Dataset Information

Comparative Analyses of Five Grapevine (Vitis vinifera L.) Cultivars Under Seasonal Water Deficit

ABSTRACT: Berry skin total protein from Cabernet Sauvignon, Merlot, Pinot Noir, Chardonnay and Semillon. Treatments were control (well-watered) versus restricted irrigation (water-deficit). Samples were taken from harvest-ripe whole berry clusters following a seasonal water deficit in treatment vines. A comparative analysis between the cultivars and treatments was performed. Associated dataset identifiers: GSE72421, PRJNA268857.

OTHER RELATED OMICS DATASETS IN: PRJNA294008

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Berry Vitis Vinifera (grape)

TISSUE(S): Plant Cell, Exocarp

SUBMITTER: Ryan Ghan

LAB HEAD: Grant R Cramer

PROVIDER: PXD001661 | Pride | 2017-12-11

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	12x_v1_UniProt_080612.fasta	Fasta
	CDD1-high_GPM22200000687.xml-pride.pride.mztab.gz	Mztab
	CDD1-high_GPM22200000687.xml-pride.xml.gz	Xml
	CDD1-high_SVS290312_RG_117.mzXML.gz	Mzxml
	CDD1-low_GPM22200000689.xml-pride.pride.mztab.gz	Mztab

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Publications

Five omic technologies are concordant in differentiating the biochemical characteristics of the berries of five grapevine (Vitis vinifera L.) cultivars.

Ghan Ryan R Van Sluyter Steven C SC Hochberg Uri U Degu Asfaw A Hopper Daniel W DW Tillet Richard L RL Schlauch Karen A KA Haynes Paul A PA Fait Aaron A Cramer Grant R GR

BMC genomics 20151116

<h4>Background</h4>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.<h4>Results</h4>Berry skins of red- (Cabernet Sauvignon, Merlot, Pinot Noir) and white-skinned (Chardonnay, Semillon) wine grapes were harvested near optimum maturity (°Brix-to-titratable acidity ratio) from the same experimental vineyard. The cultivars were ...[more]

PMID: 26573226

Similar Datasets

Project description:Purpose: to screen the candidate genes involved in the peanut drought stress response, we conducted global transcriptome analysis of peanut plants challenged with water deficit and ABA, using the Illumina HiSeq2000 sequencing platform. Methods: a sequences library of Yueyou7 were constructed at first. Then the profile of diffentialy expressed genes (DEGs) under three different treatments (control, water deficit without ABA, and water deficit with ABA) were conducted based on above sequence library. For sequencing library construction, plants were grown under normal conditions, as described previously , Seeds were planted in soil and kep in the greenhouse at temperature of 25-30M-bM-^DM-^C and water well. Three tissues (leaves, roots, and stems) were collected at three development stages (four-leaf, flowering and podding stages), respectively. Then all of these tissues were mixed to extract the total RNA for sequence library construction. For DEGs study, two-week-old plants were divided into three groups with three independent replication: (1). Water deficit without ABA groups. Plants directly steeped in water containing 30% PEG600 for 30 min in this groups. (2) Water deficit with ABA groups. Plant was subjected to 100 M-BM-5mol/L ABA for 30 min and then steeped in water containing 30% PEG6000 for 30 min in this groups, (3) Control. Plants steeped in H2O. All treatments were conducted in parallel. After treatments, Total RNA was extracted from 100 mg of plant material, and RNA integrity was checked by gel electrophoresis. Also RNA quality was checked and RNA was quantified using the Agilent 2100 Bioanalyzer (Agilent technologies, Santa Clara, CA) and Nanodrop ND-1000 (Thermo Scientific, Waltham, USA). Results: we generated 4.96M-CM-^W107 raw sequence reads and assembled the high quality reads into 92,390 unique genes. Compared with the control, we found that 621 genes (M-bM-^IM-%1.5 fold change) responded rapidly to water deficit and 2665 genes (M-bM-^IM-%1.5 fold change) responded rapidly to ABA. We found 279 genes that overlapped between water deficit and ABA responses, 264 genes that showed the same trend in expression while 15 genes expression that showed opposite trend. Among the identified genes, 257 showed high induction by ABA (>5 fold), and 19 showed high induction by drought (>5 fold). In addition, we identified 100 transcription factor genes among the ABA-inducible genes but only 22 transcription factor genes among the water deficit-inducible genes. Conclusions: we identified genes differentially expressed in the early response to water deficit or ABA. These genes were annotated with GO functional categories for water deficit (33 categories) or ABA (31 categories). We found that only 19 genes were highly induced by water deficit, but 257 genes were highly induced by ABA. Our previous work has examined many of these genes and our future work will reveal their functions and relationships. These data will facilitate functional genomic studies and have established a biotechnological platform for examination of the early drought- and ABA-responsive transcriptome regulatory network in peanut. Two-week-old plants were divided into three groups with three independent replication: (1). Water deficit without ABA groups. Plants directly steeped in water containing 30% PEG600 for 30 min in this groups. (2) Water deficit with ABA groups. Plant was subjected to 100 M-BM-5mol/L ABA for 30 min and then steeped in water containing 30% PEG6000 for 30 min in this groups, (3) Control. Plants steeped in H2O. All treatments were conducted in parallel.

