Inferring Viral Transmission Time from Phylogenies for Known Transmission Pairs.

When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.

Distinguishing Cophylogenetic Signal from Phylogenetic Congruence Clarifies the Interplay Between Evolutionary History and Species Interactions.

Interspecific interactions, including host-symbiont associations, can profoundly affect the evolution of the interacting species. Given the phylogenies of host and symbiont clades and knowledge of which host species interact with which symbiont, two questions are often asked: "Do closely related hosts interact with closely related symbionts?" and "Do host and symbiont phylogenies mirror one another?." These questions are intertwined and can even collapse under specific situations, such that they are often confused one with the other. However, in most situations, a positive answer to the first question, hereafter referred to as "cophylogenetic signal," does not imply a close match between the host and symbiont phylogenies. It suggests only that past evolutionary history has contributed to shaping present-day interactions, which can arise, for example, through present-day trait matching, or from a single ancient vicariance event that increases the probability that closely related species overlap geographically. A positive answer to the second, referred to as "phylogenetic congruence," is more restrictive as it suggests a close match between the two phylogenies, which may happen, for example, if symbiont diversification tracks host diversification or if the diversifications of the two clades were subject to the same succession of vicariance events. Here we apply a set of methods (ParaFit, PACo, and eMPRess), whose significance is often interpreted as evidence for phylogenetic congruence, to simulations under 3 biologically realistic scenarios of trait matching, a single ancient vicariance event, and phylogenetic tracking with frequent cospeciation events. The latter is the only scenario that generates phylogenetic congruence, whereas the first 2 generate a cophylogenetic signal in the absence of phylogenetic congruence. We find that tests of global-fit methods (ParaFit and PACo) are significant under the 3 scenarios, whereas tests of event-based methods (eMPRess) are only significant under the scenario of phylogenetic tracking. Therefore, significant results from global-fit methods should be interpreted in terms of cophylogenetic signal and not phylogenetic congruence; such significant results can arise under scenarios when hosts and symbionts had independent evolutionary histories. Conversely, significant results from event-based methods suggest a strong form of dependency between hosts and symbionts evolutionary histories. Clarifying the patterns detected by different cophylogenetic methods is key to understanding how interspecific interactions shape and are shaped by evolution.

The fundamental role of character coding in Bayesian morphological phylogenetics.

Phylogenetic trees establish a historical context for the study of organismal form and function. Most phylogenetic trees are estimated using a model of evolution. For molecular data, modeling evolution is often based on biochemical observations about changes between character states. For example, there are four nucleotides, and we can make assumptions about the probability of transitions between them. By contrast, for morphological characters, we may not know a priori how many characters states there are per character, as both extant sampling and the fossil record may be highly incomplete, which leads to an observer bias. For a given character, the state space may be larger than what has been observed in the sample of taxa collected by the researcher. In this case, how many evolutionary rates are needed to even describe transitions between morphological character states may not be clear, potentially leading to model misspecification. To explore the impact of this model misspecification, we simulated character data with varying numbers of character states per character. We then used the data to estimate phylogenetic trees using models of evolution with the correct number of character states and an incorrect number of character states. The results of this study indicate that this observer bias may lead to phylogenetic error, particularly in the branch lengths of trees. If the state space is wrongly assumed to be too large, then we underestimate the branch lengths, and the opposite occurs when the state space is wrongly assumed to be too small.

Michener's group-size paradox in cooperatively breeding birds.

According to Michener's paradox, most altruistic groups in nature should be small and large groups should not exist. This is because per capita productivity is thought to decrease as groups get larger, meaning that the share of indirect fitness available to each group member declines, which favours dispersal. The empirical evidence for a decrease in per capita productivity is contradictory, however, and limited to the social Hymenoptera. I report that per capita reproductive success decreased with increasing group size across 26 cooperatively breeding bird species. Small groups comprising two or three individuals were the most common (79% of 16,101 groups), and these had the highest per capita reproductive success. This close fit between per capita reproductive success and the distribution of group sizes in nature suggests that it may indeed be difficult for large groups to evolve through indirect fitness benefits alone.

Current Methods for Recombination Detection in Bacteria.

