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.     

Experimental validation of miRNA targets

MicroRNAs are natural, single-stranded, small RNA molecules that regulate gene expression by binding to target mRNAs and suppress its translation or initiate its degradation. In contrast to the identification and validation of many miRNA genes is the lack of experimental evidence identifying their corresponding mRNA targets. The most fundamental challenge in miRNA biology is to define the rules of miRNA target recognition. This is critical since the biological role of individual miRNAs will be dictated by the mRNAs that they regulate. Therefore, only as target mRNAs are validated will it be possible to establish commonalities that will enable more precise predictions of miRNA/mRNA interactions. Currently there is no clear agreement as to what experimental procedures should be followed to demonstrate that a given mRNA is a target of a specific miRNA. Therefore, this review outlines several methods by which to validate miRNA targets. Additionally, we propose that multiple criteria should be met before miRNA target validation should be considered "confirmed."     

MicroRNAs and intestinal pathophysiology

MicroRNAs (miRNAs) represent an abundant class of endogenously expressed small RNAs, which is believed to control the expression of proteins through specific interaction with their mRNAs. MiRNAs are non-coding RNAs of 18 to 24 nucleotides that negatively regulate target mRNAs by binding to their 3'-untranslated regions (UTR). Most eukaryotic cells utilize miRNA to regulate vital functions such as cell differentiation, proliferation or apopotosis. The diversity of miRNAs and of their mRNA targets strongly indicate that they play a key role in the regulation of protein expression. To date, more than 500 different miRNAs have been identified in animals and plants. There are at least 326 miRNAs in the human genome, comprising 1-4% of all expressed human genes, which makes miRNAs one of the largest classes of gene regulators. A single miRNA can bind to and regulate many different mRNA targets and, conversely, several different miRNAs can bind to and cooperatively control a single mRNA target. The correlation between the expression of miRNAs and their effects on tumorigenesis and on the proliferation of cancer cells is beginning to gain experimental evidences. Recent studies showed that abnormal expression of miRNAs represents a common feature of cancer cells and that they can function as tumor suppressor genes or as oncogenes. Therefore, this diversity of action for miRNAs on several target genes could be one of the common mechanisms involved in the deregulation of protein expression observed during intestinal disorders. In this review, the emergent functions of miRNAs in colorectal cancer and their potential role in the intestinal inflammatory process are discussed.     

A dictionary on microRNAs and their putative target pathways

While in the last decade mRNA expression profiling was among the most popular research areas, over the past years the study of non-coding RNAs, especially microRNAs (miRNAs), has gained increasing interest. For almost 900 known human miRNAs hundreds of pretended targets are known. However, there is only limited knowledge about putative systemic effects of changes in the expression of miRNAs and their regulatory influence. We determined for each known miRNA the biochemical pathways in the KEGG and TRANSPATH database and the Gene Ontology categories that are enriched with respect to its target genes. We refer to these pathways and categories as target pathways of the corresponding miRNA. Investigating target pathways of miRNAs we found a strong relation to disease-related regulatory pathways, including mitogen-activated protein kinase (MAPK) signaling cascade, Transforming growth factor (TGF)-beta signaling pathway or the p53 network. Performing a sophisticated analysis of differentially expressed genes of 13 cancer data sets extracted from gene expression omnibus (GEO) showed that targets of specific miRNAs were significantly deregulated in these sets. The respective miRNA target analysis is also a novel part of our gene set analysis pipeline GeneTrail. Our study represents a comprehensive theoretical analysis of the relationship between miRNAs and their predicted target pathways. Our target pathways analysis provides a ‘miRNA-target pathway’ dictionary, which enables researchers to identify target pathways of differentially regulated miRNAs.     

