Harnessing cognitive trajectory clusterings to examine subclinical decline risk factors.

Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling (n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [11C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [18F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 (n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups (K-means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ2, and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults.

BayesCAT: Bayesian co-estimation of alignment and tree.

Traditionally, phylogeny and sequence alignment are estimated separately: first estimate a multiple sequence alignment and then infer a phylogeny based on the sequence alignment estimated in the previous step. However, uncertainty in the alignment is ignored, resulting, possibly, in overstated certainty in phylogeny estimates. We develop a joint model for co-estimating phylogeny and sequence alignment which improves estimates from the traditional approach by accounting for uncertainty in the alignment in phylogenetic inferences. Our insertion and deletion (indel) model allows arbitrary-length overlapping indel events and a general distribution for indel fragment size. We employ a Bayesian approach using MCMC to estimate the joint posterior distribution of a phylogenetic tree and a multiple sequence alignment. Our approach has a tree and a complete history of indel events mapped onto the tree as the state space of the Markov Chain while alternative previous approaches have a tree and an alignment. A large state space containing a complete history of indel events makes our MCMC approach more challenging, but it enables us to infer more information about the indel process. The performances of this joint method and traditional sequential methods are compared using simulated data as well as real data. Software named BayesCAT (Bayesian Co-estimation of Alignment and Tree) is available at https://github.com/heejungshim/BayesCAT.

Colonization Habitat Controls Biomass, Composition, and Metabolic Activity of Attached Microbial Communities in the Columbia River Hyporheic Corridor.

Hydrologic exchange plays a critical role in biogeochemical cycling within the hyporheic zone (the interface between river water and groundwater) of riverine ecosystems. Such exchange may set limits on the rates of microbial metabolism and impose deterministic selection on microbial communities that adapt to dynamically changing dissolved organic carbon (DOC) sources. This study examined the response of attached microbial communities (in situ colonized sand packs) from groundwater, hyporheic, and riverbed habitats within the Columbia River hyporheic corridor to "cross-feeding" with either groundwater, river water, or DOC-free artificial fluids. Our working hypothesis was that deterministic selection during in situ colonization would dictate the response to cross-feeding, with communities displaying maximal biomass and respiration when supplied with their native fluid source. In contrast to expectations, the major observation was that the riverbed colonized sand had much higher biomass and respiratory activity, as well as a distinct community structure, compared with those of the hyporheic and groundwater colonized sands. 16S rRNA gene amplicon sequencing revealed a much higher proportion of certain heterotrophic taxa as well as significant numbers of eukaryotic algal chloroplasts in the riverbed colonized sand. Significant quantities of DOC were released from riverbed sediment and colonized sand, and separate experiments showed that the released DOC stimulated respiration in the groundwater and piezometer colonized sand. These results suggest that the accumulation and degradation of labile particulate organic carbon (POC) within the riverbed are likely to release DOC, which may enter the hyporheic corridor during hydrologic exchange, thereby stimulating microbial activity and imposing deterministic selective pressure on the microbial community composition.IMPORTANCE The influence of river water-groundwater mixing on hyporheic zone microbial community structure and function is an important but poorly understood component of riverine biogeochemistry. This study employed an experimental approach to gain insight into how such mixing might be expected to influence the biomass, respiration, and composition of hyporheic zone microbial communities. Colonized sands from three different habitats (groundwater, river water, and hyporheic) were "cross-fed" with either groundwater, river water, or DOC-free artificial fluids. We expected that the colonization history would dictate the response to cross-feeding, with communities displaying maximal biomass and respiration when supplied with their native fluid source. By contrast, the major observation was that the riverbed communities had much higher biomass and respiration, as well as a distinct community structure compared with those of the hyporheic and groundwater colonized sands. These results highlight the importance of riverbed microbial metabolism in organic carbon processing in hyporheic corridors.

Subclonal diversity arises early even in small colorectal tumours and contributes to differential growth fates.

