The \u3cem\u3elet-7\u3c/em\u3e MicroRNA Family Members \u3cem\u3emir\u3c/em\u3e-48, \u3cem\u3emir\u3c/em\u3e-84, and mir-241 Function Together to Regulate Developmental Timing in \u3cem\u3eCaenorhabditis elegans\u3c/em\u3e

The microRNA let-7 is a critical regulator of developmental timing events at the larval-to-adult transition in C. elegans. Recently, microRNAs with sequence similarity to let-7 have been identified. We find that doubly mutant animals lacking the let-7 family microRNA genes mir-48 and mir-84 exhibit retarded molting behavior and retarded adult gene expression in the hypodermis. Triply mutant animals lacking mir-48, mir-84, and mir-241 exhibit repetition of L2-stage events in addition to retarded adult-stage events. mir-48, mir-84, and mir-241 function together to control the L2-to-L3 transition, likely by base pairing to complementary sites in the hbl-1 3′ UTR and downregulating hbl-1 activity. Genetic analysis indicates that mir-48, mir-84, and mir-241 specify the timing of the L2-to-L3 transition in parallel to the heterochronic genes lin-28 and lin-46. These results indicate that let-7 family microRNAs function in combination to affect both early and late developmental timing decisions

Most \u3cem\u3eCaenorhabditis elegans\u3c/em\u3e MicroRNAs are Individually Not Essential for Development or Viability

MicroRNAs (miRNAs), a large class of short noncoding RNAs found in many plants and animals, often act to post-transcriptionally inhibit gene expression. We report the generation of deletion mutations in 87 miRNA genes in Caenorhabditis elegans, expanding the number of mutated miRNA genes to 95, or 83% of known C. elegans miRNAs. We find that the majority of miRNAs are not essential for the viability or development of C. elegans, and mutations in most miRNA genes do not result in grossly abnormal phenotypes. These observations are consistent with the hypothesis that there is significant functional redundancy among miRNAs or among gene pathways regulated by miRNAs. This study represents the first comprehensive genetic analysis of miRNA function in any organism and provides a unique, permanent resource for the systematic study of miRNAs

Segmental chromosomal alterations have prognostic impact in neuroblastoma: a report from the INRG project

Background: In the INRG dataset, the hypothesis that any segmental chromosomal alteration might be of prognostic impact in neuroblastoma without MYCN amplification (MNA) was tested. Methods: The presence of any segmental chromosomal alteration (chromosome 1p deletion, 11q deletion and/or chromosome 17q gain) defined a segmental genomic profile. Only tumours with a confirmed unaltered status for all three chromosome arms were considered as having no segmental chromosomal alterations. Results: Among the 8800 patients in the INRG database, a genomic type could be attributed for 505 patients without MNA: 397 cases had a segmental genomic type, whereas 108 cases had an absence of any segmental alteration. A segmental genomic type was more frequent in patients >18 months and in stage 4 disease (P<0.0001). In univariate analysis, 11q deletion, 17q gain and a segmental genomic type were associated with a poorer event-free survival (EFS) (P<0.0001, P=0.0002 and P<0.0001, respectively). In multivariate analysis modelling EFS, the parameters age, stage and a segmental genomic type were retained in the model, whereas the individual genetic markers were not (P<0.0001 and RR=2.56; P=0.0002 and RR=1.8; P=0.01 and RR=1.7, respectively). Conclusion: A segmental genomic profile, rather than the single genetic markers, adds prognostic information to the clinical markers age and stage in neuroblastoma patients without MNA, underlining the importance of pangenomic studies

International consensus for neuroblastoma molecular diagnostics: report from the International Neuroblastoma Risk Group (INRG) Biology Committee

