Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses
Genetic effects on controlling stripe rust resistance were determined in two wheat crosses, Bakhtawar-92 x Frontana (cross 1) and Inqilab-91 x Fakhre Sarhad (cross 2) using Area under Disease Progress Curve (AUDPC) as a measure of stripe rust resistance.
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irk-123456789-666512017-12-02T22:39:29Z Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses Irfaq, M. Mir Ajab Ma Hongxiang Gss Khattak Оригинальные работы Genetic effects on controlling stripe rust resistance were determined in two wheat crosses, Bakhtawar-92 x Frontana (cross 1) and Inqilab-91 x Fakhre Sarhad (cross 2) using Area under Disease Progress Curve (AUDPC) as a measure of stripe rust resistance. Генетические эффекты контроля устойчивости к желтой ржавчине злаков были определены в двух скрещиваниях пшеницы Bakhtawar-92 x Frontana (скрещивание 1) и Inquilab-91 x Fakhre-Sarhad (скрещивание 2) с использованием Area Under Disease Progress Curve (AUDPC) для измерения устойчивости. Генетичні ефекти контролю стійкості до жовтої іржі злаків були визначені в двох схрещуваннях пшениці Bakhtawar-92 x Frontana (схрещування 1) и Inquilab-91 x Fakhre-Sarhad (схрещування 2) з використанням Area Under Disease Progress Curve (AUDPC) для вимірювання стійкості. 2009 Article Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses / M. Irfaq, Mir Ajab, Ma Hongxiang, Gss Khattak // Цитология и генетика. — 2009. — Т. 43, № 3. — С. 25-38. — Бібліогр.: 25 назв. — англ. 0564-3783 http://dspace.nbuv.gov.ua/handle/123456789/66651 en Цитология и генетика Інститут клітинної біології та генетичної інженерії НАН України |
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Оригинальные работы Оригинальные работы Irfaq, M. Mir Ajab Ma Hongxiang Gss Khattak Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses Цитология и генетика |
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Genetic effects on controlling stripe rust resistance were determined in two wheat crosses, Bakhtawar-92 x Frontana (cross 1) and Inqilab-91 x Fakhre Sarhad (cross 2) using Area under Disease Progress Curve (AUDPC) as a measure of stripe rust resistance. |
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Irfaq, M. Mir Ajab Ma Hongxiang Gss Khattak |
| author_facet |
Irfaq, M. Mir Ajab Ma Hongxiang Gss Khattak |
| author_sort |
Irfaq, M. |
| title |
Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses |
| title_short |
Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses |
| title_full |
Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses |
| title_fullStr |
Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses |
| title_full_unstemmed |
Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses |
| title_sort |
assessment of genes controlling area under disease progress curve (audpc) for stripe rust (p. striiformis f. sp. tritici) in two wheat (triticum aestivum l.) crosses |
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Інститут клітинної біології та генетичної інженерії НАН України |
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2009 |
| topic_facet |
Оригинальные работы |
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http://dspace.nbuv.gov.ua/handle/123456789/66651 |
| citation_txt |
Assessment of genes controlling Area Under Disease Progress Curve (AUDPC) for stripe rust (P. striiformis f. sp. Tritici) in two wheat (Triticum aestivum L.) crosses / M. Irfaq, Mir Ajab, Ma Hongxiang, Gss Khattak // Цитология и генетика. — 2009. — Т. 43, № 3. — С. 25-38. — Бібліогр.: 25 назв. — англ. |
| series |
Цитология и генетика |
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| fulltext |
M. IRFAQ 1, MIR AJAB 2,
MA HONGXIANG 3, GSS KHATTAK 1
1 Crop Breeding Division, Nuclear Institute for Food and Agriculture (NIFA),
Peshawar, N.W.F.P., Pakistan
2 Faculty of Plant Science, Department of Biological Sciences, Quaid�i�Azam
University, Islamabad, Pakistan
3 Institute of Biotechnology, Jiangsu Academy of Agricultural Sciences, Nanjing,
Jiangsu, P.R. China
ASSESSMENT OF GENES
CONTROLLING AREA UNDER DISEASE
PROGRESS CURVE (AUDPC) FOR
STRIPE RUST (P. STRIIFORMIS F. SP.
TRITICI) IN TWO WHEAT (TRITICUM
AESTIVUM L.) CROSSES
Genetic effects on controlling stripe rust resistance were
determined in two wheat crosses, Bakhtawar�92 � Frontana
(cross 1) and Inqilab�91 � Fakhre Sarhad (cross 2) using
Area under Disease Progress Curve (AUDPC) as a measure of
stripe rust resistance. The resistant and susceptible genotypes
for crosses were identified by initial assessment of 45 wheat
accessions for stripe rust resistance. Mixed inheritance model
was applied to the data analysis of six basic populations P1,
F1, P2, B1, B2, and F2 in the crosses. The results indicated that
AUDPC in cross 1 was controlled by two major genes with
additive�dominance epistatic effect plus polygenes with addi�
tive�dominance epistatic effects (model E). Whereas in case of
cross 2, it was under the control of two major genes with addi�
tive�dominance epistatic effect plus additive�dominant poly�
genes (model E�1). Additive effect was predominant then all
other types of genetic effects suggesting the delay in selection
for resistance till maximum positive genes are accumulated in
the individuals of subsequent generations. Occurrence of
transgressive segregants for susceptibility and resistance indi�
cated the presence of resistance as well as some negative genes
for resistance in the parents. The major gene heritability was
higher than the polygene heritability in B1, B2 and F2 for the
crosses. The major gene as well as the polygene heritability
was ranging from 48.99 to 87.12 % and 2.26 and 36.80 % for
the two crosses respectively. The highest phenotypic variations
in AUDPC (2504.10 to 5833.14) for segregating progenies
(BC1, BC2 and F2) represent that the character was highly
influenced by the environment.
Introduction. Stripe (yellow) rust caused by a
fungus Puccinia striiformis f. sp. tritici, is a major
disease of wheat word wide especially in moist and
cool environments [1]. The disease appeared in
epidemic form in Pakistan during the year 2004–
2005 because of the environmental conditions made
highly conducive through tsunami effect. Grain
yield losses from 20 to 60 % in susceptible wheat
cultivars have been reported in case of severe out
break of the disease during ear emergence [2].