OBJECTIVE AND DESIGN: The goal of the study was to determine whether the mutational profile of early colorectal polyps correlated with growth behaviour. The growth of small polyps (6-9 mm) that were first identified during routine screening of patients was monitored over time by interval imaging with CT colonography. Mutations in these lesions with known growth rates were identified by targeted next-generation sequencing. The timing of mutational events was estimated using computer modelling and statistical inference considering several parameters including allele frequency and fitness. RESULTS: The mutational landscape of small polyps is varied both within individual polyps and among the group as a whole but no single alteration was correlated with growth behaviour. Polyps carried 0-3 pathogenic mutations with the most frequent being in APC, KRAS/NRAS, BRAF, FBXW7 and TP53. In polyps with two or more pathogenic mutations, allele frequencies were often variable, indicating the presence of multiple populations within a single tumour. Based on computer modelling, detectable mutations occurred at a mean polyp size of 30±35 crypts, well before the tumour is of a clinically detectable size. CONCLUSIONS: These data indicate that small colon polyps can have multiple pathogenic mutations in crucial driver genes that arise early in the existence of a tumour. Understanding the molecular pathway of tumourigenesis and clonal evolution in polyps that are at risk for progressing to invasive cancers will allow us to begin to better predict which polyps are more likely to progress into adenocarcinomas and which patients are at greater risk of developing advanced disease.

A novel statistical method for behaviour sequence analysis and its application to birdsong.

Complex vocal signals, such as birdsong, contain acoustic elements that differ in both order and duration. These elements may convey socially relevant meaning, both independently and through their interactions, yet statistical methods that combine order and duration data to extract meaning have not, to our knowledge, been fully developed. Here we design novel semi-Markov methods, Bayesian estimation and classification trees to extract order and duration information from behavioural sequences and apply these methods to songs produced by male European starlings, Sturnus vulgaris, in two social contexts in which the function of song differs: a spring (breeding) and autumn (nonbreeding) context. Additionally, previous data indicate that damage to the medial preoptic nucleus (POM), a brain area known to regulate male sexually motivated behaviour, affects structural aspects of starling song such that males in a sexually relevant context (i.e. spring) sing shorter songs than appropriate for this context. We further test the utility of our statistical approach by comparing attributes of song structure in POM-lesioned males to song produced by control spring and autumn males. Spring and autumn songs were statistically separable based on the duration and order of phrase types. Males produced more structurally complex aspects of song in spring than in autumn. Spring song was also longer and more stereotyped than autumn song, both attributes used by females to select mates. Songs produced by POM-lesioned males in some cases fell between measures of spring and autumn songs but differed most from songs produced by autumn males. Overall, these statistical methods can effectively extract biologically meaningful information contained in many behavioural sequences given sufficient sample sizes and replication numbers.

Statistical evidence for common ancestry: Application to primates.

Since Darwin, biologists have come to recognize that the theory of descent from common ancestry (CA) is very well supported by diverse lines of evidence. However, while the qualitative evidence is overwhelming, we also need formal methods for quantifying the evidential support for CA over the alternative hypothesis of separate ancestry (SA). In this article, we explore a diversity of statistical methods using data from the primates. We focus on two alternatives to CA, species SA (the separate origin of each named species) and family SA (the separate origin of each family). We implemented statistical tests based on morphological, molecular, and biogeographic data and developed two new methods: one that tests for phylogenetic autocorrelation while correcting for variation due to confounding ecological traits and a method for examining whether fossil taxa have fewer derived differences than living taxa. We overwhelmingly rejected both species and family SA with infinitesimal P values. We compare these results with those from two companion papers, which also found tremendously strong support for the CA of all primates, and discuss future directions and general philosophical issues that pertain to statistical testing of historical hypotheses such as CA.

Exploring Tree-Like and Non-Tree-Like Patterns Using Genome Sequences: An Example Using the Inbreeding Plant Species Arabidopsis thaliana (L.) Heynh.

