Statistics, data mining and machine learning for the analysis of microarray and RNA-Seq gene expression data in grapevine


The project is carried out in collaboration with researchers of the Department of Biotechnology, University of Verona. Microarray and RNA-Seq gene expression data in grapevine are analyzed with statistical methods and data mining/machine learning algorithms in order to detect associations and relationships with reference to genotype, environment, developmental stages and interactions among them.

Scientific coordinators: Paola Zuccolotto, Marco Sandri


Ripening transcriptomic program in red and white grapevine varieties correlates with berry skin anthocyanin accumulation

Massonnet M., Fasoli M., Tornielli G.B., Altieri M., Sandri M., Zuccolotto P., Paci P., Gardiman M., Zenoni S., Pezzotti M. (2017), Ripening transcriptomic program in red and white grapevine varieties correlates with berry skin anthocyanin accumulation, Plant Physiology, 174, 4, 2376-2396.

Grapevine (Vitis vinifera) berry development involves a succession of physiological and biochemical changes reflecting thetranscriptional modulation of thousands of genes. Although recent studies have investigated the dynamic transcriptomeduring berry development, most have focused on a single grapevine variety, so there is a lack of comparative datarepresenting different cultivars. Here, we report, to our knowledge, thefirst genome-wide transcriptional analysis of120 RNA samples corresponding to 10 Italian grapevine varieties collected at four growth stages. The 10 varieties,representingfive red-skinned andfive white-skinned berries, were all cultivated in the same experimental vineyard toreduce environmental variability. The comparison of transcriptional changes during berry formation and ripeningallowed us to determine the transcriptomic traits common to all varieties, thus defining the core transcriptome of berrydevelopment, as well as the transcriptional dynamics underlying differences between red and white berry varieties. A greatervariation among the red cultivars than between red and white cultivars at the transcriptome level was revealed, suggesting thatanthocyanin accumulation during berry maturation has a direct impact on the transcriptomic regulation of multiple biologicalprocesses. The expression of genes related to phenylpropanoid/flavonoid biosynthesis clearly distinguished the behaviorof red and white berry genotypes during ripening but also reflected the differential accumulation of anthocyanins in the redberries, indicating some form of cross talk between the activation of stilbene biosynthesis and the accumulation of anthocyanins inripening berries.


Grapevine field experiments reveal the contribution of genotype, the influence of environment and the effect of their interaction (GxE) on berry transcriptome

Dal Santo S., Zenoni S., Sandri M., De Lorenzis G., Magris G., De Paoli E., Di Gaspero G., Del Fabbro C., Morgante M., Brancadoro L., Grossi D., Fasoli M., Zuccolotto P., Tornielli G.B., Pezzotti M. (2018), Grapevine field experiments reveal the contribution of genotype, the influence of environment and the effect of their interaction (GxE) on berry transcriptome, The Plant Journal, 93, 6, 1143–1159.

Changes in the performance of genotypes in different environments are defined as genotype × environment (G×E) interactions. In grapevine (Vitis vinifera), complex interactions between different genotypes and climate, soil and farming practices yield unique berry qualities. However, the molecular basis of this phenomenon remains unclear. To dissect the basis of grapevine G×E interactions we characterized berry transcriptome plasticity, the genome methylation landscape and within-genotype allelic diversity in two genotypes cultivated in three different environments over two vintages. We identified, through a novel data-mining pipeline, genes with expression profiles that were: unaffected by genotype or environment, genotype-dependent but unaffected by the environment, environmentally-dependent regardless of genotype, and G×E-related. The G×E-related genes showed different degrees of within-cultivar allelic diversity in the two genotypes and were enriched for stress responses, signal transduction and secondary metabolism categories. Our study unraveled the mutual relationships between genotypic and environmental variables during G×E interaction in a woody perennial species, providing a reference model to explore how cultivated fruit crops respond to diverse environments. Also, the pivotal role of vineyard location in determining the performance of different varieties, by enhancing berry quality traits, was unraveled.

Download the data mining pipeline


Distinct metabolic signals underlie clone by environment interplay in ‘Nebbiolo’ grapes over ripening

Pagliarani C., Boccacci P., Chitarra W., Cosentino E., Sandri M., Perrone I., Mori A., Cuozzo D., Nerva L., Rossato M., Zuccolotto P., Pezzotti M., Delledonne M., Mannini F., Gribaudo I., Gambino G. (2019), Distinct metabolic signals underlie clone by environment interplay in ‘Nebbiolo’ grapes over ripening, Frontiers in Plant Science, 10, Article 1575, doi: 10.3389/fpls.2019.01575.

Several research studies were focused to understand how grapevine cultivars respond to environment; nevertheless, the biological mechanisms tuning this phenomenon need to be further deepened. Particularly, the molecular processes underlying the interplay between clones of the same cultivar and environment were poorly investigated. To address this issue, we analyzed the transcriptome of berries from three “Nebbiolo” clones grown in different vineyards, during two ripening seasons. RNA-sequencing data were implemented with analyses of candidate genes, secondary metabolites, and agronomical parameters. This multidisciplinary approach helped to dissect the complexity of clone × environment interactions, by identifying the molecular responses controlled by genotype, vineyard, phenological phase, or a combination of these factors. Transcripts associated to sugar signalling, anthocyanin biosynthesis, and transport were differently modulated among clones, according to changes in berry agronomical features. Conversely, genes involved in defense response, such as stilbene synthase genes, were significantly affected by vineyard, consistently with stilbenoid accumulation. Thus, besides at the cultivar level, clone-specific molecular responses also contribute to shape the agronomic features of grapes in different environments. This reveals a further level of complexity in the regulation of genotype × environment interactions that has to be considered for orienting viticultural practices aimed at enhancing the quality of grape productions.


Towards the definition of a detailed transcriptomic map of berry development

Fasoli M., Richter C.L., Zenoni S., Sandri M., Zuccolotto P., Dal Santo S., Pezzotti M., Dokoozlian N. and Tornielli G:B (2019), Towards the definition of a detailed transcriptomic map of berry development, BIO Web Conference, 13, 01001. Proceedings of CO.NA.VI. 2018 – 7° Convegno Nazionale di Viticoltura, Piacenza, 9-11 July 2018.

The progress of the grapevine genomics and the development of high-throughput technologies for gene expression analysis stimulated the investigation of the physical, biochemical and physiological changes of grape berry growth and maturation at transcriptomic level. The molecular information generated in the last decade is however still fragmented since it relies upon detailed analysis of few stages an d thus lacks continuity over grape development. To identify the molecular events associated with berry development at a higher temporal resolution and define a transcriptomic map, we performed RNA-seq analysis of berry samples collected every week from fruit-set to maturity in Pinot noir and Cabernet Sauvignon for three consecutive years, resulting in 219 samples. Using the most variable portion of the transcriptome, we built a preliminary transcriptomic model of berry development based on the Cabernet Sauvignon samples. The Pinot noir samples were then aligned onto this preliminary ripening map to investigate its performance in describing the development of another grape variety. A further step for testing the model was the projection of RNA-seq samples of fruit development of five red-skin Italian cultivars. For all these surveys, the transcriptomic route allowed a precise definition of the progression of berry development during both formation and ripening phases.