Functional Analysis of the Core Human Immunodeficiency Virus Type 1 Packaging Signal in a Permissive Cell Line

Packaging of type C retrovirus genomic RNAs into budding virions requires a highly specific interaction between the viral Gag precursor and unique cis-acting packaging signals on the full-length RNA genome, allowing the selection of this RNA species from among a pool of spliced viral RNAs and similar cellular RNAs. This process is thought to involve RNA secondary and tertiary structural motifs since there is little conservation of the primary sequence of this region between retroviruses. To confirm RNA secondary structures, which we and others have predicted for this region, disruptive, compensatory, and deletion mutations were introduced into proviral constructs, which were then assayed in a permissive cell line. Disruption of either of two predicted stem-loops was found to greatly reduce RNA encapsidation and replication, whereas compensatory mutations restoring base pairing to these stem-loops had a wild-type phenotype. A GGNGR motif was identified in the loops of three hairpins in this region. Results were consistent with the hypothesis that the process of efficient RNA encapsidation is linked to dimerization. Replication and encapsidation were shown to occur at a reduced rate in the absence of the previously described kissing hairpin motif.     

On the structural repertoire of pools of short, random RNA sequences

A detailed knowledge of the mapping between sequence and structure spaces in populations of RNA molecules is essential to better understand their present-day functional properties, to envisage a plausible early evolution of RNA in a prebiotic chemical environment and to improve the design of in vitro evolution experiments, among others. Analysis of natural RNAs, as well as in vitro and computational studies, show that certain RNA structural motifs are much more abundant than others, pointing out a complex relation between sequence and structure. Within this framework, we have investigated computationally the structural properties of a large pool (10⁸ molecules) of single-stranded, 35 nt-long, random RNA sequences. The secondary structures obtained are ranked and classified into structure families. The number of structures in main families is analytically calculated and compared with the numerical results. This permits a quantification of the fraction of structure space covered by a large pool of sequences. We further show that the number of structural motifs and their frequency is highly unbalanced with respect to the nucleotide composition: simple structures such as stem-loops and hairpins arise from sequences depleted in G, while more complex structures require an enrichment of G. In general, we observe a strong correlation between subfamilies—characterized by a fixed number of paired nucleotides—and nucleotide composition. Our results are compared to the structural repertoire obtained in a second pool where isolated base pairs are prohibited.     

A novel method for the identification of conserved structural patterns in RNA: From small scale to high-throughput applications

Functional RNA regions are often related to recurrent secondary structure patterns (or motifs), which can exert their role in several different ways, particularly in dictating the interaction with RNA-binding proteins, and acting in the regulation of a large number of cellular processes. Among the available motif-finding tools, the majority focuses on sequence patterns, sometimes including secondary structure as additional constraints to improve their performance. Nonetheless, secondary structures motifs may be concurrent to their sequence counterparts or even encode a stronger functional signal. Current methods for searching structural motifs generally require long pipelines and/or high computational efforts or previously aligned sequences. Here, we present BEAM (BEAr Motif finder), a novel method for structural motif discovery from a set of unaligned RNAs, taking advantage of a recently developed encoding for RNA secondary structure named BEAR (Brand nEw Alphabet for RNAs) and of evolutionary substitution rates of secondary structure elements. Tested in a varied set of scenarios, from small- to large-scale, BEAM is successful in retrieving structural motifs even in highly noisy data sets, such as those that can arise in CLIP-Seq or other high-throughput experiments.     

RNAMotif, an RNA secondary structure definition and search algorithm

RNA molecules fold into characteristic secondary and tertiary structures that account for their diverse functional activities. Many of these RNA structures are assembled from a collection of RNA structural motifs. These basic building blocks are used repeatedly, and in various combinations, to form different RNA types and define their unique structural and functional properties. Identification of recurring RNA structural motifs will therefore enhance our understanding of RNA structure and help associate elements of RNA structure with functional and regulatory elements. Our goal was to develop a computer program that can describe an RNA structural element of any complexity and then search any nucleotide sequence database, including the complete prokaryotic and eukaryotic genomes, for these structural elements. Here we describe in detail a new computational motif search algorithm, RNAMotif, and demonstrate its utility with some motif search examples. RNAMotif differs from other motif search tools in two important aspects: first, the structure definition language is more flexible and can specify any type of base–base interaction; second, RNAMotif provides a user controlled scoring section that can be used to add capabilities that patterns alone cannot provide.     

