In vivo mutation rates and the landscape of fitness costs of HIV-1

Abstract

Mutation rates and fitness costs of deleterious mutations are difficult to measure in vivo but essential for a quantitative understanding of evolution. Using whole genome deep sequencing data from longitudinal samples during untreated HIV-1 infection, we estimated mutation rates and fitness costs in HIV-1 from the dynamics of genetic variation. At approximately neutral sites, mutations accumulate with a rate of 1.2 × 10−5 per site per day, in agreement with the rate measured in cell cultures. We estimated the rate from G to A to be the largest, followed by the other transitions C to T, T to C, and A to G, while transversions are less frequent. At other sites, mutations tend to reduce virus replication. We estimated the fitness cost of mutations at every site in the HIV-1 genome using a model of mutation selection balance. About half of all non-synonymous mutations have large fitness costs (>10 percent), while most synonymous mutations have costs <1 percent. The cost of synonymous mutations is especially low in most of pol where we could not detect measurable costs for the majority of synonymous mutations. In contrast, we find high costs for synonymous mutations in important RNA structures and regulatory regions. The intra-patient fitness cost estimates are consistent across multiple patients, indicating that the deleterious part of the fitness landscape is universal and explains a large fraction of global HIV-1 group M diversity.

Estimating time of HIV-1 infection from next-generation sequence diversity

“…Most diversity in pol is synonymous and accumulates at 3rd codon positions, while diversity at 1st and 2nd codon positions remained low throughout. This pattern was less pronounced in other genes [24, 37] (see also S1 and S2 Figs). In env , in particular, frequent selective sweeps result in a saturation of diversity later in infection [17, 24].…”

“…The 1st and 2nd codon positions tend to be conserved since they result in mostly non-synonymous mutations. Depending on the fitness cost associated with the mutation, diversity at these sites saturates at different levels [37]. As the threshold x c is lowered, sites with higher and higher fitness costs contribute to the diversity measures and the effect of the saturation behavior becomes more pronounced.…”

Estimating time of HIV-1 infection from next-generation sequence diversity

“…Most diversity in pol is synonymous and accumulates at 3rd codon 129 positions, while diversity at 1st and 2nd codon positions remained low throughout. This 130 dichotomy was less pronounced in other genes [22,30] (see also S1 Fig and S2 Fig). In 131 env in particular frequent selective sweeps limit diversity later in infection [16,22].…”

“…We show that sequence diversity is a 28 useful biomarker that grows approximately linearly with time during the first 8 years of 29 infection. We found that the pol gene was best suited to calculate TI because diversity, 30 mostly at third positions, accumulated more steadily in pol than in other genomic 31 regions. Inclusion of intra-patient single nucleotide variants (iSNVs, also referred to as 32 "polymorphisms") down to the detection limit of NGS (i.e.…”

“…Therefore we further consider only 3rd codon positions in pol, 167 which gave the most precise TI estimates. saturates [30]. As the threshold x c is lowered, sites with higher and higher fitness costs 199 contribute to the diversity measures and the effect of the saturation behavior becomes 200 more pronounced.…”