WheatSustain - Knowledge-driven genomic predictions for sustainable disease resistance in wheat
Background
Progress i plant breeding is based on the ability to do precise selection of new offsprings with desired traits. Traditionally, this is done by testing of large populations in field trials over multiple years and locations. This is both costly and time consuming. Genomic selection is a relatively new method that makes it possible to use maker data to predict the breeding value of new breeding lines based on statistical models.
There is a large potential to save both time and money, if the models are reliable. The prediction models are built by genotyping a training population with thousands of anonymous markers and modelling the effects of these markers based on available phenotypic data for the same lines. This approach, although effective in many cases, ignores the huge wealth of knowledge about known genes and their effects on the phenotype.
Objective
The core idea behind WheatSustain is to incorporate the knowledge of known genes and their mode of action in the genomic prediction models that are used in plant breeding to make them more reliable. As cases for the project, we have chosen wheat, which is the largest cereal crop in Europe, and resistance to two important diseases, fusarium head blight and yellow rust (syn: stripe rust), which each illustrates important challenges that need to be resolved in order to make genomic selection into an effective and reliable selection tool in plant breeding.
More about the project
The project is based on cross-disciplinary international collaboration among leading research groups and wheat breeding programs in Norway, Ireland, Germany, Austria, Mexico, USA and Canada.
The project is organized in six work packages:
- WP1: Creating joint phenotypic and genotypic data sets (WP leader: Julio Isidro-Sánchez, UCD, Ireland )
- WP2: Comparing alternative GS strategies by computer simulations (WP leader: Theo Meuwissen, NMBU)
- WP3: Proof-of-principle case: FHB (WP leader: Hermann Bürstmayr, BOKU, Austria)
- WP4: Proof-of-principle case: stripe rust (WP leader: Hermann Bürstmayr, BOKU, Austria)
- WP5: Validation of prediction models (WP leader: Lorenz Hartl, LfL, Germany)
- WP6: Project management and dissemination (WP leader: Morten Lillemo, NMBU)
Participants
External participants
Hermann Bürstmayr, BOKU, Austria
Sebastian Michel, BOKU, Austria
Barbara Steiner, BOKU, Austria
Laura Morales, BOKU, Austria
Lorenz Hartl, LfL, Germany
Volker Mohler, LfL, Germany
Melanie Stadlmeier, LfL, Germany
Julio Isidro Sanchez, UCD, Ireland
Curt McCartney, AAFC, Canada
Maria Antonia Henriquez, AAFC, Canada
Yong-Bi Fu, AAFC, Canada
Ron Knox, AAFC, Canada
Richard Cuthbert, AAFC, Canada
Vijai Bhadauria, AAFC, Canada
Jose Crossa, CIMMYT, Mexico
Deniz Akdemir, StatGen Consulting, USA