Prediction of consensus structural motifs in a family of coregulated RNA sequences

Given a set of homologous or functionally related RNA sequences, the consensus motifs may represent the binding sites of RNA regulatory proteins. Unlike DNA motifs, RNA motifs are more conserved in structures than in sequences. Knowing the structural motifs can help us gain a deeper insight of the regulation activities. There have been various studies of RNA secondary structure prediction, but most of them are not focused on finding motifs from sets of functionally related sequences. Although recent research shows some new approaches to RNA motif finding, they are limited to finding relatively simple structures, e.g. stem-loops. In this paper, we propose a novel genetic programming approach to RNA secondary structure prediction. It is capable of finding more complex structures than stem-loops. To demonstrate the performance of our new approach as well as to keep the consistency of our comparative study, we first tested it on the same data sets previously used to verify the current prediction systems. To show the flexibility of our new approach, we also tested it on a data set that contains pseudoknot motifs which most current systems cannot identify. A web-based user interface of the prediction system is set up at http://bioinfo. cis.nctu.edu.tw/service/gprm/.     

SCARNA: fast and accurate structural alignment of RNA sequences by matching fixed-length stem fragments

MOTIVATION: The functions of non-coding RNAs are strongly related to their secondary structures, but it is known that a secondary structure prediction of a single sequence is not reliable. Therefore, we have to collect similar RNA sequences with a common secondary structure for the analyses of a new non-coding RNA without knowing the exact secondary structure itself. Therefore, the sequence comparison in searching similar RNAs should consider not only their sequence similarities but also their potential secondary structures. Sankoff's algorithm predicts the common secondary structures of the sequences, but it is computationally too expensive to apply to large-scale analyses. Because we often want to compare a large number of cDNA sequences or to search similar RNAs in the whole genome sequences, much faster algorithms are required. RESULTS: We propose a new method of comparing RNA sequences based on the structural alignments of the fixed-length fragments of the stem candidates. The implemented software, SCARNA (Stem Candidate Aligner for RNAs), is fast enough to apply to the long sequences in the large-scale analyses. The accuracy of the alignments is better or comparable with the much slower existing algorithms. AVAILABILITY: The web server of SCARNA with graphical structural alignment viewer is available at http://www.scarna.org/.     

SHAPE analysis of the FIV Leader RNA reveals a structural switch potentially controlling viral packaging and genome dimerization

Feline immunodeficiency virus (FIV) infects many species of cat, and is related to HIV, causing a similar pathology. High-throughput selective 2' hydroxyl acylation analysed by primer extension (SHAPE), a technique that allows structural interrogation at each nucleotide, was used to map the secondary structure of the FIV packaging signal RNA. Previous studies of this RNA showed four conserved stem-loops, extensive long-range interactions (LRIs) and a small, palindromic stem-loop (SL5) within the gag open reading frame (ORF) that may act as a dimerization initiation site (DIS), enabling the virus to package two copies of its genome. Our analyses of wild-type (wt) and mutant RNAs suggest that although the four conserved stem-loops are static structures, the 5' and 3' regions previously shown to form LRI also adopt an alternative, yet similarly conserved conformation, in which the putative DIS is occluded, and which may thus favour translational and splicing functions over encapsidation. SHAPE and in vitro dimerization assays were used to examine SL5 mutants. Dimerization contacts appear to be made between palindromic loop sequences in SL5. As this stem-loop is located within the gag ORF, recognition of a dimeric RNA provides a possible mechanism for the specific packaging of genomic over spliced viral RNAs.     

