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TL 1
Objective 3: Improve common bean productivity
for marginal environments in sub-Saharan Africa
Bodo Raatz
CIAT
Lisboa, September 2013
• .
Using markers for
biotic stress resistance
SNP genotpying:
Tm shift assay
A
G
from Wang et al. 2005°C
resistant
susceptible• Based on SNP-specific
primers
• Genotyping by melting
point analysis
• No fluorescent
primers required
C-A
BCMV: bc-3 candidate gene: eIF4E
NADERPOUR et al. MOLECULAR PLANT PATHOLOGY (2010)
primer 1
C
primer 2
A
primer reverse
BCMV: bc-3 Tms marker
resistent
susceptible
no call
all
Storage insects:
bruchid resistance
Bruchids (Zabrotes
subfasciatus)
PV-ATCT001, Yu et al, 2000
Dissociation Curve
APA gene
R
S
80 84
Common Bacterial Blight (CBB)
MAS with
• SU91 on Chr8 (Pedraza et al.
1997)
• SAP6 on Chr10 (Miklas et al.
2006)
Bacterial blight:
Xanthomonas
CBB resistance QTLs
Marker conversions
Chr Position G35346 AFR298 AND696 G10474 G40001 G5686 MD23-24 SEA5 VAX1
Chr01 219,278.00 T A A A A A A A A
Chr01 219,650.00 T C C C C C C C C
Chr01 219,722.00 T C C C C C C C C
Chr01 219,749.00 G A A A A A A A A
Chr01 219,950.00 C T T T T T T T T
Chr01 219,952.00 T A A A A A A A A
Chr01 220,668.00 T A A A A A A A A
Chr01 221,020.00 G C C C C C C C C
Chr01 252,386.00 C G G G G G G G G
Chr01 252,420.00 T A A A A A A A A
Chr01 253,519.00 A T T T T T T T T
Chr01 253,526.00 T G G G G G G G G
Chr01 253,542.00 C T T T T T T T T
Chr01 258,082.00 C G G G G G G G G
Chr01 264,339.00 C T T T T T T T T
Chr01 265,119.00 T G G G G G G G G
Chr01 265,168.00 T G G G G G G G G
Chr01 265,336.00 A G G G G G G G G
Chr01 265,418.00 C G G G G G G G G
Chr01 265,713.00 C T T T T T T T T
Chr01 265,722.00 C T T T T T T T T
Chr01 266,882.00 C A A A A A A A A
Chr01 267,398.00 A G G G G G G G G
Chr01 267,562.00 C A A A A A A A A
Chr01 267,688.00 T C C C C C C C C
Chr01 267,727.00 T A A A A A A A A
Chr01 268,418.00 C G G G G G G G G
Chr01 268,648.00 A C C C C C C C C
Chr01 271,111.00 A G G G G G G G G
Chr01 271,132.00 T C C C C C C C C
Chr01 271,437.00 A G G G G G G G G
Chr01 271,644.00 T C C C C C C C C
Chr01 272,223.00 G C C C C C C C C
Chr01 272,579.00 G A A A A A A A A
Chr01 272,645.00 G C C C C C C C C
Jorge et al
SNP sources:
• 1500 SNP set
BeanCAP
• 9 genotypes
sequenced
Angular Leaf Spot
Marker: Sc267437
Chr 8
G10474
Marker: P50
Chr. 4
G5686
• SNP based on SSR markers
confirmed and converted
• Finemapping on Chr 4
– Resistance gene 43.5 – 43.9 Mbp
42.0 42.5 43.0 43.5 44.0 44.5 45
0
2
4
6
8
Chromosome 4 (Mbp)
LODscore
Beat Keller, 2013
Bean Stem Maggot
• QTL mapping underway
• 100 additional SNPs genotyped (Daniel Ambachew)
• BSM evaluations in Zimbabwe, Malawi and Ethiopia
tolerant susceptible
Maps for DOR x BAT
SER16 x G35346
Drought tolerance
and root traits
-1
Yield Root traits
QTL analysis Federico Velasquez
Map for SEA x MD
MARS
• PhD thesis of Fitsum Alemayehu SARI,
Ethiopia
• Population of ~200 Lines
• Phenotyping drought & irrigated at 4
locations
– 2x Palmira, 2x Ethiopia
• Genotyping:
– Kbio/LGC ~150 SNP markers
