A comparison of methods for estimating substitution rates from ancient DNA sequence data

Tong, K. Jun; Duchêne, David A.; Duchêne, Sebastián; Geoghegan, Jemma L.; Ho, Simon Y. W.

doi:10.1186/s12862-018-1192-3

Cited by 27 publications

(21 citation statements)

References 60 publications

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“…The dog mitochondrial genome data contained samples from up to 36,000 years before the present. BETS detected temporal signal in these data, with a log Bayes factor of 38.77 for M het relative to M iso ; this result is consistent with that of a date-randomization test in a previous study (Tong et al 2018). The estimated substitution rate for these data using the best model had a mean of 1.08×10 −7 subs/site/year (95% HPD: 7.49×10 −8 to 1.52×10 −7 ).…”

Section: Resultssupporting

confidence: 90%

“…For sequence sampling times we considered the correct sampling times, no sampling times (i.e., isochronous), and permuted sampling times. We also specified tree priors as follows: an exponential-growth coalescent for the A/H1N2 influenza virus, Bordetella pertussis , coronaviruses, and Hepatitis B virus data sets, and a constant-size coalescent for the dog mitochondrial genomes as used by Tong et al (2018). We again chose the HKY+Γ substitution model, except in the analysis of Hepatitis B virus data, for which we used the GTR+Γ model (Tavaré 1986), and in the analysis of the dog data set for which we used the SRD06 substitution model (Shapiro et al 2006) for coding regions and the GTR+Γ for noncoding regions.…”

Section: Methodsmentioning

confidence: 99%

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Bayesian Evaluation of Temporal Signal in Measurably Evolving Populations

Duchêne

Lemey

Stadler

et al. 2019

Preprint

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Phylogenetic methods can use the sampling times of molecular sequence data to calibrate the molecular clock, enabling the estimation of evolutionary rates and timescales for rapidly evolving pathogens and data sets containing ancient DNA samples. A key aspect of such calibrations is whether a sufficient amount of molecular evolution has occurred over the sampling time window, that is, whether the data can be treated as having come from a measurably evolving population. Here we investigate the performance of a fully Bayesian evaluation of temporal signal (BETS) in sequence data. The method involves comparing the fit to the data of two models: a model in which the data are accompanied by the actual (heterochronous) sampling times, and a model in which the samples are constrained to be contemporaneous (isochronous). We conducted simulations under a wide range of conditions to demonstrate that BETS accurately classifies data sets according to whether they contain temporal signal or not, even when there is substantial among-lineage rate variation. We explore the behaviour of this classification in analyses of five empirical data sets: modern samples of A/H1N1 influenza virus, the bacterium Bordetella pertussis, coronaviruses from mammalian hosts, ancient DNA from Hepatitis B virus and mitochondrial genomes of dog species. Our results indicate that BETS is an effective alternative to other tests of temporal signal. In particular, this method has the key advantage of allowing a coherent assessment of the entire model, including the molecular clock and tree prior which are essential aspects of Bayesian phylodynamic analyses.

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Section: Resultssupporting

confidence: 90%

Section: Methodsmentioning

confidence: 99%

Bayesian Evaluation of Temporal Signal in Measurably Evolving Populations

Duchêne

Lemey

Stadler

et al. 2019

Preprint

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“…To assess the impact of fossil sampling, we first used a wide (85-15 Ma) and a narrow (85 -80 Ma) temporal interval, in each case either sampling fossils that were attaching randomly to the branches of the tree present at the time, or in a clustered manner, so that all but one fossil branches attached to each other ("phylo-temporal clustering", see Tong, et al 2018). The narrow interval of 5 Myr was then shifted over time, from 85-80 to 15-10 Ma, to assess the temporal depth needed in total-evidence dating analyses.…”

Section: Sampling Of Fossils and Fossil Charactersmentioning

confidence: 99%

Mismatch of the morphology model is mostly unproblematic in total-evidence dating: insights from an extensive simulation study