Recurring features of local tertiary structural elements in RNA molecules exemplified by hepatitis D virus RNA

Elements of local tertiary structure in RNA molecules are important in understanding structure-function relationships. The loop E motif, first identified in several eukaryotic RNAs at functional sites which share an exceptional propensity for UV crosslinking between specific bases, was subsequently shown to have a characteristic tertiary structure. Common sequences and secondary structures have allowed other examples of the E-loop motif to be recognized in a number of RNAs at sites of protein binding or other biological function. We would like to know if more elements of local tertiary structure, in addition to the E-loop, can be identified by such common features. The highly structured circular RNA genome of the hepatitis D virus (HDV) provides an ideal test molecule because it has extensive internal structure, a UV-crosslinkable tertiary element, and specific sites for functional interactions with proteins including host PKR. We have now found a UV-crosslinkable element of local tertiary structure in antigenomic HDV RNA which, although differing from the E-loop, has a very similar pattern of sequence and secondary structure to the UV-crosslinkable element found in the genomic strand. Despite the fact that the two structures map close to one another, the sequences comprising them are not the templates for each other. Instead, the template regions for each element are additional sites for potential higher order structure on their respective complementary strands. This wealth of recurring sequences interspersed with base-paired stems provides a context to examine other RNA species for such features and their correlations with biological function.     

In vitro RNA random pools are not structurally diverse: a computational analysis

In vitro selection of functional RNAs from large random sequence pools has led to the identification of many ligand-binding and catalytic RNAs. However, the structural diversity in random pools is not well understood. Such an understanding is a prerequisite for designing sequence pools to increase the probability of finding complex functional RNA by in vitro selection techniques. Toward this goal, we have generated by computer five random pools of RNA sequences of length up to 100 nt to mimic experiments and characterized the distribution of associated secondary structural motifs using sets of possible RNA tree structures derived from graph theory techniques. Our results show that such random pools heavily favor simple topological structures: For example, linear stem-loop and low-branching motifs are favored rather than complex structures with high-order junctions, as confirmed by known aptamers. Moreover, we quantify the rise of structural complexity with sequence length and report the dominant class of tree motifs (characterized by vertex number) for each pool. These analyses show not only that random pools do not lead to a uniform distribution of possible RNA secondary topologies; they point to avenues for designing pools with specific simple and complex structures in equal abundance in the goal of broadening the range of functional RNAs discovered by in vitro selection. Specifically, the optimal RNA sequence pool length to identify a structure with x stems is 20x.     

Evolution of secondary structure in the family of 7SL-like RNAs

Primate and rodent genomes are populated with hundreds of thousands copies of Alu and B1 elements dispersed by retroposition, i.e., by genomic reintegration of their reverse transcribed RNAs. These, as well as primate BC200 and rodent 4.5S RNAs, are ancestrally related to the terminal portions of 7SL RNA sequence. The secondary structure of 7SL RNA (an integral component of the signal recognition particle) is conserved from prokaryotes to distant eukaryotic species. Yet only in primates and rodents did this molecule give rise to retroposing Alu and B1 RNAs and to apparently functional BC200 and 4.5S RNAs. To understand this transition and the underlying molecular events, we examined, by comparative analysis, the evolution of RNA structure in this family of molecules derived from 7SL RNA.RNA sequences of different simian (mostly human) and prosimian Alu subfamilies as well as rodent B1 repeats were derived from their genomic consensus sequences taken from the literature and our unpublished results (prosimian and New World Monkey). RNA secondary structures were determined by enzymatic studies (new data on 4.5S RNA are presented) and/or energy minimization analyses followed by phylogenetic comparison. Although, with the exception of 4.5S RNA, all 7SL-derived RNA species maintain the cruciform structure of their progenitor, the details of 7SL RNA folding domains are modified to a different extent in various RNA groups. Novel motifs found in retropositionally active RNAs are conserved among Alu and B1 subfamilies in different genomes. In RNAs that do not proliferate by retroposition these motifs are modified further. This indicates structural adaptation of 7SL-like RNA molecules to novel functions, presumably mediated by specific interactions with proteins; these functions were either useful for the host or served the selfish propagation of RNA templates within the host genome.Abbreviations FAM fossil Alu element - FLAM free left Alu monomer - FRAM free right Alu monomer - L-Alu left Alu subunit - R-Alu right Alu subunit Correspondence to: D. LabudaDedicated to Dr. Robert Cedergren on the occasion of his 25th anniversary at the University of Montreal     