Neuroblastoma serves as a paradigm for utilising tumour genomic data for determining patient prognosis and treatment allocation. However, before the establishment of the International Neuroblastoma Risk Group (INRG) Task Force in 2004, international consensus on markers, methodology, and data interpretation did not exist, compromising the reliability of decisive genetic markers and inhibiting translational research efforts. The objectives of the INRG Biology Committee were to identify highly prognostic genetic aberrations to be included in the new INRG risk classification schema and to develop precise definitions, decisive biomarkers, and technique standardisation. The review of the INRG database (n=8800 patients) by the INRG Task Force finally enabled the identification of the most significant neuroblastoma biomarkers. In addition, the Biology Committee compared the standard operating procedures of different cooperative groups to arrive at international consensus for methodology, nomenclature, and future directions. Consensus was reached to include MYCN status, 11q23 allelic status, and ploidy in the INRG classification system on the basis of an evidence-based review of the INRG database. Standardised operating procedures for analysing these genetic factors were adopted, and criteria for proper nomenclature were developed. Neuroblastoma treatment planning is highly dependant on tumour cell genomic features, and it is likely that a comprehensive panel of DNA-based biomarkers will be used in future risk assignment algorithms applying genome-wide techniques. Consensus on methodology and interpretation is essential for uniform INRG classification and will greatly facilitate international and cooperative clinical and translational research studies

miR-146a is a significant brake on autoimmunity, myeloproliferation, and cancer in mice

Excessive or inappropriate activation of the immune system can be deleterious to the organism, warranting multiple molecular mechanisms to control and properly terminate immune responses. MicroRNAs (miRNAs), ~22-nt-long noncoding RNAs, have recently emerged as key posttranscriptional regulators, controlling diverse biological processes, including responses to non-self. In this study, we examine the biological role of miR-146a using genetically engineered mice and show that targeted deletion of this gene, whose expression is strongly up-regulated after immune cell maturation and/or activation, results in several immune defects. Collectively, our findings suggest that miR-146a plays a key role as a molecular brake on inflammation, myeloid cell proliferation, and oncogenic transformation

miRò: a miRNA knowledge base

miRò is a web-based knowledge base that provides users with miRNA–phenotype associations in humans. It integrates data from various online sources, such as databases of miRNAs, ontologies, diseases and targets, into a unified database equipped with an intuitive and flexible query interface and data mining facilities. The main goal of miRò is the establishment of a knowledge base which allows non-trivial analysis through sophisticated mining techniques and the introduction of a new layer of associations between genes and phenotypes inferred based on miRNAs annotations. Furthermore, a specificity function applied to validated data highlights the most significant associations. The miRò web site is available at: http://ferrolab.dmi.unict.it/miro

Pre-processing and differential expression analysis of Agilent microRNA arrays using the AgiMicroRna Bioconductor library

<p>Abstract</p> <p>Background</p> <p>The main research tool for identifying microRNAs involved in specific cellular processes is gene expression profiling using microarray technology. Agilent is one of the major producers of microRNA arrays, and microarray data are commonly analyzed by using R and the functions and packages collected in the Bioconductor project. However, an analytical package that integrates the specific characteristics of microRNA Agilent arrays has been lacking.</p> <p>Results</p> <p>This report presents the new bioinformatic tool <it>AgiMicroRNA </it>for the pre-processing and differential expression analysis of Agilent microRNA array data. The software is implemented in the open-source statistical scripting language R and is integrated in the Bioconductor project (<url>http://www.bioconductor.org</url>) under the GPL license. For the pre-processing of the microRNA signal, <it>AgiMicroRNA </it>incorporates the <it>robust multiarray average algorithm</it>, a method that produces a summary measure of the microRNA expression using a linear model that takes into account the probe affinity effect. To obtain a normalized microRNA signal useful for the statistical analysis, <it>AgiMicroRna </it>offers the possibility of employing either the processed signal estimated by the <it>robust multiarray average algorithm </it>or the processed signal produced by the Agilent image analysis software. The <it>AgiMicroRNA </it>package also incorporates different graphical utilities to assess the quality of the data. <it>AgiMicroRna </it>uses the linear model features implemented in the <it>limma </it>package to assess the differential expression between different experimental conditions and provides links to the <it>miRBase </it>for those microRNAs that have been declared as significant in the statistical analysis.</p> <p>Conclusions</p> <p><it>AgiMicroRna </it>is a rational collection of Bioconductor functions that have been wrapped into specific functions in order to ease and systematize the pre-processing and statistical analysis of Agilent microRNA data. The development of this package contributes to the Bioconductor project filling the gap in microRNA array data analysis.</p

