AREsite: a database for the comprehensive investigation of AU-rich elements

AREsite is an online resource for the detailed investigation of AU-rich elements (ARE) in vertebrate mRNA 3′-untranslated regions (UTRs). AREs are one of the most prominent cis-acting regulatory elements found in 3′-UTRs of mRNAs. Various ARE-binding proteins that possess RNA stabilizing or destabilizing functions are recruited by sequence-specific motifs. Recent findings suggest an essential role of the structural mRNA context in which these sequence motifs are embedded. AREsite is the first database that allows to quantify the structuredness of ARE motif sites in terms of opening energies and accessibility probabilities. Moreover, we also provide a detailed phylogenetic analysis of ARE motifs and incorporate information about experimentally validated targets of the ARE-binding proteins TTP, HuR and Auf1. The database is publicly available at: http://rna.tbi.univie.ac.at/AREsite

The Vienna RNA Websuite

The Vienna RNA Websuite is a comprehensive collection of tools for folding, design and analysis of RNA sequences. It provides a web interface to the most commonly used programs of the Vienna RNA package. Among them, we find folding of single and aligned sequences, prediction of RNA–RNA interactions, and design of sequences with a given structure. Additionally, we provide analysis of folding landscapes using the barriers program and structural RNA alignments using LocARNA. The web server together with software packages for download is freely accessible at http://rna.tbi.univie.ac.at/

GC content around splice sites affects splicing through pre-mRNA secondary structures

<p>Abstract</p> <p>Background</p> <p>Alternative splicing increases protein diversity by generating multiple transcript isoforms from a single gene through different combinations of exons or through different selections of splice sites. It has been reported that RNA secondary structures are involved in alternative splicing. Here we perform a genomic study of RNA secondary structures around splice sites in humans (<it>Homo sapiens</it>), mice (<it>Mus musculus</it>), fruit flies (<it>Drosophila melanogaster</it>), and nematodes (<it>Caenorhabditis elegans</it>) to further investigate this phenomenon.</p> <p>Results</p> <p>We observe that GC content around splice sites is closely associated with the splice site usage in multiple species. RNA secondary structure is the possible explanation, because the structural stability difference among alternative splice sites, constitutive splice sites, and skipped splice sites can be explained by the GC content difference. Alternative splice sites tend to be GC-enriched and exhibit more stable RNA secondary structures in all of the considered species. In humans and mice, splice sites of first exons and long exons tend to be GC-enriched and hence form more stable structures, indicating the special role of RNA secondary structures in promoter proximal splicing events and the splicing of long exons. In addition, GC-enriched exon-intron junctions tend to be overrepresented in tissue-specific alternative splice sites, indicating the functional consequence of the GC effect. Compared with regions far from splice sites and decoy splice sites, real splice sites are GC-enriched. We also found that the GC-content effect is much stronger than the nucleotide-order effect to form stable secondary structures.</p> <p>Conclusion</p> <p>All of these results indicate that GC content is related to splice site usage and it may mediate the splicing process through RNA secondary structures.</p

Assessing the Utility of Thermodynamic Features for microRNA Target Prediction under Relaxed Seed and No Conservation Requirements

BACKGROUND: Many computational microRNA target prediction tools are focused on several key features, including complementarity to 5'seed of miRNAs and evolutionary conservation. While these features allow for successful target identification, not all miRNA target sites are conserved and adhere to canonical seed complementarity. Several studies have propagated the use of energy features of mRNA:miRNA duplexes as an alternative feature. However, different independent evaluations reported conflicting results on the reliability of energy-based predictions. Here, we reassess the usefulness of energy features for mammalian target prediction, aiming to relax or eliminate the need for perfect seed matches and conservation requirement. METHODOLOGY/PRINCIPAL FINDINGS: We detect significant differences of energy features at experimentally supported human miRNA target sites and at genome-wide sites of AGO protein interaction. This trend is confirmed on datasets that assay the effect of miRNAs on mRNA and protein expression changes, and a simple linear regression model leads to significant correlation of predicted versus observed expression change. Compared to 6-mer seed matches as baseline, application of our energy-based model leads to ∼3-5-fold enrichment on highly down-regulated targets, and allows for prediction of strictly imperfect targets with enrichment above baseline. CONCLUSIONS/SIGNIFICANCE: In conclusion, our results indicate significant promise for energy-based miRNA target prediction that includes a broader range of targets without having to use conservation or impose stringent seed match rules

The Fate of miRNA* Strand through Evolutionary Analysis: Implication for Degradation As Merely Carrier Strand or Potential Regulatory Molecule?

BACKGROUND: During typical microRNA (miRNA) biogenesis, one strand of a approximately 22 nt RNA duplex is preferentially selected for entry into a silencing complex, whereas the other strand, known as the passenger strand or miRNA* strand, is degraded. Recently, some miRNA* sequences were reported as guide miRNAs with abundant expression. Here, we intended to discover evolutionary implication of the fate of miRNA* strand by analyzing miRNA/miRNA* sequences across vertebrates. PRINCIPAL FINDINGS: Mature miRNAs based on gene families were well conserved especially for their seed sequences across vertebrates, while their passenger strands always showed various divergence patterns. The divergence mainly resulted from divergence of different animal species, homologous miRNA genes and multicopy miRNA hairpin precursors. Some miRNA* sequences were phylogenetically conserved in seed and anchor sequences similar to mature miRNAs, while others revealed high levels of nucleotide divergence despite some of their partners were highly conserved. Most of those miRNA precursors that could generate abundant miRNAs from both strands always were well conserved in sequences of miR-#-5p and miR-#-3p, especially for their seed sequences. CONCLUSIONS: The final fate of miRNA* strand, either degraded as merely carrier strand or expressed abundantly as potential functional guide miRNA, may be destined across evolution. Well-conserved miRNA* strands, particularly conservation in seed sequences, maybe afford potential opportunities for contributing to regulation network. The study will broaden our understanding of potential functional miRNA* species

Navigating the unexplored seascape of pre-miRNA candidates in single-genome approaches.

International audienceMOTIVATION: The computational search for novel miRNA precursors often involves some sort of structural analysis with the aim of identifying which type of structures are prone to being recognised and processed by the cellular miRNA-maturation machinery. A natural way to tackle this problem is to perform clustering over the candidate structures along with known miRNA precursor structures. Mixed clusters allows then the identification of candidates that are similar to known precursors. Given the large number of pre-miRNA candidates that can be identified in single-genome approaches, even after applying several filters for precursor robustness and stability, a conventional structural clustering approach is unfeasible. RESULTS: We propose a method to represent candidate structures in a feature space which summarises key sequence/structure characteristics of each candidate. We demonstrate that proximity in this feature space is related to sequence/structure similarity, and we select candidates which have a high similarity to known precursors. Additional filtering steps are then applied to further reduce the number of candidates to those with greater transcriptional potential. Our method is compared to another single-genome method (TripletSVM) in two datasets, showing better performance in one and comparable performance in the other, for larger training sets. Additionally, we show that our approach allows for a better interpretation of the results.Availability and Implementation: The MinDist method is implemented using Perl scripts and is freely available at http://www.cravela.org/?mindist=1. CONTACT: [email protected]