Browse Subject Areas

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Identification and evaluation of resistance to powdery mildew and yellow rust in a wheat mapping population

  • Lijun Yang ,

    Contributed equally to this work with: Lijun Yang, Xuejiang Zhang

    Affiliations College of Life Sciences, Wuhan University, Wuhan, China, Institute for Plant Protection and Soil Science, Hubei Academy of Agricultural Sciences (HAAS), Key laboratory of Integrated Pest Management on Crop in Central China, Ministry of Agriculture, Wuhan, China

  • Xuejiang Zhang ,

    Contributed equally to this work with: Lijun Yang, Xuejiang Zhang

    Affiliation Institute for Plant Protection and Soil Science, Hubei Academy of Agricultural Sciences (HAAS), Key laboratory of Integrated Pest Management on Crop in Central China, Ministry of Agriculture, Wuhan, China

  • Xu Zhang,

    Affiliation Institute of Biotechnology, Jiangsu Academy of Agricultural Sciences (JAAS), Nanjing, China

  • Jirui Wang,

    Affiliation Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu, Sichuan, China

  • Mingcheng Luo,

    Affiliation Department of Plant Sciences, University of California Davis, Davis, CA, United States of America

  • Mujun Yang,

    Affiliation Food Crops Research Institute, Yunnan Academy of Agricultural Sciences (YAAS), Kunming, China

  • Hua Wang,

    Affiliation Institute for Plant Protection and Soil Science, Hubei Academy of Agricultural Sciences (HAAS), Key laboratory of Integrated Pest Management on Crop in Central China, Ministry of Agriculture, Wuhan, China

  • Libo Xiang,

    Affiliation Institute for Plant Protection and Soil Science, Hubei Academy of Agricultural Sciences (HAAS), Key laboratory of Integrated Pest Management on Crop in Central China, Ministry of Agriculture, Wuhan, China

  • Fansong Zeng,

    Affiliation Institute for Plant Protection and Soil Science, Hubei Academy of Agricultural Sciences (HAAS), Key laboratory of Integrated Pest Management on Crop in Central China, Ministry of Agriculture, Wuhan, China

  • Dazhao Yu , (DY); (GR)

    Affiliation Institute for Plant Protection and Soil Science, Hubei Academy of Agricultural Sciences (HAAS), Key laboratory of Integrated Pest Management on Crop in Central China, Ministry of Agriculture, Wuhan, China

  • Daolin Fu,

    Affiliation State Key Laboratory of Crop Biology, Shandong, Key Laboratory of Crop Biology, Shandong Agricultural University, Tai’an, China

  • Garry M. Rosewarne (DY); (GR)

    Current address: Agriculture Victoria, Department of Economic Development, Jobs, Transport and Resources, Horsham, Vic., Australia

    Affiliation International Maize and Wheat Improvement Centre (CIMMYT) c/o Crop Research Institute, Sichuan Academy of Agricultural Science, Jinjiang, Chengdu, China

Identification and evaluation of resistance to powdery mildew and yellow rust in a wheat mapping population

  • Lijun Yang, 
  • Xuejiang Zhang, 
  • Xu Zhang, 
  • Jirui Wang, 
  • Mingcheng Luo, 
  • Mujun Yang, 
  • Hua Wang, 
  • Libo Xiang, 
  • Fansong Zeng, 
  • Dazhao Yu


Deployment of cultivars with genetic resistance is an effective approach to control the diseases of powdery mildew (PM) and yellow rust (YR). Chinese wheat cultivar XK0106 exhibits high levels of resistance to both diseases, while cultivar E07901 has partial, adult plant resistance (APR). The aim of this study was to map resistance loci derived from the two cultivars and analyze their effects against PM and YR in a range of environments. A doubled haploid population (388 lines) was used to develop a framework map consisting of 117 SSR markers, while a much higher density map using the 90K Illumina iSelect SNP array was produced with a subset of 80 randomly selected lines. Seedling resistance was characterized against a range of PM and YR isolates, while field scores in multiple environments were used to characterize APR. Composite interval mapping (CIM) of seedling PM scores identified two QTLs (QPm.haas-6A and QPm.haas-2A), the former being located at the Pm21 locus. These QTLs were also significant in field scores, as were Qpm.haas-3A and QPm.haas-5A. QYr.haas-1B-1 and QYr.haas-2A were identified in field scores of YR and were located at the Yr24/26 and Yr17 chromosomal regions respectively. A second 1B QTL, QYr.haas-1B-2 was also identified. QPm.haas-2A and QYr.haas-1B-2 are likely to be new QTLs that have not been previously identified. Effects of the QTLs were further investigated in multiple environments through the testing of selected lines predicted to contain various QTL combinations. Significant additive interactions between the PM QTLs highlighted the ability to pyramid these loci to provide higher level of resistance. Interactions between the YR QTLs gave insights into the pathogen populations in the different locations as well as showing genetic interactions between these loci.


Powdery mildew (PM) and yellow rust (YR), caused by Blumeria graminis f. sp. tritici (Bgt) and Puccinia striiformis f. sp. tritici (Pst) respectively, are the most devastating diseases of wheat (Triticum aestivum L.) in cool climate regions [1,2]. Approximately 6 million ha of wheat in China is grown in areas prone to PM or YR epidemics. Major epidemics occurred in these regions in 1990 with grain yield losses due to PM epidemics estimated at 1.4 million tonnes [3] and to YR at 2.65 million tonnes [2,4]. Growing resistant cultivars is an effective, economical and environmentally safe approach to control these diseases [5].

Plant disease resistance can be classified as either qualitative or quantitative [6]. Qualitative resistance is generally conferred by single genes with large effects against the pathogen and can be observed in both seedling and adult plant stages. To date, 50 loci containing 78 resistant genes/alleles to PM [7,8] and 74 genes (Yr1Yr74) to YR [9,10] have been identified in bread wheat and its relatives. This type of resistance has a strong tendency to be overcome by new races, particularly when a single gene is deployed over large areas. However while the gene remains effective, it strongly affects the presence and frequency of specific pathotypes in the field [1113]. The majority of this type of resistance loci have been overcome by the pathogen with only a few, including Pm2, Pm4, Pm21 and Pm30, still effective against prevailing Bgt isolates [13,14]. In YR, only Yr5, Yr10 and Yr15 are still effective against the prevalent Chinese Pst races of Pst-CRY32, Pst-CRY33 and Pst-V26 [15].

In contrast, quantitative resistance is mediated by multiple genes or quantitative trait loci (QTLs) [6] and is most commonly observed in adult plants grown under field epidemic conditions. This type of locus often show partial but additive effect against the majority of isolates, and is considered to be broad-spectrum and durable [6], making it highly valuable to breeding programs. Although individual adult plant resistance (APR) genes or QTLs often confer partial and inadequate resistance, combinations of such genes can result in “near-immunity” [16,17]. So far, 119 resistance QTLs for PM [18] and more than 140 QTLs for YR [19] have been identified, with nearly every chromosome harboring at least one resistance locus.

Wheat cultivars containing combinations of effective resistance genes are likely to provide long-lasting control of PM and YR diseases. Cultivar XK0106 showed high level resistance to PM [20] and YR [21] in both seedling and adult stages, while E07901 exhibited APR to both PM and YR [21]. The two cultivars are promising breeding sources with favorable agronomic traits, but little is known about the genetic basis of their resistance to both diseases. The objectives of this study were to 1) map QTLs responsible for resistance to PM and YR in a population derived from E07901 and XK0106 with SSR and SNP marker genetic linkage maps and 2) assess effectiveness of the detected QTLs alone or in combination in different environments.

