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Are there laws of genome evolution?
1National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America. koonin@ncbi.nlm.nih.gov
Plos Computational Biology
|September 9, 2011
Summary
Quantitative evolutionary genomics reveals universal laws governing genome evolution, independent of natural selection. These emergent properties, observed in gene evolution rates and network structures, can be modeled using statistical physics principles.
Area of Science:
- Evolutionary genomics
- Systems biology
- Quantitative biology
Background:
- Genomic and molecular phenomic variables exhibit complex relationships.
- Understanding universal patterns in genome evolution is crucial for evolutionary biology.
Purpose of the Study:
- To identify and describe universal regularities in genome evolution.
- To investigate the underlying mechanisms, such as mathematical models, that explain these regularities.
- To assess if these regularities can be considered "laws" of evolutionary genomics.
Main Methods:
- Analysis of quantitative data from evolutionary genomics and systems biology.
- Statistical modeling, including birth-death-innovation models.
- Comparison of genomic variables (e.g., gene evolution rates, gene family size) and network properties (e.g., node degree).
Main Results:
- Discovery of universal distributions: log-normal for evolutionary rates, power-law for family size and network degree.
- Observed negative correlation between gene sequence evolution rate and expression level.
- Identified differential scaling of gene functional classes with genome size.
- Demonstrated that simple mathematical models, not explicitly including selection, can account for these universals.
Conclusions:
- Universal regularities in genome evolution appear to be emergent properties of gene ensembles, not directly shaped by selection.
- These findings suggest potential "laws of evolutionary genomics" analogous to laws in statistical physics.
- The study provides a framework for understanding genome evolution through quantitative and physical principles.
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