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68 results for “phylogenetic comparative data”

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dryad28/100

Data from: Phylogenetic and comparative genomics of the family Leptotrichiaceae and introduction of a novel fingerprinting MLVA for Streptobacillus moniliformis

Background: The Leptotrichiaceae are a family of fairly unnoticed bacteria containing both microbiota on mucous membranes as well as significant pathogens such as Streptobacillus moniliformis, the causative organism of streptobacillary rat bite fever. Comprehensive genomic studies in members of this family have so far not been carried out. We aimed to analyze 47 genomes from 20 different member species to illuminate phylogenetic aspects, as well as genomic and discriminatory properties. Results: Our data provide a novel and reliable basis of support for previously established phylogeny from this group and give a deeper insight into characteristics of genome structure and gene functions. Full genome analyses revealed that most S. moniliformis strains under study form a heterogeneous population without any significant clustering. Analysis of infra-species variability for this highly pathogenic rat bite fever organism led to the detection of three specific variable number tandem analysis loci with high discriminatory power. Conclusions: This highly useful and economical tool can be directly employed in clinical samples without laborious prior cultivation. Our and prospective case-specific data can now easily be compared by using a newly established MLVA database in order to gain a better insight into the epidemiology of this presumably under-reported zoonosis.

opencc-zeroDec 2015View details →

dryad28/100

Data from: Inferring bounded evolution in phenotypic characters from phylogenetic comparative data

Our understanding of phenotypic evolution over macroevolutionary timescales largely relies on the use of stochastic models for the evolution of continuous traits over phylogenies. The two most widely used models, Brownian motion and the Ornstein–Uhlenbeck (OU) process, differ in that the latter includes constraints on the variance that a trait can attain in a clade. The OU model explicitly models adaptive evolution toward a trait optimum and has thus been widely used to demonstrate the existence of stabilizing selection on a trait. Here we introduce a new model for the evolution of continuous characters on phylogenies: Brownian motion between two reflective bounds, or Bounded Brownian Motion (BBM). This process also models evolutionary constraints, but of a very different kind. We provide analytical expressions for the likelihood of BBM and present a method to calculate the likelihood numerically, as well as the associated R code. Numerical simulations show that BBM achieves good performance: parameter estimation is generally accurate but more importantly BBM can be very easily discriminated from both BM and OU. We then analyze climatic niche evolution in diprotodonts and find that BBM best fits this empirical data set, suggesting that the climatic niches of diprotodonts are bounded by the climate available in Australia and the neighboring islands but probably evolved with little additional constraints. We conclude that BBM is a valuable addition to the macroevolutionary toolbox, which should enable researchers to elucidate whether the phenotypic traits they study are evolving under hard constraints between bounds.

opencc-zeroDec 2015View details →

dryad28/100

Data from: Detecting adaptive evolution in phylogenetic comparative analysis using the Ornstein-Uhlenbeck model

Phylogenetic comparative analysis is an approach to inferring evolutionary process from a combination of phylogenetic and phenotypic data. The last few years have seen increasingly sophisticated models employed in the evaluation of more and more detailed evolutionary hypotheses, including adaptive hypotheses with multiple selective optima and hypotheses with rate variation within and across lineages. The statistical performance of these sophisticated models has received relatively little systematic attention, however. We conducted an extensive simulation study to quantify the statistical properties of a class of models toward the simpler end of the spectrum that model phenotypic evolution using Ornstein–Uhlenbeck processes. We focused on identifying where, how, and why these methods break down so that users can apply them with greater understanding of their strengths and weaknesses. Our analysis identifies three key determinants of performance: a discriminability ratio, a signal-to-noise ratio, and the number of taxa sampled. Interestingly, we find that model-selection power can be high even in regions that were previously thought to be difficult, such as when tree size is small. On the other hand, we find that model parameters are in many circumstances difficult to estimate accurately, indicating a relative paucity of information in the data relative to these parameters. Nevertheless, we note that accurate model selection is often possible when parameters are only weakly identified. Our results have implications for more sophisticated methods inasmuch as the latter are generalizations of the case we study.

opencc-zeroDec 2014View details →

dryad28/100

Data from: The local-clock permutation test: a simple test to compare rates of molecular evolution on phylogenetic trees

Rates of molecular evolution vary substantially between lineages, and a growing research effort is directed at uncovering the causes and consequences of this variation. Comparing local-clocks (rates of molecular evolution estimated from sets of branches of a phylogenetic tree) is a common tool in this research effort. Here, I show that a commonly used test (the Likelihood Ratio Test, LRT) will not be statistically valid for comparing local-clocks in most cases. Instead, I propose the local-clock permutation test (LCPT), a simple test which can be used to test the significance of differences between local-clocks. The LCPT could also be used to test for differences between any parameter that can be assigned to individual branches on a phylogenetic tree. Using simulated data, I show that the LCPT has good power to detect differences between local-clocks.

opencc-zeroDec 2009View details →

dryad28/100

Data from: A novel Bayesian method for inferring and interpreting the dynamics of adaptive landscapes from phylogenetic comparative data

Our understanding of macroevolutionary patterns of adaptive evolution has greatly increased with the advent of large-scale phylogenetic comparative methods. Widely used Ornstein-Uhlenbeck (OU) models can describe an adaptive process of divergence and selection. However, inference of the dynamics of adaptive landscapes from comparative data is complicated by interpretational difficulties, lack of identifiability among parameter values and the common requirement that adaptive hypotheses must be assigned a priori. Here we develop a reversible-jump Bayesian method of fitting multi-optima OU models to phylogenetic comparative data that estimates the placement and magnitude of adaptive shifts directly from the data. We show how biologically informed hypotheses can be tested against this inferred posterior of shift locations using Bayes Factors to establish whether our a priori models adequately describe the dynamics of adaptive peak shifts. Furthermore, we show how the inclusion of informative priors can be used to restrict models to biologically realistic parameter space and test particular biological interpretations of evolutionary models. We argue that Bayesian model-fitting of OU models to comparative data provides a framework for integrating of multiple sources of biological data–such as microevolutionary estimates of selection parameters and paleontological timeseries–allowing inference of adaptive landscape dynamics with explicit, process-based biological interpretations.

opencc-zeroDec 2013View details →

dryad28/100