Identification of tissue-specific microRNAs from mouse

MicroRNAs (miRNAs) are a new class of noncoding RNAs, which are encoded as short inverted repeats in the genomes of invertebrates and vertebrates [1, 2]. It is believed that miRNAs are modulators of target mRNA translation and stability, although most target mRNAs remain to be identified. Here we describe the identification of 34 novel miRNAs by tissue- specific cloning of approximately 21-nucleotide RNAs from mouse. Almost all identified miRNAs are conserved in the human genome and are also frequently found in nonmammalian vertebrate genomes, such as pufferfish. In heart, liver, or brain, it is found that a single, tissue-specifically expressed miRNA dominates the population of expressed miRNAs and suggests a role for these miRNAs in tissue specification or cell lineage decisions. Finally, a miRNA was identified that appears to be the fruitfly and mammalian ortholog of C. elegans lin-4 stRNA

SFSSClass: an integrated approach for miRNA based tumor classification

Background: MicroRNA (miRNA) expression profiling data has recently been found to be particularly important in cancer research and can be used as a diagnostic and prognostic tool. Current approaches of tumor classification using miRNA expression data do not integrate the experimental knowledge available in the literature. A judicious integration of such knowledge with effective miRNA and sample selection through a biclustering approach could be an important step in improving the accuracy of tumor classification. Results: In this article, a novel classification technique called SFSSClass is developed that judiciously integrates a biclustering technique SAMBA for simultaneous feature (miRNA) and sample (tissue) selection (SFSS), a cancer-miRNA network that we have developed by mining the literature of experimentally verified cancer-miRNA relationships and a classifier uncorrelated shrunken centroid (USC). SFSSClass is used for classifying multiple classes of tumors and cancer cell lines. In a part of the investigation, poorly differentiated tumors (PDT) having non diagnostic histological appearance are classified while training on more differentiated tumor (MDT) samples. The proposed method is found to outperform the best known accuracy in the literature on the experimental data sets. For example, while the best accuracy reported in the literature for classifying PDT samples is similar to 76.5%, the accuracy of SFSSClass is found to be similar to 82.3%. The advantage of incorporating biclustering integrated with the cancer-miRNA network is evident from the consistently better performance of SFSSClass (integration of SAMBA, cancer-miRNA network and USC) over USC (eg., similar to 70.5% for SFSSClass versus similar to 58.8% in classifying a set of 17 MDT samples from 9 tumor types, similar to 91.7% for SFSSClass versus similar to 75% in classifying 12 cell lines from 6 tumor types and similar to 382.3% for SFSSClass versus similar to 41.2% in classifying 17 PDT samples from 11 tumor types). Conclusion: In this article, we develop the SFSSClass algorithm which judiciously integrates a biclustering technique for simultaneous feature (miRNA) and sample (tissue) selection, the cancer-miRNA network and a classifier. The novel integration of experimental knowledge with computational tools efficiently selects relevant features that have high intra-class and low interclass similarity. The performance of the SFSSClass is found to be significantly improved with respect to the other existing approaches

Use of Tissue-Specific MicroRNA to Control Pathology of Wild-Type Adenovirus without Attenuation of Its Ability to Kill Cancer Cells

Replicating viruses have broad applications in biomedicine, notably in cancer virotherapy and in the design of attenuated vaccines; however, uncontrolled virus replication in vulnerable tissues can give pathology and often restricts the use of potent strains. Increased knowledge of tissue-selective microRNA expression now affords the possibility of engineering replicating viruses that are attenuated at the RNA level in sites of potential pathology, but retain wild-type replication activity at sites not expressing the relevant microRNA. To assess the usefulness of this approach for the DNA virus adenovirus, we have engineered a hepatocyte-safe wild-type adenovirus 5 (Ad5), which normally mediates significant toxicity and is potentially lethal in mice. To do this, we have included binding sites for hepatocyte-selective microRNA mir-122 within the 39 UTR of the E1A transcription cassette. Imaging versions of these viruses, produced by fusing E1A with luciferase, showed that inclusion of mir-122 binding sites caused up to 80-fold decreased hepatic expression of E1A following intravenous delivery to mice. Animals administered a ten-times lethal dose of wild-type Ad5 (5610 10 viral particles/mouse) showed substantial hepatic genome replication and extensive liver pathology, while inclusion of 4 microRNA binding sites decreased replication 50-fold and virtually abrogated liver toxicity. This modified wild-type virus retained full activity within cancer cells and provided a potent, liver-safe oncolytic virus. In addition to providing many potent new viruses for cancer virotherapy, microRNA control of virus replication should provide a new strategy for designing safe attenuated vaccines applied across a broad range of viral disease

