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Article

Mapping QTLs for Stripe Rust Resistance and Agronomic Traits in Chinese Winter Wheat Lantian 31 Using 15K SNP Array

by
Xin Li
1,†,
Wenjing Tan
1,†,
Junming Feng
1,†,
Qiong Yan
1,
Ran Tian
1,
Qilin Chen
1,
Qin Li
2,
Shengfu Zhong
3,
Suizhuang Yang
1,
Chongjing Xia
4,* and
Xinli Zhou
1,*
1
Wheat Research Institute, School of Life Sciences and Engineering, Southwest University of Science and Technology, Mianyang 621010, China
2
Department of Biology and Chemistry, Chongqing Industry and Trade Polytechnic, Fuling District, Chongqing 408000, China
3
Key Laboratory of Plant Genetics and Breeding at Sichuan Agricultural University of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
4
State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2025, 15(13), 1444; https://doi.org/10.3390/agriculture15131444
Submission received: 14 May 2025 / Revised: 26 June 2025 / Accepted: 1 July 2025 / Published: 4 July 2025
(This article belongs to the Section Crop Genetics, Genomics and Breeding)
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Abstract

Wheat stripe rust (Puccinia striiformis f. sp. tritici, Pst) resistance and agronomic traits are crucial determinants of wheat yield. Elucidating the quantitative trait loci (QTLs) associated with these essential traits can furnish valuable genetic resources for improving both the yield potential and disease resistance in wheat. Lantian 31 is an excellent Chinese winter wheat cultivar; multi-environment phenotyping across three ecological regions (2022–2024) confirmed stable adult-plant resistance (IT 1–2; DS < 30%) against predominant Chinese Pst races (CYR31–CYR34), alongside superior thousand-kernel weight (TKW) and kernel morphology. Here, we dissected the genetic architecture of these traits using a total of 234 recombinant inbred lines (RILs) derived from a cross between Lantian 31 and the susceptible cultivar Avocet S (AvS). Genotyping with a 15K SNP array, complemented by 660K SNP-derived KASP and SSR markers, identified four stable QTLs for stripe rust resistance (QYrlt.swust-1B, -1D, -2D, -6B) and eight QTLs governing plant height (PH), spike length (SL), and kernel traits. Notably, QYrlt.swust-1B (1BL; 29.9% phenotypic variance) likely represents the pleiotropic Yr29/Lr46 locus, while QYrlt.swust-1D (1DL; 22.9% variance) is the first reported APR locus on chromosome 1DL. A pleiotropic cluster on 1B (670.4–689.9 Mb) concurrently enhanced the TKW and the kernel width and area, demonstrating Lantian 31’s dual utility as a resistance and yield donor. The integrated genotyping pipeline—combining 15K SNP discovery, 660K SNP fine-mapping, and KASP validation—precisely delimited QYrlt.swust-1B to a 1.5 Mb interval, offering a cost-effective model for QTL resolution in common wheat. This work provides breeder-friendly markers and a genetic roadmap for pyramiding durable resistance and yield traits in wheat breeding programs.

