Phylogenetic mixture models can reduce node-density artifacts

We investigate the performance of phylogenetic mixture models in reducing a well-known and pervasive artifact of phylogenetic inference known as the node-density effect, comparing them to partitioned analyses of the same data. The node-density effect refers to the tendency for the amount of evolutionary change in longer branches of phylogenies to be underestimated compared to that in regions of the tree where there are more nodes and thus branches are typically shorter. Mixture models allow more than one model of sequence evolution to describe the sites in an alignment without prior knowledge of the evolutionary processes that characterize the data or how they correspond to different sites. If multiple evolutionary patterns are common in sequence evolution, mixture models may be capable of reducing node-density effects by characterizing the evolutionary processes more accurately. In gene-sequence alignments simulated to have heterogeneous patterns of evolution, we find that mixture models can reduce node-density effects to negligible levels or remove them altogether, performing as well as partitioned analyses based on the known simulated patterns. The mixture models achieve this without knowledge of the patterns that generated the data and even in some cases without specifying the full or true model of sequence evolution known to underlie the data. The latter result is especially important in real applications, as the true model of evolution is seldom known. We find the same patterns of results for two real data sets with evidence of complex patterns of sequence evolution: mixture models substantially reduced node-density effects and returned better likelihoods compared to partitioning models specifically fitted to these data. We suggest that the presence of more than one pattern of evolution in the data is a common source of error in phylogenetic inference and that mixture models can often detect these patterns even without prior knowledge of their presence in the data. Routine use of mixture models alongside other approaches to phylogenetic inference may often reveal hidden or unexpected patterns of sequence evolution and can improve phylogenetic inference.     

A novel approach to detecting and measuring recombination: new insights into evolution in viruses, bacteria, and mitochondria

An accurate estimate of the extent of recombination is important whenever phylogenetic methods are applied to potentially recombining nucleotide sequences. Here, data sets from viruses, bacteria, and mitochondria were examined for deviations from clonality using a new approach for detecting and measuring recombination. The apparent rate heterogeneity (ARH) among sites in a sequence alignment can be inflated as an artifact of recombination. However, the composition of polymorphic sites will differ in a data set with recombination-generated ARH versus a clonal data set that exhibits the equivalent degree of rate heterogeneity. This is because recombinant data sets, encompassing regions of conflicting phylogenetic history, tend to yield "starlike" trees that are superficially similar to those inferred from clonal data sets with weak phylogenetic signal throughout. Specifically, a recombinant data set will be unexpectedly rich in conflicting phylogenetic information compared with clonally generated data sets supporting the same tree shape. Its value of q-defined as the proportion of two-state parsimony-informative sites to all polymorphic sites-will be greater than that expected for nonrecombinant data. The method proposed here, the informative-sites test, compares the value of q against a null distribution of values found using Monte Carlo-simulated data evolved under the null hypothesis of clonality. A significant excess of q indicates that the assumption of clonality is not valid and hence that the ARH in the data is at least partly an artifact of recombination. Investigations of the procedure using simulated sequences indicated that it can successfully detect and measure recombination and that it is unlikely to produce "false positives." Simulations also showed that for recombinant data, na?ve use of maximum-likelihood models incorporating rate heterogeneity can lead to overestimation of the time to the most recent common ancestor. Application of the test to real data revealed for the first time that populations of viruses, like those of bacteria, can be brought close to complete linkage equilibrium by pervasive recombination. On the other hand, the test did not reject the hypothesis of clonality when applied to a data set from the coding region of human mitochondrial DNA, despite its high level of ARH and homoplasy.     