Genome sequence data contain abundant information about genealogical history, but methods for extracting and interpreting this information are not yet fully developed. We analyzed genome sequences for multiple accessions of the selfing plant, Arabidopsis thaliana, with the goal of better understanding its genealogical history. As expected from accessions of the same species, we found much discordance between nuclear gene trees. Nonetheless, we inferred the optimal population tree under the assumption that all discordance is due to incomplete lineage sorting. To cope with the size of the data (many genes and many taxa), our pipeline is based on parallel computing and divides the problem into four-taxon trees. However, just because a population tree can be estimated does not mean that the assumptions of the multispecies coalescent model hold. Therefore, we implemented a new, nonparametric test to evaluate whether a population tree adequately explains the observed quartet frequencies (the frequencies of gene trees with each resolution of each four-taxon set). This test also considers other models: panmixia and a partially resolved population tree, that is, a tree in which some nodes are collapsed into local panmixia. We found that a partially resolved population tree provides the best fit to the data, providing evidence for tree-like structure within A. thaliana, qualitatively similar to what might be expected between different, closely related species. Further, we show that the pattern of deviation from expectations can be used to identify instances of introgression and detect one clear case of reticulation among ecotypes that have come into contact in the United Kingdom. Our study illustrates how we can use genome sequence data to evaluate whether phylogenetic relationships are strictly tree-like or reticulating.

Xenorhabdus bovienii Strain Diversity Impacts Coevolution and Symbiotic Maintenance with Steinernema spp. Nematode Hosts.

UNLABELLED: Microbial symbionts provide benefits that contribute to the ecology and fitness of host plants and animals. Therefore, the evolutionary success of plants and animals fundamentally depends on long-term maintenance of beneficial associations. Most work investigating coevolution and symbiotic maintenance has focused on species-level associations, and studies are lacking that assess the impact of bacterial strain diversity on symbiotic associations within a coevolutionary framework. Here, we demonstrate that fitness in mutualism varies depending on bacterial strain identity, and this is consistent with variation shaping phylogenetic patterns and maintenance through fitness benefits. Through genome sequencing of nine bacterial symbiont strains and cophylogenetic analysis, we demonstrate diversity among Xenorhabdus bovienii bacteria. Further, we identified cocladogenesis between Steinernema feltiae nematode hosts and their corresponding X. bovienii symbiont strains, indicating potential specificity within the association. To test the specificity, we performed laboratory crosses of nematode hosts with native and nonnative symbiont strains, which revealed that combinations with the native bacterial symbiont and closely related strains performed significantly better than those with more divergent symbionts. Through genomic analyses we also defined potential factors contributing to specificity between nematode hosts and bacterial symbionts. These results suggest that strain-level diversity (e.g., subspecies-level differences) in microbial symbionts can drive variation in the success of host-microbe associations, and this suggests that these differences in symbiotic success could contribute to maintenance of the symbiosis over an evolutionary time scale. IMPORTANCE: Beneficial symbioses between microbes and plant or animal hosts are ubiquitous, and in these associations, microbial symbionts provide key benefits to their hosts. As such, host success is fundamentally dependent on long-term maintenance of beneficial associations. Prolonged association between partners in evolutionary time is expected to result in interactions in which only specific partners can fully support symbiosis. The contribution of bacterial strain diversity on specificity and coevolution in a beneficial symbiosis remains unclear. In this study, we demonstrate that strain-level differences in fitness benefits occur in beneficial host-microbe interactions, and this variation likely shapes phylogenetic patterns and symbiotic maintenance. This highlights that symbiont contributions to host biology can vary significantly based on very-fine-scale differences among members of a microbial species. Further, this work emphasizes the need for greater phylogenetic resolution when considering the causes and consequences of host-microbe interactions.

Testing for beneficial reversal of dominance during salinity shifts in the invasive copepod Eurytemora affinis, and implications for the maintenance of genetic variation.

