Inference of Horizontal Genetic Transfer from Molecular Data: An Approach Using the Bootstrap

Inconsistencies in taxonomic relationships implicit in different sets of nucleic acid sequences potentially result from horizontal transfer of genetic material between genomes. A nonparametric method is proposed to determine whether such inconsistencies are statistically significant. A similarity coefficient is calculated from ranked pairwise identities and evaluated against a distribution of similarity coefficients generated from resampled data. Subsequent analyses of partial data sets, obtained by the elimination of individual taxa, identify particular taxa to which the significance may be attributed, and can sometimes help in distinguishing horizontal genetic transfer from inconsistencies due to convergent evolution or variation in evolutionary rate. The method was successfully applied to data sets that were not found to be significantly different with existing methods that use comparisons of phylogenetic trees. The new statistical framework is also applicable to the inference of horizontal transfer from restriction fragment length polymorphism distributions and protein sequences.     

The division of the major songbird radiation into Passerida and 'core Corvoidea' (Aves: Passeriformes) — the species tree vs. gene trees

The knowledge of evolutionary relationships among oscine songbirds has been largely improved in recent years by molecular phylogenetic studies. However, current knowledge is still largely based on sequence data from a limited number of loci. In this study, we re-evaluate relationships among basal lineages within the 'core Corvoidea' and Passerida radiations, by adding additional loci to previously published data. The trees obtained from the individual genes suggest incongruent topologies. Especially the positions of Callaeatidae (wattlebirds), Cnemophilidae (satinbirds) and Melanocharitidae (longbills and berrypeckers) vary among the trees, but RAG-1 is the only gene that unambiguously suggested a 'core Corvoidea' affinity for these taxa. Analyses of various combined data sets show that the phylogenetic positions for Callaeatidae, Cnemophilidae and Melanocharitidae largely depend on which genes that have been combined. As the RAG-1 gene has contributed to a majority of the phylogenetic information in previous studies, it has deeply influenced previous molecular affinities of these taxa. Based on the current data, we found a reasonable support for a Passerida affinity of Callaeatidae and Cnemophilidae, contrary to previous molecular studies. The position of Melanocharitidae is more unstable but a basal position among Passerida is congruent with a deletion observed in the glyceraldehyde-3-phosphodehydrogenase (GAPDH) loci. Molecular clock estimations conducted on the combined data sets were generally found to be similar, but for some divergences significant differences were found. These results illustrate the potential problem of phylogenies predominantly based on characters from one or a few loci, and exemplify the importance of well-supported phylogenies before reasonable time estimates of passerine divergences could be achieved.     

Ice ages leave genetic diversity ‘hotspots’ in Europe but not in Eastern North America

After the last glacial cycle, temperate European trees migrated northward, experiencing genetic bottlenecks and founder effects, which left high haplotype endemism in southern populations and clines in genetic diversity northward. These patterns are thought to be ubiquitous across temperate forests, and are therefore used to anticipate the potential genetic consequences of future warming. We compared existing and new phylogeographic data sets (chloroplast DNA) from 14 woody taxa in Eastern North America (ENA) to data sets from 21 ecologically similar European species to test for common impacts of Quaternary climate swings on genetic diversity across diverse taxa and between continents. Unlike their European counterparts, ENA taxa do not share common southern centres of haplotype endemism and they generally maintain high genetic diversity even at their northern range limits. Differences between the genetic impacts of Quaternary climate cycles across continents suggest refined lessons for managing genetic diversity in today's warming world.     

