The imprinted H19 lncRNA antagonizes let-7 microRNAs.

Abundantly expressed in fetal tissues and adult muscle, the developmentally regulated H19 long noncoding RNA (lncRNA) has been implicated in human genetic disorders and cancer. However, how H19 acts to regulate gene function has remained enigmatic, despite the recent implication of its encoded miR-675 in limiting placental growth. We noted that vertebrate H19 harbors both canonical and noncanonical binding sites for the let-7 family of microRNAs, which plays important roles in development, cancer, and metabolism. Using H19 knockdown and overexpression, combined with in vivo crosslinking and genome-wide transcriptome analysis, we demonstrate that H19 modulates let-7 availability by acting as a molecular sponge. The physiological significance of this interaction is highlighted in cultures in which H19 depletion causes precocious muscle differentiation, a phenotype recapitulated by let-7 overexpression. Our results reveal an unexpected mode of action of H19 and identify this lncRNA as an important regulator of the major let-7 family of microRNAs.

Identification of bacterial sRNA regulatory targets using ribosome profiling.

Bacteria express large numbers of non-coding, regulatory RNAs known as 'small RNAs' (sRNAs). sRNAs typically regulate expression of multiple target messenger RNAs (mRNAs) through base-pairing interactions. sRNA:mRNA base-pairing often results in altered mRNA stability and/or altered translation initiation. Computational identification of sRNA targets is challenging due to the requirement for only short regions of base-pairing that can accommodate mismatches. Experimental approaches have been applied to identify sRNA targets on a genomic scale, but these focus only on those targets regulated at the level of mRNA stability. Here, we utilize ribosome profiling (Ribo-seq) to experimentally identify regulatory targets of the Escherichia coli sRNA RyhB. We not only validate a majority of known RyhB targets using the Ribo-seq approach, but also discover many novel ones. We further confirm regulation of a selection of known and novel targets using targeted reporter assays. By mutating nucleotides in the mRNA of a newly discovered target, we demonstrate direct regulation of this target by RyhB. Moreover, we show that Ribo-seq distinguishes between mRNAs regulated at the level of RNA stability and those regulated at the level of translation. Thus, Ribo-seq represents a powerful approach for genome-scale identification of sRNA targets.

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.

Effects of genetic variations on microRNA: target interactions.

Genetic variations within microRNA (miRNA) binding sites can affect miRNA-mediated gene regulation, which may lead to phenotypes and diseases. We perform a transcriptome-scale analysis of genetic variants and miRNA:target interactions identified by CLASH. This analysis reveals that rare variants tend to reside in CDSs, whereas common variants tend to reside in the 3' UTRs. miRNA binding sites are more likely to reside within those targets in the transcriptome with lower variant densities, especially target regions in which nucleotides have low mutation frequencies. Furthermore, an overwhelming majority of genetic variants within or near miRNA binding sites can alter not only the potential of miRNA:target hybridization but also the structural accessibility of the binding sites and flanking regions. These suggest an interpretation for certain associations between genetic variants and diseases, i.e. modulation of miRNA-mediated gene regulation by common or rare variants within or near miRNA binding sites, likely through target structure alterations. Our data will be valuable for discovering new associations among miRNAs, genetic variations and human diseases.

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.

CLIP-based prediction of mammalian microRNA binding sites.

Prediction and validation of microRNA (miRNA) targets are essential for understanding functions of miRNAs in gene regulation. Crosslinking immunoprecipitation (CLIP) allows direct identification of a huge number of Argonaute-bound target sequences that contain miRNA binding sites. By analysing data from CLIP studies, we identified a comprehensive list of sequence, thermodynamic and target structure features that are essential for target binding by miRNAs in the 3' untranslated region (3' UTR), coding sequence (CDS) region and 5' untranslated region (5' UTR) of target messenger RNA (mRNA). The total energy of miRNA:target hybridization, a measure of target structural accessibility, is the only essential feature common for both seed and seedless sites in all three target regions. Furthermore, evolutionary conservation is an important discriminating feature for both seed and seedless sites. These features enabled us to develop novel statistical models for the predictions of both seed sites and broad classes of seedless sites. Through both intra-dataset validation and inter-dataset validation, our approach showed major improvements over established algorithms for predicting seed sites and a class of seedless sites. Furthermore, we observed good performance from cross-species validation, suggesting that our prediction framework can be valuable for broad application to other mammalian species and beyond. Transcriptome-wide binding site predictions enabled by our approach will greatly complement the available CLIP data, which only cover small fractions of transcriptomes and known miRNAs due to non-detectable levels of expression. Software and database tools based on the prediction models have been developed and are available through Sfold web server at http://sfold.wadsworth.org.

MicroRNA binding sites in C. elegans 3' UTRs.

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression. Since the discovery of lin-4, the founding member of the miRNA family, over 360 miRNAs have been identified for Caenorhabditis elegans (C. elegans). Prediction and validation of targets are essential for elucidation of regulatory functions of these miRNAs. For C. elegans, crosslinking immunoprecipitation (CLIP) has been successfully performed for the identification of target mRNA sequences bound by Argonaute protein ALG-1. In addition, reliable annotation of the 3' untranslated regions (3' UTRs) as well as developmental stage-specific expression profiles for both miRNAs and 3' UTR isoforms are available. By utilizing these data, we developed statistical models and bioinformatics tools for both transcriptome-scale and developmental stage-specific predictions of miRNA binding sites in C. elegans 3' UTRs. In performance evaluation via cross validation on the ALG-1 CLIP data, the models were found to offer major improvements over established algorithms for predicting both seed sites and seedless sites. In particular, our top-ranked predictions have a substantially higher true positive rate, suggesting a much higher likelihood of positive experimental validation. A gene ontology analysis of stage-specific predictions suggests that miRNAs are involved in dynamic regulation of biological functions during C. elegans development. In particular, miRNAs preferentially target genes related to development, cell cycle, trafficking, and cell signaling processes. A database for both transcriptome-scale and stage-specific predictions and software for implementing the prediction models are available through the Sfold web server at http://sfold.wadsworth.org.

