Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in Synthetic Hexaploid...
-
Upload
borlaug-global-rust-initiative -
Category
Education
-
view
655 -
download
1
description
Transcript of Genome-wide Association Mapping of Adult Plant Resistance to Stripe Rust in Synthetic Hexaploid...
BGRI Technical Workshop New Delhi, India, 19-‐22 August 2013
H. Zegeye
Outline
Ø Introduction
Ø Materials and Methods
Ø Results
Ø Summary and conclusion
Ø Acknowledgements
Major wheat growing areas Minor wheat growing areas
Introduction
Ø Area under wheat has shown steady increase to about 2 M ha at present
Ø National average yield increased by 3x compared to 1960s (0.6 -‐ 2 t/ha), below the world’s average yield (3 t/ha)
v Ethiopia is the 2nd largest wheat producer in SSA
Factors affecting wheat productivity in Ethiopia
v Biotic stress Ø Wheat rusts (yellow, stem and leaf) and septoria
Ø Weeds (grass)
v Abiotc stress Ø Water logging Ø Low soil fertility Ø Drought-‐low moisture in lowlands
v Technical constraints Ø Shortage of appropriate varieties for d/f AEZs
v Socio-‐economic factors Ø Inputs
Yellow Stem Leaf
Variety Year of release
Epidemic Year Virulence against Estimated
loss (%) Laketch 1974 Sr? ??
Dashen 1984 1988 Yr9 58
Enkoy 1974 1994 Sr36 67-‐100 Kubsa Galama 1995 2010 Yr27 Up to 100
Major Rust Epidemics and Estimated Yield Losses in Ethiopia
Dead Wheat 2010 Farmer’s Field around Meraro,Ethio Looking at the Spot
Wheat Area Affected by Yellow Rust Epidemics During 2010 in Ethiopia
Region Zones under
epidemics
Districts under
epidemics
Wheat area affected (ha)
Area sprayed by fungicide
Percent area sprayed
Oromia 13 118 292,866 123,357 42.1
Amhara 8 77 161,348 26,579 16.5
SNNP 15 94 137,376 32,089 23.4
Total 36 289 591,590 182,026 30.8
Source: MoA report 2010 (unpublished)
ü Heavy Yellow rust infestation at tillering stage on Kubsa: Farmers bield
ü With no timely fungicide, losses estimated up to 100%
v International Scientists:
Ø Cornell University
Ø CIMMYT
Ø ICARDA
Ø India visited Farmers’ field and witness
the Yellow rust epidemic in 2010
Ø Continuous release of bread wheat cultivars with similar parentages
Ø Production of few cultivars for long time in the same area
ü Lack of continuous cultivar replacement preferred by farmers and rust resistance wheat varieties diversification
The recurrent outbreak of wheat rusts could be
....So what?
Ø It is imperative to search for new sources of resistance in
ü Cultivated wheat
ü Wild relatives
ü Synthetics
Ø Synthetic hexaploid wheat provide resistance to several abiotic and biotic stresses (van Ginkel and Ogbonnaya, 2007)
Ø The use of molecular marker tools that aids to genotype germplasm to identify markers with desirable traits that could be incorporated in breeding programs via marker assisted selection (MAS) become vital and contemporary
Ø Association Mapping(AM) is one of the techniques being
used to study the association between genotype and
phenotype that could help to identify marker-‐ trait
association
Ø Advantages of AM
ü No new crosses ü Several traits can be studied in the same population using same genotype
ü Much higher mapping resolution
…con’t
Objectives
v To characterize stripe rust resistance in a collection of synthetic hexaploid wheat
v To identify genomic regions with QTLs linked to
stripe rust resistance under bield conditions
Materials and Methods
v A total of 187 plant materials were used for this study.
