EpiTyping: analysis of epigenetic aberrations in parental imprinting and X-chromosome inactivation using RNA-seq

Human pluripotent stem cells (hPSCs) hold a central role in studying human development, in disease modeling and in regenerative medicine. These cells not only acquire genetic modifications when kept in culture, but they may also harbor epigenetic aberrations, mainly involving parental imprinting and...

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Veröffentlicht in:Nature protocols 2023-12, Vol.18 (12), p.3881-3917
Hauptverfasser: Sarel-Gallily, Roni, Keshet, Gal, Kinreich, Shay, Haim-Abadi, Guy, Benvenisty, Nissim
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Sprache:eng
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Zusammenfassung:Human pluripotent stem cells (hPSCs) hold a central role in studying human development, in disease modeling and in regenerative medicine. These cells not only acquire genetic modifications when kept in culture, but they may also harbor epigenetic aberrations, mainly involving parental imprinting and X-chromosome inactivation. Here we present a detailed bioinformatic protocol for detecting such aberrations using RNA sequencing data. We provide a pipeline designed to process and analyze RNA sequencing data for the identification of abnormal biallelic expression of imprinted genes, and thus detect loss of imprinting. Furthermore, we show how to differentiate among X-chromosome inactivation, full activation and aberrant erosion of X chromosome in female hPSCs. In addition to providing bioinformatic tools, we discuss the impact of such epigenetic variations in hPSCs on their utility for various purposes. This pipeline can be used by any user with basic understanding of the Linux command line. It is available on GitHub as a software container ( https://github.com/Gal-Keshet/EpiTyping ) and produces reliable results in 1–4 d. Key points This protocol provides a step-by-step procedure to infer the presence of epigenetic aberrations in human pluripotent stem cells from RNA sequencing data, specifically focusing on the identification of imprinting and X-inactivation status. The pipeline provides a simple and easy-to-use methodology for the reliable identification of gene- and locus-specific loss-of-imprinting events as well as the accurate discrimination among different X-inactivation statuses. The authors describe an easy-to-follow bioinformatic pipeline, called EpiTyping, for the identification of abnormal biallelic expression of imprinted genes and the analysis of the X-chromosome inactivation state from RNA sequencing data obtained from human pluripotent stem cells.
ISSN:1754-2189
1750-2799
DOI:10.1038/s41596-023-00898-5