Discriminating supported and unsupported relationships in supertrees using triplets

Why should we investigate the morphological disparity of plant clades?

BACKGROUND

Disparity refers to the morphological variation in a sample of taxa, and is distinct from diversity or taxonomic richness. Diversity and disparity are fundamentally decoupled; many groups attain high levels of disparity early in their evolution, while diversity is still comparatively low. Diversity may subsequently increase even in the face of static or declining disparity by increasingly fine sub-division of morphological 'design' space (morphospace). Many animal clades reached high levels of disparity early in their evolution, but there have been few comparable studies of plant clades, despite their profound ecological and evolutionary importance. This study offers a prospective and some preliminary macroevolutionary analyses.

METHODS

Classical morphometric methods are most suitable when there is reasonable conservation of form, but lose traction where morphological differences become greater (e.g. in comparisons across higher taxa). Discrete character matrices offer one means to compare a greater diversity of forms. This study explores morphospaces derived from eight discrete data sets for major plant clades, and discusses their macroevolutionary implications.

KEY RESULTS

Most of the plant clades in this study show initial, high levels of disparity that approach or attain the maximum levels reached subsequently. These plant clades are characterized by an initial phase of evolution during which most regions of their empirical morphospaces are colonized. Angiosperms, palms, pines and ferns show remarkably little variation in disparity through time. Conifers furnish the most marked exception, appearing at relatively low disparity in the latest Carboniferous, before expanding incrementally with the radiation of successive, tightly clustered constituent sub-clades.

CONCLUSIONS

Many cladistic data sets can be repurposed for investigating the morphological disparity of plant clades through time, and offer insights that are complementary to more focused morphometric studies. The unique structural and ecological features of plants make them ideally suited to investigating intrinsic and extrinsic constraints on disparity.

Towards a Supertree of Arthropoda: A Species-Level Supertree of the Spiny, Slipper and Coral Lobsters (Decapoda: Achelata)

While supertrees have been built for many vertebrate groups (notably birds, mammals and dinosaurs), invertebrates have attracted relatively little attention. The paucity of supertrees of arthropods is particularly surprising given their economic and ecological importance, as well as their overwhelming contribution to biodiversity. The absence of comprehensive archives of machine-readable source trees, coupled with the need for software implementing repeatable protocols for managing them, has undoubtedly impeded progress. Here we present a supertree of Achelata (spiny, slipper and coral lobsters) as a proof of concept, constructed using new supertree specific software (the Supertree Toolkit; STK) and following a published protocol. We also introduce a new resource for archiving and managing published source trees. Our supertree of Achelata is synthesised from morphological and molecular source trees, and represents the most complete species-level tree of the group to date. Our findings are consistent with recent taxonomic treatments, confirming the validity of just two families: Palinuridae and Scyllaridae; Synaxidae were resolved within Palinuridae. Monophyletic Silentes and Stridentes lineages are recovered within Palinuridae, and all sub-families within Scyllaridae are found to be monophyletic with the exception of Ibacinae. We demonstrate the feasibility of building larger supertrees of arthropods, with the ultimate objective of building a complete species-level phylogeny for the entire phylum using a divide and conquer strategy.

COSPEDTree: COuplet Supertree by Equivalence Partitioning of Taxa Set and DAG Formation

From a set of phylogenetic trees with overlapping taxa set, a supertree exhibits evolutionary relationships among all input taxa. The key is to resolve the contradictory relationships with respect to input trees, between individual taxa subsets. Formulation of this NP hard problem employs either local search heuristics to reduce tree search space, or resolves the conflicts with respect to fixed or varying size subtree level decompositions. Different approximation techniques produce supertrees with considerable performance variations. Moreover, the majority of the algorithms involve high computational complexity, thus not suitable for use on large biological data sets. Current study presents COSPEDTree, a novel method for supertree construction. The technique resolves source tree conflicts by analyzing couplet (taxa pair) relationships for each source trees. Subsequently, individual taxa pairs are resolved with a single relation. To prioritize the consensus relations among individual taxa pairs for resolving them, greedy scoring is employed to assign higher score values for the consensus relations among a taxa pair. Selected set of relations resolving individual taxa pairs is subsequently used to construct a directed acyclic graph (DAG). Vertices of DAG represents a taxa subset inferred from the same speciation event. Thus, COSPEDTree can generate non-binary supertrees as well. Depth first traversal on this DAG yields final supertree. According to the performance metrics on branch dissimilarities (such as FP, FN and RF), COSPEDTree produces mostly conservative, well resolved supertrees. Specifically, RF metrics are mostly lower compared to the reference approaches, and FP values are lower apart from only strictly conservative (or veto) approaches. COSPEDTree has worst case time and space complexities of cubic and quadratic order, respectively, better or comparable to the reference approaches. Such high performance and low computational costs enable COSPEDTree to be applied on large scale biological data sets.

