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Characterization of two new Puccinia graminis f. sp. tritici
races within the Ug99 lineage in South Africa
Botma Visser •Liezel Herselman •
Robert F. Park •Haydar Karaoglu •
Cornelia M. Bender •Zacharias A. Pretorius
Received: 29 July 2010 / Accepted: 19 September 2010 / Published online: 5 October 2010
ÓSpringer Science+Business Media B.V. 2010
Abstract Two new races of the wheat (Triticum
aestivum L.) stem rust pathogen, representing the fifth
and sixth variants described within the Ug99 lineage,
were detected in South Africa. Races TTKSP and
PTKST (North American notation) were detected in
2007 and 2009, respectively. Except for Sr24 viru-
lence, race TTKSP is phenotypically identical to
TTKSF, a commonly detected race of Puccinia
graminis f. sp. tritici (Pgt) in South Africa. PTKST
is similar to TTKSP except that it produces a lower
infection type on the Sr21 differential and has
virulence for Sr31. Simple sequence repeat (SSR)
analysis confirmed the genetic relationship amongst
TTKSF, TTKSP, PTKST and TTKSK (Ug99).
TTKSK, PTKST and TTKSF grouped together with
99% similarity, while sharing 88% genetic resem-
blance with TTKSP. These four races in turn shared
only 31% similarity with other South African races.
It is proposed that both TTKSP and PTKST represent
exotic introductions of Pgt to South Africa.
Keywords Pathotype Stem rust Triticum
aestivum Wheat TTKSK
Introduction
Puccinia graminis f. sp. tritici (Pgt) is the causal
agent of stem rust, a historically important (Saari and
Prescott 1985) and recurring (Singh et al. 2006,2008)
disease of wheat. It is highly adapted to long distance
migration through wind dispersal and rain deposition
of urediniospores (Rowell and Romig 1966; Singh
et al. 2006). In addition to natural dispersal mecha-
nisms, accidental transport by means of contaminated
clothing or goods may also contribute to the spread of
spores (Singh et al. 2006).
Currently more than 60 numbered or temporarily
designated Sr genes for resistance to stem rust are
listed in the Komugi Wheat Genetics Resource
Database (www.shigen.nig.ac.jp, accessed 16 April
2010). Utilization of many of these genes in breeding
programs has resulted in the effective control of stem
rust in most countries (Singh and McIntosh 1987;
McIntosh et al. 1995; Singh et al. 2008). However,
the detection of Ug99 (syn. TTKSK, North American
[NA] race notation, Jin et al. 2008b) in East Africa,
aPgt race with broad virulence (Pretorius et al. 2000;
B. Visser (&)L. Herselman C. M. Bender
Z. A. Pretorius
Department of Plant Sciences, University of the Free
State, P.O. Box 339, Bloemfontein 9300, South Africa
e-mail: visserb@ufs.ac.za
R. F. Park H. Karaoglu
Plant Breeding Institute Cobbitty, The University
of Sydney, Private Mail Bag 11, Camden, NSW 2570,
Australia
123
Euphytica (2011) 179:119–127
DOI 10.1007/s10681-010-0269-x
Wanyera et al. 2006; Jin et al. 2007) and adaptive
capacity (Jin et al. 2008a,2008b,2009), indicated that
continued efforts are necessary to control this disease.
The rapid adaptation of Ug99 for Sr24 virulence (Jin
et al. 2008b) was of particular concern as this gene
occurs in Kenyan commercial varieties (MacKenzie
2008). Sr24 continues to be widely used in countries
such as Australia (Park and Bariana 2008) and South
Africa (McIntosh et al. 1995). According to marker
data it is assumed that approximately 20% of South
African commercial cultivars and elite germplasm
carry the Sr24 gene (Z. A. Pretorius unpublished
data). Sr24 was initially identified as a source of
resistance to Ug99 (Jin et al. 2007).
It was recently shown that, in addition to step-wise
mutations, an exotic introduction contributed to the
genetic diversity of the South African Pgt population
(Visser et al. 2009). TTKSF, the most prevalent race
in South Africa since its first detection in 2000, shares
an identical virulence profile with Ug99, except for
avirulence towards Sr31 (Pretorius et al. 2007). This
resemblance was confirmed at the molecular level
using SSR and AFLP analyses (Visser et al. 2009).
