Estimating the Timing of Mother-to-Child Transmission of the Human Immunodeficiency Virus Type 1 Using a Viral Molecular Evolution Model

Background: Mother-to-child transmission (MTCT) is responsible for most pediatric HIV-1 infections worldwide. It can occur during pregnancy, labor, or breastfeeding. Numerous studies have used coalescent and molecular clock methods to understand the epidemic history of HIV-1, but the timing of vertical transmission has not been studied using these methods. Taking advantage of the constant accumulation of HIV genetic variation over time and using longitudinally sampled viral sequences, we used a coalescent approach to investigate the timing of MTCT. Materials and Methods Six-hundred and twenty-two clonal env sequences from the RNA and DNA viral population were longitudinally sampled from nine HIV-1 infected mother-and-child pairs [range: 277–1034 days]. For each transmission pair, timing of MTCT was determined using a coalescent-based model within a Bayesian statistical framework. Results were compared with available estimates of MTCT timing obtained with the classic biomedical approach based on serial HIV DNA detection by PCR assays. Results: Four children were infected during pregnancy, whereas the remaining five children were infected at time of delivery. For eight out of nine pairs, results were consistent with the transmission periods assessed by standard PCR-based assay. The discordance in the remaining case was likely confused by co-infection, with simultaneous introduction of multiple maternal viral variants at the time of delivery. Conclusions: The study provided the opportunity to validate the Bayesian coalescent approach that determines the timing of MTCT of HIV-1. It illustrates the power of population genetics approaches to reliably estimate the timing of transmission events and deepens our knowledge about the dynamics of viral evolution in HIV-infected children, accounting for the complexity of multiple transmission events

Using Classical Population Genetics Tools with Heterochroneous Data: Time Matters!

BACKGROUND:New polymorphism datasets from heterochroneous data have arisen thanks to recent advances in experimental and microbial molecular evolution, and the sequencing of ancient DNA (aDNA). However, classical tools for population genetics analyses do not take into account heterochrony between subsets, despite potential bias on neutrality and population structure tests. Here, we characterize the extent of such possible biases using serial coalescent simulations. METHODOLOGY/PRINCIPAL FINDINGS:We first use a coalescent framework to generate datasets assuming no or different levels of heterochrony and contrast most classical population genetic statistics. We show that even weak levels of heterochrony ( approximately 10% of the average depth of a standard population tree) affect the distribution of polymorphism substantially, leading to overestimate the level of polymorphism theta, to star like trees, with an excess of rare mutations and a deficit of linkage disequilibrium, which are the hallmark of e.g. population expansion (possibly after a drastic bottleneck). Substantial departures of the tests are detected in the opposite direction for more heterochroneous and equilibrated datasets, with balanced trees mimicking in particular population contraction, balancing selection, and population differentiation. We therefore introduce simple corrections to classical estimators of polymorphism and of the genetic distance between populations, in order to remove heterochrony-driven bias. Finally, we show that these effects do occur on real aDNA datasets, taking advantage of the currently available sequence data for Cave Bears (Ursus spelaeus), for which large mtDNA haplotypes have been reported over a substantial time period (22-130 thousand years ago (KYA)). CONCLUSIONS/SIGNIFICANCE:Considering serial sampling changed the conclusion of several tests, indicating that neglecting heterochrony could provide significant support for false past history of populations and inappropriate conservation decisions. We therefore argue for systematically considering heterochroneous models when analyzing heterochroneous samples covering a large time scale

Human and Non-Human Primate Genomes Share Hotspots of Positive Selection

Among primates, genome-wide analysis of recent positive selection is currently limited to the human species because it requires extensive sampling of genotypic data from many individuals. The extent to which genes positively selected in human also present adaptive changes in other primates therefore remains unknown. This question is important because a gene that has been positively selected independently in the human and in other primate lineages may be less likely to be involved in human specific phenotypic changes such as dietary habits or cognitive abilities. To answer this question, we analysed heterozygous Single Nucleotide Polymorphisms (SNPs) in the genomes of single human, chimpanzee, orangutan, and macaque individuals using a new method aiming to identify selective sweeps genome-wide. We found an unexpectedly high number of orthologous genes exhibiting signatures of a selective sweep simultaneously in several primate species, suggesting the presence of hotspots of positive selection. A similar significant excess is evident when comparing genes positively selected during recent human evolution with genes subjected to positive selection in their coding sequence in other primate lineages and identified using a different test. These findings are further supported by comparing several published human genome scans for positive selection with our findings in non-human primate genomes. We thus provide extensive evidence that the co-occurrence of positive selection in humans and in other primates at the same genetic loci can be measured with only four species, an indication that it may be a widespread phenomenon. The identification of positive selection in humans alongside other primates is a powerful tool to outline those genes that were selected uniquely during recent human evolution

Détecter les effets de la sélection naturelle sur l'ADN par intelligence artificielle

https://planet-vie.ens.fr : Ressources en sciences de la vie pour les enseignants. https://planet-vie.ens.fr/Des approches d'intelligence artificielle présentent de nouvelles applications pour détecter l'impact de la sélection positive sur le génome. Elles démarrent par une phase supervisée sur simulations, pour être ensuite appliquées sur des données naturelles. La résolution est progressive suivant un processus dit d'apprentissage profond. Les premiers résultats obtenus sur des données humaines semblent très prometteurs

Distinguishing shared ancestral polymorphism from recent introgression

<p>Navascués & Depaulis (2008) Distinguishing shared ancestral polymorphism from recent introgression. SMBE Barcelona (Spain) 2008</p

Combining contemporary and ancient DNA in population genetic and phylogeographical studies

The analysis of ancient DNA in a population genetic or phylogeographical framework is an emerging field, as traditional analytical tools were largely developed for the purpose of analysing data sampled from a single time point. Markov chain Monte Carlo approaches have been successfully developed for the analysis of heterochronous sequence data from closed panmictic populations. However, attributing genetic differences between temporal samples to mutational events between time points requires the consideration of other factors that may also result in genetic differentiation. Geographical effects are an obvious factor for species exhibiting geographical structuring of genetic variation. The departure from a closed panmictic model require researchers to either exploit software developed for the analysis of isochronous data, take advantage of simulation approaches using algorithms developed for heterochronous data, or explore approximate Bayesian computation. Here, we review statistical approaches employed and available software for the joint analysis of ancient and modern DNA, and where appropriate we suggest how these may be further developed