Materials and methods

Plant materials and pathogen isolates

A total of 388 DH lines were developed from a cross between wheat cultivar XK0106 and E07901. The population was generated through the maize pollination technique [22] in Yunnan Academy of Agricultural Sciences, Kunming, China. A subpopulation of 91 DH lines were randomly selected from the 388 lines. Further sub-populations of 24 lines for PM and 21 for YR were selected based on their QTL complements and used for the evaluation of QTL efficacy against PM and YR separately in four different environments. Chancellor and Mingxian 169 were used as susceptible checks in PM and YR field trials respectively. Thirty lines with known Pm (S1 Table) and four near-isogenic lines containing key Yr genes (S2 Table) were used in seedling tests.

Isolate Bgt6-11, being incompatible with XK0106 and compatible with E07901, was used for the PM seedling assays, while five Chinese Pst races including Pst-CYR29, Pst-CYR32, Pst-CYR33, Pst-Su11-4 and Pst-V26 were used for the YR seedling assays. The first four of these races have been predominant in China since the 1980s [4], and the race Pst-V26 was first isolated from Chuanmai42 in 2008 and is virulent to Yr24/26 [23]. Sixteen differential Bgt isolates were listed in S1 Table.

Seedling assays for PM and YR

Seedling resistance assays for PM were evaluated using a detached leaf segment method. Seeds of XK0106, E07901, F1, Chancellor and the DH lines were germinated and planted in square pots of 12×12×12 cm and grown to the two-leaf stage (10 days after planting). Leaf segments, 3 cm in length, were cut from the middle part of the primary leaf and placed on 0.5% water agar (w/v) supplemented with 50 mg L-1 Benzimidazole in clear plastic boxes with the abaxial epidermis facing upwards. Three independent replicates were used for each DH line. Inoculation was performed by blowing the spores into a plastic tower at a density of 4×103 conidia cm-2. The leaf segments were then incubated in a growth cabinet with 80% relative humidity and a 12 h light 12 h dark photoperiod at 18±1°C. Infection type (IT) was scored on a 0–4 scale [24] at 12 days post inoculation (dpi), when the susceptible control Chancellor showed fully developed disease symptoms (IT 4). All lines were classed into two groups according to IT with resistant lines scoring between zero and two, and susceptible lines scoring three or four. XK0106, E07901 and a set of lines with known Pm gene to 16 differential Bgt isolates were also evaluated using the above method (S1 Table).

Seedling resistance assays for YR were evaluated under controlled greenhouse conditions. Thirty seeds of parents, Mingxian169 and single gene lines were sown separately in square pots of 12×12×12 cm. Seedlings at the two-leaf stage (14 days after planting) were inoculated with urediniospores of the five respective Pst races. The inoculated plants were incubated at 10 ± 1°C in a dew chamber in the dark for 24 h, and then transferred to a greenhouse at 17 ± 2°C. IT was scored 20 days after inoculation using a 0–9 scale described by Line and Qayoum [25]. Plants with an IT of 0 to 3 were considered resistant, 4 to 6 considered intermediate and 7 to 9 susceptible.

Adult-plant assessment of PM and YR

Field trials for the QTL analysis were conducted at the Hubei Academy of Agricultural Sciences Nanhu farm (30.2856 N, 114.1839 E, 27 m) in Wuhan, Hubei Province. The PM trials were conducted during the wheat cropping seasons of 2011, 2012 and 2013 while the YR trials were conducted in 2010 and 2013. Trials had two replicates and were designed as randomized complete blocks with repeating checks. Each plot consisted of two 1.5 m rows with row spacing of 25 cm. Approximately 100 seeds were sown in each row and the susceptible check, Chancellor or Mingxian169, was planted every 20 plots and around the test lines to ensure ample PM or YR inoculum. The spreader rows of the susceptible checks were exposed to artificial inoculation of PM at stem elongation (Growth stage 30 according to [26]) with mixed conidia from the 16 Bgt isolates that were used in the seedling tests. A similar approach was adopted for YR with mixtures of Pst-CYR32 and Pst-CRY33 urediniospores suspended in the light weight mineral oil Soltrol 170 ( applied to the spreader plots at the tillering stage (Growth stage 25, [26]). Powdery mildew severity (PMS) or yellow rust severity (YRS) was scored at the mid-grain filling stage (Growth stage 75, [26]). The three upper leaves of 15 randomly selected plants were assessed using a 0–9 scale [27] for PMS and a modified Cobb scale [28] for YRS. Disease severity of 15 plants was averaged to obtain the mean PMS or YRS for each plot.

Further field evaluations were conducted on selected lines from the DH populations that contained different combinations of QTLs. PM evaluations were conducted during 2014 at four sites including Nanhu farm in Wuhan, Wolong farm (32.0157 N, 111.5950 E, 69 m) in Xiangyang, Jiangbei farm (30.1407 N, 112.1953 E, 34 m) in Jingzhou and Meijiadun farm (30.4216 N, 115.0434 E, 49 m) in Huanggang, all located in Hubei Province. The YR evaluations were carried out during 2015 at four sites of Nanhu farm, Wuhan and Wolong farm, Xiangyang in Hubei Province, Taoyuan farm (25.0819 N, 102.4520 E, 1903 m), Kunming in Yunnan Province and Gangu farm (34.4508 N, 105.1842 E, 1278 m), Gangu in Gansu Province. Each DH line was planted in a 6.67m2 plot in randomized complete block designs containing three replicates. Detailed assessment was conducted at five sampling points in each plot with the severity of the upper three leaves of 20 plants assessed at each sampling point.

All locations were on field stations owned by the research organizations and external permission was not required to conduct the experiments.

Statistical analysis

Chi-square analysis was performed to predict the minimum number of loci contributing to resistance against PM in XK0106 according to the segregation ratio of IT to isolate Bgt6-11.

Genomic DNA extraction, SSR and SNP genotyping

Young leaves of the parents and DH lines were collected and frozen in liquid nitrogen. Genomic DNA was extracted using the CTAB protocol [29]. Three hundred and ninety-five SSR markers were randomly selected from the 21 Somers consensus chromosome maps [30] to test for polymorphisms between the parents. All of the polymorphic SSR markers were used to analyze genotypes of the 388 DH lines. Two STS markers, CINAU15 [31] and CINAU17 [32], and one EST-SSR marker Xedm129 [33] associated with Pm21 were also evaluated in the population.

The PCR assays for the SSR, EST-SSR and STS markers were conducted in an EDC-810 PCR Thermocycler (Dongsheng, Beijing, China) in a reaction mixture (10 μL) containing 10 mM Tris–HCl, pH 8.3, 50 mM KCl, 1.5 mM MgCl2, 0.2 mM dNTPs, 25 ng of each primer, 50 ng genomic DNA and 0.75U Taq DNA polymerase. Amplifications were performed at 94°C for 5 min, followed by 40 cycles at 94°C for 45 s, 50–60°C (depending on specific primers) for 45 s, and 72°C for 1 min, with a final extension at 72°C for 10 min. The PCR products (2 μL) were mixed with an equal amount of loading buffer and separated on 8% non-denaturing polyacrylamide gels (39 acrylamide: 1 bisacrylamide). Gels were silver stained and photographed.