– additional 14.000 fluidigmdata points
• Marker Analysis in progress
– DNAs sent, extracted from seed
(CAL 143xSAB 620) X SAB 626 (SAB 628xCAL 143) X SAB 659 (SAB 628xCAL 143) X SAB 686
G 12229 x AND 277
CAL143
(ABA 58x AFR298)F1xSAB258(COS 16 x AFR298)F1 x SAB258
SAB258 ABA58AFR298COS16
41 lines 54 lines 30 lines
26 lines 42 lines
F5
F5F1: CAL 143xSAB 620
F1: SAB 628xCAL 143
F1: ABA 58x AFR298
F1: COS 16 x AFR298F1F1F1
F1
F1
SAB620 SAB626 SAB628 SAB659 SAB686
MARS
Evaluation EvaluationEvaluation Evaluation
Population
development
F1
F2
F4
• QTL Analysis
• Select markers
F5
MARS
MARS
Evaluation EvaluationEvaluation Evaluation
Population
development
F1
F2
F4
• QTL Analysis
• Select markers
F5
MARS
• QTL Analysis
• Select markers
Genotype
F3
MARS
Genotype
evaluate
Select worst linesSelect best lines
• QTL Analysis
• Select markers
F4
F5
evaluate
F4
F5
F4
F5
evaluate
MARS Conventional
selection
Select worst linesSelect best lines
F3 F3
2nd MARS
crossing
cycle
•Select best lines
•Make new
crosses
MAGIC
• 8-parental population established
• F4:6 Phenotyping started in July
• Genotyping: DNA ready to send for GBS
SXB 412 INB 827 ALB 213 SEN 56 SCR 2 MIB 778 SCR 9 INB 841
79 F1 5 F1 38 F1 99 F1
323 F1
272 F1
728 F1
500 selected
499 F2
996 F3 families
926 F4.5 families
926 F4:6 families
MAGIC population in common bean
(mesoamerican gene pool)
Genotype individuals
Drought phenotyping
MAGIC
• 648 genotypes in current drought trial
Breeding products
Relationship between irrigated and rainfed grain yield of 36 common bean
genotypes grown under field conditions at CIAT-Colombia (2013)
AFR298
CAL143
CAL96
DAB 231
DAB 233
DAB 236
DAB 244
DAB 251
DAB 252
DAB 256
DAB 258
DAB 267
DAB 277
DAB 295
DAB 344
DAB 353
DAB 366
DAB 374DAB 380
DAB 384
DAB 396
DAB 398
DAB 402
DAB 441DAB 489 DAB 494 DAB 514
DAB 520 DAB 525
DAB 528
DAB 534
DAB 541
DAB 545
DAB 549
DAB 555
KATB1
0
200
400
600
800
1000
1200
2000 2500 3000 3500 4000 4500
droughtYDHA
irrigated YPDA
2013 YDHA
Data management
• Adopting defined file formats
• Adopting barcoding
• Adopting use of barcoding for seed storage
organization
• Training of partners to adopt defined file
formats
Sheet 1 Sheet 2
Trial data
Controlled vocabulary
trait dictionary
Metadata
• Sowing date
• Location
• Person in charge
Capacity building
• Workshop with 30+ breeders in
Kawanda
• 2 workshops at CIAT (n ~20)
• Fitsum Alemayehu (phd student,
Ethiopia) visited CIAT for 3 months.
Conclusions
• MAS for biotic stress moving toward routine
• MAGIC and MARS moving forward
• Advanced lines show improved yield under
drought
• Data Management moving towards adoption
• Capacity building ongoing
Anticipated impact: improved germplasm …
View to the future
• Unite TL 1 and TL2 activities
• Technology changes
– GBS: for fingerprinting, population genotyping
– genomic selection
• Fingerprinting / Forensics
– Specific projects need to be defined
– Impact studies
– software
• Organizational changes
– Extend work with partners
– Data management -software
– Links to
• Soils work, agronomy
• Other downstream activities
Thank you for your attention!
