic information from DNA to proteins, numerous other classes of RNA molecules exist, which are involved in a variety of functions, such as catalyzing biochemical reactions or performing regulatory roles. In analogy to proteins, the function of RNAs depends on their structure and dynamics, which are largely determined by the ribonucleotide sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that simulate either the physical process of RNA structure formation ("Greek science" approach) or utilize information derived from known structures of other RNA molecules ("Babylonian science" approach). All computational methods suffer from various limitations that make them generally unreliable for structure prediction of long RNA sequences. However, in many cases, the limitations of computational and experimental methods can be overcome by combining these two complementary approaches with each other. In this work, we review computational approaches for RNA structure prediction, with emphasis on implementations (particular programs) that can utilize restraints derived from experimental analyses. We also list experimental approaches, whose results can be relatively easily used by computational methods. Finally, we describe case studies where computational and experimental analyses were successfully combined to determine RNA structures that would remain out of reach for each of these approaches applied separately.

The genetic code as expressed through relationships between mRNA structure and protein function

Structured RNA elements within messenger RNA often direct or modulate the cellular production of active proteins. As reviewed here, RNA structures have been discovered that govern nearly every step in protein production: mRNA production and stability; translation initiation, elongation, and termination; protein folding; and cellular localization. Regulatory RNA elements are common within RNAs from every domain of life. This growing body of RNA-mediated mechanisms continues to reveal new ways in which mRNA structure regulates translation. We integrate examples from several different classes of RNA structure-mediated regulation to present a global perspective that suggests that the secondary and tertiary structure of RNA ultimately constitutes an additional level of the genetic code that both guides and regulates protein biosynthesis.

Animal virus schemes for translation dominance

Viruses have adapted a broad range of unique mechanisms to modulate the cellular translational machinery to ensure viral translation at the expense of cellular protein synthesis. Many of these promote virus-specific translation by use of molecular tags on viral mRNA such as internal ribosome entry sites (IRES) and genome-linked viral proteins (VPg) that bind translation machinery components in unusual ways and promote RNA circularization. This review describes recent advances in understanding some of the mechanisms in which animal virus mRNAs gain an advantage over cellular transcripts, including new structural and biochemical insights into IRES function and novel proteins that function as alternate met-tRNA_i^met carriers in translation initiation. Comparisons between animal and plant virus mechanisms that promote translation of viral mRNAs are discussed.

Three-dimensional RNA structure refinement by hydroxyl radical probing

Molecular modeling guided by experimentally-derived structural information is an attractive approach for three-dimensional structure determination of complex RNAs that are not amenable to study by high-resolution methods. Hydroxyl radical probing (HRP), performed routinely in many laboratories, provides a measure of solvent accessibility at individual nucleotides. HRP measurements have, to date, only been used to evaluate RNA models qualitatively. Here, we report development of a quantitative structure refinement approach using HRP measurements to drive discrete molecular dynamics simulations for RNAs ranging in size from 80 to 230 nucleotides. HRP reactivities were first used to identify RNAs that form extensive helical packing interactions. For these RNAs, we achieved highly significant structure predictions, given inputs of RNA sequence and base pairing. This HRP-directed tertiary structure refinement approach generates robust structural hypotheses useful for guiding explorations of structure-function interrelationships in RNA.

RNA-Puzzles: a CASP-like evaluation of RNA three-dimensional structure prediction

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.

Crystal structure of the HCV IRES central domain reveals strategy for start-codon positioning

Translation of hepatitis C viral proteins requires an internal ribosome entry site (IRES) located in the 5' untranslated region of the viral mRNA. The core domain of the hepatitis C virus (HCV) IRES contains a four-way helical junction that is integrated within a predicted pseudoknot. This domain is required for positioning the mRNA start codon correctly on the 40S ribosomal subunit during translation initiation. Here, we present the crystal structure of this RNA, revealing a complex double-pseudoknot fold that establishes the alignment of two helical elements on either side of the four-helix junction. The conformation of this core domain constrains the open reading frame's orientation for positioning on the 40S ribosomal subunit. This structure, representing the last major domain of HCV-like IRESs to be determined at near-atomic resolution, provides the basis for a comprehensive cryoelectron microscopy-guided model of the intact HCV IRES and its interaction with 40S ribosomal subunits.

RNA tertiary structure prediction with ModeRNA

Noncoding RNAs perform important roles in the cell. As their function is tightly connected with structure, and as experimental methods are time-consuming and expensive, the field of RNA structure prediction is developing rapidly. Here, we present a detailed study on using the ModeRNA software. The tool uses the comparative modeling approach and can be applied when a structural template is available and an alignment of reasonable quality can be performed. We guide the reader through the entire process of modeling Escherichia coli tRNA(Thr) in a conformation corresponding to the complex with an aminoacyl-tRNA synthetase (aaRS). We describe the choice of a template structure, preparation of input files, and explore three possible modeling strategies. In the end, we evaluate the resulting models using six alternative benchmarks. The ModeRNA software can be freely downloaded from http://iimcb.genesilico.pl/moderna/ under the conditions of the General Public License. It runs under LINUX, Windows and Mac OS. It is also available as a server at http://iimcb.genesilico.pl/modernaserver/. The models and the script to reproduce the study from this article are available at http://www.genesilico.pl/moderna/examples/.