Bayesian estimation of sequence damage in ancient DNA

DNA extracted from archaeological and paleontological remains is usually damaged by biochemical processes postmortem. Some of these processes lead to changes in the structure of the DNA molecule, which can result in the incorporation of incorrect nucleotides during polymerase chain reaction. These base misincorporations, or miscoding lesions, can lead to the inclusion of spurious additional mutations in ancient DNA (aDNA) data sets. This has the potential to affect the outcome of phylogenetic and population genetic analyses, including estimates of mutation rates and genetic diversity. We present a novel model, termed the delta model, which estimates the amount of damage in DNA data and accounts for its effects in a Bayesian phylogenetic framework. The ability of the delta model to estimate damage is first investigated using a simulation study. The model is then applied to 13 aDNA data sets. The amount of damage in these data sets is shown to be significant but low (about 1 damaged base per 750 nt), suggesting that precautions for limiting the influence of damaged sites, such as cloning and enzymatic treatment, are worthwhile. The results also suggest that relatively high rates of mutation previously estimated from aDNA data are not entirely an artifact of sequence damage and are likely to be due to other factors such as the persistence of transient polymorphisms. The delta model appears to be particularly useful for placing upper credibility limits on the amount of sequence damage in an alignment, and this capacity might be beneficial for future aDNA studies or for the estimation of sequencing errors in modern DNA.     

Delta plots: a tool for analyzing phylogenetic distance data

A method is described that allows the assessment of treelikeness of phylogenetic distance data before tree estimation. This method is related to statistical geometry as introduced by Eigen, Winkler-Oswatitsch, and Dress (1988 [Proc. Natl. Acad. Sci. USA. 85:5913-5917]), and in essence, displays a measure for treelikeness of quartets in terms of a histogram that we call a delta plot. This allows identification of nontreelike data and analysis of noisy data sets arising from processes such as, for example, parallel evolution, recombination, or lateral gene transfer. In addition to an overall assessment of treelikeness, individual taxa can be ranked by reference to the treelikeness of the quartets to which they belong. Removal of taxa on the basis of this ranking results in an increase in accuracy of tree estimation. Recombinant data sets are simulated, and the method is shown to be capable of identifying single recombinant taxa on the basis of distance information alone, provided the parents of the recombinant sequence are sufficiently divergent and the mixture of tree histories is not strongly skewed toward a single tree. delta Plots and taxon rankings are applied to three biological data sets using distances derived from sequence alignment, gene order, and fragment length polymorphism.     

Simultaneously mapping and superimposing landmark configurations with parsimony as optimality criterion

All methods proposed to date for mapping landmark configurations on a phylogenetic tree start from an alignment generated by methods that make no use of phylogenetic information, usually by superimposing all configurations against a consensus configuration. In order to properly interpret differences between landmark configurations along the tree as changes in shape, the metric chosen to define the ancestral assignments should also form the basis to superimpose the configurations. Thus, we present here a method that merges both steps, map and align, into a single procedure that (for the given tree) produces a multiple alignment and ancestral assignments such that the sum of the Euclidean distances between the corresponding landmarks along tree nodes is minimized. This approach is an extension of the method proposed by Catalano et al. (2010. Phylogenetic morphometrics (I): the use of landmark data in a phylogenetic framework. Cladistics. 26:539-549) for mapping landmark data with parsimony as optimality criterion. In the context of phylogenetics, this method allows maximizing the degree to which similarity in landmark positions can be accounted for by common ancestry. In the context of morphometrics, this approach guarantees (heuristics aside) that all the transformations inferred on the tree represent changes in shape. The performance of the method was evaluated on different data sets, indicating that the method produces marked improvements in tree score (up to 5% compared with generalized superimpositions, up to 11% compared with ordinary superimpositions). These empirical results stress the importance of incorporating the phylogenetic information into the alignment step.     

