1. TL1 meeting
Progress in Objective 3:
Common beans
Bodo Raatz, CIAT
Addis Ababa, May 2012
1

2. Road map
• Ethiopian program
• SNPs
– QTLs in the making in MAGIC, MARS,
association mapping
• Markers in application MAS
• Phenotyping
2

3. Mesoamerican Andean
Gene Pool Gene Pool
Cultivated common
bean:
• Two major gene
pools
• Specific grain
classes
…that define the
structure of breeding
programs
3

4. Activity 2: SNP assay
• Collaboration with USDA-Beltsville, mediated
by Xavier
• 1500 SNPs converted to Kaspar (Kbio)
• SNPs chosen that are polymorphic within gene
pools and grain classes
• 94 lines genotyped (Milestone 2)
4

5. Activity 2: SNP assay
Phylogeny analysis … genotypes
markers
Mesoamerican
Andean
Phaseolus coccineus
Phaseolus acutifolius
5

6. Activity 5.1: MARS
PhD thesis of Fitsum Alemayehu SARI, Ethiopia
Sister lines SABs 626, CAL 143
628, 659, 686 – Released in 6
– Drought X countries in southern
Africa
– Improved
remobilization? – Vegetative vigor
– Tolerant of poor soils
• 165 markers selected for genotyping
• Results in analysis
6

7. Activity 5.1: MARS genotyping
1 2 3 4
BARC-PV-0000055
sc01018ln115966_70654_C_T_3130
sc01018ln115966_84234_C_T_3130
1.4
sc00244ln360837_151643_G_T_157 1.2 sc00518ln214431_82881_A_G_2346
sc00244ln360837_80567_T_C_1578 2.1 sc00518ln214431_38754_C_T_2345
0.4 sc00334ln300981_254308_G_A_187 sc00831ln140879_35627_G_A_2890 sc00377ln276023_97213_T_G_2002 1.0 sc00112ln569344_270381_C_T_979
1.0 0.3 sc00112ln569344_446130_C_T_981
0.7 sc00334ln300981_202658_C_T_187
0.4 sc00112ln569344_538657_G_A_982
10.1 sc00964ln122791_59538_A_C_3065 0.4 sc00835ln140787_95095_C_T_2896
sc00429ln249479_88921_A_G_2138 0.7 sc01131ln102720_84539_A_G_3253
0.2 sc00283ln338214_136440_C_T_171
1.9
0.6 sc00283ln338214_153572_G_T_171
10.1 sc00283ln338214_233599_A_C_171
62.3 0.3 sc00283ln338214_239137_G_A_171
41.8 66.8 0.8 sc00283ln338214_293493_T_C_171
sc01149ln100495_6599_A_G_32715
sc01149ln100495_19761_C_T_3271
sc01149ln100495_32702_T_C_3271
56.9 sc00043ln806145_763080_A_G_521
sc00477ln232797_55899_C_T_2254 sc00043ln806145_731182_A_G_521
sc00043ln806145_170363_C_A_516
14.5 sc00426ln251751_240727_C_T_213 sc00043ln806145_102278_G_A_515
sc00043ln806145_27550_A_G_5145
sc00050ln749641_133318_T_C_569 BARC-PV-0005808
17.5
13.9 sc02743ln31009_27860_A_G_41677
sc00079ln659676_266197_T_C_776 0.8 sc00721ln160814_116732_A_G_272
18.6 3.4
sc00458ln240490_238835_A_C_221 3.4 sc00880ln134596_94488_T_C_2958 sc00736ln157270_32680_T_C_2748
2.1 2.0
sc00022ln1003704_490507_A_C_32 sc00134ln519503_497021_C_T_110 1.6 sc00036ln871953_816000_T_G_463
4.0 sc00023ln985577_737723_A_G_342 sc00036ln871953_623598_A_C_461
5.9 2.2 2.5
sc00022ln1003704_88768_G_A_325 sc00023ln985577_404408_A_G_339 3.9 sc00036ln871953_260922_C_A_457
12.7 sc00716ln161188_139140_T_G_271
15.3 sc00003ln2130026_318965_G_A_46 17.9
sc00061ln715360_52902_C_T_6499
0.4 sc00003ln2130026_249989_T_G_45 sc00018ln1167623_926274_C_T_29
1.1 sc00003ln2130026_221589_T_C_45 55.1
3.5 sc00018ln1167623_515133_C_A_28
4.0 sc00618ln186586_8943_T_C_25469 6.7
0.2 24.0 sc00018ln1167623_30331_G_T_281
sc01409ln79819_3642_A_C_350551 1.3 sc01035ln113702_42942_G_A_3149
sc01409ln79819_56167_T_C_35060 2.6
0.4 sc00175ln461633_78259_G_T_1298
sc00009ln1640450_1304280_C_T_1 3.9 sc00175ln461633_42284_G_A_1298
sc00914ln129176_38656_G_A_3003
sc00025ln963649_165119_T_G_356
0.7 sc00025ln963649_327459_T_C_357
11.6
sc00038ln842375_5033_G_A_47257
4.1
sc00038ln842375_820428_T_C_480
11.2
sc00027ln946161_647185_A_G_380
0.5 sc00027ln946161_730836_A_C_381
7

