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27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
27 qtl discovery and-perspectives_e. van de weg
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27 qtl discovery and-perspectives_e. van de weg

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  • 1. PBA workshop, MSU JUNE’ 10 1 QTL Discovery & Perspectives of use of markers in fruit breeding programs
  • 2. Content  Introduction  QTL-Discovery  Perspectives for use  Example: Nectria (Canker) resistance  Summary PBA workshop, MSU JUNE’ 10 2
  • 3. Introduction  QTL discovery  Assessment of correlation trait ↔ molecular marker  Initial step towards Marker Assisted Breeding  Discovery  Validation  High Throughput markers  Logistics  Validation  Reproducibility on multiple families, pedigrees  Mode of action – Additive, Dominance – Gene x Gene interactions? Independent action?  Allelic diversity  Relative importance PBA workshop, MSU JUNE’ 10 3 R R R S S S
  • 4. Introduction  QTL Discovery  Assessment of correlation trait ↔ molecular marker  Requirements: 1. Trait of interest 2. Phenotypic data 3. Segregating germplasm 4. Marker data, genome-wide 5. QTL-mapping software PBA workshop, MSU JUNE’ 10 4
  • 5. QTL-Discovery in FruitBreedomics - Peach 1. Fruit related Traits PBA workshop, MSU JUNE’ 10 5 – Maturity time – Fruit Size – Flesh color – Firm/soft melting – Flesh adherence, – Titrable acidity – Total sugar – Flowering time – Flowering intensity – White anthers – Monilinia resistance 2. Phenotypic data  Historic • EU-Projects • National projects  New - FruitBreedomics 3. Segregating germplasm  18 families , ±1500 individuals  5 breeding programs, 2 countries 4. Marker Data  9K array
  • 6. QTL-Discovery in FruitBreedomics - apple 1. Fruit Quality Traits: > 10 PBA workshop, MSU JUNE’ 10 6  Fruit Quality – Taste • Firmness • Juiciness • Crispness • Total Sugar • Acidity – Storability – Shelf life – Harvest date – Fruit size – Skin Color  Resistance to Nectria 2. Phenotypic data  HiDRAS • 3 Years, Multiple time moments – Harvest, Storage 2 & 4M – Shelf Life: 2wks - 2M storage  National projects 3. Segregating germplasm  24 families , ±1600 individuals  6 breeding programs, 6 countries 4. Marker Data
  • 7. Discovery: Marker data  20K SNP array  New: available 2013 Jan 16  First marker data: Jan 18!  Great performance  Some SSR  previous projects  2013: Exciting year PBA workshop, MSU JUNE’ 10 7
  • 8. Perspectives: PBA workshop, MSU JUNE’ 10 8 Great perspectives • Many QTL discovered in EU-HiDRAS • Large intervals due to low marker density (# individuals high!) 25 56 77 0.0 0.2 0.4 1 1 14 24 51 67 0.0 0.2 0.4 2 19 24 43 76 0.0 0.2 0.4 3 2 18 32 55 73 0.0 0.2 0.4 4 8 14 20 34 45 47 69 90 100 107 0.0 0.2 0.4 5 9 40 78 0.0 0.2 0.4 6 26 35 0.0 0.2 0.4 7 18 33 52 62 0.0 0.2 0.4 8 24 42 59 69 0.0 0.2 0.4 0.6 9 13 14 40 50 64 81 104 0.0 0.2 0.4 10 13 29 45 51 61 76 0.0 0.2 0.4 12 3 18 30 45 64 89 0.0 0.2 0.4 13 8 23 37 77 110 116 0.0 0.2 0.4 15 8 14 30 47 76 0.0 0.2 0.4 16 0 12 23 25 35 55 91 100 0.0 0.2 0.4 17
  • 9. Validation & Marker development  On-going within FruitBreedomics  Development of SNP markers (WP1)  Firmness & Storability  2 genes involved in ethylene pathway  Relevance confirmed in multiple studies  Already in use for MAB • WSU, Russian programs PBA workshop, MSU JUNE’ 10 9
  • 10. Validation & Marker development: RosBREED  RosBREED project  US, USDA-SCRI  Multi State, International  Apple, Peach, Cherry, Strawberry  www.RosBREED.org  Validation apple  Acidity: • 2 loci, including Ma locus  Crispness, Juiciness (one LG)  Skin colour: Rf locus  Bitter pit: 3 loci  and others...  Validation Peach  Acidity  Sweetness  Maturity date  Fruit size  and others...
