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Article

Genome-Wide Linkage Mapping of QTL for Adult-Plant Resistance to Stripe Rust in a Chinese Wheat Population Lantian 25 × Huixianhong

by
Fangping Yang
1,*,†,
Yamei Wang
2,†,
Ling Wu
3,
Ying Guo
1,
Xiuyan Liu
1,
Hongmei Wang
4,
Xueting Zhang
1,
Kaili Ren
5,
Bin Bai
1,
Zongbing Zhan
1 and
Jindong Liu
6,*
1
Wheat Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou 730070, China
2
College of Life Sciences, Langfang Normal University, Langfang 065000, China
3
Crop Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu 610066, China
4
Institute of Biotechnology, Gansu Academy of Agricultural Sciences, Lanzhou 730070, China
5
Vegetable Research Institute, Gansu Academy of Agricultural Sciences, Lanzhou 730070, China
6
Institute of Crop Science, National Wheat Improvement Center, Chinese Academy of Agricultural Sciences, Beijing 100081, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Plants 2025, 14(16), 2571; https://doi.org/10.3390/plants14162571
Submission received: 15 June 2025 / Revised: 9 August 2025 / Accepted: 12 August 2025 / Published: 18 August 2025
(This article belongs to the Special Issue Cereals Genetics and Breeding)
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Abstract

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), represents a major global threat to wheat (Triticum aestivum. L). Planting varieties with adult-plant resistance (APR) is an effective approach for long-term management of this disease. The Chinese winter wheat variety Lantian 25 exhibits moderate-to-high APR against stripe rust under field conditions. To investigate the genetic basis of APR in Lantian 25, a set of 219 F6 recombinant inbred lines (RILs) was created from a cross between Lantian 25 (resistant parent) and Huixianhong (susceptible parent). These RILs were assessed for maximum disease severity (MDS) in Pixian of Sichuan and Qingshui of Gansu over the 2020–2021 and 2021–2022 growing seasons, resulting in data from four different environments. Genotyping was performed on these lines and their parents using the wheat Illumina 50K single-nucleotide polymorphism (SNP) arrays. Composite interval mapping (CIM) identified six quantitative trait loci (QTL), named QYr.gaas-2BS, QYr.gaas-2BL, QYr.gaas-2DS, QYr.gaas-2DL, QYr.gaas-3BS and QYr.gaas-4BL, which were consistently found across two or more environments and explained 4.8–12.0% of the phenotypic variation. Of these, QYr.gaas-2BL, QYr.gaas-2DS, and QYr.gaas-3BS overlapped with previous studies, whereas QYr.gaas-2BS, QYr.gaas-2DS, and QYr.gaas-4BL might be novel. All the resistance alleles for these QTL originated from Lantian 25. Furthermore, four kompetitive allele-specific PCR (KASP) markers, Kasp_2BS_YR (QYr.gaas-2BS), Kasp_2BL_YR (QYr.gaas-2BL), Kasp_2DS_YR (QYr.gaas-2DS) and Kasp_2DL_YR (QYr.gaas-2DL), were developed and validated in 110 wheat diverse accessions. Additionally, we identified seven candidate genes linked to stripe rust resistance, including disease resistance protein RGA2, serine/threonine-protein kinase, F-box family proteins, leucine-rich repeat family proteins, and E3 ubiquitin-protein ligases. These QTL, along with their associated KASP markers, hold promise for enhancing stripe rust resistance in wheat breeding programs.

