Dataset Information

Distinct Metabolic Signals Underlie Clone by Environment Interplay in "Nebbiolo" Grapes Over Ripening.

ABSTRACT: 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.

SUBMITTER: Pagliarani C

PROVIDER: S-EPMC6904956 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Distinct Metabolic Signals Underlie Clone by Environment Interplay in "Nebbiolo" Grapes Over Ripening.

Pagliarani Chiara C Boccacci Paolo P Chitarra Walter W Cosentino Emanuela E Sandri Marco M Perrone Irene I Mori Alessia A Cuozzo Danila D Nerva Luca L Rossato Marzia M Zuccolotto Paola P Pezzotti Mario M Delledonne Massimo M Mannini Franco F Gribaudo Ivana I Gambino Giorgio G

Frontiers in plant science 20191204

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 ...[more]

PMID: 31867031

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Project description:The role of gene-environment (GxE) interaction in disease and complex trait architectures is widely hypothesized, but currently unknown. Here, we apply three statistical approaches to quantify and distinguish three different types of GxE interaction for a given trait and E variable. First, we detect locus-specific GxE interaction by testing for genetic correlation rg<1 across E bins. Second, we detect genome-wide effects of the E variable on genetic variance by leveraging polygenic risk scores (PRS) to test for significant PRSxE in a regression of phenotypes on PRS, E, and PRSxE, together with differences in SNP-heritability across E bins. Third, we detect genome-wide proportional amplification of genetic and environmental effects as a function of the E variable by testing for significant PRSxE with no differences in SNP-heritability across E bins. Simulations show that these approaches achieve high sensitivity and specificity in distinguishing these three GxE scenarios. We applied our framework to 33 UK Biobank traits (25 quantitative traits and 8 diseases; average N=325K) and 10 E variables spanning lifestyle, diet, and other environmental exposures. First, we identified 19 trait-E pairs with rg significantly < 1 (FDR<5%) (average rg=0.95); for example, white blood cell count had rg=0.95 (s.e. 0.01) between smokers and non-smokers. Second, we identified 28 trait-E pairs with significant PRSxE and significant SNP-heritability differences across E bins; for example, BMI had a significant PRSxE for physical activity (P=4.6e-5) with 5% larger SNP-heritability in the largest versus smallest quintiles of physical activity (P=7e-4). Third, we identified 15 trait-E pairs with significant PRSxE with no SNP-heritability differences across E bins; for example, waist-hip ratio adjusted for BMI had a significant PRSxE effect for time spent watching television (P=5e-3) with no SNP-heritability differences. Across the three scenarios, 8 of the trait-E pairs involved disease traits, whose interpretation is complicated by scale effects. Analyses using biological sex as the E variable produced additional significant findings in each of the three scenarios. Overall, we infer a significant contribution of GxE and GxSex effects to complex trait and disease variance.

Dataset Information

Distinct Metabolic Signals Underlie Clone by Environment Interplay in "Nebbiolo" Grapes Over Ripening.

Publications

Distinct Metabolic Signals Underlie Clone by Environment Interplay in "Nebbiolo" Grapes Over Ripening.

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