A whole-genome RNAi Screen for C. elegans miRNA pathway genes

BACKGROUND: miRNAs are an abundant class of small, endogenous regulatory RNAs. Although it is now appreciated that miRNAs are involved in a broad range of biological processes, relatively little is known about the actual mechanism by which miRNAs downregulate target gene expression. An exploration of which protein cofactors are necessary for a miRNA to downregulate a target gene should reveal more fully the molecular mechanisms by which miRNAs are processed, trafficked, and regulate their target genes. RESULTS: A weak allele of the C. elegans miRNA gene let-7 was used as a sensitized genetic background for a whole-genome RNAi screen to detect miRNA pathway genes, and 213 candidate miRNA pathway genes were identified. About 2/3 of the 61 candidates with the strongest phenotype were validated through genetic tests examining the dependence of the let-7 phenotype on target genes known to function in the let-7 pathway. Biochemical tests for let-7 miRNA production place the function of nearly all of these new miRNA pathway genes downstream of let-7 expression and processing. By monitoring the downregulation of the protein product of the lin-14 mRNA, which is the target of the lin-4 miRNA, we have identified 19 general miRNA pathway genes. CONCLUSIONS: The 213 candidate miRNA pathway genes identified could act at steps that produce and traffic miRNAs or in downstream steps that detect miRNA::mRNA duplexes to regulate mRNA translation. The 19 validated general miRNA pathway genes are good candidates for genes that may define protein cofactors for sorting or targeting miRNA::mRNA duplexes, or for recognizing the miRNA base-paired to the target mRNA to downregulate translation.     

A strategy to rapidly identify the functional targets of microRNAs by combining bioinformatics and mRNA cytoplasmic/nucleic ratios in culture cells

MicroRNAs are approximately 22nt non-coding RNAs that are present in a broad range of multicellular organisms. MicroRNAs play important roles in many biological or pathological processes by regulating the expression of their target genes. The fast and accurate identification of miRNA targets is a bottleneck in the clarification of the function of miRNAs. Here, we established a rapid and accurate strategy to identify miRNA functional target genes by combination of bioinformatic prediction with Cytoplasmic/Nuclear (C/N) ratios of mRNAs. The strategy comprises three steps: bioinformatic prediction, determination of mRNA C/N ratios, and confirmation by Western blotting, and might be suitable to most miRNAs. Our method will make a significant contribution to the study of the biological functions of miRNAs.     

MicroRNA regulation of molecular networks mapped by global microRNA, mRNA, and protein expression in activated T lymphocytes

MicroRNAs (miRNAs) regulate specific immune mechanisms, but their genome-wide regulation of T lymphocyte activation is largely unknown. We performed a multidimensional functional genomics analysis to integrate genome-wide differential mRNA, miRNA, and protein expression as a function of human T lymphocyte activation and time. We surveyed expression of 420 human miRNAs in parallel with genome-wide mRNA expression. We identified a unique signature of 71 differentially expressed miRNAs, 57 of which were previously not known as regulators of immune activation. The majority of miRNAs are upregulated, mRNA expression of these target genes is downregulated, and this is a function of binding multiple miRNAs (combinatorial targeting). Our data reveal that consideration of this complex signature, rather than single miRNAs, is necessary to construct a full picture of miRNA-mediated regulation. Molecular network mapping of miRNA targets revealed the regulation of activation-induced immune signaling. In contrast, pathways populated by genes that are not miRNA targets are enriched for metabolism and biosynthesis. Finally, we specifically validated miR-155 (known) and miR-221 (novel in T lymphocytes) using locked nucleic acid inhibitors. Inhibition of these two highly upregulated miRNAs in CD4(+) T cells was shown to increase proliferation by removing suppression of four target genes linked to proliferation and survival. Thus, multiple lines of evidence link top functional networks directly to T lymphocyte immunity, underlining the value of mapping global gene, protein, and miRNA expression.     

