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 CurveAPA 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)

LOD

scor

e

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 ABA58 AFR298 COS16

41 lines 54 lines 30 lines

26 lines 42 lines

F5

F5 F1: CAL 143xSAB 620 F1: SAB 628xCAL 143

F1: ABA 58x AFR298 F1: COS 16 x AFR298 F1 F1 F1

F1 F1

SAB620 SAB626 SAB628 SAB659 SAB686

MARS

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 374 DAB 380

DAB 384

DAB 396

DAB 398

DAB 402

DAB 441 DAB 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

drou

ght Y

DHA

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