The role of genetic exchanges, i.e., homologous recombination (HR) and horizontal gene transfer (HGT), in bacteria cannot be overestimated for it is a pivotal mechanism leading to their evolution and adaptation, thus, tracking the signs of recombination and HGT events is importance both for fundamental and applied science. To date, dozens of bioinformatics tools for revealing recombination signals are available, however, their pros and cons as well as the spectra of solvable tasks have not yet been systematically reviewed. Moreover, there are two major groups of software. One aims to infer evidence of HR, while the other only deals with horizontal gene transfer (HGT). However, despite seemingly different goals, all the methods use similar algorithmic approaches, and the processes are interconnected in terms of genomic evolution influencing each other. In this review, we propose a classification of novel instruments for both HR and HGT detection based on the genomic consequences of recombination. In this context, we summarize available methodologies paying particular attention to the type of traceable events for which a certain program has been designed.

Indirect identification of horizontal gene transfer.

Several implicit methods to infer horizontal gene transfer (HGT) focus on pairs of genes that have diverged only after the divergence of the two species in which the genes reside. This situation defines the edge set of a graph, the later-divergence-time (LDT) graph, whose vertices correspond to genes colored by their species. We investigate these graphs in the setting of relaxed scenarios, i.e., evolutionary scenarios that encompass all commonly used variants of duplication-transfer-loss scenarios in the literature. We characterize LDT graphs as a subclass of properly vertex-colored cographs, and provide a polynomial-time recognition algorithm as well as an algorithm to construct a relaxed scenario that explains a given LDT. An edge in an LDT graph implies that the two corresponding genes are separated by at least one HGT event. The converse is not true, however. We show that the complete xenology relation is described by an rs-Fitch graph, i.e., a complete multipartite graph satisfying constraints on the vertex coloring. This class of vertex-colored graphs is also recognizable in polynomial time. We finally address the question "how much information about all HGT events is contained in LDT graphs" with the help of simulations of evolutionary scenarios with a wide range of duplication, loss, and HGT events. In particular, we show that a simple greedy graph editing scheme can be used to efficiently detect HGT events that are implicitly contained in LDT graphs.

Salt transport by the gill Na+-K+-2Cl- symporter in palaemonid shrimps: exploring physiological, molecular and evolutionary landscapes.

Palaemonid shrimps inhabit osmotic niches from marine to continental waters. They hyper-regulate hemolymph osmolality and ionic concentrations in dilute media, hypo-regulating in concentrated media. Their gill epithelia express ion transporters like the Na+-K+-2Cl- symporter (NKCC) thought to play a role in salt secretion. To examine Cl- hypo-regulatory capability and phylogenetic correlations between gill NKCC mRNA levels and protein expression, we used palaemonids ranging from marine tide pools through estuaries (Palaemon) to coastal and continental fresh waters (Macrobrachium). We established the species' upper critical salinity limits (UL50) and short- (24 h) and long-term (120h) hypo-regulatory abilities at salinities of 80% of their UL50's (80%UL50). The Palaemon species exhibited the highest UL50's and greatest hypo-regulatory capabilities; among the Macrobrachium species, UL50's were higher in the diadromous than in the hololimnetic species. While basal transcript levels of gill NKCC mRNA were highest in P. pandaliformis, levels were unaffected by salinity or exposure time in all species. However, gill NKCC protein abundance increased after 120-h exposure at the 80%UL50 in all Macrobrachium species, except M. potiuna. Unexpectedly, hemolymph hyper-osmoregulatory capability in acclimatization media correlated with gill NKCC protein synthesis, while gill NKCC mRNA expression correlated with hemolymph hyper-Cl- regulation in Macrobrachium. These findings, together with the evolutionary history of osmoregulation in this shrimp clade, suggest a role for the gill NKCC symporter in both salt uptake and secretion. The evolution of NKCC protein expression responsiveness, unlike hemolymph hypo-regulation and NKCC mRNA expression, may have been driven by environmental salinity during niche radiation. SUMMARY STATEMENT: While mRNA expression of the gill Na+-K+-2Cl- symporter is unchanged during acclimation of palaemonid shrimps to saline media, protein expression is up regulated, revealing a role in chloride secretion.

