Abstract
Histone proteoforms, often presenting multiple co-occurring post-translational modifications (PTMs), are central to chromatin regulation and gene expression. A proteoform is a specific form of a protein that includes variations arising from genetic changes, alternative RNA splicing, proteolytic processing, and PTMs. Genome-indexed histone proteoforms define the histone code, influencing cellular phenotype by dictating DNA interacting partners. Understanding the dynamics of histone proteoforms is essential for elucidating chromatin-based regulatory mechanisms. Advances in middle-down and top-down proteomics enable accurate identification and quantitation of thousands of proteoforms in a single run. However, the resulting data complexity presents significant challenges for analysis and visualization. Here, we introduce two new computational methods to analyze the dynamics of histone PTMs and demonstrate their use in mouse organs during aging. The score that we term "normalized interplay" addresses limitations of the original crosstalk score "interplay" providing a more complete and accurate measure of PTM crosstalk. The second score, ΔI or "directional interplay" is an asymmetric measure quantifying the magnitude and directionality of crosstalk between PTMs. Applying our two-stage scoring approach to data from CrosstalkDB reveals the dynamics of histone H3 modifications during aging.