Ug99 and TTKSF were distinctly different from the
other South African races, suggesting that TTKSF
was an exotic introduction into South Africa, most
probably from Ug99 ancestry in East Africa.
Two races with Sr24 virulence, namely 2SA100
and 2SA101 (Agricultural Research Council [ARC]
notation), were detected in South Africa during the
mid 1980s (Le Roux and Rijkenberg 1987). These
closely related races are avirulent and virulent to
Sr9g, respectively, and were distinctly different from
Ug99 (Jin et al. 2008b; Visser et al. 2009). Consid-
ering the data of Le Roux and Rijkenberg (1987)on
comparable entries in the current NA differential set,
2SA100 and 2SA101 code to LSH and LTH,
respectively. In 2007, TTKSP (2SA106) with Sr24
virulence was detected in the Western Cape, South
Africa (Terefe et al. 2010). Phenotypically, this race
is similar to TTKST except for avirulence to Sr31,
and similar to TTKSF except for virulence to Sr24.A
second new race, PTKST, was detected at two
locations in KwaZulu-Natal, South Africa, at the
end of 2009 (Pretorius et al. 2010). PTKST is virulent
to both Sr24 and Sr31. The objective of this study
was to determine the relationship between TTKSF,
TTKSP, PTKST, TTKSK and other Pgt stem rust
races using SSR markers.
Materials and methods
Stem rust isolates
In this study, the South African Pgt races were
represented by four single pustule isolates each of
UVPgt50, 52, 53, 55, 56, 57, 59 and 60. UVPgt58
was represented by a single isolate. All single pustule
isolates were sub-samples from the type culture of
each race and do not reflect different field collections.
The UVPgt notations reflect the wheat stem rust
cultures held at the University of the Free State.
UVPgt50, 52, 53, 55, 56, 58 and 59 are equivalent to
races 2SA4, 2SA100, 2SA102, 2SA88, 2SA104,
2SA103 and 2SA106 named by the ARC-Small
Grain Institute, Bethlehem. UVPgt57 appears to be a
single-gene mutant of UVPgt56, differing only in
virulence for SrSatu (present in Australian triticale
cultivar Satu). Likewise, UVPgt58 is similar to
UVPgt53 except for avirulence to Sr9g and UVPgt59
is similar to UVPgt55 except for Sr24 virulence in the
former. Ug99 (TTKSK, Jin et al. 2008b), from the
original Ugandan collection in 1999 (Pretorius et al.
2000), was also included.
UVPgt59 (TTKSP), received as stem rust field
collection Pg-KGI-49 from the ARC-Small Grain
Institute in 2007, was sampled from an unknown
wheat line at the Tygerhoek Experimental Farm,
Western Cape, on 26 September, 2007. UVPgt60
(PTKST) was collected on 17 November, 2009, from
a wheat cultivar suspected of carrying Sr31 in a
disease nursery near Greytown, KwaZulu-Natal.
Virulence was confirmed on several wheat cultivars
known to possess the Sr31 resistance gene (Pretorius
et al. 2010). Both races were phenotypically charac-
terized on a differential set (Table 1) using standard
procedures for inoculation of seedlings and recording
of infection types (Jin et al. 2008b). Phenotyping was
repeated in at least three independent experiments.
Single-pustule isolates of UVPgt59 and UVPgt60
were increased on wheat lines LCSr24Ag (Sr24) and
Federation*4/Kavkaz (Sr31), respectively. Uredini-
ospores were harvested and germinated as previously
described (Visser et al. 2009).
Genomic DNA extraction for SSR analysis
Total genomic DNA was isolated from fungal tissue
of the UVPgt59 and UVPgt60 isolates using CTAB
120 Euphytica (2011) 179:119–127
123
according to Saghai-Maroof et al. (1984) and as
described in Visser et al. (2009). For the other races,
previously extracted genomic DNA (Visser et al.
2009) was used in the SSR analyses.
