Virulence Structure of Blumeria graminis f. sp. tritici and Its Genetic Diversity by ISSR and SRAP Profiling Analyses
et al. (2015) Virulence Structure of Blumeria
graminis f. sp. tritici and Its Genetic Diversity by ISSR
and SRAP Profiling Analyses. PLoS ONE 10(6):
Virulence Structure of Blumeria graminis f. sp. tritici and Its Genetic Diversity by ISSR and SRAP Profiling Analyses
Na Liu 0 1
Z. Lewis Liu 0 1
Guoshu Gong 0 1
Min Zhang 0 1
Xu Wang 0 1
You Zhou 0 1
Xiaobo Qi 0 1
Huabao Chen 0 1
Jizhi Yang 0 1
Peigao Luo 0 1
Chunping Yang 0 1
0 1 College of Agronomy, Sichuan Agricultural University , Chengdu, Sichuan , China , 2 National Center for Agricultural Utilization Research, Agricultural Research Service, U.S. Department of Agriculture , Peoria , Illinois, United States of America, 3 College of Resources, Sichuan Agricultural University , Chengdu, Sichuan , China
1 Editor: David A Lightfoot, College of Agricultural Sciences , UNITED STATES
Blumeria graminis f. sp. tritici, which causes wheat powdery mildew, is an obligate biotrophic pathogen that can easily genetically adapt to its host plant. Understanding the virulence structure of and genetic variations in this pathogen is essential for disease control and for breeding resistance to wheat powdery mildew. This study investigated 17 pathogenic populations in Sichuan, China and classified 109 isolates into two distinct groups based on pathogenicity analysis: high virulence (HV, 92 isolates) and low virulence (LV, 17 isolates). Populations from Yibin (Southern region), Xichang (Western region), and Meishan (Middle region) showed lower virulence frequencies than populations from other regions. Many of the previously known resistance genes did not confer resistance in this study. The resistance gene Pm21 displayed an immune response to pathogenic challenge with all populations in Sichuan, and Pm13, Pm5b, Pm2+6, and PmXBD maintained resistance. AMOVA revealed significantly higher levels of variation within populations and lower levels of variation among populations within regions. High levels of gene flow were detected among populations in the four regions. Closely related populations within each region were distinguished by cluster analyses using ISSR and SRAP alleles. Both ISSR and SRAP allele profiling analyses revealed high levels of genetic diversity among pathogenic populations in Sichuan. Although ISSR and SRAP profiling analysis showed similar resolutions, the SRAP alleles appeared to be more informative. We did not detect any significant association between these alleles and the virulence or pathogenicity of the pathogen. Our results suggest that ISSR and SRAP alleles are more efficient for the characterization of small or closely related populations versus distantly related populations.
Competing Interests: The authors have declared
that no competing interests exist.
Wheat powdery mildew is a destructive disease worldwide that is caused by Blumeria graminis
(DC.) Speer f. sp. tritici emend. É. J. Marchal. In favorable climates, this pathogenic fungus
infects the entire leaf surface, causing leaves to wither and resulting in severe yield losses. In
Sichuan Province, an important wheat-producing region in southwest China, the disease
generally causes yield losses of 5 to 8%. In severe epidemics, local farms have reported yield losses of
up to 100% . Growing disease-resistant cultivars is a common practice for disease
management. However, new versions of pathogens often emerge rapidly and overcome host resistance
. Because of the geographically distinct climates in Sichuan, pathogens can over-summer in
cool climates with altitudes above 595 m. The pathogen populations that over-summer on
volunteer wheat plants can serve as an infection source and can attack wheat plants at lower
attitudes, potentially causing gene flow and reconstruction of the pathogen population .
To achieve an efficient wheat powdery mildew disease resistance breeding program, it is
necessary to understand the virulence frequency of powdery mildew and identify a source of
resistance genes (Pm genes). Recently, due to high selective pressure from improper application
and arrangement of resistant cultivars, the population structure of this pathogen has
undergone rapid changes, and frequent shifts in the avirulence genes have occurred. This has led to
loss-of-function of mutations in the corresponding Pm genes in China, including Pm1 and the
Pm3 series [3–5]. Meanwhile, the virulence structure of the B. graminis f. sp. tritici population
has also been affected by geographic distribution . Although wheat powdery mildew
populations have been widely studied, associations between the genetic backgrounds of wheat
powdery mildew populations and their virulence in southwest China have not been explored. This
lack of knowledge hinders disease control and genetic engineering efforts toward the
development of disease-resistant cultivars.
