Detecting Selection in the HIV-1 Genome during Sexual Transmission Events

Viruses. 2022 Feb 16;14(2):406. doi: 10.3390/v14020406.


Little is known about whether and how variation in the HIV-1 genome affects its transmissibility. Assessing which genomic features of HIV-1 are under positive or negative selection during transmission is challenging, because very few virus particles are typically transmitted, and random genetic drift can dilute genetic signals in the recipient virus population. We analyzed 30 transmitter-recipient pairs from the Zurich Primary HIV Infection Study and the Swiss HIV Cohort Study using near full-length HIV-1 genomes. We developed a new statistical test to detect selection during transmission, called Selection Test in Transmission (SeTesT), based on comparing the transmitter and recipient virus population and accounting for the transmission bottleneck. We performed extensive simulations and found that sensitivity of detecting selection during transmission is limited by the strong population bottleneck of few transmitted virions. When pooling individual test results across patients, we found two candidate HIV-1 genomic features for affecting transmission, namely amino acid positions 3 and 18 of Vpu, which were significant before but not after correction for multiple testing. In summary, SeTesT provides a general framework for detecting selection based on genomic sequencing data of transmitted viruses. Our study shows that a higher number of transmitter-recipient pairs is required to improve sensitivity of detecting selection.

Keywords: HIV-1; SHCS; Selection Test in Transmission (SeTesT); Vpu; ZPHI; transmission; transmitter–recipient pairs.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Disease Transmission, Infectious / statistics & numerical data
  • Female
  • Genetic Variation
  • HIV Infections / transmission*
  • HIV-1 / genetics*
  • Heterosexuality*
  • Human Immunodeficiency Virus Proteins / genetics
  • Humans
  • Male
  • Models, Statistical
  • Molecular Sequence Data
  • Point Mutation
  • Selection, Genetic*


  • Human Immunodeficiency Virus Proteins