Sampling-through-time in birth–death trees

Stadler, Tanja

doi:10.1016/j.jtbi.2010.09.010

Cited by 440 publications

(501 citation statements)

References 19 publications

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“…The MTBD process generalizes a constant rate birth-death process as a model for transmission [8,15]. Under the MTBD-m process, each individual has a unique state out of m possible states 1; .…”

Section: Methods (A) the Multi-type Birth-death Branching Modelmentioning

confidence: 99%

Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods

Stadler

Bonhoeffer

2013

Phil. Trans. R. Soc. B

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129

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One contribution of 18 to a Discussion Meeting Issue 'Next-generation molecular and evolutionary epidemiology of infectious disease'. Host population structure has a major influence on epidemiological dynamics. However, in particular for sexually transmitted diseases, quantitative data on population contact structure are hard to obtain. Here, we introduce a new method that quantifies host population structure based on phylogenetic trees, which are obtained from pathogen genetic sequence data. Our method is based on a maximum-likelihood framework and uses a multi-type branching process, under which each host is assigned to a type (subpopulation). In a simulation study, we show that our method produces accurate parameter estimates for phylogenetic trees in which each tip is assigned to a type, as well for phylogenetic trees in which the type of the tip is unknown. We apply the method to a Latvian HIV-1 dataset, quantifying the impact of the intravenous drug user epidemic on the heterosexual epidemic (known tip states), and identifying superspreader dynamics within the men-having-sex-with-men epidemic (unknown tip states).

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Section: Methods (A) the Multi-type Birth-death Branching Modelmentioning

confidence: 99%

Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods

Stadler

Bonhoeffer

2013

Phil. Trans. R. Soc. B

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129

211

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“…When no rate change occurs, my model simplifies to the well-studied constant rate birth-death processes (12)(13)(14)(15)(16). By deriving the likelihood function (Methods, Theorem 2.7) of a phylogenetic tree under the birth-death-shift model, maximum-likelihood time intervals together with each interval's diversification rate (speciation rate minus extinction rate) and turnover (extinction rate divided by speciation rate) can be estimated.…”

Section: A New Likelihood Approachmentioning

confidence: 99%

Mammalian phylogeny reveals recent diversification rate shifts

Stadler¹

2011

Proc. Natl. Acad. Sci. U.S.A.

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Phylogenetic trees of present-day species allow investigation of the rate of evolution that led to the present-day diversity. A recent analysis of the mammalian phylogeny challenged the view of explosive mammalian evolution after the Cretaceous-Tertiary (K/T) boundary (65 Mya). However, due to lack of appropriate methods, the diversification (speciation minus extinction) rates in the more recent past of mammalian evolution could not be determined. In this paper, I provide a method that reveals that the tempo of mammalian evolution did not change until ∼33 Mya. This constant period was followed by a peak of diversification rates between 33 and 30 Mya. Thereafter, diversification rates remained high and constant until 8.55 Mya. Diversification rates declined significantly at 8.55 and 3.35 Mya. Investigation of mammalian subgroups (marsupials, placentals, and the six largest placental subgroups) reveals that the diversification rate peak at 33-30 Mya is mainly driven by rodents, cetartiodactyla, and marsupials. The recent diversification rate decrease is significant for all analyzed subgroups but eulipotyphla, cetartiodactyla, and primates. My likelihood approach is not limited to mammalian evolution. It provides a robust framework to infer diversification rate changes and mass extinction events in phylogenies, reconstructed from, e. g., present-day species or virus data. In particular, the method is very robust toward noise and uncertainty in the phylogeny and can account for incomplete taxon sampling.macroevolution | maximum-likelihood inference | speciation rates I t has been a long-standing question whether the rise of presentday mammals began following the mass extinction event at the K/T boundary (1, 2). The hypothesis of a significant rise in mammals following the K/T boundary was challenged when the mammalian phylogeny, including 4,510 present-day species, became available (3). This phylogeny is ∼83% complete at the species level (4). It allowed detection of diversification rate (speciation rate minus extinction rate) shifts throughout the evolutionary past of almost all present-day mammals. No shift was detected at the K/T boundary; however, a peak in diversification rates at ∼93 Mya was detected (3).Estimating the time and amount of diversification rate changes is a key toward understanding evolutionary patterns (5, 6). For example, reliable diversification rate estimates can have the power to decide if species richness is typically due to intrinsic causes (the ancestor evolved a new feature) or extrinsic causes (the environment changed) or a complex combination of both. Already in 1996, Sanderson and Donoghue (ref. 5, p. 1) wrote "Few issues in evolutionary biology have received as much attention over the years [ . . . ] as those involving evolutionary rate." However, until now there has been no general framework available to estimate diversification rates and their changes through time.Detecting diversification rate changes is typically done by detecting changes in the slope of the lineages-through-time...