SARI Ethiopia
SARI SELIAN Tanzania
DARS Malawi
DR&SS Zimbabwe
KARI Kenya
CIAT Africa

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GRM 2013: Improve common bean productivity for marginal environments in sub-Saharan Africa -- B Raatz

  • 1. TL 1 Objective 3: Improve common bean productivity for marginal environments in sub-Saharan Africa Bodo Raatz CIAT Lisboa, September 2013
  • 2. • . Using markers for biotic stress resistance
  • 3. SNP genotpying: Tm shift assay A G from Wang et al. 2005°C resistant susceptible• Based on SNP-specific primers • Genotyping by melting point analysis • No fluorescent primers required
  • 4. C-A BCMV: bc-3 candidate gene: eIF4E NADERPOUR et al. MOLECULAR PLANT PATHOLOGY (2010) primer 1 C primer 2 A primer reverse
  • 5. BCMV: bc-3 Tms marker resistent susceptible no call all
  • 6. Storage insects: bruchid resistance Bruchids (Zabrotes subfasciatus) PV-ATCT001, Yu et al, 2000 Dissociation Curve APA gene R S 80 84
  • 7. Common Bacterial Blight (CBB) MAS with • SU91 on Chr8 (Pedraza et al. 1997) • SAP6 on Chr10 (Miklas et al. 2006) Bacterial blight: Xanthomonas
  • 9. Marker conversions Chr Position G35346 AFR298 AND696 G10474 G40001 G5686 MD23-24 SEA5 VAX1 Chr01 219,278.00 T A A A A A A A A Chr01 219,650.00 T C C C C C C C C Chr01 219,722.00 T C C C C C C C C Chr01 219,749.00 G A A A A A A A A Chr01 219,950.00 C T T T T T T T T Chr01 219,952.00 T A A A A A A A A Chr01 220,668.00 T A A A A A A A A Chr01 221,020.00 G C C C C C C C C Chr01 252,386.00 C G G G G G G G G Chr01 252,420.00 T A A A A A A A A Chr01 253,519.00 A T T T T T T T T Chr01 253,526.00 T G G G G G G G G Chr01 253,542.00 C T T T T T T T T Chr01 258,082.00 C G G G G G G G G Chr01 264,339.00 C T T T T T T T T Chr01 265,119.00 T G G G G G G G G Chr01 265,168.00 T G G G G G G G G Chr01 265,336.00 A G G G G G G G G Chr01 265,418.00 C G G G G G G G G Chr01 265,713.00 C T T T T T T T T Chr01 265,722.00 C T T T T T T T T Chr01 266,882.00 C A A A A A A A A Chr01 267,398.00 A G G G G G G G G Chr01 267,562.00 C A A A A A A A A Chr01 267,688.00 T C C C C C C C C Chr01 267,727.00 T A A A A A A A A Chr01 268,418.00 C G G G G G G G G Chr01 268,648.00 A C C C C C C C C Chr01 271,111.00 A G G G G G G G G Chr01 271,132.00 T C C C C C C C C Chr01 271,437.00 A G G G G G G G G Chr01 271,644.00 T C C C C C C C C Chr01 272,223.00 G C C C C C C C C Chr01 272,579.00 G A A A A A A A A Chr01 272,645.00 G C C C C C C C C Jorge et al SNP sources: • 1500 SNP set BeanCAP • 9 genotypes sequenced
  • 10. Angular Leaf Spot Marker: Sc267437 Chr 8 G10474 Marker: P50 Chr. 4 G5686 • SNP based on SSR markers confirmed and converted • Finemapping on Chr 4 – Resistance gene 43.5 – 43.9 Mbp 42.0 42.5 43.0 43.5 44.0 44.5 45 0 2 4 6 8 Chromosome 4 (Mbp) LODscore Beat Keller, 2013
  • 11. Bean Stem Maggot • QTL mapping underway • 100 additional SNPs genotyped (Daniel Ambachew) • BSM evaluations in Zimbabwe, Malawi and Ethiopia tolerant susceptible Maps for DOR x BAT SER16 x G35346
  • 12. Drought tolerance and root traits -1 Yield Root traits QTL analysis Federico Velasquez Map for SEA x MD
