Understanding the impact of endogenous viruses on host biology: a combinedcomputational and experimental strategy

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The main goal of the project is to shed light on the impact of endogenous viruses (ERVs) on the host biology using a combined computational and experimental strategy (Figure 1), focusing on three important model organisms – human, chimpanzee, and mouse. We will use the comprehensive ERV annotation available from the HERVd database together with a number of other biological databases to identify functionally relevant ERVs by three alternative approaches. First, we will apply neutrality tests to search for human ERVs which are under positive or negative selection pressure based on the variation data across many human populations. Second, we will use data on antigen presentation to find ERV families, individual ERVs, and specific ERV loci that are under negative immune selection of thymocytes. Third, we will apply comparative genomics approaches to search for evolutionarily conserved ERV loci among different species. Candidate ERV loci identified by these multifarious bioinformatics approaches will be transcriptionally activated and repressed using the CRISPRi/a technology. Subsequently we will conduct RNA-seq analyses and identify differentially expressed host genes and entire molecular networks affected by activation or repression of ERVs. In a final step, the identified candidate genes will be modulated by CRISPR in pluripotent stem cells and their functional role will be investigated by molecular biological techniques. The project is expected to generate three types of outcomes. First, we will obtain novel biological insights into biological pathways and molecular networks which interact with and are affected by ERVs. Second, the project will yield novel insights into ERV evolution. For the first time we will conduct a large-scale phylogenetic study of ERVs, identify ancient elements conserved across specific taxonomic groups as well as organism-specific loci, and study their genomic context. Third, we hope to achieve significant methodological advances in the notoriously difficult area of ERV informatics. A broad spectrum of new bioinformatics approaches and automated analysis pipelines will be developed in the course of the project and all resulting data will be integrated into the HERVd database.