8. Activity 5.1: MARS genotyping
5 6 7 8
sc00516ln215718_103432_C_T_234 sc01815ln56854_15487_C_T_37774 sc00431ln249067_99164_A_G_2143 sc00089ln640327_255418_C_T_841
9.7
sc00014ln1397360_934650_A_G_23
3.9 sc00502ln219883_127438_T_C_231
30.7 5.4
sc00067ln694271_486308_T_C_696
43.3
8.8 sc00052ln745181_210054_A_G_585
sc00162ln482802_338752_C_T_123 sc00052ln745181_283027_C_T_586
sc00162ln482802_86819_T_G_1236 6.1 sc00064ln701495_548353_A_G_676
1.7 67.2
sc00583ln198651_1233_G_A_24795
9.8
sc00169ln473620_158171_C_T_127 sc00153ln494563_454394_G_A_119
2.7 sc00158ln489092_253333_G_A_121
sc00004ln1947458_369015_C_T_68
32.4 sc00004ln1947458_475808_A_G_69
sc00004ln1947458_609051_G_A_70 30.9
sc00004ln1947458_651581_A_G_71 sc01794ln57480_20276_G_A_37654
1.9 sc00004ln1947458_666119_G_A_71
0.3 sc00004ln1947458_704961_G_A_71
1.7 sc00004ln1947458_901631_G_A_73 sc00262ln351368_101277_A_G_164
7.7 sc00004ln1947458_1019379_A_G_7
0.6 sc00004ln1947458_1047835_C_A_7
0.3
0.4 sc00004ln1947458_1101740_A_C_7
4.7 sc00004ln1947458_968323_T_C_74
59.6
sc00004ln1947458_1211738_C_T_7
sc00004ln1947458_1308111_T_C_7 50.4
sc00004ln1947458_1320715_T_C_7
sc00004ln1947458_1733897_T_C_8
BARC-PV-0001413 sc00035ln877458_767887_C_T_454
1.5 sc00002ln2152649_1120369_C_T_3
0.9 11.3
2.1 BARC-PV-0001385
sc00002ln2152649_1550949_T_G_3 sc00187ln435150_76559_G_A_1352
8

9. QTL / association mapping for drought tolerance
Andean genepool Mesoamerican genepool
CAL143 NATAL PAN127 R.C. SUG131 SEC16 SEQ11 SER8 SER16 SER22
SUGAR WONDER
F1 F1 F1 F1 F1 F1 F1 F1 F1 F1 F1 F1 F1 F1 F1 F1 F1 F1F1 F1 F1 F1 F1F1 F1
F2 F2 F2 160 plants harvested
F3 F3
F4 F4 400 lines
F4:6 F4:6
QTL/Association analysis
9

10. SNP set: Regenotyping for
improved QTL map
BAT 881 x G21212
330 polymorphic SNPs
SER16 X (SER16 X G35346)
G35346 = Phaseolus coccineus
400 polymorphic SNPs
Pinto Saltillo X Pinto Villa
170 polymorphic SNPs
10

