Identification and Analyses of Candidate Genes for Rpp4-Mediated Resistance to Asian Soybean Rust in Soybean

Asian soybean rust is a formidable threat to soybean (Glycine max) production in many areas of the world, including the United States. Only five sources of resistance have been identified (Resistance to Phakopsora pachyrhizi1 [Rpp1], Rpp2, Rpp3, Rpp4, and Rpp5). Rpp4 was previously identified in the resistant genotype PI459025B and mapped within 2 centimorgans of Satt288 on soybean chromosome 18 (linkage group G). Using simple sequence repeat markers, we developed a bacterial artificial chromosome contig for the Rpp4 locus in the susceptible cv Williams82 (Wm82). Sequencing within this region identified three Rpp4 candidate disease resistance genes (Rpp4C1-Rpp4C3 [Wm82]) with greatest similarity to the lettuce (Lactuca sativa) RGC2 family of coiled coil-nucleotide binding site-leucine rich repeat disease resistance genes. Constructs containing regions of the Wm82 Rpp4 candidate genes were used for virus-induced gene silencing experiments to silence resistance in PI459025B, confirming that orthologous genes confer resistance. Using primers developed from conserved sequences in the Wm82 Rpp4 candidate genes, we identified five Rpp4 candidate genes (Rpp4C1-Rpp4C5 [PI459025B]) from the resistant genotype. Additional markers developed from the Wm82 Rpp4 bacterial artificial chromosome contig further defined the region containing Rpp4 and eliminated Rpp4C1 (PI459025B) and Rpp4C3 (PI459025B) as candidate genes. Sequencing of reverse transcription-polymerase chain reaction products revealed that Rpp4C4 (PI459025B) was highly expressed in the resistant genotype, while expression of the other candidate genes was nearly undetectable. These data support Rpp4C4 (PI459025B) as the single candidate gene for Rpp4-mediated resistance to Asian soybean rust.

Spiroplasma in Drosophila melanogaster Populations: Prevalence, Male-Killing, Molecular Identification, and No Association with Wolbachia

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Cluster identification and characterization in the riser of a circulating fluidized bed from numerical simulation results

A methodology of identification and characterization of coherent structures mostly known as clusters is applied to hydrodynamic results of numerical simulation generated for the riser of a circulating fluidized bed. The numerical simulation is performed using the MICEFLOW code, which includes the two-fluids IIT's hydrodynamic model B. The methodology for cluster characterization that is used is based in the determination of four characteristics, related to average life time, average volumetric fraction of solid, existing time fraction and frequency of occurrence. The identification of clusters is performed by applying a criterion related to the time average value of the volumetric solid fraction. A qualitative rather than quantitative analysis is performed mainly owing to the unavailability of operational data used in the considered experiments. Concerning qualitative analysis, the simulation results are in good agreement with literature. Some quantitative comparisons between predictions and experiment were also presented to emphasize the capability of the modeling procedure regarding the analysis of macroscopic scale coherent structures. (c) 2007 Elsevier B.V. All rights reserved.

Identification and complete sequencing of novel human transcripts through the use of mouse orthologs and testis cDNA sequences

The correct identification of all human genes, and their derived transcripts, has not yet been achieved, and it remains one of the major aims of the worldwide genomics community. Computational programs suggest the existence of 30,000 to 40,000 human genes. However, definitive gene identification can only be achieved by experimental approaches. We used two distinct methodologies, one based on the alignment of mouse orthologous sequences to the human genome, and another based on the construction of a high-quality human testis cDNA library, in an attempt to identify new human transcripts within the human genome sequence. We generated 47 complete human transcript sequences, comprising 27 unannotated and 20 annotated sequences. Eight of these transcripts are variants of previously known genes. These transcripts were characterized according to size, number of exons, and chromosomal localization, and a search for protein domains was undertaken based on their putative open reading frames. In silico expression analysis suggests that some of these transcripts are expressed at low levels and in a restricted set of tissues.

Molecular phylogenetic and morphological analyses of Oidium heveae, a powdery mildew of rubber tree

Powdery mildew of rubber tree caused by Oidium heveae is an important disease of rubber plantations worldwide. Identification and classification of this fungus is still uncertain because there is no authoritative report of its morphology and no record of its teleomorphic stage. In this study, we compared five specimens of the rubber powdery mildew fungus collected in Malaysia, Thailand, and Brazil based on morphological and molecular characteristics. Morphological results showed that the fungus on rubber tree belongs to Oidium subgen. Pseudoidium. Nucleotide sequence analysis of the ribosomal DNA internal transcribed spacer (ITS) region and the large subunit rRNA gene (28S rDNA) were conducted to determine the relationships of the rubber powdery mildew fungus and to link this anamorphic fungus with its allied teleomorph. The results showed that the rDNA sequences of the two specimens from Malaysia were identical to a specimen from Thailand, whereas they differed by three bases from the two Brazilian isolates: one nucleotide position in the ITS2 and two positions in the 28S sequences. The ITS sequences of the two Brazilian isolates were identical to sequences of Erysiphe sp. on Quercus phillyraeoides collected in Japan, although the 28S sequences differed at one base from sequences of this fungus. Phylogenetic trees of both rDNA regions constructed by the distance and parsimony methods showed that the rubber powdery mildew fungus grouped with Erysiphe sp. on Q. phillyraeoides with 100% bootstrap support. Comparisons of the anamorph of two isolates of Erysiphe sp. from Q. phillyraeoides with the rubber mildew did not reveal any obvious differences between the two powdery mildew taxa, which suggests that O. heveae may be an anamorph of Erysiphe sp. on Q. phillyraeoides. Cross-inoculation tests are required to substantiate this conclusion. © The Mycological Society of Japan and Springer-Verlag 2005.