HCV IRES domain IIb affects the configuration of coding RNA in the 40S subunit's decoding groove

Hepatitis C virus (HCV) uses a structured internal ribosome entry site (IRES) RNA to recruit the translation machinery to the viral RNA and begin protein synthesis without the ribosomal scanning process required for canonical translation initiation. Different IRES structural domains are used in this process, which begins with direct binding of the 40S ribosomal subunit to the IRES RNA and involves specific manipulation of the translational machinery. We have found that upon initial 40S subunit binding, the stem-loop domain of the IRES that contains the start codon unwinds and adopts a stable configuration within the subunit's decoding groove. This configuration depends on the sequence and structure of a different stem-loop domain (domain IIb) located far from the start codon in sequence, but spatially proximal in the IRES•40S complex. Mutation of domain IIb results in misconfiguration of the HCV RNA in the decoding groove that includes changes in the placement of the AUG start codon, and a substantial decrease in the ability of the IRES to initiate translation. Our results show that two distal regions of the IRES are structurally communicating at the initial step of 40S subunit binding and suggest that this is an important step in driving protein synthesis.

A boost for the emerging field of RNA nanotechnology

This Nano Focus article highlights recent advances in RNA nanotechnology as presented at the First International Conference of RNA Nanotechnology and Therapeutics, which took place in Cleveland, OH, USA (October 23-25, 2010) ( http://www.eng.uc.edu/nanomedicine/RNA2010/ ), chaired by Peixuan Guo and co-chaired by David Rueda and Scott Tenenbaum. The conference was the first of its kind to bring together more than 30 invited speakers in the frontier of RNA nanotechnology from France, Sweden, South Korea, China, and throughout the United States to discuss RNA nanotechnology and its applications. It provided a platform for researchers from academia, government, and the pharmaceutical industry to share existing knowledge, vision, technology, and challenges in the field and promoted collaborations among researchers interested in advancing this emerging scientific discipline. The meeting covered a range of topics, including biophysical and single-molecule approaches for characterization of RNA nanostructures; structure studies on RNA nanoparticles by chemical or biochemical approaches, computation, prediction, and modeling of RNA nanoparticle structures; methods for the assembly of RNA nanoparticles; chemistry for RNA synthesis, conjugation, and labeling; and application of RNA nanoparticles in therapeutics. A special invited talk on the well-established principles of DNA nanotechnology was arranged to provide models for RNA nanotechnology. An Administrator from National Institutes of Health (NIH) National Cancer Institute (NCI) Alliance for Nanotechnology in Cancer discussed the current nanocancer research directions and future funding opportunities at NCI. As indicated by the feedback received from the invited speakers and the meeting participants, this meeting was extremely successful, exciting, and informative, covering many groundbreaking findings, pioneering ideas, and novel discoveries.

Topological constraints: using RNA secondary structure to model 3D conformation, folding pathways, and dynamic adaptation

Accompanying recent advances in determining RNA secondary structure is the growing appreciation for the importance of relatively simple topological constraints, encoded at the secondary structure level, in defining the overall architecture, folding pathways, and dynamic adaptability of RNA. A new view is emerging in which tertiary interactions do not define RNA 3D structure, but rather, help select specific conformers from an already narrow, topologically pre-defined conformational distribution. Studies are providing fundamental insights into the nature of these topological constraints, how they are encoded by the RNA secondary structure, and how they interplay with other interactions, breathing new meaning to RNA secondary structure. New approaches have been developed that take advantage of topological constraints in determining RNA backbone conformation based on secondary structure, and a limited set of other, easily accessible constraints. Topological constraints are also providing a much-needed framework for rationalizing and describing RNA dynamics and structural adaptation. Finally, studies suggest that topological constraints may play important roles in steering RNA folding pathways. Here, we review recent advances in our understanding of topological constraints encoded by the RNA secondary structure.

On the significance of an RNA tertiary structure prediction

Tertiary structure prediction is important for understanding structure-function relationships for RNAs whose structures are unknown and for characterizing RNA states recalcitrant to direct analysis. However, it is unknown what root-mean-square deviation (RMSD) corresponds to a statistically significant RNA tertiary structure prediction. We use discrete molecular dynamics to generate RNA-like folds for structures up to 161 nucleotides (nt) that have complex tertiary interactions and then determine the RMSD distribution between these decoys. These distributions are Gaussian-like. The mean RMSD increases with RNA length and is smaller if secondary structure constraints are imposed while generating decoys. The compactness of RNA molecules with true tertiary folds is intermediate between closely packed spheres and a freely jointed chain. We use this scaling relationship to define an expression relating RMSD with the confidence that a structure prediction is better than that expected by chance. This is the prediction significance, and corresponds to a P-value. For a 100-nt RNA, the RMSD of predicted structures should be within 25 A of the accepted structure to reach the P <or= 0.01 level if the secondary structure is predicted de novo and within 14 A if secondary structure information is used as a constraint. This significance approach should be useful for evaluating diverse RNA structure prediction and molecular modeling algorithms.