Maintenance of genetic variation at loci under selection has profound implications for adaptation under environmental change. In temporally and spatially varying habitats, non-neutral polymorphism could be maintained by heterozygote advantage across environments (marginal overdominance), which could be greatly increased by beneficial reversal of dominance across conditions. We tested for reversal of dominance and marginal overdominance in salinity tolerance in the saltwater-to-freshwater invading copepod Eurytemora affinis. We compared survival of F1 offspring generated by crossing saline and freshwater inbred lines (between-salinity F1 crosses) relative to within-salinity F1 crosses, across three salinities. We found evidence for both beneficial reversal of dominance and marginal overdominance in salinity tolerance. In support of reversal of dominance, survival of between-salinity F1 crosses was not different from that of freshwater F1 crosses under freshwater conditions and saltwater F1 crosses under saltwater conditions. In support of marginal overdominance, between-salinity F1 crosses exhibited significantly higher survival across salinities relative to both freshwater and saltwater F1 crosses. Our study provides a rare empirical example of complete beneficial reversal of dominance associated with environmental change. This mechanism might be crucial for maintaining genetic variation in salinity tolerance in E. affinis populations, allowing rapid adaptation to salinity changes during habitat invasions.

Bayesian estimation of the phylogeography of African gorillas with genome-differentiated population trees.

Phylogeography investigates the historical process that is responsible for the contemporary geographic distributions of populations in a species. The inference is made on the basis of molecular sequence data sampled from modern-day populations. The estimates, however, may fluctuate depending on the relevant genomic regions, because the evolution mechanism of each genome is unique, even within the same individual. In this article, we propose a genome-differentiated population tree model that allows the existence of separate population trees for each homologous genome. In each population tree, the unique evolutionary characteristics account for each genome, along with their homologous relationship; therefore, the approach can distinguish the evolutionary history of one genome from that of another. In addition to the separate divergence times, the new model can estimate separate effective population sizes, gene-genealogies and other mutation parameters. For Bayesian inference, we developed a Markov chain Monte Carlo (MCMC) methodology with a novel MCMC algorithm which can mix over a complicated state space. The stability of the new estimator is demonstrated through comparison with the Monte Carlo samples and other methods, as well as MCMC convergence diagnostics. The analysis of African gorilla data from two homologous loci reveals discordant divergence times between loci, and this discrepancy is explained by male-mediated gene flows until the end of the last ice age.

The estimation of tree posterior probabilities using conditional clade probability distributions.

In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas. I show that these alternative calculations are very similar to simple sample relative frequencies for high probability trees but are substantially more accurate for relatively low probability trees. The method allows the posterior probability of unsampled trees to be calculated when these trees contain only clades that are in other sampled trees. Furthermore, the method can be used to estimate the total probability of the set of sampled trees which provides a measure of the thoroughness of a posterior sample.

MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space.

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d(N)/d(S) rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.

An assessment of transgenomics as a tool for identifying genes involved in the evolutionary differentiation of closely related plant species.

• Transgenomics is the process of introducing genomic clones from a donor species into a recipient species and then screening the resultant transgenic lines for phenotypes of interest. This method might allow us to find genes involved in the evolution of phenotypic differences between species as well as genes that have the potential to contribute to reproductive isolation: potential speciation genes. • More than 1100 20-kbp genomic clones from Leavenworthia alabamica were moved into Arabidopsis thaliana by transformation. After screening a single primary transformant for each line, clones associated with mutant phenotypes were tested for repeatability and co-segregation. • We found 84 clones with possible phenotypic effects, of which eight were repeatedly associated with the same phenotype. One clone, 11_11B, co-segregated with a short fruit phenotype. Further study showed that 11_11B affects seed development, with as much as one-third of the seeds aborted in some fruit. • Transgenomics is a viable strategy for discovering genes of evolutionary interest. We identify methods to reduce false positives and false negatives in the future. 11_11B can be viewed as a potential speciation gene, illustrating the value of transgenomics for studying the molecular basis of reproductive isolation.

Specificity in the symbiotic association between fungus-growing ants and protective Pseudonocardia bacteria.

