Potent effect of target structure on microRNA function.

MicroRNAs (miRNAs) are small noncoding RNAs that repress protein synthesis by binding to target messenger RNAs. We investigated the effect of target secondary structure on the efficacy of repression by miRNAs. Using structures predicted by the Sfold program, we model the interaction between an miRNA and a target as a two-step hybridization reaction: nucleation at an accessible target site followed by hybrid elongation to disrupt local target secondary structure and form the complete miRNA-target duplex. This model accurately accounts for the sensitivity to repression by let-7 of various mutant forms of the Caenorhabditis elegans lin-41 3' untranslated region and for other experimentally tested miRNA-target interactions in C. elegans and Drosophila melanogaster. These findings indicate a potent effect of target structure on target recognition by miRNAs and establish a structure-based framework for genome-wide identification of animal miRNA targets.

A structural interpretation of the effect of GC-content on efficiency of RNA interference.

BACKGROUND: RNA interference (RNAi) mediated by small interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs) has become a powerful technique for eukaryotic gene knockdown. siRNA GC-content negatively correlates with RNAi efficiency, and it is of interest to have a convincing mechanistic interpretation of this observation. We here examine this issue by considering the secondary structures for both the target messenger RNA (mRNA) and the siRNA guide strand. RESULTS: By analyzing a unique homogeneous data set of 101 shRNAs targeted to 100 endogenous human genes, we find that: 1) target site accessibility is more important than GC-content for efficient RNAi; 2) there is an appreciable negative correlation between GC-content and RNAi activity; 3) for the predicted structure of the siRNA guide strand, there is a lack of correlation between RNAi activity and either the stability or the number of free dangling nucleotides at an end of the structure; 4) there is a high correlation between target site accessibility and GC-content. For a set of representative structural RNAs, the GC content of 62.6% for paired bases is significantly higher than the GC content of 38.7% for unpaired bases. Thus, for a structured RNA, a region with higher GC content is likely to have more stable secondary structure. Furthermore, by partial correlation analysis, the correlation for GC-content is almost completely diminished, when the effect of target accessibility is controlled. CONCLUSION: These findings provide a target-structure-based interpretation and mechanistic insight for the effect of GC-content on RNAi efficiency.

Rational design and rapid screening of antisense oligonucleotides for prokaryotic gene modulation.

Antisense oligodeoxynucleotides (oligos) are widely used for functional studies of both prokaryotic and eukaryotic genes. However, the identification of effective target sites is a major issue in antisense applications. Here, we study a number of thermodynamic and structural parameters that may affect the potency of antisense inhibition. We develop a cell-free assay for rapid oligo screening. This assay is used for measuring the expression of Escherichia coli lacZ, the antisense target for experimental testing and validation. Based on a training set of 18 oligos, we found that structural accessibility predicted by local folding of the target mRNA is the most important predictor for antisense activity. This finding was further confirmed by a direct validation study. In this study, a set of 10 oligos was designed to target accessible sites, and another set of 10 oligos was selected to target inaccessible sites. Seven of the 10 oligos for accessible sites were found to be effective (>50% inhibition), but none of the oligos for inaccessible sites was effective. The difference in the antisense activity between the two sets of oligos was statistically significant. We also found that the predictability of antisense activity by target accessibility was greatly improved for oligos targeted to the regions upstream of the end of the active domain for beta-galactosidase, the protein encoded by lacZ. The combination of the structure-based antisense design and extension of the lacZ assay to include gene fusions will be applicable to high-throughput gene functional screening, and to the identification of new drug targets in pathogenic microbes. Design tools are available through the Sfold Web server at http://sfold.wadsworth.org.

A structural analysis of in vitro catalytic activities of hammerhead ribozymes.

BACKGROUND: Ribozymes are small catalytic RNAs that possess the dual functions of sequence-specific RNA recognition and site-specific cleavage. Trans-cleaving ribozymes can inhibit translation of genes at the messenger RNA (mRNA) level in both eukaryotic and prokaryotic systems and are thus useful tools for studies of gene function. However, identification of target sites for efficient cleavage poses a challenge. Here, we have considered a number of structural and thermodynamic parameters that can affect the efficiency of target cleavage, in an attempt to identify rules for the selection of functional ribozymes. RESULTS: We employed the Sfold program for RNA secondary structure prediction, to account for the likely population of target structures that co-exist in dynamic equilibrium for a specific mRNA molecule. We designed and prepared 15 hammerhead ribozymes to target GUC cleavage sites in the mRNA of the breast cancer resistance protein (BCRP). These ribozymes were tested, and their catalytic activities were measured in vitro. We found that target disruption energy owing to the alteration of the local target structure necessary for ribozyme binding, and the total energy change of the ribozyme-target hybridization, are two significant parameters for prediction of ribozyme activity. Importantly, target disruption energy is the major contributor to the predictability of ribozyme activity by the total energy change. Furthermore, for a target-site specific ribozyme, incorrect folding of the catalytic core, or interactions involving the two binding arms and the end sequences of the catalytic core, can have detrimental effects on ribozyme activity. CONCLUSION: The findings from this study suggest rules for structure-based rational design of trans-cleaving hammerhead ribozymes in gene knockdown studies. Tools implementing these rules are available from the Sribo module and the Srna module of the Sfold program available through Web server at http://sfold.wadsworth.org.