  • 11. Perspectives on use in breeding  Discovery : great potential  Validation : completed for 1st genes  Marker Development : started  Logistics : started  Enhancement through intercontinental collaborations?  RosBREED  Plant & Food Research PBA workshop, MSU JUNE’ 10 11
  • 12. Nectria Canker
  • 13. Introduction on Nectria PBA workshop, MSU JUNE’ 10 13  Causes canker in apple  Problem in NW-Europe (Humid climates)  Many (popular) cvs extremely susceptible  Braeburn, Cox, Gala, Kanzi, Rubens, Prima  Fungicides for Scab act also to Nectria  Problems with Nectria may increase  Scab resistance  Susceptible parents
  • 14. Introduction to Nectria  Breeding for resistance is hard  R – highly quantitative  Only few cultivars show reasonable resistance • Jonathan, Golden Delicious, Lombart’s Calvillle, Santana  Resistance tests are laborious and time-lasting  Availability of markers: highly useful  Difficult to develop PBA workshop, MSU JUNE’ 10 14
  • 15. Discovery  Germplasm  Jonathan x Prima • Jonathan: cv with highest level of resistance • Prima: highly susceptible: chopped down in biological production PBA workshop, MSU JUNE’ 10 15
  • 16. Discovery: National Project  Germplasm  Jonathan x Prima PBA workshop, MSU JUNE’ 10 16  Phenotyping  Artificial inoculation (1994)  Greenhouse: no 2nd infection  Colonization rate: Length of cankers in time (1996)
  • 17. Phenotypic data: Frequency Distribution Size of cankers (in mm) #progeny 0 5 10 15 20 25 30 35 56 4 8 12 16 20 24 28 32 36 40 44 48 52 60 64 68 72 76 1 28 25 16 12 5 4 2 1 13 30 18 8 6 3 1 4 5 3 1 11 1 11 1 • Prima: Large experimental variation Jonathan x Prima Jonathan Prima • JP-Population: sub-groups
  • 18. 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*29.7 E32M50-202-4 -55.7 E35M49-127-13 +63.3 E35M47-127-19-fD +63.4 E32M58-224-4 +65.9 P12-5 E31M48-150-18 -79.6 E32M58-316-2- 0.0 CH02g01-217+ 0.9 E31M52-127-15- 2.8 E31M52-127-10- 3.6 E34M51-164-6- 4.3 E32M52-120-9- 13.3 E31M48-100-23+ 26.7 E34M51-159-7+ 27.0 E33M47-140-12+ 31.6 E34M53-191-6 +0.0 E34M48-283-8 +5.2 E32M58-92-10 +5.8 E34M59-255-5-Pf +7.2 CH02g01-0/226 -9.1 E34M60-272-3 -26.5 E35M54-137-8 -35.7 E31M48-165-17 +50.7 E35M50-219-4 - E31M49-139-8 -62.7 E35M54-207-6 -63.0 CH03h03-91/103 +-63.4 E33M47-348-2 -66.6 CH05f04-162/158 +- E34M59-118-12 - 66.9 E35M58-134-5 - E31M52-158-8 - E33M47-165-10 - E34M48-419-4-fD - 67.1 E31M52-158-13 -67.7 E34M48-275-9- 0.0 E31M56-328-1- 3.9 E32M47-209-3+ 5.0 E34M48-182-15-pF-Fd- 10.2 E34M50-265-3- 11.0 E34M55-106-12- 