Cultivation of genetically resistant cultivars is the
effective measure to control the disease. Race spe�
cific or vertical resistance has remained no longer
effective because of the evolution and population
diversity of new virulent pathotypes [3]. Durable
resistance controlled by the combined effect of
both major and minor genes is desired to control
the disease for longer time in an environment con�
ducive for the disease development. This requires the
availability of well known resistant genetic resources,
a better understanding of the host�pathogen inter�
action and suitable techniques to utilize the desired
genes. Adult plant resistance is most often desired
by wheat breeders in order to avoid/reduce yield
losses caused by the disease at adult plant stage [4].
Identification of genetically variable lines with
respect to stripe rust resistance is of great help to
select the parents for cross combination so as to
pyramid genes from different resistant resources in
to a single genotype with durable resistance. The
aim of the present study was to identify genotypes
with high level of resistance to stripe rust, transfer�
ring of resistant genes from resistant to suitable geno�
type through successful cross combination and to
study the genetic basis of resistance in wheat by
using Area under Disease Progress Curve (AUDPC)
as a measure of stripe rust resistance.
Materials and methods. Field evaluation of
germplasm for AUDPC at adult plant stage. Seeds of
45 bread wheat genotypes differing in their genetic
make up and origin were collected from different
sources viz Pakistan, India, CIMMYT and Brazil.
Twenty of these genotypes were belonging from
Pakistan, fifteen from CIMMYT, Mexico, nine
from India and 1 from Brazil. The accessions were
planted as stripe rust screening nursery in two
replications in two�meter�long rows per entry with
20 seeds per row in randomized complete block
design at experimental farm of Nuclear Institute
for Food and Agriculture (NIFA), Peshawar,
Pakistan during rabi, 2003–2004. The plot size per
entry in each set was kept 1.2 m2.
ІSSN 0564–3783. Цитология и генетика. 2009. № 4 25
© M. IRFAQ, MIR AJAB, MA HONGXIANG, GSS KHATTAK,
2009
Creation of artificial epiphytotic condition in the
nursery. Each entry of the nursery was bordered with
a susceptible check of ‘Morocco’ as a spreader of
stripe rust. Artificial stripe rust epiphytotic condi�
tions was created in the field as referred by [5], inoc�
ulated the nursery material at tillering stages in late
afternoon with uniform spray of spore suspension
containing mixture of urediospores of different stripe
rust (Puccinia striiformis) races prevalent in Pakis�
tan, through turbo air sprayer at the end of February,
2004. Urediospore mixture was obtained from Na�
tional Wheat Diseases Research Program (NWDRP)
at National Agriculture Research Center (NARC)
Islamabad, probably consisting of 67E0, CYR32,
78S84, 110E143A, 230E150, 230E134, Pst 106,
E139A and 110E143A pathotypes. These races has
virulence formula against the stripe rust resistant
genes as Yr1,2,3,4, 5, 6, 7, 8, 9, 10, 15, 17, YrA, and
Yr27 [1, 6]. Tween 20 was added in fresh tap water
by dissolving urediospores at a rate of 1 gram/litter
with approximate concentration of 30000/ml in the
suspension as determined by haemocytometer. The
nursery material was covered with plastic sheets to
keep the moisture for making conditions conducive
to spore germination and to avoid washing of spores
by dew drops. For spore multiplication and disease
development, plane water in the late afternoon was
sprayed on to the nursery material with the intervals
of two days (for a period of fortnight) until the dis�
ease symptoms appeared in the field.
Methodology for disease scoring and determining
AUDPC. After successful disease development,
data for rust severity (percentage of leaf area with
symptoms) was recorded on the top three leaves of
five randomly selected plants from each accession
on 0–9 points rating scale with little modification
to those of [7], as suggested by [8] (Table 1).
Second reading of all selected plants was recorded
after seven days of the first reading. Observations
on response and severity of stripe rust were record�
ed according to [9]. Rust severity was determined
by visual observation and recorded from 0 to
100 % of rust infection on 5 selected plants with in
each population according to the modified Cobb
scale [10]. For recording correct readings of sever�
ity up to interval 2 on individual plants, the term
trace (T) was used below 5 % severity. A five per�
cent interval was used from 5 to 20 percent severi�
ty and 10 percent intervals for higher readings. The
response of individual plants within each popula�
tion to the type of stripe rust infection was record�
ed in Table 2. Severity and reaction were recorded
together with severity first. The Coefficient of
infection (CI) for the rust was calculated in the
manner used in CIMMYT and IRN (USDA) i.e.,
by multiplying the response value with the intensi�
ty of infection in percent. Average coefficient of
infection (ACI) was derived from the sum of CI
values of each entry divided by the number of
replications. Based on scale by [11] for selecting
wheat varieties to powdery mildew, little modifica�
tions were made and a rating scale for disease
resistance as adapted by PARC Islamabad,
Pakistan for measuring cereal rusts severity [12],
and later adopted by ARC (Agricultural Research
Council) of Great Britain for the farmers was fol�
lowed in this study. Using the following formula,
Area under disease progress curve (AUDPC) was
calculated for individual plants from the calculat�
ed C.I. values of the original rust severity data
where Xi and X i + 1 are severity on date i and date
i + 1, respectively and ti is the number of days bet�
ween date i and date i + 1.
Genotypes/accessions selected for genetic studies.
After performing cluster analysis, for AUDPC,
seven bread wheat genotypes with wide range of
genetic variability Viz. Bakhtawar�92, Frontana,
Saleem�2000, Tatara, Inqilab�91, Fakhre�Sarhad,
and Karwan were used as parent material for
hybridization. The accession Inqilab�91 was former�
ly described to have resistance to stripe rust based
on Yr9 and Yr27 [13]. Pedigrees and Salient fea�
tures of the parent varieties are detailed as under.
In the present paper, only four genotypes Viz.
Bakhtawar�92, Frontana, Inqilab�91and Fakhre�
Sarhad were used in two crosses. Crosses between
other genotypes are to be left for further papers to
avoid complication.
Evaluation of six populations against stripe rust.
