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Evolutionary sequence analysis of complete eukaryote genomes

Blair, JE
; 
Shah, P
; 
Hedges, SB
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Genre
Review
Journal
Date
2005-03-11
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Department
Subject
Animals
 Biodiversity
 Biological Evolution
 Computational Biology
 Databases, Genetic
 Databases, Protein
 Eukaryotic Cells
 Evolution, Molecular
 Fossils
 Gene Duplication
 Genome
 Genome, Archaeal
 Humans
 Models, Genetic
 Phylogeny
 Programming Languages
 Proteins
 Sequence Analysis
 Sequence Analysis, DNA
 Sequence Analysis, Protein
 Software
 Time Factors
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http://hdl.handle.net/20.500.12613/5650
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Evolutionary sequence analysis of complete eukaryote genomes.pdf
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DOI
10.1186/1471-2105-6-53
Abstract
Background: Gene duplication and gene loss during the evolution of eukaryotes have hindered attempts to estimate phylogenies and divergence times of species. Although current methods that identify clusters of orthologous genes in complete genomes have helped to investigate gene function and gene content, they have not been optimized for evolutionary sequence analyses requiring strict orthology and complete gene matrices. Here we adopt a relatively simple and fast genome comparison approach designed to assemble orthologs for evolutionary analysis. Our approach identifies single-copy genes representing only species divergences (panorthologs) in order to minimize potential errors caused by gene duplication. We apply this approach to complete sets of proteins from published eukaryote genomes specifically for phylogeny and time estimation. Results: Despite the conservative criterion used, 753 panorthologs (proteins) were identified for evolutionary analysis with four genomes, resulting in a single alignment of 287,000 amino acids. With this data set, we estimate that the divergence between deuterostomes and arthropods took place in the Precambrian, approximately 400 million years before the first appearance of animals in the fossil record. Additional analyses were performed with seven, 12, and 15 eukaryote genomes resulting in similar divergence time estimates and phylogenies. Conclusion: Our results with available eukaryote genomes agree with previous results using conventional methods of sequence data assembly from genomes. They show that large sequence data sets can be generated relatively quickly and efficiently for evolutionary analyses of complete genomes. © 2005 Blair et al; licensee BioMed Central Ltd.
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Springer Science and Business Media LLC
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BMC Bioinformatics
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