Strong amplification of quantitative genetic variation under a balance between mutation and fluctuating stabilizing...

Area of Science:

• Evolutionary biology
• Quantitative genetics

Background:

• High heritability of quantitative traits is a long-standing puzzle in evolutionary biology.
• Classical mutation-selection balance models, assuming a constant environment, fail to explain observed heritability.
• The reasons for the failure of these models remain unclear, hindering progress.

Purpose of the Study:

• To revisit the puzzle of high heritability by relaxing the assumption of environmental stasis in quantitative genetic models.
• To investigate the impact of a slowly changing, stochastic trait optimum on heritability predictions.
• To develop a new model that better aligns with empirical observations of genetic variation.

Main Methods:

• Modified the canonical Latter-Bulmer model by incorporating a slowly changing, stochastic trait optimum.
• Analyzed the feedback between adaptation rate and selection coefficient fluctuations.
• Derived a formula to predict genetic variation within the modified model.

Main Results:

• The modified model, with a dynamic optimum, exhibits qualitatively different behavior compared to stationary optimum models.
• A feedback loop between adaptation rate and selection coefficient fluctuations was identified as a key driver.
• Heritability predictions from the new model are more consistent with observations and less sensitive to parameters than the classical model.

Conclusions:

• Environmental change, specifically a slowly fluctuating optimum, is a critical factor missing in traditional mutation-selection balance models.
• The identified feedback mechanism provides a more robust explanation for high heritability and genetic variation.
• This approach offers a new framework for understanding quantitative trait evolution in changing environments.