Evolution of the Human Immunodeficiency Virus Envelope Gene Is Dominated by Purifying Selection

Abstract

The evolution of the human immunodeficiency virus (HIV-1) during chronic infection involves the rapid, continuous turnover of genetic diversity. However, the role of natural selection, relative to random genetic drift, in governing this process is unclear. We tested a stochastic model of genetic drift using partial envelope sequences sampled longitudinally in 28 infected children. In each case the Bayesian posterior (empirical) distribution of coalescent genealogies was estimated using Markov chain Monte Carlo methods. Posterior predictive simulation was then used to generate a null distribution of genealogies assuming neutrality, with the null and empirical distributions compared using four genealogy-based summary statistics sensitive to nonneutral evolution. Because both null and empirical distributions were generated within a coalescent framework, we were able to explicitly account for the confounding influence of demography. From the distribution of corrected P-values across patients, we conclude that empirical genealogies are more asymmetric than expected if evolution is driven by mutation and genetic drift only, with an excess of lowfrequency polymorphisms in the population. This indicates that although drift may still play an important role, natural selection has a strong influence on the evolution of HIV-1 envelope. A negative relationship between effective population size and substitution rate indicates that as the efficacy of selection increases, a smaller proportion of mutations approach fixation in the population. This suggests the presence of deleterious mutations. We therefore conclude that intrahost HIV-1 evolution in envelope is dominated by purifying selection against low-frequency deleterious mutations that do not reach fixation.

Synonymous Substitution Rates Predict HIV Disease Progression as a Result of Underlying Replication Dynamics

“…The high mutation rate of HIV is expected to lead to a considerable deleterious mutation load in the viral population, such that the most recent mutations, segregating on external branches of HIV phylogenies, are likely to be deleterious [28,29]. This effect is present in each of the nine patients analyzed; mean substitution rates were consistently higher for external branches than for internal branches (Figure 1).…”

Coalescent Inference Using Serially Sampled, High-Throughput Sequencing Data from Intrahost HIV Infection

“…A natural solution to this problem would be to fit exponential functions between consecutive time points. More importantly, however, selective responses to the host immune system are known to be an important evolutionary factor (Edwards et al 2006;Lemey et al 2006), having an effect on intrahost genealogies that is not fully captured merely by adjusting the effective population size. Other commonly used methods such as BEAST (Drummond et al 2002(Drummond et al , 2005(Drummond et al , 2012Drummond and Rambaut 2007;Minin et al 2008) also ignore the effects of selection on genealogies (as well as ignoring recombination); thus, developing methods that can robustly account for both selection and recombination (and indeed other factors) remains a challenging task.…”

“…As a consequence, the genetic diversity within a single infection can be very high. Important clinical variables, such as the rate of progression to AIDS and the set point viral load, are related to the diversity and evolution of the within-patient viral population (Shankarappa et al 1999;Ross and Rodrigo 2002;Williamson 2003;Edwards et al 2006;Lemey et al 2007;Pybus and Rambaut 2009), and so genetic data from these populations are of medical relevance in addition to providing insight into molecular evolutionary processes. However, population genomic inference from HIV sequence data can be challenging as result of high rates of mutation and recombination within a small RNA genome of $10 kb.…”

Weak Selection and Protein Evolution

“…Numerous studies have reported PGIM patterns consistent with slightly deleterious amino acid changes. Excess rare polymorphisms and higher r pd for nonsynonymous compared to synonymous variation appear to be general patterns in viral (Edwards et al 2006;Pybus et al 2006;Hughes 2009) and bacterial genomes (Hughes 2005;Charlesworth and Eyre-Walker 2006;Rocha et al 2006;Hughes et al 2008) as well as in animal mtDNA (Ballard and Kreitman 1994;Nachman et al 1996;Rand and Kann 1996;Hasegawa et al 1998;Wise et al 1998;Weinreich and Rand 2000;Gerber et al 2001;Subramanian et al 2009). Similar patterns have been noted in nuclear genes from yeast (Doniger et al 2008;Liti et al 2009), Drosophila (Akashi 1996;Fay et al 2002;Loewe et al 2006;Andolfatto et al 2011), humans (Cargill et al 1999;Sunyaev et al 2000;Hughes et al 2003;Williamson et al 2005;Boyko et al 2008;Keightley and Halligan 2011;Subramanian 2012), mice (Halligan et al 2010), and plants (Bustamante et al 2002;Nordborg et al 2005;Foxe et al 2008;Fujimoto et al 2008;Gossmann et al 2010;Branca et al 2011;.…”