The frequency of virulence to prevalent resistance genes is typically determined by the
conventional evaluation method using a set of wheat cultivars; however, the ability of this method
to detect genetic backgrounds that mediate the virulence of the pathogen is limited . To
understand the genetic diversity of wheat powdery mildew, reliable molecular evidence is
needed. Historically, numerous DNA-based tools have been applied in population studies of
plant pathogens, such as random amplified polymorphic DNA (RAPD), simple sequence
repeats (SSRs), restriction fragment length polymorphisms (RFLPs) and amplified fragment
length polymorphisms (AFLPs) [7–11]. However, most of these tools have some limitations in
population genetics . The recently developed inter-simple sequence repeats (ISSRs) and
sequence-related amplified polymorphisms (SRAPs) methods are becoming popular
approaches for the characterization of populations of numerous organisms, including fungi
[13–18]. ISSRs have been demonstrated to be useful for analyzing the genetic diversity of a
wide range of fungal species, including Lentinula edodes, Agaricus, Fusarium poae, and
Blumeria graminis f. sp. tritici [19–22]. The simple, reproducible and high-throughput SRAP
method targets amplification of open reading frames (ORFs) [23–25]. It has been widely used
in research on genetic diversity, genetic linkage mapping and comparative genomic analyses in
plants, including Erianthus arundinaceum, Dactylis glomerata L., Piper spp., Lycium
ruthenicum Murr., Hedychium spp., Pisum sativum L., Brassica and Arabidopsis [26–31]. SRAP
markers have also been used to analyze the genetic diversity of fungi, such as Coprinus comatus,
Polyporus umbellatus, Sclerotinia sclerotiorum, Puccinia striiformis f. sp. tritici and Tricholoma
matsutake [25, 32–35]. In a recent study involving genetic mapping of wheat powdery mildew,
SRAP markers were commonly presented in many Pm-gene carrying cultivars [36, 37].
However, at the molecular level, the genetic diversity of powdery mildew populations is not well
We investigated the virulence of B. graminis f. sp. tritici from Sichuan, southwest China,
against 30 isogenic wheat lines. We also characterized the genetic diversity of B. graminis f. sp.
tritici using SRAP and ISSR methods. Here, we report the most updated virulence structure of
wheat powdery mildew and present our discoveries regarding gene flow caused by epidemics
of the pathogen in southwest China. This study also reveals candidate genes that may be useful
in efficient disease resistance breeding programs.
Materials and Methods
Wheat leaves showing symptoms of powdery mildew were collected from 40 counties and
subsequently grouped based on 16 administrative cities (Fig A in S1 File, Table B in S1 File).
Because of the distinct geography in the Renshou region, which is administratively governed
by Meishan City, samples collected from Renshou region were treated as an independent
population. In total, we examined 17 population groups distributed throughout the Western,
Southern, Middle, and Northeastern regions of Sichuan Province (Fig A in S1 File). The entire
sampling area is located between approximate latitudes of 26°03’ to 34°19’ and longitudes of
97°21’ to 108°31’. The sampling site in southwest China was variable with respect to
topography and included plains, basins, and mountainous regions. To avoid bias in sample collection,
diseased leaves were taken from susceptible wheat cultivars in a random pattern, as previously
reported . To avoid contamination, each diseased leaf sample was placed in a clean paper
bag. Samples were transferred to the laboratory for immediate isolation and purification of the
pathogen. The Department of Plant Pathology at Sichuan Agricultural University is an
advisory agent for plant disease management. Therefore, no specific permissions were required for
the plant disease survey, including the collection of diseased samples from these defined
regions. This study does not involve any endangered or protected species. All supplemental
files have been combined into a single file: S1 File
Isolation, purification, and maintenance of the pathogen
Healthy wheat seedlings were prepared for the isolation, purification, and maintenance of
pathogenic isolates. Seeds of a susceptible wheat cultivar (Chuanyu 20) were placed in 75%
alcohol for 3 min, washed 3 times with sterile water, and then placed on filter papers in a petri
dish. The seed-containing petri dish was incubated in a growth chamber for 1–2 days until
germination. Germinated seeds were transferred into soil-containing bottles (2.5 cm × 20 cm)
with 5–7 seeds/bottle. The seeded bottle was sealed with Parafilm to avoid contamination and
incubated in a growth chamber with controlled cycles of 14 h of continuous light at 18°C
followed by 10 h of darkness at 16°C.