1. Introduction

Stripe rust (yellow rust, YR), caused by Puccinia striiformis f. sp. tritici (Pst), is a highly damaging fungal disease affecting common wheat (Triticum aestivum). It predominantly thrives in temperate, medium-altitude, and maritime wheat-growing regions [1]. Yield losses attributed to YR range from 10 to 70%, with over 20 significant epidemics reported globally [2]. In recent years, wheat YR has affected approximately 4.2 million hectares of farmland annually, causing significant economic losses to the wheat cultivation industry in the southwestern and northwestern regions of China [2]. While fungicides offer control, their effectiveness is constrained by management and financial limitations. Consequently, resistant cultivars represent an economically viable and environmentally sustainable strategy against this disease [2,3].
Resistance to YR is broadly classified into all-stage resistance and adult-plant resistance (APR) [1,4,5]. All-stage resistance typically involves major, race-specific genes inherited qualitatively [6], but tends to be short-lived due to the rapid adaptation of new pathogen races [7]. In contrast, APR, conferred by minor, typically race non-specific genes inherited quantitatively, offers more durable resistance [5]. Combining multiple APR genes can provide effective, lasting resistance, such as Yr18 combined with additional minor genes, which has protected against YR for over 80 years in various countries including China [8].
Currently, over 90 wheat YR resistance genes at nearly 70 loci have been formally cataloged, predominantly race-specific, with many in China having been overcome by new pathogen races [9]. Among these, nineteen APR genes at various loci have been identified, some with pleiotropic effects conferring resistance to other diseases [4], namely, Yr18 (7DS) [10], Yr29 (1BL) [11], Yr30 (3BS) [12], Yr34 (5AL) [13], Yr46 (4DL) [14], Yr48 (5AL) [15], Yr49 (3DS) [16], Yr54 (2DL) [17], Yr56 (2AS) [18], Yr58 (3BS) [19], Yr60 (4AL) [20], Yr68 (4BL) [21], Yr71 (3DL) [22], Yr75 (7AL) [23], Yr77 (6DS) [24], Yr78 (6BS) [25], Yr80 (3BL) [26], Yr83 (6RL) [27], and Yr86 (2AL) [28,29,30], whereas Yr36 (6BS) [31], Yr39 (7BL) [32], Yr52 (7BL) [33], Yr59 (7BL) [34], Yr62 (4BL) [35], and Yr79 (7BL) [3] are high-temperature adult-plant (HTAP) resistance genes against stripe rust [10,11,12,13,14]. Additionally, Yr18/Lr34/Sr57/Pm38 [10], Yr29/Lr46/Sr58/Pm39 [11], Yr30/Lr27/Sr2/Pm70 [12], and Yr46/Lr67/Sr55/Pm46 [14] are pleiotropic genes which have been widely utilized in breeding programs alongside all-stage resistance genes such as Yr5, Yr10, Yr15, and Yr24/Yr26/YrCH42 [19,26,36,37,38,39,40,41,42,43]. To date, the successfully cloned genes include Yr5 [36], Yr10 [37], Yr15 [38], YrU1 [39], Yr27 [40], Yr28 [41], Yr36 [19], Yr18 [26], Yr46 [42,43], and YrNAM [44].
Over the past two decades, numerous quantitative trait loci (QTL) for YR resistance have been identified across 49 chromosomal regions [30]. Molecular markers, particularly SNP arrays, facilitate combining APR and all-stage resistance in breeding programs. However, challenges such as low polymorphism and the vast genome of common wheat limit mapping resolution. High-density linkage maps constructed using SNPs enable precise QTL analysis and identification of candidate genes.
Lantian 25, a semi-dwarf winter wheat variety, exemplifies moderate-to-high resistance to YR at maturity while being susceptible at the seedling stage, demonstrating a typical APR response. This study aims to identify APR QTL in a Lantian 25 × Huixianhong recombinant inbred line (RIL) population using SNPs and to develop markers for wheat YR resistance breeding.

2. Results

2.1. Phenotypic Evaluation

The moderately resistant parent, Lantian 25, demonstrated a mean maximum disease severity (MDS) of 20.3%, 25.6%, 20.7%, and 20.0% in Pixian 2021, Qingshui 2021, Pixian 2022, and Qingshui 2022, respectively. In contrast, the susceptible parent, Huixianhong, displayed a mean MDS of 90.5%, 100.0%, 100.0%, and 95.0% across the four environments, respectively (Figure A1). For the 219 RILs, the mean MDS were 59.7%, 59.3%, 59.4%, and 53.1% in Pixian 2021, Qingshui 2021, Pixian 2022, and Qingshui 2022, respectively. The MDS ranges for these environments were 5.0–100.0%, 1.0–100.0%, 3.0–100.0%, and 0–100.0%, respectively, indicating substantial polygenic variation in the population. Statistical analysis revealed significant correlations (r = 0.57–0.93; p < 0.01) for MDS across environments.
Analysis of variance (ANOVA) for MDS revealed highly significant differences (p < 0.01) among RILs, environments, and line × environment interactions (Table A1), indicating that stripe rust resistance is influenced by both genetic and environmental factors. The observed distribution of MDS and the significant genotype × environment interactions emphasize the quantitative nature of adult-plant resistance to stripe rust. The Hb2 for MDS was calculated as 0.72, suggests that a considerable proportion of the phenotypic variance is attributable to genetic factors, making this population suitable for QTL mapping and further genetic studies of stripe rust resistance.

2.2. QTL for APR to Stripe Rust

Six QTL for YR resistance were identified in this study, namely, Qyr.gaas-2BS, QYr.gaas-2BL, QYr.gaas-2DS, QYr.gaas-2DL, QYr.gaas-3BS, and QYr.gaas-4BL (Table 1). All the resistance alleles were contributed by Lantian 25. A major and consistent QTL, QYr.gaas-4BL, was flanked by AX-89396432 and AX-111732484 at 665.4–667.9 Mb in Pixian2020, Qingshui 2020, and Pixian 2021, and explained 8.6–12.0% of the phenotypic variances (PVE). QYr.gaas-2BS, located at the interval of AX_109302306 (96.1 Mb) and AX_108894451 (102.8 Mb), in Pixian2020 and Pixian2021, explained 7.5–8.6% of the PVE. QYr.gaas-2BL, closely linked with AX_111590697 (672.3 Mb) and AX_110245106 (697.9 Mb) in Pixian2020, Pixian 2021, and Qingshui 2021, respectively, explained 4.8–8.5% of the PVE. Two loci for YR resistance were identified on the 2D chromosome. QYr.gaas-2DS, between AX_109080248 and AX_110028411 and located at the 96.1–102.8 Mb in Pixian2020, Pixian 2021, and Qingshui 2021, respectively, explained 7.5–8.6% of the PVE. QYr.gaas-2DL, between AX_109529695 and AX_109338734 and located at the 596.0–608.6 Mb in Pixian2020, Pixian 2021 and Qingshui 2020, respectively, explained 5.2–9.6% of the PVE. QYr.gaas-3BS, between AX-111732973 and AX-110097186 and located at the 2.49–8.04 Mb on chromosome 3BS in Pixian2020, Pixian 2021, and Qingshui 2021, respectively, explained 4.9–8.5% of the PVE (Figure A2).

