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Proc Natl Acad Sci U S A. 2018 Dec 11;115(50):12565-12572. doi: 10.1073/pnas.1814589115. Epub 2018 Nov 19.

ERVmap analysis reveals genome-wide transcription of human endogenous retroviruses.

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Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520.
Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06520.
Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520;
Howard Hughes Medical Institute, Chevy Chase, MD 20815.


Endogenous retroviruses (ERVs) are integrated retroviral elements that make up 8% of the human genome. However, the impact of ERVs on human health and disease is not well understood. While select ERVs have been implicated in diseases, including autoimmune disease and cancer, the lack of tools to analyze genome-wide, locus-specific expression of proviral autonomous ERVs has hampered the progress in the field. Here we describe a method called ERVmap, consisting of an annotated database of 3,220 human proviral ERVs and a pipeline that allows for locus-specific genome-wide identification of proviral ERVs that are transcribed based on RNA-sequencing data, and provide examples of the utility of this tool. Using ERVmap, we revealed cell-type-specific ERV expression patterns in commonly used cell lines as well as in primary cells. We identified 124 unique ERV loci that are significantly elevated in the peripheral blood mononuclear cells of patients with systemic lupus erythematosus that represent an IFN-independent signature. Finally, we identified additional tumor-associated ERVs that correlate with cytolytic activity represented by granzyme and perforin expression in breast cancer tissue samples. The open-source code of ERVmap and the accompanied web tool are made publicly available to quantify proviral ERVs in RNA-sequencing data with ease. Use of ERVmap across a range of diseases and experimental conditions has the potential to uncover novel disease-associated antigens and effectors involved in human health that is currently missed by focusing on protein-coding sequences.


RNA sequencing; cancer; endogenous retroviruses; lupus; retroelements

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