Abstract
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 (°Brix-to-titratable acidity ratio) from the same experimental vineyard. The cultivars were exposed to a mild, seasonal water-deficit treatment from fruit set until harvest in 2011. Identical sample aliquots were analyzed for transcripts by grapevine whole-genome oligonucleotide microarray and RNAseq 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 RNAseq 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 RNAseq 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. The mild water deficit treatment did not significantly alter the abundance of proteins or metabolites measured in the five cultivars, but did have a small effect on gene expression. 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.
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Claims 9
Claim · model-written summary
Five omics datasets showed similar cultivar separation.
VitisOrganisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Principal components analysis of each of five Omic technologies showed similar results across cultivars in all Omic datasets”
t0“grapevine (Vitis vinifera L.) cultivars”
Claim · model-written summary
RNAseq and microarray gene data correlated at 0.80.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“genes mapped in RNAseq and microarray data revealed a strong Pearson's correlation (0.80)”
t0“grapevine (Vitis vinifera L.) cultivars”
Claim · model-written summary
Excluding cross-hybridizing probes improved RNAseq–microarray correlation to 0.93.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The exclusion of probesets associated with genes with potential for cross-hybridization on the microarray improved the correlation to 0.93”
t0“grapevine (Vitis vinifera L.) cultivars”
Claim · model-written summary
Protein–RNAseq transcript correlation was low at 0.27.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The overall concordance of protein with transcript data was low with a Pearson's correlation of 0.27 and 0.24 for the RNAseq and microarray data, respectively”
t0“grapevine (Vitis vinifera L.) cultivars”
Claim · model-written summary
Protein–microarray transcript correlation was low at 0.24.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The overall concordance of protein with transcript data was low with a Pearson's correlation of 0.27 and 0.24 for the RNAseq and microarray data, respectively”
t0“grapevine (Vitis vinifera L.) cultivars”
Claim · model-written summary
Integrated omics data produced a phenylpropanoid biosynthesis model distinguishing red and white grapes.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“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”
t0“grapevine (Vitis vinifera L.) cultivars”
Claim · model-written summary
Mild water deficit did not significantly change measured protein abundance.
- Treatment
- mild water deficit treatmente0
- Outcome
- abundance of proteinse0
- Direction
- did not significantly altere0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The mild water deficit treatment did not significantly alter the abundance of proteins or metabolites measured in the five cultivars”
t0“grapevine (Vitis vinifera L.) cultivars”
Claim · model-written summary
Mild water deficit did not significantly change measured metabolite abundance.
- Treatment
- mild water deficit treatmente0
- Outcome
- abundance of proteins or metabolitese0
- Direction
- did not significantly altere0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The mild water deficit treatment did not significantly alter the abundance of proteins or metabolites measured in the five cultivars”
t0“grapevine (Vitis vinifera L.) cultivars”
Claim · model-written summary
Mild water deficit had a small effect on gene expression.
Not reportedComparatorDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“The mild water deficit treatment did not significantly alter the abundance of proteins or metabolites measured in the five cultivars, but did have a small effect on gene expression”
t0“grapevine (Vitis vinifera L.) cultivars”
The same questions in other papers
drought · pest · VitisPositive and negative results
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Claims are grouped by organism, treatment and what was measured or targeted. A paper counts as positive when any of its claims in the group is positive.