MicroRNA binding sites in C. elegans 3' UTRs

Astaxanthin Induces Transcriptomic Responses Associated with Lifespan Extension in Caenorhabditis elegans

Astaxanthin is a marine xanthophyll carotenoid which effectively prevents intracellular oxidative stress and has beneficial effects against various human diseases. It has been shown that astaxanthin protects Caenorhabditis elegans (C. elegans) from oxidative damages and extends the lifespan of C. elegans possibly by modulating genes involved in insulin/insulin-like growth factor (IGF) signaling (IIS) and the oxidoreductase system, although the exact mechanisms remain elusive. In this study, RNA sequencing analyses were employed to identify the differentially expressed genes in C. elegans in response to astaxanthin treatment. A total of 190 mRNAs and 6 microRNAs (miRNAs) were significantly changed by astaxanthin treatment in C. elegans. Gene ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that the mRNAs and miRNAs significantly altered by astaxanthin mainly function in innate immunity, lipid metabolism and stress responses, a significant portion of which are related to lifespan regulation in C. elegans. The study revealed novel mRNA and miRNA targets of astaxanthin, providing new insights for understanding the anti-aging mechanisms and the biological function of astaxanthin.

STarMirDB: A database of microRNA binding sites

microRNAs (miRNAs) are an abundant class of small endogenous non-coding RNAs (ncRNAs) of ∼22 nucleotides (nts) in length. These small regulatory molecules are involved in diverse developmental, physiological and pathological processes. miRNAs target mRNAs (mRNAs) for translational repression and/or mRNA degradation. Predictions of miRNA binding sites facilitate experimental validation of miRNA targets. Models developed with data from CLIP studies have been used for predictions of miRNA binding sites in the whole transcriptomes of human, mouse and worm. The prediction results have been assembled into STarMirDB, a new database of miRNA binding sites available at http://sfold.wadsworth.org/starmirDB.php. STarMirDB can be searched by miRNAs or mRNAs separately or in combination. The search results are categorized into seed and seedless sites in 3′ UTR, CDS and 5′ UTR. For each predicted site, STarMirDB provides a comprehensive list of sequence, thermodynamic and target structural features that are known to influence miRNA: target interaction. A high resolution PDF diagram of the conformation of the miRNA:target hybrid is also available for visualization and publication. The results of a database search are available through both an interactive viewer and downloadable text files.

Short interspersed DNA elements and miRNAs: a novel hidden gene regulation layer in zebrafish?

In this study, we investigated by in silico analysis the possible correlation between microRNAs (miRNAs) and Anamnia V-SINEs (a superfamily of short interspersed nuclear elements), which belong to those retroposon families that have been preserved in vertebrate genomes for millions of years and are actively transcribed because they are embedded in the 3' untranslated region (UTR) of several genes. We report the results of the analysis of the genomic distribution of these mobile elements in zebrafish (Danio rerio) and discuss their involvement in generating miRNA gene loci. The computational study showed that the genes predicted to bear V-SINEs can be targeted by miRNAs with a very high hybridization E-value. Gene ontology analysis indicates that these genes are mainly involved in metabolic, membrane, and cytoplasmic signaling pathways. Nearly all the miRNAs that were predicted to target the V-SINEs of these genes, i.e., miR-338, miR-9, miR-181, miR-724, miR-735, and miR-204, have been validated in similar regulatory roles in mammals. The large number of genes bearing a V-SINE involved in metabolic and cellular processes suggests that V-SINEs may play a role in modulating cell responses to different stimuli and in preserving the metabolic balance during cell proliferation and differentiation. Although they need experimental validation, these preliminary results suggest that in the genome of D. rerio, as in other TE families in vertebrates, the preservation of V-SINE retroposons may also have been favored by their putative role in gene network modulation.

