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Published on: February 3, 2023
Compensatory Drift and the Evolutionary Dynamics of Dosage-Sensitive Duplicate Genes
Ammon Thompson1, Harold H Zakon2, Mark Kirkpatrick3
1Department of Integrative Biology, University of Texas, Austin, Texas 78712 Department of Neuroscience, University of Texas, Austin, Texas 78712 ammthompson@ucdavis.edu.
Gene duplication allows redundant genes (paralogs) to evolve new functions over time. Our compensatory drift model shows expression can diverge, enabling later functional changes.
Area of Science:
- Evolutionary genetics
- Molecular evolution
- Systems biology
Background:
- Dosage-balance selection maintains optimal combined expression of gene duplicates (paralogs).
- Understanding the evolutionary dynamics of paralogs under this selection is crucial for deciphering gene family evolution.
Purpose of the Study:
- To present and analyze the compensatory drift model for coevolving duplicate genes under dosage-balance selection.
- To investigate how gene expression divergence and neofunctionalization occur in paralogs over evolutionary time.
Main Methods:
- Development of the compensatory drift model to simulate gene duplication dynamics.
- Fitting the model to empirical data from sodium channel duplicates in teleost fish.
- Estimation of dosage-balance selection strength in observed gene families.
Main Results:
- Even with strong dosage-balance selection, individual paralog expression can diverge via drift.
- Divergence rates decrease with stronger stabilizing selection, larger mutation effects, or larger population sizes.
- Dosage-balance selection initially hinders but can later promote neofunctionalization.
Conclusions:
- Functionally redundant paralogs can undergo significant functional changes after extended periods of compensatory drift.
- The model provides insights into the evolutionary pathways of duplicate genes, including cases of neofunctionalization in electric fish.
- Dosage-balance selection plays a complex role in shaping paralog evolution, balancing constraint with the potential for innovation.
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