Gene trees and species trees – mutual influences and interdependences of population genetics and systematics

Both population genetics and systematics are core disciplines of evolutionary biology. While systematics deals with genealogical relationships among taxa, population genetics has mainly been based on allele frequencies and the distribution of genetic variants whose genealogical relations could for a long time, due mainly to methodological constraints, not be inferred. The advent of mitochondrial DNA analyses and modern sequencing techniques in the 1970s revolutionized evolutionary genetic studies and gave rise to molecular phylogenetics. In the wake of this new development systematic approaches and principles were incorporated into intraspecific studies at the population level, e.g. the concept of monophyly which is used to delineate evolutionarily significant units in conservation biology. A new discipline combining phylogenetic analyses of genetic lineages with their geographic distribution ('phylogeography') was introduced as an explicit synthesis of population genetics and systematics. On the other hand, it has increasingly become obvious that discordances between gene trees and species trees not only result from spurious data sets or methodological flaws in phylogenetic analyses, but that they often reflect real population genetic processes such as lineage sorting or hybridization. These processes have to be taken into account when evaluating the reliability of gene trees to avoid wrong phylogenetic conclusions. The present review focuses on the phenomenon of non-phylogenetic sorting of ancestral polymorphisms, its probability and its consequences for molecular systematics.     

STBase: One Million Species Trees for Comparative Biology

Comprehensively sampled phylogenetic trees provide the most compelling foundations for strong inferences in comparative evolutionary biology. Mismatches are common, however, between the taxa for which comparative data are available and the taxa sampled by published phylogenetic analyses. Moreover, many published phylogenies are gene trees, which cannot always be adapted immediately for species level comparisons because of discordance, gene duplication, and other confounding biological processes. A new database, STBase, lets comparative biologists quickly retrieve species level phylogenetic hypotheses in response to a query list of species names. The database consists of 1 million single- and multi-locus data sets, each with a confidence set of 1000 putative species trees, computed from GenBank sequence data for 413,000 eukaryotic taxa. Two bodies of theoretical work are leveraged to aid in the assembly of multi-locus concatenated data sets for species tree construction. First, multiply labeled gene trees are pruned to conflict-free singly-labeled species-level trees that can be combined between loci. Second, impacts of missing data in multi-locus data sets are ameliorated by assembling only decisive data sets. Data sets overlapping with the user’s query are ranked using a scheme that depends on user-provided weights for tree quality and for taxonomic overlap of the tree with the query. Retrieval times are independent of the size of the database, typically a few seconds. Tree quality is assessed by a real-time evaluation of bootstrap support on just the overlapping subtree. Associated sequence alignments, tree files and metadata can be downloaded for subsequent analysis. STBase provides a tool for comparative biologists interested in exploiting the most relevant sequence data available for the taxa of interest. It may also serve as a prototype for future species tree oriented databases and as a resource for assembly of larger species phylogenies from precomputed trees.     

A phylogenomic perspective on diversity,hybridization and evolutionary affinities in the stickleback genus Pungitius

Hybridization and convergent evolution are phenomena of broad interest in evolutionary biology, but their occurrence poses challenges for reconstructing evolutionary affinities among affected taxa. Sticklebacks in the genus Pungitius are a case in point: evolutionary relationships and taxonomic validity of different species and populations in this circumpolarly distributed species complex remain contentious due to convergent evolution of traits regarded as diagnostic in their taxonomy, and possibly also due to frequent hybridization among taxa. To clarify the evolutionary relationships among different Pungitius species and populations globally, as well as to study the prevalence and extent of introgression among recognized species, genomic data sets of both reference genome‐anchored single nucleotide polymorphisms and de novo assembled RAD‐tag loci were constructed with RAD‐seq data. Both data sets yielded topologically identical and well‐supported species trees. Incongruence between nuclear and mitochondrial DNA‐based trees was found and suggested possibly frequent hybridization and mitogenome capture during the evolution of Pungitius sticklebacks. Further analyses revealed evidence for frequent nuclear genetic introgression among Pungitius species, although the estimated proportions of autosomal introgression were low. Apart from providing evidence for frequent hybridization, the results challenge earlier mitochondrial and morphology‐based hypotheses regarding the number of species and their affinities in this genus: at least seven extant species can be recognized on the basis of genetic data. The results also shed new light on the biogeographical history of the Pungitius‐complex, including suggestion of several trans‐Arctic invasions of Europe from the Northern Pacific. The well‐resolved phylogeny should facilitate the utility of this genus as a model system for future comparative evolutionary studies.     

