Modeling Sex’s (Evolutionary) Appeal
Computer model supports one theory of why sex is such a good idea
Sex is a costly undertaking. Finding partners takes time and energy. Sexual contact can transmit disease. And if reproductive success is measured by how many genes you pass on, females would be better off reproducing asexually. But sex must be beneficial in some way—besides being fun—since so many plants and animals do it without going extinct. A new computational model described in the March 2, 2006, issue of Nature confirms one existing theory about why sex is advantageous on the genetic level.
“This is very difficult to measure in real organisms,” says Ricardo Azevedo, PhD, assistant professor of biology and biochemistry at the University of Houston. “But things that take years or decades in the lab take only hours in the computer.”
Evolutionary biologists have posited several reasons for the success of sexual reproduction. The mutational deterministic hypothesis suggests that sex helps remove harmful mutations from a population because offspring receive genes from two parents. But the benefits of mutation purging can only overcome the costs of sex if the rate of harmful mutations is high. Multiple mutations must also be more harmful than would be expected from their individual effects, a condition known as negative epistasis. Azevedo’s model suggests that the mutational deterministic hypothesis may be true.
Azevedo along with Christina Burch, PhD, assistant professor of biology at the University of North Carolina, Chapel Hill, and three graduate students created a model that treats each “organism” as a network of interacting genes. The network is expressed as a matrix of numbers (positive, negative or zero) representing the effect of each gene on the activity of every other gene in the organism. Large populations of sexually and asexually reproducing cyber-organisms (networks) were created with different rates of spontaneous mutation. In the first part of the simulation, each organism’s genes interact. Organisms that produce stable patterns of gene expression produce offspring in the second part of the simulation; unstable networks don’t—natural selection at work. When the populations reached equilibrium in their sensitivity to mutations, the sexual populations had become more insensitive to mutations than asexual populations and had also evolved negative epistasis. Compared to asexual creatures, they more effectively purge negative mutations from the gene pool.
“If the conditions in the model are real, then when sex evolves it creates conditions that help sustain itself over time,” Azevedo says.
“The prevalence of sex begs to be studied,” comments Andreas Wagner, PhD, an associate professor of biology at the University of New Mexico. “To the extent that an abstract model can tell you anything about the evolution of sex, [Azevedo and Burch] have made an important contribution.” But, he says, he’d like to see the work confirmed in living systems.
Azevedo agrees this paper is a first step. He is trying to make the model more applicable to multicellular organisms while his collaborator, Burch, conducts experiments with viruses in order to confirm the model’s results.