A purified isolate was obtained from each sample using the previously reported single spore
purification method [39, 40]. Briefly, a piece of a freshly detached Chuanyu 20 leaf segment
was placed on a piece of filter paper in a petri dish containing 50 μg/ml benzimidazole. Using a
swab, we transferred a single pustule from a diseased sample onto the surface of a detached
piece of fresh leaf segment. The leaf segment was incubated in a growth chamber with the light
and temperature conditions described above. This procedure was repeated every 10 days until
a single-colony isolate was obtained after three to four cycles. A purified culture was
maintained, and fresh inoculum was produced on leaves from healthy Chuanyu 20 plants grown in
bottles containing soil under the conditions described above.
Number of virulent isolates
Frequency of virulence (%)
Virulence was examined in 30 isogenic lines harboring known disease resistance genes
(Table 1). For each purified isolate, host plant responses were evaluated based on the
gene-forgene hypothesis [6, 40]. Seeds from the tested cultivars were maintained in a growth chamber
under the conditions described above. Fresh leaf segments (3 cm) were obtained from the
central regions of 10-day-old seedling leaves. Two susceptible cultivars, Chancellor and Funo,
were used for control measurements as previously described [41, 42]. All differential isogenic
lines and susceptible controls were inoculated with conidia isolated from a single spore and
placed on a piece of filter paper in a petri dish containing 50 μg/ml benzimidazole. After
inoculation, the petri dishes were maintained in a growth chamber as described above. A set of
differentials and susceptible control were inoculated in a single petri dish with each isolate, and a
minimum of three replications were performed. The leaf segments were scored 12 days after
inoculation using a previously reported system  with modifications (Table A in S1 File).
Using our more stringent evaluation standard, isolates on plant leaves showing immune
responses (rated as 0) and resistance responses (rated as I) were considered to be avirulent,
whereas isolates showing increased levels of mycelium and conidiospore production (rated as
II, III and IV) were considered to be virulent. In addition, the frequency of occurrence of the
corresponding genes for virulence in B. graminis f. sp. tritici was also calculated. The avirulent
and virulent types observed were transformed into a binary coding matrix for computational
analysis. Dendrograms were constructed by performing an unweighted pair-group analysis
with arithmetic averages (UPGMA) using NTSYS-pc version 2.10 .
DNA isolation and PCR
Genomic DNA was extracted with a fungal DNA kit (Omega Bio-Tek, Norcross, GA, USA)
following the manufacturer’s protocol. A total of 20 primers that produced clearly distinguishable
and reproducible fragments were selected and used in this study for ISSR and SRAP assays
(Table 2). For the ISSR assay, we prepared a PCR containing 10 μl 2× Power Tap PCR Master
Mix, 8 μl ddH2O, 1 μl primer and 1 μl template DNA. The amplification protocol for the ISSR
assay was as follows: 94°C for 5 min (pre-denaturation), followed by 40 cycles of 94°C for 30
sec, 45–58°C for 45 sec and 72°C for 2 min, with a final extension at 72°C for 7 min. The
amplification products were separated on a 1.5% agarose gel.
B = C, G, or T; D = A, G, or T; H = A, C, or T; V = A, C, or G.
