Proteome-wide analysis of phosphorylation events is a challenging, yet essential, task for the comprehensive and unbiased investigation of kinase action. Here we developed a phosphoproteomic approach in which quantitation consistency among reversed isotopically labeled samples is used as a central filtering rule for achieving reliability with minimal loss of data content. Exclusion of non-reverting data-points from the dataset not only reduces quantitation error and variation, but also reduces false positive identifications. Application of our approach identifies new substrates of the Mec1 and Tel kinases, expanding our understanding of the DNA damage signaling network regulated by these kinases.
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: Phosphoproteomics ; Yeast
Principal Investigators: (in alphabetical order) |
Marcus Smolka, Cornell University, United States |
Submitting User: | vitorfaca |
Faca VM, Sanford EJ, Tieu J, Comstock W, Gupta S, Marshall S, Yu H, Smolka MB.
Maximized quantitative phosphoproteomics allows high confidence dissection of the DNA damage signaling network.
Sci Rep. 2020 Oct 22;10(1):18056. Epub 2020 Oct 22.
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