Exceptional among-lineage variation in diversification rates during the radiation of Australia's most diverse vertebrate clade

The disparity in species richness among groups of organisms is one of the most pervasive features of life on earth. A number of studies have addressed this pattern across higher taxa (e.g. 'beetles'), but we know much less about the generality and causal basis of the variation in diversity within evolutionary radiations at lower taxonomic scales. Here, we address the causes of variation in species richness among major lineages of Australia's most diverse vertebrate radiation, a clade of at least 232 species of scincid lizards. We use new mitochondrial and nuclear intron DNA sequences to test the extent of diversification rate variation in this group. We present an improved likelihood-based method for estimating per-lineage diversification rates from combined phylogenetic and taxonomic (species richness) data, and use the method in a hypothesis-testing framework to localize diversification rate shifts on phylogenetic trees. We soundly reject homogeneity of diversification rates among members of this radiation, and find evidence for a dramatic rate increase in the common ancestor of the genera Ctenotus and Lerista. Our results suggest that the evolution of traits associated with climate tolerance may have had a role in shaping patterns of diversity in this group.     

Phylogenetic analysis of RAD‐seq data: examining the influence of gene genealogy conflict on analysis of concatenated data

One of the major issues in phylogenetic analysis is that gene genealogies from different gene regions may not reflect the true species tree or history of speciation. This has led to considerable debate about whether concatenation of loci is the best approach for phylogenetic analysis. The application of Next‐generation sequencing techniques such as RAD‐seq generates thousands of relatively short sequence reads from across the genomes of the sampled taxa. These data sets are typically concatenated for phylogenetic analysis leading to data sets that contain millions of base pairs per taxon. The influence of gene region conflict among so many loci in determining the phylogenetic relationships among taxa is unclear. We simulated RAD‐seq data by sampling 100 and 500 base pairs from alignments of over 6000 coding regions that each produce one of three highly supported alternative phylogenies of seven species of Drosophila. We conducted phylogenetic analyses on different sets of these regions to vary the sampling of loci with alternative gene trees to examine the effect on detecting the species tree. Irrespective of sequence length sampled per region and which subset of regions was used, phylogenetic analyses of the concatenated data always recovered the species tree. The results suggest that concatenated alignments of Next‐generation data that consist of many short sequences are robust to gene tree/species tree conflict when the goal is to determine the phylogenetic relationships among taxa.     

A genetic algorithm for maximum-likelihood phylogeny inference using nucleotide sequence data

Phylogeny reconstruction is a difficult computational problem, because the number of possible solutions increases with the number of included taxa. For example, for only 14 taxa, there are more than seven trillion possible unrooted phylogenetic trees. For this reason, phylogenetic inference methods commonly use clustering algorithms (e.g., the neighbor-joining method) or heuristic search strategies to minimize the amount of time spent evaluating nonoptimal trees. Even heuristic searches can be painfully slow, especially when computationally intensive optimality criteria such as maximum likelihood are used. I describe here a different approach to heuristic searching (using a genetic algorithm) that can tremendously reduce the time required for maximum-likelihood phylogenetic inference, especially for data sets involving large numbers of taxa. Genetic algorithms are simulations of natural selection in which individuals are encoded solutions to the problem of interest. Here, labeled phylogenetic trees are the individuals, and differential reproduction is effected by allowing the number of offspring produced by each individual to be proportional to that individual's rank likelihood score. Natural selection increases the average likelihood in the evolving population of phylogenetic trees, and the genetic algorithm is allowed to proceed until the likelihood of the best individual ceases to improve over time. An example is presented involving rbcL sequence data for 55 taxa of green plants. The genetic algorithm described here required only 6% of the computational effort required by a conventional heuristic search using tree bisection/reconnection (TBR) branch swapping to obtain the same maximum-likelihood topology.      