2.3. Candidate Gene Identification

A total of 707 annotated genes were present in the QTL regions for wheat stripe rust identified in this study and are listed in Table S1. A total of seven candidate genes were selected from the QTL regions for wheat stripe rust identified in this study, primarily involved in biological metabolism of disease resistance response, signal transformation, and the ubiquitin pathway (Table 2). Among these candidates, TraesCS2B02G479500 for QYr.gaas-2BL encoded the disease resistance protein family. TraesCS2B02G487600 for QYr.gaas-2BL encoded the disease resistance protein RGA2. For QYr.gaas-2DS and QYr.gaas-2DL, TraesCS2D02G154700 and TraesCS2D02G505900 were selected as the candidate genes and encoded the serine/threonine-protein kinase. For QYr.gaas-4BL and QYr.gaas-2BS, TraesCS4B02G391600 and TraesCS2B02G130600 encoded the F-box family proteins. One candidate gene for QYr.gaas-3BS was selected, TraesCS3B02G013100, and encoded the glycosyltransferase.
On the right is the expression level of the candidate genes, with darker colors indicating higher expression levels. On the left is information about the organs where the genes are expressed and the physiological and biochemical pathways they are involved in. The expression data are sourced from https://www.wheat-expression.com/ (accessed on 1 June 2025).

2.4. Development and Validation of Kompetitive Allele-Specific PCR (KASP) Markers

Efforts were made to develop KASP markers for all six identified QTL: QYr.gaas-2BS, QYr.gaas-2BL, QYr.gaas-2DS, QYr.gaas-2DL, QYr.gaas-3BS, and QYr.gaas-4BL. However, attempts to develop KASP markers for QYr.gaas-3BS and QYr.gaas-4BL were unsuccessful in effectively discriminating between parental genotypes within the RIL population, resulting in inconclusive outcomes (Table A2). Consequently, four KASP markers were successfully developed based on tightly linked KASP markers: Kasp_2BS_YR (QYr.gaas-2BS, 99.7 Mb), Kasp_2BL_YR (QYr.gaas-2BL, 697.7 Mb), Kasp_2DS_YR (QYr.gaas-2DS, 12.7 Mb), and Kasp_2BL_YR (QYr.gaas-2BL, 602.5 Mb). To validate the efficacy of these markers, a diverse panel with 111 cultivars was employed. For Kasp_2BS_YR, the favorable allele (CC) was present in 75 accessions, exhibiting a mean MDS of 38.0%. In contrast, the unfavorable allele (TT) was found in 32 accessions, with a mean MDS of 45.9%. This difference was statistically significant at p = 0.05 (Table 3 and Table A3). For Kasp_2BL_YR, the favorable allele (CC) was present in 69.4% of the cultivars, exhibiting a mean MDS of 39.1%. In contrast, the unfavorable allele (GG) was found in 27.9% of cultivars, with a mean MDS of 43.9%. This difference was statistically significant at p = 0.05 (Table A2). Similarly, for Kasp_2DS_YR, the favorable allele (GG) was observed in 55.0% of cultivars, demonstrating a mean MDS of 37.8%. The unfavorable allele (CC) was present in 63 cultivars, with a mean MDS of 38.3%. For Kasp_2DL_YR, the favorable allele (CC) was present in 63 of the cultivars, exhibiting a mean MDS of 38.3%. In contrast, the unfavorable allele (TT) was found in 48 cultivars, with a mean MDS of 43.7%. This difference was statistically significant at p = 0.05 (Table A2). This distinction was also statistically significant at p = 0.05.

