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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: BACKGROUND, RESULTS. Meshes: Alleles, Gene Frequency, Genes, Viral, Genetic Variation, HIV-1, Models, Genetic, Mutation, Population Density, Recombination, Genetic, Selection, Genetic.
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Does selection dramatically reduce effective population size in HIV-1 infection? Context: In HIV-1 evolution, a 100-100,000 fold discrepancy between census size and effective population size (Ne) has been noted. Although it is well known that selection can reduce Ne, high in vivo mutation and recombination rates complicate attempts to quantify the effects of selection on HIV-1 effective size. We use the inbreeding coefficient and the variance in allele frequency at a linked neutral locus to estimate the reduction in Ne due to selection in the presence of mutation and recombination. With biologically realistic mutation rates, the reduction in Ne due to selection is determined by the strength of selection, i.e., the stronger the selection, the greater the reduction. However, the dependence of Ne on selection can break down if recombination rates are very high (e.g., r > or = 0.1). With biologically likely recombination rates, our model suggests that recurrent selective sweeps similar to those observed in vivo can reduce within-host HIV-1 effective population sizes by a factor of 300 or more.
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Although other factors, such as unequal viral reproduction rates and limited migration between tissue compartments contribute to reductions in Ne, our model suggests that recurrent selection plays a significant role in reducing HIV-1 effective population sizes in vivo. Final Decision: yes