Evolutionary Fingerprinting of Genes
| Item Type |
Journal Article |
| Author |
Sergei L Kosakovsky Pond |
| Author |
Konrad Scheffler |
| Author |
Michael B Gravenor |
| Author |
Art F Y Poon |
| Author |
Simon D W Frost |
| URL |
http://www.ncbi.nlm.nih.gov/pubmed/19864470
|
| Publication |
Molecular Biology and Evolution |
| ISSN |
1537-1719 |
| Date |
Oct 28, 2009 |
| Extra |
| Journal Abbr |
Mol. Biol. Evol |
| DOI |
10.1093/molbev/msp260 |
| Accessed |
2009-12-30 14:22:35 |
| Library Catalog |
NCBI PubMed |
| Abstract |
Over time, natural selection molds every gene into a unique mosaic of sites evolving rapidly or resisting change - an 'evolutionary fingerprint' of the gene. Aspects of this evolutionary fingerprint, such as the site-specific ratio of nonsynonymous to synonymous substitution rates (dN/dS), are commonly used to identify genetic features of potential biological interest; however, no framework exists for comparing evolutionary fingerprints between genes. We hypothesize that protein coding genes with similar protein structure and/or function tend to have similar evolutionary fingerprints, and that comparing evolutionary fingerprints can be useful for discovering similarities between genes in a way that is analogous to, but independent of, discovery of similarity via sequence-based comparison tools such as BLAST. To test this hypothesis, we develop a novel model of coding sequence evolution that uses a general bivariate discrete parameterization of the evolutionary rates. We show that this approach provides a better fit to the data using a smaller number of parameters than existing models. Next, we use the model to represent evolutionary fingerprints as probability distributions and present a methodology for comparing these distributions in a way that is robust against variations in data set size and divergence. Finally, using sequences of three rapidly evolving RNA viruses (HIV-1, Hepatitis C virus and Influenza A virus) we demonstrate that genes within the same functional group tend to have similar evolutionary fingerprints. Our framework provides a sound statistical foundation for efficient inference and comparison of evolutionary rate patterns in arbitrary collections of gene alignments, clustering homologous and non-homologous genes and investigation of biological and functional correlates of evolutionary rates. |
| Title |
Evolutionary Fingerprinting of Genes |
| Date Added |
2009-12-30 09:22 |
| Date Modified |
2009-12-30 09:22 |