After making successful crosses between the select�
ed genotypes Viz. Bakhtawar�92 � Frontana and
Inqilab � Fakhre�Sarhad, six multi�generations
(P1, F1, P2, B1, B2, F2) of each cross were planted
in the experimental field of Nuclear Institute for
Food and Agriculture (NIFA), Peshawar, Pakistan
during rabi 2006–2007 in three replications with
Randomized Complete Block Design (RCBD).
The row length of 5 meters was kept for each pop�
ISSN 0564–3783. Цитология и генетика. 2009. № 426
M. Irfaq, Mir Ajab, Ma Hongxiang, GSS Khattak
ulation but number of rows were varied i.e. two
rows for parents and F1, four rows for BC1 and BC2
and 8 rows for F2 populations of all the two cross�
es in each replication. The plant to plant and row
to row spacing was maintained 10 and 30 cm
respectively. Seeds were sown at 2.5 cm depth at
the rate of 2 seed per hil which were later on
thinned to single healthy seedling per hil after ger�
mination. Same methodology was used for creat�
ing artificial epiphytotic conditions, recording dis�
ease severity and working out AUDPC as men�
tioned for the germplasm. Starting from March 24,
2007 when the wheat plants were at growth stages
from booting to milk [14], rust severity was record�
ed at four intervals (24th March, 31st March, 7th
April and 14th April 2007 with in elapse of one week
interval between to consecutive readings) on the
same randomly selected plants (60 plants from
each of the parental, 90 from F1s, 150 plant from
each of B1s and B2s while 210 plants from each of
the F2s populations). Data collection was complet�
ed with in 12 hours on each recording date.
Statistical Analysis. Mean values regarding
AUDPC and standard deviations for all the acces�
sions were worked out by using MS excel pro�
gramme. For performing cluster analysis with respect
to classification of germplasm, Euclidean distance
was estimated for all pairs of accessions. The resul�
ting Euclidean dissimilarity coefficient matrices
were used to established the relationship between
the accessions using wardґs method (Statistica ver�
sion 7.0)
Joint Segregation Analysis (JSA). The data
regarding AUDPC were analyzed according to five
ІSSN 0564–3783. Цитология и генетика. 2009. № 4 27
Assessment of genes controlling Area Under Disease Progreess Curve (AUDPC) for stripe rust
Table 1
Assessment and evaluating of stripe rust reaction and measurement of coefficient of infection
O – No visible infection
R – Resistant. Necrotic areas with or without minute uredia
MR – Moderately resistant. Small uredia present surrounded by necrotic areas
MS – Moderately susceptible. Medium uredia with no necrosis but possibly some distinct chlorosis
S – Susceptible Large uredia and little or no chlorosis present
TR – Trace severity of resistant type infection
10MR – 10 percent severity of a moderately resistant type infection
50S – 50 percent severity of a susceptible type infection
Reaction
No disease
Resistant
Resistant to Moderately Resistant
Moderately Resistant
Moderately Resistant to Moderately Susceptible
Moderately Susceptible
Moderately Susceptible to Susceptible
Susceptible
Observation
O
R
R�MR
MR
MR�MS
MS
MS�S
S
Response value
0.0
0.2
0.3
0.4
0.6
0.8
0.9
1.0
Table 2
The response of individual plants within each population to the type of stripe rust infection
Genotype
Bakhtawar�92
Frontana
Saleem�2000
Tatara
Inqilab�91
Fakhre�Sarhad
Karwan
KAUZ 'S'
Fronteira/Mentana
CHAM�6//KITE/PGO
JUP/ALD "S"//RLT 'S'/3VEE'S')
WL 711/CROW 'S'
PFAU 'S'/SERI/BOW 'S'
C182.2/C166.3/3/CNO/7C2*//CC//TOB/SWM6828
Pakistan (CIMMYT based)
Brazil
Pakistan (CIMMYT based)
NIFA, Peshawar
Pakistan (CIMMYT based)
Pakistan (CIMMYT based)
Pakistan (CIMMYT based)
143.40
35.10
103.20
45.67
244.80
60.29
70.50
Pedigree Origin/Source AUDPC
different groups of genetic models as outlined by
Gai [15, 16]. 1. One major�gene inheritance (A�1,
A�2, A�3 and A�4). 2. Two major�gene inheritance
(B�1, B�2, B�3, B�4, B�5 and B�6). 3. Polygene and
polygene inheritance (D, D�1, D�2, D�3 and D�4).
5. Two Major gene and polygene inheritance (E,
E�1, E�2, E�3, E�4, E�5 and E�6).
The observations were recorded on individual
plants from each of the six populations i.e. the two
homozygous parents (P1 and P2), the first filial
generation (F1), the two backcrosses (B1 and B2)),
and the second filial generation (F2). Based on the
assumptions [13, 14], the data was subjected to
24 types of genetic models of five groups. The most
suitable genetic models in each cross were chosen
by using maximum log of likely hood values [13,
17, 18] and Akaikeґs information criterion (AIC).
Further selection of the best fit genetic model was
made on the basis of least number of significant
values of χ2 statistics, Smirnov statistics and Kol�
mogorov statistics [14]. The data were analyzed by
using statistical software Sin. Exe, the major gene�
polygene mixed inheritance model to a joint analy�
sis of multi�generations [16] specially designed for
six generations i.e. P1, P2, F1, BC1, BC2, and F2. In
case of the best fit model the values of second order
genetic parameters as well as and for B1, B2 and F2
were worked out by using excel program of win�
dows.