Modular RNA architecture revealed by computational analysis of existing pseudoknots and ribosomal RNAs

Modular architecture is a hallmark of RNA structures, implying structural, and possibly functional, similarity among existing RNAs. To systematically delineate the existence of smaller topologies within larger structures, we develop and apply an efficient RNA secondary structure comparison algorithm using a newly developed two-dimensional RNA graphical representation. Our survey of similarity among 14 pseudoknots and subtopologies within ribosomal RNAs (rRNAs) uncovers eight pairs of structurally related pseudoknots with non-random sequence matches and reveals modular units in rRNAs. Significantly, three structurally related pseudoknot pairs have functional similarities not previously known: one pair involves the 3′ end of brome mosaic virus genomic RNA (PKB134) and the alternative hammerhead ribozyme pseudoknot (PKB173), both of which are replicase templates for viral RNA replication; the second pair involves structural elements for translation initiation and ribosome recruitment found in the viral internal ribosome entry site (PKB223) and the V4 domain of 18S rRNA (PKB205); the third pair involves 18S rRNA (PKB205) and viral tRNA-like pseudoknot (PKB134), which probably recruits ribosomes via structural mimicry and base complementarity. Additionally, we quantify the modularity of 16S and 23S rRNAs by showing that RNA motifs can be constructed from at least 210 building blocks. Interestingly, we find that the 5S rRNA and two tree modules within 16S and 23S rRNAs have similar topologies and tertiary shapes. These modules can be applied to design novel RNA motifs via build-up-like procedures for constructing sequences and folds.     

Prediction of locally stable RNA secondary structures for genome-wide surveys

MOTIVATION: Recently novel classes of functional RNAs, most prominently the miRNAs have been discovered, strongly suggesting that further types of functional RNAs are still hidden in the recently completed genomic DNA sequences. Only few techniques are known, however, to survey genomes for such RNA genes. When sufficiently similar sequences are not available for comparative approaches the only known remedy is to search directly for structural features. RESULTS: We present here efficient algorithms for computing locally stable RNA structures at genome-wide scales. Both the minimum energy structure and the complete matrix of base pairing probabilities can be computed in theta(N x L2) time and theta(N + L2) memory in terms of the length N of the genome and the size L of the largest secondary structure motifs of interest. In practice, the 100 Mb of the complete genome of Caenorhabditis elegans can be folded within about half a day on a modern PC with a search depth of L = 100. This is sufficient example for a survey for miRNAs. AVAILABILITY: The software described in this contribution will be available for download at http://www.tbi.univie.ac.at/~ivo/RNA/ as part of the Vienna RNA Package.     

Exploring the repertoire of RNA secondary motifs using graph theory; implications for RNA design

Understanding the structural repertoire of RNA is crucial for RNA genomics research. Yet current methods for finding novel RNAs are limited to small or known RNA families. To expand known RNA structural motifs, we develop a two-dimensional graphical representation approach for describing and estimating the size of RNA’s secondary structural repertoire, including naturally occurring and other possible RNA motifs. We employ tree graphs to describe RNA tree motifs and more general (dual) graphs to describe both RNA tree and pseudoknot motifs. Our estimates of RNA’s structural space are vastly smaller than the nucleotide sequence space, suggesting a new avenue for finding novel RNAs. Specifically our survey shows that known RNA trees and pseudoknots represent only a small subset of all possible motifs, implying that some of the ‘missing’ motifs may represent novel RNAs. To help pinpoint RNA-like motifs, we show that the motifs of existing functional RNAs are clustered in a narrow range of topological characteristics. We also illustrate the applications of our approach to the design of novel RNAs and automated comparison of RNA structures; we report several occurrences of RNA motifs within larger RNAs. Thus, our graph theory approach to RNA structures has implications for RNA genomics, structure analysis and design.     