11. DNA extraction from seeds
Cut seeds
DNA
extraction
Amplification Test
seeds macerated with
BM 185
stainless steel beads Tissue Lyser
11

12. Cut seeds germinate
in the field
Seed storage to planting
Germination test
In field
12

13. Activity 5.2: Advanced backcross
• Five Adv. BC populations BC2-F4
SOURCE
SER 16 SER 48
CAL 143 126 78
CAL 96 156 128
CIM 9314-36 39 -
• Most lines badly adapted
• 2012: - few lines in breeding program
- QTL appropach abandoned
13

14. Activity 5.2: Advanced backcross
Andean recurrent parent CAL 96 Mesoamerican donor SER 16
14

15. Activity 5.2: Advanced backcross
15

16. MAGIC population in common bean
(mesoamerican gene pool)
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
996 F3.5 families
F5:7 families for drought phenotyping Genotype individuals
16

17. Activity 3: MAS for biotic traits
Storage insects:
Bruchids (Zabrotes
subfasciatus)
17

18. SSR marker for bruchid resistance
PV-ATCT001 – Arc
•20 crosses
Agarose based marker:
SEQ1006
SEQ1027
RAZ105
RAZ106
CAL143
G18264
Blanco
RAZ44
Cortesia: H.F. Buendia
18

19. RI = log{(Emerged adults/hatched eggs) + 1} / DAE * 100 Activity 3: MAS for bruchid resistance
3.50
84
3.00
2.50 117
KATB9
125 24
123 63 124 65
67 CAL143 71 25 60
79 82 86
57 58 55 44 80 119 59
70 83 61 75
126 62 76
129
68
72 121
64
122
77 S
81 128 74 127
2.00 66
1 73
12 102
78
40 53
PV-ATCT001 marker
49
112 28 93 99 45
1.50
15
50 16
4 positive
120
41
90
96
95 52
heterozygote
20 111
104
37
54
46
39
100
27 RI negative
1.00 10
36 43 115
6 97 No Amplification
47
29
30 31 94
8
33 17
0.50
13
RAZ103
113
98
87
35
R
23 19 88
105 38 11 21
34
89
18 108 42 85 2
5 51 22 26 56
7 116 3 9 32
RAZ104 114 106 48 91
14 RAZ168
0.00
1000 1200 1400 1600 1800 2000 2200 2400 2600 2800
Yield (Kg/Ha)
19

20. Activity 3: SNPs for bruchid resistance
APA: Arcelin-Phytohemagglutinin-amylase Inhibitor family
kb
BAC: 71F18, Kami et al, 2006
BAC wild meso
BAT93 meso
G19833 andean
20

21. Precision introgression
• Bruchid resistance (arcelin gene) originates from
mesoamerican pool
negative Positive Positive negative
marker marker marker marker
1cM 1cM
R locus
The perfect marker is four markers
• 4 markers easily available between genepools
21

22. Activity 3: MAS for biotic traits
BGYMV (bean golden yellow
mosaic virus):
SCAR for bgm-1, but occasional
recombinants (14 crosses)
Recessive bc-3 resistance for BCMNV
(bean common mosaic necrotic virus)
(64 crosses)
22

23. bc-3 candidate gene: eIF4E
NADERPOUR et al. MOLECULAR PLANT PATHOLOGY (2010)
C-A
r r r r r r r r s s
1000 bp
820 bp
180 bp
23

24. Common Bacterial Blight (CBB)
MAS with
Bacterial blight:
• SU91 on Chr8 (Pedraza et al.
Xanthomonas
1997)
• SCAR’s : BC420 on Chr6 (Yu
et al. 1998)
• SAP6 on Chr10 (Miklas et al.
2006) .
24

