Computational Systems Biology Group, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Sydney 2145, Australia.
Charles Perkins Centre, School of Mathematics and Statistics, The University of Sydney, Sydney 2006, Australia.
Bioinformatics. 2022 Mar 28;38(7):1956-1963. doi: 10.1093/bioinformatics/btac015.
The advance of mass spectrometry-based technologies enabled the profiling of the phosphoproteomes of a multitude of cell and tissue types. However, current research primarily focused on investigating the phosphorylation dynamics in specific cell types and experimental conditions, whereas the phosphorylation events that are common across cell/tissue types and stable regardless of experimental conditions are, so far, mostly ignored.
Here, we developed a statistical framework to identify the stable phosphoproteome across 53 human phosphoproteomics datasets, covering 40 cell/tissue types and 194 conditions/treatments. We demonstrate that the stably phosphorylated sites (SPSs) identified from our statistical framework are evolutionarily conserved, functionally important and enriched in a range of core signaling and gene pathways. Particularly, we show that SPSs are highly enriched in the RNA splicing pathway, an essential cellular process in mammalian cells, and frequently disrupted by cancer mutations, suggesting a link between the dysregulation of RNA splicing and cancer development through mutations on SPSs.
The source code for data analysis in this study is available from Github repository https://github.com/PYangLab/SPSs under the open-source license of GPL-3. The data used in this study are publicly available (see Section 2.8).
Supplementary data are available at Bioinformatics online.
基于质谱的技术的进步使得对多种细胞和组织类型的磷酸化蛋白质组进行分析成为可能。然而,目前的研究主要集中在研究特定细胞类型和实验条件下的磷酸化动力学,而跨越细胞/组织类型且不受实验条件影响的磷酸化事件迄今为止大多被忽视。
在这里,我们开发了一种统计框架,用于鉴定跨越 53 个人类磷酸蛋白质组数据集的稳定磷酸蛋白质组,涵盖 40 种细胞/组织类型和 194 种条件/处理。我们证明,从我们的统计框架中鉴定出的稳定磷酸化位点(SPSs)是进化保守的、功能重要的,并且在一系列核心信号和基因途径中富集。特别是,我们表明 SPSs 在 RNA 剪接途径中高度富集,这是哺乳动物细胞中的一个基本细胞过程,并且经常被癌症突变所破坏,这表明 SPS 上的突变导致 RNA 剪接失调与癌症发展之间存在联系。
本研究中数据分析的源代码可从 Github 存储库 https://github.com/PYangLab/SPSs 获得,该存储库遵循 GPL-3 的开源许可证。本研究中使用的数据是公开可用的(见第 2.8 节)。
补充数据可在生物信息学在线获得。