NULL MODELS FOR THE NUMBER OF EVOLUTIONARY STEPS IN A CHARACTER ON A PHYLOGENETIC TREE

Random trees and random characters can be used in null models for testing phylogenetic hypothesis. We consider three interpretations of random trees: first, that trees are selected from the set of all possible trees with equal probability; second, that trees are formed by random speciation or coalescence (equivalent); and third, that trees are formed by a series of random partitions of the taxa. We consider two interpretations of random characters: first, that the number of taxa with each state is held constant, but the states are randomly reshuffled among the taxa; and second, that the probability each taxon is assigned a particular state is constant from one taxon to the next. Under null models representing various combinations of randomizations of trees and characters, exact recursion equations are given to calculate the probability distribution of the number of character state changes required by a phylogenetic tree. Possible applications of these probability distributions are discussed. They can be used, for example, to test for a panmictic population structure within a species or to test phylogenetic inertia in a character's evolution. Whether and how a null model incorporates tree randomness makes little difference to the probability distribution in many but not all circumstances. The null model's sense of character randomness appears more critical. The difficult issue of choosing a null model is discussed.     

A preliminary classification of evolutionary radiations

Rapid increases in taxonomic diversity are generally described as adaptive or evolutionary radiations. Such radiations differ widely in the rate and extent of morphologic innovation, taxonomic diversification and phylogenetic breadth, suggesting that several patterns, and likely processes, are involved. At least four distinct patterns of evolutionary radiation can be identified: novelty events, which generate new morphological complexity (altering the body plan of the group under consideration) but not necessarily with the associated production of many lower taxa; broad diversification events involving many independent lineages that undergo diversification, generate many new species and are driven by new ecological opportunities; economic radiations of a limited group of ecologically (but not necessarily phylogenetically) related clades exploiting a limited new ecologic opportunity; and adaptive radiations that may occur at any taxonomic level, but involve a rapid increase in diversity within a single clade, including “true”; adaptive radiations. Many events produce simple diversity increases with no corresponding increase in genetic/developmental/morphological/behavioral sophistication, but the most evolutionarily interesting events add new levels of complexity.     

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, evolutionary process, and rate

A recent advance in the phylogenetic comparative analysis of continuous traits has been explicit, model-based measurement of "phylogenetic signal" in data sets composed of observations collected from species related by a phylogenetic tree. Phylogenetic signal is a measure of the statistical dependence among species' trait values due to their phylogenetic relationships. Although phylogenetic signal is a measure of pattern (statistical dependence), there has nonetheless been a widespread propensity in the literature to attribute this pattern to aspects of the evolutionary process or rate. This may be due, in part, to the perception that high evolutionary rate necessarily results in low phylogenetic signal; and, conversely, that low evolutionary rate or stabilizing selection results in high phylogenetic signal (due to the resulting high resemblance between related species). In this study, we use individual-based numerical simulations on stochastic phylogenetic trees to clarify the relationship between phylogenetic signal, rate, and evolutionary process. Under the simplest model for quantitative trait evolution, homogeneous rate genetic drift, there is no relation between evolutionary rate and phylogenetic signal. For other circumstances, such as functional constraint, fluctuating selection, niche conservatism, and evolutionary heterogeneity, the relationship between process, rate, and phylogenetic signal is complex. For these reasons, we recommend against interpretations of evolutionary process or rate based on estimates of phylogenetic signal.     

