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Updated: Apr 5, 2026

Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing
Published on: October 16, 2018
Disentangling the impact of within-host evolution and transmission dynamics on the tempo of HIV-1 evolution
Bram Vrancken1, Guy Baele, Anne-Mieke Vandamme
1aDepartment of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium bCentro de Malária e Outras Doenças Tropicais Instituto de Higiene e Medicina Tropical and Unidade de Microbiologia, Universidade Nova de Lisboa, Lisboa, Portugal cDepartment of Biomathematics dDepartment of Human Genetics, David Geffen School of Medicine at UCLA eDepartment of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles, California, USA.
Objective:
To determine how HIV-1 risk groups impact transmitted diversity and the tempo of viral evolution at a population scale.
Methods:
We investigated a set of previously described transmission chains (n = 70) using a population genetic approach, and tested whether the expected differences in proportions of multivariant transmissions are reflected by varying proportions of transmitted diversity between men having sex with men (MSM) and heterosexual (HET) subpopulations - the largest contributors to HIV spread. To assess evolutionary rate differences among the different risk groups, we compiled risk group datasets for subtypes A1, B and CRF01_AE, and directly compared the absolute substitution rate and its synonymous and non-synonymous components.
Results:
There was sufficient demographic signal to inform the transmission model in Bayesian evolutionary analysis by sampling trees using env data to compare the transmission bottleneck size between the MSM and HET risk groups. We found no indications for a different proportion of transmitted genetic diversity at the population level between these groups. In the direct rate comparisons between the risk groups, however, we consistently recovered a higher evolutionary rate in the male-dominated risk group compared to the HET datasets.
Conclusion:
We find that the risk group composition affects the viral evolutionary rate and therefore potentially also the adaptation rate. In particular, risk group-specific sex ratios, and the variation in within-host evolutionary rates between men and women, impose evolutionary rate differences at the epidemic level, but we cannot exclude a role of varying transmission rates.
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