Generation of a predicted protein database from EST data and application to iTRAQ analyses in grape (Vitis vinifera cv. Cabernet Sauvignon) berries at ripening initiation

Lücker, Joost, Laszczak, Mario, Smith, Derek and Lund, Steven T. (2009) Generation of a predicted protein database from EST data and application to iTRAQ analyses in grape (Vitis vinifera cv. Cabernet Sauvignon) berries at ripening initiation. BMC Genomics, 10 . doi:10.1186/1471-2164-10-50


Author Lücker, Joost
Laszczak, Mario
Smith, Derek
Lund, Steven T.
Title Generation of a predicted protein database from EST data and application to iTRAQ analyses in grape (Vitis vinifera cv. Cabernet Sauvignon) berries at ripening initiation
Journal name BMC Genomics   Check publisher's open access policy
ISSN 1471-2164
Publication date 2009-01
Sub-type Article (original research)
DOI 10.1186/1471-2164-10-50
Open Access Status DOI
Volume 10
Total pages 17
Place of publication London, United Kingdom
Publisher BioMed Central
Language eng
Formatted abstract
Background: iTRAQ is a proteomics technique that uses isobaric tags for relative and absolute quantitation of tryptic peptides. In proteomics experiments, the detection and high confidence annotation of proteins and the significance of corresponding expression differences can depend on the quality and the species specificity of the tryptic peptide map database used for analysis of the data. For species for which finished genome sequence data are not available, identification of proteins relies on similarity to proteins from other species using comprehensive peptide map databases such as the MSDB.

Results: We were interested in characterizing ripening initiation ('veraison') in grape berries at the protein level in order to better define the molecular control of this important process for grape growers and wine makers. We developed a bioinformatic pipeline for processing EST data in order to produce a predicted tryptic peptide database specifically targeted to the wine grape cultivar, Vitis vinifera cv. Cabernet Sauvignon, and lacking truncated N- and C-terminal fragments. By searching iTRAQ MS/MS data generated from berry exocarp and mesocarp samples at ripening initiation, we determined that implementation of the custom database afforded a large improvement in high confidence peptide annotation in comparison to the MSDB. We used iTRAQ MS/MS in conjunction with custom peptide db searches to quantitatively characterize several important pathway components for berry ripening previously described at the transcriptional level and confirmed expression patterns for these at the protein level.

Conclusion: We determined that a predicted peptide database for MS/MS applications can be derived from EST data using advanced clustering and trimming approaches and successfully implemented for quantitative proteome profiling. Quantitative shotgun proteome profiling holds great promise for characterizing biological processes such as fruit ripening initiation and may be further improved by employing preparative techniques and/or analytical equipment that increase peptide detection sensitivity via a shotgun approach.
Keyword Proteomic Analysis
Mass-Spectra
Arabidopsis
Biosynthesis
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Biological Sciences Publications
 
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