Chris Toomajian, postdoctoral researcher in molecular and computational biology in the USC College of Letters, Arts and Sciences, led a group that sought to replace the standard neutral model, a common but unrealistic test for natural selection, with a statistical method based on hard genomic data.
The group's research will be published online April 25 by Public Library of Science.
"Do we now have enough data to see the standard neutral model wasn't appropriate?" Toomajian asked. "We know something more now about how the population has been structured."
The standard neutral model makes improbable assumptions about population structure, such as assigning each individual an equal chance of reproducing.
Co-author Magnus Nordborg, associate professor of molecular and computational biology in USC College, predicted that earlier research would need to be revisited because the model makes it too easy to infer selection at any given gene.
"Once you start looking at enough cases then you realize that, oops, it's all under selection. I think a lot of that research is going to end up in the trash can," Nordborg said.
The group's method can be applied to any organism, including humans.
The PLoS paper focused on the weed Arabidopsis thaliana, and in particular on the FRIGIDA (FRI) gene, known to influence flowering time.
A. thaliana was once a plant that bloomed annually. But two versions of FRI that appeared thousands of years ago enabled the plant to flower year-round, helping it out-compete other plants.
Toomajian and his group showed that these two versions, also called gene variants, are too common to have spread solely by chance.
"We've shown that for one gene with an important role in that [flowering] process, there's good evidence that there's natural selection
Source:University of Southern California