Uso de Sistema de Informações Geográficas (SIG) para cadastramento de experimentos na Embrapa Uva e Vinho em Bento Gonçalves, RS, Brasil.

O uso de Sistemas de Informação Geográfica (SIGs) permite organizar e gerenciar informações de uma determinada área.Resumo

Sistema de Informação Geográfica aplicado à análise do uso do solo e do meio ambiente da Fazenda Experimental da Embrapa Uva e Vinho.

A Embrapa Uva e Vinho está envolvida no projeto de Implantação das Diretrizes Institucionais de Gestão Ambiental nas Unidades da Embrapa. Para o Plano de Manejo para Fazendas Experimentais das Unidades, uma das ações do projeto está sendo desenvolvida no Laboratório de Sensoriamento Remoto e Geoprocessamento, que é a construção de uma banco de dados georeferenciados.Resumo

Uso de SIG para identificar conflito do uso do solo na fazenda experimental da Embrapa Uva e Vinho em Bento Gonçalves, RS, Brasil: influência na rede de drenagens referentes as nascentes dos afluentes da bacia hidrográfica do rio Taquari-Antas.

The experimental farm of Embrapa Grape and Wine in Bento Gonçalves, state of Rio Grande do Sul, Brazil is part of the Taquari-Antas watershed is included in the Biosphere Reserve of the Atlantic. In this place develops activities occupying an area of ninety-four hectares. 67.34% of this area is covered by native forest and secondary vegetation, which were established as Legal Reserve Area (ARL) and Permanent Preservation Area (APP). The establishment of the drainage framework generated from the high-resolution digital elevation model (DEM), and native forest, were drawn APP (for permanent preservation areas) and legal reserve of rural property. The land cover conflict in the area of this farm regards to buildings near the areas of preservation are being framed in accordance with a proposal for preservation and restoration with native species. Through software SPRING 5.0.1, it was possible to carry by construction of georeferencing maps through crossing vectors for the land use conflicts analysis, the limits and the related drainage framework with APPs and RL with the identification of the springs. These data had been produced from high resolution aerialphoto image analysis, DEM generated from the aerial restitution and it is part of the data base image of the Laboratory of Remote Sensing and Geoprocessing - Embrapa Grape and Wine

DIANA-microT Web server upgrade supports Fly and Worm miRNA target prediction and bibliographic miRNA to disease association

microRNAs (miRNAs) are small endogenous RNA molecules that are implicated in many biological processes through post-transcriptional regulation of gene expression. The DIANA-microT Web server provides a user-friendly interface for comprehensive computational analysis of miRNA targets in human and mouse. The server has now been extended to support predictions for two widely studied species: Drosophila melanogaster and Caenorhabditis elegans. In the updated version, the Web server enables the association of miRNAs to diseases through bibliographic analysis and provides insights for the potential involvement of miRNAs in biological processes. The nomenclature used to describe mature miRNAs along different miRBase versions has been extensively analyzed, and the naming history of each miRNA has been extracted. This enables the identification of miRNA publications regardless of possible nomenclature changes. User interaction has been further refined allowing users to save results that they wish to analyze further. A connection to the UCSC genome browser is now provided, enabling users to easily preview predicted binding sites in comparison to a wide array of genomic tracks, such as single nucleotide polymorphisms. The Web server is publicly accessible in www.microrna.gr/microT-v4

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

Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia.