25. CBB resistance QTLs
Chr 8 Chr 10
Map size : 166.82 cM Map size : 117.59 cM
0 BMbS15
10
12
14
16
18
20
22
24
26
28
30
10
2
4
6
8
4
6
8
0
0
1
2
3
BMbS13 BM212
0
3 SUcat01
BMbS12A
Xc
Xf
5 BMbS5
9 SU91 R2 =49% 21 BMd42
SUag01
12 gVQ
13 BMbS10 38 PV158
15 BMbS4
47 PV181
40 BMb1196w
51 PV185
SAP6
Xc
55
60 BMa27
R2 =20%
78 BM151
83 BMb386
86 BMb277
94 PVBR173 93 BMb96
102 BMc63
109 IAC54
111 BMc121 111 BMb302
113 BMb167
118 BMc66
141 PVBR71
Xc
167 BMb1319w Xf
25

26. Activity 4: Drought tolerant traits
• 36 advanced lines characterized (milestone 6)
• Drought trials in
– 2 saison in CIAT (2010, 2011), Palmira, ±drought
– 1 saison in Ethiopia, ±drought
• 3 visual scales for wilting, podfilling and degree
of leaf loss analyzed (milestone 7)
26

27. Relationship between irrigated and rainfed grain yield of 36
common bean genotypes grown under field conditions at
CIAT-Colombia
1200
DAB 295
Rainfed grain yield (kg ha-1)
DAB 489
DAB 528 DAB 494
1000 DAB 261 DAB 441
DAB 395
Mean: 798 DAB 557 DAB 541
DAB 525
LSD0.05: 383 DAB 520 DAB 555 DAB 545
800
DAB 318 DAB 432
DAB 353 DAB 317
DAB 302
DAB 344
DAB 380 DAB 530
600 KATB 1 AFR 298
DAB 564
DAB 493
CAL 143
400 CAL 96
Mean: 2934
LSD0.05: 565
200
1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800
Irrigated grain yield (kg ha-1)
27

28. Activity 4: Visual scales
Resistance to Wilting
28

29. Relationship between leaf wilting and rainfed grain yield of
36 common bean genotypes grown under field conditions
at CIAT-Colombia
1200
r = -0.36*** DAB 295
Rainfed grain yield (kg ha-1)
DAB 494 DAB 528
DAB 489
DAB 441
1000 DAB 261
DAB 395
DAB 504 DAB 326
DAB 534
DAB 532 DAB 557 Mean: 798
DAB 545 DAB 514 LSD0.05: 383
DAB 520 DAB 555
800 DAB 290
DAB 432 DAB 353
DAB 318 DAB 317
DAB 302
DAB 380 DAB 344
DAB 530
600 AFR 298 KATB 1
DAB 564
DAB 493
CAL 143
400 CAL 96
Mean: 18.9
LSD0.05: 8.6
200
5 10 15 20 25 30 35
Wilting score at 41 days after planting
Adapted from King et al. 2009 Crop Science 49:290-298;
0 = no wilting and 100 = plant death
29

30. Relationship between seed filling and rainfed grain yield of
36 common bean genotypes grown under field conditions
1200
at CIAT-Colombia
DAB 295
DAB 489
r = -0.47***
Rainfed grain yield (kg ha-1)
DAB 494 DAB 528
DAB 441
1000 DAB 261
DAB 395
DAB 534
DAB 504 DAB 532
DAB 557 DAB 525
DAB 549
DAB 520
DAB 555 DAB 545
800 Mean: 798 DAB 290
DAB 318
DAB 432 DAB 286
LSD0.05: 383 DAB 353 DAB 317
DAB 530 DAB 302
DAB 344
DAB 380
600 KATB 1
DAB 564
DAB 493
AFR 298
CAL 143
CAL 96
400
Mean: 4.78
LSD0.05: 2.0
200
2 3 4 5 6 7
Rainfed seed fill score
0 = well-filled grain; 10 = more than 50% of grain is not well-filled
30

31. Conclusions
• SNPs used in QTL and association mapping
• MARS moving forward
– Seed DNA extraction permits flexibility
• MAS for biotic stress in implementation,
moving toward routine
• Advanced lines show improved yield
• Visual scale of pod filling useful
31

32. Thank you for your attention!
32