4.8 Article

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

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ELIFE
卷 2, 期 -, 页码 -

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ELIFE SCIENCES PUBLICATIONS LTD
DOI: 10.7554/eLife.01123

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资金

  1. Swiss National Science Foundation [33CS30_134277/Swiss HIV Cohort Study, 31003A_132863/1, PP00P3_133703/1]
  2. Santos Suarez Foundation, Lausanne
  3. Hungarian Academy of Sciences
  4. Michael Smith Foundation for Health Research
  5. Canadian Institutes of Health Research
  6. Sciex-NMS Program [10.267]
  7. Spanish Ministry of Science and Innovation [SAF 2007-61036, 2010-17226, 2010-18917]
  8. Fundacion para la investigacion y prevencion del SIDA en Espana [36558/06, 36641/07, 36779/08, 360766/09]
  9. RETIC de Investigacion en SIDA [RD06/006/0036]
  10. National Institute of Allergy and Infectious Diseases (NIAID) [P01-AI074415]
  11. Bill and Melinda Gates Foundation
  12. SNF Professorship [PP00P3_133703/1]
  13. ICREA Funding Source: Custom
  14. Swiss National Science Foundation (SNF) [31003A_132863, PP00P3_133703] Funding Source: Swiss National Science Foundation (SNF)

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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 x 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.

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