1. Introduction

Wheat (Triticum aestivum L.), a cornerstone of global food security, provides approximately 20% of dietary calories and protein worldwide (http://www.fao.org/faostat/ accessed on 26 June 2025). Among biotic constraints, stripe rust, caused by the fungus Puccinia striiformis Westend. f. sp. tritici Erikss. (Pst), is one of the most economically devastating diseases in more than 60 countries [1,2]. Since its detection in Zimbabwe in 2018, its expanding geographic range has intensified threats to production, particularly in temperate regions [3], exemplifying the continued threat to wheat production worldwide. Yield losses average 5–10% annually but can exceed 70% in susceptible cultivars under early infection [4,5], causing more than USD 1 billion of economic losses annually [6].
While host resistance remains the most sustainable control strategy, the rapid evolution of Pst virulent races frequently overcomes major resistance genes (Yr genes) in commercial cultivars [7]. Consequently, fungicide dependency has risen globally, but excessive applications raise concerns about environmental toxicity [8,9] and selection for reduced fungicide sensitivity in Pst populations [10]. In China, where the disease epidemics devastate approximately 6 million hectares annually in high-risk provinces (Gansu, Shaanxi, Sichuan, and Yunnan), breeding cultivars with durable resistance is critical to reducing reliance on chemical controls [11].
Of the 87 formally named stripe rust resistance genes (Yr1–Yr87) in hexaploid wheat and its wild relatives [12], most confer all-stage resistance (ASR), which is often race-specific and vulnerable to pathogen evolution [13]. In contrast, adult-plant resistance (APR), though typically partial and polygenic, offers broader durability. Pyramiding APR genes (e.g., Yr12, Yr13) can confer near-complete resistance while mitigating selection pressure for virulent Pst lineages [14,15]. Some types of APR are referred to as high-temperature adult-plant (HTAP) resistance because their effectiveness increases at high temperatures (usually 25–30 °C) [16,17]. However, few APR/HTAP loci have been functionally validated in elite Chinese wheat germplasm, underscoring the need to characterize novel QTLs in regionally adapted wheat cultivars.
Modern wheat breeding faces the dual challenge of enhancing yield-related agronomic traits while maintaining durable disease resistance. Key quantitative traits including the grain weight, plant height, and spike architecture are governed by complex gene networks and exhibit significant genotype × environment (G × E) interactions [18,19]. Striking this balance is particularly critical in China, where stripe rust epidemics threaten 70% of wheat acreage, necessitating cultivars that harmonize resistance with regional adaptability.
Conventional polymerase chain reaction (PCR)-based molecular markers like randomly amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), and simple sequence repeat (SSR) have limited utility in wheat breeding owing to their low throughput and density [20]. The continuous progress in high-throughput single-nucleotide polymorphism (SNP) genotyping technologies, such as high-density SNP chips [21], provides the wheat community with a powerful tool for genetic and genomic studies and marker-assisted breeding. With the emergence of and continuous improvement in the wheat genome [22], many wheat SNPs have been developed and used for mapping the genes/QTLs of various wheat traits, especially for the study of wheat stripe rust resistance genes. For example, the Illumina Wheat 9K iSelect SNP array [23] was used to map wheat adult-plant stripe rust resistance genes Yr77, Yr78 [24], and Yr79 [25]. The Illumina Wheat 90K iSelect SNP genotyping array [21], developed under the leadership of Kansas State University, contains 81,587 SNP loci. This chip was successfully used for the fine localization of wheat rust resistance genes Lr52 and Yr47 [26] and the wheat stripe rust resistance genes Yr80 [27] and Yr61 [28]. The Wheat 660K SNP array [29] developed in China has been applied to the mapping of important trait genes related to wheat and detecting target genomic regions in wheat breeding. The Wheat 660K SNP array has been widely used to identify genetic loci for quality traits, agronomic traits, and disease resistance in common wheat [30,31]. The Wheat 15K SNP array containing 13,947 SNP markers (http://www.cgmb.com.cn/) was developed based on the Wheat 660K SNP array; it has already been successfully used in wheat preharvest sprouting (PHS) QTL mapping [32]. Wheat 55K SNP array markers were also selected from the Wheat 660K SNP array; it has been used in genetic mapping for stripe rust resistance [33,34,35] and agronomic trait [36] QTLs. Among these SNP arrays, the 15K SNP array is generally adequate and cost-effective for mapping traits of interest; even with the lower SNP density of the 15K SNP array, the fluorescence-based genotyping technology Kompetitive Allele-Specific PCR (KASP) marker can be used to convert an SNP into a simple robust marker [37].
Lantian 31, released in 2013 by the Wheat Research Institute of Gansu Academy of Agricultural Sciences, is a Chinese winter wheat cultivar that exhibits susceptibility to predominant Chinese Pst races (e.g., CYR32, CYR34) at the seedling stage but has demonstrated a high level of Pst resistance at the adult-plant stages over several field tests [38,39], with exceptional abiotic stress tolerance and superior agronomic performance, such as cold resistance, drought tolerance, large grains, and high thousand-grain weight. The objectives of the current study were to (1) identify and map the QTLs responsible for conferring stripe rust resistance in Lantian 31, (2) map QTLs associated with various agronomic traits in an RIL population derived from a cross between AvS (Avocet S) and Lantian 31, and (3) validate KASP markers flanking major-effect QTLs for accelerated introgression into elite breeding lines. Our work bridges the gap between genomic discovery and practical breeding by prioritizing loci that concurrently enhance rust resistance and yield potential.