SSR analysis of Pgt races
SSR analysis of all isolates was done using 24 primer
combinations that were developed at the Plant
Breeding Institute Cobbitty, University of Sydney,
Australia (H. Karaoglu and R.F. Park unpublished
data). The isolates of UVPgt59 and UVPgt60 were
also fingerprinted with SSR primer combinations
described by Szabo (2007) and used by Visser et al.
(2009). Selected isolates previously used by Visser
et al. (2009) were again fingerprinted using both SSR
primer sets to facilitate correlation between the two
data sets.
Each 15 ll PCR reaction contained 10 ng total
genomic DNA, 10 pmol of each primer and a 19
concentration of KapaTaq ReadyMix (KapaBiosys-
tems, Cape Town, South Africa). The amplification
regime was 94°C for 1 min, followed by 31 cycles of
94°C for 30 s, 53 or 55°C for 30 s (depending on the
primer pair used) and 72°C for 30 s. A final elongation
step of 10 min at 72°C was included. To confirm
success of the amplifications, 5 ll of each PCR mixture
was analysed on a 1.5% (w/v) agarose gel (Sambrook
et al. 1989). Polyacrylamide gel electrophoresis was
performed as described in Visser et al. (2009).
Table 1 Infection types produced by Pgt races TTKSK (Ug99), TTKSF (UVPgt55), TTKSP (UVPgt59) and PTKST (UVPgt60) on
differentiating lines and scored according to the 0 to 4 scale (Stakman et al. 1962)
Entry Sr gene Infection type
TTKSK
a
TTKSF TTKSP PTKST
ISr5-Ra 53?
b
444
Cns_T_mono_deriv 21 Not tested 3– 3 22??
Einkorn 21 1 2 2 ;1=
Vernstein 9e 3?444
ISr7b-Ra 7b 4444
ISr11-Ra 11 3?444
ISr6-Ra 64444
ISr8a-Ra 8a 3?444
Acme 9g 3?444
W2691SrTt-1 36 ;1 =c0; 0; 0;
W2691Sr9b 9d 3?444
Festiguay 30 3?3?? 3?? 3??
Renown 17 3?3?? 3?? 3??
ISr9a-Ra 9a Not tested 4 4 4
ISr9d-Ra 9d Not tested 4 4 4
W2691Sr10 10 Not tested 4 4 4
CnsSrTmp Tmp Not tested 2 2 2
LCSr24Ag 24 1233
Sr31/6*LMPG 31 41?14
Trident 38 3?3?? 3?3??
McNair 701 McN 4444
Barleta Benvenuto 8b 4444
Coorong (triticale) 27 ;;;;
Kiewiet (triticale) Unknown ; ; ; ;
Satu (triticale) Satu Not tested ; ; ;
a
Data from the original description of Ug99 (Pretorius et al. 2000). Tester lines different from the current set were Reliance (Sr5),
Vernal (Sr9e), Marquis (Sr7b), Yalta (Sr11), W2402 (Sr9b), Gamka (Sr24) and Federation4*/Kavkaz (Sr31)
Euphytica (2011) 179:119–127 121
123
Data analysis
A binary matrix recording specific SSR fragments as
present (1) or absent (0) was generated for each isolate.
Pairwise genetic distances were expressed as the
complement of Jaccard’s similarity coefficient (Jaccard
1908). Cluster analyses were performed using UPGMA
(unweighted pairgroup method using arithmetic aver-
ages; Sokal and Michener 1958). Statistical analyses
were computed using NTSYS-pc version 2.02i (Rohlf
1998; Exeter Software, NY, USA) and dendrograms
were created using the SAHN program of NTSYS-pc.
The robustness of the dendrogram was tested by
estimating the co-phenetic correlation values for each
dendrogram and comparing them with the original
genetic similarity matrix using Mantel’s matrix corre-
spondence test (Mantel 1967). Values were calculated
using the COPH and MXCOMP programs. To assess
the genetic variation among races and among isolates
within races, analysis of molecular variance (AMOVA)
(Excoffier et al. 1992) was performed using the
statistical program Arlequin version 3.1 (Excoffier
et al. 2005). AMOVA was performed to test the
structure among races and groups based on UPGMA
clustering results (Visser et al. 2009). The significance
levels for all AMOVA tests were set at 0.05. The
fixation index F
ST
was calculated and provided a
measure of genetic differentiation of groups. Values of
F
ST
greater than 0.25 indicate significant genetic
differentiation (Hartl and Clark 1997).
