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Five Omic Technologies Are Concordant in Differentiating the Biochemical Characteristics of the Berries of Five Grapevine (Vitis vinifera L.) Cultivars

ABSTRACT: Background: Grape cultivars and wines are distinguishable by their color, flavor and aroma profiles. Omic analyses (transcripts, proteins and metabolites) are powerful tools for assessing biochemical differences in biological systems. Results: Berry skins of red- (Cabernet Sauvignon, Merlot, Pinot Noir) and white-skinned (Chardonnay, Semillon) wine grapes were harvested near optimum maturity from the same experimental vineyard and ˚Brix-to-titratable acidity ratio. Identical sample aliquots were analyzed for transcripts by grapevine whole-genome oligonucleotide microarray and RNA-seq technologies, proteins by nano-liquid chromatography-mass spectroscopy, and metabolites by gas chromatography-mass spectroscopy and liquid chromatography-mass spectroscopy. Principal components analysis of each of five Omic technologies showed similar results across cultivars in all Omic datasets. Comparison of the processed data of genes mapped in RNA-seq and microarray data revealed a strong Pearson's correlation (0.80). The exclusion of probesets associated with genes with potential for cross-hybridization on the microarray improved the correlation to 0.93. The overall concordance of protein with transcript data was low with a Pearson's correlation of 0.27 and 0.24 for the RNA-seq and microarray data, respectively. Integration of metabolite with protein and transcript data produced an expected model of phenylpropanoid biosynthesis, which distinguished red from white grapes, yet provided detail of individual cultivar differences. Conclusions: The five Omic technologies were consistent in distinguishing cultivar variation. There was high concordance between transcriptomic technologies, but generally protein abundance did not correlate well with transcript abundance. The integration of multiple high-throughput Omic datasets revealed complex biochemical variation amongst five cultivars of an ancient and economically important crop species.

ORGANISM(S): Vitis vinifera

PROVIDER: GSE72421 | GEO | 2015/11/12

SECONDARY ACCESSION(S): PRJNA294008

REPOSITORIES: GEO

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Project description:Background: Grape cultivars and wines are distinguishable by their color, flavor and aroma profiles. Omic analyses (transcripts, proteins and metabolites) are powerful tools for assessing biochemical differences in biological systems. Results: Berry skins of red- (Cabernet Sauvignon, Merlot, Pinot Noir) and white-skinned (Chardonnay, Semillon) wine grapes were harvested near optimum maturity from the same experimental vineyard and Ë?Brix-to-titratable acidity ratio. Identical sample aliquots were analyzed for transcripts by grapevine whole-genome oligonucleotide microarray and RNA-seq technologies, proteins by nano-liquid chromatography-mass spectroscopy, and metabolites by gas chromatography-mass spectroscopy and liquid chromatography-mass spectroscopy. Principal components analysis of each of five Omic technologies showed similar results across cultivars in all Omic datasets. Comparison of the processed data of genes mapped in RNA-seq and microarray data revealed a strong Pearson's correlation (0.80). The exclusion of probesets associated with genes with potential for cross-hybridization on the microarray improved the correlation to 0.93. The overall concordance of protein with transcript data was low with a Pearson's correlation of 0.27 and 0.24 for the RNA-seq and microarray data, respectively. Integration of metabolite with protein and transcript data produced an expected model of phenylpropanoid biosynthesis, which distinguished red from white grapes, yet provided detail of individual cultivar differences. Conclusions: The five Omic technologies were consistent in distinguishing cultivar variation. There was high concordance between transcriptomic technologies, but generally protein abundance did not correlate well with transcript abundance. The integration of multiple high-throughput Omic datasets revealed complex biochemical variation amongst five cultivars of an ancient and economically important crop species. Vitis vinifera L. cv. Cabernet Sauvignon, Chardonnay, Merlot, Pinot Noir, Semillon berries were harvested from Nevada Agricultural Experiment Station Valley Road Vineyard, Reno, NV, USA. Whole-genome microarray analysis was used to assess the transcriptomic response of berry skins at harvest, approximately 24 Â°Brix (2011 vintage). Vines were grown under water deficit and well-watered conditions. At least two clusters harvested from non-adjacent vines were used for each of five experimental replicates.

Project description:In the production of seedless table grapes, it is conventional to use plant growth regulators including gibberellins. Little is known about the differences in aroma volatiles between seedless-treated grapes and nontreated (seeded) grapes. Therefore, in this study, the aroma volatile profiles of seedless-treated and nontreated ‘Shine Muscat’ grape berries during ripening were compared using gas chromatography-mass spectrometry. Measurements of volatiles during ripening showed 202 peaks in the seedless-treated and nontreated whole grape berries. According to two-way analysis of variance, the number of volatiles with differences between seedless-treated and nontreated berries and/or between ripening stages was 123, whereas those with no differences between treatments and between ripening stages was 79. Two-way hierarchical clustering analysis for the 123 volatiles showed that seedless-treated berries at the early ripening stages were separated from the other berries, and the seedless-treated and nontreated berries at the post-ripening stage were classified into the same cluster. At the early ripening stage, more lipoxygenase-pathway volatiles were produced in the seedless-treated berries than in the non-treated ones. Linalool compounds increased in both seedless-treated and nontreated berries with ripening. Gene expression profile comparisons using principal component analysis of RNA-sequencing data showed that the seedless-treated berries ripened earlier than the nontreated berries at the early ripening stage. The number of differentially expressed genes in the seedless-treated berries decreased during ripening. Using weighted gene co-expression network analyses, 12 modules and 24 modules were detected in berry skin and flesh, respectively. The correlation analysis revealed that 33 volatiles correlated with four modules in the skin and 50 volatiles correlated with nine modules in the flesh. Most of the volatiles correlated with these modules were those that showed significant differences between treatments and/or ripening stages by two-way analysis of variance. The differences in the aroma volatile profiles between seedless-treated and nontreated berries decreased as harvest was delayed, suggesting that delaying the harvest may make it possible to bring the aroma of seedless-treated ‘Shine Muscat’ berries closer to the original aroma of the seeded berries.

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Five Omic Technologies Are Concordant in Differentiating the Biochemical Characteristics of the Berries of Five Grapevine (Vitis vinifera L.) Cultivars

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