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Inferring Evolutionary Histories of Pathway Regulation from Transcriptional Profiling Data
"... One of the outstanding challenges in comparative genomics is to interpret the evolutionary importance of regulatory variation between species. Rigorous molecular evolutionbased methods to infer evidence for natural selection from expression data are at a premium in the field, and to date, phylogene ..."
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One of the outstanding challenges in comparative genomics is to interpret the evolutionary importance of regulatory variation between species. Rigorous molecular evolutionbased methods to infer evidence for natural selection from expression data are at a premium in the field, and to date, phylogenetic approaches have not been wellsuited to address the question in the small sets of taxa profiled in standard surveys of gene expression. We have developed a strategy to infer evolutionary histories from expression profiles by analyzing suites of genes of common function. In a manner conceptually similar to molecular evolution models in which the evolutionary rates of DNA sequence at multiple loci follow a gamma distribution, we modeled expression of the genes of an a prioridefined pathway with rates drawn from an inverse gamma distribution. We then developed a fitting strategy to infer the parameters of this distribution from expression measurements, and to identify gene groups whose expression patterns were consistent with evolutionary constraint or rapid evolution in particular species. Simulations confirmed the power and accuracy of our inference method. As an experimental testbed for our approach, we generated and analyzed transcriptional profiles of four Saccharomyces yeasts. The results revealed pathways with signatures of constrained and accelerated regulatory evolution in individual yeasts and across the phylogeny, highlighting the prevalence of pathwaylevel expression change during the divergence of yeast species. We anticipate that our pathwaybased phylogenetic approach will be of broad utility in the search to understand
ASYMPTOTIC THEORY WITH HIERARCHICAL AUTOCORRELATION: ORNSTEIN–UHLENBECK TREE MODELS 1
"... Hierarchical autocorrelation in the error term of linear models arises when sampling units are related to each other according to a tree. The residual covariance is parametrized using the treedistance between sampling units. When observations are modeled using an Ornstein–Uhlenbeck (OU) process alo ..."
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Hierarchical autocorrelation in the error term of linear models arises when sampling units are related to each other according to a tree. The residual covariance is parametrized using the treedistance between sampling units. When observations are modeled using an Ornstein–Uhlenbeck (OU) process along the tree, the autocorrelation between two tips decreases exponentially with their tree distance. These models are most often applied in evolutionary biology, when tips represent biological species and the OU process parameters represent the strength and direction of natural selection. For these models, we show that the mean is not microergodic: no estimator can ever be consistent for this parameter and provide a lower bound for the variance of its MLE. For covariance parameters, we give a general sufficient condition ensuring microergodicity. This condition suggests that some parameters may not be estimated at the same rate as others. We show that, indeed, maximum likelihood estimators of the autocorrelation parameter converge at a slower rate than that of generally microergodic parameters. We showed this theoretically in a symmetric tree asymptotic framework and through simulations on a large real tree comprising 4507 mammal species.
Model and algorithm for hierarchical analysis.
 Sport Science,
, 2009
"... Abstract The aim of this research was to define initial mode, i.e. paradigm ..."
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Abstract The aim of this research was to define initial mode, i.e. paradigm
Euclidean nature of phylogenetic distance matrices
 Systematic Biology
, 2011
"... Abstract.— – Phylogenies are fundamental to comparative biology as they help to identify independent events on which statistical tests rely. Two groups of phylogenetic comparative methods (PCMs) can be distinguished: those that take phylogenies into account by introducing explicit models of evoluti ..."
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Abstract.— – Phylogenies are fundamental to comparative biology as they help to identify independent events on which statistical tests rely. Two groups of phylogenetic comparative methods (PCMs) can be distinguished: those that take phylogenies into account by introducing explicit models of evolution and those that only consider phylogenies as a statistical constraint and aim at partitioning trait values into a phylogenetic component (phylogenetic inertia) and one or multiple specific components related to adaptive evolution. The way phylogenetic information is incorporated into the PCMs depends on the method used. For the first group of methods, phylogenies are converted into variance–covariance matrices of traits following a given model of evolution such as Brownian motion (BM). For the second group of methods, phylogenies are converted into distance matrices that are subsequently transformed into Euclidean distances to perform principal coordinate analyses. Here, we show that simply taking the elementwise square root of a distance matrix extracted from a phylogenetic tree ensures having a Euclidean distance matrix. This is true for any type of distances between species
Generalization and Robustness of Batched Weighted Average Algorithm with Vgeometrically Ergodic Markov Data
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LETTER Niche conservatism constrains Australian honeyeater assemblages in stressful environments
"... The hypothesis of phylogenetic niche conservatism proposes that most extant members of a clade remain in ancestral environments because expansion into new ecological space imposes a selectional load on a population. A prediction that follows is that local assemblages contain increasingly phylogenet ..."
