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Bruce Rannala

Publications and source records attributed to Bruce Rannala.

16 recordsLinked to original sources
PubMed2006

Inferring complex DNA substitution processes on phylogenies using uniformization and data augmentation.

A new method is developed for calculating sequence substitution probabilities using Markov chain Monte Carlo (MCMC) methods. The basic strategy is to use uniformization to transform the original continuous time Markov process into a Poisson substitution process and a discrete Markov chain of state transitions. An efficient MCMC algorithm for evaluating substitution probabilities by this approach using a continuous gamma distribution to model site-specific rates is outlined. The method is applied to the problem of inferring branch lengths and site-specific rates from nucleotide sequences under a general time-reversible (GTR) model and a computer program BYPASSR is developed. Simulations are used to examine the performance of the new program relative to an existing program BASEML that uses a discrete approximation for the gamma distributed prior on site-specific rates. It is found that BASEML and BYPASSR are in close agreement when inferring branch lengths, regardless of the number of rate categories used, but that BASEML tends to underestimate high site-specific substitution rates, and to overestimate intermediate rates, when fewer than 50 rate categories are used. Rate estimates obtained using BASEML agree more closely with those of BYPASSR as the number of rate categories increases. Analyses of the posterior distributions of site-specific rates from BYPASSR suggest that a large number of taxa are needed to obtain precise estimates of site-specific rates, especially when rates are very high or very low. The method is applied to analyze 45 sequences of the alpha 2B adrenergic receptor gene (A2AB) from a sample of eutherian taxa. In general, the pattern expected for regions under negative selection is observed with third codon positions having the highest inferred rates, followed by first codon positions and with second codon positions having the lowest inferred rates. Several sites show exceptionally high substitution rates at second codon positions that may represent the effects of positive selection.

Algorithms↗
PubMed2005

Bayesian estimation of species divergence times under a molecular clock using multiple fossil calibrations with soft bounds.

We implement a Bayesian Markov chain Monte Carlo algorithm for estimating species divergence times that uses heterogeneous data from multiple gene loci and accommodates multiple fossil calibration nodes. A birth-death process with species sampling is used to specify a prior for divergence times, which allows easy assessment of the effects of that prior on posterior time estimates. We propose a new approach for specifying calibration points on the phylogeny, which allows the use of arbitrary and flexible statistical distributions to describe uncertainties in fossil dates. In particular, we use soft bounds, so that the probability that the true divergence time is outside the bounds is small but nonzero. A strict molecular clock is assumed in the current implementation, although this assumption may be relaxed. We apply our new algorithm to two data sets concerning divergences of several primate species, to examine the effects of the substitution model and of the prior for divergence times on Bayesian time estimation. We also conduct computer simulation to examine the differences between soft and hard bounds. We demonstrate that divergence time estimation is intrinsically hampered by uncertainties in fossil calibrations, and the error in Bayesian time estimates will not go to zero with increased amounts of sequence data. Our analyses of both real and simulated data demonstrate potentially large differences between divergence time estimates obtained using soft versus hard bounds and a general superiority of soft bounds. Our main findings are as follows. (1) When the fossils are consistent with each other and with the molecular data, and the posterior time estimates are well within the prior bounds, soft and hard bounds produce similar results. (2) When the fossils are in conflict with each other or with the molecules, soft and hard bounds behave very differently; soft bounds allow sequence data to correct poor calibrations, while poor hard bounds are impossible to overcome by any amount of data. (3) Soft bounds eliminate the need for "safe" but unrealistically high upper bounds, which may bias posterior time estimates. (4) Soft bounds allow more reliable assessment of estimation errors, while hard bounds generate misleadingly high precisions when fossils and molecules are in conflict.

Animals↗
PubMed2005

In silico analysis of disease-association mapping strategies using the coalescent process and incorporating ascertainment and selection.

