New computational model predicts gene function of plant genes quickly

Washington, Feb 1 (ANI): Scientists have created a new computational model that can be used to predict gene function of uncharacterized plant genes with unprecedented speed and accuracy.

The network, dubbed AraNet, has over 19,600 genes associated to each other by over 1 million links and can increase the discovery rate of new genes affiliated with a given trait tenfold.

"In essence, AraNet is based on the simple idea that genes that physically reside in the same neighborhood, or turn on in concert with one another are probably associated with similar traits," explained corresponding author Sue Rhee at the Carnegie Institution's Department of Plant Biology.

"We call it guilt by association. Based on over 50 million scientific observations, AraNet contains over 1 million linkages of the 19,600 genes in the tiny, experimental mustard plant Arabidopsis thaliana," she said.

"We made a map of the associations and demonstrated that we can use the network to propose that uncharacterized genes are linked to specific traits based on the strength of their associations with genes already known to be linked to those characteristics," she added.

The network allows for two main types of testable hypotheses.

The first uses a set of genes known to be involved in a biological process such as stress responses, as a "bait" to find new genes ("prey") involved in stress responses.

The bait genes are linked to each other based on over 24 different types of experiments or computations.

If they are linked to each other much more frequently or strongly than by chance, one can hypothesize that other genes that are as well linked to the bait genes have a high probability of being involved in the same process.

The second testable hypothesis is to predict functions for uncharacterized genes.

There are 4,479 uncharacterized genes in AraNet that have links to ones that have been characterized, so a significant portion of all the unknowns now get a new hint as to their function.

The scientists tested the accuracy of AraNet with computational validation tests and laboratory experiments on genes that the network predicted as related.

The researchers selected three uncharacterized genes.

Two of them exhibited phenotypes that AraNet predicted. One is a gene that regulates drought sensitivity, now named Drought sensitive 1 (Drs1).

The other regulates lateral root development, called Lateral root stimulator 1 (Lrs1).

The researchers found that the network is much stronger forecasting correct associations than previous small-scale networks of Arabidopsis genes.

"AraNet has the potential to help realize the promise of genomics in plant engineering and personalized medicine," said Rhee. (ANI)