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Comparative analyses of whole-genome protein sequences from multiple organisms.
- Source :
-
Scientific reports [Sci Rep] 2018 May 01; Vol. 8 (1), pp. 6800. Date of Electronic Publication: 2018 May 01. - Publication Year :
- 2018
-
Abstract
- Phylogenies based on entire genomes are a powerful tool for reconstructing the Tree of Life. Several methods have been proposed, most of which employ an alignment-free strategy. Average sequence similarity methods are different than most other whole-genome methods, because they are based on local alignments. However, previous average similarity methods fail to reconstruct a correct phylogeny when compared against other whole-genome trees. In this study, we developed a novel average sequence similarity method. Our method correctly reconstructs the phylogenetic tree of in silico evolved E. coli proteomes. We applied the method to reconstruct a whole-proteome phylogeny of 1,087 species from all three domains of life, Bacteria, Archaea, and Eucarya. Our tree was automatically reconstructed without any human decisions, such as the selection of organisms. The tree exhibits a concentric circle-like structure, indicating that all the organisms have similar total branch lengths from their common ancestor. Branching patterns of the members of each phylum of Bacteria and Archaea are largely consistent with previous reports. The topologies are largely consistent with those reconstructed by other methods. These results strongly suggest that this approach has sufficient taxonomic resolution and reliability to infer phylogeny, from phylum to strain, of a wide range of organisms.
- Subjects :
- Algorithms
Amino Acid Sequence
Archaea classification
Bacteria classification
Base Sequence
Escherichia coli genetics
Eukaryota classification
Humans
Sequence Alignment
Whole Genome Sequencing
Archaea genetics
Bacteria genetics
Eukaryota genetics
Genome
Phylogeny
Sequence Analysis, Protein statistics & numerical data
Subjects
Details
- Language :
- English
- ISSN :
- 2045-2322
- Volume :
- 8
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Scientific reports
- Publication Type :
- Academic Journal
- Accession number :
- 29717164
- Full Text :
- https://doi.org/10.1038/s41598-018-25090-8