5 resultados para Identification of a putative gene

em Universidad Politécnica de Madrid


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Oligosaccharide synthesis is an important cryoprotection strategy used by woody plants during winter dormancy. At the onset of autumn, starch stored in the stem and buds is broken down in response to the shorter days and lower temperatures resulting in the buildup of oligosaccharides. Given that the enzyme DSP4 is necessary for diurnal starch degradation in Arabidopsis leaves, this study was designed to address the role of DSP4 in this seasonal process in Castanea sativa Mill. The expression pattern of the CsDSP4 gene in cells of the chestnut stem was found to parallel starch catabolism. In this organ, DSP4 protein levels started to rise at the start of autumn and elevated levels persisted until the onset of spring. In addition, exposure of chestnut plantlets to 4 °C induced the expression of the CsDSP4 gene. In dormant trees or cold-stressed plantlets, the CsDSP4 protein was immunolocalized both in the amyloplast stroma and nucleus of stem cells, whereas in the conditions of vegetative growth, immunofluorescence was only detected in the nucleus. The studies indicate a potential role for DSP4 in starch degradation and cold acclimation following low temperature exposure during activity–dormancy transition.

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Background Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60-mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results After an exhaustive process of pre-processing to ensure data quality--lost values imputation, probes quality, data smoothing and intraclass variability filtering--the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955)

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Background:Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods: A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60-mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results: After an exhaustive process of pre-processing to ensure data quality--lost values imputation, probes quality, data smoothing and intraclass variability filtering--the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions: We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).

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Unfavorable environmental and developmental conditions may cause disturbances in protein folding in the endoplasmic reticulum (ER) that are recognized and counteracted by components of the Unfolded Protein Response (UPR) signaling pathways. The early cellular responses include transcriptional changes to increase the folding and processing capacity of the ER. In this study, we systematically screened a collection of inducible transgenic Arabidopsis plants expressing a library of transcription factors for resistance toward UPR-inducing chemicals. We identified 23 candidate genes that may function as novel regulators of the UPR and of which only three genes (bZIP10, TBF1, and NF-YB3) were previously associated with the UPR. The putative role of identified candidate genes in the UPR signaling is supported by favorable expression patterns in both developmental and stress transcriptional analyses. We demonstrated that WRKY75 is a genuine regulator of the ER-stress cellular responses as its expression was found to be directly responding to ER stress-inducing chemicals. In addition, transgenic Arabidopsis plants expressing WRKY75 showed resistance toward salt stress, connecting abiotic and ER-stress responses.

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Common bean (Phaseolus vulgaris L.) is a leguminous in high demand for human nutrition and a very important agricultural product. Production of common bean is constrained by environmental stresses such as drought. Although conventional plant selection has been used to increase production yield and stress tolerance, drought tolerance selection based on phenotype is complicated by associated physiological, anatomical, cellular, biochemical, and molecular changes. These changes are modulated by differential gene expression. A common method to identify genes associated with phenotypes of interest is the characterization of Single Nucleotide Polymorphims (SNPs) to link them to specific functions. In this work, we selected two drought-tolerant parental lines from Mesoamerica, Pinto Villa, and Pinto Saltillo. The parental lines were used to generate a population of 282 families (F3:5) and characterized by 169 SNPs. We associated the segregation of the molecular markers in our population with phenotypes including flowering time, physiological maturity, reproductive period, plant, seed and total biomass, reuse index, seed yield, weight of 100 seeds, and harvest index in three cultivation cycles. We observed 83 SNPs with significant association (p < 0.0003 after Bonferroni correction) with our quantified phenotypes. Phenotypes most associated were days to flowering and seed biomass with 58 and 44 associated SNPs, respectively. Thirty-seven out of the 83 SNPs were annotated to a gene with a potential function related to drought tolerance or relevant molecular/biochemical functions. Some SNPs such as SNP28 and SNP128 are related to starch biosynthesis, a common osmotic protector; and SNP18 is related to proline biosynthesis, another well-known osmotic protector.