Cardioviral RNA structure logo analysis: entropy, correlations, and prediction

In recent years, there has been an increased number of sequenced RNAs leading to the development of new RNA databases. Thus, predicting RNA structure from multiple alignments is an important issue to understand its function. Since RNA secondary structures are often conserved in evolution, developing methods to identify covariate sites in an alignment can be essential for discovering structural elements. Structure Logo is a technique established on the basis of entropy and mutual information measured to analyze RNA sequences from an alignment. We proposed an efficient Structure Logo approach to analyze conservations and correlations in a set of Cardioviral RNA sequences. The entropy and mutual information content were measured to examine the conservations and correlations, respectively. The conserved secondary structure motifs were predicted on the basis of the conservation and correlation analyses. Our predictive motifs were similar to the ones observed in the viral RNA structure database, and the correlations between bases also corresponded to the secondary structure in the database.     

Self containment, a property of modular RNA structures, distinguishes microRNAs

RNA molecules will tend to adopt a folded conformation through the pairing of bases on a single strand; the resulting so-called secondary structure is critical to the function of many types of RNA. The secondary structure of a particular substring of functional RNA may depend on its surrounding sequence. Yet, some RNAs such as microRNAs retain their specific structures during biogenesis, which involves extraction of the substructure from a larger structural context, while other functional RNAs may be composed of a fusion of independent substructures. Such observations raise the question of whether particular functional RNA substructures may be selected for invariance of secondary structure to their surrounding nucleotide context. We define the property of self containment to be the tendency for an RNA sequence to robustly adopt the same optimal secondary structure regardless of whether it exists in isolation or is a substring of a longer sequence of arbitrary nucleotide content. We measured degree of self containment using a scoring method we call the self-containment index and found that miRNA stem loops exhibit high self containment, consistent with the requirement for structural invariance imposed by the miRNA biogenesis pathway, while most other structured RNAs do not. Further analysis revealed a trend toward higher self containment among clustered and conserved miRNAs, suggesting that high self containment may be a characteristic of novel miRNAs acquiring new genomic contexts. We found that miRNAs display significantly enhanced self containment compared to other functional RNAs, but we also found a trend toward natural selection for self containment in most functional RNA classes. We suggest that self containment arises out of selection for robustness against perturbations, invariance during biogenesis, and modular composition of structural function. Analysis of self containment will be important for both annotation and design of functional RNAs. A Python implementation and Web interface to calculate the self-containment index are available at http://kim.bio.upenn.edu/software/.     

Predicting candidate genomic sequences that correspond to synthetic functional RNA motifs

Riboswitches and RNA interference are important emerging mechanisms found in many organisms to control gene expression. To enhance our understanding of such RNA roles, finding small regulatory motifs in genomes presents a challenge on a wide scale. Many simple functional RNA motifs have been found by in vitro selection experiments, which produce synthetic target-binding aptamers as well as catalytic RNAs, including the hammerhead ribozyme. Motivated by the prediction of Piganeau and Schroeder [(2003) Chem. Biol., 10, 103–104] that synthetic RNAs may have natural counterparts, we develop and apply an efficient computational protocol for identifying aptamer-like motifs in genomes. We define motifs from the sequence and structural information of synthetic aptamers, search for sequences in genomes that will produce motif matches, and then evaluate the structural stability and statistical significance of the potential hits. Our application to aptamers for streptomycin, chloramphenicol, neomycin B and ATP identifies 37 candidate sequences (in coding and non-coding regions) that fold to the target aptamer structures in bacterial and archaeal genomes. Further energetic screening reveals that several candidates exhibit energetic properties and sequence conservation patterns that are characteristic of functional motifs. Besides providing candidates for experimental testing, our computational protocol offers an avenue for expanding natural RNA's functional repertoire.     

RNA structural motifs: building blocks of a modular biomolecule

RNAs are modular biomolecules, composed largely of conserved structural subunits, or motifs. These structural motifs comprise the secondary structure of RNA and are knit together via tertiary interactions into a compact, functional, three-dimensional structure and are to be distinguished from motifs defined by sequence or function. A relatively small number of structural motifs are found repeatedly in RNA hairpin and internal loops, and are observed to be composed of a limited number of common 'structural elements'. In addition to secondary and tertiary structure motifs, there are functional motifs specific for certain biological roles and binding motifs that serve to complex metals or other ligands. Research is continuing into the identification and classification of RNA structural motifs and is being initiated to predict motifs from sequence, to trace their phylogenetic relationships and to use them as building blocks in RNA engineering.