MIR376A is a regulator of starvation-induced autophagy

Background: Autophagy is a vesicular trafficking process responsible for the degradation of long-lived, misfolded or abnormal proteins, as well as damaged or surplus organelles. Abnormalities of the autophagic activity may result in the accumulation of protein aggregates, organelle dysfunction, and autophagy disorders were associated with various diseases. Hence, mechanisms of autophagy regulation are under exploration. Methods: Over-expression of hsa-miR-376a1 (shortly MIR376A) was performed to evaluate its effects on autophagy. Autophagy-related targets of the miRNA were predicted using Microcosm Targets and MIRanda bioinformatics tools and experimentally validated. Endogenous miRNA was blocked using antagomirs and the effects on target expression and autophagy were analyzed. Luciferase tests were performed to confirm that 3’ UTR sequences in target genes were functional. Differential expression of MIR376A and the related MIR376B was compared using TaqMan quantitative PCR. Results: Here, we demonstrated that, a microRNA (miRNA) from the DlkI/Gtl2 gene cluster, MIR376A, played an important role in autophagy regulation. We showed that, amino acid and serum starvation-induced autophagy was blocked by MIR376A overexpression in MCF-7 and Huh-7 cells. MIR376A shared the same seed sequence and had overlapping targets with MIR376B, and similarly blocked the expression of key autophagy proteins ATG4C and BECN1 (Beclin 1). Indeed, 3’ UTR sequences in the mRNA of these autophagy proteins were responsive to MIR376A in luciferase assays. Antagomir tests showed that, endogenous MIR376A was participating to the control of ATG4C and BECN1 transcript and protein levels. Moreover, blockage of endogenous MIR376A accelerated starvation-induced autophagic activity. Interestingly, MIR376A and MIR376B levels were increased with different kinetics in response to starvation stress and tissue-specific level differences were also observed, pointing out to an overlapping but miRNA-specific biological role. Conclusions: Our findings underline the importance of miRNAs encoded by the DlkI/Gtl2 gene cluster in stress-response control mechanisms, and introduce MIR376A as a new regulator of autophagy

MicroRNAs and Developmental Robustness: A New Layer Is Revealed

MicroRNAs provide a new layer of regulation to ensure that a developmental program of programmed cell death yields a reproducible outcome in spite of perturbations to the system

miRNA Regulatory Circuits in ES Cells Differentiation: A Chemical Kinetics Modeling Approach

MicroRNAs (miRNAs) play an important role in gene regulation for Embryonic Stem cells (ES cells), where they either down-regulate target mRNA genes by degradation or repress protein expression of these mRNA genes by inhibiting translation. Well known tables TargetScan and miRanda may predict quite long lists of potential miRNAs inhibitors for each mRNA gene, and one of our goals was to strongly narrow down the list of mRNA targets potentially repressed by a known large list of 400 miRNAs. Our paper focuses on algorithmic analysis of ES cells microarray data to reliably detect repressive interactions between miRNAs and mRNAs. We model, by chemical kinetics equations, the interaction architectures implementing the two basic silencing processes of miRNAs, namely “direct degradation” or “translation inhibition” of targeted mRNAs. For each pair (M,G) of potentially interacting miRMA gene M and mRNA gene G, we parameterize our associated kinetic equations by optimizing their fit with microarray data. When this fit is high enough, we validate the pair (M,G) as a highly probable repressive interaction. This approach leads to the computation of a highly selective and drastically reduced list of repressive pairs (M,G) involved in ES cells differentiation