Sebastián Duchêne

Molecular-clock methods for estimating evolutionary rates and timescales.

The molecular clock presents a means of estimating evolutionary rates and timescales using genetic data. These estimates can lead to important insights into evolutionary processes and mechanisms, as well as providing a framework for further biological analyses. To deal with rate variation among genes and among lineages, a diverse range of molecular‐clock methods have been developed. These methods have been implemented in various software packages and differ in their statistical properties, ability to handle different models of rate variation, capacity to incorporate various forms of calibrating information and tractability for analysing large data sets. Choosing a suitable molecular‐clock model can be a challenging exercise, but a number of model‐selection techniques are available. In this review, we describe the different forms of evolutionary rate heterogeneity and explain how they can be accommodated in molecular‐clock analyses. We provide an outline of the various clock methods and models that are available, including the strict clock, local clocks, discrete clocks and relaxed clocks. Techniques for calibration and clock‐model selection are also described, along with methods for handling multilocus data sets. We conclude our review with some comments about the future of molecular clocks.

Analyses of evolutionary dynamics in viruses are hindered by a time-dependent bias in rate estimates

Time-scales of viral evolution and emergence have been studied widely, but are often poorly understood. Molecular analyses of viral evolutionary time-scales generally rely on estimates of rates of nucleotide substitution, which vary by several orders of magnitude depending on the timeframe of measurement. We analysed data from all major groups of viruses and found a strong negative relationship between estimates of nucleotide substitution rate and evolutionary timescale. Strikingly, this relationship was upheld both within and among diverse groups of viruses. A detailed case study of primate lentiviruses revealed that the combined effects of sequence saturation and purifying selection can explain this time-dependent pattern of rate variation. Therefore, our analyses show that studies of evolutionary time-scales in viruses require a reconsideration of substitution rates as a dynamic, rather than as a static, feature of molecular evolution. Improved modelling of viral evolutionary rates has the potential to change our understanding of virus origins.

Mitogenome Phylogenetics: The Impact of Using Single Regions and Partitioning Schemes on Topology, Substitution Rate and Divergence Time Estimation

The availability of mitochondrial genome sequences is growing as a result of recent technological advances in molecular biology. In phylogenetic analyses, the complete mitogenome is increasingly becoming the marker of choice, usually providing better phylogenetic resolution and precision relative to traditional markers such as cytochrome b (CYTB) and the control region (CR). In some cases, the differences in phylogenetic estimates between mitogenomic and single-gene markers have yielded incongruent conclusions. By comparing phylogenetic estimates made from different genes, we identified the most informative mitochondrial regions and evaluated the minimum amount of data necessary to reproduce the same results as the mitogenome. We compared results among individual genes and the mitogenome for recently published complete mitogenome datasets of selected delphinids (Delphinidae) and killer whales (genus Orcinus). Using Bayesian phylogenetic methods, we investigated differences in estimation of topologies, divergence dates, and clock-like behavior among genes for both datasets. Although the most informative regions were not the same for each taxonomic group (COX1, CYTB, ND3 and ATP6 for Orcinus, and ND1, COX1 and ND4 for Delphinidae), in both cases they were equivalent to less than a quarter of the complete mitogenome. This suggests that gene information content can vary among groups, but can be adequately represented by a portion of the complete sequence. Although our results indicate that complete mitogenomes provide the highest phylogenetic resolution and most precise date estimates, a minimum amount of data can be selected using our approach when the complete sequence is unavailable. Studies based on single genes can benefit from the addition of a few more mitochondrial markers, producing topologies and date estimates similar to those obtained using the entire mitogenome.

The impact of calibration and clock-model choice on molecular estimates of divergence times.

Phylogenetic estimates of evolutionary timescales can be obtained from nucleotide sequence data using the molecular clock. These estimates are important for our understanding of evolutionary processes across all taxonomic levels. The molecular clock needs to be calibrated with an independent source of information, such as fossil evidence, to allow absolute ages to be inferred. Calibration typically involves fixing or constraining the age of at least one node in the phylogeny, enabling the ages of the remaining nodes to be estimated. We conducted an extensive simulation study to investigate the effects of the position and number of calibrations on the resulting estimate of the timescale. Our analyses focused on Bayesian estimates obtained using relaxed molecular clocks. Our findings suggest that an effective strategy is to include multiple calibrations and to prefer those that are close to the root of the phylogeny. Under these conditions, we found that evolutionary timescales could be estimated accurately even when the relaxed-clock model was misspecified and when the sequence data were relatively uninformative. We tested these findings in a case study of simian foamy virus, where we found that shallow calibrations caused the overall timescale to be underestimated by up to three orders of magnitude. Finally, we provide some recommendations for improving the practice of molecular-clock calibration.