Phylosymmetric Algebras: Mathematical Properties of a New Tool in Phylogenetics.

In phylogenetics, it is of interest for rate matrix sets to satisfy closure under matrix multiplication as this makes finding the set of corresponding transition matrices possible without having to compute matrix exponentials. It is also advantageous to have a small number of free parameters as this, in applications, will result in a reduction in computation time. We explore a method of building a rate matrix set from a rooted tree structure by assigning rates to internal tree nodes and states to the leaves, then defining the rate of change between two states as the rate assigned to the most recent common ancestor of those two states. We investigate the properties of these matrix sets from both a linear algebra and a graph theory perspective and show that any rate matrix set generated this way is closed under matrix multiplication. The consequences of setting two rates assigned to internal tree nodes to be equal are then considered. This methodology could be used to develop parameterised models of amino acid substitution which have a small number of parameters but convey biological meaning.

Partner abundance controls mutualism stability and the pace of morphological change over geologic time.

Mutualisms that involve symbioses among specialized partners may be more stable than mutualisms among generalists, and theoretical models predict that in many mutualisms, partners exert reciprocal stabilizing selection on traits directly involved in the interaction. A corollary is that mutualism breakdown should increase morphological rates of evolution. We here use the largest ant-plant clade (Hydnophytinae), with different levels of specialization for mutualistic ant symbionts, to study the ecological context of mutualism breakdown and the response of a key symbiosis-related trait, domatium entrance hole size, which filters symbionts by size. Our analyses support three predictions from mutualism theory. First, all 12 losses apparently only occur from a generalist symbiotic state. Second, mutualism losses occurred where symbionts are scarce, in our system at high altitudes. Third, domatium entrance hole size barely changes in specialized symbiotic species, but evolves rapidly once symbiosis with ants has broken down, with a "morphorate map" revealing that hotspots of entrance hole evolution are clustered in high-altitude areas. Our study reveals that mutualistic strategy profoundly affects the pace of morphological change in traits involved in the interaction and suggests that shifts in partners' relative abundances may frequently drive reversions of generalist mutualisms to autonomy.

LSX: automated reduction of gene-specific lineage evolutionary rate heterogeneity for multi-gene phylogeny inference.

BACKGROUND: Lineage rate heterogeneity can be a major source of bias, especially in multi-gene phylogeny inference. We had previously tackled this issue by developing LS3, a data subselection algorithm that, by removing fast-evolving sequences in a gene-specific manner, identifies subsets of sequences that evolve at a relatively homogeneous rate. However, this algorithm had two major shortcomings: (i) it was automated and published as a set of bash scripts, and hence was Linux-specific, and not user friendly, and (ii) it could result in very stringent sequence subselection when extremely slow-evolving sequences were present. RESULTS: We address these challenges and produce a new, platform-independent program, LSX, written in R, which includes a reprogrammed version of the original LS3 algorithm and has added features to make better lineage rate calculations. In addition, we developed and included an alternative version of the algorithm, LS4, which reduces lineage rate heterogeneity by detecting sequences that evolve too fast and sequences that evolve too slow, resulting in less stringent data subselection when extremely slow-evolving sequences are present. The efficiency of LSX and of LS4 with datasets with extremely slow-evolving sequences is demonstrated with simulated data, and by the resolution of a contentious node in the catfish phylogeny that was affected by an unusually high lineage rate heterogeneity in the dataset. CONCLUSIONS: LSX is a new bioinformatic tool, with an accessible code, and with which the effect of lineage rate heterogeneity can be explored in gene sequence datasets of virtually any size. In addition, the two modalities of the sequence subsampling algorithm included, LS3 and LS4, allow the user to optimize the amount of non-phylogenetic signal removed while keeping a maximum of phylogenetic signal.

A trait-based approach to predict population genetic structure in bees.