Fungus-growing ants (tribe Attini) engage in a mutualism with a fungus that serves as the ants' primary food source, but successful fungus cultivation is threatened by microfungal parasites (genus Escovopsis). Actinobacteria (genus Pseudonocardia) associate with most of the phylogenetic diversity of fungus-growing ants; are typically maintained on the cuticle of workers; and infection experiments, bioassay challenges and chemical analyses support a role of Pseudonocardia in defence against Escovopsis through antibiotic production. Here we generate a two-gene phylogeny for Pseudonocardia associated with 124 fungus-growing ant colonies, evaluate patterns of ant-Pseudonocardia specificity and test Pseudonocardia antibiotic activity towards Escovopsis. We show that Pseudonocardia associated with fungus-growing ants are not monophyletic: the ants have acquired free-living strains over the evolutionary history of the association. Nevertheless, our analysis reveals a significant pattern of specificity between clades of Pseudonocardia and groups of related fungus-growing ants. Furthermore, antibiotic assays suggest that despite Escovopsis being generally susceptible to inhibition by diverse Actinobacteria, the ant-derived Pseudonocardia inhibit Escovopsis more strongly than they inhibit other fungi, and are better at inhibiting this pathogen than most environmental Pseudonocardia strains tested. Our findings support a model that many fungus-growing ants maintain specialized Pseudonocardia symbionts that help with garden defence.

BUCKy: gene tree/species tree reconciliation with Bayesian concordance analysis.

MOTIVATION: BUCKy is a C++ program that implements Bayesian concordance analysis. The method uses a non-parametric clustering of genes with compatible trees, and reconstructs the primary concordance tree from clades supported by the largest proportions of genes. A population tree with branch lengths in coalescent units is estimated from quartet concordance factors. AVAILABILITY: BUCKy is open source and distributed under the GNU general public license at www.stat.wisc.edu/∼ane/bucky/.

Fine-scale phylogenetic discordance across the house mouse genome.

Population genetic theory predicts discordance in the true phylogeny of different genomic regions when studying recently diverged species. Despite this expectation, genome-wide discordance in young species groups has rarely been statistically quantified. The house mouse subspecies group provides a model system for examining phylogenetic discordance. House mouse subspecies are recently derived, suggesting that even if there has been a simple tree-like population history, gene trees could disagree with the population history due to incomplete lineage sorting. Subspecies of house mice also hybridize in nature, raising the possibility that recent introgression might lead to additional phylogenetic discordance. Single-locus approaches have revealed support for conflicting topologies, resulting in a subspecies tree often summarized as a polytomy. To analyze phylogenetic histories on a genomic scale, we applied a recently developed method, Bayesian concordance analysis, to dense SNP data from three closely related subspecies of house mice: Mus musculus musculus, M. m. castaneus, and M. m. domesticus. We documented substantial variation in phylogenetic history across the genome. Although each of the three possible topologies was strongly supported by a large number of loci, there was statistical evidence for a primary phylogenetic history in which M. m. musculus and M. m. castaneus are sister subspecies. These results underscore the importance of measuring phylogenetic discordance in other recently diverged groups using methods such as Bayesian concordance analysis, which are designed for this purpose.

A Bayesian perspective on a non-parsimonious parsimony model.

Several stochastic models of character change, when implemented in a maximum likelihood framework, are known to give a correspondence between the maximum parsimony method and the method of maximum likelihood. One such model has an independently estimated branch-length parameter for each site and each branch of the phylogenetic tree. This model--the no-common-mechanism model--has many parameters, and, in fact, the number of parameters increases as fast as the alignment is extended. We take a Bayesian approach to the no-common-mechanism model and place independent gamma prior probability distributions on the branch-length parameters. We are able to analytically integrate over the branch lengths, and this allowed us to implement an efficient Markov chain Monte Carlo method for exploring the space of phylogenetic trees. We were able to reliably estimate the posterior probabilities of clades for phylogenetic trees of up to 500 sequences. However, the Bayesian approach to the problem, at least as implemented here with an independent prior on the length of each branch, does not tame the behavior of the branch-length parameters. The integrated likelihood appears to be a simple rescaling of the parsimony score for a tree, and the marginal posterior probability distribution of the length of a branch is dependent upon how the maximum parsimony method reconstructs the characters at the interior nodes of the tree. The method we describe, however, is of potential importance in the analysis of morphological character data and also for improving the behavior of Markov chain Monte Carlo methods implemented for models in which sites share a common branch-length parameter.

