The First Genome-Scale Network of Rice Genes Can Predict Their Functions to Help Make Biofuels

[caption id="attachment_3077" align="alignright" width="357" caption="This schematic is of a full-size view of a RiceNet layout. It's color-coded to show the probability of gene network links (red = higher probability and blue = lower probability). (Image source: Insuk Lee, Yonsei University)"][/caption]

An international team of researchers, including scientists in the U.S. Department of Energy (DOE)’s Joint BioEnergy Institute (JBEI), created the world’s first genome-scale model for predicting genes and gene networks in a plant species – rice, to be precise. This model, dubbed RiceNet, allows researchers to view multiple sets of data of genes and genetic pathways, which then allows them to predict the functions of entire gene networks. Professor Pamela Ronald and her co-researchers of the University of California (UC) Davis conducted experiments proving that RiceNet is indeed able to accurately determine gene functions in rice.

One may wonder why it would be so crucial to discover the functions of certain genes in rice. Well, rice is a food staple for about half of the world’s population and can be used as a model plant for the perennial plants, or those that live for longer than two years, that seem to be perfect candidates for creating cellulosic biofuels (fuels whose energy is derived from organic materials such as grass, corn, and vegetable oil through the process of carbon fixation), which would decrease dependence on other, non-renewable energy sources. Ronald said it best: “The ability to identify key genes that control simple or complex traits in rice has important biological, agricultural, and economic consequences. RiceNet offers an attractive and potentially rapid route for focusing crop engineering efforts on the small sets of genes that are deemed most likely to affect the traits of interest.”

Personally, I think that the ability to access multiple data sets at one time is very useful and efficient. Networks similar to RiceNet may well be the future of genetics research; in fact, RiceNet is already accessible for this very purpose: the creators of RiceNet also made an online model that can select ideal rice genes based on RiceNet’s data, which can be used here.