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Network archaeology: uncovering ancient networks from present-day interactions
Saket Navlakha1, Carl Kingsford
1Department of Computer Science and Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA.
Plos Computational Biology
|May 3, 2011
Summary
We developed novel algorithms to reconstruct ancestral protein-protein interaction (PPI) networks, revealing how protein complexes evolved in yeast. Our findings show significant rewiring and duplication-driven growth in PPI networks over time.
Area of Science:
- Computational Biology
- Evolutionary Biology
- Network Science
Background:
- Reconstructing ancestral protein-protein interaction (PPI) networks is crucial for understanding evolutionary processes.
- Current methods are limited by the unavailability of historical network data.
Purpose of the Study:
- To develop novel algorithms for reconstructing the evolutionary history of present-day PPI networks.
- To infer protein ages and evolutionary events in the yeast PPI network.
Main Methods:
- Developed likelihood-based algorithms to infer past network states by reversing assumed growth models.
- Compared different network growth models (duplication-mutation, forest fire, preferential attachment).
- Estimated protein ages and analyzed network structural changes over evolutionary time.
Main Results:
- Reconstructed yeast PPI network history, with estimated protein ages aligning with sequence-based data.
- Found that duplication-based models better explain PPI network evolution than social network models.
- Predicted significant complex rewiring and the formation of new interactions within existing complexes.
Conclusions:
- The present-day yeast PPI network encodes substantial evolutionary history.
- Protein complexes undergo significant evolutionary rewiring, with new interactions often forming internally.
- The developed algorithms provide a powerful tool for studying the evolution of biological networks.
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