Grape berry development and maturation have been intensively studied and can be described as a succession of several physiological and biochemical changes reflecting the transcriptional modulation of many genes; nonetheless little is known about these transcriptional changes and their regulation. The aim of this research project is to understand the physiological and biochemical differences among ten Italian cultivars by analyzing and comparing the evolution of all the transcriptomes during berry development, as well as to find common transcriptomic traits. Ten varieties, five red and five white, were chosen among several hundreds of Italian varieties for their diversity in agronomical and oenological traits, and for adaptation to different growing locations. The ten varieties were all grown in the same experimental vineyard (Conegliano, Veneto region, Italy) and grape berry samples were collected during the same growing season (2011) at four different phenological stages, two pre- and two post-véraison, in triplicate. In total, 120 RNA samples were sequenced using the Illumina HighSeq technology. An average of 33.4 million single-ended reads for each sample was obtained, with a read length of 100 bases. The raw reads were aligned onto the 12X sequence of the Pinot Noir 40024 reference genome. An average of 28.5 million reads per sample was mapped, representing a mapping quality of 85.3%. At present, we are analyzing all data in order to obtain an overview of gene expression profiles during grape berry development for each variety. By comparing red or white varieties transcriptomes among themselves, and likewise red varieties transcriptomes versus the white ones at each berry growth stage, it will be possible to gain insights into the specific gene expression profiles of each variety and each colour-group. By this approach, it will be also possible to uncover commonly expressed genes in all the cultivars which will be considered as putative molecular biomarkers involved in berry development.
BERRY TRANSCRIPTOME COMPARISON OF TEN ITALIAN GRAPEVINE VARIETIES
Massonnet, Melanie;Altieri, Mario;ZENONI, Sara;TORNIELLI, Giovanni Battista;DAL SANTO, SILVIA;FASOLI, Marianna;DELLEDONNE, Massimo;PEZZOTTI, Mario
2013-01-01
Abstract
Grape berry development and maturation have been intensively studied and can be described as a succession of several physiological and biochemical changes reflecting the transcriptional modulation of many genes; nonetheless little is known about these transcriptional changes and their regulation. The aim of this research project is to understand the physiological and biochemical differences among ten Italian cultivars by analyzing and comparing the evolution of all the transcriptomes during berry development, as well as to find common transcriptomic traits. Ten varieties, five red and five white, were chosen among several hundreds of Italian varieties for their diversity in agronomical and oenological traits, and for adaptation to different growing locations. The ten varieties were all grown in the same experimental vineyard (Conegliano, Veneto region, Italy) and grape berry samples were collected during the same growing season (2011) at four different phenological stages, two pre- and two post-véraison, in triplicate. In total, 120 RNA samples were sequenced using the Illumina HighSeq technology. An average of 33.4 million single-ended reads for each sample was obtained, with a read length of 100 bases. The raw reads were aligned onto the 12X sequence of the Pinot Noir 40024 reference genome. An average of 28.5 million reads per sample was mapped, representing a mapping quality of 85.3%. At present, we are analyzing all data in order to obtain an overview of gene expression profiles during grape berry development for each variety. By comparing red or white varieties transcriptomes among themselves, and likewise red varieties transcriptomes versus the white ones at each berry growth stage, it will be possible to gain insights into the specific gene expression profiles of each variety and each colour-group. By this approach, it will be also possible to uncover commonly expressed genes in all the cultivars which will be considered as putative molecular biomarkers involved in berry development.
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