The genotyping of the sub-population was conducted at the Genome Center of the University of California, Davis. The DNA of 80 DH lines and the parents were extracted and then genotyped through the 90K Illumina iSelect SNP array [34] following the manufacturer’s protocol. SNP allele clustering and genotype calling was performed with Genome Studio software v2010.3. Each of the SNP clusters were manually examined to correct imperfect calling of automated clustering. SNP markers with ambiguous SNP calling between parents and/or with a negative hybridization response in most lines were removed from the data set.

Genetic map construction and QTL analysis

Initial linkage group (LG) construction using the polymorphic SSR markers was completed with Joinmap 4.0 [35]. Linkage analysis and marker ordering were carried out using the regression mapping algorithm with a threshold log-likelihood (LOD) ratio ≥3.0 with the recombination values being converted to genetic distances using the Kosambi mapping function. LGs were assigned to chromosomes by reference to Somers consensus maps [30].

Initially, mean PMS and YRS of all the lines from each year were used to identify QTLs with the SSR LG map. Composite Interval Mapping (CIM) was performed with WinQTL Cartographer version 2.5 [36] using Model 6 with five markers as controls and employing a window size of 10 cM. Significant thresholds for QTL detection were calculated for each dataset using 1,000 permutations with a genome-wide error rate of 0.05. Phenotypic variance (R2) explained by a QTL was obtained by the square of the partial correlation coefficient. Genetic maps were drawn using MapChart2.2 (

The SNP marker-LGs were constructed using MultiPoint software ( Prior to map construction, all non-polymorphic SNP markers between parents as well as those markers with greater than 20% missing data were omitted. Eleven lines with poor quality data were also omitted. Segregation of the remaining SNP markers were subjected to Chi-square tests and severely distorted markers deviating from the expected segregation ratio (1:1) at the probability level p = 0.001 were excluded from further analyses. A maximum threshold rfs value of 0.05 to 0.15 with a 0.01 step was used to initially group the markers into different LGs. Multipoint linkage analysis of loci within each LG was then performed with the maximum likelihood (ML) mapping algorithm and the marker order was further verified through re-sampling for quality control via jack-knifing [37]. Markers with known chromosomal locations on the 90K_consensus_map ([34];;name=Wheat_2014_90KSNP) were used to assign LGs to chromosomes. Redundant SNP linked markers were removed with the remaining SNP markers being outlined in S3 Table. The complete marker dataset is supplied in S4 Table. These were also used to draw chromosome maps using MapChart 2.2 ( This approach was repeated with the combined sets of SSR and SNP markers.

QTLs were mapped on the combined marker LGs using the phenotypic data of 80 remained DH lines of PM and YR. CIM was performed with WinQTL Cartographer version 2.5 [36] with the same parameters as described above. Significant thresholds for QTL detection were calculated for each dataset using 1,000 permutations with a genome-wide error rate of 0.05 (significant) and 0.1 (suggestive). Phenotypic variance (R2) explained by a QTL was obtained by the square of the partial correlation coefficient.


Phenotypic evaluations of PM and YR in seedling tests

XK0106 and F1 lines of the cross between E07901 and XK0106 were highly resistant to Bgt6-11 (IT 0), whereas cultivar E07901 was highly susceptible (IT 4). The seedling assay of the DH population segregated in a 1:1 ratio (Table 1), indicating that a single gene was involved in XK0106 resistance. This was supported by the IT data for this population as it fitted a U-shaped frequency distribution. However there were a number lines with ITs of 1 to 3, suggesting the possibility that other minor QTLs may have been present in altering seedling IT.

Table 1. Genetic analysis of seedling resistance to Bgt6-11 in a doubled haploid (DH) population derived from E07901 × XK0106.

The PM reaction patterns of XK0106 and E07901 to 16 differential Bgt isolates were compared with those of lines possessing known genes. The responses of XK0106 showed an identical pattern to that of Yangmai5/sub.6v (Pm21) with immunity (IT 0) to all the test isolates, while E07901 was susceptible (IT3 or 4) to all isolates except BgtE01 (S1 Table).

The YR seedling ITs showed that XK0106 was resistant (IT 0–3) to four out of five Pst races but susceptible to Pst-V26 (IT 8). This compatible reaction was similar to that observed in the Avocet Yr26 NIL. E07901 was susceptible or moderately susceptible to all of the races tested, indicating that it doesn’t have Yr10, Yr15 or Yr24/26 (S2 Table).

Phenotypic evaluation of PM and YR at the adult-plant stage

The mean severity of PM varied from 7.9% to 34.7% over the three years of testing, with 2012 being the highest (Table 2). XK0106 maintained its immunity in all of these seasons while E07901 ranged between 11.8% and 61.5%. The PMS of the 388 DH lines showed an L-type distribution with approximately half of the lines having a severity of zero while the rest of the lines were continuously distributed (Fig 1A). A number of lines consistently had a higher PMS than that of the susceptible parent E07901 (Table 2).

Fig 1. Frequency distribution of disease severity.

Number of individuals from the E07901 × XK0106 doubled haploid population occurring in classes of disease severity for (A) powdery mildew severity and (B) yellow rust severity.

Table 2. Summary of disease severity scores of 388 DH lines and their parents grown in Wuhan in the years indicated.

Disease scores are the leaf area covered by powdery mildew or yellow rust from two replicates.

XK0106 was immune in both of the environments tested while E07901 had YRS scores of 10.0 and 26.5%. Mean YRS of the 388 lines in the DH population ranged between 6.0 and 17.0% and the severity of single DH lines varied between 0 to 100% in each of the two years (Table 2). The frequency distribution of DHs for YRS was continuous with a pronounced skewness towards resistance (Fig 1B).

Genetic linkage mapping and QTL analysis

Overall, 134 (33.9%) of the 395 SSR markers showed polymorphisms between the parents. This was further reduced to 117 useful markers when run on the entire population and led to the construction of a genetic map with 26 linkage groups. Apart from chromosomes 1A and 1B, all other wheat chromosomes had between one and three LGs. Chromosome 3B had the greatest coverage with ten SSR markers, while chromosomes 3A, 4B and 6D had the least with only 2 markers each. Chromosome 2B had the longest genetic distance (130.5 cM), while chromosome 5A had the shortest distance (3.9 cM) (S3 Table).

The SNP marker set dramatically increased the marker density and chromosome coverage. In all, 11,746 (14.4%) out of 81,587 SNPs showed polymorphisms between parents and 11,330 could be incorporated into the map (including the 117 SSR markers). This resulted in 33 LGs and each was assigned to the different chromosomes of wheat according to 90K_consensus_ map information [34]. Each chromosome contained at least 1 LG and the group D chromosomes had the least representation of markers (225). The genetic map spanned 3,351 cM with an average density of one marker every 2.5 cM. Chromosomes 5B and 4D had the largest (119) and the fewest (14) number of markers, respectively. Chromosome 5A had the longest genetic distance (266.9 cM) and chromosome 4D had the shortest genetic distance (48.7 cM) (S3 Table).

Composite interval mapping was conducted on both the SSR map containing 117 markers from 388 lines as well as the SSR+SNP map containing 11,330 marker from 80 lines. All QTLs identified in the SSR analysis were also identified in the combined marker analysis, although the former analysis always had much higher LOD scores (Table 3).

Table 3. Position and effects of quantitative trait loci (QTL) for seedling resistance to powdery mildew (PM) and adult plant resistance (APR) to PM and yellow rust (YR) in different environments (years).

