Single-Cell Histone Modification Profiling with Cell Enrichment Using sortChIC

Helena Viñas Gaza, Vivek Bhardwaj, Peter Zeller*

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    Abstract

    Histone post-translational modifications (PTMs) influence the overall structure of the chromatin and gene expression. Over the course of cell differentiation, the distribution of histone modifications is remodeled, resulting in cell type-specific patterns. In the past, their study was limited to abundant cell types that could be purified in necessary numbers. However, studying these cell type-specific dynamic changes in heterogeneous in vivo settings requires sensitive single-cell methods. Current advances in single-cell sequencing methods remove these limitations, allowing the study of nonpurifiable cell types. One complicating factor is that some of the most biologically interesting cell types, including stem and progenitor cells that undergo differentiation, only make up a small fraction of cells in a tissue. This makes whole-tissue analysis rather inefficient. In this chapter, we present a sort-assisted single-cell Chromatin ImmunoCleavage sequencing technique (sortChIC) to map histone PTMs in single cells. This technique combines the mapping of histone PTM location in combination with surface staining-based enrichment, to allow the integration of established strategies for rare cell type enrichment. In general terms, this will enable researchers to quantify local and global chromatin changes in dynamic complex biological systems and can provide additional information on their contribution to lineage and cell-type specification in physiological conditions and disease.

    Original languageEnglish
    Pages (from-to)215-241
    Number of pages27
    JournalMethods in molecular biology (Clifton, N.J.)
    Volume2846
    DOIs
    Publication statusPublished - 15 Aug 2024

    Keywords

    • Chromatin
    • Epigenetics
    • FACS sorting
    • Histone modifications
    • Sequencing data
    • Single-cell ChIC-seq technique

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