pep2pro: a new tool for comprehensive proteome data analysis to reveal information about organ-specific proteomes in Arabidopsis thaliana.
pep2pro is a comprehensive proteome analysis database specifically suitable for flexible proteome data analysis. The pep2pro database schema offers solutions to the various challenges of developing a proteome data analysis database and because data integrated in pep2pro are in relational format, it enables flexible and detailed data analysis. The information provided here will facilitate building proteome data analysis databases for other organisms or applications. The capacity of the pep2pro database for the integration and analysis of large proteome datasets was demonstrated by creating the pep2pro dataset, which is an organ-specific characterisation of the Arabidopsis thaliana proteome containing 14 522 identified proteins based on 2.6 million peptide spectrum assignments. This dataset provides evidence of protein expression and reveals organ-specific processes. The high coverage and density of the dataset are essential for protein quantification by normalised spectral counting and allowed us to extract information that is usually not accessible in low-coverage datasets. With this quantitative protein information we analysed organ- and organelle-specific sub-proteomes. In addition we matched spectra to regions in the genome that were not predicted to have protein coding capacity and provide PCR validation for selected revised gene models. Furthermore, we analysed the peptide features that distinguish detected from non-detected peptides and found substantial disagreement between predicted and detected proteotypic peptides, suggesting that large-scale proteomics data are essential for efficient selection of proteotypic peptides in targeted proteomics surveys. The pep2pro dataset is available as a resource for plant systems biology at www.pep2pro.ethz.ch.
Department of Biology, ETH Zurich, Universitaetstrasse 2, 8092 Zurich, Switzerland. kbaerenfaller@ethz.ch
Katja
K
Baerenfaller
Matthias
M
Hirsch-Hoffmann
Julia
J
Svozil
Roger
R
Hull
Doris
D
Russenberger
Sylvain
S
Bischof
Qingtao
Q
Lu
Wilhelm
W
Gruissem
Sacha
S
Baginsky
D017360:Arabidopsis / Q000033:anatomy & histology* / Q000235:genetics / Q000378:metabolism*; D029681:Arabidopsis Proteins / Q000032:analysis* / Q000235:genetics / Q000378:metabolism; D015415:Biomarkers / Q000032:analysis / Q000378:metabolism; D030562:Databases, Protein; D020407:Internet; D058977:Molecular Sequence Annotation; D016366:Open Reading Frames / Q000235:genetics; D010446:Peptide Fragments / Q000032:analysis; D018514:Plant Structures / Q000235:genetics / Q000378:metabolism*; D016133:Polymerase Chain Reaction; D020543:Proteome / Q000032:analysis* / Q000235:genetics / Q000378:metabolism; D040901:Proteomics / Q000379:methods*; D012985:Software Design; D053719:Tandem Mass Spectrometry
D029681:Arabidopsis Proteins; D015415:Biomarkers; D010446:Peptide Fragments; D020543:Proteome