Phylogenetic relationship of the kingdoms Animalia, Plantae, and Fungi, inferred from 23 different protein species

The phylogenetic relationship among the kingdoms Animalia, Plantae, and Fungi remains uncertain, because of lack of solid fossil evidence. In spite of the extensive molecular phylogenetic analyses since the early report, this problem is a longstanding controversy; the proposed phylogenetic relationships differ for different authors, depending on the molecules and methods that they use. To settle this problem, we have accumulated 23 different protein species from the three kingdoms and have inferred the phylogenetic trees by three different methods-- the maximum-likelihood method, the neighbor-joining method, and the maximum-parsimony method--for each data set. Although inferred tree topologies differ for different protein species and methods used, both the maximum-likelihood analysis based on the difference (delta l) between the total log-likelihood of a tree and that of the maximum- likelihood tree and bootstrap probability (P) of 23 proteins consisting of 10,051 amino acid sites in total have shown that a tree ((A,F),P), in which Plantae (P) is an outgroup to an Animalia (A)-Fungi (F) clade, is the maximum-likelihood tree; the delta l (= 0.0) and P (94%) of ((A,F),P) are significantly larger than those of ((A,P),F) (delta l = - 54.4 +/- 36.3; and P = 6%) and ((F,P),A) (delta l = -141.1 +/- 30.9; and P = 0%).(ABSTRACT TRUNCATED AT 250 WORDS)      

A structural EM algorithm for phylogenetic inference.

A central task in the study of molecular evolution is the reconstruction of a phylogenetic tree from sequences of current-day taxa. The most established approach to tree reconstruction is maximum likelihood (ML) analysis. Unfortunately, searching for the maximum likelihood phylogenetic tree is computationally prohibitive for large data sets. In this paper, we describe a new algorithm that uses Structural Expectation Maximization (EM) for learning maximum likelihood phylogenetic trees. This algorithm is similar to the standard EM method for edge-length estimation, except that during iterations of the Structural EM algorithm the topology is improved as well as the edge length. Our algorithm performs iterations of two steps. In the E-step, we use the current tree topology and edge lengths to compute expected sufficient statistics, which summarize the data. In the M-Step, we search for a topology that maximizes the likelihood with respect to these expected sufficient statistics. We show that searching for better topologies inside the M-step can be done efficiently, as opposed to standard methods for topology search. We prove that each iteration of this procedure increases the likelihood of the topology, and thus the procedure must converge. This convergence point, however, can be a suboptimal one. To escape from such "local optima," we further enhance our basic EM procedure by incorporating moves in the flavor of simulated annealing. We evaluate these new algorithms on both synthetic and real sequence data and show that for protein sequences even our basic algorithm finds more plausible trees than existing methods for searching maximum likelihood phylogenies. Furthermore, our algorithms are dramatically faster than such methods, enabling, for the first time, phylogenetic analysis of large protein data sets in the maximum likelihood framework.     

Automated Masking of AFLP Markers Improves Reliability of Phylogenetic Analyses

The amplified fragment length polymorphisms (AFLP) method has become an attractive tool in phylogenetics due to the ease with which large numbers of characters can be generated. In contrast to sequence-based phylogenetic approaches, AFLP data consist of anonymous multilocus markers. However, potential artificial amplifications or amplification failures of fragments contained in the AFLP data set will reduce AFLP reliability especially in phylogenetic inferences. In the present study, we introduce a new automated scoring approach, called “AMARE” (AFLP MAtrix REduction). The approach is based on replicates and makes marker selection dependent on marker reproducibility to control for scoring errors. To demonstrate the effectiveness of our approach we record error rate estimations, resolution scores, PCoA and stemminess calculations. As in general the true tree (i.e. the species phylogeny) is not known, we tested AMARE with empirical, already published AFLP data sets, and compared tree topologies of different AMARE generated character matrices to existing phylogenetic trees and/or other independent sources such as morphological and geographical data. It turns out that the selection of masked character matrices with highest resolution scores gave similar or even better phylogenetic results than the original AFLP data sets.     