3. Discussion

To date, over 350 wheat stripe rust resistance QTL or genes have been identified from wheat and related species through linkage analysis or association mapping methodologies. In the study, QYr.gaas-2BS (97.9 Mb) and QYr.gaas-2BL (676.8 Mb) were identified. Stripe rust resistance genes, including Yr5/YrSP (739.4 Mb), Yr7 (660.0 Mb), QYr.sicau-2B.1 (732.1 Mb), QYr.sicau-2B.2 (799.5 Mb), QYr.sicau-2B (759.0 Mb), QYr.caas-2BL.2 (685.8 Mb), QYr.spa-2B.1 (280.9 Mb), QYrqn.nwafu-2BL (674.0 Mb), QYr.nwafu-2BL (796.8 Mb), QYraq.cau-2BL (671.0 Mb), QYr.inra-2BL (615.8–621.0 Mb), and QYr.caas-2BL (693.7–733.2 Mb), were identified on chromosome 2BS and 2BL [45,46,47,48,49,50,51,52]. Among them, QYrqn.nwafu-2BL (674.0 Mb) and QYraq.cau-2BL (671.0 Mb) overlapped with QYr.gaas-2BL identified in our study. However, no overlap was observed between QYr.gaas-2BS and previously identified loci on chromosome 2B. Thus, QYr.gaas-2BS might be novel.
In the present study, QYr.gaas-2DS and QYr.gaas-2DL were localized to the distal region of chromosome 2DS and 2DL, with the peak marker positioned between 96.1–102.8 Mb and 596.0–608.6 Mb. To date, six stripe rust resistance genes have been identified on chromosome 2D: Yr8, Yr16, Yr54, Yr55, Yr37, and YrCK [45,53,54,55]. The APR gene Yr16 and QYr.inra-2DS have been mapped to the centromeric region of chromosome 2D [46], indicating that these loci are distinct from QYr.gaas-2DS. Furthermore, Ren et al. [47] reported a QTL on chromosome 2D flanked by the SSR markers Xgwm539 (513.1 Mb) and Xcfd44 (608.6 Mb), which overlapped with QYr.gaas-2DL identified in this study. Several other QTL have been mapped to various positions on chromosome 2D: QYr.ufs-2D (72.6 Mb) [56], QYr.caas-2DS (12.3–19.6 Mb) [54], QYr.2DS (19.6 Mb) [53], and QYr.inra-2DS (72.6 Mb) [23]. The distinct genomic location of QYr.gaas-2DS compared to previously reported QTL suggests that it may represent a novel locus conferring stripe rust resistance.
The 3B chromosome is rich in stripe rust resistance genes [57,58,59]. Over 15 loci for stripe rust have been identified distributed on the 3B chromosome [28,29,30]. Of these, QYr.cimmyt-3BS from Pavon76 [33], QYr.inra-3BS from Renan [21], QYr.ucw-3BS from UC110 [60], and QRYr-3B from Pastor have shown effective and stable resistance for stripe rust. Furthermore, the well-known adult-plant resistance gene for stripe rust, Yr30, is located on chromosome 3BS, overlapping with the locus identified in this study. Thus, we hypothesized that QYr.gaas-3BS might correspond to Yr30. To verify this, we genotyped Lantian 25 using the reported marker (gwm533) and confirmed that Lantian 25 carries Yr30 [34]. This finding supports the conclusion that QYr.gaas-3BS is indeed Yr30.
Yr18, Yr29, Yr30, and Yr46 have good resistance effects against stripe rust and are widely used in Chinese varieties, especially in the Huang-Huai winter wheat region and the southwestern wheat region. We conducted extensive testing for Yr18, Yr29, Yr30, and Yr46 in 2014 and have well-established primers and detection systems. However, only Yr30 was detected in Lantian25 and maybe QYr.gaas-3BS. Furthermore, Yr18, Yr29 and Yr46 are located on chromosomes 7DS, 1BL, and 4DL, respectively. In this study, we detected eight loci related to wheat stripe rust resistance in Lantian25, located on chromosomes 2BS, 2BL, 2DS, 2DL, 3BS, and 4BL, none of which are on the same chromosomes as the three important stripe rust resistance genes mentioned above. In addition to Yr18, Yr29, Yr30, and Yr46, we also tested for Yr17 and Yr26, but none were detected in Lantian25.
Nine stable and effective loci for stripe rust resistance were identified on chromosome 4BL [22,61,62,63,64], namely, Qyr.wpg-4B.1(531.1 Mb), Yr62 (509.0–568.6 Mb) [22], QYrhm.nwafu-4B (523.4–568.6) [62], QYr.caas-4BL (509.0–544.6), QYr.nwafu-4BL (189.7–192 Mb), QYr.nwafu-4BL (640.1 Mb), QPst.jic-4B (610.6 Mb), QPst.jic-4B (592.6–622.3 Mb), and QYr.sun-4B (250.0 Mb) [19,26,41,42,43,65,66]. No overlap was identified between QYr.gaas-4BL (665.4–667.9 Mb) and the loci mentioned above [22,61,62,63,64,65]. Thus, QYr.gaas-4BL may be novel.
In total, seven candidate genes were selected based on the genetic interval, annotation, and expression patterns (Figure 1). TraesCS2B02G479500 and TraesCS2B02G487600 (QYr.gaas-2BL) encoded the disease resistance protein family. The majority of plant disease resistance genes encode disease resistance proteins, including leaf rust, stripe rust, or powdery mildew resistance [67,68], like TaRPS2 for wheat stripe rust [66] and TaRPP13 for powdery mildew [67]. In plants, the disease resistance protein family gene exhibits a higher degree of conservation. Previous studies have indicated that the wheat leaf rust resistance gene Lr10 may function as a guardee, directly interacting with pathogen effectors, while RGA2 assumes the role of a guard. In other proposed models, the plant RGA2 gene recognizes pathogen effectors through indirect mechanisms, resulting in a more complex process [68,69]. Both TraesCS2D02G154700 for QYr.gaas-2DS and TraesCS2D02G505900 for QYr.gaas-2DL encoded the serine/threonine-protein kinase, which significantly associated with powdery mildew or septoria leaf blotch [70,71]. For QYr.gaas-4BL and QYr.gaas-2BS, TraesCS4B02G391600 and TraesCS2B02G130600 encoded the F-box family proteins, in response to various pathogens in the degradation machinery [72,73]. TraesCS3B02G013100 for QYr.gaas-3BS was selected and encoded as the glycosyltransferase, which is annotated as a component of plant immune signaling pathways [74].
While conventional breeding methodologies have contributed significantly to the enhancement of disease resistance, the selection process remains time-intensive and relatively inefficient [75]. QTL identified across multiple environments offer promising potential for implementation in MAS strategies. The present investigation corroborates previous findings, indicating that the incorporation of 4–5 APR genes with minor-to-intermediate effects within a single line may confer enhanced levels of resistance to stripe rust. This observation underscores the potential for pyramiding multiple resistance loci to achieve durable and broad-spectrum resistance. KASP, a uniplex SNP genotyping platform that provides a cost-effective and scalable approach for applications requiring small-to-moderate marker numbers, such as MAS and QTL fine mapping. In this study, Kasp_2BS_YR, Kasp_2BL_YR, Kasp_2DS_YR, and Kasp_2DL_YR were successfully developed based on tightly linked SNP markers. These markers have demonstrated their utility as valuable tools for MAS in wheat breeding programs aimed at improving yellow rust resistance. By enabling rapid and accurate genotyping of resistance-associated loci, these markers facilitate the efficient introgression of beneficial alleles into elite germplasm. Furthermore, the ability to combine multiple resistance loci through MAS offers the potential to develop wheat cultivars with enhanced and durable resistance to stripe rust.