Neanderthal behaviour, diet, and disease inferred from ancient DNA in dental calculus

Recent genomic data have revealed multiple interactions between Neanderthals and modern humans, but there is currently little genetic evidence regarding Neanderthal behaviour, diet, or disease. Here we describe the shotgun-sequencing of ancient DNA from five specimens of Neanderthal calcified dental plaque (calculus) and the characterization of regional differences in Neanderthal ecology. At Spy cave, Belgium, Neanderthal diet was heavily meat based and included woolly rhinoceros and wild sheep (mouflon), characteristic of a steppe environment. In contrast, no meat was detected in the diet of Neanderthals from El Sidrón cave, Spain, and dietary components of mushrooms, pine nuts, and moss reflected forest gathering. Differences in diet were also linked to an overall shift in the oral bacterial community (microbiota) and suggested that meat consumption contributed to substantial variation within Neanderthal microbiota. Evidence for self-medication was detected in an El Sidrón Neanderthal with a dental abscess and a chronic gastrointestinal pathogen (Enterocytozoon bieneusi). Metagenomic data from this individual also contained a nearly complete genome of the archaeal commensal Methanobrevibacter oralis (10.2× depth of coverage)—the oldest draft microbial genome generated to date, at around 48,000 years old. DNA preserved within dental calculus represents a notable source of information about the behaviour and health of ancient hominin specimens, as well as a unique system that is useful for the study of long-term microbial evolution.

The Performance of the Date-Randomization Test in Phylogenetic Analyses of Time-Structured Virus Data

Rates and timescales of viral evolution can be estimated using phylogenetic analyses of time-structured molecular sequences. This involves the use of molecular-clock methods, calibrated by the sampling times of the viral sequences. However, the spread of these sampling times is not always sufficient to allow the substitution rate to be estimated accurately. We conducted Bayesian phylogenetic analyses of simulated virus data to evaluate the performance of the date-randomization test, which is sometimes used to investigate whether time-structured data sets have temporal signal. An estimate of the substitution rate passes this test if its mean does not fall within the 95% credible intervals of rate estimates obtained using replicate data sets in which the sampling times have been randomized. We find that the test sometimes fails to detect rate estimates from data with no temporal signal. This error can be minimized by using a more conservative criterion, whereby the 95% credible interval of the estimate with correct sampling times should not overlap with those obtained with randomized sampling times. We also investigated the behavior of the test when the sampling times are not uniformly distributed throughout the tree, which sometimes occurs in empirical data sets. The test performs poorly in these circumstances, such that a modification to the randomization scheme is needed. Finally, we illustrate the behavior of the test in analyses of nucleotide sequences of cereal yellow dwarf virus. Our results validate the use of the date-randomization test and allow us to propose guidelines for interpretation of its results.

17th Century Variola Virus Reveals the Recent History of Smallpox

Summary Smallpox holds a unique position in the history of medicine. It was the first disease for which a vaccine was developed and remains the only human disease eradicated by vaccination. Although there have been claims of smallpox in Egypt, India, and China dating back millennia [1, 2, 3, 4], the timescale of emergence of the causative agent, variola virus (VARV), and how it evolved in the context of increasingly widespread immunization, have proven controversial [4, 5, 6, 7, 8, 9]. In particular, some molecular-clock-based studies have suggested that key events in VARV evolution only occurred during the last two centuries [4, 5, 6] and hence in apparent conflict with anecdotal historical reports, although it is difficult to distinguish smallpox from other pustular rashes by description alone. To address these issues, we captured, sequenced, and reconstructed a draft genome of an ancient strain of VARV, sampled from a Lithuanian child mummy dating between 1643 and 1665 and close to the time of several documented European epidemics [1, 2, 10]. When compared to vaccinia virus, this archival strain contained the same pattern of gene degradation as 20th century VARVs, indicating that such loss of gene function had occurred before ca. 1650. Strikingly, the mummy sequence fell basal to all currently sequenced strains of VARV on phylogenetic trees. Molecular-clock analyses revealed a strong clock-like structure and that the timescale of smallpox evolution is more recent than often supposed, with the diversification of major viral lineages only occurring within the 18th and 19th centuries, concomitant with the development of modern vaccination.