Polynomial supertree methods revisited

Supertree methods allow to reconstruct large phylogenetic trees by combining smaller trees with overlapping leaf sets into one, more comprehensive supertree. The most commonly used supertree method, matrix representation with parsimony (MRP), produces accurate supertrees but is rather slow due to the underlying hard optimization problem. In this paper, we present an extensive simulation study comparing the performance of MRP and the polynomial supertree methods MinCut Supertree, Modified MinCut Supertree, Build-with-distances, PhySIC, PhySIC_IST, and super distance matrix. We consider both quality and resolution of the reconstructed supertrees. Our findings illustrate the tradeoff between accuracy and running time in supertree construction, as well as the pros and cons of voting- and veto-based supertree approaches. Based on our results, we make some general suggestions for supertree methods yet to come.

SuperTriplets: a triplet-based supertree approach to phylogenomics

MOTIVATION

Phylogenetic tree-building methods use molecular data to represent the evolutionary history of genes and taxa. A recurrent problem is to reconcile the various phylogenies built from different genomic sequences into a single one. This task is generally conducted by a two-step approach whereby a binary representation of the initial trees is first inferred and then a maximum parsimony (MP) analysis is performed on it. This binary representation uses a decomposition of all source trees that is usually based on clades, but that can also be based on triplets or quartets. The relative performances of these representations have been discussed but are difficult to assess since both are limited to relatively small datasets.

RESULTS

This article focuses on the triplet-based representation of source trees. We first recall how, using this representation, the parsimony analysis is related to the median tree notion. We then introduce SuperTriplets, a new algorithm that is specially designed to optimize this alternative formulation of the MP criterion. The method avoids several practical limitations of the triplet-based binary matrix representation, making it useful to deal with large datasets. When the correct resolution of every triplet appears more often than the incorrect ones in source trees, SuperTriplets warrants to reconstruct the correct phylogeny. Both simulations and a case study on mammalian phylogenomics confirm the advantages of this approach. In both cases, SuperTriplets tends to propose less resolved but more reliable supertrees than those inferred using M(atrix) Representation with Parsimony.

AVAILABILITY

Online and JAVA standalone versions of SuperTriplets are available at http://www.supertriplets.univ-montp2.fr/.

PhySIC_IST: cleaning source trees to infer more informative supertrees

Background

Supertree methods combine phylogenies with overlapping sets of taxa into a larger one. Topological conflicts frequently arise among source trees for methodological or biological reasons, such as long branch attraction, lateral gene transfers, gene duplication/loss or deep gene coalescence. When topological conflicts occur among source trees, liberal methods infer supertrees containing the most frequent alternative, while veto methods infer supertrees not contradicting any source tree, i.e. discard all conflicting resolutions. When the source trees host a significant number of topological conflicts or have a small taxon overlap, supertree methods of both kinds can propose poorly resolved, hence uninformative, supertrees.

Results

To overcome this problem, we propose to infer non-plenary supertrees, i.e. supertrees that do not necessarily contain all the taxa present in the source trees, discarding those whose position greatly differs among source trees or for which insufficient information is provided. We detail a variant of the PhySIC veto method called PhySIC_IST that can infer non-plenary supertrees. PhySIC_IST aims at inferring supertrees that satisfy the same appealing theoretical properties as with PhySIC, while being as informative as possible under this constraint. The informativeness of a supertree is estimated using a variation of the CIC (Cladistic Information Content) criterion, that takes into account both the presence of multifurcations and the absence of some taxa. Additionally, we propose a statistical preprocessing step called STC (Source Trees Correction) to correct the source trees prior to the supertree inference. STC is a liberal step that removes the parts of each source tree that significantly conflict with other source trees. Combining STC with a veto method allows an explicit trade-off between veto and liberal approaches, tuned by a single parameter.