Ø 181 SHWs: ICARDA
Ø 6 bread wheat: Kulumsa Research Center, Ethiopia
ü The check cultivars show variable reaction to stripe rust under Oield conditions in hot spot areas in Arsi and Bale,
Ethiopia
Ø SHWs were screened against stripe rust under bield conditions in Ethiopia at Meraro and Arsi Robe from
2010-‐2011
Ø simple design used with 2 rows of 1m length
Ø SHWs were Characterized at seedling stage in greenhouse
Phenotyping
Disease scoring
Ø Consecutive scores were taken in ten days interval until the disease progress ceased
Ø Modibied Cobb’s scale was adopted for Severity while bield responses (R, MR, MS, S)-‐ Roelfs et al., 1992
Ø The terminal scores were converted to coefbicient of infection
Ø 0 to 4 scale was adopted for scoring seedling reaction (McIntosh et al., 1995)
Genotyping
Ø DNA extraction(Ogbonnaya et al., 2001)
Ø 9000 SNP Illumina’s inbinium assay
Ø Genome Studio® for ‘Allele calling’
Ø Monomorphic & polymorphic SNPs markers with low allelic frequency of < 5% were culled out from the analysis
Ø 4040 polymorphic SNPs used 17 days old seedlings collected for
DNA extraction
Population Structure (Q)
v Estimated using 42 unlinked SNP markers considering at least 50 cM apart between markers within the same chromosome
v Software ‘STRUCTURE v.2.3.4’ (Pritchard et al., 2000)
v K=1…15 sub-‐populations assumed
Linkage Disequilibrium (LD)
Ø Software: TASSEL v3.0
Ø 4040 unlinked SNPs
Ø r2 used to estimate LD
Ø r2 plotted against genetic distance
Association Analysis
Ø TASSEL V.3
Ø Mixed Linear model (MLM)
Ø The results of the MLM analysis that accounted for population structure (Q and K matrices) was adopted
ü P<0.01
Results
Reaction of some SHWs across location and at seedling stage to stripe rust
Gentype 2010 2011
Seedling (0 to 4)
Meraro A.Robe Meraro A.Robe
Kubsa 100S 90S 100S 70S 2
68.111/RGB-‐U//WARD RESEL/3/STIL/4/AE.SQUARROSA (164) 30MS 10S 5MR TR 2C
DOY1/AE.SQUARROSA (322) 20SMS 5S 0 5S 3
68.111/RGB-‐U//WARD RESEL/3/STIL/4/AE.SQUARROSA (631) 10MS 0 0 0 3
68.111/RGB-‐U//WARD RESEL/3/STIL/4/AE.SQUARROSA (684) 10MR 0 0 0 1
RABI//GS/CRA/3/AE.SQUARROSA (190) TR 0 TR TS 3
SORA/AE.SQUARROSA (191) 20MS 5S TR 0 0
SORA/AE.SQUARROSA (208) 5MS 5S TR 0 3
DOY1/AE.SQUARROSA (415) 10MR 0 TR 5S :N
SCA/AE.SQUARROSA (409) 5R 0 TR 0 3
STY-‐US/CELTA//PALS/3/SRN-‐5/4/AE.SQUARROSA (502) 5SMS TR TR 5S 3
DOY1/AE.SQUARROSA (516) 5MSMR 5MS TR TS 4
DOY1/AE.SQUARROSA (1024) 5MR TS TR TR 4
…con’t
The frequency of SHWs under different severity classes tested at Meraro, Ethiopia in 2011
0
10
20
30
40
50
60
R MR MS S
Freq
uenc
y of
dis
ease
sev
erity
(%
)
Host Reaction0
10
20
30
40
50
60
R MR MS S
Host Reaction
Freq
uenc
y of
dis
ease
sev
erity
(%
)