Expression of heat shock protein 70 in nasopharyngeal carcinomas: different expression patterns correlate with distinct clinical prognosis.

BACKGROUND: Heat shock protein 70, a stress protein, has been implicated in tumor progression. However, its role in nasopharyngeal carcinoma (NPC) progression has not yet been clearly investigated. METHODS: Immunohistochemistry (IHC) was employed to examine the expression patterns of Hsp70, human leukocyte antigen -A (HLA-A) in NPC tissue samples. RESULTS: The expression of Hsp70 exhibited different spatial patterns among nuclear, membrane and cytoplasm in 507 NPC tumor tissues. Kaplan-Meier survival analysis demonstrated that different Hsp70 expression patterns are correlated with different patient outcomes. High membranal and cytoplasmic levels of Hsp70 predicted good survival of patients. In contrast, high nuclear abundance of Hsp70 correlated with poor survival. Moreover, the membranal and cytoplasmic levels of Hsp70 were positively correlated with levels of the MHC I molecule HLA-A. CONCLUSIONS: Different Hsp70 expression patterns had distinct predictive values. The different spatial abundance of Hsp70 may imply its important role in NPC development and provide insight for the development of novel therapeutic strategies involving immunotherapy for NPC.

Sfold Tools for MicroRNA Target Prediction.

Computational prediction of miRNA binding sites on target mRNAs facilitates experimental investigation of miRNA functions. In this chapter, we describe STarMir and STarMirDB, two application modules of the Sfold RNA package. STarMir is a Web server for performing miRNA binding site predictions for mRNA and target sequences submitted by users. STarMirDB is a database of precomputed transcriptome-scale predictions. Both STarMir and STarMirDB provide comprehensive sequence, thermodynamic, and target structure features, a logistic probability as a measure of confidence for each predicted site, and a publication-quality diagram of the predicted miRNA-target hybrid. In addition, STarMir now offers a new quantitative score to address combined regulatory effects of multiple seed and seedless sites. This score provides a quantitative measure of the overall regulatory effects of both seed and seedless sites on the target. STarMir and STarMirDB are freely available to all through the Sfold Web application server at http://sfold.wadsworth.org .

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 .

An extensive network of TET2-targeting MicroRNAs regulates malignant hematopoiesis.

The Ten-Eleven-Translocation 2 (TET2) gene, which oxidates 5-methylcytosine in DNA to 5-hydroxylmethylcytosine (5hmC), is a key tumor suppressor frequently mutated in hematopoietic malignancies. However, the molecular regulation of TET2 expression is poorly understood. We show that TET2 is under extensive microRNA (miRNA) regulation, and such TET2 targeting is an important pathogenic mechanism in hematopoietic malignancies. Using a high-throughput 3' UTR activity screen, we identify >30 miRNAs that inhibit TET2 expression and cellular 5hmC. Forced expression of TET2-targeting miRNAs in vivo disrupts normal hematopoiesis, leading to hematopoietic expansion and/or myeloid differentiation bias, whereas coexpression of TET2 corrects these phenotypes. Importantly, several TET2-targeting miRNAs, including miR-125b, miR-29b, miR-29c, miR-101, and miR-7, are preferentially overexpressed in TET2-wild-type acute myeloid leukemia. Our results demonstrate the extensive roles of miRNAs in functionally regulating TET2 and cellular 5hmC and reveal miRNAs with previously unrecognized oncogenic potential. Our work suggests that TET2-targeting miRNAs might be exploited in cancer diagnosis.

Expression of human leukocyte antigen G is associated with prognosis in nasopharyngeal carcinoma.

Human leukocyte antigen G (HLA-G) has multiple immune regulatory functions including the induction of immune tolerance in malignancies. The roles of HLA-G have not been investigated in nasopharyngeal carcinoma (NPC). This study is aimed to evaluate the role of HLA-G as prognostic factor for NPC patients as well as its role in the immune regulation. Western assays showed high HLA-G expression in NPC cell lines, but low in the immortalized nasopharyngeal epithelial cell line NP69. HLA-G protein was further detected in 79.2% of 552 NPC specimens with immunohistochemistry (IHC), but not in normal nasopharyngeal epithelium tissue. Moreover, high expression of HLA-G predicted poor survival of NPC patients and positively correlated with tumor N classification and recurrence or metastasis. Multivariate analysis indicated that HLA-G was an independent and unfavorable prognostic factor. Furthermore, the presence of CD68+ macrophages and IL-10 were also examined, which are two prognostic markers of NPC and important factors for regulating immune surveillance. The correlations of HLA-G with these two immune factors were revealed in NPC tissues. Taken together, our results suggest that HLA-G is an independent biomarker for NPC prognosis, and HLA-G might contribute to NPC progression, which might jointly regulate immune surveillance in NPC together with macrophages and IL-10.

Face recognition using dual-tree complex wavelet features.

We propose a novel facial representation based on the dual-tree complex wavelet transform for face recognition. It is effective and efficient to represent the geometrical structures in facial image with low redundancy. Moreover, we experimentally verify that the proposed method is more powerful to extract facial features robust against the variations of shift and illumination than the discrete wavelet transform and Gabor wavelet transform.