PHYRN: a robust method for phylogenetic analysis of highly divergent sequences

Both multiple sequence alignment and phylogenetic analysis are problematic in the "twilight zone" of sequence similarity (≤ 25% amino acid identity). Herein we explore the accuracy of phylogenetic inference at extreme sequence divergence using a variety of simulated data sets. We evaluate four leading multiple sequence alignment (MSA) methods (MAFFT, T-COFFEE, CLUSTAL, and MUSCLE) and six commonly used programs of tree estimation (Distance-based: Neighbor-Joining; Character-based: PhyML, RAxML, GARLI, Maximum Parsimony, and Bayesian) against a novel MSA-independent method (PHYRN) described here. Strikingly, at "midnight zone" genetic distances (~7% pairwise identity and 4.0 gaps per position), PHYRN returns high-resolution phylogenies that outperform traditional approaches. We reason this is due to PHRYN's capability to amplify informative positions, even at the most extreme levels of sequence divergence. We also assess the applicability of the PHYRN algorithm for inferring deep evolutionary relationships in the divergent DANGER protein superfamily, for which PHYRN infers a more robust tree compared to MSA-based approaches. Taken together, these results demonstrate that PHYRN represents a powerful mechanism for mapping uncharted frontiers in highly divergent protein sequence data sets.     

Polyhedral Geometry of Phylogenetic Rogue Taxa

It is well known among phylogeneticists that adding an extra taxon (e.g. species) to a data set can alter the structure of the optimal phylogenetic tree in surprising ways. However, little is known about this “rogue taxon” effect. In this paper we characterize the behavior of balanced minimum evolution (BME) phylogenetics on data sets of this type using tools from polyhedral geometry. First we show that for any distance matrix there exist distances to a “rogue taxon” such that the BME-optimal tree for the data set with the new taxon does not contain any nontrivial splits (bipartitions) of the optimal tree for the original data. Second, we prove a theorem which restricts the topology of BME-optimal trees for data sets of this type, thus showing that a rogue taxon cannot have an arbitrary effect on the optimal tree. Third, we computationally construct polyhedral cones that give complete answers for BME rogue taxon behavior when our original data fits a tree on four, five, and six taxa. We use these cones to derive sufficient conditions for rogue taxon behavior for four taxa, and to understand the frequency of the rogue taxon effect via simulation.     

Rate asymmetry after genome duplication causes substantial long-branch attraction artifacts in the phylogeny of Saccharomyces species

Whole-genome duplication (WGD) produces sets of gene pairs that are all of the same age. We therefore expect that phylogenetic trees that relate these pairs to their orthologs in other species should show a single consistent topology. However, a previous study of gene pairs formed by WGD in the yeast Saccharomyces cerevisiae found conflicting topologies among neighbor-joining (NJ) trees drawn from different loci and suggested that this conflict was the result of "asynchronous functional divergence" of duplicated genes (Langkjaer, R. B., P. F. Cliften, M. Johnston, and J. Piskur. 2003. Yeast genome duplication was followed by asynchronous differentiation of duplicated genes. Nature 421:848-852). Here, we test whether the conflicting topologies might instead be due to asymmetrical rates of evolution leading to long-branch attraction (LBA) artifacts in phylogenetic trees. We constructed trees for 433 pairs of WGD paralogs in S. cerevisiae with their single orthologs in Saccharomyces kluyveri and Candida albicans. We find a strong correlation between the asymmetry of evolutionary rates of a pair of S. cerevisiae paralogs and the topology of the tree inferred for that pair. Saccharomyces cerevisiae gene pairs with approximately equal rates of evolution tend to give phylogenies in which the WGD postdates the speciation between S. cerevisiae and S. kluyveri (B-trees), whereas trees drawn from gene pairs with asymmetrical rates tend to show WGD pre-dating this speciation (A-trees). Gene order data from throughout the genome indicate that the "A-trees" are artifacts, even though more than 50% of gene pairs are inferred to have this topology when the NJ method as implemented in ClustalW (i.e., with Poisson correction of distances) is used to construct the trees. This LBA artifact can be ameliorated, but not eliminated, by using gamma-corrected distances or by using maximum likelihood trees with robustness estimated by the Shimodaira-Hasegawa test. Tests for adaptive evolution indicated that positive selection might be the cause of rate asymmetry in a substantial fraction (19%) of the paralog pairs.     

