WheatSustain

WheatSustain - Knowledge-driven genomic predictions for sustainable disease resistance in wheat

SusCrop ERA-NET project focusing on improving genomic selection for disease resistance in wheat by using knowledge about genes and their functions to make more reliable predictions.

WheatSustain
01. Apr 2019 - 31. des 2022
SusCrop ERA-NET
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

Morten Lillemo
Morten Lillemo
Project coordinator.
Min Lin
Min Lin
Postdoc. Involved in the research on yellow rust resistance.
Vinay Nannuru
Vinay Nannuru
Project PhD student. Doing research on FHB resistance.
Theodorus Meuwissen
Theodorus Meuwissen
Work Package leader - WP2: Comparing alternative GS strategies by computer simulations

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