Evolutionary dynamics of local pandemic H1N1/2009 influenza virus lineages revealed by whole-genome analysis

Virus gene sequencing and phylogenetics can be used to study the epidemiological dynamics of rapidly evolving viruses. With complete genome data, it becomes possible to identify and trace individual transmission chains of viruses such as influenza virus during the course of an epidemic. Here we sequenced 153 pandemic influenza H1N1/09 virus genomes from United Kingdom isolates from the first (127 isolates) and second (26 isolates) waves of the 2009 pandemic and used their sequences, dates of isolation, and geographical locations to infer the genetic epidemiology of the epidemic in the United Kingdom. We demonstrate that the epidemic in the United Kingdom was composed of many cocirculating lineages, among which at least 13 were exclusively or predominantly United Kingdom clusters. The estimated divergence times of two of the clusters predate the detection of pandemic H1N1/09 virus in the United Kingdom, suggesting that the pandemic H1N1/09 virus was already circulating in the United Kingdom before the first clinical case. Crucially, three clusters contain isolates from the second wave of infections in the United Kingdom, two of which represent chains of transmission that appear to have persisted within the United Kingdom between the first and second waves. This demonstrates that whole-genome analysis can track in fine detail the behavior of individual influenza virus lineages during the course of a single epidemic or pandemic.     

Estimating divergence dates from molecular sequences

The ability to date the time of divergence between lineages using molecular data provides the opportunity to answer many important questions in evolutionary biology. However, molecular dating techniques have previously been criticized for failing to adequately account for variation in the rate of molecular evolution. We present a maximum- likelihood approach to estimating divergence times that deals explicitly with the problem of rate variation. This method has many advantages over previous approaches including the following: (1) a rate constancy test excludes data for which rate heterogeneity is detected; (2) date estimates are generated with confidence intervals that allow the explicit testing of hypotheses regarding divergence times; and (3) a range of sequences and fossil dates are used, removing the reliance on a single calculated calibration rate. We present tests of the accuracy of our method, which show it to be robust to the effects of some modes of rate variation. In addition, we test the effect of substitution model and length of sequence on the accuracy of the dating technique. We believe that the method presented here offers solutions to many of the problems facing molecular dating and provides a platform for future improvements to such analyses.      

Estimating the Rate of Intersubtype Recombination in Early HIV-1 Group M Strains

West Central Africa has been implicated as the epicenter of the HIV-1 epidemic, and almost all group M subtypes can be found there. Previous analysis of early HIV-1 group M sequences from Kinshasa in the Democratic Republic of Congo, formerly Zaire, revealed that isolates from a number of individuals fall in different positions in phylogenetic trees constructed from sequences from opposite ends of the genome as a result of recombination between viruses of different subtypes. Here, we use discrete ancestral trait mapping to develop a procedure for quantifying HIV-1 group M intersubtype recombination across phylogenies, using individuals'' gag (p17) and env (gp41) subtypes. The method was applied to previously described HIV-1 group M sequences from samples obtained in Kinshasa early in the global radiation of HIV. Nine different p17 and gp41 intersubtype recombinant combinations were present in the data set. The mean number of excess ancestral subtype transitions (NEST) required to map individuals'' p17 subtypes onto the gp14 phylogeny samples, compared to the number required to map them onto the p17 phylogenies, and vice versa, indicated that excess subtype transitions occurred at a rate of approximately 7 × 10⁻³ to 8 × 10⁻³ per lineage per year as a result of intersubtype recombination. Our results imply that intersubtype recombination may have occurred in approximately 20% of lineages evolving over a period of 30 years and confirm intersubtype recombination as a substantial force in generating HIV-1 group M diversity.     

Comparative analyses for adaptive radiations

Biologists generally agree that most morphological variation between closely related species is adaptive. The most common method of comparative analysis to test for co-evolved character variation is based on a Brownian-motion model of character evolution. If we are to test for the evolution of character-covariation, and we believe that characters have evolved adaptively to fill niches during an adaptive radiation, then it is appropriate to employ appropriate models for character evolution. We show here that under several models of adaptive character evolution and coevolution during an adaptive radiation, which result in closely related species being more similar to each other than to more distantly related species, cross-species analyses are statistically more appropriate than contrast analyses. If the evolution of some traits fits the Brownian-motion model, while others evolve to fill niches during an adaptive radiation, it might be necessary to identify the number of relevant niche dimensions and the modes of character evolution before deciding on appropriate statistical procedures. Alternatively, maximum-likelihood procedures might be used to determine appropriate transformations of phylogenetic branch lengths that accord with particular models of character evolution.     

Fold or hold: experimental evolution in vitro

We introduce a system for experimental evolution consisting of populations of short oligonucleotides (Oli populations) evolving in a modified quantitative polymerase chain reaction (qPCR). It is tractable at the genetic, genomic, phenotypic and fitness levels. The Oli system uses DNA hairpins designed to form structures that self‐prime under defined conditions. Selection acts on the phenotype of self‐priming, after which differences in fitness are amplified and quantified using qPCR. We outline the methodological and bioinformatics tools for the Oli system here and demonstrate that it can be used as a conventional experimental evolution model system by test‐driving it in an experiment investigating adaptive evolution under different rates of environmental change.     

Phylogenetic evidence for deleterious mutation load in RNA viruses and its contribution to viral evolution

Populations of RNA viruses are often characterized by abundant genetic variation. However, the relative fitness of these mutations is largely unknown, although this information is central to our understanding of viral emergence, immune evasion, and drug resistance. Here we develop a phylogenetic method, based on the distribution of nonsynonymous and synonymous changes, to assess the relative fitness of polymorphisms in the structural genes of 143 RNA viruses. This reveals that a substantial proportion of the amino acid variation observed in natural populations of RNA viruses comprises transient deleterious mutations that are later purged by purifying selection, potentially limiting virus adaptability. We also demonstrate, for the first time, the existence of a relationship between amino acid variability and the phylogenetic distribution of polymorphisms. From this relationship, we propose an empirical threshold for the maximum viable deleterious mutation load in RNA viruses.     

Relax,Keep Walking — A Practical Guide to Continuous Phylogeographic Inference with BEAST

Spatially explicit phylogeographic analyses can be performed with an inference framework that employs relaxed random walks to reconstruct phylogenetic dispersal histories in continuous space. This core model was first implemented 10 years ago and has opened up new opportunities in the field of phylodynamics, allowing researchers to map and analyze the spatial dissemination of rapidly evolving pathogens. We here provide a detailed and step-by-step guide on how to set up, run, and interpret continuous phylogeographic analyses using the programs BEAUti, BEAST, Tracer, and TreeAnnotator.