miRQuest: integration of tools on a Web server for microRNA research.

This report describes the miRQuest - a novel middleware available in a Web server that allows the end user to do the miRNA research in a user-friendly way. It is known that there are many prediction tools for microRNA (miRNA) identification that use different programming languages and methods to realize this task. It is difficult to understand each tool and apply it to diverse datasets and organisms available for miRNA analysis. miRQuest can easily be used by biologists and researchers with limited experience with bioinformatics. We built it using the middleware architecture on a Web platform for miRNA research that performs two main functions: i) integration of different miRNA prediction tools for miRNA identification in a user-friendly environment; and ii) comparison of these prediction tools. In both cases, the user provides sequences (in FASTA format) as an input set for the analysis and comparisons. All the tools were selected on the basis of a survey of the literature on the available tools for miRNA prediction. As results, three different cases of use of the tools are also described, where one is the miRNA identification analysis in 30 different species. Finally, miRQuest seems to be a novel and useful tool; and it is freely available for both benchmarking and miRNA identification at http://mirquest.integrativebioinformatics.me/.

CoffeebEST: an integrated resource for Coffea spp expressed sequence tags.

Coffee is one of the most important commodities in the world, and its production relies mainly on two species, Coffea arabica and Coffea canephora. Although there are diverse transcriptome datasets available for coffee trees, few research groups have exploited the potential knowledge contained in these data, especially with respect to fruit and seed development. Here, we present a comparative analysis of the transcriptomes of Coffea arabica and Coffea canephora with a focus on fruit development using publicly available expressed sequence tags (ESTs). Most of the fruit and seed EST data has been obtained from C. canephora. Therefore, we performed a fruit EST analysis of the 5 developmental stages of this species (18, 22, 30, 42, and 46 weeks after flowering) comprising 29,009 sequences. We compared C. canephora fruit ESTs to reference unigenes of C. canephora (7710 contigs and 8955 singletons) and C. arabica (15,656 contigs and 16,351 singletons). Additional analyses included functional annotation based on Gene Onthology, as well as an annotation using PlantCyc, a curated plant protein database. The Coffee Bean EST (CoffeebEST) is a public database available at http://bioinfo-02.cp.utfpr.edu.br/. This database represents an additional resource for the coffee scientific community, offering a user-friendly collection of information for non-specialists in coffee molecular biology to support experimental research on comparative and functional genomics.

Prediction of potential novel microRNAs in soybean when in symbiosis.

MicroRNAs (miRNAs) are small molecules, noncoding proteins that are involved in many biological processes, especially in plants; among these processes is nodulation in the legume. Biological nitrogen fixation is a key process, with critical importance to the soybean crop. This study aimed to identify the potential of novel miRNAs to act during the root nodulation process. We utilized a set of transcripts that were differentially expressed in soybean roots 10 days after inoculation with Bradyrhizobium japonicum, which were obtained in a previous study, and performed a set of computational analyses that led us to select new miRNAs potentially involved in nodulation. Among these analyses, the set of transcripts were submitted to an in silico annotation of noncoding RNAs, including a search of similarity against miRNA public databases, ab initio tools for miRNA identification, structural search against miRNA families, prediction of the secondary structure of miRNA precursors, and prediction of the sequences of mature miRNAs. Subsequently, we applied filter procedures based on miRNA selections described in the literature (e.g., free energy value). In the next step, a manual curation inspection of the annotation was performed and the top candidates were selected and used for prediction of potential target genes, which were later checked manually in the database of the soybean genome. This prediction led us to the identification of 9 potential new miRNAs; among these, 4 were conserved in other plants. Moreover, we predicted their target genes might play important roles in the regulation of nodulation.