Vitis vinifera
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA285081 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Somatic variation is a valuable source of trait diversity in clonally propagated crops. In grapevine, which has been clonally propagated worldwide for centuries, important phenotypes such as white berry colour are the result of genetic changes caused by transposable elements. Additionally, epiallele formation may play a role in determining geo-specific (‘terroir’) differences in grapes and thus ultimately in wine. This genomic plasticity might be co-opted for crop improvement via somatic embryogenesis, but that depends on a species-specific understanding of the epigenetic regulation of transposable element (TE) expression and silencing in these cultures. For this reason, we used whole-genome bisulphite sequencing, mRNA sequencing and small RNA sequencing to study the epigenetic status and expression of TEs in embryogenic callus, in comparison with leaf tissue.
2021-08-27 | GSE164586 | GEO
Project description:Genomic differences between seeded and seedless grapes
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Project description:By implementing a leaf-removal treatment in the berry bunch zone, grapes were predominantly exposed to elevated light and their complete transcriptomes (as generated by RNASeq) were compared at four developmental stages.
2017-09-06 | GSE98873 | GEO
Project description:Response of Tempranillo grapes to immersion in a concentrated NaCl solution
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Project description:Pacbio HiFi, ONT and Hi-C sequencing data of nine grapes
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Project description:Full transcriptomes of the infection of Vitis vinifera grapes with the Botrytis cinerea wild-type Vv3 and Sl3 strains, at 24h and 48h, were studied.
2026-06-08 | GSE327899 | GEO
Project description:Effect of high CO2 levels and low temperature storage on table grapes quality harvested at two maturity stages.
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Project description:Anthocyanins, total phenols, soluble sugar and fruit shape play a significant role in determining the distinct fruit quality and customer preference. However, for the majority of fruit species, little is known about the transcriptomics and underlying regulatory networks that control the generation of overall quality during fruit growth and ripening. This study incorporated the quality-related transcriptome data from 6 ecological zones across 3 fruit development and maturity phases of Chardonnay cultivars. With the help of this dataset, we were able to build a complex regulatory network that may be used to identify important structural genes and transcription factors that control the anthocyanins, total phenols, soluble sugars and fruit shape in grapes. Overall, our findings set the groundwork to improve grape quality in addition to offering novel views on quality control during grape development and ripening.
2023-06-21 | GSE231025 | GEO
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 ˚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.
2015-11-12 | GSE72421 | GEO