The most significant QTL detected for PMS was derived from XK0106 and was located on chromosome 6A. It was designated QPm.haas-6A and was identified in the seedling test (LOD 27.8) and in the field in 2011, 2012 and 2013 (respective LODs of 4.1, 26.3 and 5.9)(Table 3, Fig 2). QPm.haas-2A was derived from E07901 and was located on chromosome 2A. It was significant in the seedling test (LOD 7.9) and in the field in 2011 (LOD 6.7), and was a suggestive QTL (LOD 3.0) in 2013. QPm.haas-3A and QPm.haas-5A were significant in the field assays in 2011 and 2012 respectively. The former QTL, located on chromosome 3A, was derived from E07901 while the latter was on 5A and derived from XK0106. QPm.haas-2A, QPm.haas-3A and QPm.haas-5 were not detected in the SSR map.

Fig 2. Linkage groups of wheat chromosomes showing SSR and SNP markers in QTL regions linked to resistance against powdery mildew (PM) and yellow rust (YR) in the DH population of E07901 × XK0106.

Boxed QTLs show regions of significance at P≤0.05 and error bars at P≤0.1. Markers in bold highlight loci the peak marker for the associated QTL. Some related genes/QTLs were also shown in the LG by linked marker position in the consensus maps.

Three QTLs were detected in the YRS analysis, namely QYr.haas-1B-1, QYr.haas-1B-2 and QYr.haas-2A. The first QTL was derived from XK0106 whilst the other two were from E07901. QYr.haas-1B-1 was significant in both 2010 (LOD 10.6) and 2013 (LOD 6.4) while QYr.haas-1B-2 was only significant in 2013 (LOD 5.1) and QYr.haas-2A only in 2010 (LOD 4.3). The QTLs for QYr.haas-1B-1 and QYr.haas-2A were detected in both the SSR and the combined analyses (Table 3, Fig 2).

Resistance evaluation of QTLs to PM and YR

The effects of the different PM QTLs were further tested in four environments in 2014 by selecting three DH lines each that contained various combinations of the different QTLs (Table 4). The four sites had sound epidemics although Wuhan and Xiangyang had heavier disease development. In lines that had only QPm.haas-2A or QPm.haas-3A, PMS was significantly reduced in Huanggang and Jingzhou, but not at the more heavily infected sites. Lines with only QPm.haas-5A had no effect against PMS in any environment. In nearly all environments, the combination of QPm.haas-2A with either QPm.haas3A or QPm.haas-5A significantly reduced disease severity below that of lines only containing QPm.haas-2A. Lines containing the combination of QPm.haas-3A and QPm.haas-5A fared no better than lines with QPm.haas-3A alone. The combination of all three QTLs reduced PMS when compared to lines containing the QPm.haas.2A/QPm.haas-3A combination, but were no better than the QPm.haas.2A/QPm.haas-5A combination.

Table 4. Mean severity of lines containing combinations of the indicated QTLs from the E07901 × XK0106 DH population, highlighting the additive effects of the QTLs to powdery mildew at multiple locations in 2014.

A similar process was completed for YR where three DH lines were selected for each of the QTL combinations and tested for YRS in four environments in 2015. There were no lines that contained the combination of all three QTLs. Lines containing QYr.haas-1B-1 showed immune responses in three environments but had the same score as the null lines in Gangu. QYr.haas-1B-2 had a partial effect in reducing YRS, but this was again ineffective in Gangu while QYr.haas-2A had a partial effect that was significant in all environments. The combination of QYr.haas-1B-1 with either QTL was not significantly different from the scores of QYr.haas-1B-1 in Wuhan, Xiangyang and Kunming. However, QYr.haas-1B-1 and QYr.haas-2A did reduce disease severity by more than QYr.haas-2A alone in Gangu. Finally, QYr.haas-1B-2 and QYr.haas-2A acted additively to reduce disease severity in all environments by more than that observed when these QTLs were present alone (Table 5).

Table 5. Mean severity of lines containing combinations of the indicated QTLs from the E07901 × XK0106 DH population, highlighting the additive effects of the QTLs to yellow rust in multiple locations in 2015.


This study identified resistance loci to PM and YR in a DH population derived from a cross between E07901 and XK0106 and evaluated the effectiveness of these loci in different combinations and environments. One QTL (QPm.haas-6A) for PMS was detected at seedling and adult plant stages in all environments and its seedling reactions and genomic location identified it as Pm21. A further three QTLs were found for PMS, QPm.haas-2A, QPm.haas-3A and QPm.haas-5A. QPm.haas-2A was significant in the seedling test and two field environments and is likely a previously unidentified gene. The YRS study identified three QTLs with QYr.haas-1B-1 having a strong effect in both QTL field environments, while QYr.haas-1B-2 and QYr.haas-2A were only effective in 2013 and 2010 respectively. Seedling pathotype testing and the genomic location also suggest QYr.haas-1B-2 had not previously been identified, although QYr.haas-1B-1 is likely Yr24/26 and QYr.haas-2A is Yr17. A novel strategy was developed to understand how the different QTLs interacted in different environments. Specific lines from the DH population that contained various combinations of QTLs were used as an effective means by which to characterize genotype × environment interactions of these loci in multiple environments.

Comparison of QTLs to known resistance genes

The major seedling resistance of Pm21 was located on chromosome 6A and associated with well characterized markers, in particular, 6V-CINAU15, which is deemed a functional marker for this gene [31]. Indeed this marker, along with the other Pm21 associated markers of 6V-CINAU17 and Xedm129 [32,33], all occurred within the QTL region of QPm.haas-6A. Furthermore, SNP markers also associated with this QTL, RAC875_rep_c69836_475, RAC875_c48891_87 and the peak marker RAC875_c68978_220, have also been placed in this region through consensus maps [34]. This designation is also supported by seedling tests to 16 B. graminis isolates where XK0106 was immune to all isolates and matched the pattern produced by Yangmai5/sub.6v, a line with the Pm21 containing translocation. Pm21 was introduced into common wheat through the translocation T6VS-6AL derived from 6VS of Haynaldia villosa (2n = 2x = 14, VV) [38]. As it gives high levels of resistance to PM, the T6VS 6AL translocation has been widely used in breeding programs since 2002, particularly in powdery mildew prevalent provinces including Sichuan, Guizhou, Gansu and Jiangsu. Cultivars released such as Neimai8, Neimai836, Neimai10, Neimai11 and Mianmai39 have all been widely planted in Sichuan Province and contain Pm21 [31]. XK0106 originated from Sichuan Province and as its resistance has now been confirmed to contain Pm21, it must also be derived from a T6VS-6AL translocation line.

There have been two other introgressions containing PM resistance genes on chromosome 6A, MIRE, introgressed from T. dicoccum [39] and MIG from T. dicoccoides [40]. Map positions clearly differentiate these loci from Pm21 [40]. These 6A introgressions show the value of wild species in contributing useful resistances to the common wheat gene pool.

