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Submitted by ChenLiang on Fri, 09/02/2016 - 21:59



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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 and[1]

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[2]

Prediction and validation of microRNA (miRNA) targets are essential for understanding functions of miRNAs in gene regulation. Crosslinking immunoprecipitation (CLIP) allows direct identification of a huge number of Argonaute-bound target sequences that contain miRNA binding sites. By analysing data from CLIP studies, we identified a comprehensive list of sequence, thermodynamic and target structure features that are essential for target binding by miRNAs in the 3' untranslated region (3' UTR), coding sequence (CDS) region and 5' untranslated region (5' UTR) of target messenger RNA (mRNA). The total energy of miRNA:target hybridization, a measure of target structural accessibility, is the only essential feature common for both seed and seedless sites in all three target regions. Furthermore, evolutionary conservation is an important discriminating feature for both seed and seedless sites. These features enabled us to develop novel statistical models for the predictions of both seed sites and broad classes of seedless sites. Through both intra-dataset validation and inter-dataset validation, our approach showed major improvements over established algorithms for predicting seed sites and a class of seedless sites. Furthermore, we observed good performance from cross-species validation, suggesting that our prediction framework can be valuable for broad application to other mammalian species and beyond. Transcriptome-wide binding site predictions enabled by our approach will greatly complement the available CLIP data, which only cover small fractions of transcriptomes and known miRNAs due to non-detectable levels of expression. Software and database tools based on the prediction models have been developed and are available through Sfold web server at[3]

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression. Since the discovery of lin-4, the founding member of the miRNA family, over 360 miRNAs have been identified for Caenorhabditis elegans (C. elegans). Prediction and validation of targets are essential for elucidation of regulatory functions of these miRNAs. For C. elegans, crosslinking immunoprecipitation (CLIP) has been successfully performed for the identification of target mRNA sequences bound by Argonaute protein ALG-1. In addition, reliable annotation of the 3' untranslated regions (3' UTRs) as well as developmental stage-specific expression profiles for both miRNAs and 3' UTR isoforms are available. By utilizing these data, we developed statistical models and bioinformatics tools for both transcriptome-scale and developmental stage-specific predictions of miRNA binding sites in C. elegans 3' UTRs. In performance evaluation via cross validation on the ALG-1 CLIP data, the models were found to offer major improvements over established algorithms for predicting both seed sites and seedless sites. In particular, our top-ranked predictions have a substantially higher true positive rate, suggesting a much higher likelihood of positive experimental validation. A gene ontology analysis of stage-specific predictions suggests that miRNAs are involved in dynamic regulation of biological functions during C. elegans development. In particular, miRNAs preferentially target genes related to development, cell cycle, trafficking, and cell signaling processes. A database for both transcriptome-scale and stage-specific predictions and software for implementing the prediction models are available through the Sfold web server at[4]