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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Published on: July 14, 2015
A genomic perspective on protein families
R L Tatusov1, E V Koonin, D J Lipman
1National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.
Science (New York, N.Y.)
|October 24, 1997
Summary
Researchers classified conserved genes into 720 Clusters of Orthologous Groups (COGs) by comparing proteins across diverse genomes. This framework aids in understanding gene function and evolutionary relationships, especially for poorly characterized genomes.
Area of Science:
- Genomics
- Bioinformatics
- Evolutionary Biology
Background:
- Genome sequencing is rapidly advancing, generating vast amounts of data.
- Classifying conserved genes based on homology is crucial for extracting maximum information.
- Understanding homologous relationships aids in functional and evolutionary genome analysis.
Purpose of the Study:
- To classify conserved genes by their homologous relationships.
- To establish a framework for functional and evolutionary genome analysis.
- To enable functional predictions for poorly characterized genomes.
Main Methods:
- Comparative analysis of proteins encoded in seven complete genomes from five major phylogenetic lineages.
- Elucidation of consistent patterns of sequence similarities.
- Delineation of Clusters of Orthologous Groups (COGs).
Main Results:
- 720 Clusters of Orthologous Groups (COGs) were delineated.
- Each COG comprises orthologous proteins or paralogs from at least three lineages.
- Orthologs were found to typically share the same function.
Conclusions:
- COGs provide a framework for functional and evolutionary genome analysis.
- Functional information can be transferred within a COG, aiding in predictions for uncharacterized genomes.
- This classification system enhances the utility of accumulating genome sequence data.
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