The database of experimentally supported targets: a functional update of TarBase

TarBase5.0 is a database which houses a manually curated collection of experimentally supported microRNA (miRNA) targets in several animal species of central scientific interest, plants and viruses. MiRNAs are small non-coding RNA molecules that exhibit an inhibitory effect on gene expression, interfering with the stability and translational efficiency of the targeted mature messenger RNAs. Even though several computational programs exist to predict miRNA targets, there is a need for a comprehensive collection and description of miRNA targets with experimental support. Here we introduce a substantially extended version of this resource. The current version includes more than 1300 experimentally supported targets. Each target site is described by the miRNA that binds it, the gene in which it occurs, the nature of the experiments that were conducted to test it, the sufficiency of the site to induce translational repression and/or cleavage, and the paper from which all these data were extracted. Additionally, the database is functionally linked to several other relevant and useful databases such as Ensembl, Hugo, UCSC and SwissProt. The TarBase5.0 database can be queried or downloaded from http://microrna.gr/tarbase

MicroRNAs in cardiac arrhythmia: DNA sequence variation of MiR-1 and MiR-133A in long QT syndrome.

Long QT syndrome (LQTS) is a genetic cardiac condition associated with prolonged ventricular repolarization, primarily a result of perturbations in cardiac ion channels, which predisposes individuals to life-threatening arrhythmias. Using DNA screening and sequencing methods, over 700 different LQTS-causing mutations have been identified in 13 genes worldwide. Despite this, the genetic cause of 30-50% of LQTS is presently unknown. MicroRNAs (miRNAs) are small (∼ 22 nucleotides) noncoding RNAs which post-transcriptionally regulate gene expression by binding complementary sequences within messenger RNAs (mRNAs). The human genome encodes over 1800 miRNAs, which target about 60% of human genes. Consequently, miRNAs are likely to regulate many complex processes in the body, indeed aberrant expression of various miRNA species has been implicated in numerous disease states, including cardiovascular diseases. MiR-1 and MiR-133A are the most abundant miRNAs in the heart and have both been reported to regulate cardiac ion channels. We hypothesized that, as a consequence of their role in regulating cardiac ion channels, genetic variation in the genes which encode MiR-1 and MiR-133A might explain some cases of LQTS. Four miRNA genes (miR-1-1, miR-1-2, miR-133a-1 and miR-133a-2), which encode MiR-1 and MiR-133A, were sequenced in 125 LQTS probands. No genetic variants were identified in miR-1-1 or miR-133a-1; but in miR-1-2 we identified a single substitution (n.100A> G) and in miR-133a-2 we identified two substitutions (n.-19G> A and n.98C> T). None of the variants affect the mature miRNA products. Our findings indicate that sequence variants of miR-1-1, miR-1-2, miR-133a-1 and miR-133a-2 are not a cause of LQTS in this cohort

