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Pleiotropy, apparent stabilizing selection and uncovering fitness optima
Katrina McGuigan1, Locke Rowe, Mark W Blows
1School of Biological Sciences, University of Queensland, Brisbane 4072, QLD, Australia. k.mcguigan1@uq.edu.au
Trends in Ecology & Evolution
|November 25, 2010
Summary
Pleiotropy, where genes affect multiple traits, complicates evolutionary studies. This review shows how analyzing trait combinations with genetic variation can reveal fitness optima and simplify studying complex fitness landscapes.
Area of Science:
- Evolutionary Biology
- Quantitative Genetics
Background:
- Evolutionary theory highlights that single-trait evolution is difficult to study in isolation due to pleiotropy.
- Pleiotropy can create the illusion of stabilizing selection on traits by linking them to fitness.
- Genetic variation often concentrates in specific combinations of traits, not individual traits.
Purpose of the Study:
- To review how trait combinations with high genetic variation can be utilized in evolutionary studies.
- To demonstrate how these trait combinations can help identify fitness optima defined by stabilizing selection.
- To propose a method for overcoming challenges in measuring numerous fitness-influencing traits or total fitness.
Main Methods:
- Review of existing literature on pleiotropy and its effects on trait evolution and genetic variation.
- Analysis of how joint effects of traits on fitness influence observed selection patterns.
- Conceptual framework for using trait combinations with high genetic variation to infer fitness landscapes.
Main Results:
- Widespread pleiotropy leads to apparent stabilizing selection on metric traits.
- Genetic variation is often constrained to specific combinations of traits.
- Trait combinations with substantial genetic variation can serve as proxies for fitness optima.
Conclusions:
- Analyzing trait combinations with high genetic variation offers a powerful approach to understanding evolutionary optima.
- This method simplifies the study of complex fitness landscapes by focusing on key trait combinations.
- It provides a viable strategy for researchers to study fitness when direct measurement of all traits is impractical.
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