Results. Genetic diversity for stripe rust and selec�
tion of genotypes for crosses. Based on Area Under
Disease Progress Curve (AUDPC), Euclidean dis�
similarity coefficient matrix (not shown) was con�
structed for 45 wheat accessions and phenogram
ISSN 0564–3783. Цитология и генетика. 2009 № 428
M. Irfaq, Mir Ajab, Ma Hongxiang, GSS Khattak
Table 3
Grouping based on different clusters for 45 Bread wheat accessions evaluated during 2003
Cluster
1
2
3
Mean/SD Accessions with Euclidean Distances
Frequ�
ency
9
11
13
20
24.44
28.88
104.49 ± 14.31
133.88 ± 13.66
73.57 ± 18.84
%
age
Group A
Group B
Saleem�
2K (6.63)
CB�171
(4.83)
B�92
(7.51)
DRRM
03
(7.14)
Frontana
(13.68)
CT�
02204
(3.38)
CT�
02248
(4.34)
CT�
02306
(5.89)
CM�03�
04
(5.44)
Tatara
(7.34)
CT�
02390
(5.54)
CT�
01183
(6.65)
CT�
01084
(4.19)
V�2156
(6.65)
F�Sarhad
(7.76)
Karwan
(2.81)
CB�61
(8.43)
Metal
Tail
(5.90)
CT�
02009
(5.54)
CT�
99022
(4.98)
CB�185
(8.62
CB�82
(6.21)
CT�
02019
(6.48)
V�03007
(8.46)
AS�2002
(7.84)
CB�148
(4.64)
CT�
02081
(6.48)
CB�145
(10.61)
CB�195
(9.77)
CT�
02266
(2.44)
BANA�4
(16.16)
UQAB
(6.40)
CT�
02267
(3.45)
4
5
9
3
20
6.67
178.65 ± 12.94
244.40 ± 6.61
CT�02192
(5.18)
E�29
(5.91)
Inqilab�91
(6.46)
V�84051
(7.10)
CB�197
(9.79)
Soleman
(4.37)
CB�289
(5.80)
CB�179
(6.92)
CB�196
(6.50)
CB�325
(4.44)
E�41
(4.24)
Mango
(6.28)
Note. In Parentheses is the Euclidian distance representing the repartition/closeness among the lines including in the
same cluster.
ІSSN 0564–3783. Цитология и генетика. 2009. № 4 29
Assessment of genes controlling Area Under Disease Progreess Curve (AUDPC) for stripe rust
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6
9
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0
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5
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7
6
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±
2
3
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5
1
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±
1
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6
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2
±
6
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8
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6
9
9
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0
±
6
0
.8
2
2
5
0
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±
5
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5
7
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9
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3
±
7
5
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6
P
1
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1
P
2
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C
1
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C
2
F
2
5 1
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2 8 1
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iz
e
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e
a
n
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h
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ri
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c
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/S
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o
f
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re
a
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n
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r
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is
e
a
se
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ro
g
re
ss
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ro
ss
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ss
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il
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k
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re
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rh
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)
constructed is presented in Fig. 1. The dissimilarity
range was from 2.44 to 16.16 among all the acces�
sions. The dendrogram showed two groups and five
clusters. Group A consisted on three clusters and B
on two ones. Since the cluster analysis is based on
AUDPC therefore, the clusters were obtained on
the basis of linkage distance and related traits.
Grouping based on different clusters along with
Euclidean distances, means and standard devia�
tion is presented in Table 3. In group A, nine geno�
types i.e. Saleem�2k, CT�02248, CT�01183, CB�
61, CB�185, AS�2002, CB�145 and BANA�4 were
in cluster 1 which presents 20 percent of the total
material (Table 4). The accessions in cluster 1 (9 %
of the total material) showed AUDPC in acceptable
range (104.49 ± 14.31) < (182). Cluster 2 (Table 3)
accounts for 24.44 percent of the total material and
consists of eleven accessions (Bakhtawar�92, CT�
02306, CT�01084, Metal Tail, CB�82, CB�148,
DRRM�03–04, CM�03–04, V�2156).
Cluster 3 is consisted of 28.88 % of the total
population and comprised of thirteen accessions
(Frontana, Tatara, Fakhre�Sarhad, CT�02009,
CT�02019, CT�02081, CT�02266, CT�02267,
CT�02204, CT�02390, Karwan, CT�99022 and V�
03007). Having very low AUDPC (73.57 ± 18.8),
the accessions included in this cluster showed high
level of resistance to the disease and can be utilized
as source of resistance for stripe rust. Clusters 4
and 5 representing 20 and 7 % of the total materi�
ISSN 0564–3783. Цитология и генетика. 2009. № 430
M. Irfaq, Mir Ajab, Ma Hongxiang, GSS Khattak
Fig. 1. Phonogram based on eleven quantitative traits in 45 wheat genotypes used as germplasm
ІSSN 0564–3783. Цитология и генетика. 2009. № 4 31
Assessment of genes controlling Area Under Disease Progreess Curve (AUDPC) for stripe rust
Fig. 2. Frequency distribution of plant population: a – under AUDPC level of F2, P1 and P2
in cross 1; b – under AUDPC level in F2, BC1 and BC2 for cross 1; c – under AUDPC level
in F1, P1 and P2 for cross 3; d – under AUDPC F2, BC1, and BC2 for cross 3
al and with AUDPC of 178.65 and 244.0 respec�
tively were lying in susceptible and highly suscepti�
ble range. On the basis of susceptibility and high
level of resistance to stripe rust, the crosses were
performed between highly susceptible and highly
resistant parents so as to determine the gene action
on the control of the disease.
Genetic control of stripe rust resistance (AUDPC).
The frequency distribution and the mean values
(Table 3), show the tendency of F1 and BC2 towards
the resistant parents (Frontana, and Fakhre�
Sarhad) which were used as the pollen donor par�
ents in the crosses. Normal distribution of F2 and
occurrence of transgressive segregants of resistant
as well as susceptible types indicate the quantita�
tively controlled nature of AUDPC. Transgressive
segregation for resistant plants refers to the pres�
ence of resistant genes in the parents for control�
ling stripe rust. The susceptible transgressive segre�
gants refer to the fact that some negative genes
were also dispersed in the parents which affected
the resistance when came in accumulation in indi�
vidual of F2 or those of subsequent generations.
The frequency distribution represented as linear
bar chart for six generations (Fig. 2) clarify the
behaviour and tendency of each generation in the
crosses. Highest phenotypic variances ranged
between 2504.08 and 6658.02 for the segregating
progenies (Table 4) indicate that the trait was high�
ly influenced by the environmental conditions.