4. Materials and Methods

4.1. Germplasm Development and Characterization

A population of 219 F2:6 RILs was derived from the cross between Lantian 25 and Huixianhong. Both parental lines exhibited high susceptibility to the predominant Pst races CYR29, CYR31, CYR32, CYR33, and CYR34 at the seedling stage. However, Lantian 25 demonstrated moderate resistance at the adult-plant stage under field conditions. The RIL population was developed using the single seed descent method, with one randomly selected spike harvested per generation for advancement. Additionally, 110 wheat cultivars, predominantly from the Yellow-Huai Wheat Region, was utilized to validate the efficacy of KASP markers for stripe rust resistance.

4.2. Field Experimentation

The F2:6 RILs and their progenitors were evaluated for APR to YR at two locations: Pixian (30°05′ N, 102°54′ E) and Qingshui (34°05′ N, 104°35′ E). Trials were conducted during the 2020–2021 and 2021–2022 cropping seasons, providing data from four distinct environments. Both sites are recognized YR hotspots in China, offering optimal conditions for rust pathogen proliferation. The experimental design employed randomized complete blocks with two replicates per location. Each plot consisted of a single 1.5 m row, with 0.25 m inter-row spacing. About 50 seeds were sown per row. The highly susceptible cultivar Huixianhong was planted every tenth row as a disease spreader. To ensure sufficient inoculum pressure, border rows of cv. Huixianhong encircled the experimental plots at both locations.
Inoculations were performed at the jointing stage using a mixture of prevalent Chinese Pst races (CYR31, CYR32, CYR33, and CYR34) applied via spray method. Inoculations occurred around January 5 in Pixian and April 10 in Qingshui. Disease severity (DS) assessments commenced 12–18 days post-inoculation, once the susceptible control Huixianhong exhibited pronounced symptoms. DS was recorded weekly, typically 2–3 times, with the MDS selected for subsequent analysis and QTL mapping.

4.3. Genotyping and Genetic Map Construction and QTL Analysis

All 219 RILs were genotyped using the wheat 50K iSelect SNP array. SNPs with >20% missing data or minor allele frequency (MAF) <0.5 were excluded from further analysis according to Wen et al. [76]. The filtered SNPs were grouped into bin markers by IciMapping v4.2 (https://isbreeding.caas.cn/rj/qtllcmapping/294445.htm (accessed on 1 June 2025)) [77] and the linkage map was constructed by the regression mapping algorithm (JoinMap v4.0) (JoinMap v4.0). QTL analysis was conducted by inclusive composite interval mapping (ICIM) implemented in IciMapping 4.1 according to Liu et al. [78]. A logarithm of odds (LOD) threshold of 2.75 was established for QTL significance based on 1000 permutations at p = 0.05. Physical positions for SNPs were according to the IWGSC2.1.
MDS data from four environments across three cropping seasons were utilized for ANOVA conducted using IciMapping 4.1. The contributions of RILs and environments were assessed using PROC MIXED, with environments treated as fixed effects, while lines, line × environment interactions, and replicates nested within environments were considered random effects. Broad-sense heritability (H2b) for YR was calculated using the formula: H2b = σ2g/(σ2g + σ2ge/r + σ2ε/re). Of these, σ2g: genotypic; σ2ge: genotype × environment interaction; and σ2: residual error variances, respectively. The terms e and r denote the number of environments and replicates per environment, respectively.

