miRTar Hunter: A prediction system for identifying human microRNA target sites

MicroRNAs (miRNAs) are important regulators of gene expression and play crucial roles in many biological processes including apoptosis, differentiation, development, and tumorigenesis. Recent estimates suggest that more than 50% of human protein coding genes may be regulated by miRNAs and that each miRNA may bind to 300–400 target genes. Approximately 1,000 human miRNAs have been identified so far with each having up to hundreds of unique target mRNAs. However, the targets for a majority of these miRNAs have not been identified due to the lack of large-scale experimental detection techniques. Experimental detection of miRNA target sites is a costly and time-consuming process, even though identification of miRNA targets is critical to unraveling their functions in various biological processes. To identify miRNA targets, we developed miRTar Hunter, a novel computational approach for predicting target sites regardless of the presence or absence of a seed match or evolutionary sequence conservation. Our approach is based on a dynamic programming algorithm that incorporates more sequence-specific features and reflects the properties of various types of target sites that determine diverse aspects of complementarities between miRNAs and their targets. We evaluated the performance of our algorithm on 532 known human miRNA:target pairs and 59 experimentally-verified negative miRNA:target pairs, and also compared our method with three popular programs for 481 miRNA:target pairs. miRTar Hunter outperformed three popular existing algorithms in terms of recall and precision, indicating that our unique scheme to quantify the determinants of complementary sites is effective at detecting miRNA targets. miRTar Hunter is now available at http://203.230.194.162/~kbkim.     

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.     

Heavy metal-regulated new microRNAs from rice

MicroRNAs (miRNAs) are a novel class of short, endogenous non-coding small RNAs that have the ability to base pair with their target mRNAs to repress their translation or induce their degradation in both plants and animals. To identify heavy metal stress-regulated novel miRNAs, we constructed a library of small RNAs from rice seedlings that were exposed to toxic levels of cadmium (Cd²⁺). Sequencing of the library and subsequent analysis revealed 19 new miRNAs representing six families. These cloned new rice miRNAs have sequence conservation neither in Arabidopsis nor in any other species. Most of the new rice miRNAs were up- or down-regulated in response to the metal exposure. On the base of sequence complementarity, a total of 34 miRNA targets were predicted, of which 23 targets are functionally annotated and the other 11 records belong to unknown proteins. Some predicted targets of miRNAs are associated with the regulation of the response to heavy metal-induced stresses. In addition to the new miRNAs, we detected nine previously reported miRNAs and 56 other novel endogenous small RNAs in rice. These findings suggest that the number of new miRNAs in rice is unsaturated and some of them may play critical roles in plant responses to environmental stresses.     

Sequence variation of MicroRNAs and their binding sites in Arabidopsis

Major differences exist between plants and animals both in the extent of microRNA (miRNA)-based gene regulation and the sequence complementarity requirements for miRNA-messenger RNA pairing. Whether these differences affect how these sites evolve at the molecular level is unknown. To determine the extent of sequence variation at miRNAs and their targets in a plant species, we resequenced 16 miRNA families (66 miRNAs in total) and all 52 of the characterized binding sites for these miRNAs in the plant model Arabidopsis (Arabidopsis thaliana), accounting for around 50% of the known miRNAs and binding sites in this species. As has been shown previously in humans, we find that both miRNAs and their target binding sites have very low nucleotide variation and divergence compared to their flanking sequences in Arabidopsis, indicating strong purifying selection on these sites in this species. Sequence data flanking the mature miRNAs, however, exhibit normal levels of polymorphism for the accessions in this study and, in some cases, nonneutral evolution or subtle effects on predicted pre-miRNA secondary structure, suggesting that there is raw material for the differential function of miRNA alleles. Overall, our results show that despite differences in the architecture of miRNA-based regulation, miRNAs and their targets are similarly constrained in both plants and animals.     

Identification of MiRNA from Eggplant (Solanum melongena L.) by Small RNA Deep Sequencing and Their Response to Verticillium dahliae Infection

MiRNAs are a class of non-coding small RNAs that play important roles in the regulation of gene expression. Although plant miRNAs have been extensively studied in model systems, less is known in other plants with limited genome sequence data, including eggplant (Solanum melongena L.). To identify miRNAs in eggplant and their response to Verticillium dahliae infection, a fungal pathogen for which clear understanding of infection mechanisms and effective cure methods are currently lacking, we deep-sequenced two small RNA (sRNA) libraries prepared from mock-infected and infected seedlings of eggplants. Specifically, 30,830,792 reads produced 7,716,328 unique miRNAs representing 99 known miRNA families that have been identified in other plant species. Two novel putative miRNAs were predicted with eggplant ESTs. The potential targets of the identified known and novel miRNAs were also predicted based on sequence homology search. It was observed that the length distribution of obtained sRNAs and the expression of 6 miRNA families were obviously different between the two libraries. These results provide a framework for further analysis of miRNAs and their role in regulating plant response to fungal infection and Verticillium wilt in particular.     

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.     

Designing small multiple-target artificial RNAs

MicroRNAs (miRNAs) are naturally occurring small RNAs that regulate the expression of several genes. MiRNAs’ targeting rules are based on sequence complementarity between their mature products and targeted genes’ mRNAs. Based on our present understanding of those rules, we developed an algorithm to design artificial miRNAs to target simultaneously a set of predetermined genes. To validate in silico our algorithm, we tested different sets of genes known to be targeted by a single miRNA. The algorithm finds the seed of the corresponding miRNA among the solutions, which also include the seeds of new artificial miRNA sequences potentially capable of targeting these genes as well. We also validated the functionality of some artificial miRNAs designed to target simultaneously members of the E2F family. These artificial miRNAs reproduced the effects of E2Fs inhibition in both normal human fibroblasts and prostate cancer cells where they inhibited cell proliferation and induced cellular senescence. We conclude that the current miRNA targeting rules based on the seed sequence work to design multiple-target artificial miRNAs. This approach may find applications in both research and therapeutics.