For the SRAP assay, the PCR mix consisted of 10 μl 2× Power Tap PCR Master Mix, 7 μl
ddH2O, 1 μl each of the F and R primers, and 1 μl template. The SRAP amplification protocol
was as follows: 94°C for 5 min (pre-denaturation); 5 cycles of 94°C for 1 min, 35°C for 1 min,
and 72°C for 1.5 min; 35 cycles of 94°C for 1 min, 50°C for 1 min, and 72°C for 1.5 min; and a
final extension of 72°C for 7 min. The amplification products were separated on a 2% agarose
ISSR and SRAP data for each DNA sample were coded as 1 (presence) or 0 (absence) to
produce a binary matrix, and dendrograms were constructed by UPGMA using NTSYS-pc version
2.10 . Genetic diversity analysis was performed using PopGene 32 software . The
parameters calculated for genetic diversity included the total number of bands (TNB), the
number of polymorphic bands (NPB), the percentage of polymorphic bands (PPB), the observed
number of alleles (Na), the effective number of alleles (Ne), Shannon’s information index (I),
Nei’s (1973) gene diversity (H), and gene flow (Nm). The polymorphic information content
(PIC) and the resolving power (Rp) of the primers were evaluated using previously described
formulas [46, 47]. Components of genetic variance within and among populations were
estimated by analysis of molecular variance (AMOVA) using Arlequin3.0 . Matrix data
derived from the ISSR and SRAP methods were compared using the Mantel test with GenAlEx
6.501 at 999 permutations (Mantel, 1967) [49–51].
Virulence frequency. A total of 109 purified pathogenic isolates of B. graminis f. sp. tritici
were obtained from 327 samples of infected leaves collected from 40 counties representing 17
populations in Sichuan, China (Fig A in S1 File, Table B in S1 File). Of the 28 previously
identified resistance genes, Pm21 (harbored by Yangmai5/Sub.6v) displayed a unique immune
response to all 109 isolates tested (Table 1). It was the only gene able to maintain a resistance
response during challenge with all pathogenic isolates in Sichuan. The virulence frequency was
less than 20% in four isogenes: Pm13, Pm5b, Pm2+6, and PmXBD (harbored by cultivars R4A,
Aquila, Maris Huntsman, and Xiaobaidong) (Table 1). The virulence frequencies were greater
than 60% for previously recognized resistance genes, including Pm1, Pm2, Pm3a, Pm3b, Pm3d,
Pm3e, Pm3f, Pm4a, Pm4b, Pm5, Pm6, Pm7, Pm9, and Pm19 (Table 1). The remaining genes
displayed intermediate levels of resistance or susceptibility with virulence frequencies between
20% and 60%.
Many isolates from the Middle region displayed high levels of virulence (Fig 1A); however,
some isolates from this region displayed low virulence. Most of the resistance genes appeared
to be distributed in the Meishan population (MS) (Fig 1B). The number of genes for virulence
were varied significantly among regional populations, ranging from 4 to 26 genes (Table 3).
The Southern region had the highest number of genes, with a frequency of up to 80% in Zigong
(ZG) and Luzhou (LZ) (Table 3, Fig 1C). In this high-virulence region, the frequency of
virulence in the Yibin population (YB) was 43%, which was significantly lower than that in other
populations in the region. Overall, for regional comparison, the Western region showed the
lowest distribution of virulence, as represented by Xichang (XC) and Ya’an (YA). Another
notable population with a lower gene frequency was identified in Meishan (MS) in the Middle
region. Although populations in the Middle region showed high virulence frequencies, the
number of resistance genes was also relatively higher, especially in the Meishan region,
compared with that observed in other regions.
Fig 1. Virulence distribution of Blumeria graminis f. sp. tritici in Sichuan, China.
Cluster analysis of virulence. Based on pathogenicity, cluster analysis was performed to
sort the 109 purified isolates from throughout Sichuan province into two distinct groups. At a
similarity coefficient cutoff of 0.63, 92 isolates fell into a large cluster with a high frequency of
virulence (63.19%). This group was designated the high-virulence (HV) group (Fig 2). The
Number of genes a
a Number of detected genes for virulence of Blumeria graminis f. sp. tritici.
low-virulence (LV) group consisted of 17 isolates and showed an average virulence frequency
of 38.63%. The LV group included nine isolates from the Middle region, four isolates from the
Western region, three isolates from the Northeastern region, and one isolate from the Southern
region (Fig 2, Table C in S1 File). In this group, there was a close relationship between isolates
B4, 51, 75, 87, and 119, which displayed a significantly lower frequency of virulence than other
isolates in the LV group. The lowest virulence frequency was 0.13% for isolate B51 from
Renshou in the Middle region. The Middle region also appeared to have more sources of
resistance. Regionally, isolates from the Meishan population showed relatively lower virulence
frequencies compared with isolates from other populations (Fig 1, Table C in S1 File).
