Data from: Meta-analysis of Arabidopsis thaliana phospho-proteomics data reveals compartmentalization of phosphorylation motifs

Protein (de)phosphorylation plays an important role in plants. To provide
a robust foundation for subcellular phosphorylation signaling network
analysis and kinase-substrate relationships, we performed a meta-analysis
of 27 published and unpublished in-house mass spectrometry–based
phospho-proteome data sets for Arabidopsis thaliana covering a range of
processes, (non)photosynthetic tissue types, and cell cultures. This
resulted in an assembly of 60,366 phospho-peptides matching to 8141
nonredundant proteins. Filtering the data for quality and consistency
generated a set of medium and a set of high confidence phospho-proteins
and their assigned phospho-sites. The relation between single and
multiphosphorylated peptides is discussed. The distribution of p-proteins
across cellular functions and subcellular compartments was determined and
showed overrepresentation of protein kinases. Extensive differences in
frequency of pY were found between individual studies due to proteomics
and mass spectrometry workflows. Interestingly, pY was underrepresented in
peroxisomes but overrepresented in mitochondria. Using motif-finding
algorithms motif-x and MMFPh at high stringency, we identified
compartmentalization of phosphorylation motifs likely reflecting localized
kinase activity. The filtering of the data assembly improved signal/noise
ratio for such motifs. Identified motifs were linked to kinases through
(bioinformatic) enrichment analysis. This study also provides insight into
the challenges/pitfalls of using large-scale phospho-proteomic data sets
to nonexperts.