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“…These trees are used as Bayesian priors for phylogenies (i.e., topology and divergence times) in the tip-dating analysis presented in the main text. The equations presented here follow Stadler (2010), Didier et al (2012), and Stadler et al (2012), with subsequent modifications by Gavryushkina et al (2014). I encourage readers to refer to these references for additional details on birth-death sampling models and their applications.…”

Section: Appendix Probability Density Of Fbd Phylogenetic Treesmentioning

confidence: 99%

“…However, ordered trees are subsequently modified to labeled trees (using a conversion factor) to calculate likelihoods (Stadler, 2010). Ordered trees distinguish between left and right branches and identify nodes via a unique left-right path from the root, whereas labeled trees instead give sampled nodes distinct labels to describe branching patterns and divergences (Stadler, 2010;Gavryushikina et al, 2014). Each labeled phylogenetic tree (Ψ) consists of two elements: a discrete ranked tree topology Ψ and a continuous time vector τ.…”

Section: Appendix Probability Density Of Fbd Phylogenetic Treesmentioning

confidence: 99%

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Bayesian estimation of fossil phylogenies and the evolution of early to middle Paleozoic crinoids (Echinodermata)

Wright¹

2017

J. Paleontol.

137

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Abstract.-Knowledge of phylogenetic relationships among species is fundamental to understanding basic patterns in evolution and underpins nearly all research programs in biology and paleontology. However, most methods of phylogenetic inference typically used by paleontologists do not accommodate the idiosyncrasies of fossil data and therefore do not take full advantage of the information provided by the fossil record. The advent of Bayesian 'tip-dating' approaches to phylogeny estimation is especially promising for paleosystematists because time-stamped comparative data can be combined with probabilistic models tailored to accommodate the study of fossil taxa. Under a Bayesian framework, the recently developed fossilized birth-death (FBD) process provides a more realistic tree prior model for paleontological data that accounts for macroevolutionary dynamics, preservation, and sampling when inferring phylogenetic trees containing fossils. In addition, the FBD tree prior allows for the possibility of sampling ancestral morphotaxa. Although paleontologists are increasingly embracing probabilistic phylogenetic methods, these recent developments have not previously been applied to the deep-time invertebrate fossil record. Here, I examine phylogenetic relationships among Ordovician through Devonian crinoids using a Bayesian tip-dating approach. Results support several clades recognized in previous analyses sampling only Ordovician taxa, but also reveal instances where phylogenetic affinities are more complex and extensive revisions are necessary, particularly among the Cladida. The name Porocrinoidea is proposed for a well-supported clade of Ordovician 'cyathocrine' cladids and hybocrinids. The Eucladida is proposed as a clade name for the sister group of the Flexibilia herein comprised of cladids variously considered 'cyathocrines,' 'dendrocrines,' and/or 'poteriocrines' by other authors.

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Sampling-through-time in birth–death trees

Cited by 440 publications

References 19 publications

Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods

Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods

Mammalian phylogeny reveals recent diversification rate shifts

Bayesian estimation of fossil phylogenies and the evolution of early to middle Paleozoic crinoids (Echinodermata)

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