Genes pattern and selection of suitable genetic
models for controlling AUDPC. Using the criterion
of the maximum log of likelihood estimates and
smaller AIC values (Table 5), Model E, E�1 and B�
1 were most suitable for controlling AUDPC in
ISSN 0564–3783. Цитология и генетика. 2009. № 432
M. Irfaq, Mir Ajab, Ma Hongxiang, GSS Khattak
Fig. 2. Finish
Table 5
Maximum likelihood estimates and AIC values for AUDPC
under various genetic models estimated through
the IECM* algorithm
Model
A�1
A�2
A�3
A�4
B�1
B�2
B�3
B�4
B�5
B�6
C
C�1
D
D�1
D�2
D�3
D�4
E
E�1
E�2
E�3
E�4
E�5
E�6
Maximum
log of likeli�
hood
–3862.55
–3874.50
–3992.06
–3922.90
–3727.13
–3807.06
–3858.87
–3911.65
–3991.57
–3991.57
–3771.80
–3813.54
–3737.84
–3759.35
–3759.35
–3807.42
–3785.38
–3701.76
–3722.78
–3765.82
–3729.67
–3781.47
–3800.74
–3771.56
AIC
7733.10
7755.00
7990.12
7851.80
7474.26
7626.12
7725.74
7829.32
7991.15
7989.15
7563.60
7641.08
7499.68
7536.71
7534.71
7630.84
7586.77
7439.53
7475.57
7553.64
7477.34
7578.94
7619.48
7559.12
Model
A�1
A�2
A�3
A�4
B�1
B�2
B�3
B�4
B�5
B�6
C
C�1
D
D�1
D�2
D�3
D�4
E
E�1
E�2
E�3
E�4
E�5
E�6
Maximum
log of like�
lihood
–3900.42
–3913.78
–4086.09
–4038.12
–3769.34
–3852.96
–3945.91
–3929.03
–4074.69
–4074.69
–3788.73
–3828.23
–3768.41
–3778.32
–3778.32
–3813.94
–3793.32
–3756.51
–3760.58
–3790.63
–3778.03
–3796.56
–3816.85
–3781.50
AIC
7808.83
7833.56
8178.18
8082.24
7558.69
7717.92
7899.82
7864.05
8157.38
8155.38
7597.46
7670.46
7560.83
7574.65
7572.65
7643.88
7602.65
7549.02
7551.16
7603.26
7574.06
7609.13
7651.71
7579.00
Cross 1:
Bakhtawar�92 � Frontana
Cross 2:
Inqilab�91 � Fakhre�Sarhad
*IECM: Iterated Expectation and Conditional Maximiza�
tion (Gai and Wang, 1998)
cross 1 while models E�1, D�2 and B�1 were suitable
for cross�2. Further selection of the best fit model
for each cross was made on the basis of least num�
ber of significant values of the five statistics pre�
sented in Table 6, clearly showing that E and E�1
were the best fit models for cross 1 and cross 2
respectively. Using the component parameters given
in Table 7 the first and second order genetic param�
eters for corresponding best fit genetic model for
the two crosses were calcu lated (Table 8).
ІSSN 0564–3783. Цитология и генетика. 2009. № 4 33
Assessment of genes controlling Area Under Disease Progreess Curve (AUDPC) for stripe rust
Table 6
Tests for goodness�of�fit regarding AUDPC of model B�1, E and E�1 for crosses Bakhtawar�92 � Frontana
and Inqilab�91 � Fakhre�Sarhad
Cross 2: Inqilab�91 � Fakhre�Sarhad
Model
E
B�1
E�1
E
E�1
B�1
P1
F1
P2
B1
B2
F2
P1
F1
P2
B1
B2
F2
P1
F1
P2
B1
B2
F2
P1
F1
P2
B1
B2
F2
P1
F1
P2
B1
B2
F2
P1
F1
P2
B1
B2
F2
0.08(0.77)
0.01 (0.92)
0.67 (0.41)
0.82(0.36)
0.02(0.89)
0.60 (0.43)
0.51 (0.47)
12.59 ***
0.17(0.68)
0.00 (0.95)
0.01(0.92)
35.21 ***
0.07 (0.79)
0.00(0.94)
0.84(0.36)
0.75 (0.38)
0.67 (0.41)
6.86**
0.00(0.99)
0.00 (1.0)
0.00 (1.0)
2.75 *
0.01(0.93)
1.22(0.27)
0.12(0.73)
0.00(0.98)
0.12(0.73)
3.57(0.59)
3.02(0.08)
1.20(0.27)
0.12(0.73)
0.12(0.73)
0.14(0.70)
6.77 **
0.40(0.52)
2.25(0.13)
0.33 (0.57)
1.42 (0.23)
2.52 (0.11)
0.06(0.80)
0.15(0.70)
0.69(0.40)
1.58 (0.21)
19.51 ***
0.82 (0.36)
0.03 (0.86)
0.00 (0.96)
46.81 ***
0.28 (0.59)
1.18(0.28)
2.66 (0.10)
0.80 (0.37)
0.59 (0.44)
8.11***
0.57(0.45)
0.54(0.46)
0.79 (0.37)
2.16(0.14)
0.00(0.98)
2.07(0.15)
0.18(0.67)
0.52 (0.43)
1.49(0.22)
3.63(0.06)
2.83(0. 09)
2.77(0.09)
0.03(0.84)
0.85(0.35)
0.00(0.94)
6.15 **
1.75(0.19)
4.23*
11.59 ***
19.00 ***
10.08 ***
6.37 **
0.96(0.32)
0.11(0.73)
5.10 **
15.42 ***
4.12 **
0.24 (0.62)
0.03 (0.86)
19.23 (0.15)
9.77***
21.15 ***
8.87 ***
0.06(0.81)
0.10(0.90)
1.56 (0.21)
9.15***
8.65 ***
12.62***
0.30(0.58)
0.20(0.65)
2.16(0.14)
9.11***
8.71 ***
12.57 ***
0.09(0.76)
0.00(0.99)
5.83**
0.38 (0.54
25.52***
1.28(0.26)
0.03 (0.87)
8.00***
5.82**
0.28 (>0.05)
0.43 (>0.05)
0.10 (>0.05)
0.25(>0.05)
0.05 *
0.11 (>0.05)
0.18*
1.85 (>0.05)
0.22 (>0.05)
0.04 **
0.04***
3.77 (>0.05)
0.24 (>0.05)
0.49 (>0.05)
0.39 (>0.05)
0.19 (>0.05)
0.09 **
0.69 (>0.05)
0.23 (>0.05)
0.19 (>0.05)
0.24 (>0.05)
0.34 (>0.05)
0.03 **
0.23 (>0.05)
0.24 (>0.05)
0.19 (>0.05)
0.31 (>0.05)
0.38 (>0.05)
0.28 (>0.05)
0.28 (>0.05)
0.07 *
0.60 (>0.05)
0.09 **
0.77 (>0.05)
0.33 (>0.05)
0.36 (>0.05)
0.13 *
0.13 *
0.13 *
0.07 *
0.05*
0.05 *
0.11 *
0.23 (>0.05)
0.12**
0.04 **
0.05***
0.21 (>0.05)
0.11**
0.14*
0.13**
0.08 **
0.06*
0.09**
0.09**
0.11***
0.11 ***
0.08**
0.04**
0.07**
0.11**
0.11**
0.12**
0.09**
0.07*
0.07*
0.07**
0.17(>0.05)
0.07**
0.12(>0.05)
0.10***
0.09**
Generation U1
2 U2
2 U2
3
nW2 Dn
Cross 1: Bakhtawar 92 � Frontana
Note. In parenthesis is the probability value. *, **, *** represents the 0.05, 0.01, 0.001 significance levels respectively
U1
2
, U2
2
, U2
3
: χ2
statistics with 1 degree of freedom; nW
2
: Smirnov’s statistics; Dn : Kolmogorov’s statistics.