Functional homogeneity in microRNA target heterogeneity--a new sight into human microRNomics

MicroRNomics is a novel genomics that studies the identification, targets, biological functions, etc., of microRNAs (miRNAs) on a genomic scale. Computational target prediction algorithms are important applications in microRNomics. However, the overlaps between target sets predicted by different algorithms for one miRNA are often small. Our work is initiated to find the reasons causing "heterogeneity" and investigate whether the heterogeneous targets are homogeneous on functional levels by integrating similarity metrics. The results suggest that most human miRNAs own heterogeneous targets. The dissimilarity of thermodynamic characteristics and the different treatment of 3'-compensatory sites adopted by algorithms are the main reasons for target "heterogeneity." Meanwhile, we find most miRNA heterogeneous targets are functional homogeneity because of the common principles such as sites conservation and G:U wobble pairs in different algorithms. Our findings reveal the "functional homogeneity in miRNA target heterogeneity." The conclusions provide a perspective of microRNomics on functional levels, which introduce a new sight into human miRNA targets.     

A bioinformatics-based update on microRNAs and their targets in rainbow trout (Oncorhynchus mykiss)

MicroRNAs (miRNAs) participate in various vitally biological processes via controlling target genes activity and thousands of miRNAs have been identified in many species to date, including 18,698 known animal miRNA in miRBase. However, there are only limited studies reported in rainbow trout (Oncorhynchus mykiss) especially via the computational-based approaches. In present study, we systematically investigated the miRNAs in rainbow trout using a well-developed comparative genome-based homologue search. A total of 196 potential miRNAs, belonging to 124 miRNA families, were identified, most of which were firstly reported in rainbow trout. The length of miRNAs ranged from 17 to 24 nt with an average of 20 nt while the length of their precursors varied from 47 to 152 nt with an average of 85 nt. The identified miRNAs were not evenly distributed in each miRNA family, with only one member per family for a majority, and multiple members were also identified for several families. Nucleotide U was dominant in the pre-miRNAs with a percentage of 30.04%. The rainbow trout pre-miRNAs had relatively high negative minimal folding free energy (MFE) and adjusted MFE (AMFE). Not only the mature miRNAs but their precursor sequences are conserved among the living organisms. About 2466 O. mykiss genes were predicted as potential targets for 189 miRNAs. Gene Ontology (GO) analysis showed that nearly 2093, 2107, and 2081 target genes are involved in cellular component, molecular function, and biological processes respectively. KEGG pathway enrichment analysis illuminated that these miRNAs targets might regulate 105 metabolic pathways, including those of purine metabolism, nitrogen metabolism, and oxidative phosphorylation. This study has provided an update on rainbow trout miRNAs and their targets, which represents a foundation for future studies.     

Missing value imputation for microRNA expression data by using a GO-based similarity measure

Missing values are commonly present in microarray data profiles. Instead of discarding genes or samples with incomplete expression level, missing values need to be properly imputed for accurate data analysis. The imputation methods can be roughly categorized as expression level-based and domain knowledge-based. The first type of methods only rely on expression data without the help of external data sources, while the second type incorporates available domain knowledge into expression data to improve imputation accuracy. In recent years, microRNA (miRNA) microarray has been largely developed and used for identifying miRNA biomarkers in complex human disease studies. Similar to mRNA profiles, miRNA expression profiles with missing values can be treated with the existing imputation methods. However, the domain knowledge-based methods are hard to be applied due to the lack of direct functional annotation for miRNAs. With the rapid accumulation of miRNA microarray data, it is increasingly needed to develop domain knowledge-based imputation algorithms specific to miRNA expression profiles to improve the quality of miRNA data analysis. We connect miRNAs with domain knowledge of Gene Ontology (GO) via their target genes, and define miRNA functional similarity based on the semantic similarity of GO terms in GO graphs. A new measure combining miRNA functional similarity and expression similarity is used in the imputation of missing values. The new measure is tested on two miRNA microarray datasets from breast cancer research and achieves improved performance compared with the expression-based method on both datasets. The experimental results demonstrate that the biological domain knowledge can benefit the estimation of missing values in miRNA profiles as well as mRNA profiles. Especially, functional similarity defined by GO terms annotated for the target genes of miRNAs can be useful complementary information for the expression-based method to improve the imputation accuracy of miRNA array data. Our method and data are available to the public upon request.