QPm.haas-2A was flanked by the markers BS00065434_51 and RAC875_c5082_841 with the peak marker being wsnp_JD_c289_450995 (position 164.2 cM Fig 2A). A consensus map of Wang et al.[34] placed this QTL towards the telomere of 2AL. Several QTLs including QPm.inra-2A [41], QPm.vt-2A [42,43], Qpm.ttu-2A [43] and Qpm.crag-2A [44] have been identified on chromosome 2A. Li et al. [18] reviewed all PM QTLs and located QPm.inra-2A on the short arm of 2A. QPm.vt-2A was near the centromere on 2AL and was associated with Xgwm312 [42]. On our map this marker is 90 cM (Position 93.8 cM Fig 2A) from the QTL peak marker. The map positions therefore clearly differentiate QPm.haas-2A from the two aforementioned QTLs. Qpm.ttu-2A and Qpm.crag-2A were located near the telomere of 2AL with the former being tightly linked to Xwmc658 [43]. Again in our map this marker is over 28 cM from the QTL peak (Position 192.5 cM Fig 2A). Mingeot et al. [44] mapped Qpm.crag-2A to the same locus as the seedling resistance gene Pm4b, and described the QTL as a residual effect of the defeated gene. S1 Table shows numerous differences between the seedling reactions of Armada, a Pm4b carrying line, and E07901, the QPm.haas-2A donor. This also indicates that Qpm.haas-2A is different from Qpm.crag-2A (Pm4b) and is therefore likely a new QTL for PM.

The Qpm.haas-3A and Qpm.haas-5A loci had minor effects in 2011 and 2012, respectively. It was difficult to judge the relationship of these QTL with other known QTLs on chromosome 3A and 5A as there was an absence of shared markers between our maps and other reported maps. However these QTLs and their associated markers could be useful to pyramid minor genes for durable resistance.

QYr.haas-1B-1 on chromosome 1B was detected in both 2010 and 2013 and is likely to be Yr24/26 due to its map location and virulence testing. Yr24/26 has been mapped to chromosome 1BL with associated markers Xwe173 and Xbarc181 [23,45,46,47]. The Somers consensus SSR map ([30]; places the peak SSR marker of QYr.haas-1B-1, Xcfd65, at the same position as Xgwm11 and Xgwm18. Furthermore, the resistance patterns of XK0106 (QYr.haas-1B-1 donor) to five Chinese Pst races in seedling tests were similar to that of the Avocet NIL line containing Yr24/26 (S2 Table). These data provide strong evidence of the Yr24/26 supposition.

Excalibur_c43567_282 and Xgwm413 were associated with QYr.haas-1B-2 and both have been located to chromosome 1BS on consensus genetic maps [34]. Apart from Yr24/26, there are several other genes that have been identified on this chromosome including Yr10[43], Yr15[44], YrCH42, YrH52 [48], Yr29/Lr46[49], Yr64andYr65[9]. More recently, Yr24/26 and YrCH42 have been shown to be identical due to their similar genomic position and reaction patterns against 26 Pst isolates [45]. The closest known YR genes to QYr.haas-2B-2 are Yr10 [48] and Yr15 [49] and both of these were clearly differentiated from QYr.haas-1B-2 through seedling pathotype tests. Despite detailed mapping, YrH52 could not be separated from Yr15 and as both are derived from T. dicoccoides, they have yet to be clearly identified as different loci [50,51]. E07901 (QYr.haas-1B-2 donor) was MS to S against five pathogens tested, while the Yr10 NIL had a resistant reaction to CYR29 and Sul1-4 and the Yr15 NIL had a resistant reaction to all pathotypes. Furthermore, these genes are rarely used in current breeding programs in China [15,25] with Yr15 being derived from T. dicoccoides [49,50] and presents with significant linkage drag. QYrco.wpg-1B.1 has also been reported in this region as a QTL that had both race specific seedling reactions and robust APR [52]. The marker Xpsp3000 mapped 2–4.4 cM proximal to the seedling reaction QTL QYrco.wpg-1B.1 and 1.2cM from Yr10 [53], suggesting a very similar location for these loci, although pedigree data suggested that they were different genes. QYr.haas-1B-2 could be differentiated from QYrco.wpg-1B.1 with the marker Xgwm413. This marker was 3.2 cM proximal to QYr.haas-1B-2, yet 44 cM proximal to QYrco.wpg-1B.1 [52]. Furthermore, Xpsp3000 and Xgwm413 are 59 cM apart on the Somers Consensus map [30].

QYr.haas-1B-2 is unlikely to be any of the other gene identified on 1B. YrH52 is from T. dicoccoides and has only been introgressed into T. durum with the gene containing segment suffering from negative crossover interference [50]. Yr29/Lr46 is a single locus that is located towards the telomere of chromosome 1BL [54] while Yr64 and Yr65 have only recently been introduced from T. durum and are yet to be deployed in hexaploid wheat [9]. All of these data suggest that QYr.haas-1B-2 is likely a new QTL for YR.

Another QTL for YR was mapped to the telomeric end of chromosome 2AS (QYr.haas-2A) with the SSR markers Xbarc124 and Xwmc177. Several YR resistance genes or QTLs have been reported on chromosome 2AS including the race-specific gene Yr17 [41], as well as QYr.ufs-2A [55], QYr.uga-2AS [56] and QYr.ucw-2AS [57]. Yr17 was also located towards the teleomere of 2AS, and was associated with Xgwm636 [41]. This marker, along with the two QYr.haas-2A associated markers, are within 7 cM of each other on the Somers consensus map [30]. As QYr.haas-2A could not be differentiated from Yr17 by neither map position nor seedling assays, we made the conservative assumption that QYr.haas-2A was likely to be Yr17, although testing with an avirulent pathotype would be required to confirm this.

Resistance evaluation of QTLs to PM and YR

Durable resistance to rust diseases under severe epidemics has been achieved through the combining of three minor loci to control leaf rust [58] and up to five to control yellow rust [59]. Although QPm.haas-6A (Pm21) is still an effective major gene, given its wide-spread deployment over a large area in numerous Chinese cultivars, there is a strong possibility that it will breakdown in the coming years. This study investigates the role the minor QTLs could play in the absence of Pm21. The additive effect of various combinations of these minor QTLs were investigated in several environments by selecting three lines that contained each of the various QTL combinations. This novel approach allowed detailed investigations of the major QTLs without having to grow out the entire mapping population. This has the advantage of being able to grow more replicates of each line, increasing the plot size and being able to take more detailed notes on each plot. These factors result in more accurate scores for each line tested. There is a disadvantage in not being able to identify new QTLs that may be environment specific, however such QTLs are often relatively minor in effect.

Disease pressure had a significant impact upon whether single loci could reduce disease severity. Huanggang and Jingzhou had the lowest disease severity of powdery mildew as evidenced by scores of lines with the null QTL combination. In these low severity sites, both QPm.haas-2A and QPm.haas-3A significantly reduced disease severity, yet had no effect at the high disease sites of Wuhan and Xiangyang. QPm.haas-5A had little effect when present by itself (Table 4). It is doubtful however that any of these loci in isolation would provide much protection of yield even under moderate disease pressures.

Combinations of QTLs identified interesting additive effects. QPm.haas-2A and QPm.haas-5A combined well and reduced disease severity in all environments despite the lack of effect of QPm.haas-5A alone. This is indicative of an epistatic interaction between these two loci. Contrastingly, the QPm.haas-3A/QPm.haas-5A combination was no better than the 3A QTL alone. Such as situation has been previously observed in another YR QTL study where both QTLs on chromosomes 3D and 5D gave moderate protection in isolation and that was no different than the protection provided when they were combined. However these QTLs were clearly additive with all other loci [17]. Such an interaction suggests they may share part of a similar pathway in their respective defense responses and the two PM QTLs identified herein follow a similar pattern.