We present a new method for simulating samples of marker haplotypes, genotypes, or diplotypes in case-control studies in which the markers are linked to a disease locus in any specified region of the genome. The method allows realistic features to be incorporated into the simulations, including selection acting on disease alleles, sample ascertainment of disease chromosomes and polymorphic markers, a genetic dominance model of disease expression that allows incomplete penetrance and phenocopies, and an accurate genetic map of recombination rates and hotspots for recombination in the human genome (or, alternatively, an improved method for simulating the distribution of hotspots). The new method uses an approach that combines simulation of the coalescent process for the sampled chromosomes with a diffusion process used to model the evolution of the disease-mutation frequency over time. Examples illustrate how the method may be used to study the expected power of a marker-disease association study.

Alleles↗
PubMed2005

Branch-length prior influences Bayesian posterior probability of phylogeny.

The Bayesian method for estimating species phylogenies from molecular sequence data provides an attractive alternative to maximum likelihood with nonparametric bootstrap due to the easy interpretation of posterior probabilities for trees and to availability of efficient computational algorithms. However, for many data sets it produces extremely high posterior probabilities, sometimes for apparently incorrect clades. Here we use both computer simulation and empirical data analysis to examine the effect of the prior model for internal branch lengths. We found that posterior probabilities for trees and clades are sensitive to the prior for internal branch lengths, and priors assuming long internal branches cause high posterior probabilities for trees. In particular, uniform priors with high upper bounds bias Bayesian clade probabilities in favor of extreme values. We discuss possible remedies to the problem, including empirical and full Bayesian methods and subjective procedures suggested in Bayesian hypothesis testing. Our results also suggest that the bootstrap proportion and Bayesian posterior probability are different measures of accuracy, and that the bootstrap proportion, if interpreted as the probability that the clade is true, can be either too liberal or too conservative.

Bayes Theorem↗
PubMed2005

Evidence from the stop-EGFP mouse supports a niche-sharing model of epidermal proliferative units.

The classical model of epidermal proliferative units (EPUs) postulates that each EPU is composed of a single column of corneocytes plus epidermal cells directly below the column and is maintained by a single stem cell within the unit. Using the stop-enhanced green fluorescent protein (stop-EGFP) transgenic mouse system, we previously showed epidermal stem cell clonal lineages could produce multiple adjacent corneocytes (i.e. epidermal cells belonging to multiple adjacent EPUs), contradicting the classical EPU model. One possible problem with our earlier study was that N-ethyl-N-nitrosourea (ENU) was used to generate mutations for clonal analysis. This could alter the normal environment of the epidermal tissue and might lead to an artificial expansion of stem cell clonal lineages. In this study, we replicate our earlier findings using untreated stop-EGFP mice and relying on spontaneous mutations to generate clonal cell lineages. We propose an alternative to the classical EPU model to explain the dynamic nature of epidermal proliferation. Our niche-sharing model of EPUs allows epidermal cells to horizontally migrate among EPUs, so that multiple stem cells cooperatively maintain a larger proliferative compartment.

Animals↗
PubMed2004

A stop-EGFP transgenic mouse to detect clonal cell lineages generated by mutation.

The investigation of cell lineages and clonal organization in tissues is facilitated by techniques that allow labelling of clonal cell lineages. Here, we describe a novel transgenic mouse that allows clonal cell lineages to be traced in virtually any tissue. A green fluorescent cell lineage is generated by a random mutation at an enhanced green fluorescent protein gene that carries a premature stop codon, ensuring clonality. The transgenic system allows efficient detection of mutations and stem-cell fate mapping in the epidermis using live mice, as well as in the kidney and liver post-mortem. Cell lineages that descended from single epidermal stem cells were found to be capable of generating three adjacent corneocytes using the system, providing evidence for horizontal migration of epidermal cells between epidermal proliferative units (EPUs), in contrast to the classical EPU model. The transgenic mouse system is expected to provide a novel tool for stem-cell lineage studies.

Animals↗
PubMed2004

Frequentist properties of Bayesian posterior probabilities of phylogenetic trees under simple and complex substitution models.

What does the posterior probability of a phylogenetic tree mean?This simulation study shows that Bayesian posterior probabilities have the meaning that is typically ascribed to them; the posterior probability of a tree is the probability that the tree is correct, assuming that the model is correct. At the same time, the Bayesian method can be sensitive to model misspecification, and the sensitivity of the Bayesian method appears to be greater than the sensitivity of the nonparametric bootstrap method (using maximum likelihood to estimate trees). Although the estimates of phylogeny obtained by use of the method of maximum likelihood or the Bayesian method are likely to be similar, the assessment of the uncertainty of inferred trees via either bootstrapping (for maximum likelihood estimates) or posterior probabilities (for Bayesian estimates) is not likely to be the same. We suggest that the Bayesian method be implemented with the most complex models of those currently available, as this should reduce the chance that the method will concentrate too much probability on too few trees.

