Rodrigo Duarte Drummond

Identification of new ABA- and MEJA-activated sugarcane bZIP genes by data mining in the SUCEST database.

Sugarcane is generally propagated by cuttings of the stalk containing one or more lateral buds, which will develop into a new plant. The transition from the dormant into the active stage constitutes a complex phenomenon characterized by changes in accumulation of phytohormones and several other physiological aspects. Abscisic acid (ABA) and methyl-jasmonate (MeJA) are major signaling molecules, which influence plant development and stress responses. These plant regulators modulate gene expression with the participation of many transcriptional factors. Basic leucine zipper proteins (bZIPs) form a large family of transcriptional factors involved in a variety of plant physiological processes, such as development and responses to stress. Query sequences consisting of full-length protein sequence of each of the Arabidopsis bZIP families were utilized to screen the sugarcane EST database (SUCEST) and 86 sugarcane assembled sequences (SAS) coding for bZIPs were identified. cDNA arrays and RNA-gel blots were used to study the expression of these sugarcane bZIP genes during early plantlet development and in response to ABA and MeJA. Six bZIP genes were found to be differentially expressed during development. ABA and MeJA modulated the expression of eight sugarcane bZIP genes. Our findings provide novel insights into the expression of this large protein family of transcriptional factors in sugarcane.

Prospecting sugarcane genes involved in aluminum tolerance

Aluminum is one of the major factors that affect plant development in acid soils, causing a substantial reduction in yield in many crops. In South America, about 66% of the land surface is made up of acid soils where high aluminum saturation is one of the main limiting factors for agriculture. The biochemical and molecular basis of aluminum tolerance in plants is far from being completely understood despite a growing number of studies, and in the specific case of sugarcane there are virtually no reports on the effects of gene regulation on aluminum stress. The objective of the work presented in this paper was to prospect the sugarcane expressed sequence tag (SUCEST) data bank for sugarcane genes related to several biochemical pathways known to be involved in the responses to aluminum toxicity in other plant species and yeast. Sugarcane genes similar to most of these genes were found, including those coding for enzymes that alleviate oxidative stress or combat infection by pathogens and those which code for proteins responsible for the release of organic acids and signal transducers. The role of these genes in aluminum tolerance mechanisms is reviewed. Due to the high level of genomic conservation in related grasses such as maize, barley, sorghum and sugarcane, these genes may be valuable tools which will help us to better understand and to manipulate aluminum tolerance in these species.

Gene expression profiling in maize roots under aluminum stress

To investigate the molecular mechanisms of Al toxicity, cross-species cDNA array approach was employed to identify expressed sequence tags (ESTs) regulated by Al stress in root tips of Al-tolerant maize (Zea mays) genotype Cat100-6 and Al-sensitive genotype S1587-17. Due to the high degree of conservation observed between sugarcane and maize, we have analyzed the expression profiling of maize genes using 2 304 sugarcane (ESTs) obtained from different libraries. We have identified 85 ESTs in Al stressed maize root tips with significantly altered expression. Among the up-regulated ESTs, we have found genes encoding previously identified proteins induced by Al stress, such as phenyl ammonia-lyase, chitinase, Bowman-Birk proteinase inhibitor, and wali7. In addition, several novel genes up-and downregulated by Al stress were identified in both genotypes.

Well log denoising and geological enhancement based on discrete wavelet transform and hybrid thresholding

Well logging is an important tool for the characterization of subsurface rocks, being commonly used in the study of reservoir geology. It is well known that signals obtained as responses from geological media contain noise that can affect their interpretation, and that wavelet transform is more suitable than the Fourier transform to denoise non-stationary signals, as the ones obtained from well logs. On the other hand, there are several parameters that must be considered when working with wavelet transform, such as the choice of the wavelet basis function (mother wavelet), the decomposition level and also the function and rules that “control” which and how the coefficients will be used for signal reconstruction. This study analyzes the process of denoising well log data by discrete wavelet transform. Since the well log data are usually used in lithological classification, we propose a method associated with the k-nearest neighbor classification algorithm to investigate how different combinations of parameters affect the output signals and its performance in the classification, thus making it a data driven process. We propose a new thresholding function that shows better results when compared with traditional ones. The potential of wavelet transform as a tool to aid geological interpretation is evidenced by the identification of important geological features of the Namorado Field, Campos Basin, Brazil.

Maximum Autocorrelation Factors applied to electrofacies classification

A vast amount of data is obtained during the development of a petroleum field. Seismic data, well logs, core and production data, all contribute to a better reservoir characterization and modeling. Several methods of multivariate data analysis can be used to support its interpretation, helping in important tasks as the identification of lithological facies. The most used and widely known of those methods is Principal Component Analysis (PCA) which intends to reduce data dimension while keeping as much as possible of their variance. Data dimension reduction can also be performed with the method of Maximum Autocorrelation Factors (MAF) which seeks to keep the spatial autocorrelation in data. In this work both methods were applied to data from well logs of the Namorado field, testing their performances in the classification of electrofacies. Following data dimension reduction, supervised classification methods known as k-nearest neighbors (kNN) and weighted k-nearest neighbors (wk-NN) were applied, and the results obtained were compared by cross-validation. MAF showed to be more efficient than PCA in reducing data dimension, while keeping relevant information. The wk-NN performed a little better in classifying electrofacies than the usual k-NN. According to these results, the combination of MAF and wk-NN can be a valuable tool for classifying the facies of uncored wells from their logs.

Evaluation of the performance of different plastics used to seal nylon cDNA arrays

Os arranjos de cDNA sao uma poderosa ferramenta para o estudo de padroes de expressao genica. Os arranjos em membranas de nailon apresentam ainda a vantagem de poderem ser reutilizados diversas vezes. Porem, um ponto bastante delicado em estudos de expressao genica em larga escala e a sensibilidade. No caso de arranjos em membranas de nailon, a deteccao dos sinais pode ser afetada pelo envoltorio plastico utilizado para manter as membranas umidas. Nesse estudo, nos avaliamos os efeitos de cinco tipos de plasticos na transmissao radioativa detectada, no numero de genes com sinal acima da emissao de fundo e na variabilidade dos dados. O plastico produzido com polietileno com 69 μm de espessura apresentou uma forte interferencia na emissao radioativa, bloqueando 68.7% do sinal detectado. Este bloqueio na transmitância diminuiu o numero de genes detectados e aumentou a variabilidade dos dados. Outros plasticos mais finos tiveram resultados melhores. Apesar de plasticos feitos de cloreto de polivinilideno e cloreto de polivinila (ambos com 13 μm de espessura) e polietileno (29 e 7 μm de espessura) terem diferentes niveis de transmitância, todos apresentaram performances semelhantes nos testes realizados. Cloreto de polivinilideno e polietileno com 29 μm de espessura foram os plasticos escolhidos devido a facilidade de manuseio. Para outros tipos de plasticos, e recomendavel realizar um teste de suas performances antes de utiliza-los para envolver membranas de nailon, de forma a obter o maximo de informacao dos experimentos com arranjos de cDNA.