Virus-mediated single-cell transcriptional heterogeneity and differential fates in EBV-driven lymphoproliferative disease models Authors Elliott D. SoRelle [1,2], Joanne Dai , Emma N. Bonglack , Emma M. Heckenberg , Katie Willard , Scott White , Jeffrey A. Bailey , Kris C. Wood [3,5], Benjamin B. Yellen [5,6], Cliburn Chan , & Micah A. Luftig  Affiliations  Department of Molecular Genetics and Microbiology, Duke University  Department of Biostatistics and Bioinformatics, Duke University  Department of Pharmacology and Cancer Biology, Duke University  Department of Pathology and Laboratory Medicine, Brown University  Celldom, Inc., San Carlos, CA  Department of Mechanical Engineering, Duke University Abstract Single-cell measurement and analytical techniques have become indispensable for studying changes in gene expression and regulation in the context of human diseases. Single-cell methods are especially well-suited to studies in virology, as they can reveal complex host-pathogen dynamics and resolve key factors that influence distinct fates of infected cells. In this work, we use single-cell RNA sequencing (scRNA-seq) to study gene expression in five lymphoblastoid cell lines (LCLs), which are derived from primary B cells immortalized by infection with Epstein-Barr Virus (EBV). We find that LCLs, which are widely used as lymphoma models and for genetic and immunologic studies, exhibit unexpected and significant transcriptional heterogeneity linked to distinct infection states of EBV. Notably, all five samples (including the prominent GM12878 line) comprise B cells across a continuum of transcriptional states ranging from EBV-induced NF-kappa B-mediated activation to terminal plasma cell differentiation. The presence of these and other distinct phenotypes highlight the influence of viral infection on cellular complexity and diversity. Moreover, our findings strongly suggest variable fitness of individual cells within LCL populations. To further investigate the dynamic nature of EBV infection with clonal resolution, we have designed time-resolved assays to track thousands of individual cells in parallel over days to weeks in culture using a recently reported microfluidic system. We expect that analysis of single-cell growth trajectories at high throughput will complement and deepen transcriptomic insights into EBV-induced lymphoproliferation and post-infection cellular fates.