A minimum-spanning network was constructed
based on the minimum number of markers between
different genotypes. The network was constructed
using NETWORK 4.5.0.0 software (www.fluxus-
engineering.com), employing the median-joining
approach (Bandelt et al. 1999).
Results and discussion
Virulence profiles of TTKSP and PTKST
The infection type (IT) data in Table 1show that
UVPgt59 differed from UVPgt55 (TTKSF) only by
its virulence to Sr24 and it was thus coded TTKSP
(Table 1) according to the NA nomenclature system
(Jin et al. 2008b). In addition to Sr31 virulence,
isolate UVPgt60 differed from TTKSF and TTKSP
only in regard to the IT on the Sr21 differentials. All
eight single-pustule isolates, sub-cultured from
UVPgt60, produced an intermediate IT (2 to 2??)
on the Sr21 differential line CS_T mono_deriv
(Table 1) and coded to PTKST. The UVPgt60
isolates also produced a clear low IT (;1 =) on
T. monococcum cv. Einkorn, the original Stakman
et al. (1962) differential for Sr21 (Pretorius et al.
2010). TTKSF and TTKSP produced IT 3 on CS_T
mono_deriv and IT 2 on Einkorn. The discrepancy in
the response of lines containing Sr21 to isolates within
the Ug99 lineage warrants further investigation.
Based on stem rust phenotype, TTKSP appeared to
be a single step mutant from TTKSF. Given the
existence of TTKSP in South Africa, the initial
conclusion was that this race added virulence for Sr31
to give rise to PTKST. However, the low reaction
conferred by Sr21 suggested that PTKST may be an
introduction rather than a local adaptation from
TTKSP. Infection type data recorded during the
original description of Ug99 (TTKSK) (Pretorius
et al. 2000) are also included in Table 1.
Marker polymorphism
Among the 24 SSR markers developed at the
University of Sydney and tested on genomic DNA
extracted from 33 South African and four Ug99
isolates of Pgt, six primer pairs failed to amplify
fragments. Another two each amplified a single faint
fragment. The latter amplifications were not repeat-
able and these eight primer pairs were therefore
excluded from the analysis. The remaining 16 SSR
primer combinations amplified a total of 69 alleles of
which 54 (78%) were polymorphic (Table 2). The
number of alleles ranged from one for primer pair
A19 to 17 for primer pair A2 with a mean of 4.3 per
primer pair. Fifteen monomorphic alleles were
amplified by nine primer pairs. In contrast to the
SSR study by Visser et al. (2009), the amplified
polymorphic alleles were not only present in TTKSK
and TTKSF and absent in the other races or vice
versa, but polymorphisms were evident between
different races that originally grouped together.
Genetic diversity
Previously, SSR analysis of UVPgt50, UVPgt52,
UVPgt53, UVPgt55, UVPgt56, UVPgt57, UVPgt58
and Ug99 using primer combinations developed by
122 Euphytica (2011) 179:119–127
123
Szabo (2007) divided the races into two groups with
one consisting of Ug99 and UVPgt55 and the second
group containing the rest (Visser et al. 2009). It was
not possible to distinguish between races within each
group, as well as between isolates of each race,
except for one isolate (56.2) of UVPgt56 which had a
unique banding pattern. After combining the SSR
data of UVPgt59 and UVPgt60 with that generated
for the other races using the Szabo (2007) primers, a
dendrogram was constructed using Jaccard’s coeffi-
cient of similarity and UPGMA for clustering. Based
on the available data, the 37 isolates were again
divided into two groups (Fig. 1). There was a good fit
between the Jaccard’s coefficient matrix and the
symmetrical matrix produced by the UPGMA-based
dendrogram with the cophenetic correlation coeffi-
cient (r) being 0.9987.
