Browsing by Author "Aguayo, Daniel"

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    Metabolomic and biochemical analysis of mesocarp tissues from table grape berries with contrasting firmness reveals cell wall modifications associated to harvest and cold storage
    (2022) Balic, Ivan; Olmedo, Patricio; Zepeda, Baltasar; Rojas, Barbara; Ejsmentewicz, Troy; Barros, Miriam; Aguayo, Daniel; Moreno, Adrian A.; Pedreschi, Romina; Meneses, Claudio; Campos-Vargas, Reinaldo
    Tissue texture influences the grape berry consumers acceptance. We studied the biological differences between the inner and outer mesocarp tissues in hard and soft berries of table grapes cv NN107. Texture analysis revealed lower levels of firmness in the inner mesocarp as compared with the outer tissue. HPAEC-PAD analysis showed an increased abundance of cell wall monosaccharides in the inner mesocarp of harder berries at harvest. Immunohistochemical analysis displayed differences in homogalacturonan methylesterification and cell wall calcium between soft and hard berries. This last finding correlated with a differential abundance of calcium measured in the alcohol-insoluble residues (AIR) of the inner tissue of the hard berries. Analysis of abundance of polar metabolites suggested changes in cell wall carbon supply precursors, providing new clues in the identification of the biochemical factors that define the texture of the mesocarp of grape berries.
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    The Botrytis cinerea Gene Expression Browser
    (2023) Perez-Lara, Gabriel; Moyano, Tomas C.; Vega, Andrea; Larrondo, Luis F.; Polanco, Ruben; Alvarez, Jose M.; Aguayo, Daniel; Canessa, Paulo
    For comprehensive gene expression analyses of the phytopathogenic fungus Botrytis cinerea, which infects a number of plant taxa and is a cause of substantial agricultural losses worldwide, we developed BEB, a web-based B. cinerea gene Expression Browser. This computationally inexpensive web-based application and its associated database contain manually curated RNA-Seq data for B. cinerea. BEB enables expression analyses of genes of interest under different culture conditions by providing publication-ready heatmaps depicting transcript levels, without requiring advanced computational skills. BEB also provides details of each experiment and user-defined gene expression clustering and visualization options. If needed, tables of gene expression values can be downloaded for further exploration, including, for instance, the determination of differentially expressed genes. The BEB implementation is based on open-source computational technologies that can be deployed for other organisms. In this case, the new implementation will be limited only by the number of transcriptomic experiments that are incorporated into the platform. To demonstrate the usability and value of BEB, we analyzed gene expression patterns across different conditions, with a focus on secondary metabolite gene clusters, chromosome-wide gene expression, previously described virulence factors, and reference genes, providing the first comprehensive expression overview of these groups of genes in this relevant fungal phytopathogen. We expect this tool to be broadly useful in B. cinerea research, providing a basis for comparative transcriptomics and candidate gene identification for functional assays.