Within-host and between-host evolutionary rates across the HIV-1 genome

Alizon, Samuel; Fraser, Christophe

doi:10.1186/1742-4690-10-49

Cited by 116 publications

(140 citation statements)

References 33 publications

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“…It is worth noting that some pairwise MLEs are suggestive of a higher mutation rate in parts of the env region (described previously by Alizon and Fraser 2013). There is also some variability in the median-based recombination rate estimates across regions, but this is consistent with Monte Carlo sampling error.…”

Section: Real Data Analysissupporting

confidence: 72%

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

et al. 2016

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Human immunodeficiency virus (HIV) is a rapidly evolving pathogen that causes chronic infections, so genetic diversity within a single infection can be very high. High-throughput "deep" sequencing can now measure this diversity in unprecedented detail, particularly since it can be performed at different time points during an infection, and this offers a potentially powerful way to infer the evolutionary dynamics of the intrahost viral population. However, population genomic inference from HIV sequence data is challenging because of high rates of mutation and recombination, rapid demographic changes, and ongoing selective pressures. In this article we develop a new method for inference using HIV deep sequencing data, using an approach based on importance sampling of ancestral recombination graphs under a multilocus coalescent model. The approach further extends recent progress in the approximation of so-called conditional sampling distributions, a quantity of key interest when approximating coalescent likelihoods. The chief novelties of our method are that it is able to infer rates of recombination and mutation, as well as the effective population size, while handling sampling over different time points and missing data without extra computational difficulty. We apply our method to a data set of HIV-1, in which several hundred sequences were obtained from an infected individual at seven time points over 2 years. We find mutation rate and effective population size estimates to be comparable to those produced by the software BEAST. Additionally, our method is able to produce local recombination rate estimates. The software underlying our method, Coalescenator, is freely available. KEYWORDS coalescent; importance sampling; HIV evolution; conditional sampling distribution; recombination H UMAN immunodeficiency virus (HIV) is a rapidly evolving pathogen that causes a chronic infection for an individual's lifetime. 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. Furthermore, natural selection is expected to play an important role in shaping within-host HIV genetic diversity (Rouzine and Coffin 1999;Neher and Leitner 2010;Batorsky et al. 2011;Pennings et al. 2014). For example, phylogenies constructed from serially sampled intrahost population sequences are typically characterized by a ladder-like topology (Shankarappa et al. 1999), indicating a rapid and continual tur...

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Section: Real Data Analysissupporting

confidence: 72%

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

et al. 2016

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“…Interestingly, Ho et al recently showed that the latent reservoir may be up to 60-fold greater than previously estimated [33], further corroborating the central role of latency in infection dynamics. The recent findings suggesting preferential transmission of latent viruses, which necessitates a prevalence of latent lineages in the plasma, are also in line with our results [9][10][11][12]. From a biological perspective, latency explains the overdispersion in the molecular clock, previously observed but poorly understood.…”

Section: Discussionsupporting

confidence: 91%

“…Recent findings suggest that latency may also be involved in transmission, as latent forms appear to be preferentially transmitted than more recent variants [9][10][11][12]. This implies that activated latent viruses are able to survive and propagate under immune pressure to reach sufficient numbers in the plasma to be transmitted.…”

Section: Introductionmentioning

confidence: 99%

Reduced evolutionary rates in HIV-1 reveal extensive latency periods among replicating lineages

Immonen

Leitner

2014

Retrovirology

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Background: HIV-1 can persist for the duration of a patient's life due in part to its ability to hide from the immune system, and from antiretroviral drugs, in long-lived latent reservoirs. Latent forms of HIV-1 may also be disproportionally involved in transmission. Thus, it is important to detect and quantify latency in the HIV-1 life cycle. Results: We developed a novel molecular clock-based phylogenetic tool to investigate the prevalence of HIV-1 lineages that have experienced latency. The method removes alternative sources that may affect evolutionary rates, such as hypermutation, recombination, and selection, to reveal the contribution of generation-time effects caused by latency. Our method was able to recover latent lineages with high specificity and sensitivity, and low false discovery rates, even on relatively short branches on simulated phylogenies. Applying the tool to HIV-1 sequences from 26 patients, we show that the majority of phylogenetic lineages have been affected by generation-time effects in every patient type, whether untreated, elite controller, or under effective or failing treatment. Furthermore, we discovered extensive effects of latency in sequence data (gag, pol, and env) from reservoirs as well as in the replicating plasma population. To better understand our phylogenetic findings, we developed a dynamic model of virus-host interactions to investigate the proportion of lineages in the actively replicating population that have ever been latent. Assuming neutral evolution, our dynamic modeling showed that under most parameter conditions, it is possible for a few activated latent viruses to propagate so that in time, most HIV-1 lineages will have been latent at some time in their past.

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“…On the other hand, HIV-1 rapidly evolves during the course of infection in response to selective pressure induced by the host's immune response [6]. Therefore, to develop an effective vaccine, it is necessary to continuously monitor rapid genetic changes [7,8].…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Dynamics of Tat in HIV-1 Subtypes B and C

2015

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Evolutionary characteristics of HIV-1 have mostly studied focusing its structural genes, Gag, Pol and Env. However, regarding the process of HIV-1's evolution, few studies emphasize on genetic changes in regulatory proteins. Here we investigate the evolutionary dynamics of HIV-1, targeting one of its important regulatory proteins, Tat. We performed a phylogenetic analysis and employed a Bayesian coalescent-based approach using the BEAST package to investigate the evolutionary changes in Tat over time in the process of HIV-1 evolution. HIV-1 sequences of subtypes B and C from different parts of the world were obtained from the Los Alamos database. The mean estimated nucleotide substitution rates for Tat in HIV-1 subtypes B and C were 1.53x10-3 (95% highest probability density- HPD Interval: 1.09 x10-3 to 2.08x10-3) and 2.14x10-3 (95% HPD Interval: 1.35 x10-3 to 2.91x10-3) per site per year, respectively, which is relatively low compared to structural proteins. The median times of the most recent common ancestors (tMRCA) were estimated to be around 1933 (95% HPD, 1907–1952) and 1956 (95% HPD, 1934–1970) for subtypes B and C, respectively. Our analysis shows that subtype C appeared in the global population two decades after the introduction of subtype B. A Gaussian Markov random field (GMRF) skyride coalescent analysis demonstrates that the early expansion rate of subtype B was quite high, rapidly progressing during the 1960s and 1970s to the early 1990s, after which the rate increased up to the 2010s. In contrast, HIV-1 subtype C exhibited a relatively slow occurrence rate until the late 1980s when there was a sharp increase up to the end of 1990s; thereafter, the rate of occurrence gradually slowed. Our study highlights the importance of examining the internal/regulatory genes of HIV-1 to understand its complete evolutionary dynamics. The study results will therefore contribute to better understanding of HIV-1 evolution.

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Within-host and between-host evolutionary rates across the HIV-1 genome

Cited by 116 publications

References 33 publications

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

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

Reduced evolutionary rates in HIV-1 reveal extensive latency periods among replicating lineages

Evolutionary Dynamics of Tat in HIV-1 Subtypes B and C

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