mirMark: a site-level and UTR-level classifier for miRNA target prediction

MiRNAs play important roles in many diseases including cancers. However computational prediction of miRNA target genes is challenging and the accuracies of existing methods remain poor. We report mirMark, a new machine learning-based method of miRNA target prediction at the site and UTR levels. This method uses experimentally verified miRNA targets from miRecords and mirTarBase as training sets and considers over 700 features. By combining Correlation-based Feature Selection with a variety of statistical or machine learning methods for the site- and UTR-level classifiers, mirMark significantly improves the overall predictive performance compared to existing publicly available methods. MirMark is available from https://github.com/lanagarmire/MirMark.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0500-5) contains supplementary material, which is available to authorized users.     

PROmiRNA: a new miRNA promoter recognition method uncovers the complex regulation of intronic miRNAs

The regulation of intragenic miRNAs by their own intronic promoters is one of the open problems of miRNA biogenesis. Here, we describe PROmiRNA, a new approach for miRNA promoter annotation based on a semi-supervised statistical model trained on deepCAGE data and sequence features. We validate our results with existing annotation, PolII occupancy data and read coverage from RNA-seq data. Compared to previous methods PROmiRNA increases the detection rate of intronic promoters by 30%, allowing us to perform a large-scale analysis of their genomic features, as well as elucidate their contribution to tissue-specific regulation. PROmiRNA can be downloaded from http://promirna.molgen.mpg.de.     

Hedgehog Signaling Strength Is Orchestrated by the mir-310 Cluster of MicroRNAs in Response to Diet

Since the discovery of microRNAs (miRNAs) only two decades ago, they have emerged as an essential component of the gene regulatory machinery. miRNAs have seemingly paradoxical features: a single miRNA is able to simultaneously target hundreds of genes, while its presence is mostly dispensable for animal viability under normal conditions. It is known that miRNAs act as stress response factors; however, it remains challenging to determine their relevant targets and the conditions under which they function. To address this challenge, we propose a new workflow for miRNA function analysis, by which we found that the evolutionarily young miRNA family, the mir-310s (mir-310/mir-311/mir-312/mir-313), are important regulators of Drosophila metabolic status. mir-310s-deficient animals have an abnormal diet-dependent expression profile for numerous diet-sensitive components, accumulate fats, and show various physiological defects. We found that the mir-310s simultaneously repress the production of several regulatory factors (Rab23, DHR96, and Ttk) of the evolutionarily conserved Hedgehog (Hh) pathway to sharpen dietary response. As the mir-310s expression is highly dynamic and nutrition sensitive, this signal relay model helps to explain the molecular mechanism governing quick and robust Hh signaling responses to nutritional changes. Additionally, we discovered a new component of the Hh signaling pathway in Drosophila, Rab23, which cell autonomously regulates Hh ligand trafficking in the germline stem cell niche. How organisms adjust to dietary fluctuations to sustain healthy homeostasis is an intriguing research topic. These data are the first to report that miRNAs can act as executives that transduce nutritional signals to an essential signaling pathway. This suggests miRNAs as plausible therapeutic agents that can be used in combination with low calorie and cholesterol diets to manage quick and precise tissue-specific responses to nutritional changes.     

Investigating microRNA-Target Interaction-Supported Tissues in Human Cancer Tissues Based on miRNA and Target Gene Expression Profiling

Recent studies have revealed that a small non-coding RNA, microRNA (miRNA) down-regulates its mRNA targets. This effect is regarded as an important role in various biological processes. Many studies have been devoted to predicting miRNA-target interactions. These studies indicate that the interactions may only be functional in some specific tissues, which depend on the characteristics of an miRNA. No systematic methods have been established in the literature to investigate the correlation between miRNA-target interactions and tissue specificity through microarray data. In this study, we propose a method to investigate miRNA-target interaction-supported tissues, which is based on experimentally validated miRNA-target interactions. The tissue specificity results by our method are in accordance with the experimental results in the literature.

Availability and Implementation

Our analysis results are available at http://tsmti.mbc.nctu.edu.tw/ and http://www.stat.nctu.edu.tw/hwang/tsmti.html.     

Enhancing protein-vitamin binding residues prediction by multiple heterogeneous subspace SVMs ensemble

Background

Vitamins are typical ligands that play critical roles in various metabolic processes. The accurate identification of the vitamin-binding residues solely based on a protein sequence is of significant importance for the functional annotation of proteins, especially in the post-genomic era, when large volumes of protein sequences are accumulating quickly without being functionally annotated.