2. Materials and Methods

2.1. Plant Materials

A recombinant inbred line (RIL) population comprising 234 F6 individuals was developed from a cross between the Australian spring wheat “Avocet S” (AvS; susceptible to Pst races CYR31–CYR34) and the Chinese winter wheat cultivar Lantian 31 (Long Bow/Lantian 10) in 2021. Lantian 31 was selected for its stable adult-plant resistance (APR) to predominant Chinese Pst races and superior agronomic performance in arid northwestern China [38]. The population was advanced using single-seed descent (SSD) [40], with all RILs and parents retained for phenotyping.

2.2. Greenhouse Resistance Phenotyping

The seedling and adult-plant stages of AvS and Lantian 31 were assessed for their reaction to Pst races CYR31, CYR32, CYR33, and CYR34 in a greenhouse. For the seedling tests, five seeds of each RIL and parent were sown in 50-well trays, whereas for the adult-plant tests, three plants were grown in pots of 20 cm diameter and 15 cm height. At the two-leaf stage for seedlings and the booting stage for adult plants, they were inoculated with a mixture of urediniospores and talc (at a ratio of approximately 1:20) for each race. Following the inoculation, the plants were placed in a dew chamber at 10 °C, in the dark, for a 24 h period and then transferred to a greenhouse with a day and night temperature of 22 °C and 18 °C and a photoperiod of 16hr and 8hr, respectively. Mingxian169, which is known to be susceptible to all Pst races in China, was used as a susceptible control. Infection types (ITs) were recorded using a 0–9 scale [41] when the susceptible control (Mingxian169) showed full sporulation for subsequent QTL analysis. DS was scored by measuring the percentage of the leaf area covered by stripe rust symptoms, with a scale of 0–100% according to the modified Cobb Scale [42].

2.3. Field Resistance and Agronomic Trait Evaluation

Lantian 31, AvS, and the 234 RILs were assessed for their response to naturally occurring stripe rust in field trials conducted in Mianyang (MY) in Sichuan Province from 2022 to 2024, Yangling (YL) in Shaanxi Province in 2023, and Guangyuan (GY) in Sichuan Province in 2024. The sowing and harvesting dates for these five environments are detailed in Table S1, along with corresponding weather conditions, which include the average annual temperature, annual rainfall, and annual average humidity. The trials followed a randomized complete block design with three replicates per site. Each RIL was planted in 1 m rows containing 20 to 30 seeds, with 25 cm spacing between rows. Spreader rows, consisting of two susceptible wheat cultivars (Mingxian169 and AvS), were planted every 20 rows to ensure uniform disease pressure.
Due to low natural inoculum, nurseries were inoculated at flag leaf emergence with a bulk urediniospore mixture collected from regional epidemics (2022–2023). The response to stripe rust was evaluated two times at each site for each replicate, using the IT and disease severity (DS) as indicators. The IT was recorded on a scale of 0 (resistant) to 9 (susceptible) [41]. The DS was scored on a scale of 0–100% according to the modified Cobb Scale [42]. Both the IT and DS data were used in the analysis.
Six agronomic traits were recorded in Mianyang from 2023 to 2024, Yangling in 2023, and Guangyuan in 2024: the plant height (PH), spike length (SL), thousand-kernel weight (TKW), kernel length (KL), kernel width (KW), and kernel area (KA). In each environment, five biological replicates were performed for each agronomic trait. The PH was measured at physiological maturity, from the stem base to the tip of the spikes, excluding the awns; three plants were randomly measured in each line. The SL was measured from a random sample of three spikes from the base of the ear to the tip, excluding the awns. One thousand kernels were counted from threshed grains and weighed to estimate the TKW. Subsequently, 100 seeds were selected per genotype to measure the KL, KW, and KA with WSeen’s SC-A1 automatic seed test and thousand-kernel weight.

2.4. Genetic and Statistical Analysis

Phenotypic data were analyzed using a mixed linear model in SAS 9.3 (SAS Institute Inc., Cary, NC, USA), treating genotypes as fixed effects and environments/replicates as random effects. Trait means were calculated across replicates and environments for downstream analysis. Parent comparisons on agrimony data were conducted by t-test; Pairwise Pearson correlations among agronomic and resistance traits were computed to identify pleiotropic relationships. IciMapping v4.2 was used to calculate the broad-sense heritability (h2) with the phenotype data of the RILs and two parents [43].