  • 13. MARS • PhD thesis of Fitsum Alemayehu SARI, Ethiopia • Population of ~200 Lines • Phenotyping drought & irrigated at 4 locations – 2x Palmira, 2x Ethiopia • Genotyping: – Kbio/LGC ~150 SNP markers – additional 14.000 fluidigmdata points • Marker Analysis in progress – DNAs sent, extracted from seed
  • 14. (CAL 143xSAB 620) X SAB 626 (SAB 628xCAL 143) X SAB 659 (SAB 628xCAL 143) X SAB 686 G 12229 x AND 277 CAL143 (ABA 58x AFR298)F1xSAB258(COS 16 x AFR298)F1 x SAB258 SAB258 ABA58AFR298COS16 41 lines 54 lines 30 lines 26 lines 42 lines F5 F5F1: CAL 143xSAB 620 F1: SAB 628xCAL 143 F1: ABA 58x AFR298 F1: COS 16 x AFR298F1F1F1 F1 F1 SAB620 SAB626 SAB628 SAB659 SAB686 MARS
  • 17. MARS • QTL Analysis • Select markers
  • 18. Genotype F3 MARS Genotype evaluate Select worst linesSelect best lines • QTL Analysis • Select markers F4 F5 evaluate F4 F5 F4 F5 evaluate MARS Conventional selection Select worst linesSelect best lines F3 F3 2nd MARS crossing cycle •Select best lines •Make new crosses
  • 19. MAGIC • 8-parental population established • F4:6 Phenotyping started in July • Genotyping: DNA ready to send for GBS
  • 20. SXB 412 INB 827 ALB 213 SEN 56 SCR 2 MIB 778 SCR 9 INB 841 79 F1 5 F1 38 F1 99 F1 323 F1 272 F1 728 F1 500 selected 499 F2 996 F3 families 926 F4.5 families 926 F4:6 families MAGIC population in common bean (mesoamerican gene pool) Genotype individuals Drought phenotyping
  • 21. MAGIC • 648 genotypes in current drought trial
  • 22. Breeding products Relationship between irrigated and rainfed grain yield of 36 common bean genotypes grown under field conditions at CIAT-Colombia (2013) AFR298 CAL143 CAL96 DAB 231 DAB 233 DAB 236 DAB 244 DAB 251 DAB 252 DAB 256 DAB 258 DAB 267 DAB 277 DAB 295 DAB 344 DAB 353 DAB 366 DAB 374DAB 380 DAB 384 DAB 396 DAB 398 DAB 402 DAB 441DAB 489 DAB 494 DAB 514 DAB 520 DAB 525 DAB 528 DAB 534 DAB 541 DAB 545 DAB 549 DAB 555 KATB1 0 200 400 600 800 1000 1200 2000 2500 3000 3500 4000 4500 droughtYDHA irrigated YPDA 2013 YDHA
  • 23. Data management • Adopting defined file formats • Adopting barcoding • Adopting use of barcoding for seed storage organization • Training of partners to adopt defined file formats Sheet 1 Sheet 2 Trial data Controlled vocabulary trait dictionary Metadata • Sowing date • Location • Person in charge
  • 24. Capacity building • Workshop with 30+ breeders in Kawanda • 2 workshops at CIAT (n ~20) • Fitsum Alemayehu (phd student, Ethiopia) visited CIAT for 3 months.
  • 25. Conclusions • MAS for biotic stress moving toward routine • MAGIC and MARS moving forward • Advanced lines show improved yield under drought • Data Management moving towards adoption • Capacity building ongoing Anticipated impact: improved germplasm …
  • 26. View to the future • Unite TL 1 and TL2 activities • Technology changes – GBS: for fingerprinting, population genotyping – genomic selection • Fingerprinting / Forensics – Specific projects need to be defined – Impact studies – software • Organizational changes – Extend work with partners – Data management -software – Links to • Soils work, agronomy • Other downstream activities
  • 27. Thank you for your attention! SARI Ethiopia SARI SELIAN Tanzania DARS Malawi DR&SS Zimbabwe KARI Kenya CIAT Africa