Lower Statistical Support with Larger Data Sets: Insights from the Ochrophyta Radiation

It is commonly assumed that increasing the number of characters has the potential to resolve evolutionary radiations. Here, we studied photosynthetic stramenopiles (Ochrophyta) using alignments of heterogeneous origin mitochondrion, plastid, and nucleus. Surprisingly while statistical support for the relationships between the six major Ochrophyta lineages increases when comparing the mitochondrion (6,762 sites) and plastid (21,692 sites) trees, it decreases in the nuclear (209,105 sites) tree. Statistical support is not simply related to the data set size but also to the quantity of phylogenetic signal available at each position and our ability to extract it. Here, we show that this ability for current phylogenetic methods is limited, because conflicting results were obtained when varying taxon sampling. Even though the use of a better fitting model improved signal extraction and reduced the observed conflicts, the plastid data set provided higher statistical support for the ochrophyte radiation than the larger nucleus data set. We propose that the higher support observed in the plastid tree is due to an acceleration of the evolutionary rate in one short deep internal branch, implying that more phylogenetic signal per position is available to resolve the Ochrophyta radiation in the plastid than in the nuclear data set. Our work therefore suggests that, in order to resolve radiations, beyond the obvious use of data sets with more positions, we need to continue developing models of sequence evolution that better extract the phylogenetic signal and design methods to search for genes/characters that contain more signal specifically for short internal branches.     

A mitochondrial-DNA-based phylogeny for some evolutionary-genetic model species of Colias butterflies (Lepidoptera, Pieridae)

We study the phylogenetic relationships among some North American Colias ("sulfur") butterflies, using mitochondrial gene sequences (ribosomal RNA, cytochrome oxidase I+II) totaling about 20% of the mitochondrial genome. We find that (1) the lowland species complex shows a branching order different from earlier views; (2) several montane and northern taxa may be more distinct than in earlier views; (3) one morphologically conservative Holarctic assemblage, C. hecla, is differentiated at the molecular-genetic level into at least three taxa which occupy distinct positions in the phylogeny and are sisters to diverse other taxa. These conclusions, constituting phylogenetic hypotheses, are supported by parsimony, maximum-likelihood, and Bayesian reconstruction algorithms. They are tested formally, by interior branch tests and paired-site tests, against alternative hypotheses derived from conventional species and subspecies naming combinations. In all cases our hypotheses are supported by these tests and the conventional alternatives are rejected. The "barcoding" subset of cytochrome oxidase I sequence identifies only some of the taxa supported by our full data set. Comparison of genetic divergence values among Colias taxa with those among related Pierid butterflies suggests that species radiations within Colias are comparatively younger. This emerging Colias phylogeny facilitates comparisons of genetic polymorphism and other adaptive mechanisms among taxa, thereby connecting micro- and macro-evolutionary processes.     

Escaping from the Felsenstein Zone by Detecting Long Branches in Phylogenetic Data

Long branches in a true phylogeny tend to disrupt hierarchical character covariation (phylogenetic signal) in the distribution of traits among organisms. The distortion of hierarchical structure in character-state matrices can lead to errors in the estimation of phylogenetic relationships and inconsistency of methods of phylogenetic inference. Examination of trees distorted by long-branch attraction will not reveal the identities of problematic taxa, in part because the distortion can mask long branches by reducing inferred branch lengths and through errors in branching order. Here we present a simple method for the detection of taxa whose placement in evolutionary trees is made difficult by the effects of long-branch attraction. The method is an extension of a tree-independent conceptual framework of phylogenetic data exploration (RASA). Taxa that are likely to attract are revealed because long branches leave distinct footprints in the distribution of character states among taxa, and these traces can be directly observed in the error structure of the RASA regression. Problematic taxa are identified using a new diagnostic plot called the taxon variance plot, in which the apparent cladistic and phenetic variances contributed by individual taxa are compared. The procedure for identifying long edges employs algorithms solved in polynomial time and can be applied to morphological, molecular, and mixed characters. The efficacy of the method is demonstrated using simulated evolution and empirical evidence of long branches in a set of recently published sequences. We show that the accuracy of evolutionary trees can be improved by detecting and combating the potentially misleading influences of long-branch taxa.     

How much can cladistics tell us about early hominid relationships?

