Visualization of large-scale, multi-dimensional omics data is a major challenge. Experimental study designs in proteomics research produce multiple data layers, e.g. relationships between hundreds of proteins, their interactions and abundances as a function of time or perturbation, as well as dynamics of post-translational modifications (PTMs) and allelic variants (proteoforms). These different levels and types of information of proteins and proteoforms complicate data analysis and generation of insightful and comprehensible graphic visualizations. Middle-down mass spectrometry of histone proteins now allows quantifying hundreds of histone proteoforms including co-existing methylation, acetylation and phosphorylation events at distinct amino acid residues within histone molecules. The histone PTM landscape plays a dominant role in the regulation of chromatin activity and transcriptional and epigenetic control. The dynamics of these reversible modifications are governed by reader, writer and eraser enzymes that cooperate to regulate molecular mechanisms that rely on multiple interdependent PTM marks in histones and nucleosomes in chromatin. This PTM crosstalk can be quantified and provides a detailed picture of the underlying rules for setting the histone PTM landscape and chromatin activity, and is available to the community via our CrosstalkDB platform. Here, we developed a new computational method, PTM-CrossTalkMapper, to visualize the dynamics of histone PTMs for different experimental conditions, replicates and proteoforms onto a landscape, thereby describing the crosstalk and interplay between PTMs in a more comprehensible manner. We show the power of combining different levels of information on such crosstalk maps for histone PTM dynamics in mouse organs during the aging process. The PTM-CrossTalkMapper toolkit provides flexible functions to create these maps in various scenarios of multi-dimensional experimental designs, including histone PTM patterns and PTM crosstalk. The source code is available at https://github.com/veitveit/CrossTalkMapper.

中文翻译：

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使用 PTM-CrossTalkMapper 可视化组蛋白修饰的动态及其串扰

大规模、多维组学数据的可视化是一项重大挑战。蛋白质组学研究中的实验研究设计产生多个数据层，例如数百种蛋白质之间的关系、它们作为时间或扰动的函数的相互作用和丰度，以及翻译后修饰 (PTM) 和等位基因变体（蛋白质型）的动力学。蛋白质和蛋白质组的这些不同级别和类型的信息使数据分析和富有洞察力和可理解的图形可视化的生成复杂化。组蛋白的中下质谱现在可以量化数百种组蛋白蛋白质型，包括组蛋白分子内不同氨基酸残基的共存甲基化、乙酰化和磷酸化事件。组蛋白 PTM 景观在染色质活性的调节以及转录和表观遗传控制中起主导作用。这些可逆修饰的动力学由读取器、写入器和擦除器酶控制，它们协同调节依赖于组蛋白和染色质核小体中多个相互依赖的 PTM 标记的分子机制。这种 PTM 串扰可以量化并提供设置组蛋白 PTM 景观和染色质活动的基本规则的详细图片，并且可以通过我们的 CrosstalkDB 平台向社区提供。在这里，我们开发了一种新的计算方法 PTM-CrossTalkMapper，用于可视化不同实验条件下组蛋白 PTM 的动态，复制和蛋白质组在景观上，从而以更易于理解的方式描述 PTM 之间的串扰和相互作用。我们展示了在衰老过程中将不同级别的信息结合到小鼠器官中组蛋白 PTM 动态的串扰图上的能力。PTM-CrossTalkMapper 工具包提供了灵活的功能，可以在多维实验设计的各种场景中创建这些映射，包括组蛋白 PTM 模式和 PTM 串扰。源代码可从 https://github.com/veitveit/CrossTalkMapper 获得。包括组蛋白 PTM 模式和 PTM 串扰。源代码可从 https://github.com/veitveit/CrossTalkMapper 获得。包括组蛋白 PTM 模式和 PTM 串扰。源代码可从 https://github.com/veitveit/CrossTalkMapper 获得。