Avaliação demográfica, clinico-laboratorial e genética de indivíduos com lupus eritematoso sistêmico e artrite reumatóide residentes em região tropical

The aetiology of autoimmunes disease is multifactorial and involves interactions among environmental, hormonal and genetic factors. Many different genes may contribute to autoimmunes disease susceptibility. The major histocompatibility complex (MHC) genes have been extensively studied, however many non-polymorphic MHC genes have also been reported to contribute to autoimmune diseases susceptibility. The aim of the present study was to evaluate the influence of SLC11A1 gene in systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). Ninety-six patients with SLE, 37 with RA and 202 controls enrolled in this case-control study, were evaluated with regard to demographic, genetic, laboratorial and clinical data. SLE mainly affects females in the ratio of 18 women for each man, 88,3% of the patients aged from 15 to 45 years old and it occurs with similar frequency in whites and mulattos. The rate of RA between women and men was 11:1, with 77,1% of the cases occurring from 31 to 60 years. The genetic analysis of the point mutation -236 of the SLC11A1 gene by SSCP did not show significant differences between alleles/genotypes in patients with SLE or RA when compared to controls. The most frequent clinical manifestations in patients with SLE were cutaneous (87%) and joint (84.9%). In patients with RA, the most frequent out-joint clinical manifestation were rheumatoid nodules (13,5%). Antinuclear antibodies were present in 100% of the patients with SLE. There was no significant relation between activity of disease and presence of rheumatoid factor in patients with RA, however 55,6% of patients with active disease presented positive rheumatoid factor. Significant association between alleles/genotypes of point mutation -236 and clinical manifestations was not found

Avaliação demográfica, clinico-laboratorial e genética de indivíduos com lupus eritematoso sistêmico e artrite reumatóide residentes em região tropical

The aetiology of autoimmunes disease is multifactorial and involves interactions among environmental, hormonal and genetic factors. Many different genes may contribute to autoimmunes disease susceptibility. The major histocompatibility complex (MHC) genes have been extensively studied, however many non-polymorphic MHC genes have also been reported to contribute to autoimmune diseases susceptibility. The aim of the present study was to evaluate the influence of SLC11A1 gene in systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). Ninety-six patients with SLE, 37 with RA and 202 controls enrolled in this case-control study, were evaluated with regard to demographic, genetic, laboratorial and clinical data. SLE mainly affects females in the ratio of 18 women for each man, 88,3% of the patients aged from 15 to 45 years old and it occurs with similar frequency in whites and mulattos. The rate of RA between women and men was 11:1, with 77,1% of the cases occurring from 31 to 60 years. The genetic analysis of the point mutation -236 of the SLC11A1 gene by SSCP did not show significant differences between alleles/genotypes in patients with SLE or RA when compared to controls. The most frequent clinical manifestations in patients with SLE were cutaneous (87%) and joint (84.9%). In patients with RA, the most frequent out-joint clinical manifestation were rheumatoid nodules (13,5%). Antinuclear antibodies were present in 100% of the patients with SLE. There was no significant relation between activity of disease and presence of rheumatoid factor in patients with RA, however 55,6% of patients with active disease presented positive rheumatoid factor. Significant association between alleles/genotypes of point mutation -236 and clinical manifestations was not found

Predição de promotores de Bacillus subtilis usando técnicas de aprendizado de máquina

One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database

Prospecção de genes associados ao processo de floração em tomateiro.

Flowering is a process marked by switch of shoot apical meristem to floral meristem, and it involves a complex regulation by endogenous and environmental factors. Analyses of key flowering genes have been carried out primarily in Arabidopsis thaliana and have provided a foundation for understanding the underlying molecular genetic mechanisms controlling different aspects of floral development. Several homologous have been found in other species, but for crops species such as tomatoes this process is not well known. The aim of this work was to use the genetic natural variation associated to the flowering process and use molecular tools such as subtractive libraries and real time PCR in order to identify and analyze the expression from genes that may be associated to flowering in these two species: L. esculentum cv Micro-Tom and L. pimpinellifolium. Our results showed there were identified many genes related to vegetative and possibly to the flowering process. There were also identified many sequences that were unknown. We ve chosen three genes to analyze the expression by real time PCR. The histone H2A gene gave an expression higher in L. pimpinellifolium, due to this the expression of this gene may be associated to flowering in this specie. It was also analyzed the expression of an unknown gene that might be a key factor of the transition to flowering, also in L. pimpinellifolium. For the elongation factor 1-α expression, the expression results were not informative, so this gene may have a constitutive expression in vegetative and flowering state. The results observed allowed us to identify possible genes that may be related to the flowering process. For further results it will be necessary a better characterization of them.

Conservação genética da orquídea Cattleya granulosa Lindley

Cattleya granulosa Lind is a large and endemic orchid in Atlantic Forest fragments in Northeast Brazil. The facility of collecting, uniqueness of their flowers, which have varying colors between green and reddish brown, and distribution in coastal areas of economic interest make their populations a constant target of predation, which also suffer from environmental degradation. Due to the impact on their populations, the species is threatened. In this study, we evaluate the levels of spatial aggregation in a preserved population, analyze the phylogenetic relationships of C. granulosa Lindl. with four other Laeliinae species (Brassavola tuberculata, C. bicolor, C. labiata and C. schofieldiana) and also to evaluate the genetic diversity of 12 remaining populations of C. granulosa Lindl. through ISSR. There was specificity of epiphytic C. granula Lindl. with a single host tree, species of Eugenia sp. C. granulosa Lindl. own spatial pattern, with the highest density of neighbors within up to 5 m. Regarding the phylogenetic relationships and genetic patterns with other species of the genus, C. bicolor exhibited the greatest genetic diversity (HE = 0.219), while C. labiata exhibited the lowest level (HE = 0.132). The percentage of genetic variation among species (AMOVA) was 23.26%. The principal component analysis (PCA) of ISSR data showed that unifoliate and bifoliolate species are genetically divergent. PCA indicated a close relationship between C. granulosa Lindl. and C. schofieldiana, a species considered to be a variety of C. granulosa Lindl. by many researchers. Population genetic analysis using ISSR showed all polymorphic loci. The high genetic differentiation between populations (ФST = 0.391, P < 0.0001) determined the structure into nine groups according to log-likelihood of Bayesian analysis, with a similar pattern in the dendrogram (UPGMA) and PCA. A positive and significant correlation between geographic and genetic distances between populations was identified (r = 0.794, P = 0.017), indicating isolation by distance. Patterns of allelic diversity suggest the occurrence of population bottlenecks in most populations of C. granulosa Lindl. (n = 8). Genetic data indicate that enable the maintenance of genetic diversity of the species is complex and is directly related to the conservation of different units or groups that are spatially distant.