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:Background: The composition of grapevine berry at harvest is a major determinant of wine quality. Optimal oenological maturity of berries is characterized by a high sugar/acidity ratio, high anthocyanin content in the skin, and low astringency. However, harvest time is still mostly determined empirically, based on crude biochemical composition and berry tasting. In this context, it is interesting to identify genes that are expressed/repressed specifically at the late stages of ripening and which may be used as indicators of maturity. Results: Whole bunches and berries sorted by density were collected in vineyard on Chardonnay (white cultivar) grapevines for two consecutive years at three stages of ripening (7-days before harvest (TH-7),harvest (TH), and 10-days after harvest (TH+10)). Microvinification and sensory analysis indicate that the quality of the wines made from the whole bunches collected at TH-7, TH and TH+10 differed, TH providing the highest quality wines. In parallel, gene expression was studied with Qiagen/Operon microarrays using two types of samples, i.e. whole bunches and berries sorted by density. Only 12 genes were consistently up- or down-regulated in whole bunches and density sorted berries for the two years studied in Chardonnay. 52 genes were differentially expressed between the TH-7 and TH samples. In order to determine whether these genes followed a similar pattern of expression during the late stagesof berry ripening in a red cultivar, nine genes were selected for RT-PCR analysis with Cabernet Sauvignon grown under two different temperature regimes affecting the precocity of ripening. The expression profiles and their relationship to ripening were confirmed in Cabernet Sauvignon for seven genes, encoding a carotenoid cleavage dioxygenase, a galactinol synthase, a late embryogenesis abundant protein, a dirigent-like protein, a histidine kinase receptor, avalencene synthase and a putative S-adenosyl-L-methionine:salicylic acid carboxyl methyltransferase. Conclusions: This set of up- and down-regulated genes characterize the late stages of berry ripening in the two cultivars studied, and are indirectly linked to wine quality. They might be used directly or indirectly to design immunological, biochemical or molecular tools aimed at the determination of optimal ripening in these cultivars.

Project description:Background: Global climate change, in particular the entailed predicted temperature increase, will noticeably affect plants vegetative and reproductive development. High temperatures alter the composition of the grapevine fruit, one of the most important fruits produced worldwide. This is leading to variable yield and quality, already observed in many growing regions in recent years. However, physiological processes underlying temperature response and tolerance of the grapevine fruit have hardly been investigated. Currently, all studies on fleshy fruits investigating their abiotic stress response on a molecular level were conducted during the day but possible night-specific variations were overlooked. The present study explores the grapevine fruit transcriptomic response at different developmental stages upon heat stress at day and night. Methodology/Principal Results: Short heat stresses (2 h) were applied at day and night to vines bearing clusters sequentially ordered according to the developmental stages along their vertical axis. The recently proposed microvine model was grown in climatic chambers in order to circumvent common constraints and biases introduced in field experiments with perennial vines. Post-véraison berry heterogeneity inside clusters was evaded upon constituting homogenous batches following organic acid and sugar measurements on individual berries. A whole genome transcriptomic approach was subsequently conducted using NimbelGen® 090918 12X microarrays (30K). Results revealed important differences in heat stress responsive pathways according to day or night treatment, in particular regarding genes within phenylpropanoid metabolism. Precise distinction of post-véraison stages led to a stage-specific detection of anthocyanin-related transcripts repressed by heat. Important modifications in cell wall-related processes as well as indications for a heat-induced delay of ripening and sugar accumulation were observed at véraison and reversed in later stages. Conclusion: This first day - night study on heat stress adaption of the grapevine berry shows that the transcriptome of fleshy fruits is differentially affected by abiotic stress at night. The present results emphasize the necessity to include different developmental stages and especially different time points in transcriptomic studies. A total of 12 samples were analyzed representing three berry developmental stages (two after the onset of ripening, one during green growth). At each stage, heat stress was applied at day and night. Controls and treated berry samples were drawn in triplicates (two in duplicates) at day and at night on the microvine dwarf (Dwarf Rapid Cycling and Continous Flowering; DRCF) gibberellin-insensitive (GAI) mutant.