Animals↗
PubMed2003

Bayesian inference of recent migration rates using multilocus genotypes.

A new Bayesian method that uses individual multilocus genotypes to estimate rates of recent immigration (over the last several generations) among populations is presented. The method also estimates the posterior probability distributions of individual immigrant ancestries, population allele frequencies, population inbreeding coefficients, and other parameters of potential interest. The method is implemented in a computer program that relies on Markov chain Monte Carlo techniques to carry out the estimation of posterior probabilities. The program can be used with allozyme, microsatellite, RFLP, SNP, and other kinds of genotype data. We relax several assumptions of early methods for detecting recent immigrants, using genotype data; most significantly, we allow genotype frequencies to deviate from Hardy-Weinberg equilibrium proportions within populations. The program is demonstrated by applying it to two recently published microsatellite data sets for populations of the plant species Centaurea corymbosa and the gray wolf species Canis lupus. A computer simulation study suggests that the program can provide highly accurate estimates of migration rates and individual migrant ancestries, given sufficient genetic differentiation among populations and sufficient numbers of marker loci.

Animal Migration↗
PubMed2003

Bayes estimation of species divergence times and ancestral population sizes using DNA sequences from multiple loci.

The effective population sizes of ancestral as well as modern species are important parameters in models of population genetics and human evolution. The commonly used method for estimating ancestral population sizes, based on counting mismatches between the species tree and the inferred gene trees, is highly biased as it ignores uncertainties in gene tree reconstruction. In this article, we develop a Bayes method for simultaneous estimation of the species divergence times and current and ancestral population sizes. The method uses DNA sequence data from multiple loci and extracts information about conflicts among gene tree topologies and coalescent times to estimate ancestral population sizes. The topology of the species tree is assumed known. A Markov chain Monte Carlo algorithm is implemented to integrate over uncertain gene trees and branch lengths (or coalescence times) at each locus as well as species divergence times. The method can handle any species tree and allows different numbers of sequences at different loci. We apply the method to published noncoding DNA sequences from the human and the great apes. There are strong correlations between posterior estimates of speciation times and ancestral population sizes. With the use of an informative prior for the human-chimpanzee divergence date, the population size of the common ancestor of the two species is estimated to be approximately 20,000, with a 95% credibility interval (8000, 40,000). Our estimates, however, are affected by model assumptions as well as data quality. We suggest that reliable estimates have yet to await more data and more realistic models.

Algorithms↗
PubMed2003

Likelihood models of somatic mutation and codon substitution in cancer genes.

The role of somatic mutation in cancer is well established and several genes have been identified that are frequent targets. This has enabled large-scale screening studies of the spectrum of somatic mutations in cancers of particular organs. Cancer gene mutation databases compile the results of many studies and can provide insight into the importance of specific amino acid sequences and functional domains in cancer, as well as elucidate aspects of the mutation process. Past studies of the spectrum of cancer mutations (in particular genes) have examined overall frequencies of mutation (at specific nucleotides) and of missense, nonsense, and silent substitution (at specific codons) both in the sequence as a whole and in a specific functional domain. Existing methods ignore features of the genetic code that allow some codons to mutate to missense, or stop, codons more readily than others (i.e., by one nucleotide change, vs. two or three). A new codon-based method to estimate the relative rate of substitution (fixation of a somatic mutation in a cancer cell lineage) of nonsense vs. missense mutations in different functional domains and in different tumor tissues is presented. Models that account for several potential influences on rates of somatic mutation and substitution in cancer progenitor cells and allow biases of mutation rates for particular dinucleotide sequences (CGs and dipyrimidines), transition vs. transversion bias, and variable rates of silent substitution across functional domains (useful in detecting investigator sampling bias) are considered. Likelihood-ratio tests are used to choose among models, using cancer gene mutation data. The method is applied to analyze published data on the spectrum of p53 mutations in cancers. A novel finding is that the ratio of the probability of nonsense to missense substitution is much lower in the DNA-binding and transactivation domains (ratios near 1) than in structural domains such as the linker, tetramerization (oligomerization), and proline-rich domains (ratios exceeding 100 in some tissues), implying that the specific amino acid sequence may be less critical in structural domains (e.g., amino acid changes less often lead to cancer). The transition vs. transversion bias and effect of CpG dinucleotides on mutation rates in p53 varied greatly across cancers of different organs, likely reflecting effects of different endogenous and exogenous factors influencing mutation in specific organs.