A support vector machine based test for incongruence between sets of trees in tree space

ABSTRACT: BACKGROUND: The increased use of multi-locus data sets for phylogenetic reconstruction has increased the need to determine whether a set of gene trees significantly deviate from the phylogenetic patterns of other genes. Such unusual gene trees may have been influenced by other evolutionary processes such as selection, gene duplication, or horizontal gene transfer. RESULTS: Motivated by this problem we propose a nonparametric goodness-of-fit test for two empirical distributions of gene trees, and we developed the software GeneOut to estimate a p-value for the test. Our approach maps trees into a multi-dimensional vector space and then applies support vector machines (SVMs) to measure the separation between two sets of pre-defined trees. We use a permutation test to assess the significance of the SVM separation. To demonstrate the performance of GeneOut, we applied it to the comparison of gene trees simulated within different species trees across a range of species tree depths. Applied directly to sets of simulated gene trees with large sample sizes, GeneOut was able to detect very small differences between two set of gene trees generated under different species trees. Our statistical test can also include tree reconstruction into its test framework through a variety of phylogenetic optimality criteria. When applied to DNA sequence data simulated from different sets of gene trees, results in the form of receiver operating characteristic (ROC) curves indicated that GeneOut performed well in the detection of differences between sets of trees with different distributions in a multi-dimensional space. Furthermore, it controlled false positive and false negative rates very well, indicating a high degree of accuracy. CONCLUSIONS: The non-parametric nature of our statistical test provides fast and efficient analyses, and makes it an applicable test for any scenario where evolutionary or other factors can lead to trees with different multi-dimensional distributions. The software GeneOut is freely available under the GNU public license.     

Phylogenetic signal in AFLP data sets

AFLP markers provide a potential source of phylogenetic information for molecular systematic studies. However, there are properties of restriction fragment data that limit phylogenetic interpretation of AFLPs. These are (a) possible nonindependence of fragments, (b) problems of homology assignment of fragments, (c) asymmetry in the probability of losing and gaining fragments, and (d) problems in distinguishing heterozygote from homozygote bands. In the present study, AFLP data sets of Lactuca s.l. were examined for the presence of phylogenetic signal. An indication of this signal was provided by carrying out tree length distribution skewness (g1) tests, permutation tail probability (PTP) tests, and relative apparent synapomorphy analysis (RASA). A measure of the support for internal branches in the optimal parsimony tree (MPT) was made using bootstrap, jackknife, and decay analysis. Finally, the extent of congruence in MPTs for AFLP and internal transcribed spacer (ITS)-1 data sets for the same taxa was made using the partition homogeneity test (PHT) and the Templeton test. These analytical studies suggested the presence of phylogenetic signal in the AFLP data sets, although some incongruence was found between AFLP and ITS MPTs. An extensive literature survey undertaken indicated that authors report a general congruence of AFLP and ITS tree topologies across a wide range of taxonomic groups, suggesting that the present results and conclusions have a general bearing. In these earlier studies and those for Lactuca s.l., AFLP markers have been found to be informative at somewhat lower taxonomic levels than ITS sequences. Tentative estimates are suggested for the levels of ITS sequence divergence over which AFLP profiles are likely to be phylogenetically informative.     

Treeness triangles: visualizing the loss of phylogenetic signal

It is well known that molecular data "saturates" with increasing sequence divergence (thereby losing phylogenetic information) and that in addition the accumulation of misleading information due to chance similarities or to systematic bias may accompany saturation as well. Exploratory data analysis methods that can quantify the extent of signal loss or convergence for a given data set are scarce. Such methods are needed because genomics delivers very long sequence alignments spanning substantial phylogenetic depth, where site saturation may be compounded by systematic biases or other alternative signals. Here we introduce the Treeness Triangle (TT) graph, in which signals detectable by Hadamard (spectral) analysis are summed into 3 categories--those supporting 1) external and 2) internal branches in the optimal tree, in addition to 3) the residuals (potential internal branches not present in the optimal tree). These 3 values are plotted in a standard ternary coordinate system. The approach is illustrated with simulated and real data sets, the latter from complete chloroplast genomes, where potential problems of paralogy or lateral gene acquisition can be excluded. The TT uncovers the divergence-dependent loss of phylogenetic signal as subsets of chloroplast genomes are investigated that span increasingly deeper evolutionary timescales. The rate of signal loss (or signal retention) varies with the gene and/or the method of analysis.     

