Protein Database for Grape Berry Ripening
Author Information
Author(s): Joost Lücker, Mario Laszczak, Derek Smith, Steven T. Lund
Primary Institution: University of British Columbia
Hypothesis
Can a predicted peptide database derived from EST data improve protein identification in grape berries during ripening initiation?
Conclusion
The study successfully created a predicted peptide database that significantly improved the identification of proteins involved in grape berry ripening.
Supporting Evidence
- The custom peptide database improved high confidence protein discovery by 20.2% and 7.4% in two iTRAQ datasets.
- 1424 proteins were identified in the mesocarp using the custom database compared to 1184 using the MSDB.
- The study confirmed expression patterns for proteins involved in isoprenoid and flavonoid metabolism during grape ripening.
Takeaway
Researchers made a special database to help find proteins in grapes as they ripen, which helps understand how grapes change during this time.
Methodology
The study involved creating a predicted peptide database from EST data and using iTRAQ for quantitative proteome profiling of grape berries.
Potential Biases
Potential bias in protein identification due to reliance on EST data and the absence of a complete genome sequence.
Limitations
The study's findings are limited by the lack of finished genome sequence data for grapevine and potential variability in protein detection due to seasonal growing conditions.
Participant Demographics
Grape clusters from Vitis vinifera cv. Cabernet Sauvignon were sampled from a commercial vineyard.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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