Izmir 2014 lesley boyd


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Izmir 2014 lesley boyd

  1. 1. New strategies and technologies in breeding for durable stripe (yellow) rust resistance in wheat 2nd International Wheat Stripe Rust Symposium, 28th April -1st May 2014, Izmir, Turkey Dr Lesley A. Boyd, Research Group Leader, National Institute of Agricultural Botany (NIAB), Cambridge, UK
  2. 2. Informed resistance breeding The plant recognises universal, common factors produced by the pathogen: PAMPS Pathogen produces unique effectors that modify the plant environment and suppress plant defence Disease Effector-triggered immunity-ETI Some effectors become Avir genes, recognised by the plant’s R-genes Pattern- Recognition Receptor (PRR) R-gene PTI and ETI lead to the induction of common defence processes, which include the genes that confer durable, partial, adult plant resistance PAMP-triggered immunity -PTI Boyd et al Trends in Genetics 2013 PRR
  3. 3. Informed resistance breeding Non-Host resistance and PTI ERA-PG project: TritNONHOST (2009-2012) and ERA- CAP project: DURESTrit (2014-2017) Co-ordinator Dr Patrick Schweizer, IPK, Gatersleben, Germany TritNONHOST team Patrick’s group
  4. 4. 0 20 40 60 80 100 120 140 160 180 pIPKTA9 pG Y1_TaPERO BAC _632F23 BAC _LRR _Kin pIPKTA9_LRR _Kin pIPKTA9 pG Y1_TaPERO BAC _632F23 BAC _LRR _Kin pIPKTA9_LRR _Kin Rel.haustoriumindex(%) Barley-Bgh Wheat-Bgt Expression of HvRNR8 confers partial resistance in wheat but has no effect in barley
  5. 5. Informed resistance breeding: RNR8 story 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 control chitin 60' chitin 180' Control non infiltrated TaRNR8 chitin induced 0 0.5 1 1.5 2 2.5 3 3.5 4 control 60 Flag 60 Flag180 TaRNR8 flagellin induced TaRNR8 transcript levels in the wheat cv Renan
  6. 6. Non-Host Resistance summary: RLKs are a complex group of proteins that potentially play different roles in host- and nonhost interactions  RLKs such as RNR8 may encode upstream components of NHR that escape effector suppression It may therefore be possible to select or engineer non-host-like pathogen resistance into crops such as wheat Transgenic wheat lines o/e HvRNR8 and silenced for TaRNR8 will be tested for resistance towards muliple pathogens Within DURESTrit we have 3 more LRR_RLK with similar transient phenotypes
  7. 7. Identification and exploitation of natural variation in disease resistance The BBSRC wheat pre-breeding program is divided into 4 pillars (Landraces, Synthetics, Alien Introgression, Elite Wheat) and 2 themes (Phenotyping and Genotyping). PILLAR 1 Landraces PILLAR 2 Synthetics PILLAR 3 Wild relative PILLAR 4 Elite Genotyping Phenotyping BBSRC Funded Wheat breeders
  8. 8. Identification and exploitation of natural variation in disease resistance • Historically new sources of R-gene resistance have been identified from the 1O, 2O and often the 3O wheat gene pool. • Within the WISP project, Ian and Julie King at Nottingham University have made over 17,000 crosses between hexaploid wheat and diploid relative. • At NIAB we have created synthetic hexaploid wheats from crossing tetraploid wheat to Ae. tauschii accessions first characterised by FIGS (Focused Identification of Germplasm Strategy) to identify environmental selection diversity and by DNA markers to determine genetic diversity. • Simon Griffiths, NRP, Norwich is exploring the 1o gene pool within the Watkin’s landrace collection. e.g. Yr51 (Bariana et al TAG 2013) • Keith Edwards at Bristol University has developed both SNP array and SNP markers using KASPar technology that support the genomic identification of valuable genetic regions. •Working with UK wheat breeders these materials are crossed back to elite UK winter wheats.
  9. 9. Informed resistance breeding In wheat over 60 stripe rust resistance loci have been assigned a Yr designation, while some 140 QTL for stripe rust resistance have been reported in the literature, located to 49 chromosomal regions through consensus mapping (Wellings et al 2013, Rosewarne et al TAG 2013)
  10. 10. Identification and exploitation of natural variation in disease resistance: QTL How do we identify the Lr34/Yr18/Pm38 complex-like genes, i.e. those that restrict pathogen invasion, growth and reproduction?