Turnip mosaic potyvirus probably first spread to Eurasian brassica crops from wild orchids about 1000 years ago

Turnip mosaic potyvirus (TuMV) is probably the most widespread and damaging virus that infects cultivated brassicas worldwide. Previous work has indicated that the virus originated in western Eurasia, with all of its closest relatives being viruses of monocotyledonous plants. Here we report that we have identified a sister lineage of TuMV-like potyviruses (TuMV-OM) from European orchids. The isolates of TuMV-OM form a monophyletic sister lineage to the brassica-infecting TuMVs (TuMV-BIs), and are nested within a clade of monocotyledon-infecting viruses. Extensive host-range tests showed that all of the TuMV-OMs are biologically similar to, but distinct from, TuMV-BIs and do not readily infect brassicas. We conclude that it is more likely that TuMV evolved from a TuMV-OM-like ancestor than the reverse. We did Bayesian coalescent analyses using a combination of novel and published sequence data from four TuMV genes [helper component-proteinase protein (HC-Pro), protein 3(P3), nuclear inclusion b protein (NIb), and coat protein (CP)]. Three genes (HC-Pro, P3, and NIb), but not the CP gene, gave results indicating that the TuMV-BI viruses diverged from TuMV-OMs around 1000 years ago. Only 150 years later, the four lineages of the present global population of TuMV-BIs diverged from one another. These dates are congruent with historical records of the spread of agriculture in Western Europe. From about 1200 years ago, there was a warming of the climate, and agriculture and the human population of the region greatly increased. Farming replaced woodlands, fostering viruses and aphid vectors that could invade the crops, which included several brassica cultivars and weeds. Later, starting 500 years ago, inter-continental maritime trade probably spread the TuMV-BIs to the remainder of the world.

Comparative analysis estimates the relative frequencies of co-divergence and cross-species transmission within viral families

The cross-species transmission of viruses from one host species to another is responsible for the majority of emerging infections. However, it is unclear whether some virus families have a greater propensity to jump host species than others. If related viruses have an evolutionary history of co-divergence with their hosts there should be evidence of topological similarities between the virus and host phylogenetic trees, whereas host jumping generates incongruent tree topologies. By analyzing co-phylogenetic processes in 19 virus families and their eukaryotic hosts we provide a quantitative and comparative estimate of the relative frequency of virus-host co-divergence versus cross-species transmission among virus families. Notably, our analysis reveals that cross-species transmission is a near universal feature of the viruses analyzed here, with virus-host co-divergence occurring less frequently and always on a subset of viruses. Despite the overall high topological incongruence among virus and host phylogenies, the Hepadnaviridae, Polyomaviridae, Poxviridae, Papillomaviridae and Adenoviridae, all of which possess double-stranded DNA genomes, exhibited more frequent co-divergence than the other virus families studied here. At the other extreme, the virus and host trees for all the RNA viruses studied here, particularly the Rhabdoviridae and the Picornaviridae, displayed high levels of topological incongruence, indicative of frequent host switching. Overall, we show that cross-species transmission plays a major role in virus evolution, with all the virus families studied here having the potential to jump host species, and that increased sampling will likely reveal more instances of host jumping.

Genome-scale rates of evolutionary change in bacteria.

Estimating the rates at which bacterial genomes evolve is critical to understanding major evolutionary and ecological processes such as disease emergence, long-term host–pathogen associations and short-term transmission patterns. The surge in bacterial genomic data sets provides a new opportunity to estimate these rates and reveal the factors that shape bacterial evolutionary dynamics. For many organisms estimates of evolutionary rate display an inverse association with the time-scale over which the data are sampled. However, this relationship remains unexplored in bacteria due to the difficulty in estimating genome-wide evolutionary rates, which are impacted by the extent of temporal structure in the data and the prevalence of recombination. We collected 36 whole genome sequence data sets from 16 species of bacterial pathogens to systematically estimate and compare their evolutionary rates and assess the extent of temporal structure in the absence of recombination. The majority (28/36) of data sets possessed sufficient clock-like structure to robustly estimate evolutionary rates. However, in some species reliable estimates were not possible even with ‘ancient DNA’ data sampled over many centuries, suggesting that they evolve very slowly or that they display extensive rate variation among lineages. The robustly estimated evolutionary rates spanned several orders of magnitude, from approximately 10−5 to 10−8 nucleotide substitutions per site year−1. This variation was negatively associated with sampling time, with this relationship best described by an exponential decay curve. To avoid potential estimation biases, such time-dependency should be considered when inferring evolutionary time-scales in bacteria.