Genetic model E for cross 1 determines mixed
additive�dominant�epistatic effect of major genes
plus additive – dominant�epistasis of polygenes.
The additive (da, db) and dominant (ha, hb) effects
contributed by two major genes (A & B) to the
control of AUDPC were estimated to be 83.65,
24.83 and –25.19, –6.37 respectively. The positive
signs of the additive effect with respect to major
genes in the cross indicated that AUDPC was con�
trolled by the positive additive action of the major
genes where as the negative signs of the dominant
components of the major genes indicate that
resistance to stripe rust was adversely affected by
the dominant action of the major genes. The dom�
inant ratios (ha/da and hb/db) of the gene A and B
was –0.30 and –0.26 respectively, representing the
predominance of the additive gene action due to
major genes rather then the dominant effect. The
negative signs of non allelic dominant interaction
of the two major genes as well as of additive � addi�
tive effect (i) in the cross indicate the dispersion of
some negative genes in parents (Bakhtawar�92 and
Frontana), which adversely affected resistance to
stripe rust. Therefore, selection for resistance
should be delayed to subsequent generations till
maximum resistant polygenes are accumulated in
the individual plants. The additive � dominant
effect of gene A over gene B (Jab) and that of B over
A (Jba) was 14.67 and 24.08 respectively. The dom�
inant � dominant type of non allelic interaction (l)
was recorded as 10.
Genetic control of AUDPC in cross 2. Model E�
1(best fit for cross 2), representing mixed action of
two major additive�dominance epistatic genes plus
additive�dominant polygenes. The population mean
(242.98) (Table 8) refers to the average AUDPC
equal to the mean of F2 generation. The negative
signs of the dominant effect (–74.29& –100.56)
due to first and second major genes (A & B) in
these crosses represent that resistance to stripe rust
is controlled by negative dominant effect of the
major genes. Additive effect due to the two major
genes (A & B) was conspicuous in controlling
AUDPC in cross Inqilab�91 � Fakhre Sarhad with
higher effect due to gene A (28.32) then that of
gene B (4.34). The negative sign under mixed
additive � additive (i) type of genetic effect repre�
sents the dispersion of some negative polygenes
between the parents (Inqilab and Fakhre Sarhad)
which adversely affect the AUDPC when come in
combination in the segregating progenies. However,
the over all additive effect due to polygene was
higher and positive (91.29) representing the conspic�
uous favourable effect of polygene on AUDPC.
The dominant � dominant (l) type effect was the
highest (101.63) representing the favurability of
ISSN 0564–3783. Цитология и генетика. 2009. № 434
M. Irfaq, Mir Ajab, Ma Hongxiang, GSS Khattak
Table 7
Maximum likelihood estimates of component parameters regarding AUDPC for four Bread wheat crosses
in their respective best fit models
Cross 2: Inqilab 91 � Fakhre�Sarahad (Model E�1)
Parameter
μ1
μ2
μ3
μ41
μ42
μ43
μ1
μ2
μ3
μ41
μ42
μ43
233.28
155.00
65.98
249.10
233.42
175.38
309.53
185.32
78.23
287.82
124.80
124.54
μ44
μ51
μ52
μ53
μ54
μ61
μ44
μ51
μ52
μ53
μ54
μ61
130.23
154.00
101.33
60.55
55.91
256.63
207.04
148.04
228.41
175.61
115.52
258.32
μ62
μ63
μ64
μ65
μ66
μ67
μ62
μ63
μ64
μ65
μ66
μ67
240.96
208.67
182.91
137.76
85.10
91.03
95.29
299.87
95.04
177.54
257.91
299.87
μ68
μ69
σ2
σ4
2
σ5
2
σ6
2
μ68
μ69
σ2
σ4
2
σ5
2
σ6
2
44.31
39.67
355.65
931.67
759.40
355.65
205.12
145.02
276.12
1083.18
1560.68
963.41
Estimate Parameter Estimate Parameter Estimate Parameter Estimate
Cross 1: Bakhtawar 92 � Frontana (Model E)
mixed epistasis due to major genes and polygenes
in controlling AUDPC in Inqilab�91 � Fakhre�
Sarhad. Dominance due to polygenes though small�
er (15.57) but was favourable because of its positive
sign value for controlling the trait (Table 8).