Clustering of RNA secondary structures with application to messenger RNAs.

There is growing evidence of translational gene regulation at the mRNA level, and of the important roles of RNA secondary structure in these regulatory processes. Because mRNAs likely exist in a population of structures, the popular free energy minimization approach may not be well suited to prediction of mRNA structures in studies of post-transcriptional regulation. Here, we describe an alternative procedure for the characterization of mRNA structures, in which structures sampled from the Boltzmann-weighted ensemble of RNA secondary structures are clustered. Based on a random sample of full-length human mRNAs, we find that the minimum free energy (MFE) structure often poorly represents the Boltzmann ensemble, that the ensemble often contains multiple structural clusters, and that the centroids of a small number of structural clusters more effectively characterize the ensemble. We show that cluster-level characteristics and statistics are statistically reproducible. In a comparison between mRNAs and structural RNAs, similarity is observed for the number of clusters and the energy gap between the MFE structure and the sampled ensemble. However, for structural RNAs, there are more high-frequency base-pairs in both the Boltzmann ensemble and the clusters, and the clusters are more compact. The clustering features have been incorporated into the Sfold software package for nucleic acid folding and design.

Sfold web server for statistical folding and rational design of nucleic acids.

The Sfold web server provides user-friendly access to Sfold, a recently developed nucleic acid folding software package, via the World Wide Web (WWW). The software is based on a new statistical sampling paradigm for the prediction of RNA secondary structure. One of the main objectives of this software is to offer computational tools for the rational design of RNA-targeting nucleic acids, which include small interfering RNAs (siRNAs), antisense oligonucleotides and trans-cleaving ribozymes for gene knock-down studies. The methodology for siRNA design is based on a combination of RNA target accessibility prediction, siRNA duplex thermodynamic properties and empirical design rules. Our approach to target accessibility evaluation is an original extension of the underlying RNA folding algorithm to account for the likely existence of a population of structures for the target mRNA. In addition to the application modules Sirna, Soligo and Sribo for siRNAs, antisense oligos and ribozymes, respectively, the module Srna offers comprehensive features for statistical representation of sampled structures. Detailed output in both graphical and text formats is available for all modules. The Sfold server is available at http://sfold.wadsworth.org and http://www.bioinfo.rpi.edu/applications/sfold.

Boltzmann ensemble features of RNA secondary structures: a comparative analysis of biological RNA sequences and random shuffles.

Ensemble-based approaches to RNA secondary structure prediction have become increasingly appreciated in recent years. Here, we utilize sampling and clustering of the Boltzmann ensemble of RNA secondary structures to investigate whether biological sequences exhibit ensemble features that are distinct from their random shuffles. Representative messenger RNAs (mRNAs), structural RNAs, and precursor microRNAs (miRNAs) are analyzed for nine ensemble features. These include structure clustering features, the energy gap between the minimum free energy (MFE) and the ensemble, the numbers of high-frequency base pairs in the ensemble and in clusters, the average base-pair distance between the MFE structure and the ensemble, and between-cluster and within-cluster sums of squares. For each of the features, we observe a lack of significant distinction between mRNAs and their random shuffles. For five features, significant differences are found between structural RNAs and random counterparts. For seven features including the five for structural RNAs, much greater differences are observed between precursor miRNAs and random shuffles. These findings reveal differences in the Boltzmann structure ensemble among different types of functional RNAs. In addition, for two ensemble features, we observe distinctive, non-overlapping distributions for precursor miRNAs and random shuffles. A distributional separation can be particularly useful for the prediction of miRNA genes.

Analysis of microRNA-target interactions by a target structure based hybridization model.

MicroRNAs (miRNAs) are small non-coding RNAs that repress protein synthesis by binding to target messenger RNAs (mRNAs) in multicellular eukaryotes. The mechanism by which animal miRNAs specifically recognize their targets is not well understood. We recently developed a model for modeling the interaction between a miRNA and a target as a two-step hybridization reaction: nucleation at an accessible target site, followed by hybrid elongation to disrupt local target secondary structure and form the complete miRNA-target duplex. Nucleation potential and hybridization energy are two key energetic characteristics of the model. In this model, the role of target secondary structure on the efficacy of repression by miRNAs is considered, by employing the Sfold program to address the likelihood of a population of structures that co-exist in dynamic equilibrium for a specific mRNA molecule. This model can accurately account for the sensitivity to repression by let-7 of both published and rationally designed mutant forms of the Caenorhabditis elegans lin-41 3' UTR, and for the behavior of many other experimentally-tested miRNA-target interactions in C. elegans and Drosophila melanogaster. The model is particularly effective in accounting for certain false positive predictions obtained by other methods. In this study, we employed this model to analyze a set of miRNA-target interactions that were experimentally tested in mammalian models. These include targets for both mammalian miRNAs and viral miRNAs, and a viral target of a human miRNA. We found that our model can well account for both positive interactions and negative interactions. The model provides a unique explanation for the lack of function of a conserved seed site in the 3' UTR of the viral target, and predicts a strong interaction that cannot be predicted by conservation-based methods. Thus, the findings from this analysis and the previous analysis suggest that target structural accessibility is generally important for miRNA function in a broad class of eukaryotic systems. The model can be combined with other algorithms to improve the specificity of predictions by these algorithms. Because the model does not involve sequence conservation, it is readily applicable to target identification for microRNAs that lack conserved sites, non-conserved human miRNAs, and poorly conserved viral mRNAs. StarMir is a new Sfold application module developed for the implementation of the structure-based model, and is available through Sfold Web server at http://sfold.wadsworth.org.