Although cladistic analysis has been used to compare hypotheses of relationships among early hominids, the outcomes of different studies have depended entirely on the assumptions made by different investigators. Problems include the close genetic relationship of early hominid taxa, small fossil sample sizes, possible correlations among characters, and a lack of understanding about the evolutionary factors affecting characters. This study investigates the interaction of some of these problems affecting early hominid phylogenetics. Monte Carlo simulations of character state evolution in closely related taxa demonstrate that the sample sizes and close genetic relationships of early hominids do not permit cladistic analyses to obtain unequivocal results. Even with unrealistically good assumptions about the evolutionary dynamics affecting characters, the probability of the most parsimonious hypothesis being true is unacceptably small. In the face of these problems, even phylogenetic statements that are supported by a strong consensus of cladistic studies may nevertheless be in error, and such errors are likely to confound the placement of new specimens and taxa. Advancement in our knowledge of hominid phylogeny can depend only on a fuller understanding of the natural history and evolutionary dynamics of traits.     

Phylogenetic analysis and intraspecific variation: performance of parsimony,likelihood, and distance methods

Intraspecific variation is abundant in all types of systematic characters but is rarely addressed in simulation studies of phylogenetic method performance. We compared the accuracy of 15 phylogenetic methods using simulations to (1) determine the most accurate method(s) for analyzing polymorphic data (under simplified conditions) and (2) test if generalizations about the performance of phylogenetic methods based on previous simulations of fixed (nonpolymorphic) characters are robust to a very different evolutionary model that explicitly includes intraspecific variation. Simulated data sets consisted of allele frequencies that evolved by genetic drift. The phylogenetic methods included eight parsimony coding methods, continuous maximum likelihood, and three distance methods (UPGMA, neighbor joining, and Fitch-Margoliash) applied to two genetic distance measures (Nei's and the modified Cavalli-Sforza and Edwards chord distance). Two sets of simulations were performed. The first examined the effects of different branch lengths, sample sizes (individuals sampled per species), numbers of characters, and numbers of alleles per locus in the eight-taxon case. The second examined more extensively the effects of branch length in the four-taxon, two-allele case. Overall, the most accurate methods were likelihood, the additive distance methods (neighbor joining and Fitch-Margoliash), and the frequency parsimony method. Despite the use of a very different evolutionary model in the present article, many of the results are similar to those from simulations of fixed characters. Similarities include the presence of the "Felsenstein zone," where methods often fail, which suggests that long-branch attraction may occur among closely related species through genetic drift. Differences between the results of fixed and polymorphic data simulations include the following: (1) UPGMA is as accurate or more accurate than nonfrequency parsimony methods across nearly all combinations of branch lengths, and (2) likelihood and the additive distance methods are not positively misled under any combination of branch lengths tested (even when the assumptions of the methods are violated and few characters are sampled). We found that sample size is an important determinant of accuracy and affects the relative success of methods (i.e., distance and likelihood methods outperform parsimony at small sample sizes). Attempts to generalize about the behavior of phylogenetic methods should consider the extreme examples offered by fixed-mutation models of DNA sequence data and genetic-drift models of allele frequencies.     

Genetic algorithm for large-scale maximum parsimony phylogenetic analysis of proteins

Inferring phylogeny is a difficult computational problem. For example, for only 13 taxa, there are more then 13 billion possible unrooted phylogenetic trees. Heuristics are necessary to minimize the time spent evaluating non-optimal trees. We describe here an approach for heuristic searching, using a genetic algorithm, that can reduce the time required for weighted maximum parsimony phylogenetic inference, especially for data sets involving a large number of taxa. It is the first implementation of a weighted maximum parsimony criterion using amino acid sequences. To validate the weighted criterion, we used an artificial data set and compared it to a number of other phylogenetic methods. Genetic algorithms mimic the natural selection's ability to solve complex problems. We have identified several parameters affecting the genetic algorithm. Methods were developed to validate these parameters, ensuring optimal performance. This approach allows the construction of phylogenetic trees with over 200 taxa in practical time on a regular PC.