Data Interpretation, Statistical↗
PubMed2003

Detecting correlation between characters in a comparative analysis with uncertain phylogeny.

The importance of accommodating the phylogenetic history of a group when performing a comparative analysis is now widely recognized. The typical approaches either assume the tree is known without error, or they base inferences on a collection of well-supported trees or on a collection of trees generated under a stochastic model of cladogenesis. However, these approaches do not adequately account for the uncertainty of phylogenetic trees in a comparative analysis, especially when data relevant to the phylogeny of a group are available. Here, we develop a method for performing comparative analyses that is based on an extension of Felsenstein's independent contrasts method. Uncertainties in the phylogeny, branch lengths, and other parameters are accommodated by averaging over all possible trees, weighting each by the probability that the tree is correct. We do this in a Bayesian framework and use Markov chain Monte Carlo to perform the high-dimensional summations and integrations required by the analysis. We illustrate the method using comparative characters sampled from Anolis lizards.

Animals↗
PubMed2002

Disease surveillance in recombining pathogens: multilocus genotypes identify sources of human Coccidioides infections.

Molecular surveillance of pathogenic microbes works by genotyping isolates with DNA fingerprinting techniques and then using these genotypes to assign individuals to populations. Clonality is assumed in many fingerprinting studies, although this assumption has been shown to be false for many organisms. To accommodate recombining organisms into surveillance programs, methods using population allele frequencies in combination with individual multilocus genotypes are necessary. Here, we develop a statistical method appropriate for haploid recombining microbes that allows individuals to be assigned to populations. We illustrate the usefulness of this technique by inferring the source populations for Coccidioides isolates recovered from patients treated outside the endemic area of Coccidioides sp., the etiological agents of human coccidioidomycosis, but with a travel history including visits to one or more endemic areas.

Alleles↗
PubMed2002

Identifiability of parameters in MCMC Bayesian inference of phylogeny.

Methods for Bayesian inference of phylogeny using DNA sequences based on Markov chain Monte Carlo (MCMC) techniques allow the incorporation of arbitrarily complex models of the DNA substitution process, and other aspects of evolution. This has increased the realism of models, potentially improving the accuracy of the methods, and is largely responsible for their recent popularity. Another consequence of the increased complexity of models in Bayesian phylogenetics is that these models have, in several cases, become overparameterized. In such cases, some parameters of the model are not identifiable; different combinations of nonidentifiable parameters lead to the same likelihood, making it impossible to decide among the potential parameter values based on the data. Overparameterized models can also slow the rate of convergence of MCMC algorithms due to large negative correlations among parameters in the posterior probability distribution. Functions of parameters can sometimes be found, in overparameterized models, that are identifiable, and inferences based on these functions are legitimate. Examples are presented of overparameterized models that have been proposed in the context of several Bayesian methods for inferring the relative ages of nodes in a phylogeny when the substitution rate evolves over time.

Algorithms↗
PubMed2002

DMLE+: Bayesian linkage disequilibrium gene mapping.

SUMMARY: The program DMLE+ allows Bayesian inference of the location of a gene carrying a mutation influencing a discrete trait (such as a disease) and/or other parameters of interest (such as mutation age) based on the observed linkage disequilibrium at multiple genetic markers. DMLE+ uses either individual marker genotypes, or haplotypes, integrates over uncertain population allele frequencies, and can incorporate prior information about gene location from an annotated human genome sequence. AVAILABILITY: DMLE+ is available in both Windows GUI and portable UNIX command line versions at http://dmle.org.

Bayes Theorem↗