The first group (Fig. 1) consisted of UVPgt55,
UVPgt59, UVPgt60 and Ug99, whereas the second
group contained the remaining races. The genetic
similarity between the two groups increased from
24.5% previously (without UVPgt59 and UVPgt60)
to 36%. Within the first group, UVPgt55, UVPgt60
and Ug99 clustered separately from UVPgt59 with a
similarity of 97%, but it was again impossible to
distinguish between the other races.
To improve the resolution between the individual
isolates of the different races, a dendrogram (r=
0.9958) was constructed using the 69 SSR alleles
generated using SSR primer pairs developed at the
University of Sydney (Fig. 2). Again, two major groups
were found with the genetic similarity between the two
groups decreasing to 27%. Within the first group,
UVPgt55, UVPgt60 and Ug99 clustered separately
from UVPgt59 with an 81% similarity between the two
subgroups. Isolates Ug99.1, Ug99.2 and Ug99.3, clus-
tering with UVPgt60, showed a genetic similarity of
97% with isolate Ug99.4 that clustered with UVPgt55.
Within the second group, two subgroups were
evident (genetic similarity of 73%) with isolates from
UVPgt50, UVPgt52, UVPgt53 and UVPgt57 cluster-
ing together with a similarity of 93%. Isolates of
UVPgt53 fell into two smaller groups indicating
genetic heterogeneity between the four isolates. The
second subgroup consisted of isolates from UVPgt56
and UVPgt58 with a genetic similarity of 92%.
When the two SSR data sets were used to construct
a combined dendrogram (Fig. 3), a similar pattern
was observed (r=0.9997) except that the genetic
similarity of the different associations was lower than
that using the Szabo (2007) primers, but higher than
when the University of Sydney primers were used. It
was still impossible to distinguish between UVPgt50,
UVPgt52 and UVPgt57, whereas there was some
differentiation between different isolates from
UVPgt53 and UVPgt56.
AMOVA was used to determine the main source
of genetic variation. When isolates of all races were
divided into two groups (UVPgt55, UVPgt59,
UVPgt60 and Ug99 in group 1 and the other races
in group 2 based on dendrogram results) 91.3%
(P\0.001) of the molecular variability could be
attributed to variation between the two groups, with
Table 2 Number of alleles and allele sizes generated by 16
SSR primer pairs developed at the University of Sydney
Locus N
a
a
N
p
b
Allele size (bp)
A1 2 2 405 402
A2 17 15 336 333 331 329 327 326 324
323 321 316 313 310 308
303 297 295 269
A4 3 2 241 238 230
A6 2 0 320 305
A7 10 9 311 306 299 297 294 291 285
279 276 273
A8 3 3 286 283 277
A10 3 3 594 389 358
A11 3 2 364 330 327
A12 5 2 241 235 230 222 216
A13 2 2 464 457
A15 3 2 247 243 231
A17 5 2 243 236 231 221 216
A19 1 0 244
A20 2 2 318 312
A21 5 5 233 229 225 219 134
A23 3 3 322 320 316
Total number
of alleles
69 54
Percentage
of polymorphic
alleles
78
Average number
of alleles per
primer set
4.3 3.4
Monomorphic allele sizes are underlined while the polymorphic
allele sizes are in normal script
a
N
a
, number of alleles
b
N
p
, number of polymorphic alleles
Euphytica (2011) 179:119–127 123
123
Jaccard similarity coefficient
0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
50.1
50.2
50.3
50.4
52.1
52.2
52.3
52.4
53.1
53.2
53.3
53.4
56.1
56.3
56.4
57.1
57.2
57.3
57.4
58.1
56.2
55.1
55.2
55.3
55.4
Ug99.1
Ug99.2
Ug99.3
Ug99.4
60.1
60.2
60.3
60.4
59.1
59.2
59.3
59.4
Fig. 1 Dendrogram of 37
Pgt isolates based on
UPGMA cluster analysis
and the Jaccard similarity
coefficients calculated from
38 SSR alleles (Visser et al.
2009) generated using SSR
primer pairs developed by
Szabo (2007)
Jaccard similarity coefficient
0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
50.1
50.2
50.3
50.4
52.1
52.2
52.3
52.4
57.1
57.2
57.3
57.4
53.2
53.4
53.1
53.3
56.1
58.1
56.2
56.3
56.4
55.1
55.2
55.3
55.4
Ug99.4
Ug99.1
Ug99.2
Ug99.3
60.1
60.2
60.3
60.4
59.1
59.2
59.3
59.4
Fig. 2 Dendrogram of 37
Pgt isolates based on
UPGMA cluster analysis
and the Jaccard similarity
coefficients calculated from
69 SSR alleles generated
using SSR primer pairs
developed at the University
of Sydney
124 Euphytica (2011) 179:119–127
123
7.9% attributed to variation among races within
groups and 0.71% among isolates within each race.