STarMir Tools for Prediction of microRNA Binding Sites

MicroRNAs (miRNAs) are a class of endogenous short noncoding RNAs that regulate gene expression by targeting messenger RNAs (mRNAs), which results in translational repression and/or mRNA degradation. As regulatory molecules, miRNAs are involved in many mammalian biological processes and also in the manifestation of certain human diseases. As miRNAs play central role in the regulation of gene expression, understanding miRNA-binding patterns is essential to gain an insight of miRNA mediated gene regulation and also holds promise for therapeutic applications. Computational prediction of miRNA binding sites on target mRNAs facilitates experimental investigation of miRNA functions. This chapter provides protocols for using the STarMir web server for improved predictions of miRNA binding sites on a target mRNA. As an application module of the Sfold RNA package, the current version of STarMir is an implementation of logistic prediction models developed with high-throughput miRNA binding data from cross-linking immunoprecipitation (CLIP) studies. The models incorporated comprehensive thermodynamic, structural, and sequence features, and were found to make improved predictions of both seed and seedless sites, in comparison to the established algorithms (Liu et al., Nucleic Acids Res 41:e138, 2013). Their broad applicability was indicated by their good performance in cross-species validation. STarMir is freely available at http://sfold.wadsworth.org/starmir.html .

Characterization of the mammalian miRNA turnover landscape

Steady state cellular microRNA (miRNA) levels represent the balance between miRNA biogenesis and turnover. The kinetics and sequence determinants of mammalian miRNA turnover during and after miRNA maturation are not fully understood. Through a large-scale study on mammalian miRNA turnover, we report the co-existence of multiple cellular miRNA pools with distinct turnover kinetics and biogenesis properties and reveal previously unrecognized sequence features for fast turnover miRNAs. We measured miRNA turnover rates in eight mammalian cell types with a combination of expression profiling and deep sequencing. While most miRNAs are stable, a subset of miRNAs, mostly miRNA*s, turnovers quickly, many of which display a two-step turnover kinetics. Moreover, different sequence isoforms of the same miRNA can possess vastly different turnover rates. Fast turnover miRNA isoforms are enriched for 5′ nucleotide bias against Argonaute-(AGO)-loading, but also additional 3′ and central sequence features. Modeling based on two fast turnover miRNA*s miR-222-5p and miR-125b-1-3p, we unexpectedly found that while both miRNA*s are associated with AGO, they strongly differ in HSP90 association and sensitivity to HSP90 inhibition. Our data characterize the landscape of genome-wide miRNA turnover in cultured mammalian cells and reveal differential HSP90 requirements for different miRNA*s. Our findings also implicate rules for designing stable small RNAs, such as siRNAs.

STarMir: a web server for prediction of microRNA binding sites

STarMir web server predicts microRNA (miRNA) binding sites on a target ribonucleic acid (RNA). STarMir is an implementation of logistic prediction models developed with miRNA binding data from crosslinking immunoprecipitation (CLIP) studies (Liu,C., Mallick, B., Long, D., Rennie, W.A., Wolenc, A., Carmack, C.S. and Ding, Y. (2013). CLIP-based prediction of mammalian microRNA binding sites. Nucleic Acids Res., 41(14), e138). In both intra-dataset and inter-dataset validations, the models showed major improvements over established algorithms in predictions of both seed and seedless sites. General applicability of the models was indicated by good performance in cross-species validations. The input data for STarMir is processed by the web server to perform prediction of miRNA binding sites, compute comprehensive sequence, thermodynamic and target structure features and a logistic probability as a measure of confidence for each predicted site. For each of seed and seedless sites and for all three regions of a mRNA (3′ UTR, CDS and 5′ UTR), STarMir output includes the computed binding site features, the logistic probability and a publication-quality diagram of the predicted miRNA:target hybrid. The prediction results are available through both an interactive viewer and downloadable text files. As an application module of the Sfold RNA package (http://sfold.wadsworth.org), STarMir is freely available to all at http://sfold.wadsworth.org/starmir.html.