Results

In this paper, a new predictor called TargetVita is designed and implemented for predicting protein-vitamin binding residues using protein sequences. In TargetVita, features derived from the position-specific scoring matrix (PSSM), predicted protein secondary structure, and vitamin binding propensity are combined to form the original feature space; then, several feature subspaces are selected by performing different feature selection methods. Finally, based on the selected feature subspaces, heterogeneous SVMs are trained and then ensembled for performing prediction.

Conclusions

The experimental results obtained with four separate vitamin-binding benchmark datasets demonstrate that the proposed TargetVita is superior to the state-of-the-art vitamin-specific predictor, and an average improvement of 10% in terms of the Matthews correlation coefficient (MCC) was achieved over independent validation tests. The TargetVita web server and the datasets used are freely available for academic use at http://csbio.njust.edu.cn/bioinf/TargetVita or http://www.csbio.sjtu.edu.cn/bioinf/TargetVita.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-297) contains supplementary material, which is available to authorized users.     

miRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data

Background

Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction.

Result

We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram.

Conclusions

We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.miRPlant and its manual are freely available at http://www.australianprostatecentre.org/research/software/mirplant or http://sourceforge.net/projects/mirplant/.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-275) contains supplementary material, which is available to authorized users.     

Translational Control of the Oogenic Program by Components of OMA Ribonucleoprotein Particles in Caenorhabditis elegans

The oocytes of most sexually reproducing animals arrest in meiotic prophase I. Oocyte growth, which occurs during this period of arrest, enables oocytes to acquire the cytoplasmic components needed to produce healthy progeny and to gain competence to complete meiosis. In the nematode Caenorhabditis elegans, the major sperm protein hormone promotes meiotic resumption (also called meiotic maturation) and the cytoplasmic flows that drive oocyte growth. Prior work established that two related TIS11 zinc-finger RNA-binding proteins, OMA-1 and OMA-2, are redundantly required for normal oocyte growth and meiotic maturation. We affinity purified OMA-1 and identified associated mRNAs and proteins using genome-wide expression data and mass spectrometry, respectively. As a class, mRNAs enriched in OMA-1 ribonucleoprotein particles (OMA RNPs) have reproductive functions. Several of these mRNAs were tested and found to be targets of OMA-1/2-mediated translational repression, dependent on sequences in their 3′-untranslated regions (3′-UTRs). Consistent with a major role for OMA-1 and OMA-2 in regulating translation, OMA-1-associated proteins include translational repressors and activators, and some of these proteins bind directly to OMA-1 in yeast two-hybrid assays, including OMA-2. We show that the highly conserved TRIM-NHL protein LIN-41 is an OMA-1-associated protein, which also represses the translation of several OMA-1/2 target mRNAs. In the accompanying article in this issue, we show that LIN-41 prevents meiotic maturation and promotes oocyte growth in opposition to OMA-1/2. Taken together, these data support a model in which the conserved regulators of mRNA translation LIN-41 and OMA-1/2 coordinately control oocyte growth and the proper spatial and temporal execution of the meiotic maturation decision.     

TargetCompare: A web interface to compare simultaneous miRNAs targets

MicroRNAs (miRNAs) are small non-coding nucleotide sequences between 17 and 25 nucleotides in length that primarily function in the regulation of gene expression. A since miRNA has thousand of predict targets in a complex, regulatory cell signaling network. Therefore, it is of interest to study multiple target genes simultaneously. Hence, we describe a web tool (developed using Java programming language and MySQL database server) to analyse multiple targets of pre-selected miRNAs. We cross validated the tool in eight most highly expressed miRNAs in the antrum region of stomach. This helped to identify 43 potential genes that are target of at least six of the referred miRNAs. The developed tool aims to reduce the randomness and increase the chance of selecting strong candidate target genes and miRNAs responsible for playing important roles in the studied tissue.

