PLoS Computational Biology (Jan 2012)

Highly sensitive and specific detection of rare variants in mixed viral populations from massively parallel sequence data.

  • Alexander R Macalalad,
  • Michael C Zody,
  • Patrick Charlebois,
  • Niall J Lennon,
  • Ruchi M Newman,
  • Christine M Malboeuf,
  • Elizabeth M Ryan,
  • Christian L Boutwell,
  • Karen A Power,
  • Doug E Brackney,
  • Kendra N Pesko,
  • Joshua Z Levin,
  • Gregory D Ebel,
  • Todd M Allen,
  • Bruce W Birren,
  • Matthew R Henn

DOI
https://doi.org/10.1371/journal.pcbi.1002417
Journal volume & issue
Vol. 8, no. 3
p. e1002417

Abstract

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Viruses diversify over time within hosts, often undercutting the effectiveness of host defenses and therapeutic interventions. To design successful vaccines and therapeutics, it is critical to better understand viral diversification, including comprehensively characterizing the genetic variants in viral intra-host populations and modeling changes from transmission through the course of infection. Massively parallel sequencing technologies can overcome the cost constraints of older sequencing methods and obtain the high sequence coverage needed to detect rare genetic variants ( 97% sensitivity and > 97% specificity on control read sets. On data derived from a patient after four years of HIV-1 infection, V-Phaser detected 2,015 variants across the -10 kb genome, including 603 rare variants (< 1% frequency) detected only using phase information. V-Phaser identified variants at frequencies down to 0.2%, comparable to the detection threshold of allele-specific PCR, a method that requires prior knowledge of the variants. The high sensitivity and specificity of V-Phaser enables identifying and tracking changes in low frequency variants in mixed populations such as RNA viruses.