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- 1. Mogens Støvring Hovmøller, Sajid Ali, Stephanie Walter, Chris K Sørensen, Mehran Patpour, Yan-Yun Chen, Tine Thach, Julian R Algaba, Poul Lassen, Jens G Hansen and Annemarie F Justesen, Global Rust Reference Center: Achievements and challenges ahead in breeding for stripe rust resistance in wheat
- 2. Outline • Facilities: People, space and resources • The Scandinavian “early-warning” system • Current stripe rust situation in Europe • Story of the “Warrior” race in Europe, • Lessons learnt from 25 years of yellow/stripe rust research
- 3. International collaborators • Kumarse Nazari, ICARDA • Amor Yahyaoui, ICARDA • Ravi Singh, CIMMYT • Dave Hodson, CIMMYT • Claude Pope, INRA (F) • Jonathan Yuen, Uppsala University (S) • Cristobal Uauy, JIC (UK) • Rosemary Bayles, NIAB (UK) • Kerstin Flath, JKI (D) • James Brown, JIC(UK) • > 40 people who submitted wheat rust samples from Asia, Africa and South America GRRC-team March 2014
- 5. GRRC green house & lab space, April 2014 • 7 quarantine zones (8-12 cabins/zone) • 3 pathogen labs • 1 molecular lab • N2 storage facility • Flakkebjerg: 150 ha field experimental area
- 6. Attack in previous resistant variety (OBS-nurseries, extension, farmers fields, etc.) GRRC Multiplication of spores samples from infected plants Year 0 Year 1 Year 2 and later The ”Scandinavian model” for yellow/stripe rust early-warning
- 7. Attack in previous resistant variety (OBS-nurseries, extension, farmers fields, etc.) GRRC Multiplication of spores samples from infected plants Year0 The ”Scandinavian model” for yellow/stripe rust early-warning • Spore samples stored in N2 isolate bank • DNA fingerprint: Laboratory • Race testing: Seedlings in green house, (& test for aggressiveness)
- 8. Attack in previous resistant variety (OBS-nurseries, extension, farmers fields, etc.) GRRC Multiplication of spores samples From infected plants Year 0 The ”Scandinavian model” for yellow/stripe rust early-warning • Spore samples stored in N2 isolate bank • DNA fingerprint: Laboratory • Race testing: Seedlings in green house, (& test for aggressiveness) • Interpretation of results in EU/global context • Publication on-line: • www.wheatrust.org If ”new” raceMutiplication of additional spore samples
- 9. Attack in previous resistant variety (OBS-nurseries, extension, farmers fields, etc.) GRRC Multiplication of spores samples From infected plants Year 0 The ”Scandinavian model” for yellow/stripe rust early-warning • Spore samples stored in N2 isolate bank • DNA fingerprint: Laboratory • Race testing: Seedlings in green house, (& test for aggressiveness) • Interpretation of results in EU/global kontekst • Publicering on-line: www.wheatrust.org If ”new” raceMutiplication of additional spore samples Private plant breeding companies: Screening for resistance using new (and other) races GRRC: Inoc. Nurseries using the new race green house/ field Year 1
- 10. Attack in previous resistant variety (OBS-nurseries, extension, farmers fields, etc.) GRRC Multiplication of spores samples From infected plants Year 0 The ”Scandinavian model” for yellow/stripe rust early-warning • Spore samples stored in N2 isolate bank • DNA fingerprint: Laboratory • Race testing: Seedlings in green house, (& test for aggressiveness) • Interpretation of results in EU/global context • Publication on-line: www.wheatrust.org If ”new” raceMutiplication of additional spore samples Rust susceptibility to new race in breeding lines and varieties Disease management recommendations: • Crop protection on-line resistance grouping • Extension leaflets • Annual report of variety trials (October) • Articles newspapers/ magazines • Oral presentations Year 1
- 11. Attack in previous resistant variety (OBS-nurseries, extension, farmers fields, etc.) GRRC Multiplication of spores samples From infected plants Year 0 The ”Scandinavian model” for yellow/stripe rust early-warning • Spore samples stored in N2 isolate bank • DNA fingerprint: Laboratory • Race testing: Seedlings in green house, (& test for aggressiveness) • Interpretation of results in EU/global kontekst • Publicering on-line: www.wheatrust.org If ”new” raceMutiplication of additional spore samples Rust susceptibility to new race in breeding lines and varieties Disease management recommendations: • Crop protection on-line resistance grouping • Extension leaflets • Annual report of variety trials (October) • Articles newspapers/ magazines • Oral presentations Year 1 Year 2 and later ongoing • Release of new resistant varieties • Variety testing (yield, quality, resistance) • Marketing and seed multiplication (Denmark: 25-30% of recommended list varieties are exchanged every year)