Efficiency of Markov chain Monte Carlo tree proposals in Bayesian phylogenetics.

The main limiting factor in Bayesian MCMC analysis of phylogeny is typically the efficiency with which topology proposals sample tree space. Here we evaluate the performance of seven different proposal mechanisms, including most of those used in current Bayesian phylogenetics software. We sampled 12 empirical nucleotide data sets--ranging in size from 27 to 71 taxa and from 378 to 2,520 sites--under difficult conditions: short runs, no Metropolis-coupling, and an oversimplified substitution model producing difficult tree spaces (Jukes Cantor with equal site rates). Convergence was assessed by comparison to reference samples obtained from multiple Metropolis-coupled runs. We find that proposals producing topology changes as a side effect of branch length changes (LOCAL and Continuous Change) consistently perform worse than those involving stochastic branch rearrangements (nearest neighbor interchange, subtree pruning and regrafting, tree bisection and reconnection, or subtree swapping). Among the latter, moves that use an extension mechanism to mix local with more distant rearrangements show better overall performance than those involving only local or only random rearrangements. Moves with only local rearrangements tend to mix well but have long burn-in periods, whereas moves with random rearrangements often show the reverse pattern. Combinations of moves tend to perform better than single moves. The time to convergence can be shortened considerably by starting with a good tree, but this comes at the cost of compromising convergence diagnostics based on overdispersed starting points. Our results have important implications for developers of Bayesian MCMC implementations and for the large group of users of Bayesian phylogenetics software.

A Bayesian model of AFLP marker evolution and phylogenetic inference.

Amplified Fragment Length Polymorphism (AFLP) markers are formed by selective amplification of DNA fragments from digested total genomic DNA. The technique is popular because it is a relatively inexpensive way to produce large numbers of reproducible genetic markers. In this paper, we describe a Bayesian approach to modeling AFLP marker evolution by nucleotide substitution and an MCMC approach to estimate phylogeny from AFLP marker data. We demonstrate the method on species in Carex section Ovales, a group of sedges common in North America. We compare the results of our analysis with a clustering method based on Nei and Li's restriction-site distance and a two-state Bayesian analysis using MrBayes.

Bayesian estimation of concordance among gene trees.

Multigene sequence data have great potential for elucidating important and interesting evolutionary processes, but statistical methods for extracting information from such data remain limited. Although various biological processes may cause different genes to have different genealogical histories (and hence different tree topologies), we also may expect that the number of distinct topologies among a set of genes is relatively small compared with the number of possible topologies. Therefore evidence about the tree topology for one gene should influence our inferences of the tree topology on a different gene, but to what extent? In this paper, we present a new approach for modeling and estimating concordance among a set of gene trees given aligned molecular sequence data. Our approach introduces a one-parameter probability distribution to describe the prior distribution of concordance among gene trees. We describe a novel 2-stage Markov chain Monte Carlo (MCMC) method that first obtains independent Bayesian posterior probability distributions for individual genes using standard methods. These posterior distributions are then used as input for a second MCMC procedure that estimates a posterior distribution of gene-to-tree maps (GTMs). The posterior distribution of GTMs can then be summarized to provide revised posterior probability distributions for each gene (taking account of concordance) and to allow estimation of the proportion of the sampled genes for which any given clade is true (the sample-wide concordance factor). Further, under the assumption that the sampled genes are drawn randomly from a genome of known size, we show how one can obtain an estimate, with credibility intervals, on the proportion of the entire genome for which a clade is true (the genome-wide concordance factor). We demonstrate the method on a set of 106 genes from 8 yeast species.