2 resultados para computational analysis, microarray design, transcript profiling, vascular tissues, white spruce (Picea glauca)

em Instituto Gulbenkian de Ciência


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Grapevine is an extremely important crop worldwide.In southern Europe, post-flowering phases of the growth cycle can occur under high temperatures, excessive light, and drought conditions at soil and/or atmospheric level. In this study, we subjected greenhouse grown grapevine, variety Aragonez, to two individual abiotic stresses, water deficit stress(WDS), and heat stress (HS). The adaptation of plants to stress is a complex response triggered by cascades of molecular net works involved in stress perception, signal transduction, and the expression of specific stress-related genes and metabolites. Approaches such as array-based transcript profiling allow assessing the expression of thousands of genes in control and stress tissues. Using microarrays, we analyzed the leaf transcriptomic profile of the grapevine plants. Photosynthesis measurements verified that the plants were significantly affected by the stresses applied. Leaf gene expression was obtained using a high-throughput transcriptomic grapevine array, the 23K custom-made Affymetrix Vitis GeneChip. We identified 1,594 genes as differentially expressed between control and treatments and grouped them into ten major functional categories using MapMan software. The transcriptome of Aragonez was more significantly affected by HS when compared with WDS. The number of genes coding for heat-shock proteins and transcription factors expressed solely in response to HS suggesting their expression as unique signatures of HS. However, across-talk between the response pathways to both stresses was observed at the level of AP2/ERF transcription factors.

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Alachlor has been a commonly applied herbicide and is a substance of ecotoxicological concern. The present study aims to identify molecular biomarkers in the eukaryotic model Saccharomyces cerevisiae that can be used to predict potential cytotoxic effects of alachlor, while providing new mechanistic clues with possible relevance for experimentally less accessible eukaryotes. It focuses on genome-wide expression profiling in a yeast population in response to two exposure scenarios exerting effects from slight to moderate magnitude at phenotypic level. In particular, 100 and 264 genes, respectively, were found as differentially expressed on a 2-h exposure of yeast cells to the lowest observed effect concentration (110 mg/L) and the 20% inhibitory concentration (200 mg/L) of alachlor, in comparison with cells not exposed to the herbicide. The datasets of alachlor-responsive genes showed functional enrichment in diverse metabolic, transmembrane transport, cell defense, and detoxification categories. In general, the modifications in transcript levels of selected candidate biomarkers, assessed by quantitative reverse transcriptase polymerase chain reaction, confirmed the microarray data and varied consistently with the growth inhibitory effects of alachlor. Approximately 16% of the proteins encoded by alachlor-differentially expressed genes were found to share significant homology with proteins from ecologically relevant eukaryotic species. The biological relevance of these results is discussed in relation to new insights into the potential adverse effects of alachlor in health of organisms from ecosystems, particularly in worst-case situations such as accidental spills or careless storage, usage, and disposal.