1 resultado para Signal filtering and prediction
em Instituto Gulbenkian de Ciência
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Resumo:
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.