Dataset Information

Vitis vinifera cv Merlot

ABSTRACT: Metabarcoding data of fungal communities associated with leaf, bark and ground cover samples collected in an untreated vineyard planted with Vitis vinifera cv Merlot.

PROVIDER: PRJNA847784 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR19634500_1.fastq.gz	Fastqsanger.gz
	SRR19634500_2.fastq.gz	Fastqsanger.gz
	SRR19634600_1.fastq.gz	Fastqsanger.gz
	SRR19634600_2.fastq.gz	Fastqsanger.gz
	SRR19634700_1.fastq.gz	Fastqsanger.gz

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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.

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Vitis vinifera cv Merlot

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