Understanding population genetic structure is key to developing predictions about species susceptibility to environmental change, such as habitat fragmentation and climate change. It has been theorized that life-history traits may constrain some species in their dispersal and lead to greater signatures of population genetic structure. In this study, we use a quantitative comparative approach to assess if patterns of population genetic structure in bees are driven by three key species-level life-history traits: body size, sociality, and diet breadth. Specifically, we reviewed the current literature on bee population genetic structure, as measured by the differentiation indices Nei's GST, Hedrick's G'ST , and Jost's D. We then used phylogenetic generalised linear models to estimate the correlation between the evolution of these traits and patterns of genetic differentiation. Our analyses revealed a negative and significant effect of body size on genetic structure, regardless of differentiation index utilized. For Hedrick's G'ST and Jost's D, we also found a significant impact of sociality, where social species exhibited lower levels of differentiation than solitary species. We did not find an effect of diet specialization on population genetic structure. Overall, our results suggest that physical dispersal or other functions related to body size are among the most critical for mediating population structure for bees. We further highlight the importance of standardizing population genetic measures to more easily compare studies and to identify the most susceptible species to landscape and climatic changes.

Bayesian and parsimony approaches reconstruct informative trees from simulated morphological datasets.

Phylogenetic analysis aims to establish the true relationships between taxa. Different analytical methods, however, can reach different conclusions. In order to establish which approach best reconstructs true relationships, previous studies have simulated datasets from known tree topologies, and identified the method that reconstructs the generative tree most accurately. On this basis, researchers have argued that morphological datasets should be analysed by Bayesian approaches, which employ an explicit probabilistic model of evolution, rather than parsimony methods-with implied weights parsimony sometimes identified as particularly inaccurate. Accuracy alone, however, is an inadequate measure of a tree's utility: a fully unresolved tree is perfectly accurate, yet contains no phylogenetic information. The highly resolved trees recovered by implied weights parsimony in fact contain as much useful information as the more accurate, but less resolved, trees recovered by Bayesian methods. By collapsing poorly supported groups, this superior resolution can be traded for accuracy, resulting in trees as accurate as those obtained by a Bayesian approach. By contrast, equally weighted parsimony analysis produces trees that are less resolved and less accurate, leading to less reliable evolutionary conclusions.

StarBEAST2 Brings Faster Species Tree Inference and Accurate Estimates of Substitution Rates.

Fully Bayesian multispecies coalescent (MSC) methods like *BEAST estimate species trees from multiple sequence alignments. Today thousands of genes can be sequenced for a given study, but using that many genes with *BEAST is intractably slow. An alternative is to use heuristic methods which compromise accuracy or completeness in return for speed. A common heuristic is concatenation, which assumes that the evolutionary history of each gene tree is identical to the species tree. This is an inconsistent estimator of species tree topology, a worse estimator of divergence times, and induces spurious substitution rate variation when incomplete lineage sorting is present. Another class of heuristics directly motivated by the MSC avoids many of the pitfalls of concatenation but cannot be used to estimate divergence times. To enable fuller use of available data and more accurate inference of species tree topologies, divergence times, and substitution rates, we have developed a new version of *BEAST called StarBEAST2. To improve convergence rates we add analytical integration of population sizes, novel MCMC operators and other optimizations. Computational performance improved by 13.5× and 13.8× respectively when analyzing two empirical data sets, and an average of 33.1× across 30 simulated data sets. To enable accurate estimates of per-species substitution rates, we introduce species tree relaxed clocks, and show that StarBEAST2 is a more powerful and robust estimator of rate variation than concatenation. StarBEAST2 is available through the BEAUTi package manager in BEAST 2.4 and above.

Phylogenetic Tools for Generalized HIV-1 Epidemics: Findings from the PANGEA-HIV Methods Comparison.

Viral phylogenetic methods contribute to understanding how HIV spreads in populations, and thereby help guide the design of prevention interventions. So far, most analyses have been applied to well-sampled concentrated HIV-1 epidemics in wealthy countries. To direct the use of phylogenetic tools to where the impact of HIV-1 is greatest, the Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium generates full-genome viral sequences from across sub-Saharan Africa. Analyzing these data presents new challenges, since epidemics are principally driven by heterosexual transmission and a smaller fraction of cases is sampled. Here, we show that viral phylogenetic tools can be adapted and used to estimate epidemiological quantities of central importance to HIV-1 prevention in sub-Saharan Africa. We used a community-wide methods comparison exercise on simulated data, where participants were blinded to the true dynamics they were inferring. Two distinct simulations captured generalized HIV-1 epidemics, before and after a large community-level intervention that reduced infection levels. Five research groups participated. Structured coalescent modeling approaches were most successful: phylogenetic estimates of HIV-1 incidence, incidence reductions, and the proportion of transmissions from individuals in their first 3 months of infection correlated with the true values (Pearson correlation > 90%), with small bias. However, on some simulations, true values were markedly outside reported confidence or credibility intervals. The blinded comparison revealed current limits and strengths in using HIV phylogenetics in challenging settings, provided benchmarks for future methods' development, and supports using the latest generation of phylogenetic tools to advance HIV surveillance and prevention.

