Empirical and hierarchical Bayesian estimation of ancestral states

Several methods have been proposed to infer the states at the ancestral nodes on a phylogeny. These methods assume a specific tree and set of branch lengths when estimating the ancestral character state. Inferences of the ancestral states, then, are conditioned on the tree and branch lengths being true. We develop a hierarchical Bayes method for inferring the ancestral states on a tree. The method integrates over uncertainty in the tree, branch lengths, and substitution model parameters by using Markov chain Monte Carlo. We compare the hierarchical Bayes inferences of ancestral states with inferences of ancestral states made under the assumption that a specific tree is correct. We find that the methods are correlated, but that accommodating uncertainty in parameters of the phylogenetic model can make inferences of ancestral states even more uncertain than they would be in an empirical Bayes analysis.     

Bayesian estimation of ancestral character states on phylogenies

Biologists frequently attempt to infer the character states at ancestral nodes of a phylogeny from the distribution of traits observed in contemporary organisms. Because phylogenies are normally inferences from data, it is desirable to account for the uncertainty in estimates of the tree and its branch lengths when making inferences about ancestral states or other comparative parameters. Here we present a general Bayesian approach for testing comparative hypotheses across statistically justified samples of phylogenies, focusing on the specific issue of reconstructing ancestral states. The method uses Markov chain Monte Carlo techniques for sampling phylogenetic trees and for investigating the parameters of a statistical model of trait evolution. We describe how to combine information about the uncertainty of the phylogeny with uncertainty in the estimate of the ancestral state. Our approach does not constrain the sample of trees only to those that contain the ancestral node or nodes of interest, and we show how to reconstruct ancestral states of uncertain nodes using a most-recent-common-ancestor approach. We illustrate the methods with data on ribonuclease evolution in the Artiodactyla. Software implementing the methods (BayesMultiState) is available from the authors.     

A Bayesian estimation approach for the mortality in a stage-structured demographic model

Journal of Mathematical Biology - Control interventions in sustainable pest management schemes are set according to the phenology and the population abundance of the pests. This information can be...     

A bayesian analysis of metazoan mitochondrial genome arrangements

Genome arrangements are a potentially powerful source of information to infer evolutionary relationships among distantly related taxa. Mitochondrial genome arrangements may be especially informative about metazoan evolutionary relationships because (1) nearly all animals have the same set of definitively homologous mitochondrial genes, (2) mitochondrial genome rearrangement events are rare relative to changes in sequences, and (3) the number of possible mitochondrial genome arrangements is huge, making convergent evolution of genome arrangements appear highly unlikely. In previous studies, phylogenetic evidence in genome arrangement data is nearly always used in a qualitative fashion-the support in favor of clades with similar or identical genome arrangements is considered to be quite strong, but is not quantified. The purpose of this article is to quantify the uncertainty among the relationships of metazoan phyla on the basis of mitochondrial genome arrangements while incorporating prior knowledge of the monophyly of various groups from other sources. The work we present here differs from our previous work in the statistics literature in that (1) we incorporate prior information on classifications of metazoans at the phylum level, (2) we describe several advances in our computational approach, and (3) we analyze a much larger data set (87 taxa) that consists of each unique, complete mitochondrial genome arrangement with a full complement of 37 genes that were present in the NCBI (National Center for Biotechnology Information) database at a recent date. In addition, we analyze a subset of 28 of these 87 taxa for which the non-tRNA mitochondrial genomes are unique where the assumption of our inversion-only model of rearrangement is more plausible. We present summaries of Bayesian posterior distributions of tree topology on the basis of these two data sets.     

A primer-based approach to genome walking

A genome walking strategy based on annealing and ligation of single-stranded DNA primers to 3′ overhangs following restriction endonuclease digestion was developed. A set of primers contains 4 nucleotides at the 3′ end that are complementary to overhangs formed by restriction endonucleasesApaI;PstI;SacI andSphI. Following ligation, 5′ end overhangs are formed on the DNA, which serves as sites for the adaptor primers and nested primers for PCR amplification in combination with the gene-specific primers. This strategy was verified by the amplification of up to 4 kb of a potato leafroll virus full-length infectious clone. The procedure could be adopted to target any upstream and downstream regions flanking known sequences within the plant genome.     

A Bayesian approach to the evolution of social learning

There has been much interest in understanding the evolution of social learning. Investigators have tried to understand when natural selection will favor individuals who imitate others, how imitators should deal with the fact that available models may exhibit different behaviors, and how social and individual learning should interact. In all of this work, social learning and individual learning have been treated as alternative, conceptually distinct processes. Here we present a Bayesian model in which both individual and social learning arise from a single inferential process. Individuals use Bayesian inference to combine social and nonsocial cues about the current state of the environment. This model indicates that natural selection favors individuals who place heavy weight on social cues when the environment changes slowly or when its state cannot be well predicted using nonsocial cues. It also indicates that a conformist bias should be a universal aspect of social learning.     

A Bayesian, combinatorial approach to capture-recapture

It is shown that, in the capture-recapture method, the widely used formulae of Bailey or Chapman-Seber give the most likely value for the size of the population, but systematically underestimate the probability that the population is larger than any given size. We take here a first step in a combinatorial approach which does not suffer from this flaw: formulae are given which can be used in the closed case (no birth, death or migrations between captures) when at least two animals have been recaptured and when there is homogeneity with regard to capture probability. Numerical and heuristic evidence is presented pointing to the fact that the error incurred when using the formulae of Bailey or Chapman-Seber depends asymptotically only on the number of recaptured animals, and will not diminish if the number of captured animals becomes large while the number of recaptured animals remains constant. A result that was stated and left unproven by Darroch is proven here.     

The tendency to recreate ancestral CG dinucleotides in the human genome

Background  

The CG dinucleotides are known to be deficient in the human genome, due to a high mutation rate from 5-methylated CG to TG and its complementary pair CA. Meanwhile, many cellular functions rely on these CG dinucleotides, such as gene expression controlled by cytosine methylation status. Thus, CG dinucleotides that provide essential functional substrates should be retained in genomes. How these two conflicting processes regarding the fate of CG dinucleotides - i.e., high mutation rate destroying CG dinucleotides, vs. functional processes that require their preservation remains an unsolved question.     

Evolution of gastropod mitochondrial genome arrangements

Background  

Gastropod mitochondrial genomes exhibit an unusually great variety of gene orders compared to other metazoan mitochondrial genome such as e.g those of vertebrates. Hence, gastropod mitochondrial genomes constitute a good model system to study patterns, rates, and mechanisms of mitochondrial genome rearrangement. However, this kind of evolutionary comparative analysis requires a robust phylogenetic framework of the group under study, which has been elusive so far for gastropods in spite of the efforts carried out during the last two decades. Here, we report the complete nucleotide sequence of five mitochondrial genomes of gastropods (Pyramidella dolabrata, Ascobulla fragilis, Siphonaria pectinata, Onchidella celtica, and Myosotella myosotis), and we analyze them together with another ten complete mitochondrial genomes of gastropods currently available in molecular databases in order to reconstruct the phylogenetic relationships among the main lineages of gastropods.