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Published on: July 17, 2021
Evolutionary fingerprinting of genes
Sergei L Kosakovsky Pond1, Konrad Scheffler, Michael B Gravenor
1Department of Medicine, University of California, San Diego, USA. spond@ucsd.edu
Molecular Biology and Evolution
|October 30, 2009
Summary
Natural selection creates unique evolutionary fingerprints for each gene. A new framework compares these fingerprints, revealing functional similarities between genes, independent of sequence similarity.
Area of Science:
- Evolutionary biology
- Genomics
- Bioinformatics
Background:
- Natural selection shapes genes into unique evolutionary patterns, termed "evolutionary fingerprints."
- The ratio of nonsynonymous to synonymous substitution rates (dN/dS) is a key aspect of these fingerprints.
- Existing methods lack a framework for comparing evolutionary fingerprints across different genes.
Purpose of the Study:
- To develop a novel computational framework for comparing gene evolutionary fingerprints.
- To test the hypothesis that genes with similar protein structure/function exhibit similar evolutionary fingerprints.
- To establish a method for discovering gene similarities independent of sequence-based comparisons.
Main Methods:
- Developed a novel model for coding sequence evolution using a bivariate discrete parameterization of evolutionary rates.
- Represented evolutionary fingerprints as probability distributions.
- Created a methodology for comparing these distributions, robust to data set size and divergence.
Main Results:
- The novel model offers a better fit with fewer parameters than existing models.
- Genes within the same functional groups showed similar evolutionary fingerprints in rapidly evolving RNA viruses (HIV-1, HCV, influenza A).
- The framework successfully clustered homologous and nonhomologous genes based on evolutionary rates.
Conclusions:
- The developed framework provides a robust statistical foundation for comparing evolutionary rate patterns.
- This approach facilitates the discovery of functional relationships between genes.
- It enables further investigation into the biological and functional correlates of evolutionary rates.
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