Population Structure (Q)
-‐9500
-‐9000
-‐8500
-‐8000
-‐7500
-‐7000
-‐6500
-‐6000
-‐5500
-‐5000 2 3 4 5 6 7 8 9 10 11 12 13 14 15
K
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Ln(P)
Using 42 unlinked markers
LD decay
R2
Genetic distance (cM)
R2=0.22
Detected QTLs associated with stripe rust resistance at adult plant stage
Marker Chromosome Position (cM) P-‐value R2 wsnp_Ex_c10657_17376448 1AL 6.5 8.79E-‐03 3.5 wsnp_RFL_Contig3850_4199825 1AS 175.6 3.72E-‐03 4.5 wsnp_RFL_Contig2449_2013497 1BS 34.8 3.96E-‐03 4.2 wsnp_Ex_c11177_18096010 1BS 35.3 2.86E-‐03 4.5 wsnp_Ex_c14_27570 1BS 35.3 1.68E-‐03 5.1 wsnp_Ku_c62848_63784645 1BS 35.5 1.51E-‐03 5.2 wsnp_Ku_c30982_40765341 1BS 37.2 5.04E-‐03 5.4 wsnp_BE442716B_Ta_2_2 1DS 38.2 8.55E-‐03 5.2 wsnp_BE591501B_Ta_2_1 1BS 38.8 4.03E-‐03 4.6 wsnp_Ex_c10233_16784994 1BS 39.5 7.38E-‐03 5.0 wsnp_Ku_c66585_65967792 1BS 39.7 9.18E-‐03 4.8 wsnp_Ku_c6158_10825959 1BS 66.5 3.72E-‐03 4.3
Total=26 R2= 3.4% to 8.1%
Marker Chromosome Position (cM) P-‐value R2
wsnp_Ku_rep_c69876_69364477 2AS 93.2 9.97E-‐04 5.6
wsnp_Ex_c1604_3060855 2AS 160.7 5.67E-‐03 3.9
wsnp_CAP7_c3519_1643682 2DS 165.4 1.74E-‐04 7.3
wsnp_Ra_c9738_16174002 3AL 15.9 2.52E-‐03 6.1
wsnp_Ex_c742_1458033 3AS 40.9 7.39E-‐03 3.6
wsnp_Ex_rep_c106152_90334299 3AL 46.2 5.12E-‐04 7.8
wsnp_JG_c2509_1153697 3AL 56.7 7.48E-‐04 7.4
wsnp_RFL_Contig4734_5671036 3AL 104.8 3.90E-‐03 5.8
wsnp_Ex_c55096_57733894 3AL 163.0 7.50E-‐03 3.6
wsnp_Ex_rep_c104141_88935451 3AS 163.6 5.02E-‐04 8.1
wsnp_Ex_c41074_47987860 4AL 93.5 3.96E-‐03 4.2
wsnp_RFL_Contig2828_2623246 4DL 12.1 9.67E-‐03 3.4
wsnp_Ku_c35386_44598937 5A 112.5 5.32E-‐04 6.2
wsnp_Ex_c25505_34772008 6DL 50.8 2.14E-‐03 5.0
…con’t
Map position of signibicant markers
wsnp_Ex_c17884_26647952 0.0 wsnp_Ex_c10657_17376448 6.5 wsnp_Ku_c5756_10191339 24.7
wsnp_Ex_c10595_17291999 52.3
wsnp_Ku_c5210_9290700 100.5
wsnp_JD_rep_c49006_33254974 150.1
wsnp_RFL_Contig3850_4199825 175.6 wsnp_Ex_c52086_55808824 181.2
1A wsnp_Ra_c19335_28504388 21.9 wsnp_RFL_Contig2449_2013497 34.8 wsnp_Ex_c11177_18096010 wsnp_Ex_c14_27570 35.3 wsnp_Ku_c62848_63784645 35.5 wsnp_Ku_c30982_40765341 37.2 wsnp_BE442716B_Ta_2_2 38.2 wsnp_BE591501B_Ta_2_1 38.8 wsnp_Ex_c10233_16784994 39.5 wsnp_Ku_c66585_65967792 39.7 wsnp_CAP7_c940_480745 46.9 wsnp_JD_c5659_6814240 59.7 wsnp_Ku_c6158_10825959 66.5 wsnp_Ex_rep_c69766_68723140 69.6
1B
wsnp_Ex_rep_c68599_67447880 90.2 wsnp_Ku_rep_c69876_69364477 93.2 wsnp_bg606625A_Ta_2_1 103.4
wsnp_Ex_c2887_5330787 127.4
wsnp_Ex_c5984_10493714 150.3 wsnp_Ex_c1604_3060855 160.7 wsnp_Ku_c54793_58953037 165.0
2A
wsnp_Ra_rep_c71290_69343893 150.5 wsnp_Ex_rep_c66522_64795143 158.2 wsnp_CAP7_c3519_1643682 165.4 wsnp_Ku_c4319_7847988 168.0
