Computational protocol: Integrating Phosphoproteomics and Bioinformatics to Study Brassinosteroid-Regulated Phosphorylation Dynamics in Arabidopsis

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Protocol publication

[…] Raw spectrum files were processed for phosphopeptide identification and phosphosite quantification with MaxQuant software version ( []. Peptide identification was performed using Andromeda search engine [] against the Arabidopsis TAIR10 database (; version pep_20101214). Search criteria were trypsin specificity, fixed modification of carbamidomethyl, variable modifications of oxidationand phosphorylation, and two allowed missed cleavages. A minimum peptide length of seven amino acids was required. Precursor mass tolerance was set at 6 ppm, and fragment ion tolerance at 0.5 Da. A target-decoy search strategy was used in this study []. Protein, peptide, and site identification were accepted on the basis of posterior error probability with a false discovery rate (FDR) of 1 %. Precursors of already identified peptides were further searched using the “match between runs” option in MaxQuant, which matches precursor masses in a 2 min retention time window. The localization probability of all putative phosphorylation sites was determined using the MaxQuant post-translational modification score algorithm. The proteomics data have been deposited to the ProteomeXchange Consortium [] via the PRIDE partner repository with the dataset identifier PXD001473. Proteins were counted separately if a peptide matched to multiple proteins in the database search. Identified phosphorylation sites were grouped into three classes based on the phosphorylation localization probability score: class I (p > 0.75), class II (0.5 < p ≤ 0.75), and class III (p ≤ 0.5) []. Class I sites were considered as confident assignments and used for all analyses in the study. […]

Pipeline specifications

Software tools MaxQuant, Andromeda
Databases TAIR
Application MS-based untargeted proteomics
Organisms Arabidopsis thaliana, Bovine orthopneumovirus