ANÁLISIS DE INSTRUMENTOS DE MEDICIÓN DEL PENSAMIENTO CRÍTICO

Critical thinking is a relevant ability nowadays in higher education, but there is a lack of consensus on its definitions and assessment instruments. This article offers a conceptual and methodological review about the instruments used to measure critical thinking, in order to generate a discussion that allows a better understanding and appreciation of the aspects that are considered in this skill. The methodology consisted of a systematic review of studies in databases, selecting 31 studies out of 97 founded, and 8 of them for deep analysis; atopic content analysis in definitions and test characteristics is also used. Results show the existence of many differences in definitions and assessments of critical thinking, with a variety of tests and little consensus on the measured components. The need of an integrative model of Critical Thinking, considering cognitive, metacognitive and dispositional skills is discussed.El pensamiento crítico es una competencia relevante hoy en día en la formación universitaria, con escaso consenso conceptual y metodológico en sus instrumentos de medición. En este artículo se ofrece una revisión acerca de los instrumentos que se han utilizado para medir el pensamiento crítico, con la finalidad de generar una discusión que permita una mejor comprensión y valoración de los aspectos que componen esta habilidad. La metodología utilizada consiste en una revisión sistemática de estudios en bases de datos, seleccionando 31 estudios de 97 encontrados, y analizando en profundidad ocho de ellos; se utilizó además, análisis de contenido temático para las definiciones y características de instrumentos. Los resultados señalan la existencia de divergencias a la hora de definir y evaluar el pensamiento crítico, con variedad de instrumentos y escaso consenso en los componentes medidos. Se discute la necesidad de lograr un modelo de Pensamiento Crítico integrado que considere habilidades cognitivas, metacognitivas y disposicionales

Quantitative Analysis of miRNA Expression in Seven Human Foetal and Adult Organs

miRNAs have been found to repress gene expression at posttranscriptional level in cells. Studies have shown that expression of miRNAs is tissue-specific and developmental-stage-specific. The mechanism behind this could be explained by miRNA pathways. In this study, totally 54 miRNAs were analysed in 7 matched human foetal and adult organs (brain, colon, heart, kidney, liver, lung and spleen) using real-time PCR. Quantitative analysis showed that a big proportion of the 54 miRNAs have higher general expression in the organs of the foetal period than the adult period, with the exception of the heart. The miRNA gene promoter methylation level in the adult stages was higher than in the foetal stages. Moreover, there is a high general expression level of several miRNAs in both stages of brain, kidney, liver, lung and spleen, but not seen in colon and heart. Our results indicate that the miRNAs may play a bigger role in the foetal stage than the adult stage of brain, colon, kidney, liver, lung and spleen. The majority of the miRNAs analysed may play an important role in the growth and development of brain, kidney, liver, lung and spleen. However, a minority of the miRNAs may be functional in colon and heart

Preferential regulation of stably expressed genes in the human genome suggests a widespread expression buffering role of microRNAs

In this study, we comprehensively explored the stably expressed genes (SE genes) and fluctuant genes (FL genes) in the human genome by a meta-analysis of large scale microarray data. We found that these genes have distinct function distributions. miRNA targets are shown to be significantly enriched in SE genes by using propensity analysis of miRNA regulation, supporting the hypothesis that miRNAs can buffer whole genome expression fluctuation. The expression-buffering effect of miRNA is independent of the target site number within the 3'-untranslated region. In addition, we found that gene expression fluctuation is positively correlated with the number of transcription factor binding sites in the promoter region, which suggests that coordination between transcription factors and miRNAs leads to balanced responses to external perturbations

miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments

Next-generation sequencing allows now the sequencing of small RNA molecules and the estimation of their expression levels. Consequently, there will be a high demand of bioinformatics tools to cope with the several gigabytes of sequence data generated in each single deep-sequencing experiment. Given this scene, we developed miRanalyzer, a web server tool for the analysis of deep-sequencing experiments for small RNAs. The web server tool requires a simple input file containing a list of unique reads and its copy numbers (expression levels). Using these data, miRanalyzer (i) detects all known microRNA sequences annotated in miRBase, (ii) finds all perfect matches against other libraries of transcribed sequences and (iii) predicts new microRNAs. The prediction of new microRNAs is an especially important point as there are many species with very few known microRNAs. Therefore, we implemented a highly accurate machine learning algorithm for the prediction of new microRNAs that reaches AUC values of 97.9% and recall values of up to 75% on unseen data. The web tool summarizes all the described steps in a single output page, which provides a comprehensive overview of the analysis, adding links to more detailed output pages for each analysis module. miRanalyzer is available at http://web.bioinformatics.cicbiogune.es/microRNA/