A consistent phylogenetic backbone for the fungi

The kingdom of fungi provides model organisms for biotechnology, cell biology, genetics, and life sciences in general. Only when their phylogenetic relationships are stably resolved, can individual results from fungal research be integrated into a holistic picture of biology. However, and despite recent progress, many deep relationships within the fungi remain unclear. Here, we present the first phylogenomic study of an entire eukaryotic kingdom that uses a consistency criterion to strengthen phylogenetic conclusions. We reason that branches (splits) recovered with independent data and different tree reconstruction methods are likely to reflect true evolutionary relationships. Two complementary phylogenomic data sets based on 99 fungal genomes and 109 fungal expressed sequence tag (EST) sets analyzed with four different tree reconstruction methods shed light from different angles on the fungal tree of life. Eleven additional data sets address specifically the phylogenetic position of Blastocladiomycota, Ustilaginomycotina, and Dothideomycetes, respectively. The combined evidence from the resulting trees supports the deep-level stability of the fungal groups toward a comprehensive natural system of the fungi. In addition, our analysis reveals methodologically interesting aspects. Enrichment for EST encoded data-a common practice in phylogenomic analyses-introduces a strong bias toward slowly evolving and functionally correlated genes. Consequently, the generalization of phylogenomic data sets as collections of randomly selected genes cannot be taken for granted. A thorough characterization of the data to assess possible influences on the tree reconstruction should therefore become a standard in phylogenomic analyses.     

The local-clock permutation test: a simple test to compare rates of molecular evolution on phylogenetic trees

Rates of molecular evolution vary substantially between lineages, and a growing effort is directed at uncovering the causes and consequences of this variation. Comparing local-clocks (rates of molecular evolution estimated from different sets of branches of a phylogenetic tree) is a common tool in this research effort. Here, I show that a commonly used test (the Likelihood Ratio Test, LRT) will not be statistically valid for comparing local-clocks in most cases. Instead, I propose the local-clock permutation test (LCPT), a simple test that can be used to test the significance of differences between local-clocks. The LCPT could also be used to test for differences between any parameter that can be assigned to individual branches on a phylogenetic tree. Using simulated data, I show that the LCPT has good power to detect differences between local-clocks.     

Variation in modes and rates of evolution in nuclear and mitochondrial ribosomal DNA in the mushroom genus Amanita (Agaricales, Basidiomycota): phylogenetic implications

Modes and rates of molecular evolution, and congruence and combinability for phylogenetic reconstruction, of portions of the nuclear large ribosomal subunit (nLSU-rDNA) and mitochondrial small subunit (mtSSU-rDNA) genes were investigated in the mushroom genus Amanita. The AT content was higher in the mtSSU-rDNA than in the nLSU-rDNA. A transition bias in which AT substitutions were as frequent as transitions was present in the mtSSU-rDNA but not in the nLSU-rDNA. Among-sites rate variation in nucleotide substitutions at variable sites was present in the nLSU-rDNA but not in the mtSSU-rDNA. Likelihood ratio tests indicated very different models of evolution for the two molecules. A molecular clock could be rejected for both data sets. Rates of molecular evolution in the two molecules were uncoupled: faster evolutionary rates in the mtSSU-rDNA and nLSU-rDNA were not observed for the same taxa. In separate phylogenetic analyses, the nLSU-rDNA data set had higher phylogenetic resolution. The partition homogeneity test and statistical bootstrap support for branches indicated absence of conflict in the phylogenetic signal in the two data sets; however, tree topologies produced from the separate data sets were not congruent. Heterogeneity in modes and rates of evolution in the two molecules pose difficulties for a combined analysis of the two data sets: the use of equally weighted parsimony is not fully satisfactory when rate heterogeneity is present, and it is impractical to determine a model for maximum-likelihood analysis that fits simultaneously two heterogeneous data sets. Overall topologies produced from either the separated or the combined analyses using various tree reconstruction methods were identical for nearly all statistically significant branches.     