ISSR amplification. DNA from each of 105 isolates was amplified using the ISSR method.
A total of 186 clearly distinguishable amplification fragments ranging from 100 to 2,000 bp
were obtained using 10 ISSR primers (Fig 3A). Among these, 135 fragments were polymorphic,
with an average of more than 13 polymorphic bands for each primer. ISSR primers 835 and
808 were the most efficient, producing 16 and 15 polymorphic bands, respectively. The lowest
number of bands was obtained from primer 890, which generated 11 polymorphic bands.
DNA fragments derived from this primer also displayed the highest PIC score of 0.41
(Table 4). The rates of informative polymorphic bands from ISSR amplifications varied from
65% to 80%, with PIC scores ranging from 0.32 to 0.41.
SRAP amplification. A total of 154 bands ranging from 100 to 2,000 bp were obtained
from 10 SRAP primers (Fig 3B). Among these, 107 bands were polymorphic, with an average
of 10.7 bands per primer. Primers Me6/Em8 and Me4/Em8 generated the highest number of
polymorphic bands, and primer set Me5/Em5 produced the lowest number of informative
bands. The polymorphism scores for primer sets Me5/Em5, Me6/Em8 and Me1/Em1 were
Fig 2. UPGMA dendrogram of Blumeria graminis f. sp. tritici strains based on the virulence data.
Fig 3. Representative molecular marker profile. (A): ISSR profiles in the tested 21 strains of Blumeria graminis f. sp. tritici with primer 807. (B): SRAP
profiles in the tested 21 strains of Blumeria graminis f. sp. tritici with primer Me2/Em8.
41.7%, 81.3% and 81.3%, respectively (Table 4). These primers had an average PIC of 0.314,
ranging from 0.236 to 0.349. The primer pairs Me2/Zm8, Me6/Zm8, Me8Zm8, Me8Zm4, Me1/
Zm1, and Me8/Zm6 all had PIC values greater than 0.30, while the primer pairs Me6/Em8,
Me1/Em1, and Me8/Em4 generated the most polymorphic information and had the highest
PIC scores, ranging from 0.33 to 0.36.
Cluster analysis. Cluster analysis based on Nei’s unbiased genetic distances was
performed using ISSR profiling for 105 isolates collected from all regions in Sichuan. Three groups
(ISSR1, ISSR2 and ISSR3) were established from the 105 isolates. ISSR1 contained 94 isolates
that can be divided into two subgroups: ISSR1-1 and ISSR1-2 (Fig B in S1 File). However,
groupings based on ISSR data reflected neither virulence/pathogenicity nor the geographical
origin of the isolates. We conducted additional analyses based on the regional origin of the
isolates and obtained four more informative trees for each region (Fig 4A–4D). From the 42
isolates from the Middle region, two distinct groups were formed: the ISSR-M1 group contained
36 isolates, and the ISSR-M2 group contained 6 isolates (Fig 4A). The 6 isolates in the ISSR-M2
group were from Meishan, Renshou, and Chengdu, whereas the ISSR-M1 group included
isolates from all locations in the Middle region. Of the 29 isolates from the Northeastern region,
PIC, polymorphic information content; RP, resolving power.