- 12. The current Stripe rust situation in Europe Triticale, Denmark, 11th March, 2014
- 13. The current Stripe rust situation in Europe Wheat: The Nederlands, 1st April 2014 Photo: Wopke van der Werf
- 14. Race dynamics of P. striiformis in Europe 2000-2013
- 15. Pie chart Spatial distribution of races 2010-2013
- 16. Case study: Origin, spread and distribution of the Warrior race Methodology Selection of isolates Part A • Representative isolates of the Warrior race 2011-2013 [Spain, France, Germany, United Kingdom, Denmark, Sweden] • Representative isolates of non-Warrior races 2000-2010 [European origin] • Representative isolates from epidemic sites in Central Asia 2010-2012 [Uzbekistan, Tajikistan] Part B • Reference isolates from global study representing 6 continents 2005- 2010 (Ali et al., 2014) , including recombining populations from the Himalayan region “Center of diversity”
- 17. Case study: Origin, spread and distribution of the Warrior race Methodology Isolate characterization Part A isolates • Race phenotyped in national labs: France, Germany, UK • GRRC: Denmark, Sweden, Spain, Portugal, Uzbekistan, Tajikistan some overlaps of isolates and differential seeds between national labs and GRRC • SSR genotyped at GRRC/Uppsala, using 16 of 20 SSR markers from Ali et al., 2014 Part B isolates • Genotyping results from Ali et al. 2014 (INRA-Grignon, France) aligned with results for Part A isolates One common dataset developed
- 18. Case study: Origin, spread and distribution of the Warrior race Results • Race phenotyping: One dominant race, another group was identified based on supplementary differentials, occasional small differences at the quantitative level for specific differentials • SSR genotyping: One dominant MLG, at least two others were identified • No isolates in the „Global set‟ (Ali et al. 2014) covering six continents had a matching race/SSR genotype • Never detected in GRRC surveyed areas
- 19. K2 K3 K4 K5 K6 K7 K8 K9 K10 G1 G2 G3 G4 G5 G6 Central Asia 2010- 2013 Europe 2011- 2013 Worldwide groups following Ali et al. 2014: PLOS Pathogens
- 20. K2 K3 K4 K5 K6 K7 K8 K9 K10 G1 G2 G3 G4 G5 G6 Central Asia 2010- 2013 Europe 2011- 2013 Worldwide groups following Ali et al. 2014: PLOS Pathogens
- 21. Case study: Origin, spread and distribution of the Warrior race Question 1: Mutant/recombinant within the existing European Pst pop. No, Warrior is not a NW European type strain – many alleles exotic to EU pop Question 2: Does Warrior represent a recent invasion into Europe from the central Asian 2010 and onward epidemics? No, although sharing some alleles with central Asian population. CA pop was distinct, and Warrior type isolates were not re-sampled in Central Asia Question 3: What is the likely origin or the Warrior race? Closely related but still divergent from the predominant Chinese population (the exact race/SSR genotype not represented in previous studies
- 22. Chris Sørensen
- 23. Lessons learnt • Ongoing, pathogen phenotyping necessary for rapid detection of new pathogen variability (challenging – without coordinated reference collections/materials/labs – it may not work)
- 24. Lessons learnt • Ongoing, pathogen phenotyping necessary for rapid detection of new pathogen variability (challenging – without coordinated reference collections/materials/labs – it may not work) • Race phenotyping not sufficient for understanding spread and evolution • Molecular genotyping/sequencing not sufficient for getting the relevant information concerning host „susceptibility‟ • Assessment of quantitative traits important (e.g., adaptation to warm environments) but labor intensive • Rapid responses (and reporting) essential
- 25. Lessons learnt • Ongoing, pathogen phenotyping necessary for rapid detection of new pathogen variability (challenging – without coordinated reference collections/materials/labs – it may not work) • Race phenotyping not sufficient for understanding spread and evolution • Molecular genotyping/sequencing not sufficient for getting the relevant information concerning host „susceptibility‟ • Assessment of quantitative traits important (e.g., adaptation to warm environments) but labor intensive • Rapid responses (and reporting) essential • Rapid pathogen spread – Rapid pathogen evolution at all levels • Center of diversity in “Himalayan region” – clonal reproduction most other places • Diversity for disease resistance in the host important, - R-genes with minor effects may also be „overcome‟ but at a slower rate • Avoid “rust suckers”
