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Sex: The power of randomization
Liudmyla Vasylenko1, Marcus W Feldman2, Christos Papadimitriou3
1Department of Evolutionary and Environmental Biology and Institute of Evolution, University of Haifa, 3498838, Israel.
Theoretical Population Biology
|January 15, 2019
Summary
Sexual reproduction and recombination harness randomness to accelerate evolution. This allows natural selection to efficiently test genetic combinations, unlike in asexual populations.
Area of Science:
- Evolutionary Biology
- Genetics
- Computer Science
Background:
- Randomness in evolutionary biology traditionally viewed as a source of novelty via mutation.
- Randomization in computer science and other sciences is used to break patterns and remove bias.
- Sex and recombination are fundamental processes in many eukaryotic organisms.
Purpose of the Study:
- To demonstrate how sex and recombination harness the pattern-breaking power of randomness in nature.
- To explain the evolutionary advantage of sexual reproduction in finite populations.
- To contrast the role of randomness in sexual versus asexual reproduction.
Main Methods:
- Conceptual analysis comparing randomness in evolutionary biology and computer science.
- Theoretical exploration of how sex and recombination facilitate random genetic combinations.
- Comparative analysis of evolutionary dynamics in sexual and asexual populations.
Main Results:
- Sex and recombination enable natural selection to test alleles across a random sample of genetic interactions.
- This process favors alleles that perform well in a wide range of potential genetic combinations.
- Asexual populations lack this mechanism, limiting their ability to adapt through combinatorial testing.
Conclusions:
- The pattern-breaking power of randomness, as utilized in computer science, is actively harnessed by sex and recombination in evolution.
- Sexual reproduction provides a significant adaptive advantage by enabling efficient exploration of genetic variation.
- Randomization through sex and recombination is crucial for adaptation in finite populations.
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