H. Zegeye

1. BGRI
Technical
Workshop
New
Delhi,
India,
19-­‐22
August
2013
H.
Zegeye

2. Outline
Ø Introduction
Ø Materials
and
Methods
Ø Results
Ø Summary
and
conclusion
Ø Acknowledgements

3. 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

4. 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

5. 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

6. 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(unpublished)

7. 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

8.
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

9. ....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

10. 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
…con’t

11.
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

12.
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

13.
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

14. 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)

15. 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

16. 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

17. Linkage
Disequilibrium
(LD)
Ø Software:
TASSEL
v3.0
Ø 4040
unlinked
SNPs
Ø r2
used
to
estimate
LD
Ø r2
plotted
against
genetic
distance

18. 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

19. Results

20. 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

21. …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
Frequencyofdiseaseseverity
(%)
Host Reaction
0
10
20
30
40
50
60
R MR MS S
Host Reaction
Frequencyofdiseaseseverity
(%)

22. 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

23. LD
decay
R2
Genetic
distance
(cM)
R2=0.22

24. 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%

25. 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
…con’t

26. Map
position
of
signibicant
markers
wsnp_Ex_c17884_266479520.0
wsnp_Ex_c10657_173764486.5
wsnp_Ku_c5756_1019133924.7
wsnp_Ex_c10595_1729199952.3
wsnp_Ku_c5210_9290700100.5
wsnp_JD_rep_c49006_33254974150.1
wsnp_RFL_Contig3850_4199825175.6
wsnp_Ex_c52086_55808824181.2
1A
wsnp_Ra_c19335_2850438821.9
wsnp_RFL_Contig2449_201349734.8
wsnp_Ex_c11177_18096010wsnp_Ex_c14_2757035.3
wsnp_Ku_c62848_6378464535.5
wsnp_Ku_c30982_4076534137.2
wsnp_BE442716B_Ta_2_238.2
wsnp_BE591501B_Ta_2_138.8
wsnp_Ex_c10233_1678499439.5
wsnp_Ku_c66585_6596779239.7
wsnp_CAP7_c940_48074546.9
wsnp_JD_c5659_681424059.7
wsnp_Ku_c6158_1082595966.5
wsnp_Ex_rep_c69766_6872314069.6
1B
wsnp_Ex_rep_c68599_6744788090.2
wsnp_Ku_rep_c69876_6936447793.2
wsnp_bg606625A_Ta_2_1103.4
wsnp_Ex_c2887_5330787127.4
wsnp_Ex_c5984_10493714150.3
wsnp_Ex_c1604_3060855160.7
wsnp_Ku_c54793_58953037165.0
2A
wsnp_Ra_rep_c71290_69343893150.5
wsnp_Ex_rep_c66522_64795143158.2
wsnp_CAP7_c3519_1643682165.4
wsnp_Ku_c4319_7847988168.0
2D

27. wsnp_Ra_c9738_1617400215.9
wsnp_Ex_c44447_5049667637.1
wsnp_Ex_c742_145803340.9
wsnp_Ku_c40218_4848441043.3
wsnp_Ex_rep_c106152_9033429946.2
wsnp_JG_c2509_115369756.7
wsnp_BG263769A_Td_2_162.5
wsnp_RFL_Contig429_497862881.4
wsnp_Ku_c4886_875364697.8
wsnp_RFL_Contig4734_5671036104.8
wsnp_BF292596A_Ta_1_3119.1
wsnp_Ex_c20250_29303152135.5
wsnp_BE604885A_Ta_2_1151.5
wsnp_Ex_c55096_57733894163.0
wsnp_Ex_rep_c104141_88935451163.6
wsnp_Ku_c35632_44814164171.5
3A
wsnp_Ex_c2288_429343083.5
wsnp_Ra_rep_c87547_7984290987.1
wsnp_Ex_c41074_4798786093.5
wsnp_JD_c38619_2799227995.4
wsnp_Ku_c8059_1376368399.5
4A
wsnp_Ex_rep_c107564_911445230.5
wsnp_CAP11_c356_2809108.0
wsnp_Ku_c25831_3579767610.0
wsnp_RFL_Contig2828_262324612.1
wsnp_Ku_c9140_1539016615.3
wsnp_BE444858D_Ta_1_118.9
4D
wsnp_RFL_Contig44_5147697103.3
wsnp_Ku_c15816_24541162107.5
wsnp_Ku_rep_c103857_90489662110.1
wsnp_Ku_c35386_44598937112.5
wsnp_Ku_c14139_22353229114.5
wsnp_Ra_c21347_30731133118.3
5A
wsnp_Ex_c6942_119664690.0
wsnp_BE471213D_Ta_2_12.4
wsnp_Ex_c4518_81195036.1
wsnp_Ex_c62371_620360447.1
wsnp_JD_c7795_88678438.5
6D
…con’t

28. 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%

29. 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)

30. 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