2.5. Genotyping and Linkage Map Construction

The genomic DNA of parents and RILs was extracted from fresh leaves of seedling plants at the jointing stage in the Mianyang field in 2021 using a modified cetyltrimethylammonium bromide method [44]. DNA samples were quantified using a NanoDrop ND-1000 spectrophotometer (Nanodrop Technologies, Wilmington, NC, USA). Stock DNA solutions were diluted to 50 ng/μL-1 for marker genotyping. The RIL population and parents were then genotyped with the wheat 15K single-nucleotide polymorphism (SNP) chips containing 13,947 SNP markers at China Golden Marker Biotech Co., Ltd. (http://www.cgmb.com.cn/, accessed on 26 June 2025) (Beijing, China).
To mitigate the impact of low-quality SNPs on the mapping results, the SNP data were processed as follows: (1) Low-quality markers with more than 20% missing values and missing or heterozygous in one or both parents were deleted. (2) Redundant markers were eliminated by the BIN function in QTL IciMapping version 4.2 [43]. Linkage maps were constructed using the MAP function in QTL IciMapping, and then the recombination frequency was converted to marker distance in centiMorgans (cM) according to the Kosambi function [45].
To validate the mapping of resistance QTLs, SSR markers were selected from the specific chromosomal regions where the resistance QTLs were mapped to identify those polymorphic between the parents. The polymorphic markers were used to genotype the RILs according to PCR and polyacrylamide electrophoresis methods, as previously reported [46]. The SSR primer sequences were from the GrainGenes website (https://wheat.pw.usda.gov/GG3/, accessed on 14 May 2025), and the primers were synthesized by Sangon Biotech Corporation (Shanghai, China). The 660K SNP array was also used to genotype parents; then, SNPs physically located near the QTLs between AvS and Lantian 31 were selected, and these SNPs were then converted to the KASP primers, and all of the KASP markers with polymorphisms were used to genotype the RILs at China Golden Marker corporation (Beijing, China).

2.6. QTL Analysis

The genotype data from the SNP array, SSR, and newly developed KASP were taken together for the final QTL analysis. Inclusive composite interval mapping (ICIM) [47] was used to search the QTLs of phenotypic traits from each environment using QTL IciMapping version 4.2 [43]. The initial QTL scan was conducted across all 21 chromosome linkage maps and associated traits using a threshold LOD score of 2.5 [35,48,49]. After preliminarily identifying the chromosomes containing potential QTLs, individual linkage maps of these chromosomes underwent 1000 permutation tests for each trait. This process aimed to determine the final LOD threshold for each trait with a Type I error rate of 0.05. If the final threshold was lower than 2.5, the threshold of 2.5 was retained. The refined LOD values for each trait were subsequently used for QTL screening to minimize the risk of false positives in the identified QTLs [50]. Furthermore, the step parameter was set to 1 cM, and the PIN parameter was set to 0.0001. QTL positions were determined by performing a blastn analysis of closely linked flanking markers on the IWGSC wheat refseq v1.0 genome. Final maps were visualized with QTL IciMapping and Adobe Illustrator 2025 (version 29.1.0).