Klopfstein

Ryer

Coiro

et al. 2019

Preprint

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Calibrating the molecular clock is the most contentious step in every dating analysis, but the emerging total-evidence dating approach promises increased objectivity. It combines molecular and morphological data of extant and fossil taxa in a Bayesian framework.Information about absolute node ages stems from the inferred fossil placements and associated branch lengths, under the assumption of a morphological clock. We here use computer simulations to assess the impact of mismatch of the morphology model, such as misspecification of character states and transition rates, non-stationarity of the evolutionary process, and extensive variation of evolutionary rates among branches. Comparisons with published datasets suggest that, at least for evolutionary rates typically observed in discrete morphological characters, the total-evidence dating framework is surprisingly robust to these factors. We show that even with relatively low numbers of morphological characters sampled, extensive model mismatch is mostly irrelevant for the performance of the method.The only exception we found are cases of highly asymmetric state frequencies and thus transition rates, but these can be accounted for by appropriate morphology models. In contrast, we find that the temporal scope of fossil sampling has a major impact on divergence time estimates, with the time signal quickly eroding if only rather young fossils are included in an analysis. Our results suggest that total-evidence dating might work even without a good understanding of morphological evolution and that study design should instead focus on an adequate sampling of all relevant fossils, even those with highly incomplete preservation.

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“…It has also been shown that extinct samples can only provide reliable calibration information if the extinct samples are well distributed throughout the tree between the root and the tips (i.e. low phylo-temporal clustering) (Tong et al, 2018). The use of aDNA to date parasite origins is therefore most useful for relatively shallow divergence events, e.g.…”

Section: Incorporating Extinct Samples Into the Treementioning

confidence: 99%

The molecular clock as a tool for understanding host-parasite evolution

Warnock¹,

Engelstädter²

2020

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The molecular clock in combination with evidence from the geological record can be applied to infer the timing and dynamics of evolutionary events. This has enormous potential to shed light on the complex and often evasive evolution of parasites. Here, we provide an overview of molecular clock methodology and recent advances that increase the potential for the study of host-parasite coevolutionary dynamics, with a focus on Bayesian approaches to divergence time estimation. We highlight the challenges in applying these methods to the study of parasites, including the nature of parasite genomes, the incompleteness of the rock and fossil records, and the complexity of hostparasite interactions. Developments in models of molecular evolution and approaches to deriving temporal constraints from geological evidence will help overcome some of these issues. However, 1 we also describe a case study in which the timescale of host-parasite coevolution cannot easily be inferred using existing methods -that of the alpha-proteobacteria Wolbachia. We conclude by providing a prospective on future methodological developments and data collection that will facilitate in understanding the role of parasitism in deep time. IntroductionA timeline for events throughout geological history is required to address many questions in evolutionary biology, including establishing the sequence of key evolutionary transitions and assessing the role of environmental and evolutionary variables on the evolution of life (Rota-Stabelli et al., 2013;Betts et al., 2018;Morris et al., 2018;Silvestro et al., 2018). Due to the paucity of rocks from different time periods and environments, and the low fossilisation potential of many soft-bodied species, we cannot rely on the fossil record to establish this timeline very precisely (Benton et al., 2009; Parham et al., 2011;Holland, 2016). The genomes of living species provide an alternative source of evidence for inferring the sequence of events in deep time, although in themselves they provide no information about absolute time. Phylogenetic methods that enable us to leverage both sources of evidence simultaneously provide the most promising approach for generating a more precise timeline and a richer view of the past than either record can provide alone (Donoghue and Benton, 2007;Landis, 2017;Álvarez-Carretero et al., 2019).It is estimated that more than half of all living species are parasites (Windsor, 1998;Bass et al., 2015), that is, species that rely on a host organism for survival, at the expense of the other species.The ubiquity of the parasitic lifestyle and the often strong selection pressure imposed by parasites on their hosts (Hughes et al., 2012) indicate that parasites have played an important role in shaping the evolution of life, but the challenge in detecting many parasite species, both now and in the past, suggest that this role is not well understood (Dobson et al., 2008;De Baets and Littlewood, 2015). Estimating the time of origin of parasitism across different groups enables us to answer ...

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A comparison of methods for estimating substitution rates from ancient DNA sequence data

Cited by 27 publications

References 60 publications

Bayesian Evaluation of Temporal Signal in Measurably Evolving Populations

Bayesian Evaluation of Temporal Signal in Measurably Evolving Populations

Mismatch of the morphology model is mostly unproblematic in total-evidence dating: insights from an extensive simulation study

The molecular clock as a tool for understanding host-parasite evolution

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