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Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting-free algorithm.

ABSTRACT: Ancestral state reconstruction is a method used to study the evolutionary trajectories of quantitative characters on phylogenies. Although efficient methods for univariate ancestral state reconstruction under a Brownian motion model have been described for at least 25 years, to date no generalization has been described to allow more complex evolutionary models, such as multivariate trait evolution, non-Brownian models, missing data, and within-species variation. Furthermore, even for simple univariate Brownian motion models, most phylogenetic comparative R packages compute ancestral states via inefficient tree rerooting and full tree traversals at each tree node, making ancestral state reconstruction extremely time-consuming for large phylogenies. Here, a computationally efficient method for fast maximum likelihood ancestral state reconstruction of continuous characters is described. The algorithm has linear complexity relative to the number of species and outperforms the fastest existing R implementations by several orders of magnitude. The described algorithm is capable of performing ancestral state reconstruction on a 1,000,000-species phylogeny in fewer than 2 s using a standard laptop, whereas the next fastest R implementation would take several days to complete. The method is generalizable to more complex evolutionary models, such as phylogenetic regression, within-species variation, non-Brownian evolutionary models, and multivariate trait evolution. Because this method enables fast repeated computations on phylogenies of virtually any size, implementation of the described algorithm can drastically alleviate the computational burden of many otherwise prohibitively time-consuming tasks requiring reconstruction of ancestral states, such as phylogenetic imputation of missing data, bootstrapping procedures, Expectation-Maximization algorithms, and Bayesian estimation. The described ancestral state reconstruction algorithm is implemented in the Rphylopars functions anc.recon and phylopars.

SUBMITTER: Goolsby EW

PROVIDER: S-EPMC5395464 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting-free algorithm.

Goolsby Eric W EW

Ecology and evolution 20170321 8

Ancestral state reconstruction is a method used to study the evolutionary trajectories of quantitative characters on phylogenies. Although efficient methods for univariate ancestral state reconstruction under a Brownian motion model have been described for at least 25 years, to date no generalization has been described to allow more complex evolutionary models, such as multivariate trait evolution, non-Brownian models, missing data, and within-species variation. Furthermore, even for simple univ ...[more]

PMID: 28428869

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Project description:BackgroundThe use of molecular genetic data in phylogenetic systematics has revolutionized this field of research in that several taxonomic groupings defined by traditional taxonomic approaches have been rejected by molecular data. The taxonomic classification of the oribatid mite group Circumdehiscentiae ("Higher Oribatida") is largely based on morphological characters and several different classification schemes, all based upon the validity of diagnostic morphological characters, have been proposed by various authors. The aims of this study were to test the appropriateness of the current taxonomic classification schemes for the Circumdehiscentiae and to trace the evolution of the main diagnostic traits (the four nymphal traits scalps, centrodorsal setae, sclerits and wrinkled cuticle plus octotaxic system and pteromorphs both in adults) on the basis of a molecular phylogenetic hypothesis by means of parsimony, likelihood and Bayesian approaches.ResultsThe molecular phylogeny based on three nuclear markers (28S rDNA, ef-1alpha, hsp82) revealed considerable discrepancies to the traditional classification of the five "circumdehiscent" subdivisions, suggesting paraphyly of the three families Scutoverticidae, Ameronothridae, Cymbaeremaeidae and also of the genus Achipteria. Ancestral state reconstructions of six common diagnostic characters and statistical evaluation of alternative phylogenetic hypotheses also partially rejected the current morphology-based classification and suggested multiple convergent evolution (both gain and loss) of some traits, after a period of rapid cladogenesis, rendering several subgroups paraphyletic.ConclusionsPhylogenetic studies revealed non-monophyly of three families and one genus as a result of a lack of adequate synapomorphic morphological characters, calling for further detailed investigations in a framework of integrative taxonomy. Character histories of six morphological traits indicate that their evolution followed a rather complex pattern of multiple independent gains (and losses). Thus, the observed pattern largely conflicts with current morphological classifications of the Circumdehiscentiae, suggesting that the current taxonomic classification schemes are not appropriate, apart from a recently proposed subdivision into 24 superfamilies.

Dataset Information

Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting-free algorithm.

Publications

Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting-free algorithm.

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