3. Results

3.1. Phenotypic Evaluation of Parents and RILs

In the greenhouse tests, four races of Pst, namely CYR31, CYR32, CYR33, and CYR34, were used to assess the resistance level of AvS and Lantian 31 at the seedling and adult-plant stages. AvS exhibited high susceptibility with IT 8 to CRY31 and CRY32, IT 9 to CRY33 and CRY34 during the seedling stage, IT 9 to CRY31, and IT8 to CRY32, CRY33, and CRY34 during adult-plant tests in the greenhouse (Figure S1A,C). In contrast, Lantian 31 displayed resistance (IT 1) to CYR31 and CYR32 but was susceptible (IT 7) to CYR33 and CYR34 (Figure S1B) at the seedling stage. Furthermore, Lantian 31 demonstrated a high level of resistance (IT 1-2) to all tested races during the adult-plant tests (Figure S1D).
Across the five field environments (2022–2024), AvS was susceptible (IT 8-9), while Lantian 31 maintained stable resistance (IT 1-2). The severity of the disease ranged from 4.2% in Mianyang 2023 to 30% in Guangyuan 2024 for Lantian 31 (Table S2). In contrast, AvS had disease severity values ranging from 66.7% in Mianyang 2024 to 100% in both Mianyang 2022 and Mianyang 2023 (Table S2). The mean severity of stripe rust among the RILs varied from 25% in Yangling 2023 to 78.7% in Mianyang 2022 (Table S2). The distributions of the average infection types (ITs) and disease severity (DS) for the RILs were continuous (Figure 1), indicating the quantitative inheritance of resistance in Lantian 31. The broad-sense heritability (h2) was high for IT (0.87) and DS (0.84), underscoring the genetic basis of resistance (Table 1). The IT and DS were strongly correlated across environments (r = 0.41–0.96; p < 0.001) (Table S3).
The ANOVA revealed significant genetic variation (p < 0.001) among RILs in plant height (PH), spike length (SL), and kernel traits (TKW, KL, KW, KA), with h2 ranging from 0.91 to 0.96 (Table 2). In the field evaluation, Lantian 31 showed substantially higher TKW, KL, KW, and KA compared to AvS, indicating the greater grain production of Lantian 31 under Pst disease pressure (Figure 2 and Figure S2). The continuous trait distributions in RILs (Figure 3) supported polygenic control, with significant genotype × environment (G×E) interactions (p < 0.001) for all traits.

3.2. Linkage Map Construction

Genotyping with the 15K SNP array identified 4844 polymorphic markers between AvS and Lantian 31. After filtering, 1168 SNPs were removed owing to more than 10% missing data; the remaining 3676 SNPs fell into 2633 bins (1043 were redundant) that were used to construct a genetic linkage map. The final map spanned 8403 cM across all 21 chromosomes, covering a cumulative length of 8403 cM. The A, B, and D genomes accounted for 710 (27%), 1231 (46.8%), and 692 (26.2%) of the markers, respectively. These genomes encompassed lengths of 2755.02, 2215.5, and 3432.48 cM, with average marker intervals of 3.9, 1.8, and 4.9 cM, respectively.
To achieve the effective mapping of targeted QTLs, nine KASP markers designed from the QTL-linked SNPs were tested on the parental genotypes AvS and Lantian 31 (Figure S3). These markers were then applied to the entire AvS/Lantian 31 RIL population, allowing unambiguous genotype calling. Additionally, two previously mapped SSR markers on chromosome 6B were tested for polymorphism between the parents, and their chromosomal location across the entire RIL population was confirmed. In total, 2633 SNP markers, 9 KASP markers, and 2 SSR markers were used for the final linkage map construction. The primer sequences for the SSR and KASP markers can be found in Table S4.

3.3. QTL Analysis of Stripe Rust Resistance

A total of four QTLs were detected (Table 3) by the threshold LOD scores shown in Table S5, which were calculated by 1000 permutation tests with a Type I error rate of 0.05. The four QTLs were located on four different chromosomes. These loci, designated as QYrlt.swust-1B, QYrlt.swust-1D, QYrlt.swust-2D, and QYrlt.swust-6B, exhibited logarithm of odds (LOD) scores ranging from 2.57 to 23.85, collectively explaining 5.17–29.93% of infection type (IT) variance and 5.25–23.33% of disease severity (DS) variance.
The QTL QYrlt.swust-1B was located in a 1.97 cM interval spanned by KASP markers AX-111488534 and AX-109350463 on the long arm of chromosome 1B (Table 3; Figure 4A). This explained an average of 5.17–29.93% of the phenotypic variation in IT and 6.11–23.33% of the phenotypic variation in DS across environments. QYrlt.swust-1D was located in an interval of 18.4 cM and flanked by markers AX-111092902 and AX-94935157; this explained 6.5–17.44% of the variation in IT and 6.98–22.9% of the variation in DS (Table 3; Figure 4B). QYrlt.swust-2D was in the marker interval between AX-110876453 and AX-108909887 spanning 6 cM; it explained 6.18–11.60% of the variation in IT and 5.25–10.88% of the variation in DS (Table 3; Figure 4C). QTL QYrlt.swust-6B, which was represented by the two closest flanking markers AX-111732191 and AX-110442365 in an interval of 3 cM, explained 5.89–20.27% of the phenotypic variation in IT and 9.34–11.03% of the phenotypic variation in DS (Table 3; Figure 4D). The additive effects of all QTLs detected across all environments were negative, indicating that all four stripe rust resistance QTLs originated from the male parent, Lantian 31. No stripe rust resistance QTLs were detected in the maternal parent, AvS.

