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Questioning the ubiquity of neofunctionalization
Todd A Gibson1, Debra S Goldberg
1Computational Bioscience Program, University of Colorado Denver, Aurora, Colorado, United States of America. Todd.Gibson@ucdenver.edu
Plos Computational Biology
|January 3, 2009
Summary
Gene duplication drives functional diversity through neofunctionalization and subfunctionalization. However, this study reveals subfunctionalization and self-interactions are more significant drivers in protein interaction evolution, challenging previous models.
Area of Science:
- Evolutionary biology
- Molecular biology
- Systems biology
Background:
- Gene duplication is a primary source of functional novelty.
- Neofunctionalization and subfunctionalization are proposed mechanisms for functional divergence.
- Protein interactions are used as a proxy for protein functions in evolutionary studies.
Purpose of the Study:
- To re-evaluate the roles of neofunctionalization and subfunctionalization in protein interaction network evolution.
- To identify factors that may have led to the overestimation of neofunctionalization.
- To propose a more accurate model for protein interaction evolution.
Main Methods:
- Analysis of empirical protein interaction data.
- Review of evolutionary models of protein interactions.
- Critique of theoretical models for neofunctionalization.
Main Results:
- Self-interacting proteins are underreported in high-throughput assays.
- Paralog analysis may be confounded by subsequent duplication events.
- Theoretical models of neofunctionalization fail to replicate empirical network clustering.
Conclusions:
- Subfunctionalization is a more significant driver of protein interaction evolution than previously thought.
- Self-interactions play a crucial role in protein interaction networks.
- The role of neofunctionalization in protein interaction evolution may be overestimated.
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