Virus-driven human gene misregulation in disease

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ABSTRACT Thousands of genetic variants have been established for hundreds of human diseases. Yet, the vast majority of these diseases remain idiopathic. Interplay between genetics and the environment likely plays a role in many diseases. In particular, hundreds of associations between viral exposure and disease risk have been established. But with rare exceptions, the mechanisms underlying increased disease risk are unknown. We have recently discovered that the Epstein-Barr virus EBNA2 transcriptional co-factor binds up to half of the risk loci associated with seven autoimmune diseases (142 loci in total), with many examples of allele-dependent EBNA2 binding to autoimmune risk variants. We hypothesize that risk allele-dependent binding of viral TFs explains why other viruses cause or influence specific diseases. However, the data required to discover these mechanisms are currently incomplete. Herpesviruses and human papilloma virus play established roles in several human diseases, and their genomes encode many TFs. We will generate the functional genomics datasets needed to discover the roles of these viral TFs (vTFs) in human disease processes. We anticipate discovering multiple causal human disease variants whose mechanisms act in a viral TF and allele- dependent manner, leading to understanding of disease mechanisms and new therapeutic opportunities. Our approach is a generalizable blueprint for global characterization of pathogenic effects on host gene regulation. Aim 1. Create global maps of viral TF-driven human gene regulation. For eight viruses, we will transfect a viral TF into physiologically and pathologically relevant human primary cells and cell lines. We will measure the effect of vTFs on human gene expression by performing RNA-seq in cells with and without vTF transfection. We will monitor the binding of vTFs to the human genome using chromatin immunoprecipitation and calculate the enrichment of each vTF at established risk loci for all human diseases using our RELI algorithm. Aim 2. Uncover the mechanisms and downstream functional impact of viral TF-human genome interactions. We will characterize the mechanisms by which vTFs alter the human regulatory landscape. We will measure the effect of vTFs on human chromatin accessibility (ATAC-seq) and DNA looping (HiChIP-seq). We will use these datasets to construct computational models evaluating disease-relevant mechanisms. We will examine downstream effects of vTF activity on human cell phenotypes by monitoring cell proliferation, cytokine release, and growth factor release subsequent to vTF transfection. Aim 3. Test the allele-dependency of viral TF-provoked human disease mechanisms. We will identify vTF interactions involving human disease risk allele-dependent mechanisms. We will functionally screen for vTF- and disease risk allele-dependent effects on gene regulatory activity using Massively Parallel Reporter Assays. We will interrogate virus-host genomic datasets for allelic behavior using our MARIO computational pipeline. We will validate risk allele-dependent vTF mechanisms using CRISPR-based genome editing.