Researchers at the University of Chicago have gained new insight into the co- evolution of plants and the microbes that attack them. In the August 12 issue of Nature, the researchers report findings that go against the widely held "arms race" theory in which plant resistance genes fight brief battles with microbes before both plant and pathogen mutate to higher and higher levels of resistance and virulence.
Joy Bergelson, assistant professor of ecology & evolution at the University of Chicago, favors an alternative hypothesis she calls 'trench warfare', in which cycles of disease epidemics maintain relatively stable forms of resistance and susceptibility genes over long periods of time.
"The arms race theory has been a generally accepted model for the evolution of disease resistance genes because it is intuitive, but its never been scientifically tested" says Bergelson. "Our results were surprising in demonstrating that an arms race is not occurring for the resistance gene we studied."
The researchers focused on the Rpm1 gene in Arabidopsis, the common mustard plant. Rpm1 is either present or absent in a given plant. These two alternative states are called the gene's alleles, which are located at a specific spot on the DNA called the gene locus. The Rpm1 allele confers resistance to certain pathogens. When it is absent at the Rpm1 locus (the null allele) the plant is susceptible to pathogenic attack.
To understand the evolutionary dynamics of the Rpm1 resistance gene, Bergelson and colleagues looked at the number of base pair differences in the DNA surrounding the Rpm1 gene locus. Base pair differences, also known as polymorphisms, accumulate over long periods of evolutionary time, and serve as a kind of molecular clock that gives researchers clues as to the age of alleles. The more polymorphisms, the older the alleles.
Bergelson's new analysis found that the number of polymorphisms was much higher than would be predicted by the arms race hypothesis, where resistance alleles are thought to be very young and have a high turnover rate. "The number of polymorphisms we counted indicates that alleles at the Rpm1 locus are roughly 9.8 million years old," says Bergelson.
The researchers also counted differences in the Rpm1 gene itself in two closely related species of Arabidopsis. They found that most differences accumulated in non-coding regions that don't affect the functionality of the resistance gene product.
"If the gene were subject to the high turnover predicted by the arms race hypothesis, then as the plant responds to a rapidly evolving pathogen, we would expect there to be many changes in the Rpm1 protein. Instead, it seems that it really hasn't changed for close to 10 million years, the age of the species' common ancestor" explains Eli Stahl, a graduate student in Bergelson's lab and an author of the paper.
Bergelson and colleagues developed a trench warfare model in which resistant and susceptible individuals are maintained by being selected for or against at different times during natural pathogen epidemics. During an epidemic, susceptible plants die off until remaining they are so few and far between, that the pathogen has no more available hosts and gradually fades away. Resistant plants dominate for a while until susceptible plants begin to make a comeback in the absence of pathogens.
"Ecological models of disease tend to exhibit cyclical behavior, since the severity of epidemics both depends upon and impacts the frequency of susceptible individuals. We found features of our polymorphism data that support the long term cycling predicted by our trench warfare model" explains Bergelson.
This study provides indirect support for a long-standing belief that organisms face tradeoffs. "We can only explain the decrease in resistant individuals after an epidemic by assuming that there must be a cost to maintaining Rpm1 in the absence of the pathogen," says Bergelson whose team is conducting further investigations to test directly for costs and understand exactly why they are present.
The approach will enable researchers to better understand ecological dynamics, like pathogen epidemics, by studying their cumulative impact on genetic evolution.
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