Under the second order genetic parameters
(Table 7), the phenotypic variation (σp2) is parti�
tioned into genetic and environmental variation (σe2)
for the two crosses. The genetic component of vari�
ation in turn is subdivided into variation due to
major genes (σmg2) and polygenes (σpg2). Since resist�
ance to stripe rust is controlled by two major genes
plus polygenes therefore, the phenotypic variance
(σp2) in BC1, BC2 and F2 was higher in both the
crosses. The major�gene heritability (hmg2) which is
the most important second order parameter was
73.49, 48.99 and 87.12 in BC1, BC2 and F2 respec�
tively for cross 1. The polygene heritability (hpg2)
which is less important component was estimated
as 16.90, 36.80 and 6.71 for BC1, BC2 and F2 respec�
tively in cross Bakhtawar�92 � Frontana. For cross
2, the major gene heritability was 72.76, 63.06 and
86.25 where as the polygene heritability was 22.51,
28.14 and 9.61 for BC1, BC2 and F2 respectively.
Discussion and conclusions. Using AUDPC as
the measure of stripe rust resistance in wheat, the
data analysis of the present paper was made under
the procedures outlined by [15, 19] with the
advantage over the method suggested by [20] as the
former has the power to determine the number of
major genes, individual effects due to the major
genes as well as collective effect of the polygenes
involved in the controlling of the trait. Moreover,
the data is subjected to twenty�four different
genetic models as suggested by [16]. According to
the procedure, individual effects of the major
genes were also determined under the second
order genetic parameters (Table 8). In contrast the
later procedure measures the trait only as the poly�
genic system without measuring the effect of indi�
vidual genes [19].
The crosses were between resistant and suscep�
tible parents using the resistant one as the pollen
donor parent in F1. Frequency distribution of plant
population for AUDPC revealed transgressive seg�
regation with respect to susceptibility and resist�
ance in the segregating generations (F2) of all the
crosses. Susceptible transgressive segregants have
ІSSN 0564–3783. Цитология и генетика. 2009. № 4 35
Assessment of genes controlling Area Under Disease Progreess Curve (AUDPC) for stripe rust
Table 8
Estimates of first and second order genetic parameters for Stripe rust resistance (AUDPC) in four bread wheat crosses
Cross 2: Inqilab�91 � Fakhre�Sarhad (Model E�1)
1
st
order
parameter
m1
m2
m3
m4
m5
m6
da
db
m
da
db
ha
hb
ha/da
hb/db
242.98
28.32
4.34
–74.29
–100.56
–2.62
–23.17
i
jab
jba
l
[d]
[h]
–49.10
–83.24
–109.76
101.63
91.29
15.57
σp
2
σmg
2
σe
2
σpg
2
hmg
2 (%)
hpg
2 (%)
5833.14
4244.2
276.12
1312.80
72.76
22.51
3138.64
1979.20
276.12
883.32
63.06
28.14
6658.02
5742.29
276.12
639.62
86.25
9.61
125.65
166.24
175.31
141.47
165.24
145.98
83.65
24.83
ha
hb
ha/da
hb/db
i
jab
jba
l
–25.19
–6.37
–0.30
–0.26
–0.85
14.67
24.08
10.12
3699.50
2718.6
355.65
625.26
73.49
16.90
2504.1
1226.82
355.65
921.63
48.99
36.80
5769.5
5026.59
355.65
387.29
87.12
6.71
σp
2
σmg
2
σe
2
σpg
2
hmg
2 (%)
hpg
2 (%)
Estimate
1
st
order
parameter
Estimate
2
nd
order
parameter
BC1 BC2 F2
Estimate
Cross 1: Bakhtawar�92 � Frontana (Model E)
also been reported by Bjarko and Line [21] for leaf
rust and Ma et al. [22] for stripe rust in wheat.
Transgressive segregants in half diallel wheat crosses
have also been mentioned in case of Septoria tritici
blotch resistant [23]. Both susceptible and resistant
type of transgressive segregants for stripe rust were
reported by [8] in F2 and F3 generations of some
wheat crosses.
The fitness of the two different models (model
E for cross1 and model E�1 for cross 2) in the two
crosses is because of the difference in the genetic
background of the parents involved in the two
crosses. However, AUDPC in both the crosses was
under the control of two major genes plus poly�
genes. The ratios of dominance to additive effect
(h/d) for both the major genes in the two crosses
have negative sign valves, referring to the recessive�
ly controlled nature of AUDPC in both the cross�
es. The positive sign and higher values of the addi�
tive effects due to the major genes show pre domi�
nance of the additive effect on AUDPC in both the
crosses. The estimated additive effects due to
major gene A and B in the crosses were ranging
from 28.32 to 83.65 and 4.34 to 24.83 respectively
(Table 8). The negative and positive signs of the
additive as well as dominant effect due to the major
genes and polygenes in different crosses may occur
due to the difference in the genetic background of
the parents involved in the crosses [19]. Generally,
the dominant and additive effects exerted by poly�
genes were less than those of the major genes. It is
because the polygenes contributed very low frac�
tion to the phenotypic variation (σp2) with very low
values of polygene heritability (16.90, 36.80,
6.71 % in cross 1 and 22.51, 28.14, 9.61 % in cross
2 for BC1, BC2 and F2 respectively). The present
results are in accordance to those found by [19]
regarding resistance to bean fly in soybean with
respect to heritability values due to major genes as
well as polygenes. Under the mix epistasis effect of
both major as well as polygenes for cross 1, nega�
tive genes for controlling AUDPC were present
among the two parents which means that selection
for resistance should be delayed to subsequent gen�
erations till maximum resistant polygenes are
accumulated in more or less homozygous form in
the individual plants. Additive effect with respect
to stripe rust resistance has also been reported by
some recent investigators in some wheat crosses
[17]. The additive � dominant effect (J) due to the
second major gene and dominant � dominant
effect (l) under epistasis was positive for cross 1.
Additive � dominant as well as dominant � domi�
nant epistasis for leaf rust in some wheat crosses
has also been reported by [21] which coincides
with the present results in case of cross 1. An addi�
tive/modifying action of two genes for stripe rust in
a segregating generation resulted from a cross
between susceptible and resistant cultivars of
wheat have also been suggested [4]. In another
study [8], segregation ratio of 1: 2: 5, has been
reported suggesting the involvement of three genes
with epistasis for resistance to stripe rust at
seedling stage. In a cross between highly resistant
and susceptible parents, two genes were suggested
with additive effect to be responsible for stripe rust
resistance in wheat [22].