The F
ST
value of 0.993 was indicative of the high
genetic differentiation among the races.
A minimum-spanning network of the combined data
(Fig. 4) produced a pattern similar to Fig. 3. A total of
74 mutational events separated the two main groups.
Within one group, all UVPgt59 isolates were separated
Jaccard similarity coefficient
0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00
50.1
50.2
50.3
50.4
52.1
52.2
52.3
52.4
57.1
57.4
57.2
57.3
53.2
53.4
53.1
53.3
56.1
58.1
56.2
56.3
56.4
55.1
Ug99.4
55.4
55.2
55.3
Ug99.1
60.4
60.1
60.2
Ug99.2
Ug99.3
60.3
59.1
59.3
59.4
59.2
Fig. 3 Dendrogram of 37
Pgt isolates based on
UPGMA cluster analysis
and the Jaccard similarity
coefficients calculated from
107 SSR alleles generated
using SSR primer pairs
developed by Szabo (2007)
and the University of
Sydney
58.1
2
2
56.2
74
10
56.1
56.3
56.4
50.1-50.4
52.1-52.4
57.1-57.4
53.1
53.3
53.2
53.4
55.1-55.4
Ug99.4
59.1-59.4
Ug99.1-Ug99.3
60.1-60.4 9
2
Fig. 4 Minimum-spanning network of 37 tested Pgt isolates
based on the combined SSR data set generated by primers
developed by Szabo (2007) and the University of Sydney. The
diameter of each filled node is proportional to the number of
rust isolates and the dark coloured sections represent a single
isolate with that specific genotype. Open nodes indicate
hypothetical intermediate genotypes. The number indicated
next to the connecting lines represents the number of
mutational events separating each genotype. No number
represents a single event
Euphytica (2011) 179:119–127 125
123
by nine mutational events from three Ug99 isolates and
the UVPgt60 isolates and by one further mutationalstep
from the four isolates of UVPgt55 and one isolate of
Ug99. In the other group, the cluster consisting of all
four isolates of each of UVPgt50, UVPgt52 and
UVPgt57 were separated by ten events from a hypo-
thetical intermediate isolate linked to UVPgt56 and
UVPgt58. Results indicated the possibility of recom-
bination between isolates of UVPgt56 and UVPgt58.
Conclusions
Based on infection type and SSR results, the close
genetic relationship between TTKSP (UVPgt59),
TTKSF (UVPgt55), PTKST (UVPgt60) and TTKSK
(Ug99) was confirmed. TTKSP is the fifth described
variant within the Ug99 lineage (Jin et al. 2008a). The
IT data strongly suggested that TTKSP represents a
single step variant of TTKSF whereby it acquired Sr24
virulence. This hypothesis was supported by the fact
that both these races are avirulent to Sr31. However,
from the SSR and minimum spanning network data it is
clear that TTKSP is genetically more distant from
Ug99 than TTKSF. Since the sexual phase of Pgt has
never been detected in South Africa due to the apparent
absence of a susceptible alternate host, TTKSP may
represent an exotic introduction. Further research is
needed to determine the relationship of TTKSP with
other African Pgt isolates within the Ug99 lineage.
PTKST, the sixth described race in this group, also
seems to be a Pgt introduction to South Africa and
highlights the vulnerability of the wheat industry to
foreign pathogenic races. This emphasizes the need
for regular monitoring of the stem rust pathogen, in
particular isolates in the variable Ug99 lineage, as
well as continued resistance breeding.
Acknowledgments The Winter Cereal Trust is acknowledged
for funding this project.
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