Constructing a broadly inclusive seed plant phylogeny.

PREMISE OF THE STUDY: Large phylogenies can help shed light on macroevolutionary patterns that inform our understanding of fundamental processes that shape the tree of life. These phylogenies also serve as tools that facilitate other systematic, evolutionary, and ecological analyses. Here we combine genetic data from public repositories (GenBank) with phylogenetic data (Open Tree of Life project) to construct a dated phylogeny for seed plants. METHODS: We conducted a hierarchical clustering analysis of publicly available molecular data for major clades within the Spermatophyta. We constructed phylogenies of major clades, estimated divergence times, and incorporated data from the Open Tree of Life project, resulting in a seed plant phylogeny. We estimated diversification rates, excluding those taxa without molecular data. We also summarized topological uncertainty and data overlap for each major clade. KEY RESULTS: The trees constructed for Spermatophyta consisted of 79,881 and 353,185 terminal taxa; the latter included the Open Tree of Life taxa for which we could not include molecular data from GenBank. The diversification analyses demonstrated nested patterns of rate shifts throughout the phylogeny. Data overlap and inference uncertainty show significant variation throughout and demonstrate the continued need for data collection across seed plants. CONCLUSIONS: This study demonstrates a means for combining available resources to construct a dated phylogeny for plants. However, this approach is an early step and more developments are needed to add data, better incorporating underlying uncertainty, and improve resolution. The methods discussed here can also be applied to other major clades in the tree of life.

Support for linguistic macrofamilies from weighted sequence alignment.

Computational phylogenetics is in the process of revolutionizing historical linguistics. Recent applications have shed new light on controversial issues, such as the location and time depth of language families and the dynamics of their spread. So far, these approaches have been limited to single-language families because they rely on a large body of expert cognacy judgments or grammatical classifications, which is currently unavailable for most language families. The present study pursues a different approach. Starting from raw phonetic transcription of core vocabulary items from very diverse languages, it applies weighted string alignment to track both phonetic and lexical change. Applied to a collection of ∼1,000 Eurasian languages and dialects, this method, combined with phylogenetic inference, leads to a classification in excellent agreement with established findings of historical linguistics. Furthermore, it provides strong statistical support for several putative macrofamilies contested in current historical linguistics. In particular, there is a solid signal for the Nostratic/Eurasiatic macrofamily.

The influence of molecular markers and methods on inferring the phylogenetic relationships between the representatives of the Arini (parrots, Psittaciformes), determined on the basis of their complete mitochondrial genomes.