Lines with all three PM QTLs fared little better than lines with the QPm.haas-2A/QPm.haas-5A combination, again highlighting the non-additive effect of QPm.haas-3A. This is important information for breeders who wish to pursue additive resistances to achieve durability. The two minor genes with additive effects that have been combined in this study reduced disease severity by two thirds in the stronger epidemic environments and further reduced it to negligible levels in less severe sites. It is hoped that, as is the case for the rust diseases, by recombining two to three more loci, near-immunity may be reached. Indeed such loci are readily available. A number of pleiotropic, durable APR loci that give intermediate levels of resistance to leaf rust, yellow rust and stem rust have been identified, and recent work has shown they also have effects against PM. These loci have been termed Lr34/Yr18/Sr57/Pm38 [60], Lr46/Yr29/Sr58/Pm39 [61] and Lr67/Yr46/Sr55/Pm46 [62]. Sound molecular markers are available and it would be a straight-forward breeding exercise to recombine these with the QTLs described herein, in an attempt to generate near-immune lines.

A similar approach of selecting lines with various QTLs was adopted with YR. This gave insights not only into additive effects of different loci, but also of pathogen composition in the various environments. This was most clearly demonstrated with the prevalence of Pst-V26 in Gangu where QYr.haas-1B-1 containing lines scored high, but were immune at other sites. Virulence to Yr24/26 was first detected in China on wheat cultivar Chuanmai42 in the Sichuan Basin in 2008 [63]. Virulence was subsequently shown in Gansu on lines 92R137 and Guinong22 [64], and steadily increased throughout the region [65]. This race is not yet dominant in populations in Wuhan, Xiangyang and Kunming, and QYr.haas-1B-1 (Yr24/26) showed excellent resistance in these three sites in 2015. Furthermore, the very low scores of lines combining QYr.haas-1B-1 with other QTLs reflected the overriding response strong seedling resistances have when combined with intermediate levels of resistance. It seems likely that Pst-V26 also has virulence to QYr.haas-1B-2 as this QTL was not only ineffective in isolation in Gangu, but so were the lines that combined it with the Yr24/26 locus.

QYr.haas-1B-2 and QYr.haas-2A had significant effects in reducing YR severity but did not create the immune response as observed with Yr24/26. The QYr.haas-2A effect is consistent with Yr17 where resistance is often incomplete, which can be influenced by genetic background and growing conditions [7]. This locus was still effective in Gangu and partially reduced disease severity. Furthermore, when Yr17 was combined with either Yr24/26 or QYr.haas-1B-2, disease scores in Gangu were further lowered. This suggests that there were mixed isolates in the field, some with virulence to Yr17 and other with virulence to the other QTLs.

Genetic map and the number of QTL detected

In this study, two marker sets were used to empirically investigate the effectiveness of population size and marker density in identifying QTLs. A QTL analysis was initially undertaken with a sparse genetic map (117 SSR markers) but with a large population size (388 lines). A subsequent analysis used a high density genetic map (11,330 markers) with a small population size (80 lines). The QTLs detected in the SSR map spanned much longer chromosome segments and this is not surprising given the low marker density of 10.6 cM per marker compared to the much higher density in the SNP map (2.5 cM per marker). Furthermore, the LOD scores in the SSR map were generally two to four times higher than in the SNP map and is a reflection of the vastly larger population sizes giving much greater confidence in the QTLs observed. However, most telling was the total number of QTLs identified, with seven different loci proving significant in the SNP map, while only three were apparent in the SSR map. This is again due to the greater genome coverage afforded by the SNP map as additionally identified QTLs were mostly in regions without any SSR coverage. The only exception was QYr.haas-1B-2 that was derived from E07901. However this was close to the XK0106 derived QYr.haas-1B-1 which provided immunity that would mask the more minor effects of the former QTL in the sparse SSR map.

In conclusion, major seedling resistance genes were found for both pathogens and these corresponded to Pm21, Yr24/26 and Yr17. Two new QTLs were likely identified in QPm.haas-2A and QYr.haas-1B-2, along with two other minor PM QTLs. QTL combination studies showed the ability to pyramid some of the PM QTLs is a starting point for developing near-immune lines based on QTLs, and gave insights into the pathogen populations in the YR sites. Finally, empirical testing of overlapping mapping populations with different marker densities and population sizes highlighted the usefulness of SNP platforms, even in relatively small populations.

Supporting information

S1 Table. Reaction type of sixteen differentials Bgt isolates on a set of known Pm genes lines and on the bi-parent.


S2 Table. Reaction types pattern of 5 Chinese Pst toXK0106, E07901 and 4Yr single-gene lines containing known gene in chromosome 1B and 2A.


S3 Table. Molecular markers linkage groups and map distances of the E07901 × XK0106 wheat map.


S4 Table. Original dataset of molecular marker linkage groups of the E07901 × XK0106 wheat mapping population.



The authors gratefully acknowledge Prof. Xianchun Xia (Institute of Crop Science, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences) for constructive comments to improve this manuscript. We thank Prof. Yiling Zhou (Institute of Plant Protection, China Academy of Agricultural Sciences) for kindly providing differential Bgt isolates and Prof. Dejun Han (Institute of Plant Pathology, Northwest A&F University), for providing Pst isolates and Yr single-gene lines. We also thank Shuangjun Gong, Wenqi Shi, Wei Huang, Ling Cheng, Mingfeng Xue and Bing Yuan (Hubei Academy of Agricultural Sciences) for experimental help and discussion.

Author Contributions

  1. Conceptualization: LY XJZ DY DF.
  2. Formal analysis: JW XJZ ML DF GMR.
  3. Funding acquisition: DY.
  4. Investigation: LY XJZ XZ JW ML MY HW LX FZ GMR.
  5. Methodology: LY.
  6. Resources: XZ MY DF.
  7. Visualization: LY.
  8. Writing – original draft: LY XJZ DY DF GMR.
  9. Writing – review & editing: LY GMR.