Availability

http://lghm.ufpa.br/targetcompare     

Birds do it,bees do it,worms and ciliates do it too: DNA methylation from unexpected corners of the tree of life

Studies describing intricate patterns of DNA methylation in nematode and ciliate are controversial due to the uncertainty of genomic evolutionary conservation of DNA methylation enzymes.See related research articles http://genomebiology.com/2012/13/10/R99 and http://genomebiology.com/2012/13/10/R100     

Of RNA-binding proteins and their targets: interaction determines expression

Combining the prediction of interactions between mRNAs and RNA-binding proteins with experimental expression profiles uncovers novel regulatory paradigms concerning proliferation and differentiation processes.See related research, http://genomebiology.com/2014/15/1/R13     

Distinctive Behaviors of Druggable Proteins in Cellular Networks

The interaction environment of a protein in a cellular network is important in defining the role that the protein plays in the system as a whole, and thus its potential suitability as a drug target. Despite the importance of the network environment, it is neglected during target selection for drug discovery. Here, we present the first systematic, comprehensive computational analysis of topological, community and graphical network parameters of the human interactome and identify discriminatory network patterns that strongly distinguish drug targets from the interactome as a whole. Importantly, we identify striking differences in the network behavior of targets of cancer drugs versus targets from other therapeutic areas and explore how they may relate to successful drug combinations to overcome acquired resistance to cancer drugs. We develop, computationally validate and provide the first public domain predictive algorithm for identifying druggable neighborhoods based on network parameters. We also make available full predictions for 13,345 proteins to aid target selection for drug discovery. All target predictions are available through canSAR.icr.ac.uk. Underlying data and tools are available at https://cansar.icr.ac.uk/cansar/publications/druggable_network_neighbourhoods/.     

Competing endogenous RNA database

A given mRNA can be regulated by interactions with miRNAs and in turn the availability of these miRNAs can be regulated by their interactions with alternate mRNAs. The concept of regulation of a given mRNA by alternate mRNA (competing endogenous mRNA) by virtue of interactions with miRNAs through shared miRNA response elements is poised to become a fundamental genetic regulatory mechanism. The molecular basis of the mRNA-mRNA cross talks is via miRNA response elements, which can be predicted based on both molecular interaction and evolutionary conservation. By examining the co-occurrence of miRNA response elements in the mRNAs on a genome-wide basis we predict competing endogenous RNA for specific mRNAs targeted by miRNAs. Comparison of the mRNAs predicted to regulate PTEN with recently published work, indicate that the results presented within the competing endogenous RNA database (ceRDB) have biological relevance.

Availability

http://www.oncomir.umn.edu/cefinder/     

Identification of evolutionarily meaningful information within the mammalian RNA editing landscape

A large comparative genomic sequence study has determined the extent of conservation between RNA editing sites within the mammalian evolutionary tree.See related research by Pinto et al., http://genomebiology.com/2014/15/1/R5     

Genome sequence of the chromate-resistant bacterium Leucobacter salsicius type strain M1-8T

Leucobacter salsicius M1-8^T is a member of the Microbacteriaceae family within the class Actinomycetales. This strain is a Gram-positive, rod-shaped bacterium and was previously isolated from a Korean fermented food. Most members of the genus Leucobacter are chromate-resistant and this feature could be exploited in biotechnological applications. However, the genus Leucobacter is poorly characterized at the genome level, despite its potential importance. Thus, the present study determined the features of Leucobacter salsicius M1-8^T, as well as its genome sequence and annotation. The genome comprised 3,185,418 bp with a G+C content of 64.5%, which included 2,865 protein-coding genes and 68 RNA genes. This strain possessed two predicted genes associated with chromate resistance, which might facilitate its growth in heavy metal-rich environments.     

Fertility and Polarized Cell Growth Depends on eIF5A for Translation of Polyproline-Rich Formins in Saccharomyces cerevisiae

eIF5A is an essential and evolutionary conserved translation elongation factor, which has recently been proposed to be required for the translation of proteins with consecutive prolines. The binding of eIF5A to ribosomes occurs upon its activation by hypusination, a modification that requires spermidine, an essential factor for mammalian fertility that also promotes yeast mating. We show that in response to pheromone, hypusinated eIF5A is required for shmoo formation, localization of polarisome components, induction of cell fusion proteins, and actin assembly in yeast. We also show that eIF5A is required for the translation of Bni1, a proline-rich formin involved in polarized growth during shmoo formation. Our data indicate that translation of the polyproline motifs in Bni1 is eIF5A dependent and this translation dependency is lost upon deletion of the polyprolines. Moreover, an exogenous increase in Bni1 protein levels partially restores the defect in shmoo formation seen in eIF5A mutants. Overall, our results identify eIF5A as a novel and essential regulator of yeast mating through formin translation. Since eIF5A and polyproline formins are conserved across species, our results also suggest that eIF5A-dependent translation of formins could regulate polarized growth in such processes as fertility and cancer in higher eukaryotes.