Supertrees join the mainstream of phylogenetics

School of Biological and Chemical Sciences, Queen Mary, University of London, Mile End Road, London E1 4NS, UK.
Trends in Ecology & Evolution (Impact Factor: 16.2). 12/2008; 24(1):1-3. DOI: 10.1016/j.tree.2008.08.006
Source: PubMed


Supertree methods are fairly widely used to build comprehensive phylogenies for particular groups, but concerns remain over the adequacy of existing approaches. Steel and Rodrigo recently introduced a statistical model of incongruence between trees, allowing maximum-likelihood supertree inference. This approach to supertree construction will enable hypothesis-testing and model-choice methods that are now routine in sequence phylogenetics to be applied in this setting, and might form an important part of future phylogenetic inference from genomic data.

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Available from: James A Cotton, Apr 19, 2015
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    • "Supertree approaches are appealing in that they only require source trees to share some (but not all) taxa. One can immediately see its utility, particularly with large, disparate datasets of extinct and extant taxa (Cotton and Wilkinson, 2009). This approach may elevate the incorporation of multiple lines of ecological and historical evidence into a resolved phylogeny that, in turn, provides a baseline for hypothesis testing. "
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    ABSTRACT: Species are the currency of biodiversity and an accurate recognition of their status is a scientific necessity, particularly given the onset of the Anthropocene (the most recent biodiversity crisis). Yet, concept-based species approaches are contentious whereas those more deterministic work against the fluidity of speciation itself. This conceptual gap can be bridged through a comprehensive assessment of the nine subspecies comprising the historically enigmatic Western Rattlesnake (Crotalus viridis) complex, one that employs three disparate datasets. First, mitochondrial DNA (mtDNA) sequence data were used to derive a Bayesian phylogenetic hypothesis that revealed two well- supported lineages, each with subspecies as distinct clades. Second, morphological data relating to head shape were analyzed using Geometric Morphometric (GM) methodology to again reveal two distinct lineages, each composed of subspecies that differ significantly in shape, yet with confounding factors that obscure evolutionary relationships. Finally, GIS-based macroecological variables gathered from museum specimens again demonstrated significant subspecific niches, suggesting the potential for ecological speciation within the complex. The three datasets (molecular, morphological, and ecological) were coalesced using supertree methodology to derive a single hypothesis that supported two distinct lineages but with obscured subspecific relationships. They were also utilized in crosshair classification tests that quantified ‘historical’ and ‘recent’ non-exchangeability among lineages and subspecies (i.e., if these entities were distinct amongst themselves and worthy of taxonomic recognition). In this regard, sufficient genetic, ecological and morphological non-exchangeability exists between lineages and among subspecies to warrant species designations for six II of 9 Western Rattlesnake subspecies, with the remaining three retained at subspecific status. These efforts thus represent a comprehensive and contemporary perspective of Western Rattlesnake biodiversity, and shed light on a group that has proven elusive across two centuries of scientific inquiry.
    05/2012, Degree: Ph.D., Supervisor: Dr. Marlis Douglas, Dr. Michael Douglas
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    ABSTRACT: The Robinson-Foulds (RF) distance is by far the most widely used measure of dissimilarity between trees. Although the distribution of these distances has been investigated for twenty years, an algorithm that is explicitly polynomial time has yet to be described for computing this distribution (which is also the dis- tribution of trees around a given tree under the popular Robinson-Foulds metric). In this paper we derive a polynomial-time algorithm for this distribution. We show how the distribution can be approximated by a Poisson distribution determined by the proportion of leaves that lie in ‘cherries’ of the given tree. We also describe how our results can be used to derive normalization constants that are required in a recently-proposed maximum likelihood approach to supertree construction.
    IEEE/ACM Transactions on Computational Biology and Bioinformatics 07/2009; 6(3). DOI:10.1109/TCBB.2009.32 · 1.44 Impact Factor
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