Abstract

Advances in mass spectrometry (MS) have revolutionized the ability to measure global changes in histone post-translational modifications (PTMs). The method routinely quantifies over 60 modification states in a single sample, far exceeding the capabilities of traditional western blotting. Thus, MS-based histone analysis has become an increasingly popular tool for understanding how genetic and environmental factors influence epigenetic states. However, histone proteomics experiments exhibit unique challenges, such as batch-to-batch reproducibility, accurate peak integration, and noisy data. Here, we discuss the steps of histone PTM analysis, from sample preparation and peak integration to data analysis and validation. We outline a set of best practices for ensuring data quality, accurate normalization, and robust statistics. Using these practices, we quantify histone modifications in 5 human cell lines, revealing that each cell line exhibits a unique epigenetic signature. We also provide a reproducible workflow for histone PTM analysis in the form of an R script, which is freely available at https://github.com/DenuLab/HistoneAnalysisWorkflow.

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