2D
wsnp_Ra_c9738_16174002 15.9
wsnp_Ex_c44447_50496676 37.1 wsnp_Ex_c742_1458033 40.9 wsnp_Ku_c40218_48484410 43.3 wsnp_Ex_rep_c106152_90334299 46.2 wsnp_JG_c2509_1153697 56.7 wsnp_BG263769A_Td_2_1 62.5 wsnp_RFL_Contig429_4978628 81.4 wsnp_Ku_c4886_8753646 97.8 wsnp_RFL_Contig4734_5671036 104.8 wsnp_BF292596A_Ta_1_3 119.1 wsnp_Ex_c20250_29303152 135.5 wsnp_BE604885A_Ta_2_1 151.5 wsnp_Ex_c55096_57733894 163.0 wsnp_Ex_rep_c104141_88935451 163.6 wsnp_Ku_c35632_44814164 171.5
3A
wsnp_Ex_c2288_4293430 83.5 wsnp_Ra_rep_c87547_79842909 87.1 wsnp_Ex_c41074_47987860 93.5 wsnp_JD_c38619_27992279 95.4 wsnp_Ku_c8059_13763683 99.5
4A
wsnp_Ex_rep_c107564_91144523 0.5 wsnp_CAP11_c356_280910 8.0 wsnp_Ku_c25831_35797676 10.0 wsnp_RFL_Contig2828_2623246 12.1 wsnp_Ku_c9140_15390166 15.3 wsnp_BE444858D_Ta_1_1 18.9
4D
wsnp_RFL_Contig44_5147697 103.3 wsnp_Ku_c15816_24541162 107.5 wsnp_Ku_rep_c103857_90489662 110.1 wsnp_Ku_c35386_44598937 112.5 wsnp_Ku_c14139_22353229 114.5 wsnp_Ra_c21347_30731133 118.3
5A
wsnp_Ex_c6942_11966469 0.0 wsnp_BE471213D_Ta_2_1 2.4 wsnp_Ex_c4518_8119503 6.1 wsnp_Ex_c62371_62036044 7.1 wsnp_JD_c7795_8867843 8.5
6D
…con’t
SNP markers signibicantly associated with resistance to stripe rust at seedling stage
No Marker Chrom. Pos(cM) P-‐value R2 1 wsnp_Ku_c6158_10825959 1BS 66.5 6.52E-‐03 4.1
2 wsnp_Ku_c30982_40765341 1BS 37.2 6.55E-‐03 5.5
3 wsnp_Ex_c1318_2520916 1DS 85.0 6.67E-‐03 5.5
4 wsnp_Ex_c25974_35235456 1DS 85.7 3.72E-‐03 6.2
5 wsnp_Ex_c1318_2519998 1DS 86.5 6.81E-‐03 5.4
6 wsnp_Ex_c6920_11929171 1DS 89.4 6.71E-‐03 5.5
7 wsnp_BG275030D_Ta_2_2 2DL 41.9 9.01E-‐03 5.1
8 wsnp_Ex_c25945_35206573 3DS 12.4 1.28E-‐04 8.2
9 wsnp_Ex_c19724_28721580 5B 126.3 7.67E-‐03 3.9
10 wsnp_Ex_c19928_28951983 6A 178.4 8.08E-‐03 3.8
11 wsnp_Ex_c4480_8056013 6DS 6.4 5.81E-‐03 4.1
12 wsnp_Ku_rep_c71225_70941765 6DS 6.4 5.81E-‐03 4.1
13 wsnp_Ex_c4480_8055475 6DS 6.4 4.88E-‐03 4.3
14 wsnp_Ex_c62371_62036044 6DS 7.1 8.87E-‐03 5.2
R2 = 3.8 to 8.2%
Summary and Conclusion
��� Usefulness of AM for marker trait association is demonstrated on SHWs
��� Identibied list of SNP markers closely linked to Yr resistance
��� SHW genotypes possessing potentially novel resistance alleles at different QTL should be further investigated and could be used as parental lines in a marker-‐assisted backcrossing scheme
��� About 26 signibicant associations obtained (needs validation)
Acknowledgment
ICARDA K. Nazari W. Tadesse O. Abdalla A. Jighly
EIAR-KARC Bedada Girma – DRRW Solomon G. – KARC Director Firdisa Eticha – KARC-Wheat
Advisors Francis. C. O Ayele B. Hussien M
EIAR
Study leave Funding All 2013 BGRI Organizers
Cristobal Uauy-‐Jonns Center