Prediction of both conserved and nonconserved microRNA targets in animals

MOTIVATION: MicroRNAs (miRNAs) are involved in many diverse biological processes and they may potentially regulate the functions of thousands of genes. However, one major issue in miRNA studies is the lack of bioinformatics programs to accurately predict miRNA targets. Animal miRNAs have limited sequence complementarity to their gene targets, which makes it challenging to build target prediction models with high specificity. RESULTS: Here we present a new miRNA target prediction program based on support vector machines (SVMs) and a large microarray training dataset. By systematically analyzing public microarray data, we have identified statistically significant features that are important to target downregulation. Heterogeneous prediction features have been non-linearly integrated in an SVM machine learning framework for the training of our target prediction model, MirTarget2. About half of the predicted miRNA target sites in human are not conserved in other organisms. Our prediction algorithm has been validated with independent experimental data for its improved performance on predicting a large number of miRNA down-regulated gene targets. AVAILABILITY: All the predicted targets were imported into an online database miRDB, which is freely accessible at http://mirdb.org.     

MicroRNAs with analogous target complementarities perform with highly variable efficacies in Arabidopsis

In plants, the silencing efficacy of microRNAs (miRNAs) is thought to be predominantly determined by the degree of complementarity to their target genes. Here, silencing efficacy was determined for Arabidopsis miR159 and four artificial miRNAs (amiRNAs) that all target MYB33/MYB65 with analogous complementarities. As determined through complementation of a loss-of-function mir159 mutant, the amiRNAs displayed highly variable efficacies, none of which was as strong as endogenous miR159. This was despite amiRNA expression levels being many fold-higher than miR159 in wild-type. The results highlight the variable nature of miRNA silencing efficacy in plants, where it appears that factors additional to complementarity strongly impact silencing.     

Improved knockdown from artificial microRNAs in an enhanced miR-155 backbone: a designer's guide to potent multi-target RNAi

Artificial microRNA (amiRNA) sequences embedded in natural microRNA (miRNA) backbones have proven to be useful tools for RNA interference (RNAi). amiRNAs have reduced off-target and toxic effects compared to other RNAi-based methods such as short-hairpin RNAs (shRNA). amiRNAs are often less effective for knockdown, however, compared to their shRNA counterparts. We screened a large empirically-designed amiRNA set in the synthetic inhibitory BIC/miR-155 RNA (SIBR) scaffold and show common structural and sequence-specific features associated with effective amiRNAs. We then introduced exogenous motifs into the basal stem region which increase amiRNA biogenesis and knockdown potency. We call this modified backbone the enhanced SIBR (eSIBR) scaffold. Using chained amiRNAs for multi-gene knockdown, we show that concatenation of miRNAs targeting different genes is itself sufficient for increased knockdown efficacy. Further, we show that eSIBR outperforms wild-type SIBR (wtSIBR) when amiRNAs are chained. Finally, we use a lentiviral expression system in cultured neurons, where we again find that eSIBR amiRNAs are more potent for multi-target knockdown of endogenous genes. eSIBR will be a valuable tool for RNAi approaches, especially for studies where knockdown of multiple targets is desired.     

Sucrose induction of <Emphasis Type="Italic">Arabidopsis</Emphasis> miR398 represses two Cu/Zn superoxide dismutases

MicroRNAs (miRNAs) are approximately 21-nt RNAs that reduce target accumulation through mRNA cleavage or translational repression. Arabidopsis miR398 regulates mRNAs encoding two copper superoxide dismutase (CSD) enzymes and a cytochrome c oxidase subunit. miR398 itself is down-regulated in response to copper and stress. Here we show that miR398 is positively regulated by sucrose, resulting in decreased CSD1 and CSD2 mRNA and protein accumulation. This sucrose regulation is maintained both in the presence and absence of physiologically relevant levels of supplemental copper. Additionally, we show that plants expressing CSD1 and CSD2 mRNAs with altered miR398 complementarity sites display increased mRNA accumulation, whereas CSD1 and CSD2 protein accumulation remain sensitive to miR398 levels, suggesting that miR398 can act as a translational repressor when target site complementarity is reduced. These results reveal a novel miR398 regulatory mechanism and demonstrate that plant miRNA targets can resist miRNA regulation at the mRNA level while maintaining sensitivity at the level of protein accumulation. Our results suggest that even in plants, where miRNAs are thought to act primarily through target mRNA cleavage, monitoring target protein levels along with target mRNA levels is necessary to fully assess the consequences of disrupted miRNA-mRNA pairing. Moreover, the limited complementarity required to maintain robust miR398-directed repression of target protein accumulation suggests that similarly regulated endogenous plant miRNA targets may have eluded detection.     

Systematic identification of microRNA functions by combining target prediction and expression profiling

Target predictions and validations are major obstacles facing microRNA (miRNA) researchers. Animal miRNA target prediction is challenging because of limited miRNA sequence complementarity to the targets. In addition, only a small number of predicted targets have been experimentally validated and the miRNA mechanism is poorly understood. Here we present a novel algorithm for animal miRNA target prediction. The algorithm combines relevant parameters for miRNA target recognition and heuristically assigns different weights to these parameters according to their relative importance. A score calculation scheme is introduced to reflect the strength of each parameter. We also performed microarray time course experiments to identify downregulated genes due to miRNA overexpression. The computational target prediction is combined with the miRNA transfection experiment to systematically identify the gene targets of human miR-124. miR-124 overexpression led to a significant downregulation of many cell cycle related genes. This may be the result of direct suppression of a few cell growth inhibitors at the early stage of miRNA overexpression, and these targeted genes were continuously suppressed over a long period of time. Our high-throughput approach can be generalized to globally identify the targets and functions of other miRNAs.     

Complementary miRNA pairs suggest a regulatory role for miRNA:miRNA duplexes

microRNAs (miRNAs) are 21-22-nucleotide noncoding RNAs that are widely believed to regulate complementary mRNA targets. However, due to the modest amount of pairing involved, only a few out of the hundreds of known animal miRNAs have thus far been connected to mRNA targets. Here, we considered the possibility that miRNAs might regulate non-mRNA targets, namely other miRNAs. To do so, we conducted a systematic assessment of the nearly complete catalogs of animal miRNAs for potential miRNA:miRNA complements. Our analysis uncovered several compelling examples that strongly suggest a function for miRNA duplexes, thus adding a potential layer of regulatory sophistication to the small RNA world. Interestingly, the most striking examples involve miRNAs complementary to members of the K-box family and Brd-box family, two classes of miRNAs previously implicated in regulation of Notch target genes. We emphasize that patterns of nucleotide constraint indicate that miRNA complementarity is not a simple consequence of miRNA:miRNA* complementarity; however, our findings do suggest that the potential regulatory consequences of the latter also deserve investigation.     

Data mining for miRNAs and their targets in the Triticeae.

MicroRNAs (miRNAs) and the mRNA targets of miRNAs were identified by sequence complementarity within a DNA sequence database for species of the Triticeae. Data screening identified 28 miRNA precursor sequences from 15 miRNA families that contained conserved mature miRNA sequences within predicted stem-loop structures. In addition, the identification of 337 target sequences among Triticeae genes provided further evidence of the existence of 26 miRNA families in the cereals. MicroRNA targets included genes that are homologous to known targets in diverse model species as well as novel targets. MicroRNA precursors and targets were identified in 10 related species, though the great majority of them were identified in bread wheat, Triticum aestivum, and barley, Hordeum vulgare, the two species with the largest EST data sets among the Triticeae.