4.4. KASP Marker Development and Candidate Gene Identification

SNPs were converted to KASPs using PolyMarker. Genotyping was performed using 384-well plates and analyzed on a PHERA starplus SNP platform. Genotype calling was conducted using KlusterCaller v1.0 software (LGC company, Londong, UK). All KASP markers were validated using the panel of 110 cultivars. The validation panel consisted of 111 wheat accessions, primarily from different wheat-growing regions in China, including modern cultivars, advanced lines, and landraces. All accessions were evaluated for stripe rust resistance during the 2014–2015 and 2015–2016 cropping seasons at the Pixian Experimental Station of the Sichuan Academy of Agricultural Sciences and the Gangu Qingshui Experimental Station of the Gansu Academy of Agricultural Sciences, as well as during the 2014–2015 cropping season at the Zhongliang Experimental Station of the Tianshui Institute of Agricultural Science in Gansu Province. These three locations are hotspots for stripe rust in China, with environmental conditions conducive to disease development. Field trials were conducted using a randomized complete block design with three replicates, three-row plots, 20 cm row spacing, and 1.5 m row length. Every 10th row was planted with the highly susceptible control cultivar Huixianhong. Inoculation was performed at the jointing stage by spraying a mixture of prevalent Chinese races, including CYR32, CYR33, and CYR34. MDS was recorded 18 to 20 days after flowering. The MDS from each environment and the mean values across the five environments for each accession were used for subsequent validation analysis. Differences in stripe rust severity between KASP marker classes were analyzed using Student’s t-test to determine statistical significance.
To elucidate potential candidate genes associated with stripe rust resistance QTL detected in the Lantian 25/Huixianhong RIL population, genes located at the confidence interval of each QTL were extracted from the wheat IWGSC v2.1. Genes were considered candidates if they contained SNPs in coding regions and were not annotated as hypothetical, transposon, or retrotransposon proteins.

5. Conclusions

This study elucidates the genetic basis of APR to stripe rust in Lantian 25. Six QTL, namely, QYr.gaas-2BS, QYr.gaas-2BL, QYr.gaas-2DS, QYr.gaas-2DL, QYr.gaas-3BS, and QYr.gaas-4BL, were consistently identified, explaining 4.8–12.0% of PVEs. Among these, QYr.gaas-2BL, QYr.gaas-2DS, and QYr.gaas-4BL overlap with previously reported loci, while QYr.gaas-2BS, QYr.gaas-2DS, and QYr.gaas-4BL represent potential novel loci. Notably, all resistance alleles originated from Lantian 25. The development of validated four KASP markers (Kasp_2BS_YR, Kasp_2BL_YR, Kasp_2DS_YR, and Kasp_2DL_YR) and identification of candidate genes (e.g., disease resistance proteins, kinases, and ubiquitin ligases) provide actionable tools for MAS breeding. These findings advance our understanding of APR mechanisms and offer robust genetic resources and molecular tools for enhancing durable stripe rust resistance in wheat breeding.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/plants14162571/s1, Table S1: The higher confidence genes located in the QTL for stripe rust resistance in this study.

Author Contributions

Conceptualization, F.Y. and Y.W.; methodology, L.W.; software, Y.G.; validation, X.L. and H.W.; formal analysis, X.Z.; investigation, K.R.; resources, B.B.; data curation, Z.Z.; writing—review and editing, J.L.; visualization, F.Y.; supervision, F.Y.; project administration, F.Y.; funding acquisition, F.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (32060481, 32260485 and 32401902) and the 2025 Seed Industry Breakthrough Project of Gansu Provincial Agriculture and Rural Affairs (ZYGG-2025-8).

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

APRAdult-plant resistance
RILsRecombinant inbred lines
SNPSingle-nucleotide polymorphism
SRStripe rust
QTLQuantitative trait loci
KASPKompetitive allele-specific PCR
MASMarker-assisted selection
PVEPhenotypic variance explained
YRYellow rust

