Profiling the Human Phosphoproteome to Estimate the True Extent of Protein Phosphorylation

Public
phosphorylation
databases such as PhosphoSitePlus (PSP)
and PeptideAtlas (PA) compile results from published papers or openly
available mass spectrometry (MS) data. However, there is no database-level
control for false discovery of sites, likely leading to the overestimation
of true phosphosites. By profiling the human phosphoproteome, we estimate
the false discovery rate (FDR) of phosphosites and predict a more
realistic count of true identifications. We rank sites into phosphorylation
likelihood sets and analyze them in terms of conservation across 100
species, sequence properties, and functional annotations. We demonstrate
significant differences between the sets and develop a method for
independent phosphosite FDR estimation. Remarkably, we report estimated
FDRs of 84, 98, and 82% within sets of phosphoserine (pSer), phosphothreonine
(pThr), and phosphotyrosine (pTyr) sites, respectively, that are supported
by only a single piece of identification evidencethe majority
of sites in PSP. We estimate that around 62 000 Ser, 8000 Thr,
and 12 000 Tyr phosphosites in the human proteome are likely
to be true, which is lower than most published estimates. Furthermore,
our analysis estimates that 86 000 Ser, 50 000 Thr,
and 26 000 Tyr phosphosites are likely false-positive identifications,
highlighting the significant potential of false-positive data to be
present in phosphorylation databases.