bioRxivPlant BiologyPreprint
Mapping the Arabidopsis thaliana proteome in PeptideAtlas and the nature of the unobserved (dark) proteome; strategies towards a complete proteome
K. J. van Wijk, T. Leppert, Z. Sun, A. Kearly, M. Li, L. Mendoza, I. Guzchenko, E. debley, G. Sauermann, P. Routray, S. Malhotra, A. D. L. Nelson, Q. Sun, E. W. Deutsch
Abstract
This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected PTMs, and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying [~]0.6 million unique peptides and 18267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for building the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome - the dark proteome. This dark proteome is highly enriched for certain (e.g. CLE, CEP, IDA, PSY) but not other (e.g. THIONIN, CAP,) signaling peptides families, E3 ligases, TFs, and other proteins with unfavorable physicochemical properties. A machine learning model trained on RNA expression data and protein properties predicts the probability for proteins to be detected. The model aids in discovery of proteins with short-half life (e.g. SIG1,3 and ERF-VII TFs) and completing the proteome. PeptideAtlas is linked to TAIR, JBrowse, PPDB, SUBA, UniProtKB and Plant PTM Viewer.
- organism: Arabidopsis
- assay: proteomics
- research focus: cell type annotation
- approach: machine learning (classical)
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