Percentage of polymorphic bands (%)
one unique isolate from Guanyuan, B88, was clearly separated and represented a single isolate
group, ISSR-NE2. The other 28 isolates from this region essentially clustered into one group:
ISSR-NE1 (Fig 4B). Similarly, in the Southern region, 12 isolates were clustered into two groups
(ISSR-S1 and ISSR-S2), whereas the B175 isolate from Zigong formed a unique group
(ISSR-S2) (Fig 4C). Isolates from the Western region were more similar, forming only two
subgroups (ISSR-W1 and ISSR-W2) (Fig 4D). Thus, isolates from the Western region displayed
lower diversity than isolates from all other regions. The regional variations in ISSR alleles in
isolates from the Northeastern region were distinct from those of isolates from all other regions
For the data obtained from SRAP profiling, we performed the same series of analyses used
on the ISSR data. The UPGMA dendrogram derived from SRAP profiling of 105 isolates
revealed three groups: SRAP1, SRAP2 and SRAP3. The SRAP1 group was further separated
into four subgroups (Fig C in S1 File). There were no overlaps or close relationships between
the SRAP and ISSR groupings. There were also no close relationships to virulence or to the
geographical origin of the isolates. Regional analysis identified two subgroups in the Middle region
(SRAP-M1 and SRAP-M2), two subgroups in the Northeastern region (SRAP-NE-1 and
SRAP-NE2), two subgroups in the Southern region (SRAP-S1 and SRAP-S2), and two
subgroups in the Western region (SRAP-W1 and SRAP-W2) (Fig 5A–5D). Unlike the different
outcomes derived from SRAP and ISSR analyses of the entire group of isolates, groupings of
isolates at the regional level showed similar results with both methods. In general, clusters from
each region contained the same member of isolates. However, variations in alleles between
Fig 4. UPGMA dendrogram of Blumeria graminis f. sp. tritici strains based on the ISSR data showing
relationships among strains isolated from the Middle region (A), Northeastern region (B), Southern
region (C), Western region (D); Regional relationships (E) are also shown.
Fig 5. UPGMA dendrogram of Blumeria graminis f. sp. tritici strains based on the SRAP data showing relationships among strains isolated from
the Middle region (A), Northeastern region (B), Southern region (C), Western region (D); Regional relationships (E) are also shown.
SRAP and ISSR were clearly observed among the isolates. For example, isolates B86 and B98 in
group SRAP-S1 from the Southern region were identical in the SRAP analysis but different in
the ISSR analysis (Figs 4C and 5C). In other regions, similar patterns were observed in the
analysis of isolates within the same group. There was a high level of variation in the SRAP and ISSR
alleles for all regions except the Western region. However, the pathogenicity or virulence of
isolates within groupings did not appear to be closely related to their group assignments. In the
regional comparisons, the ISSR and SRAP analyses of allele polymorphisms revealed similar
relationships among regional populations with little variation. Both analyses indicate that
Northeastern populations are distantly related to populations from the other regions (Figs 4E
We also pooled the ISSR and SRAP data of all 105 isolates and performed a combined
analysis. The resulting UPGMA dendrogram had low resolution power (Fig D in S1 File). Isolate
classifications in the combined analysis showed no close relationship to either the ISSR or
SRAP analysis. There was no correlation between the ISSR and SRAP matrices, as indicated by
the low correlation coefficient (r = 0.438) generated by the Mantel test (Mantel 1967).
Genetic diversity analysis. There were high levels of genetic diversity in the 17
populations in Sichuan based on both ISSR and SRAP analyses. On a regional basis, the ISSR method
suggested that there were higher levels of variation in the Middle region compared with the
other regions (Table 5). On the other hand, the SRAP method suggested that there was more
variation for populations in the Western region; however, the Middle region had the highest
observed number of alleles (Na) based on SRAP analysis. Both ISSR and SRAP analysis showed
that populations in the Southern region had the least variation as measured by the observed
number of alleles (Na), the effective number of alleles (Ne), Nei’s genetic diversity (H), and
Shannon’s information index (I) (Table 5).
The gene flow among the four regions was estimated to be 7.984 by ISSR and 8.126 by
SRAP analysis (Table 5). Our data suggest that there were high levels of gene migration among
these regions. Considering gene flow within each region, the Southern region showed the
lowest level of gene flow, estimated at 0.448 and 0.401 using ISSR and SRAP alleles, respectively.
Compared with the Southern region, the Northeastern region had a higher rate of gene flow,
estimated at 1.526 and 1.686 using ISSR and SRAP alleles, respectively. The rate of gene flow
for Middle populations was estimated at 2.148 by ISSR and at 1.851 by SRAP. The Western
region had the highest level of gene flow at 2.88 and 3.991, as determined by ISSR and SRAP,
respectively. These results suggest that pathogenic populations migrated within the Western
region. The results of AMOVA showed significantly high levels of variation within the 17
Na, observed number of alleles; Ne, effective number of alleles [Kimura and Crow (1964)]; H, Nei’s (1973) gene diversity; I, Shannon’s information index
[Lewontin (1972)]; Nm, gene flow. Mean values of Na, Ne, H, I are presented in this table.
