Scientific ReportsGenetic & Genomic MedicinePeer-reviewed journal article
The influence of human genetic variation on Epstein-Barr virus sequence diversity
Sina RüegeriD, Christian HammeriD, Alexis Loetscher, Paul J. McLareniD, Dylan LawlessiD, Olivier NaretiD, Nina KhannaiD, Enos BernasconiiD, Matthias L. CavassiniiD, Huldrych F. GünthardiD, Christian R. KahlertiD, Andri RauchiD, Daniel Pearce DepledgeiD, Sofia MorfopoulouiD, Judith BreueriD, Evgeny M. ZdobnoviD, Jacques FellayiD, the Swiss HIV Cohort Study, Karoline Aebi‐PoppiD, Alexia AnagnostopoulosiD, Manuel BattegayiD, Jürg BöniiD, Dominique L. BrauniD, Heiner C. BucheriD, Alexandra CalmyiD, , Sabine YerlyiD
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Abstract
Epstein-Barr virus (EBV) is one of the most common viruses latently infecting humans. Little is known about the impact of human genetic variation on the large inter-individual differences observed in response to EBV infection. To search for a potential imprint of host genomic variation on the EBV sequence, we jointly analyzed paired viral and human genomic data from 268 HIV-coinfected individuals with CD4+ T cell count <200/mm3 and elevated EBV viremia. We hypothesized that the reactivated virus circulating in these patients could carry sequence variants acquired during primary EBV infection, thereby providing a snapshot of early adaptation to the pressure exerted on EBV by the individual immune response. We searched for associations between host and pathogen genetic variants, taking into account human and EBV population structure. Our analyses revealed significant associations between human and EBV sequence variation. Three polymorphic regions in the human genome were found to be associated with EBV variation: one at the amino acid level (BRLF1:p.Lys316Glu); and two at the gene level (burden testing of rare variants in BALF5 and BBRF1). Our findings confirm that jointly analyzing host and pathogen genomes can identify sites of genomic interactions, which could help dissect pathogenic mechanisms and suggest new therapeutic avenues.
- organism: human
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- approach: statistical model
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