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Greedy selection of species for ancestral state reconstruction on phylogenies: elimination is better than insertion.

ABSTRACT: Accurate reconstruction of ancestral character states on a phylogeny is crucial in many genomics studies. We study how to select species to achieve the best reconstruction of ancestral character states on a phylogeny. We first show that the marginal maximum likelihood has the monotonicity property that more taxa give better reconstruction, but the Fitch method does not have it even on an ultrametric phylogeny. We further validate a greedy approach for species selection using simulation. The validation tests indicate that backward greedy selection outperforms forward greedy selection. In addition, by applying our selection strategy, we obtain a set of the ten most informative species for the reconstruction of the genomic sequence of the so-called boreoeutherian ancestor of placental mammals. This study has broad relevance in comparative genomics and paleogenomics since limited research resources do not allow researchers to sequence the large number of descendant species required to reconstruct an ancestral sequence.

SUBMITTER: Li G

PROVIDER: S-EPMC2816206 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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Greedy selection of species for ancestral state reconstruction on phylogenies: elimination is better than insertion.

Li Guoliang G Ma Jian J Zhang Louxin L

PloS one 20100204 2

Accurate reconstruction of ancestral character states on a phylogeny is crucial in many genomics studies. We study how to select species to achieve the best reconstruction of ancestral character states on a phylogeny. We first show that the marginal maximum likelihood has the monotonicity property that more taxa give better reconstruction, but the Fitch method does not have it even on an ultrametric phylogeny. We further validate a greedy approach for species selection using simulation. The vali ...[more]

PMID: 20140213

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Project description:As genome sequencing efforts are unveiling the genetic diversity of the biosphere with an unprecedented speed, there is a need to accurately describe the structural and functional properties of groups of extant species whose genomes have been sequenced, as well as their inferred ancestors, at any given taxonomic level of their phylogeny. Elaborate approaches for the reconstruction of ancestral states at the sequence level have been developed, subsequently augmented by methods based on gene content. While these approaches of sequence or gene-content reconstruction have been successfully deployed, there has been less progress on the explicit inference of functional properties of ancestral genomes, in terms of metabolic pathways and other cellular processes. Herein, we describe PathTrace, an efficient algorithm for parsimony-based reconstructions of the evolutionary history of individual metabolic pathways, pivotal representations of key functional modules of cellular function. The algorithm is implemented as a five-step process through which pathways are represented as fuzzy vectors, where each enzyme is associated with a taxonomic conservation value derived from the phylogenetic profile of its protein sequence. The method is evaluated with a selected benchmark set of pathways against collections of genome sequences from key data resources. By deploying a pangenome-driven approach for pathway sets, we demonstrate that the inferred patterns are largely insensitive to noise, as opposed to gene-content reconstruction methods. In addition, the resulting reconstructions are closely correlated with the evolutionary distance of the taxa under study, suggesting that a diligent selection of target pangenomes is essential for maintaining cohesiveness of the method and consistency of the inference, serving as an internal control for an arbitrary selection of queries. The PathTrace method is a first step towards the large-scale analysis of metabolic pathway evolution and our deeper understanding of functional relationships reflected in emerging pangenome collections.

Dataset Information

Greedy selection of species for ancestral state reconstruction on phylogenies: elimination is better than insertion.

Publications

Greedy selection of species for ancestral state reconstruction on phylogenies: elimination is better than insertion.

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