Based on a joint scaling test, while conducting
studies on gene action regarding durable, high�
temperature, adult�plant (HTAP) resistance for
stripe rust in parental, F1, F2 and backcross popu�
lations for some crosses in wheat, [24] reported the
involvement of epistasis in controlling AUDPC
with significant additive � additive component.
Using generation mean analysis, [25] has reported
additive�dominance model (absence of epistasis)
digenic epistasis with predominant additive gene
effect, significant «i» type and «l» type of epistatic
interaction for powdery mildew in different cross�
es of wheat. The previous results are more or less in
correspondence with the two crosses of the present
study.
However, the contradictions between the pres�
ent and the previous results might because all these
previous investigators used either diallel or genera�
tion mean analysis as the statistical approach
which measure the genetic effect as the polygenic
system and have no power to determine the effect
of the individual major genes and aggregate effect
of the polygene.
The first author acknowledges the award of schol�
arship by Higher Education Commission of Pakistan
(HEC) as a visiting Scientist to Institute of Biotech�
nology, Jiangsu Academy of Agricultural Science,
Nanjing, China. The statistical procedures adapted
in the present study were suggested by Prof. Dr.
Hongxiang Ma, Head, Institute of Biotechnology,
Jiangsu Academy of Agricultural Science, Nanjing,
China for which the author acknowledges his efforts.
ISSN 0564–3783. Цитология и генетика. 2009. № 436
M. Irfaq, Mir Ajab, Ma Hongxiang, GSS Khattak
M. Irfag, Mir Ajab, Ma Hongxiang, GSS Khattak
ASSESSMENT OF GENES CONTROLLING AREA
UNDER DISEASE PROGREESS CURVE (AUDPC)
FOR STRIPE RUST
Генетические эффекты контроля устойчивости к
желтой ржавчине злаков были определены в двух
скрещиваниях пшеницы Bakhtawar�92 � Frontana
(скрещивание 1) и Inquilab�91 � Fakhre�Sarhad (скре�
щивание 2) с использованием Area Under Disease
Progress Curve (AUDPC) для измерения устойчивости.
Устойчивые и чувствительные генотипы в этих скре�
щиваниях были определены с помощью начальной
оценки на устойчивость к желтой ржавчине 45 образ�
цов пшеницы. Модель смешанного наследования бы�
ла применена к анализу данных шести основных по�
пуляций P1, F1, P2, B1, B2 и F2 в скрещиваниях. Резуль�
таты показали, что AUDPC в скрещивании 1 контро�
лируется двумя основными генами с аддитивно�до�
минантным эпистатическим эффектом и полигенами
с аддитивно�доминантными эпистатическими эф�
фектами (модель Е). В случае скрещивания 2 – под
контролем двух основных генов с аддитивно�доми�
нантным эпистатическим эффектом плюс аддитивно�
доминантных полигенов (модель Е�1). Аддитивный
эффект был преобладающим над всеми остальными
типами генетических эффектов, что позволяет пред�
положить задержку селекции на устойчивость до тех
пор, пока максимальное количество позитивных ге�
нов накапливается у особей последующих поколений.
Наличие трансгрессивных сегрегантов на чувстви�
тельность и устойчивость показало наличие как генов
устойчивости, так и неких негативных генов у родите�
лей. Наследуемость основного гена было выше, чем
наследуемость полигенов для B1, B2 и F2 в скрещива�
ниях. Наследуемость основного гена так же, как и по�
лигенов, была в пределах от 48,99 до 87,12 % и от
2,26 до 36,80 % для двух скрещиваний соответствен�
но. Наибольшая фенотипическая вариабельность
в AUDPC (от 2504.10 до 5833,14) в сегрегирующих по�
колениях (ВС1, ВС2 и F2) показывает, что на проявле�
ние признака влияют факторы окружающей среды.
M. Irfag, Mir Ajab, Mа Hongxiang, GSS Khattak
ASSESSMENT OF GENES CONTROLLING AREA
UNDER DISEASE PROGREESS CURVE (AUDPC)
FOR STRIPE RUST
Генетичні ефекти контролю стійкості до жовтої ір�
жі злаків були визначені в двох схрещуваннях пшени�
ці Bakhtawar�92 � Frontana (схрещування 1) и Inquilab�
91 � Fakhre�Sarhad (схрещування 2) з використанням
Area Under Disease Progress Curve (AUDPC) для вимі�
рювання стійкості. Стійкі та чутливі генотипи в цих
схрещуваннях були визначені за допомогою початко�
вої оцінки на стійкість до жовтої іржі 45 зразків пше�
ниці. Модель змішуваного спадкування була застосо�
вана до аналізу даних шести основних популяцій P1,
F1, P2, B1, B2 та F2 в схрещуваннях. Результати показа�
ли, що AUDPC у схрещуванні 1 контролюється двома
основними генами з адитивно�домінантним епіста�
тичним ефектом і полігенами з аддитивно�домінант�
ними епістатичним ефектами (модель Е). У випадку
схрещування 2 – під контролем двох основних генів
з адитивно�домінантним епістатичним ефектом плюс
адитивно�домінантних полігенів (модель Е�1). Ади�
тивний ефект був переважаючим над всіма іншими
типами генетичних ефектів, що дозволяє припустити
затримку селекції на стійкість до того часу, поки мак�
симальна кількість позитивних генів накопичується
у особин наступних поколінь. Наявність трансгресив�
них сегрегантів на чутливість та стійкість показала на�
явність як генів стійкості, так і деяких негативних ге�
нів у батьків. Успадковування основного гена було ви�
ще, ніж успадкування полігенів B1, B2 та F2 в схрещу�
ваннях. Успадковування основного гена, також
як і полігенів була в межах від 48,99 до 87,12 % та від
2,26 до 36,80 % для двох схрещувань, відповідно. Най�
більша фенотипічна варіабельність в AUDPC (від
2504.10 до 5833.14) в сегрегуючих поколіннях (BС1,
BС2 та F2) показує, що на виявлення ознаки вплива�
ють фактори оточуючого середовища.
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ISSN 0564–3783. Цитология и генетика. 2009. № 438
M. Irfaq, Mir Ajab, Ma Hongxiang, GSS Khattak
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