An integrated approach to identification and conservation of medicinal plants in the tropical forest - A Brazilian experience

An integrated and interdisciplinary research programme with native medicinal plants from tropical forests has been performed in order to obtain new forest products for sustainable use in regional markets vis-à-vis ecosystem conservation. For the success of this programme ethnopharmacological studies are very important with respect to (i) identification of useful plants including medicinal and aromatic species; (ii) recuperation and preservation of traditional knowledge about native plants; and (iii) identification of potential plants with economic value. The plants are selected with a view to evaluate efficacy and safety (pharmacological and toxicological studies), and phytochemical profile and quality control (phytochemical and chromatographic characterization). These studies are very important to add value to plant products and also to mitigate unscrupulous exploitation of medicinal plants by local communities, since multiple use of plants represents an excellent strategy for sustaining the tropical ecosystem through ex situ and in situ conservation. Thus, conservation of tropical resources is possible in conjunction with improvements in the quality of life of the traditional communities and production of new products with therapeutic, cosmetic and 'cosmeceutic' value. © NIAB 2005.

Identification and frequency of transposable elements in Eucalyptus

Transposable elements (TE) are major components of eukaryotic genomes and involved in cell regulation and organism evolution. We have analyzed 123,889 expressed sequence tags of the Eucalyptus Genome Project database and found 124 sequences representing 76 TE in 9 groups, of which copia, MuDR and FAR1 groups were the most abundant. The low amount of sequences of TE may reflect the high efficiency of repression of these elements, a process that is called TE silencing. Frequency of groups of TE in Eucalyptus libraries which were prepared with different tissues or physiologic conditions from seedlings or adult plants indicated that developing plants experience the expression of a much wider spectrum of TE groups than that seen in adult plants. These are preliminary results that identify the most relevant TE groups involved with Eucalyptus development, which is important for industrial wood production. Copyright by the Brazilian Society of Genetics.

An approach based on neural networks for identification of fault sections in radial distribution systems

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

Microcalcification enhancement and classification on mammograms using the wavelet transform

This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of perturbations on high frequency subband it's possible to classify its borders as smooth, rugged or undefined. Results show a false positive reduction of 69.27% using a region growing algorithm. © 2008 IEEE.

Multiplex PCR use for Staphylococcus aureus identification and oxacillin and mupirocin resistance evaluation

Oxacillin-resistant Staphylococcus aureus represents a serious problem in hospitals worldwide, increasing infected patients' mortality and morbidity and raising treatment costs and internment time. In this study, the results of using the Multiplex PCR technique to amplify fragments of the genes femA (specific-species), mecA (oxacillin resistance) and ileS-2 (mupirocin resistance) were compared with those of tests conventionally used to identify S. aureus isolates and ascertain their resistance to drugs. Fifty S. aureus strains were isolated from patients receiving treatment at UNOESTE University Hospital in Presidente Prudente, SP, Brazil. The 686 bp fragment corresponding to the gene femA was amplified and detected in all the isolates. On the other hand, the 310 bp fragment corresponding to the mecA gene was amplified in 29 (58%) of the isolates. All of the isolates showed sensitivity to mupirocin in the agar diffusion test, which was corroborated by the lack of any amplicon of the 456 bp fragment corresponding to the ileS-2 gene, in the PCR bands. The conventional tests to identify S. aureus and detect resistance to oxacillin and mupirocin showed 100% agreement with the PCR Multiplex results. The use of techniques for rapid and accurate identification of bacteria and assessment of their resistance may be valuable in the control of infection by resistant strains, allowing the rapid isolation and treatment of an infected patient. However, the results demonstrate that traditional phenotypic tests are also reliable, though they take more time.

Identification and filtering of uncharacteristic noise in the CMS hadron calorimeter

Commissioning studies of the CMS hadron calorimeter have identified sporadic uncharacteristic noise and a small number of malfunctioning calorimeter channels. Algorithms have been developed to identify and address these problems in the data. The methods have been tested on cosmic ray muon data, calorimeter noise data, and single beam data collected with CMS in 2008. The noise rejection algorithms can be applied to LHC collision data at the trigger level or in the offline analysis. The application of the algorithms at the trigger level is shown to remove 90% of noise events with fake missing transverse energy above 100 GeV, which is sufficient for the CMS physics trigger operation. © 2010 IOP Publishing Ltd and SISSA.

MODY 2: Mutation identification and molecular ancestry in a Brazilian family

Maturity Onset Diabetes of the Young (MODY) is a heterogeneous group of genetic diseases characterized by a primary defect in insulin secretion and hyperglycemia, non-ketotic disease, monogenic autosomal dominant mode of inheritance, age at onset less than 25. years, and lack of auto-antibodies. It accounts for 2-5% of all cases of non-type 1 diabetes. MODY subtype 2 is caused by mutations in the glucokinase (GCK) gene. In this study, we sequenced the GCK gene of two volunteers with clinical diagnosis for MODY2 and we were able to identify four mutations including one for a premature stop codon (c.76C>T). Based on these results, we have developed a specific PCR-RFLP assay to detect this mutation and tested 122 related volunteers from the same family. This mutation in the GCK gene was detected in 21 additional subjects who also had the clinical features of this genetic disease. In conclusion, we identified new GCK gene mutations in a Brazilian family of Italian descendance, with one due to a premature stop codon located in the second exon of the gene. We also developed a specific assay that is fast, cheap and reliable to detect this mutation. Finally, we built a molecular ancestry model based on our results for the migration of individuals carrying this genetic mutation from Northern Italy to Brazil. © 2012 Elsevier B.V.

Fuzzy community structure detection by particle competition and cooperation

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.