- 27. Helsingør (30 km N Copenhagen), Denmark, July 5-8, 2015
Notas del editor
- Data management system developed by Aarhus University, Denmark in collaboration with BGRI / FAOSits on top of a centralized Crop Problem Dbase – currently holds survey and pathotype data but will be expanded to include trap nursery and molecular diagnostic data. Flexible dbase capable of holding all 3 rust diseases – expansion in progress to incorporate yellow rust data.Toolbox permits: user management (different access / permission levels); on-line data entry; data quality control and publishingOutputs: Series of data-base driven graphical tools. Currently: survey mapping, pathotype frequencies and distributions over time. Additional tools planned for the future. All outputs as iframes so seemelessly embedded in external websites eg Rust SPORE at FAO.Standard data export / exchange permitting direct connection to external applications eg RustMapper at CIMMYT.
- Data management system developed by Aarhus University, Denmark in collaboration with BGRI / FAOSits on top of a centralized Crop Problem Dbase – currently holds survey and pathotype data but will be expanded to include trap nursery and molecular diagnostic data. Flexible dbase capable of holding all 3 rust diseases – expansion in progress to incorporate yellow rust data.Toolbox permits: user management (different access / permission levels); on-line data entry; data quality control and publishingOutputs: Series of data-base driven graphical tools. Currently: survey mapping, pathotype frequencies and distributions over time. Additional tools planned for the future. All outputs as iframes so seemelessly embedded in external websites eg Rust SPORE at FAO.Standard data export / exchange permitting direct connection to external applications eg RustMapper at CIMMYT.
- Data management system developed by Aarhus University, Denmark in collaboration with BGRI / FAOSits on top of a centralized Crop Problem Dbase – currently holds survey and pathotype data but will be expanded to include trap nursery and molecular diagnostic data. Flexible dbase capable of holding all 3 rust diseases – expansion in progress to incorporate yellow rust data.Toolbox permits: user management (different access / permission levels); on-line data entry; data quality control and publishingOutputs: Series of data-base driven graphical tools. Currently: survey mapping, pathotype frequencies and distributions over time. Additional tools planned for the future. All outputs as iframes so seemelessly embedded in external websites eg Rust SPORE at FAO.Standard data export / exchange permitting direct connection to external applications eg RustMapper at CIMMYT.
- Data management system developed by Aarhus University, Denmark in collaboration with BGRI / FAOSits on top of a centralized Crop Problem Dbase – currently holds survey and pathotype data but will be expanded to include trap nursery and molecular diagnostic data. Flexible dbase capable of holding all 3 rust diseases – expansion in progress to incorporate yellow rust data.Toolbox permits: user management (different access / permission levels); on-line data entry; data quality control and publishingOutputs: Series of data-base driven graphical tools. Currently: survey mapping, pathotype frequencies and distributions over time. Additional tools planned for the future. All outputs as iframes so seemelessly embedded in external websites eg Rust SPORE at FAO.Standard data export / exchange permitting direct connection to external applications eg RustMapper at CIMMYT.
- Data management system developed by Aarhus University, Denmark in collaboration with BGRI / FAOSits on top of a centralized Crop Problem Dbase – currently holds survey and pathotype data but will be expanded to include trap nursery and molecular diagnostic data. Flexible dbase capable of holding all 3 rust diseases – expansion in progress to incorporate yellow rust data.Toolbox permits: user management (different access / permission levels); on-line data entry; data quality control and publishingOutputs: Series of data-base driven graphical tools. Currently: survey mapping, pathotype frequencies and distributions over time. Additional tools planned for the future. All outputs as iframes so seemelessly embedded in external websites eg Rust SPORE at FAO.Standard data export / exchange permitting direct connection to external applications eg RustMapper at CIMMYT.