Performing large-scale simulations, we observe that STC+PhySIC_IST infers much more informative supertrees than PhySIC, while preserving low type I error compared to the well-known MRP method. Two biological case studies on animals confirm that the STC preprocess successfully detects anomalies in the source trees while STC+PhySIC_IST provides well-resolved supertrees agreeing with current knowledge in systematics.

Conclusion

The paper introduces and tests two new methodologies, PhySIC_IST and STC, that demonstrate the interest in inferring non-plenary supertrees as well as preprocessing the source trees. An implementation of the methods is available at: .

Majority-rule supertrees

Most supertree methods proposed to date are essentially ad hoc, rather than designed with particular properties in mind. Although the supertree problem remains difficult, one promising avenue is to develop from better understood consensus methods to the more general supertree setting. Here, we generalize the widely used majority-rule consensus method to the supertree setting. The majority-rule consensus tree is the strict consensus of the median trees under the symmetric-difference metric, so we can generalize the consensus method by generalizing this metric to trees with differing leaf sets. There are two different natural generalizations, based on pruning or grafting leaves to produce comparable trees, and these two generalizations produce two different, but related, majority-rule supertree methods.

Increasing data transparency and estimating phylogenetic uncertainty in supertrees: Approaches using nonparametric bootstrapping

The estimation of ever larger phylogenies requires consideration of alternative inference strategies, including divide-and-conquer approaches that decompose the global inference problem to a set of smaller, more manageable component problems. A prominent locus of research in this area is the development of supertree methods, which estimate a composite tree by combining a set of partially overlapping component topologies. Although promising, the use of component tree topologies as the primary data dissociates supertrees from complexities within the underling character data and complicates the evaluation of phylogenetic uncertainty. We address these issues by exploring three approaches that variously incorporate nonparametric bootstrapping into a common supertree estimation algorithm (matrix representation with parsimony, although any algorithm might be used), including bootstrap-weighting, source-tree bootstrapping, and hierarchical bootstrapping. We illustrate these procedures by means of hypothetical and empirical examples. Our preliminary experiments suggest that these methods have the potential to improve the correspondence of supertree estimates to those derived from simultaneous analysis of the combined data and to allow uncertainty in supertree topologies to be quantified. The ability to increase the transparency of supertrees to the underlying character data has several practical implications and sheds new light on an old debate. These methods have been implemented in the freely available program, tREeBOOT.

A higher-level MRP supertree of placental mammals

BACKGROUND

The higher-level phylogeny of placental mammals has long been a phylogenetic Gordian knot, with disagreement about both the precise contents of, and relationships between, the extant orders. A recent MRP supertree that favoured 'outdated' hypotheses (notably, monophyly of both Artiodactyla and Lipotyphla) has been heavily criticised for including low-quality and redundant data. We apply a stringent data selection protocol designed to minimise these problems to a much-expanded data set of morphological, molecular and combined source trees, to produce a supertree that includes every family of extant placental mammals.

RESULTS

The supertree is well-resolved and supports both polyphyly of Lipotyphla and paraphyly of Artiodactyla with respect to Cetacea. The existence of four 'superorders'--Afrotheria, Xenarthra, Laurasiatheria and Euarchontoglires--is also supported. The topology is highly congruent with recent (molecular) phylogenetic analyses of placental mammals, but is considerably more comprehensive, being the first phylogeny to include all 113 extant families without making a priori assumptions of suprafamilial monophyly. Subsidiary analyses reveal that the data selection protocol played a key role in the major changes relative to a previously published higher-level supertree of placentals.

CONCLUSION

The supertree should provide a useful framework for hypothesis testing in phylogenetic comparative biology, and supports the idea that biogeography has played a crucial role in the evolution of placental mammals. Our results demonstrate the importance of minimising poor and redundant data when constructing supertrees.