Researchers at The Samuel Roberts Noble Foundation, Michigan Technological University (MTU) and University of California, Riverside (UCR) recently received a three-year, $1.45 million grant from the National Science Foundation (NSF).
This grant will enable the Noble Foundation's Patrick X. Zhao, Ph.D., principal investigator, and co-principal investigators, Hairong Wei, Ph.D. (MTU) and Shizhong Xu, Ph.D. (UCR) to develop the formulas and models needed to study how genes or groups of genes (genotypes) are connected to and control the characteristics traits (phenotypes) of plants. This would turn gene data into valuable information for plant breeders to use when breeding improved varieties.
"This grant will help us generate new methods and tools to decipher plant the associations between genes and physical traits. This will further enhance plant breeding programs, Zhao said. "This is a great opportunity to join with other researchers and combine our expertise to study these associations more in-depth than ever before. Through this collaborative research, we look forward to advancing bioinformatics for the basic plant science research, plant breeding, and ultimately to improving agriculture and our communities.
Plants have unique phenotypes, some of which can be easily seen, like flower colors. Others, however, require a more in-depth analysis to be seen, such as disease resistance or drought tolerance. Previously, researchers looked at individual genes to determine certain traits but realized that, very often, larger networks of genes were controlling those traits.
"Plant breeders want to know how these complex genetic variants and gene networks impact the plant's function," Zhao said. "This research is a more advanced way of looking at how the larger gene networks control these processes. We have to look at the bigger picture to more successfully understand why and how plants possess certain traits.
Today's technology allows plant researchers to study vast amounts of gene information. The challenge is analyzing these data to understand how genes work together to express certain traits.
Once researchers can understand how phenotypes are controlled, that knowledge can be applied to develop more effective plant breeding programs to increase productivity and target economically important traits in agricultural crops. "This research has the potential to develop tools that will better equip plant breeders to develop improved plant varieties with desired traits that will allow farmers and ranchers to grow more with fewer resources, Zhao said.
This grant builds on a previous NSF commitment started in 2010 that investigated how gene networks control gene expression in plants.