Source of variation
populations. In contrast, variation among the four regions was less significant. The variation
among populations within a region was slightly higher than the variation among regions
Using 109 purified pathogenic isolates of B. graminis f. sp. tritici representing 17 populations
in Sichuan, China, we identified two distinct virulence groups: HV and LV. In addition, we
revealed an updated virulence structure for populations in the Middle, Northeastern, Southern,
and Western regions of Sichuan. By applying ISSR and SRAP molecular markers, we also
characterized the genetic diversity of the pathogen and detected high levels of genetic variation
among populations in Sichuan. Our results suggest that ISSR and SRAP alleles can be used
independently to study closely related populations, although these alleles do not reveal
significant associations with the virulence or pathogenicity of the pathogen.
Traditionally, a visible mycelium or conidiospore has been considered to be a symptom of
an avirulent response. In this study, we used a more stringent standard for disease evaluation,
and we rated such symptoms as a virulent response. We believe that the evaluation standards
used in this study provide a more realistic view of the host response that will support the
development of more efficient disease resistance breeding programs. Using this standard, we found
that the resistance gene Pm21 had an immune response against all pathogenic isolates. Low
virulence frequencies were detected for the genes Pm13, Pm5b, Pm2+6, and PmXBD. However,
many previously identified resistance genes lose their function against pathogens with higher
virulence frequencies, including Pm1, Pm2, Pm3a, Pm3b, Pm3d, Pm3e, Pm3f, Pm4a, Pm4b,
Pm5, Pm6, Pm7, Pm9 and Pm19. Such pathogens accounted for more than 80% of the
pathogenic isolates investigated. These results highlight the potential for epidemics under favorable
conditions [1, 52].
B. graminis f. sp. tritici is a highly variable wheat pathogen, and its virulence frequencies are
influenced by resistance genes expressed in cultivars grown in the field [40, 53, 54]. High
virulence frequencies were observed for Pm5, Pm3a, Pm3b and Pm3d, indicating the high
prevalence of these genes in the host cultivars examined. Conversely, resistance genes with low
virulence frequencies, such as Pm13, Pm5b, and Pm2+6, were either rarely present or
completely absent among the cultivars investigated. Consistent planting of a single cultivar
over time leads to the loss of resistance in that cultivar, which results in rapid and frequent
breakdown of disease resistance, making disease management challenging .
High virulence frequencies were observed for many genes in this study, confirming that
these populations had successfully adapted to the host resistance genes. Isolates in the Middle
region had high levels of virulence, and populations in the Southern region contained the
highest numbers of genes for virulence, with frequencies of up to 80%. Due to the loss of
disease resistance, the corresponding isogenic cultivars should no longer be used for large-scale
planting or disease resistance breeding programs in these regions. On the other hand, Pm13,
Pm5b, Pm2+6, and PmXBD retained a higher level of resistance to powdery mildew as
indicated by lower virulence frequencies. Thus, these resistance genes are strong candidates for
wheat breeding programs. Pm21, a commonly introduced resistance gene in China ,
triggered a unique immune response to all pathogenic isolates in Sichuan. We also demonstrated
that virulence responses vary by geographic location. For example, populations in the Southern
region generally had high virulence frequencies, whereas populations in Yibin displayed the
lowest virulence frequencies in this region. Regardless of geographic differences, we believe
that the resistance gene Pm21 remains the top candidate for use in disease resistance breeding
programs. Because high levels of virulence were observed in the Middle and Southern
populations, we recommend the introduction of a new source of resistance in these regions. In
addition, a close monitoring of any dynamic changes in the virulence structure is necessary.
