Motivation: Inferring species phylogenies with a history of gene losses and duplications is a challenging and an important task in computational biology. This problem can be solved by duplication-loss models in which the primary step is to reconcile a rooted gene tree with a rooted species tree. Most modern methods of phylogenetic reconstruction (from sequences) produce unrooted gene trees. This limitation leads to the problem of transforming unrooted gene tree into a rooted tree, and then reconciling rooted trees. The main questions are 'What about biological interpretation of choosing rooting?', 'Can we find efficiently the optimal rootings?', 'Is the optimal rooting unique?'.
Results: In this paper we present a model of reconciling unrooted gene tree with a rooted species tree, which is based on a concept of choosing rooting which has minimal reconciliation cost. Our analysis leads to the surprising property that all the minimal rootings have identical distributions of gene duplications and gene losses in the species tree. It implies, in our opinion, that the concept of an optimal rooting is very robust, and thus biologically meaningful. Also, it has nice computational properties. We present a linear time and space algorithm for computing optimal rooting(s). This algorithm was used in two different ways to reconstruct the optimal species phylogeny of five known yeast genomes from approximately 4700 gene trees. Moreover, we determined locations (history) of all gene duplications and gene losses in the final species tree. It is interesting to notice that the top five species trees are the same for both methods.
Availability: Software and documentation are freely available from http://bioputer.mimuw.edu.pl/~gorecki/urec
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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