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Selection on recombination in a multi-locus system.
D Charlesworth1, B Charlesworth
1Laboratory of Environmental Mutagenesis, National Institute of Environmental Health Sciences, P. O. Box 12233 Research Triangle Park, North Carolina 27709.
Genetics
|March 1, 1979
Summary
Selection on recombination rates in finite populations was investigated. Computer simulations showed selection for reduced recombination consistently outweighed selection for increased recombination.
Area of Science:
- Population genetics
- Evolutionary biology
- Quantitative genetics
Background:
- The Wills and Miller (1976) model examines selection acting on recombination rates within finite populations.
- Understanding the evolution of recombination is crucial in population genetics.
- Finite population sizes introduce genetic drift, influencing selection dynamics.
Purpose of the Study:
- To investigate the Wills and Miller (1976) model of selection on recombination rates using computer simulations.
- To explore the interplay between selection on linked loci and modifier genes affecting recombination.
- To determine the net effect of selection when both increasing and decreasing recombination are possible.
Main Methods:
- Computer simulations were employed to model populations with 80 selected loci.
- A modifier gene, either linked or unlinked, influenced the map length of selected loci.
- Multiplicative fitness interactions between loci and heterozygote advantage were assumed.
Main Results:
- In all simulated scenarios, selection favoring a reduction in recombination rates was dominant.
- The influence of the modifier gene on map length was consistently overcome by selection for reduced recombination.
- The strength of selection for reduced recombination outweighed any potential selection for increased recombination.
Conclusions:
- Selection for reduced recombination is a powerful force in finite populations, even with heterozygote advantage and multiplicative fitness.
- The evolution of recombination rates is strongly influenced by the balance of selection pressures.
- Computer modeling provides valuable insights into complex evolutionary genetic processes.
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