Polymorphism analyses derived from ISSR and SRAP profiles revealed that 105 isolates of
B. graminis f. sp. tritici from 17 populations formed three groups. A reasonable level of
polymorphic information was observed, ranging from 65% to 80% for ISSRs and 42% to 81% for
SRAPs. These levels are similar to the levels found in previous reports [57–61]. No close
relationships were detected by ISSR or SRAP analyses of the entire population. Because ISSR
profiling detects random inter-simple sequence repeats in the genome and SRAP profiling reflects
sequence variation within gene coding regions, there is no overlap between the principles of
the two methods. Attempts to combine the two methods to identify taxonomic entities have
produced inconclusive results [60, 62]. Similarly, our attempt to combine the two methods did
not improve the resolution. The results of this study suggest that ISSR and SRAP methods can
be used independently, but not in combination, to characterize closely related populations as
In contrast to the inconsistent grouping of the total isolates by ISSR and SRAP alleles,
cluster analysis by either technique generates similar isolate classifications for populations that are
closely related at the regional level. The isolates belonging to groups derived from ISSR and
SRAP alleles were identical in the Middle and Southern regions. Groupings of isolates in the
Northeastern and Western regions were also very similar. However, the relationships among
isolates within the group were different in terms of allele variations between SRAPs and ISSRs
with different principles. Groupings by these methods did not appear to have any relationship
with the virulence of the isolates, which is consistent with previous observations [54, 63]. It is
unlikely that these molecular markers are involved in gene functions related to virulence or
pathogenicity. Notably, close relationships were identified among isolates in the SRAP-M2 and
ISSR-M2 groups from Chengdu, Meishan, and Renshou using both methods (Figs 4A and 5A).
Although there were allele variations, the close relationship between isolates from the same
geographic location was clear using both methods. This suggests that ISSR and SRAP methods
may be more efficient for characterizing small or closely related populations than for distantly
related populations. AMOVA revealed significantly higher levels of variation within
populations than among populations within regions, indicating a higher level of genetic diversity but
a lower level of genetic divergence in Sichuan. These data also suggest that high levels of genetic
overlap are the result of extensive gene flow. Gene flow and differentiation are important
factors in evaluating the genetic structure of a population . The estimated gene flow among
the four regions was moderate, with Nm = 7.984 and 8.126 by ISSR and SRAP analysis,
respectively. This suggests that gene migration and long-distance pathogen transference occurred
among these four regions. A high level of gene flow was observed in the Western region
between Xichang (altitude > 1500 m) and Ya’an (altitude ~ 595–775 m), representing
longdistance gene migration over more than 240 km. Wheat powdery mildew was reportedly
transferred from high to low altitude areas by wind , and long-distance disease transference has
been previously observed [66–68]. In this study, a greater number of genes for virulence were
detected in the Southern region compared to the other regions. However, the rate of gene flow
within the Southern region was low, indicating persistent local evolution within this region.
In Sichuan, wheat is a major crop and is planted in large areas. The uniquely diverse
geography and climate in southwestern China yield conditions that are favorable for wheat powdery
mildew growth, transference, and the resultant epidemics. Our study highlights the potential
threat of this disease in major wheat-producing regions of China. Understanding the genetic
diversity of the pathogen is essential for the development of efficient disease control programs.
The novel candidate resistance genes and the data regarding the virulence structure and
population diversity of this pathogen that were presented in this study will support more focused
efforts in the management of wheat powdery mildew.
S1 File. Standards for classifying the virulence of wheat powdery mildew in wheat seedling
stages (Table A). Characteristics of the isolates used in this study (Table B). The frequency of
genes for virulence of 17 powdery mildew isolates in the low-virulence group (Table C).
Locations at which wheat leaves infected with powdery mildew were collected (Fig A). A UPGMA
dendrogram of Blumeria graminis f. sp. tritici strains based on ISSR data (Fig B). A UPGMA
dendrogram of Blumeria graminis f. sp. tritici strains based on SRAP data (Fig C). A UPGMA
dendrogram of Blumeria graminis f. sp. tritici strains based on combined data from ISSR and
SRAP markers (Fig D).
We are grateful to all members of our lab at Sichuan Agricultural University and the Institute
of Plant Protection, Chinese Academy of Agricultural Science, for providing the cultivars
harboring the different resistance genes. We are also grateful to all of the other Plant Protection
Stations for supporting our research.
Conceived and designed the experiments: NL GSG MZ HBC JZY PGL CPY. Performed the
experiments: NL XW YZ XBQ. Analyzed the data: NL ZLL GSG. Contributed
reagents/materials/analysis tools: NL GSG MZ YZ XBQ. Wrote the paper: NL ZLL GSG.
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