  1. 1. Bennett FGA. Resistance to powdery mildew in wheat: a review of its use in agriculture and breeding programmes. Plant Pathol. 1984;33:279–300.
  2. 2. Wan AM, Chen XM, He ZH. Wheat stripe rust in China. Aust J Agric Res. 2007; 58:605–619.
  3. 3. Zhuang QS. Chinese wheat improvement and pedigree analysis. China Agriculture Press, Beijing, 2003; pp469–487.
  4. 4. Chen WQ, Wu LR, Liu TG, Xu SC, Jin SL, Peng YL, et al. Race dynamics, diversity, and virulence evolution in Puccinia striiformis f. sp. tritici, the causal agent of wheat stripe rust in China from 2003 to 2007. Plant Dis. 2009; 93:1093–1101.
  5. 5. Huang X, Röder M. Molecular mapping of powdery mildew resistance genes in wheat: a review. Euphytica. 2004; 137:203–223.
  6. 6. Kou Y, Wang S. Broad-spectrum and durability: Understanding of quantitative disease resistance. Curr Opin Plant Biol. 2010; 13:181–185. pmid:20097118
  7. 7. McIntosh RA, Dubcovsky J, Rogers WJ, Morris CF, Appels R, Xia XC. Catalogue of gene symbols for wheat: 2013–2014 supplement. 2014; Available:
  8. 8. Hao YF, Parks R, Cowger C, Chen ZB, Wang YY, Bland D, et al. Molecular characterization of a new powdery mildew resistance gene Pm54 in soft red winter wheat. Theor Appl Genet. 2015; 128:465–476. pmid:25533209
  9. 9. Cheng P, Xu LS, Wang MN, See DR, Chen XM. Molecular mapping of genes Yr64 and Yr65 for stripe rust resistance in hexaploid derivatives of durum wheat accessions PI 331260 and PI 480016. Theor Appl Genet. 2014; 127:2267–2277. pmid:25142874
  10. 10. Dracatos PM, Zhang P, Park RF, McIntosh RA, Wellings CR. Complementary resistance genes in wheat selection 'Avocet R' confer resistance to stripe rust. Theor Appl Genet. 2016; 129:65–76. pmid:26433828
  11. 11. Limpert E, Felsenstein FG, Andrivon D. Analysis of virulence in populations of wheat powdery mildew in Europe. J Phytopathol. 1987; 120:1–8.
  12. 12. Markell SG, Milus EA. Emergence of a novel population of Puccinia striiformis f. sp. tritici in Eastern United States. Phytopathology 2008; 98:632–639. pmid:18944286
  13. 13. Zeng FS, Yang LJ, Gong SJ, Shi WQ, Zhang XJ, Wang H, et al. Virulence and Diversity of Blumeria graminis f. sp. tritici Population in China. J Integrat Agricul. 2014; 13(11):2424–2437.
  14. 14. Hua W, Liu ZJ, Zhu J, Xie CJ, Yang TM, Zhou YL, et al. Identification and genetic mapping of Pm42, a new recessive wheat powdery mildew resistance gene derived from wild emmer (Triticum turgidum var. dicoccoides). Theor Appl Genet. 2009; 119:223–230. pmid:19407985
  15. 15. Yuan FP, Wei GR, Zhan GM, Yao S, Chen W, Zeng QD, et al. Characterization on virulence of main prevalent pathotypes of Puccinia striiformis f. sp. tritici (Pst) in China. Journal of Triticeae Crops. 2014; 34 (11):1577–1582.
  16. 16. Singh RP, Huerta-Espino J, Bhavani S, Herrera-Foessel SA, Singh D, Singh PK, et al. Race non-specific resistance to rust diseases in CIMMYT spring wheats. Euphytica. 2011; 179:175–186.
  17. 17. Yang EN, Rosewarne GM, Herrera-Foessel SA, Huerta-Espino J, Tang ZX, Sun CF, et al. QTL analysis of the spring wheat ‘‘Chapio” identifies stable stripe rust resistance despite inter-continental genotype and environment interactions. Theor Appl Genet. 2013; 126:1721–1732. pmid:23558982
  18. 18. Li ZF, Lan CX, He ZH, Singh RP, Rosewarne GM, Chen XM, et al. Overview and application of QTL for adult plant resistance to leaf rust and powdery mildew in wheat. Crop Sci. 2014; 54(5):1907–1925.
  19. 19. Rosewarne GM, Herrera-Foessel SA, Singh RP; Huerta-Espino J, Lan CX, He ZH. Quantitative trait loci of stripe rust resistance in wheat. Theor Appl Genet. 2013; 126:2427–2449. pmid:23955314
  20. 20. Yang LJ, Zeng FS, Gong SJ, Shi WQ, Zhang XJ, Wang H, et al. Evaluation of resistance to powdery mildew in 68 Chinese major wheat cultivars and postulation of their resistance genes. Scientia Agricultura Sinica. 2013; 46(16):3354–3368.
  21. 21. Yang LJ, Wang H, Gong SJ, Xiang LB, Zhang XJ, Zeng FS, et al. Resistance evaluation of wheat cultivars and high-generation lines on stripe rust in the field. Hubei Agricul Sci. 2014; 53(24):6009–6012.
  22. 22. Gu J, Liu K, Li SX, Tian YX, Yang HX, Yang MJ. Study on the in vitro culture of cut plant in wheat haploid embryo induction by wheat x maize cross. J Triticeae Crops. 2008; 28(1):1–5.
  23. 23. Zhang XJ, Han DJ, Zeng QD, Duan YH, Yuan FP, Shi JD, et al. Fine mapping of wheat stripe rust resistance gene Yr26 based on collinearity of wheat with Brachypodium distachyon and rice. PLoS One. 2013; 8(3)e57885. pmid:23526955
  24. 24. Liu ZY, Sun QX, Ni ZF, Yang TM. Development of SCAR markers linked to the Pm21 gene conferring resistance to powdery mildew in common wheat. Plant Breed. 1999; 118:215–219.
  25. 25. Line RF, Qayoum A. Virulence, aggressiveness, evolution, and distribution of races of Puccinia striiformis (the cause of stripe rust of wheat) in North America, 1968–87. US Dept Agric Tech Bull. 1992; 1788.
  26. 26. Zadoks JC, Chang TT, Konzak CF. A decimal code for growth stages of cereals. Weed Res. 1974; 14:415–421.
  27. 27. Saari EE, Prescott JM. A scale for appraising the foliar intensity of wheat diseases. Plant Dis Rep. 1975; 59:377–380.
  28. 28. Peterson RF, Campbell AB, Hannah AE. A diagrammatic scale of estimating rust severity on leaves and stems of cereals. Can J Res Sec C. 1948; 26:496–500.
  29. 29. Sharp PG, Kreis M, Shewry PR, Gale MD. Location of ß-amylase sequence in wheat and its relatives. Theor Appl Genet. 1988; 75:289–290.
  30. 30. Somers DJ, Isaac P, Edwards K. A high-density microsatellite consensus map for bread wheat (Triticum aestivum L.). Theor Appl Genet. 2004; 109:1105–1114. pmid:15490101
  31. 31. Cao AZ, Xing LP, Wang XY, Yang XM, Wang W, Sun YL, et al. Serine/threonine kinase gene Stpk-V, a key member of powdery mildew resistance gene Pm21, confers powdery mildew resistance in wheat. Proc Natl Acad Sci. 2011; 108:7727–7732. pmid:21508323
  32. 32. Wang CM, Bie TD, Chen QZ, Cao AZ, Chen PD. Development and application of molecular markers specific to chromosome 6VS of Haynaldiavillosa. Acta Agronomica Sinica. 2007; 33(10):1595–1600.
  33. 33. Qi XL, Cui F, Yu L, Ding AM, Li J, Chen GL, et al. Molecular tagging of wheat powdery mildew resistance gene Pm21 by EST-SSR and STS markers. Mol Plant Breed. 2010; 4(1):1–5.
  34. 34. Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, et al. Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array. Plant Biotechnol J. 2014; 12:1–10.
  35. 35. Van Ooijen JW, Voorrips RE. JoinMap 4.0, Software for the calculation of genetic linkage maps. Plant Research International, Wangeningen, Netherlands, 2007.
  36. 36. Wang S, Basten CJ, Zeng ZB. Windows QTL Cartographer 2.5. 2007; Department of Statistics, North Carolina State University, Raleigh, NC. Available:
  37. 37. Mester D, Ronin YI, Hu Y, Nevo E, Korol A. Constructing large scale genetic maps using evolutionary strategy algorithm. Genetics. 2003; 165:2269–2282. pmid:14704202
  38. 38. Chen PD, Qi LL, Zhou B, Zhang SZ, Liu DJ. Development and molecular cytogenetic analysis of wheat-Haynaldia villosa 6VS/6AL translocation lines specifying resistance to powdery mildew. Theor Appl Genet. 1995; 91:1125–1128. pmid:24170007
  39. 39. Chantret N, Sourdille P, Röder MS, Tavaud M, Bernard M, Doussinalt G. Location and mapping of the powdery mildew resistance gene MIRE and detection of a resistance QTL by bulked segregant analysis (BSA) with microsatellites in wheat. Theor Appl Genet. 2000; 100:1217–1224.
  40. 40. Xie CJ, Sun QX, Ni ZF, Yang TM, Nevo E, Fahima T. Chromosomal location of a Triticum dicoccoides-derived powdery mildew resistance gene in common wheat by using microsatellite markers. Theor Appl Genet. 2003; 106:341–345. pmid:12582861
  41. 41. Paillard S, Trotoux-Verplancke G, Perretant MR, Mohamadi F, Leconte M, Coëdel S, et al. Durable resistance to stripe rust is due to three specific resistance genes in French bread wheat cultivar Apache. Theor Appl Genet. 2012; 125:955–965. pmid:22610360
  42. 42. Liu S, Griffey CA, Maroof MAS. Identification of molecular markers associated with adult plant resistance to powdery mildew in common wheat cultivar Massey. Crop Sci. 2001; 41:1268–1275.
  43. 43. Tucker DM, Griffey CA, Liu S, Brown-Guedira G, Marshall DS, Maroof MAS. Confirmation of three quantitative trait loci conferring adult plant resistance to powdery mildew in two winter wheat populations. Euphytica. 2007; 155:1–13.
  44. 44. Mingeot D, Chantret N, Baret PV, Dekeyser A, Boukhatem N, Sourdille P, et al. Mapping QTL involved in adult plant resistance to powdery mildew in the winter wheat line RE714 in two susceptible genetic backgrounds. Plant Breed. 2002; 121:133–140.
  45. 45. Li GQ, Li ZF, Yang WY, Zhang Y. Molecular mapping of stripe rust resistance gene YrCH42 in Chinese wheat cultivar Chuanmai 42 and its allelism with Yr24 and Yr26.Theor Appl Genet. 2006; 112:1434–1440. pmid:16525837
  46. 46. Ma JX, Zhou RH, Dong YS, Wang LF. Molecular mapping and detection of the yellow rust resistance gene Yr26 in wheat transferred from Triticum turgidum L. Using microsatellite markers. Euphytica. 2001; 120:219–226.
  47. 47. Wang CM, Zhang YP, Han DJ, Kang ZS, Li GP, Cao AZ, et al. SSR and STS markers for wheat stripe rust resistance gene Yr26. Euphytica. 2008; 159:359–366.
  48. 48. Payne PI, Holt LM, Johnson R, Snape JW. Linkage mapping of four gene loci, Glu-B1, Gli-B1, Rg1 and Yr10 on chromosome 1B of bread wheat. Genetica Agraria. 1986; 40:231–242.
  49. 49. McIntosh RA, Silk J, The TT. Cytogenetic studies in wheat XVII. Monosomic analysis and linkage relationships of gene Yr15 for resistance to stripe rust. Euphytica. 1996; 89:395–399.
  50. 50. Peng JH, Fahima T, Röder MS, Li YC, Dahan A, Grama A, et al. Microsatellite tagging of the stripe rust resistance gene YrH52 derived from wild emmer wheat Triticum dicoccoides, and suggestive negative crossover interference in chromosome 1B. Theor Appl Genet. 1999; 98:862–872.
  51. 51. Peng JH, Fahima T, Röder MS, Huang QY, Dahan A, Li YC, Grama A, Nevo E. High-density molecular map of chromosomal region harboring stripe-rust resistance genes YrH52 and Yr15 derived from wild emmer wheat, Triticum dicoccoides. Genetica. 2000; 109:199–210. pmid:11430483
  52. 52. Case AJ, Naruoka Y, Chen X, Garland-Campbell KA, Zemetra RS, Carter A H. Mapping Stripe Rust Resistance in a Brundage X Coda Winter Wheat Recombinant Inbred Line Population. PLoS One. 2014; 9(3):e91758. pmid:24642574
  53. 53. Wang LF, Ma JX, Zhou RH, Wang XM, Jia JZ. Molecular tagging of the yellow rust resistance gene Yr10 in common wheat, P.I.178383 (Triticum aestivum L.). Euphytica. 2002; 124:71–73.
  54. 54. William M, Singh RP, Huerta-Espino J, Ortiz Islas S, Hoisington D. Molecular marker mapping of leaf rust resistance gene Lr46 and its association with stripe rust resistance gene Yr29 in wheat. Phytopathology. 2003; 93:153–159. pmid:18943129
  55. 55. Agenbag GM, Pretorius ZA, Boyd LA, Bender CM, Prins R. Identification of adult plant resistance to stripe rust in the wheat cultivar Cappelle-Desprez. Theor Appl Genet. 2012; 125:109–120. pmid:22350093
  56. 56. Hao YF, Chen ZB, Wang YY, Bland D, Buck J, Brown-Guedira G, Johnson J. Characterization of a major QTL for adult plant resistance to stripe rust in US soft red winter wheat. Theor Appl Genet. 2011; 123:1401–1411. pmid:21830107
  57. 57. Lowe I, Jankuloski L, Chao S, Chen X, See D, Dubcovsky J. Mapping and validation of QTL which confer partial resistance to broadly virulent post-2000 North American races of stripe rust in hexaploid wheat. Theor Appl Genet. 2011; 123:143–157. pmid:21455722
  58. 58. Rosewarne GM, Li ZF, Singh RP, Yang EN, Herrera-Foessel SA, Huerta-Espino J. QTL analysis of leaf rust reactions in wheat reveal novel seedling genes and intercontinental genotype x environment interactions. Mol Breeding. 2015; 35:127–138.
  59. 59. Singh RP, Huerta-Espino J, Rajaram S. Achieving near-immunity to leaf and stripe rusts in wheat by combining slow rusting resistance genes. Acta Phytopathologica et Entomologica Hungarica. 2000; 35:133–139.
  60. 60. Krattinger SG, Lagudah ES, Spielmeyer W, Singh RP, Huerta-Espino J, McFadden H, et al. A putative ABC transporter confers durable resistance to multiple fungal pathogens in wheat. Science. 2009; 323:1360–1363. pmid:19229000
  61. 61. Lillemo M, Asalf B, Singh RP, Huerta-Espino J, Chen XM, He ZH, Bjørnstad Å. The adult plant rust resistance loci Lr34/Yr18 and Lr46/Yr29 are important determinants of partial resistance to powdery mildew in bread wheat line Saar. Theor Appl Genet. 2008; 116:1155–1166. pmid:18347772
  62. 62. Herrera-Fossel SA, Lagudah ES, Huerta-Espino J, Hayden MJ, Bariana HS, Singh D, Singh RP. New slow-rusting leaf rust and stripe rust resistance genes Lr67 and Yr46 in wheat are pleiotropic or closely linked. Theor Appl Genet. 2011; 122:239–249. pmid:20848270
  63. 63. Liu TG, Peng YL, Chen WQ, Zhang ZY. First detection of virulence in Puccinia striiformis f. sp. tritici in China to resistance genes Yr24 (= Yr26) present in wheat cultivar Chuanmai 42. Plant Dis. 2010; 94:1163.
  64. 64. Jia QZ, Huang J, Cao SQ, Zhang B, Wang XM, Jin SL. Discovery of new stripe rust strain infecting Chinese major wheat resistant material Guinong 22 and its preliminary pathogenicity analysis. Gansu Agric Sci Technol. 2012; 32:3–5.
  65. 65. Han DJ, Wang QL, Chen XM, Zeng QD, Wu JH, Xue WB, et al. Emerging Yr26-virulent races of Puccinia striiformis f. tritici are threatening wheat production in the Sichuan Basin, China. Plant Dis. 2015; 99:754–760.