  11. 11. Objective of TritNONHOST 11 wheat barley powdery mildew Blumeria graminis f. sp. tritici host: wheat, nonhost: barley Blumeria graminis f. sp. hordei host: barley, nonhost: wheat rust Puccinia triticina host: wheat, nonhost: barley Puccinia hordei host: barley, nonhost: wheat blast Magnaporthe oryzae host: wheat and barley new Magnaporthe species nonhost: wheat and barley JamesKolmer,USDAARS
  12. 12. General pathogen-regulated genes 12 wheatbarley Blumeria 5570 Magnaporthe 3252 Puccinia 3763 Blumeria 4811 Magnaporthe 2777 Puccinia 10756 The general response of wheat and barley against different pathogen species utilizes common pathways  PAMP-triggered immunity functional categories in MapMan functional categories in MapMan 1276 1573
  13. 13. Identification and exploitation of natural variation in disease resistance: QTL MAGIC populations An innovative approach to dissecting the genetic control of complex traits in wheat Alison Bentley, P Howell, J Cockram, G Rose, T Barber, R Horsnell, N Gosman, P Bansept, M Scutari, A Greenland and I Mackay
  14. 14. Mapping in multi-founder experimental populations MAGIC Multi-parent Advanced Genetic InterCross • Genetically diverse population, bringing-in multiple alleles and allowing for multiple recombination events. • Good for identifying multiple interacting genetic loci and traits. • Allows for greater precision in mapping of QTL. 28210315 descendants of Founder 1
  15. 15. The NIAB Elite MAGIC population Focus on mapping QTL segregating in current elite UK germplasm Variety Reason for inclusion Alchemy Yield, disease resistance, soft feed Brompton 1BL/1RS, hard feed type, OWBM resistance Claire Slow apical development, soft biscuit/distilling type Hereward High quality benchmark Gp1 bread making type Rialto 1BL/1RS, Gp2 moderate bread making type Robigus High yielding, soft biscuit/distilling type, OWBM resistance Soissons Early flowering French Gp2 bread making type Xi19 Facultative, high quality Gp1 bread making type 90K SNP array NIAB Elite MAGIC population allele freqs in lines (AAm * 2 + ABm)/((AAm + ABm + BBm) * 2) Frequency 0.2 0.4 0.6 0.8 1.0 020406080100 Potential frequency of an allele in the MAGIC population
  16. 16. Yellow rust resistance in NIAB MAGIC population 22nd August 2011 ‘Warrior’ Pst race
  17. 17. Yellow rust resistance in NIAB MAGIC population 0 1 2 3-4 95-6 7-8 Yellow rust glasshouse seedling test using the ‘Warrior’ race
  18. 18. MAGIC line means BLUP (log2) Frequency 0.0 0.5 1.0 1.5 2.0 2.5 3.0 050100150200250300 Parent 1 Hereward Parent 2 Robigus Resistant progeny Yellow rust resistance in NIAB MAGIC population Yellow rust glasshouse seedling tests – distribution of disease scores BLUP (log2 adjusted scores) Frequency
  19. 19. Yellow rust resistance in NIAB MAGIC population Yellow rust field assessment – natural infection 1 2 3 4 5 6 7 Glasshouse and field (yellow rust) disease scores field yellow rust yellowrustseedlingtest Field YR scores SeedlingYRscores MAGIC lines showing more yellow rust resistance in the seedling tests than the most resistant founder parent, cultivar Hereward, also showed higher levels of resistance in the field
  20. 20. Yellow rust resistance in NIAB MAGIC population Mapping hits – Yellow rust seedling and field tests Gp 1 Gp 2 Gp 3 Gp 4 Gp 5 Gp 6 Gp 7 unlinked -log10(P) Gp 1 Gp 2 Gp 3 Gp 4 Gp 5 Gp 6 Gp 7 unlinked -log10(P) Seedling resistance Field resistance
  21. 21. Yellow rust resistance in NIAB MAGIC population 3 large effects observed 0 2 RAC875_c50347_258 genotype class log2yellowrust Estimates (Intercept) 1.0283 SNP 1 0.6476 SNP 2 0.4223 SNP 3 0.4069 SNP 1 SNP 1: “0” allele is associated with lower levels of yellow rust infection, i.e. resistant allele
  22. 22. Favourable alleles are dispersed Yellow rust resistance in NIAB MAGIC population Lines showing transgressive segregation for yellow rust resistance.
  23. 23. Informed resistance breeding: Summary • There is still potential for the identification of new sources of R-gene resistance with the 1O, 2O and the 3O wheat gene pool. • In addition, a better understanding of the primary interaction between pathogen and host (PTI and NHR) could lead to novel targets for resistance breeding. • While the plant gene targets of effectors and the genetic pathways responsible for resistance provide targets for genetic modification.
  24. 24. Acknowledgements TritNONHOST team: • Dr. Patrick Schweizer • Jeyaraman Rajaraman • Dr. Lesley Boyd • Dr. Graham McGrann • Dr. Francesca Stefanato • Dr. Rients Niks • Dr. Reza Aghnoum • Dr. Sajid Rehman • Dr. Ulrich Schaffrath • Rhoda Delventhal Additional collaborators: • Dr. Pete Hedley • Dr. Björn Usadel • Dr. Pamela Abbruscato Wheat MAGIC population: • Alison Bentley • Phil Howell • James Cockram • Gemme Rose • Toby Barber • Richard Horsnell • Nick Gosman • Pauline Bansept • M Scutari • Andy Greenland • Ian Mackay Pyramiding disease resistance QTLs: • Mike Grimmer • Sara Clarke • Neil Paveley PAMP-Triggered Immunity: • Chris Ridout • Hank-jan Schoonbeek SCPRID team: • Prof. Sakkie Pretorius • Dr . Renee Prins • Dr. Gloudi Agenbag • Dr. Peter Njau • Dr. Godwin Macharia • Dr. Ruth Wanyera • Ms. Ngina Waweru