BACKGROUND: Conures are a morphologically diverse group of Neotropical parrots classified as members of the tribe Arini, which has recently been subjected to a taxonomic revision. The previously broadly defined Aratinga genus of this tribe has been split into the 'true' Aratinga and three additional genera, Eupsittula, Psittacara and Thectocercus. Popular markers used in the reconstruction of the parrots' phylogenies derive from mitochondrial DNA. However, current phylogenetic analyses seem to indicate conflicting relationships between Aratinga and other conures, and also among other Arini members. Therefore, it is not clear if the mtDNA phylogenies can reliably define the species tree. The inconsistencies may result from the variable evolution rate of the markers used or their weak phylogenetic signal. To resolve these controversies and to assess to what extent the phylogenetic relationships in the tribe Arini can be inferred from mitochondrial genomes, we compared representative Arini mitogenomes as well as examined the usefulness of the individual mitochondrial markers and the efficiency of various phylogenetic methods. RESULTS: Single molecular markers produced inconsistent tree topologies, while different methods offered various topologies even for the same marker. A significant disagreement in these tree topologies occurred for cytb, nd2 and nd6 genes, which are commonly used in parrot phylogenies. The strongest phylogenetic signal was found in the control region and RNA genes. However, these markers cannot be used alone in inferring Arini phylogenies because they do not provide fully resolved trees. The most reliable phylogeny of the parrots under study is obtained only on the concatenated set of all mitochondrial markers. The analyses established significantly resolved relationships within the former Aratinga representatives and the main genera of the tribe Arini. Such mtDNA phylogeny can be in agreement with the species tree, owing to its match with synapomorphic features in plumage colouration. CONCLUSIONS: Phylogenetic relationships inferred from single mitochondrial markers can be incorrect and contradictory. Therefore, such phylogenies should be considered with caution. Reliable results can be produced by concatenated sets of all or at least the majority of mitochondrial genes and the control region. The results advance a new view on the relationships among the main genera of Arini and resolve the inconsistencies between the taxa that were previously classified as the broadly defined genus Aratinga. Although gene and species trees do not always have to be consistent, the mtDNA phylogenies for Arini can reflect the species tree.

Phylogenetic Analysis Supports the Aerobic-Capacity Model for the Evolution of Endothermy.

The evolution of endothermy is a controversial topic in evolutionary biology, although several hypotheses have been proposed to explain it. To a great extent, the debate has centered on the aerobic-capacity model (AC model), an adaptive hypothesis involving maximum and resting rates of metabolism (MMR and RMR, respectively; hereafter "metabolic traits"). The AC model posits that MMR, a proxy of aerobic capacity and sustained activity, is the target of directional selection and that RMR is also influenced as a correlated response. Associated with this reasoning are the assumptions that (1) factorial aerobic scope (FAS; MMR/RMR) and net aerobic scope (NAS; MMR - RMR), two commonly used indexes of aerobic capacity, show different evolutionary optima and (2) the functional link between MMR and RMR is a basic design feature of vertebrates. To test these assumptions, we performed a comparative phylogenetic analysis in 176 vertebrate species, ranging from fish and amphibians to birds and mammals. Using disparity-through-time analysis, we also explored trait diversification and fitted different evolutionary models to study the evolution of metabolic traits. As predicted, we found (1) a positive phylogenetic correlation between RMR and MMR, (2) diversification of metabolic traits exceeding that of random-walk expectations, (3) that a model assuming selection fits the data better than alternative models, and (4) that a single evolutionary optimum best fits FAS data, whereas a model involving two optima (one for ectotherms and another for endotherms) is the best explanatory model for NAS. These results support the AC model and give novel information concerning the mode and tempo of physiological evolution of vertebrates.

Phylogenetics and the human microbiome.

The human microbiome is the ensemble of genes in the microbes that live inside and on the surface of humans. Because microbial sequencing information is now much easier to come by than phenotypic information, there has been an explosion of sequencing and genetic analysis of microbiome samples. Much of the analytical work for these sequences involves phylogenetics, at least indirectly, but methodology has developed in a somewhat different direction than for other applications of phylogenetics. In this article, I review the field and its methods from the perspective of a phylogeneticist, as well as describing current challenges for phylogenetics coming from this type of work.

Quantifying MCMC exploration of phylogenetic tree space.

In order to gain an understanding of the effectiveness of phylogenetic Markov chain Monte Carlo (MCMC), it is important to understand how quickly the empirical distribution of the MCMC converges to the posterior distribution. In this article, we investigate this problem on phylogenetic tree topologies with a metric that is especially well suited to the task: the subtree prune-and-regraft (SPR) metric. This metric directly corresponds to the minimum number of MCMC rearrangements required to move between trees in common phylogenetic MCMC implementations. We develop a novel graph-based approach to analyze tree posteriors and find that the SPR metric is much more informative than simpler metrics that are unrelated to MCMC moves. In doing so, we show conclusively that topological peaks do occur in Bayesian phylogenetic posteriors from real data sets as sampled with standard MCMC approaches, investigate the efficiency of Metropolis-coupled MCMC (MCMCMC) in traversing the valleys between peaks, and show that conditional clade distribution (CCD) can have systematic problems when there are multiple peaks.