Zinc anilido-oxazolinate complexes as initiators for ring opening polymerization.

Three new anilido-oxazolines, ortho-C(6)H(4)(NHAr')(4,4-dimethyl-2-oxazoline) [Ar'=2,4,6-trimethylphenyl, HNPh(TriMe)Oxa (1); 2,6-diisopropylphenyl, HNPh(DiiPr)Oxa (2); 2-methoxyphenyl, HNPh(OMe)Oxa (3)], have been prepared. Reactions of 1 or 2 with one molar equivalent of ZnEt(2) in tetrahydrofuran or hexane solution give the zinc ethyl complexes (NPh(TriMe)Oxa)ZnEt (4) and (NPh(DiiPr)Oxa)ZnEt (5). The dinuclear zinc benzyloxide complexes, [(NAr'Oxa)Zn(mu-OBn)](2), [Ar'=2,4,6-trimethylphenyl, (6); 2-methoxyphenyl, (7)], were synthesized by the reaction of 4 with one molar equivalent of benzyl alcohol in tetrahydrofuran solution (for 6) or by treatment of with 3 one molar equivalent of ZnEt(2) in tetrahydrofuran solution followed by the addition of one molar equivalent of benzyl alcohol (for 7). The molecular structures are reported for compounds 6 and 7. Their catalytic activities toward the ring opening polymerization reactions are under investigation.

Effect of target secondary structure on RNAi efficiency.

RNA interference (RNAi) mediated by small interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs) has become a powerful tool for gene knockdown studies. However, the levels of knockdown vary greatly. Here, we examine the effect of target disruption energy, a novel measure of target accessibility, along with other parameters that may affect RNAi efficiency. Based on target secondary structures predicted by the Sfold program, the target disruption energy represents the free energy cost for local alteration of the target structure to allow target binding by the siRNA guide strand. In analyses of 100 siRNAs and 101 shRNAs targeted to 103 endogenous human genes, we find that the disruption energy is an important determinant of RNAi activity and the asymmetry of siRNA duplex asymmetry is important for facilitating the assembly of the RNA-induced silencing complex (RISC). We estimate that target accessibility and duplex asymmetry can improve the target knockdown level significantly by nearly 40% and 26%, respectively. In the RNAi pathway, RISC assembly precedes target binding by the siRNA guide strand. Thus, our findings suggest that duplex asymmetry has significant upstream effect on RISC assembly and target accessibility has strong downstream effect on target recognition. The results of the analyses suggest criteria for improving the design of siRNAs and shRNAs.

RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble.

Prediction of RNA secondary structure by free energy minimization has been the standard for over two decades. Here we describe a novel method that forsakes this paradigm for predictions based on Boltzmann-weighted structure ensemble. We introduce the notion of a centroid structure as a representative for a set of structures and describe a procedure for its identification. In comparison with the minimum free energy (MFE) structure using diverse types of structural RNAs, the centroid of the ensemble makes 30.0% fewer prediction errors as measured by the positive predictive value (PPV) with marginally improved sensitivity. The Boltzmann ensemble can be separated into a small number (3.2 on average) of clusters. Among the centroids of these clusters, the "best cluster centroid" as determined by comparison to the known structure simultaneously improves PPV by 46.5% and sensitivity by 21.7%. For 58% of the studied sequences for which the MFE structure is outside the cluster containing the best centroid, the improvements by the best centroid are 62.5% for PPV and 31.4% for sensitivity. These results suggest that the energy well containing the MFE structure under the current incomplete energy model is often different from the one for the unavailable complete model that presumably contains the unique native structure. Centroids are available on the Sfold server at http://sfold.wadsworth.org.

Structure clustering features on the Sfold Web server.

UNLABELLED: The energy landscape of RNA secondary structures is often complex, and the Boltzmann-weighted ensemble usually contains distinct clusters. Furthermore, the minimum free energy structure often lies outside of the cluster containing the structure determined by comparative sequence analysis. We have developed procedures to characterize and visualize the Boltzmann-weighted ensemble, and have made them available on the Sfold Web server. The new features on the Web server include clustering statistics, ensemble and cluster centroids, multi-dimensional scaling display and energy landscape representation of the Boltzmann-weighted ensemble. AVAILABILITY: http://sfold.wadsworth.org; http://www.bioinfo.rpi.edu/applications/sfold CONTACT: chanc@wadsworth.org.