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Phosphoproteomics has drawn great attention of biologist since phosphorylation is proven to play an important role in regulation of proteins. Mass spectrometry technology has helped with the development of phosphoproteomics due to its ability in generating large amount of detailed information after analyzing the phosphoproteome samples. However, interpreting the phosphoproteome data deprived from mass spectrometry can be time-consuming. Here, we introduced a free R language-based platform which can be used in accelerating phosphoproteome data analysis. This platform has integrated different functions and methods which are popularly used in phosphoproteome data analysis, so users can customize their analysis according to their demands.Most proteins undergo some form of modification after translation, and phosphorylation is one of the most relevant and ubiquitous post-translational modifications. The succession of protein phosphorylation and dephosphorylation catalyzed by protein kinase and phosphatase, respectively, constitutes a key mechanism of molecular information flow in cellular systems. The protein interactions of kinases, phosphatases, and their regulatory subunits and substrates are the main part of phosphorylation networks. To elucidate the landscape of phosphorylation events has been a central goal pursued by both experimental and computational approaches. Substrate specificity (e.g., sequence, structure) or the phosphoproteome has been utilized in an array of different statistical learning methods to infer phosphorylation networks. In this chapter, different computational phosphorylation network inference-related methods and resources are summarized and discussed.The PhosPhAt 4.0 database contains information on Arabidopsis phosphorylation sites identified by mass spectrometry in large-scale experiments from different research groups. So far PhosPhAt 4.0 has been one of the most significant large-scale data resources for plant phosphorylation studies. Functionalities of the web application, besides display of phosphorylation sites, include phosphorylation site prediction and kinase-target relationships retrieval. Here, we present an overview and user instructions for the PhosPhAt 4.0 database, with strong emphasis on recent renewals regarding protein annotation by SUBA4.0 and Mapman4, and additional phosphorylation site information imported from other databases, such as UniProt. Here, we provide a user guide for the retrieval of phosphorylation motifs from the kinase-target database and how to visualize these results. The improvements incorporated into the PhosPhAt 4.0 database have produced much more functionality and user flexibility for phosphoproteomic analysis.Both the phosphorylation and dephosphorylation of plant proteins is involved in multiple biological processes, especially in regard to signal transduction. The identification of phosphopeptides from MS (mass spectrometry)-based methods and their subsequent quantification play an important role in plant phosphoproteomics analysis. Phosphopeptide(s) identification and label-free quantification can determine dynamic changes of phosphorylation events in plants. see more Both MaxQuant and Proteome Discoverer are professional software tools used to identify and quantify large-scale MS-based phosphoproteomic data. This chapter gives a detailed workflow of MaxQuant and Proteome Discoverer software to analyze large amounts of phosphoproteomic-related MS data for the identification and quantification of label-free plant phosphopeptides.The green alga Chlamydomonas reinhardtii is an extremely useful model organism, and protein phosphorylation is an extremely important posttranslational modification. We have established the protocol 2-D difference gel electrophoresis (DIGE), combined with the fluorescence staining with Pro-Q Diamond, that successfully detects subtle changes of spot mobility caused by protein phosphorylation between Chlamydomonas samples.Pro-Q diamond phosphoprotein gel stain is a fluorescent stain to detect phosphorylated proteins in polyacrylamide gels with high sensitivity. Here, we describe an entire procedure for phosphoproteomics analysis of Arabidopsis seedlings by a combination of Pro-Q diamond stain and two-dimensional gel electrophoresis (2-DE). The workflow involves total protein preparation, protein separation by 2-DE, the second-dimensional gel staining, phosphoproteins detection, and peptides preparation for matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis. Approximately 300 phosphoproteins can be detected using this method.Protein phosphorylation plays important roles in the regulation of plant growth and development as well as adaption to changing environments. Large-scale identification of the phosphorylated proteins could provide both a global view of and specific targets involved in the mechanism underlying these processes. The progress of phosphoproteomic study for higher plants has lagged behind that of animals due to technical challenges, particularly the difficulty in solubilizing proteins from plant tissues with a rigid cell wall and the interference of the secondary metabolites, polysaccharides, and pigments throughout the whole processes of sample preparation and LC-MS analysis. Thus, it is critical to improve the efficiency of protein extraction and to remove the interfering metabolites before phosphopeptides enrichment. Here we describe a protocol for plant protein extraction and phosphopeptides enrichment by Fe3+-immobilized metal ion affinity chromatography (Fe3+-IMAC). Strong detergents such as SDS were used to extract proteins from plant tissues, and the secondary metabolites were removed by protein precipitation and washing of the pellets. The protein samples were digested and the resulting peptides were prefractionated. Phosphopeptides enriched from each fraction were combined before analysis with LC-MS.Plants absorb water and nutrients from soil through roots and transmit these resources through the xylem to the shoot. Roots therefore participate in information and material transduction as well as signal communication with the shoot. The importance of reversible protein phosphorylation in the regulation of plant growth and development has been amply demonstrated through decades of research. Here, we present a simple mass spectrometry-based shotgun phosphoproteomics protocol for Arabidopsis root tissue. Through this method, we can profile the Arabidopsis root phosphoproteome and construct signal networks of key proteins to better understand their roles in plant growth and development.