Modelling the evolution of protein coding sequences sampled from Measurably Evolving Populations

Goode, Matthew; Guindon, Stéphane; Rodrigo, Allen G.

doi:10.1142/9781848163324_0013

Cited by 4 publications

(12 citation statements)

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“…For example, while human population size, urban densities, per cent forested areas, and HDI might be relatively stable or change very gradually, airline traffic has changed significantly, both in frequency and the connectivity between countries. Future studies can include the utilization of the epoch model ( Goode et al, 2008 ; Bielejec et al, 2014 in the investigation of diffusion factors, as it allows different rate matrices to be specified for different time periods.…”

Section: Discussionmentioning

confidence: 99%

Determinants of dengue virus dispersal in the Americas

et al. 2020

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Dengue viruses (DENV) are classified into four serotypes, each of which contains multiple genotypes. DENV genotypes introduced into the Americas over the past five decades have exhibited different rates and patterns of spatial dispersal. In order to understand factors underlying these patterns we utilized a statistical framework that allows for the integration of ecological, socioeconomic and air transport mobility data as predictors of viral diffusion while inferring the phylogeographic history. Predictors describing spatial diffusion based on several covariates were compared using a generalized linear model (GLM) approach, where the support for each scenario and its contribution is estimated simultaneously from the data set. While different predictors were identified for different serotypes, our analysis suggests that overall diffusion of DENV-1, -2, and -3 in the Americas was associated with airline traffic. The other significant predictors included human population size, the geographical distance between countries and between urban centers and the density of people living in urban environments.

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Section: Discussionmentioning

confidence: 99%

Determinants of dengue virus dispersal in the Americas

et al. 2020

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“…To test this hypothesis, we used models that build upon the standard Mk models typically used to model discrete traits, but allows the rate of gains and losses to change at a discrete time point along the phylogeny. We thus divide the phylogeny into two “epochs” in which independent models of trait evolution are fit to each epoch [ 54 – 56 ]. Thus, the model has 3 additional parameters, the location of the time shift, and the change in the rate of both gains and losses after the time shift.…”

Section: Methodsmentioning

confidence: 99%

A Comprehensive Study of Cyanobacterial Morphological and Ecological Evolutionary Dynamics through Deep Geologic Time

2016

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Cyanobacteria have exerted a profound influence on the progressive oxygenation of Earth. As a complementary approach to examining the geologic record—phylogenomic and trait evolutionary analyses of extant species can lead to new insights. We constructed new phylogenomic trees and analyzed phenotypic trait data using novel phylogenetic comparative methods. We elucidated the dynamics of trait evolution in Cyanobacteria over billion-year timescales, and provide evidence that major geologic events in early Earth’s history have shaped—and been shaped by—evolution in Cyanobacteria. We identify a robust core cyanobacterial phylogeny and a smaller set of taxa that exhibit long-branch attraction artifacts. We estimated the age of nodes and reconstruct the ancestral character states of 43 phenotypic characters. We find high levels of phylogenetic signal for nearly all traits, indicating the phylogeny carries substantial predictive power. The earliest cyanobacterial lineages likely lived in freshwater habitats, had small cell diameters, were benthic or sessile, and possibly epilithic/endolithic with a sheath. We jointly analyzed a subset of 25 binary traits to determine whether rates of trait evolution have shifted over time in conjunction with major geologic events. Phylogenetic comparative analysis reveal an overriding signal of decreasing rates of trait evolution through time. Furthermore, the data suggest two major rate shifts in trait evolution associated with bursts of evolutionary innovation. The first rate shift occurs in the aftermath of the Great Oxidation Event and “Snowball Earth” glaciations and is associated with decrease in the evolutionary rates around 1.8–1.6 Ga. This rate shift seems to indicate the end of a major diversification of cyanobacterial phenotypes–particularly related to traits associated with filamentous morphology, heterocysts and motility in freshwater ecosystems. Another burst appears around the time of the Neoproterozoic Oxidation Event in the Neoproterozoic, and is associated with the acquisition of traits involved in planktonic growth in marine habitats. Our results demonstrate how uniting genomic and phenotypic datasets in extant bacterial species can shed light on billion-year old events in Earth’s history.

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“…This has been demonstrated by Goode et al (2008), who employed a particular codon parameterization to allow for sites to switch among a neutrally evolving class, a class of negatively selected sites and a class of positively selected sites (cf. M2, Nielsen and Yang 1998) before and after the start of HIV-1 antiretroviral therapy.…”

Section: Discussionmentioning

confidence: 99%

Inferring Heterogeneous Evolutionary Processes Through Time: from Sequence Substitution to Phylogeography

et al. 2014

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Molecular phylogenetic and phylogeographic reconstructions generally assume time-homogeneous substitution processes. Motivated by computational convenience, this assumption sacrifices biological realism and offers little opportunity to uncover the temporal dynamics in evolutionary histories. Here, we propose an evolutionary approach that explicitly relaxes the time-homogeneity assumption by allowing the specification of different infinitesimal substitution rate matrices across different time intervals, called epochs, along the evolutionary history. We focus on an epoch model implementation in a Bayesian inference framework that offers great modeling flexibility in drawing inference about any discrete data type characterized as a continuous-time Markov chain, including phylogeographic traits. To alleviate the computational burden that the additional temporal heterogeneity imposes, we adopt a massively parallel approach that achieves both fine- and coarse-grain parallelization of the computations across branches that accommodate epoch transitions, making extensive use of graphics processing units. Through synthetic examples, we assess model performance in recovering evolutionary parameters from data generated according to different evolutionary scenarios that comprise different numbers of epochs for both nucleotide and codon substitution processes. We illustrate the usefulness of our inference framework in two different applications to empirical data sets: the selection dynamics on within-host HIV populations throughout infection and the seasonality of global influenza circulation. In both cases, our epoch model captures key features of temporal heterogeneity that remained difficult to test using ad hoc procedures. [Bayesian inference; BEAGLE; BEAST; Epoch Model; phylogeography; Phylogenetics.]

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Modelling the evolution of protein coding sequences sampled from Measurably Evolving Populations

Cited by 4 publications

References 0 publications

Determinants of dengue virus dispersal in the Americas

Determinants of dengue virus dispersal in the Americas

A Comprehensive Study of Cyanobacterial Morphological and Ecological Evolutionary Dynamics through Deep Geologic Time

Inferring Heterogeneous Evolutionary Processes Through Time: from Sequence Substitution to Phylogeography

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