BACKGROUND: In mammalians, HIF is a master regulator of hypoxia gene expression through direct binding to DNA, while its role in microRNA expression regulation, critical in the hypoxia response, is not elucidated genome wide. Our aim is to investigate in depth the regulation of microRNA expression by hypoxia in the breast cancer cell line MCF-7, establish the relationship between microRNA expression and HIF binding sites, pri-miRNA transcription and microRNA processing gene expression. METHODS: MCF-7 cells were incubated at 1% Oxygen for 16, 32 and 48 h. SiRNA against HIF-1α and HIF-2α were performed as previously published. MicroRNA and mRNA expression were assessed using microRNA microarrays, small RNA sequencing, gene expression microarrays and Real time PCR. The Kraken pipeline was applied for microRNA-seq analysis along with Bioconductor packages. Microarray data was analysed using Limma (Bioconductor), ChIP-seq data were analysed using Gene Set Enrichment Analysis and multiple testing correction applied in all analyses. RESULTS: Hypoxia time course microRNA sequencing data analysis identified 41 microRNAs significantly up- and 28 down-regulated, including hsa-miR-4521, hsa-miR-145-3p and hsa-miR-222-5p reported in conjunction with hypoxia for the first time. Integration of HIF-1α and HIF-2α ChIP-seq data with expression data showed overall association between binding sites and microRNA up-regulation, with hsa-miR-210-3p and microRNAs of miR-27a/23a/24-2 and miR-30b/30d clusters as predominant examples. Moreover the expression of hsa-miR-27a-3p and hsa-miR-24-3p was found positively associated to a hypoxia gene signature in breast cancer. Gene expression analysis showed no full coordination between pri-miRNA and microRNA expression, pointing towards additional levels of regulation. Several transcripts involved in microRNA processing were found regulated by hypoxia, of which DICER (down-regulated) and AGO4 (up-regulated) were HIF dependent. DICER expression was found inversely correlated to hypoxia in breast cancer. CONCLUSIONS: Integrated analysis of microRNA, mRNA and ChIP-seq data in a model cell line supports the hypothesis that microRNA expression under hypoxia is regulated at transcriptional and post-transcriptional level, with the presence of HIF binding sites at microRNA genomic loci associated with up-regulation. The identification of hypoxia and HIF regulated microRNAs relevant for breast cancer is important for our understanding of disease development and design of therapeutic interventions

DIANA-microT web server: elucidating microRNA functions through target prediction

Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT

Subcellular location prediction of proteins using support vector machines with alignment of block sequences utilizing amino acid composition

Background: Subcellular location prediction of proteins is an important and well-studied problem in bioinformatics. This is a problem of predicting which part in a cell a given protein is transported to, where an amino acid sequence of the protein is given as an input. This problem is becoming more important since information on subcellular location is helpful for annotation of proteins and genes and the number of complete genomes is rapidly increasing. Since existing predictors are based on various heuristics, it is important to develop a simple method with high prediction accuracies. Results: In this paper, we propose a novel and general predicting method by combining techniques for sequence alignment and feature vectors based on amino acid composition. We implemented this method with support vector machines on plant data sets extracted from the TargetP database. Through fivefold cross validation tests, the obtained overall accuracies and average MCC were 0.9096 and 0.8655 respectively. We also applied our method to other datasets including that of WoLF PSORT. Conclusion: Although there is a predictor which uses the information of gene ontology and yields higher accuracy than ours, our accuracies are higher than existing predictors which use only sequence information. Since such information as gene ontology can be obtained only for known proteins, our predictor is considered to be useful for subcellular location prediction of newly-discovered proteins. Furthermore, the idea of combination of alignment and amino acid frequency is novel and general so that it may be applied to other problems in bioinformatics. Our method for plant is also implemented as a web-system and available on http://sunflower.kuicr.kyoto-u.ac.jp/~tamura/slpfa.html webcite

Bacterial production and direct functional screening of expanded molecular libraries for discovering inhibitors of protein aggregation.

Protein misfolding and aggregation are associated with a many human disorders, including Alzheimer's and Parkinson's diseases. Toward increasing the effectiveness of early-stage drug discovery for these conditions, we report a bacterial platform that enables the biosynthesis of molecular libraries with expanded diversities and their direct functional screening for discovering protein aggregation inhibitors. We illustrate this approach by performing, what is to our knowledge, the largest functional screen of small-size molecular entities described to date. We generated a combinatorial library of ~200 million drug-like, cyclic peptides and rapidly screened it for aggregation inhibitors against the amyloid-β peptide (Aβ42), linked to Alzheimer's disease. Through this procedure, we identified more than 400 macrocyclic compounds that efficiently reduce Aβ42 aggregation and toxicity in vitro and in vivo. Finally, we applied a combination of deep sequencing and mutagenesis analyses to demonstrate how this system can rapidly determine structure-activity relationships and define consensus motifs required for bioactivity