Project description:The aim of this work was to study the metabolism of grape berry skin, a tissue that has a protective role against damage by physical injuries and pathogen attacks. This role requires a metabolism able to sustain biosynthetic activities such as those relating to secondary compounds (i.e. flavonoids). In order to draw the attention on these biochemical processes, a proteomic and metabolomic comparative analysis was performed among Riesling Italico, Pinot Gris, Pinot Noir and Croatina cultivars, which are known to accumulate anthocyanins to a different extent. The application of multivariate statistics on the dataset pointed out that the cultivars were distinguishable from each other and the order in which they were grouped mainly reflected their relative anthocyanin contents. Sorting the spots according to their significance selected proteins were characterized by LC-ESI-MS/MS. Considering the functional distribution, the identified proteins were involved in many physiological processes such as stress, defense, carbon metabolism, energy conversion and secondary metabolism. The trends of some metabolites were related to those of the protein data. Taken together, the results permitted to highlight the relationships between the secondary compound pathways and the main metabolism (e.g. glycolysis and TCA cycle). Moreover, the trend of accumulation of many proteins involved in stress responses, reinforced the idea that they could play a role in the cultivar specific developmental plan.
Project description:We applied the RNA-Seq approach to reconstruct the transcriptome of Vitis vinifera cv. Corvina, using RNA pooled from a comprehensive set of sampled tissues in different organs and development steps, and we were able to reconstruct some novel and putative private Corvina genes. We analyzed the expression of these genes in three berry developmental conditions, and posit that they may play some role in the formation of the mature organ. Background: Plants display a high genetic and phenotypic variability among different cultivars. Understanding the genetic components that contribute to phenotypic diversity is necessary to disentangle genetic factors from the environment. Given the high degree of genetic diversity among plant cultivars a whole-genome sequencing and re-annotation of each variety is required but a reliable genome assembly is hindered by the high heterozigosity and sequence divergence. Results: we show the feasibility of an approach based on sequencing of cDNA by RNA-Seq to analyze varietal diversity between a local grape cultivar Corvina and the PN40024 grape reference genome. We detected 15,260 known genes and we annotated alternative splicing isoforms for 9,463 genes. Our approach allowed to define 2,321 protein coding putative novel genes in unannotated or unassembled regions of the reference genome PN40024 and 180 putative private Corvina genes whose sequence is not shared with the reference genome. Conclusions: With a de novo assembly based approach we were able to reconstruct a substantial part of the Corvina transcriptome and we improved substantially known genes annotations by better defining the structure of known genes, annotating splicing isoforms and detecting unannotated genes. Moreover our results clearly define sets of private genes which are likely part of the âdispensableâ genome and potentially involved into influencing some cultivar-specific characteristics. In plant biology a transcriptome de novo assembly approach should not be limited to species where no reference genome is available as it can improve the annotation lead to the identification of genes peculiar of a cultivar.
Project description: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.
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.
Project description:Bud endodormancy induction response of two genotypes (Seyval, a hybrid white wine grape and Vitis riparia, PI588259, a native North American grape species) was compared under long (15 h) and short (13 h) photoperiods. Proteins were extracted from both genotypes for all time points and experimental conditions. The proteins were separaed by 2D-PAGE, trypsin digested, and the peptides identified with a MALDI-TOF-TOF mass spectrometer. A master gel was made and mapped with all proteins from both genotypes. The proteins were identified by matching the peptide sequences against the 8X Vitis vinifera grape genome in NCBI. This study was funded by NSF grant DBI064755 and is the result of a collaboration between Dr. Anne Fennell at South Dakota State University and Dr. Grant R. Cramer at the University of Nevada, Reno.
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.
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.
Project description:MicroRNAs (miRNAs) play a important part in post-transcriptional gene regulation and have been shown to control many genes involved in various biological and metabolic processes. There have been extensive studies to discover miRNAs and analyze their functions in model plant species, such as Arabidopsis and rice and other plants. However, the number of miRNAs discovered in grape is relatively low and little is known about miRNAs responded gibberellin during fruit germination. In this study, a small RNA library from gibberellin grape fruits was sequenced by the high throughput sequencing technology. A total of 16,033,273 reads were obtained. 812,099 total reads representing 1726 unique sRNAs matched to known grape miRNAs. Further analysis confirmed a total of 149 conserved grapevine miRNA (Vv-miRNA) belonging to 27 Vv-miRNA families were validated, and 74 novel potential grapevine-specific miRNAs and 23 corresponding novel miRNAs* were discovered. Twenty-seven (36.5%) of the novel miRNAs exhibited differential QRT-PCR expression profiles in different development gibberellin-treated grapevine berries that could further confirm their existence in grapevine. QRT-PCR analysis on transcript abundance of 27 conserved miRNA family and the new candidate miRNAs revealed that most of them were differentially regulated by the gibberellin, with most conserved miRNA family and 26 miRNAs being specifically induced by gibberellin exposure. All novel sequences had not been earlier described in other plant species. In addition, 117 target genes for 29 novel miRNAs were successfully predicted. Our results indicated that miRNA-mediated gene expression regulation is present in gibberellin-treated grape berries. This study led to the confirmation of 101 known miRNAs and the discovery of 74 novel miRNAs in grapevine. Identification of miRNAs resulted in significant enrichment of the gibberellin of grapevine miRNAs and provided insights into miRNA regulation of genes expressed in grape berries. GSM604831 is the control for the gibberellin-treated sample.
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.