Abstract | A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control

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A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control

Abstract

Affiliation details

École Polytechnique Fédérale de Lausanne, Switzerland; University Hospital and University of Lausanne, Switzerland; Eötvös Loránd University and the Hungarian Academy of Sciences, Hungary; Swiss Institute of Bioinformatics, Switzerland; Microsoft Research, United States; BC Centre for Excellence in HIV/AIDS, Canada; Simon Fraser University, Canada; Murdoch University, Australia; Vanderbilt University Medical Center, United States; Universitat Autònoma de Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Spain; Instituto de Salud Carlos III, Spain; University of Bern & Inselspital, Switzerland; University Hospital and University of Zürich, Switzerland; Regional Hospital of Lugano, Switzerland; Cantonal Hospital, Switzerland; University of Basel, Switzerland; Geneva University Hospitals, Switzerland; St. Petersburg State University, Russia; Massachusetts General Hospital, United States; University of British Columbia, Canada

HIV-1 sequence diversity is affected by selection pressures arising from host genomic factors. Using paired human and viral data from 1071 individuals, we ran >3000 genome-wide scans, testing for associations between host DNA polymorphisms, HIV-1 sequence variation and plasma viral load (VL), while considering human and viral population structure. We observed significant human SNP associations to a total of 48 HIV-1 amino acid variants (p<2.4 × 10−12). All associated SNPs mapped to the HLA class I region. Clinical relevance of host and pathogen variation was assessed using VL results. We identified two critical advantages to the use of viral variation for identifying host factors: (1) association signals are much stronger for HIV-1 sequence variants than VL, reflecting the ‘intermediate phenotype’ nature of viral variation; (2) association testing can be run without any clinical data. The proposed genome-to-genome approach highlights sites of genomic conflict and is a strategy generally applicable to studies of host–pathogen interaction.

DOI: http://dx.doi.org/10.7554/eLife.01123.001