Overcoming deep roots, fast rates, and short internodes to resolve the ancient rapid radiation of eupolypod II ferns

Backbone relationships within the large eupolypod II clade, which includes nearly a third of extant fern species, have resisted elucidation by both molecular and morphological data. Earlier studies suggest that much of the phylogenetic intractability of this group is due to three factors: (i) a long root that reduces apparent levels of support in the ingroup; (ii) long ingroup branches subtended by a series of very short backbone internodes (the "ancient rapid radiation" model); and (iii) significantly heterogeneous lineage-specific rates of substitution. To resolve the eupolypod II phylogeny, with a particular emphasis on the backbone internodes, we assembled a data set of five plastid loci (atpA, atpB, matK, rbcL, and trnG-R) from a sample of 81 accessions selected to capture the deepest divergences in the clade. We then evaluated our phylogenetic hypothesis against potential confounding factors, including those induced by rooting, ancient rapid radiation, rate heterogeneity, and the Bayesian star-tree paradox artifact. While the strong support we inferred for the backbone relationships proved robust to these potential problems, their investigation revealed unexpected model-mediated impacts of outgroup composition, divergent effects of methods for countering the star-tree paradox artifact, and gave no support to concerns about the applicability of the unrooted model to data sets with heterogeneous lineage-specific rates of substitution. This study is among few to investigate these factors with empirical data, and the first to compare the performance of the two primary methods for overcoming the Bayesian star-tree paradox artifact. Among the significant phylogenetic results is the near-complete support along the eupolypod II backbone, the demonstrated paraphyly of Woodsiaceae as currently circumscribed, and the well-supported placement of the enigmatic genera Homalosorus, Diplaziopsis, and Woodsia.     

Molecular phylogenetics of the lizard genus Microlophus (squamata:tropiduridae): aligning and retrieving indel signal from nuclear introns

We use a multigene data set (the mitochondrial locus and nine nuclear gene regions) to test phylogenetic relationships in the South American "lava lizards" (genus Microlophus) and describe a strategy for aligning noncoding sequences that accounts for differences in tempo and class of mutational events. We focus on seven nuclear introns that vary in size and frequency of multibase length mutations (i.e., indels) and present a manual alignment strategy that incorporates insertions and deletions (indels) for each intron. Our method is based on mechanistic explanations of intron evolution that does not require a guide tree. We also use a progressive alignment algorithm (Probabilistic Alignment Kit; PRANK) and distinguishes insertions from deletions and avoids the "gapcost" conundrum. We describe an approach to selecting a guide tree purged of ambiguously aligned regions and use this to refine PRANK performance. We show that although manual alignment is successful in finding repeat motifs and the most obvious indels, some regions can only be subjectively aligned, and there are limits to the size and complexity of a data matrix for which this approach can be taken. PRANK alignments identified more parsimony-informative indels while simultaneously increasing nucleotide identity in conserved sequence blocks flanking the indel regions. When comparing manual and PRANK with two widely used methods (CLUSTAL, MUSCLE) for the alignment of the most length-variable intron, only PRANK recovered a tree congruent at deeper nodes with the combined data tree inferred from all nuclear gene regions. We take this concordance as an objective function of alignment quality and present a strongly supported phylogenetic hypothesis for Microlophus relationships. From this hypothesis we show that (1) a coded indel data partition derived from the PRANK alignment contributed significantly to nodal support and (2) the indel data set permitted detection of significant conflict between mitochondrial and nuclear data partitions, which we hypothesize arose from secondary contact of distantly related taxa, followed by hybridization and mtDNA introgression.