Metabolomics-Assisted Breeding

May 19, 2014

By Dr. Lindsey Hoffman

Species and cultivar selection is one of the most important decisions a turfgrass manager can make. Putting the right plant in the right place is the first step to cultivating a healthy, sustainable turfgrass surface.  With this in mind, one of the main objectives of the turfgrass breeding program at the University of Minnesota is the development of perennial ryegrass (Lolium perenne L.) cultivars with improved freezing tolerance and better overall winterhardiness.  The program has been successful in developing and releasing cultivars such as Arctic Green (released in 2007) and Polar Green (released in 2013).  Although these cultivars have improved winterhardiness, they still lack levels of winterhardiness necessary for long-term success in a cold climate.

A major constraint in the process of cultivar development is the selection of germplasm to be incorporated into the breeding program.  Screening large quantities of plant material is time consuming, cumbersome, and requires several years of evaluation in both the field and controlled environment chambers.  An improved screening method would facilitate the process of germplasm selection and cultivar development and release.

Metabolomics is a research technique that has recently been identified for use as a potential breeding tool.   Specifically, metabolomics allows for the detection of many the metabolites (such as carbohydrates and proteins) in the plant at one time.  The basis for using this technique in breeding comes from the fact that plants differ in their metabolic composition; therefore, unique metabolites or differences in metabolite amounts may serve as a way to screen and select for improved germplasm. 

To date, we have developed a metabolomics-assisted breeding method for screening perennial ryegrass plants for improved freezing tolerance.  In addition, this method has been used to screen and select plants for enhanced rust resistance.  Although still in the beginning phases, the utilization of metabolomics in the University of Minnesota turfgrass breeding program appears promising.