Appendix A

Plants 14 02571 g0a1
Figure A1. Frequency distributions for stripe rust responses in the Lantian 25/Huixianhong RIL population.
Figure A1. Frequency distributions for stripe rust responses in the Lantian 25/Huixianhong RIL population.
Plants 14 02571 g0a1
Plants 14 02571 g0a2
Figure A2. QTL and corresponding LOD curves identified in this study.
Figure A2. QTL and corresponding LOD curves identified in this study.
Plants 14 02571 g0a2
Table A1. Analysis of variance of the maximum disease severity for stripe rust in the Lantian 25/Huixianhong RIL population.
Table A1. Analysis of variance of the maximum disease severity for stripe rust in the Lantian 25/Huixianhong RIL population.
Source of VarianceDfMean SquareF Value
Replicate (environment)215718.8 *
Environment438,028212.0 *
Line218312517.4 *
Line × Environment10883111.7 *
Error1654179
* Significant at p < 0.05.
Table A2. The KASP primers for the four markers developed in this study.
Table A2. The KASP primers for the four markers developed in this study.
Kasp MarkerPrimeSequence
Kasp_2BS_YFAXGAAGGTGACCAAGTTCATGCTtgCtagtgaaatcaagtgtatgatA
HEMGAAGGTCGGAGTCAACGGATTtgCtagtgaaatcaagtgtatgatG
Common
Kasp_2BL_YRFAXGAAGGTGACCAAGTTCATGCTGGGTAGCATTGATCTAAACTCCTG
HEMGAAGGTCGGAGTCAACGGATTGGGTAGCATTGATCTAAACTCCTC
CommonctgagcgactgtttcttattgtT
Kasp_2DS_YRFAXGAAGGTGACCAAGTTCATGCTCTACAAACATGGTTCACATTGAC
HEMGAAGGTCGGAGTCAACGGATTACTACAAACATGGTTCACATTGAT
CommonTGCATCATCTCCACCGGAAC
Kasp_2DL_YFAXGAAGGTGACCAAGTTCATGCTgttctcgatctgtatgctgaagtA
HEMGAAGGTCGGAGTCAACGGATTgttctcgatctgtatgctgaagtG
CommonagatgactttccagatgtagggA
Table A3. The genotype and stripe rust responses for the 111 wheat accessions by the four developed KASP markers.
Table A3. The genotype and stripe rust responses for the 111 wheat accessions by the four developed KASP markers.
NameOriginMDS (%)Kasp_2BS_YRKasp_2BL_YRKasp_2DS_YRKasp_2DL_YR
WheatearUSA33.2CCCCGGCC
11CA40Beijing21.8CCCCAACC
12CA29Beijing64.3CCCCGGCC
CA0548Beijing83.3CCCCAATT
CA0816Beijing22.3CCCCGGCC
CA0958Beijing59.7CCGGAATT
CA1055Beijing60.3TTGGGGCC
CA1090Beijing69.5TTGGAATT
CA1119Beijing30.4TTGGGGCC
CA1133Beijing30.7CCCCGGCC
CA9722Beijing61.4CCCCAATT
Jing411Beijing27.8CCCCGGCC
Jing9428Beijing68.3CCCCAATT
Zhongmai175Beijing22.3CCGGAATT
Zhongmai415Beijing74.6CCCCGGCC
Zhongyou9507Beijing50.5CCCCAATT
HoldfastBritain18.5CCCCGGCC
00127-2-2Gansu7.9CCCCGGCC
863-13Gansu19.4CCCCGGCC
BaigetiaoGansu20.1CCCCGGTT
Baimangmai1Gansu24TTGGGGCC
CP07-9-1-1-2F6Gansu41.3CCCCGGCC
DabaijiankouGansu21.6CCGGAATT
Damai1Gansu18.9CCCCGGCC
Hangxuan2Gansu25.8CCCCGGCC
HonghuomaiGansu33CCCCGGCC
HonglaomangmaiGansu43.6TTCCGGTT
HuomaiziGansu31.5CCCCAATT
JinhuangmaiGansu24.4TTGGGGCC
Lanhangxuan122Gansu34.2CCCCAATT
Lantian 25Gansu36.4TTGGAATT
Lantian26Gansu10.3CCCCGGCC
LongdonghongGansu23.8CCCCGGCC
Longjian103Gansu32.3CCCCAATT
Longjian196Gansu26CCCCGGCC
Longjian301Gansu59.9CCCCGGCC
Pingliang45Gansu37.5CGCGGGCC
TutoumaiGansu29.5CCCCAATT
XiaobeijiekouGansu23.7CCCCGGCC
Xifeng20Gansu56.5CCCCAACC
YoumangmazhamaiGansu47.3CCCCGGCC
Hengguan33Hebei45CCCCAATT
Shijiazhuang8Hebei57.1CCGGGGCC
Ag303-29Henan39.8TTGGAATT
Ag303-8Henan45GCGCGGCC
Ag311-8Henan47.1CCCCAATT
Aikang58Henan58.2CCCCGGCC
Bainong64Henan37.5CCCCAATT
C40468Henan46.7TTCCGGCC
C40469Henan51.9TTCCAACC
C40470Henan54TTGGGGCC
C40472Henan55.3CCCCAATT
C40473Henan48.4CCGGGGCC
C40477Henan38.2CCCCGGCC
C40481Henan46.1TTCCAATT
C40485Henan24.1CCCCGGCC
C50835Henan42.1TTGGAATT
C50837Henan26.6TTGGAATT
C50843Henan39.2CCCCGGCC
C50845Henan25.2TTGGGGCC
C50850Henan52.5CCCCAATT
C50851Henan51.3CCCCAATT
C50855Henan53.6CCCCGGCC
C50865Henan39.3GCGCAGCC
He106Henan31CCCCGGCC
He109Henan45.6TTCCAATT
He12Henan18.8CCCCGGCC
He120Henan25.8CCCCAATT
He18Henan31.5CCCCAATT
He193Henan19CCCCGGCC
He2Henan47.3TTCCAATT
He222Henan26.6CCCCAATT
He231Henan33.9TTGGAATT
He244Henan19.4CCCCGGCC
He256Henan48.7CCCCGGCC
He3Henan30.3TTGGAATT
He48Henan30.9TTGGGGCC
He53Henan38.5TTGGAATT
He7Henan28.6CCCCGGCC
He87Henan27.8CCCCAATT
Pingyuan50Henan11.1CCCCGGCC
Zheng9023Henan49.3CCCCAATT
Zhengmai366Henan29.4CCCCGGCC
Zhongmai871Henan36.6CCCCAATT
Zhongmai875Henan35.5CCGGAATT
Zhongmai895Henan34.7CCCCAATT
Zhoumai13Henan45.8TTCCAATT
Zhoumai16Henan41.2CCCCGGCC
Zhoumai18Henan22.8CCCCGGCC
LibellulaItaly19.3TTGGAATT
PascalItaly7.1CCCCGGCC
AbbondanzaItaly64.2TTGGGGCC
FunoItaly8.6CCCCAATT
Ningdong10Ningxia25CCCCGGCC
Ningdong10Ningxia25CCCCGGCC
Ningdong11Ningxia83.2CCCCAATT
Lovrin10Romania69TTGGGGCC
Changwu131Shaanxi52.9CCCCGGCC
Xiaoyan6Shaanxi75.9CCCCAATT
Jimai19Shandong46TTGGGGCC
Jimai22Shandong36.6TTGGAATT
Jinan13Shandong74.2CCCCGGCC
Jinan17Shandong59.8CCCCGGCC
Liangxing66Shandong52.3TTGGAATT
Linmai4Shandong51.8TTGGAATT
Lumai21Shandong72.5TTCCGGCC
Weimai8Shandong60.4CCCCGGCC
Yannong19Shandong90.9TTGGAATT
ChineseSpringSichuan34.4CCCCGGCC
Chuanmai107Sichuan62.1CGCGAATT
Fan6 75.9TTGGGGCC