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The hypothesis of phylogenetic niche conservatism proposes that most extant members of a clade remain in ancestral environments because expansion into new ecological space imposes a selectional load on a population. A prediction that follows is that local assemblages contain increasingly phylogenetically clustered subsets of species with increasing difference from the ancestral environment of a clade. We test this in Australian Meliphagidae, a continental radiation of birds that originated in wet, subtropical environments, but subsequently spread to drier environments as Australia became more arid during the late Cenozoic. We find local assemblages are increasingly phylogenetically clustered along a gradient of decreasing precipitation. The pattern is less clear along a temperature gradient. We develop a novel phyloclimatespace to visualise the expansion of some lineages into drier habitats. Although few species extend into arid regions, those that do occupy larger ranges and thus local species richness does not decline predictably with precipitation.
Learning From Noniid Data: Fast Rates for the OnevsAll Multiclass Plugin Classifiers
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A Consistent Estimator of the Evolutionary Rate
, 2014
"... We consider a branching particle system where particles reproduce according to the pure birth Yule process with the birth rate λ, conditioned on the observed number of particles to be equal n. Particles are assumed to move independently on the real line according to the Brownian motion with the loca ..."
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We consider a branching particle system where particles reproduce according to the pure birth Yule process with the birth rate λ, conditioned on the observed number of particles to be equal n. Particles are assumed to move independently on the real line according to the Brownian motion with the local variance σ2. In this paper we treat n particles as a sample of related species. The spatial Brownian motion of a particle describes the development of a trait value of interest (e.g. log–body–size). We propose an unbiased estimator R2n of the evolutionary rate ρ2 = σ2/λ. The estimator R2n is proportional to the sample variance S2n computed from n trait values. We find an approximate formula for the standard error of R2n based on a neat asymptotic relation for the variance of S2n. (Keywords: Branching Brownian motion, conditioned branching process, tree–free phylogenetic comparative method, quantitative trait evolution, Yule process)
Testing for Depéret’s Rule (Body Size Increase) in Mammals using Combined Extinct and Extant Data
, 2015
"... Abstract.—Whether or not evolutionary lineages in general showa tendency to increase in body size has often beendiscussed. This tendency has been dubbed “Cope’s rule ” but becauseCope never hypothesized it, we suggest renaming it afterDepéret, who formulated it clearly in 1907. Depéret’s rule has tr ..."
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Abstract.—Whether or not evolutionary lineages in general showa tendency to increase in body size has often beendiscussed. This tendency has been dubbed “Cope’s rule ” but becauseCope never hypothesized it, we suggest renaming it afterDepéret, who formulated it clearly in 1907. Depéret’s rule has traditionally been studied using fossil data, but more recently a number of studies have used presentday species. While several paleontological studies of Cenozoic placental mammals have found support for increasing body size, most studies of extant placentals have failed to detect such a trend. Here, we present a
DOI:10.1093/sysbio/syr066 Euclidean Nature of Phylogenetic Distance Matrices
, 2011
"... Abstract.— – Phylogenies are fundamental to comparative biology as they help to identify independent events on which statistical tests rely. Two groups of phylogenetic comparative methods (PCMs) can be distinguished: those that take phylogenies into account by introducing explicit models of evoluti ..."
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Abstract.— – Phylogenies are fundamental to comparative biology as they help to identify independent events on which statistical tests rely. Two groups of phylogenetic comparative methods (PCMs) can be distinguished: those that take phylogenies into account by introducing explicit models of evolution and those that only consider phylogenies as a statistical constraint and aim at partitioning trait values into a phylogenetic component (phylogenetic inertia) and one or multiple specific components related to adaptive evolution. The way phylogenetic information is incorporated into the PCMs depends on the method used. For the first group of methods, phylogenies are converted into variance–covariance matrices of traits following a given model of evolution such as Brownian motion (BM). For the second group of methods, phylogenies are converted into distance matrices that are subsequently transformed into Euclidean distances to perform principal coordinate analyses. Here, we show that simply taking the elementwise square root of a distance matrix extracted from a phylogenetic tree ensures having a Euclidean distance matrix. This is true for any type of distances between species