20.7 E31M52-75-14- 22.0 CH05g11-243/233+- 22.7 CH04c07-112/114-+ 24.6 CH05d03-158/173+- 33.0 E31M56-188-3+ 33.3 E34M57-250-7-Fd+ 36.2 E34M60-290-2a-Fd+ 37.8 E34M54-340-19- 41.8 E34M55-167-8+ 43.1 E34M53-225-4- 43.6 E32M52-148-8- 46.9 E31M48-228-10 -0.0 E31M48-195-12 -10.9 CH04f06-175/178 -+ ***13.6 E34M48-179-16-Pf +15.1 E32M47-92-19 +16.1 E33M51-112-15 +16.7 E33M47-172-9 +19.7 E33M47-275-4 -27.3 CH05g11-243/0 +-32.8 CH04c07-106/108 -+33.8 CH05d03-152/179 -+43.2 E34M60-247-6 +44.9 E34M49-170-4 -45.6 E35M47-149-16-Pf-fD +47.3 E34M55-166-9 +47.8 E35M58-95-8 -58.6 J13 P13 J14 P14 *** +-***** ******** +-******** * E34M50-177-8- 0.0 CH05c06-104/118 16.3 E35M47-287-6- 17.1 CH05e04a-159/167 18.6 LY05b- 22.4 E32M52-264-4+ 34.1 E31M48-435-2- 42.0 E32M47-129-8+ 46.6 E34M47-198-4+ 46.7 E31M52-52-20+ E32M58-113-7+ 51.7 E35M53-91-8+ 55.6 E34M48-122-22+ 56.5 E32M48-51-18+ 56.9 E32M52-114b-10-pF- E34M59-243-7- 57.0 E35M54-388-16- 57.1 E35M61-218-5+ 57.3 CH05e04a-159/0 -+0.0 CH05c06-104/110 -+ ******0.2 E35M50-99-15 + ******3.4 E34M57-292-5 + *****10.4 E33M47-357-1 - ***21.8 E31M49-81-9 + ****26.0 CH05a04-163/183 +- ***27.8 E31M49-480-14 -48.0 E31M51-257-1 +49.0 E31M52-218-5 -56.2 E34M54-200-6 -59.8 E32M58-176-5-fD +61.5 E34M50-101-17 -61.6 E35M59-228-2 - E32M52-113-12-Pf -63.7 E35M49-108-16 +65.8 E32M52-330-3-Pf +65.9 E34M51-276-4 -67.0 E34M48-140-21 + E34M48-138-32 +67.4 E33M60-107-15-fD +67.9 E34M48-130-27 -79.0 J16 P16 E31M48-150-18 -79.6 E32M58-316-2- 0.0 CH02g01-217+ 0.9 E31M52-127-15- 2.8 E31M52-127-10- 3.6 E34M51-164-6- 4.3 E32M52-120-9- 13.3 E31M48-100-23+ 26.7 E34M51-159-7+ 27.0 E33M47-140-12+ 31.6 E34M53-191-6 +0.0 E34M48-283-8 +5.2 E32M58-92-10 +5.8 E34M59-255-5-Pf +7.2 CH02g01-0/226 -9.1 E34M60-272-3 -26.5 E35M54-137-8 -35.7 E31M48-165-17 +50.7 E35M50-219-4 - E31M49-139-8 -62.7 E35M54-207-6 -63.0 CH03h03-91/103 +-63.4 E33M47-348-2 -66.6 CH05f04-162/158 +- E34M59-118-12 - 66.9 E35M58-134-5 - E31M52-158-8 - E33M47-165-10 - E34M48-419-4-fD - 67.1 E31M52-158-13 -67.7 E34M48-275-9- 0.0 E31M56-328-1- 3.9 E32M47-209-3+ 5.0 E34M48-182-15-pF-Fd- 10.2 E34M50-265-3- 11.0 E34M55-106-12- 20.7 E31M52-75-14- 22.0 CH05g11-243/233+- 22.7 CH04c07-112/114-+ 24.6 CH05d03-158/173+- 33.0 E31M56-188-3+ 33.3 E34M57-250-7-Fd+ 36.2 E34M60-290-2a-Fd+ 37.8 E34M54-340-19- 41.8 E34M55-167-8+ 43.1 E34M53-225-4- 43.6 E32M52-148-8- 46.9 E31M48-228-10 -0.0 E31M48-195-12 -10.9 CH04f06-175/178 -+ ***13.6 E34M48-179-16-Pf +15.1 E32M47-92-19 +16.1 E33M51-112-15 +16.7 E33M47-172-9 +19.7 E33M47-275-4 -27.3 CH05g11-243/0 +-32.8 CH04c07-106/108 -+33.8 CH05d03-152/179 -+43.2 E34M60-247-6 +44.9 E34M49-170-4 -45.6 E35M47-149-16-Pf-fD +47.3 E34M55-166-9 +47.8 E35M58-95-8 -58.6 J13 P13 J14 P14 *** +-***** ******** +-******** * E34M50-177-8- 0.0 CH05c06-104/118 16.3 E35M47-287-6- 17.1 CH05e04a-159/167 18.6 LY05b- 22.4 E32M52-264-4+ 34.1 CH05e04a-159/0 -+0.0 CH05c06-104/110 -+ ******0.2 E35M50-99-15 + ******3.4 E34M57-292-5 + *****10.4 E33M47-357-1 - ***21.8 E31M49-81-9 + ****26.0 CH05a04-163/183 +- ***27.8 J16 P16 Marker data  AFLP & SSR  1998-2000
  • 19. QTL –mapping PBA workshop, MSU JUNE’ 10 19  Effect QTL:  Additive  Q1+Q2 -> Cankers as small as for Jonathan • Prima 47 mm • Jonathan: 23 mm • JxP_Q1Q2: 23 mm  Highly effective! 6 . 7 . 8 . 9 . 10 . 11 . 12 . 13 . 14 . 15 .P-Q38 . 9 . 10 . 11 . 12 . 13 . 14 . 15 . 16 . 17 . J-Q2. 12 . 13 . 14 . 15 . 16 . 17 . J-Q1  3 QTL identified  2x Jonathan, 1x Prima
  • 20. Fruitbreedomics PBA workshop, MSU JUNE’ 10 20 6 . 7 . 8 . 9 . 10 . 11 . 12 . 13 . 14 . 15 .P-Q38 . 9 . 10 . 11 . 12 . 13 . 14 . 15 . 16 . 17 . J-Q2. 12 . 13 . 14 . 15 . 16 . 17 . J-Q1  Position?  J-Q1 • No markers for distal part • Sub-optimum?  J-Q2 • 1 marker / 35 cM • Position?
  • 21. Fruitbreedomics Progresses on these historic data  Fine-mapping  Increase marker density PBA workshop, MSU JUNE’ 10 21 J01 J02 J03 J04 J05 J06 J07 J08 J09 J10 J11 J12 J13 J14 J15 J16 J17 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 • SNP-array: ±8000 markers for JxP • ±3000 for Jonathan
  • 22. Fruitbreedomics Progresses on these historic data  Fine-mapping  Increase marker density  Validation:  Reproducibility: 2nd mapping population  Extension  Stability over environments • Phenotype JxP in Sweden  Other parameters for resistance • Infection percentage Larisa Gustavsson Hilde Nybom
  • 23. Summary  Title: QTL Discovery & Perspectives of use of markers in fruit breeding programs  QTL Discovery 1st step to application  Discovery  Validation  High Throughput markers  Logistics  Assessment of correlation trait ↔ molecular marker  Potential - couple of years  Apple > 10 fruit quality traits + Nectria resistance  Peach > Flowering + Fruit traits + Monilinia resistance  Potential - short term (from / building on other projects)  Apple: Fruit firmness (ACS, ACO), Skin Color (Rf), Acidity (Ma), Bitter pit  Peach: Sub-acid/Acid, Flat/round (Peach/Nectarine, Yellow/white flesh)  Pipeline-Logistics: under development PBA workshop, MSU JUNE’ 10 23

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