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Plants 14 02571 g001
Figure 1. Expression patterns for the candidate genes identified in this study.
Figure 1. Expression patterns for the candidate genes identified in this study.
Plants 14 02571 g001
Table 1. QTL for stripe rust resistance in the Lantian 25 × Huixianhong RIL population.
Table 1. QTL for stripe rust resistance in the Lantian 25 × Huixianhong RIL population.
QTLEnvironmentGenetic IntervalStart (Mb) End (Mb)LODPVE (%)Add
QYr.gaas-2BSE1, E3AX_109302306-
A_108894451		96.0102.82.6–3.95.0–8.46.1–8.0
QYr.gaas-2BLE1, E3, E4AX_111590697-
AX_110245106		672.3697.72.5–4.04.8–8.56.3–8.1
QYr.gaas-2DSE1, E2, E3AX_109080248-
AX_110028411		96.1102.93.6–3.97.5–8.66.5–8.3
QYr.gaas-2DLE1, E2, E3AX_109529695-
AX_109338734		596.0608.62.7–4.55.2–9.66.3–8.3
QYr.gaas-3BSE1, E3, E4AX-111732973-
AX-110097186		2.498.042.6–3.84.9–8.56.2–7.9
QYr.gaas-4BLE1, E2, E3AX-89396432-
AX-111732484		665.4667.93.9–5.68.6–12.07.5–10.2
Table 2. The candidate genes for RSA-related traits identified in the Doumai/Shi 4185 RIL population.
Table 2. The candidate genes for RSA-related traits identified in the Doumai/Shi 4185 RIL population.
QTLCandidate GeneStart (Mb)Annotation
QYr.gaas-2BSTraesCS2B02G13060097.9F-box family proteins
QYr.gaas-2BLTraesCS2B02G479500676.8Disease resistance protein family
QYr.gaas-2BLTraesCS2B02G487600683.7Disease resistance protein RGA2
QYr.gaas-2DSTraesCS2D02G15470098.3Serine/threonine-protein kinase
QYr.gaas-2DLTraesCS2D02G505900599.9Serine/threonine-protein kinase
QYr.gaas-3BSTraesCS3B02G0131006.06Glycosyltransferase
QYr.gaas-4BLTraesCS4B02G391600667.4F-box family protein
Table 3. Effects of four developed KASP markers on stripe rust resistance in the natural population.
Table 3. Effects of four developed KASP markers on stripe rust resistance in the natural population.
QTLGenotypeNumber of LinesMDS (%)p-Value
Kasp_2BS_YRTT3245.90.030 *
CC7538.0
Kasp_2BL_YRGG3143.90.039 *
CC7739.1
Kasp_2DS_YRGG6137.80.043 *
AA4944.2
Kasp_2DL_YRTT4843.70.022 *
CC6338.3
* indicate significant at p < 0.05.
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Yang, F.; Wang, Y.; Wu, L.; Guo, Y.; Liu, X.; Wang, H.; Zhang, X.; Ren, K.; Bai, B.; Zhan, Z.; et al. Genome-Wide Linkage Mapping of QTL for Adult-Plant Resistance to Stripe Rust in a Chinese Wheat Population Lantian 25 × Huixianhong. Plants 2025, 14, 2571. https://doi.org/10.3390/plants14162571

AMA Style

Yang F, Wang Y, Wu L, Guo Y, Liu X, Wang H, Zhang X, Ren K, Bai B, Zhan Z, et al. Genome-Wide Linkage Mapping of QTL for Adult-Plant Resistance to Stripe Rust in a Chinese Wheat Population Lantian 25 × Huixianhong. Plants. 2025; 14(16):2571. https://doi.org/10.3390/plants14162571

Chicago/Turabian Style

Yang, Fangping, Yamei Wang, Ling Wu, Ying Guo, Xiuyan Liu, Hongmei Wang, Xueting Zhang, Kaili Ren, Bin Bai, Zongbing Zhan, and et al. 2025. "Genome-Wide Linkage Mapping of QTL for Adult-Plant Resistance to Stripe Rust in a Chinese Wheat Population Lantian 25 × Huixianhong" Plants 14, no. 16: 2571. https://doi.org/10.3390/plants14162571

APA Style

Yang, F., Wang, Y., Wu, L., Guo, Y., Liu, X., Wang, H., Zhang, X., Ren, K., Bai, B., Zhan, Z., & Liu, J. (2025). Genome-Wide Linkage Mapping of QTL for Adult-Plant Resistance to Stripe Rust in a Chinese Wheat Population Lantian 25 × Huixianhong. Plants, 14(16), 2571. https://doi.org/10.3390/plants14162571

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