Ontology highlight
ABSTRACT:
PROVIDER: PRJNA777448 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR16760700_1.fastq.gz | Fastqsanger.gz | |||
| SRR16760700_2.fastq.gz | Fastqsanger.gz | |||
| SRR16760701_1.fastq.gz | Fastqsanger.gz | |||
| SRR16760701_2.fastq.gz | Fastqsanger.gz | |||
| SRR16760702_1.fastq.gz | Fastqsanger.gz |
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Project description:This study aimed at investigating the effect in Grapevine of two different rootstocks (1103 Paulsen - P - and Mgt 101-14 - M) in comparison with not grafted plants - F - on the transcriptome of berry skin in Pinot noir (clone Entav 115), to explore the influence of rootstock-scion interaction on grape quality. 7-year old grapevine plants were grown in 70-liters, in an open field arranged in a randomized block design with 9 replicates for each root system. The plants were maintained in the same agronomic conditions: all the pots were fertilized and were abundantly irrigated. Berry samples (15 per plant, 3 plants per replicate), were collected at two different developmental stage: veraison (1) and maturation (2), and dissected to separate skin tissues. Total RNA was extracted from berry skins and DNase treated. 18 mRNA seq libraries were prepared, starting from total RNA (1 µg), using TruSeq RNA sample preparation kit (Illumina), according to manufacturers’ instructions. Libraries were quantified through qRT-PCR, as recommended by the protocol, and single-end sequenced for 100 bases on an Illumina Genome Analyzer (GAIIx).
2020-07-06 | E-MTAB-8758 | biostudies-arrayexpress
Project description:SuperSAGE is a method of digital gene expression profiling that allows isolation of 26bp tag fragments from expressed transcripts. Because its tag size is larger than that of conventional SAGE, SuperSAGE allowed a secure tag-to-gene annotation using BLAST search against grape genome databases.Transcript profiles in nine samples of grape berry tissues under different light conditions were obtained by SuperSAGE analysis and used for screening the genes which have co-ordinated transcript profiles with the change in the flavonoid composition in the samples analyzed. Candidate genes related to flavonoid biosynthesis and regulation were identified. Nine different grape samples, i.e., flowers, grape berries of Cabernet Sauvignon at 2, 7, 9 weeks after flowering (WAF), berry skins at 17 days after flowering (DAF) shaded after flowering, and berry skins at 17DAF shaded from flowering to 14DAF and then light exposed, were analyzed.
2014-06-03 | E-GEOD-55473 | biostudies-arrayexpress
Project description:Taste and color, which are important organoleptic qualities of grape berry, undergo rapid and substantial changes during development and ripening. In this study, we use two cultivars ‘Sanbenti’ and its bud sport ‘11-06-25’ to explore expression profiles differences and identify genes associated with total soluble solid (TSS) and total anthocyanins during grape berry development stages using RNA sequencing.
2019-12-25 | GSE142313 | GEO
Project description:Grapevine is a perennial crop often cultivated by grafting a scion cultivar on a suitable rootstock. Rootstocks influence scions, particularly with regard to water uptake and vigor. Therefore, one of the possibilities to adapt viticulture to the extended drought stress periods is to select rootstocks conferring increased tolerance to drought. However, the molecular mechanisms associated with the ability of rootstock/scion combination to influence grape berry metabolism under drought stress are still poorly understood. The transcriptomic changes induced by drought stress in grape berries (cv. Pinot noir) from vines grafted on either 110R (drought tolerant) or 125AA (drought sensitive) rootstock were compared. The experiments were conducted in the vineyard for two years and two grape berry developmental stages (50% and 100 % veraison. The genome-wide microarray approach showed that water stress strongly impacts gene expression in the berries, through ontology categories that cover cell wall metabolism, primary and secondary metabolism, signalling, stress, and hormones, and that some of these effects strongly depend on the rootstock genotype. Indeed, under drought stress, berries from vines grafted on 110R displayed a different transcriptional response compared to 125AA concerning genes related to jasmonate, phenylpropanoid metabolism and PR-proteins. The data also suggests a link between jasmonate and secondary metabolism in water-stressed berries. Overall, genes related to secondary metabolism and jasmonate are more induced and/or less repressed by drought stress in the berries grafted on the drought-sensitive rootstock 125AA. These rootstock-dependent gene expression changes are relevant for berry composition and sensory properties.
2015-03-19 | GSE66391 | GEO
Project description:This study aimed at investigating the effect in Grapevine of two different rootstocks (1103 Paulsen - P - and Mgt 101-14 - M) in comparison with not grafted plants - F - on the miRNome of berry skin in Pinot noir (clone Entav 115), to explore the influence of rootstock-scion interaction on grape quality. 7-year old grapevine plants were grown in 70-liters, in an open field arranged in a randomized block design with 9 replicates for each root system. The plants were maintained in the same agronomic conditions: all the pots were fertilized and were abundantly irrigated. Berry samples (15 per plant, 3 plants per replicate), were collected at two different developmental stage: veraison (1) and maturation (2), and dissected to separate skin tissues. Total RNA was extracted and DNase treated, small RNA libraries were prepared using the TruSeq Small RNA Sample Preparation Kit (Illumina®), following all manufacturers' instructions. Eighteen bar-coded small RNA libraries were constructed starting from 1 µg of total RNAs.
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Project description:The first GSSM of V. vinifera was reconstructed (MODEL2408120001). Tissue-specific models for stem, leaf, and berry of the Cabernet Sauvignon cultivar were generated from the original model, through the integration of RNA-Seq data. These models have been merged into diel multi-tissue models to study the interactions between tissues at light and dark phases.
2024-09-02 | MODEL2408160001 | BioModels
Project description:Seedless varieties are of particular importance to the table-grape and raisin industries. Gibberellin (GA) application is widely used in the early stages of seedless berry development to increase berry size and economic value. However, the underlying mechanism of GA induction of berry enlargement is not well understood. Here, RNA-sequencing analysis of âCentennial Seedlessâ (Vitis vinifera L.) berries treated with GA3 12 days after flowering is reported.
2014-12-05 | E-MTAB-4247 | biostudies-arrayexpress
Project description:We performed a comprehensive high-throughput transcript sequencing of ten different grapevine cultivars, which resulted in the first high coverage atlas of the grape berry transcriptome.
2015-09-04 | E-MTAB-4350 | biostudies-arrayexpress
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 °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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Project description:Changes in gene expression during berry development during a grape growing season were analysed. The effect on gene expression of different viticultural practises during grape berry development was investigated in this study by comparing two pruning methods (spur versus machine). Grape berries were collected and pooled on a weekly basis to obtain a developmental series comprised of 17 developmental stages from flowering until harvest across the grape growing season for both spur and machine pruned vines. Gene expression patterns during development and between pruning treatments were obtained. Keywords: Time course, developmental series and treatments
2018-11-22 | GSE7680 | GEO