3.4. Combinational Effects of QTLs on Stripe Rust Resistance

To evaluate the additive effects of QTL combinations on stripe rust resistance, 234 RILs were categorized into 16 groups based on the presence/absence of markers linked to the four identified QTLs (Figure 5). RILs harboring a single QTL exhibited intermediate resistance, with significantly lower efficacy compared to lines carrying multiple QTL combinations. The mean IT and DS values demonstrated a progressive reduction in stripe rust infection as the number of QTLs increased (Figure 5). Lines with all four QTLs mirrored the resistance levels of the resistant parent, while lines lacking QTLs aligned with the susceptible parent. The resistance efficacy followed a hierarchical pattern, four-QTL combinations > three-QTL > two-QTL > single-QTL lines, confirming the additive contribution of these loci.

3.5. QTL Analysis of Agronomic Traits

Interval composite interval mapping (ICIM) identified eight QTLs associated with agronomic traits across environments (Table 4). At least one QTL was associated with each trait. A stable QTL for plant height (QPH.swust-4B) on chromosome 4B explained 32.83–41.32% of the phenotypic variance across all four environments. The spike length was influenced by a major QTL (QSL.swust-2D) on chromosome 2D (LOD: 7.9–14.7; phenotypic variance: 14.62–24.54%). The thousand-kernel weight (TKW) was governed by two QTLs: QTKW.swust-1B (6.00–15.34% variance) and QTKW.swust-4B (6.43–19.99% variance). The kernel length (QKL.swust-2D; 6.98–10.34% variance) and kernel width (chromosome 1B: QKW.swust-1B, 6.99–13.17%; chromosome 5A: QKW.swust-5A, ~7%) were also mapped. Notably, a 1.5 Mb region on chromosome 1B (670.4–689.9 Mb) harbored a QTL cluster associated with the TKW, kernel width, and kernel area (QKA.swust-1B; 5.81–11.92% variance), suggesting pleiotropic effects or tightly linked loci.

3.6. Analysis of Correlation Among Traits

Correlation coefficients (Table 5) revealed strong positive associations between the IT and DS (r = 0.94), the TKW and kernel area (r = 0.92), and the kernel width and area (r = 0.88). Stripe rust severity (IT/DS) was negatively correlated with the TKW, kernel length, and kernel width, indicating yield losses under high disease pressure. The plant height (PH) showed no significant association with the IT/DS but exhibited moderate correlations with the spike length and kernel length, width, and area (r = 0.36–0.47). The TKW, a critical yield component, was positively linked to kernel dimensions (r = 0.72–0.88), supporting its utility as a proxy for indirect selection in yield improvement.

4. Discussion

In this study, we focused on the source of stripe rust resistance in the wheat variety Lantian 31. Lantian 31 (Long Bow/Lantian 10) is a winter wheat variety developed in 2013 by the Gansu Academy of Agricultural Sciences using the pedigree method. It is resistant to stripe rust, cold, and drought and possesses excellent agronomy traits. Lantian 31 plays a significant role in the sustained control of stripe rust and wheat breeding in Longnan, Gansu, and the surrounding areas.
The identification of four additive QTLs (QYrlt.swust-1B, -1D, -2D, -6B) in Lantian 31 provides a genetic blueprint for its decade-long field resistance against evolving Puccinia striiformis f. sp. Tritici (Pst) populations in China. While seedling susceptibility to CYR33 and CYR34 suggests the absence of all-stage resistance (ASR) against these races, the robust adult-plant resistance (IT 1–2; DS < 30%) across all tested races underscores the cultivar’s reliance on adult-plant resistance (APR) mechanisms. This dichotomy aligns with the emerging model of “layered defense” in wheat, where APR complements residual ASR to delay pathogen adaptation [51].

4.1. QYrlt.swust-1BL Likely Corresponds to Yr29, Conferring APR

QTL QYrlt.swust-1B, located between 668.93 and 670.43 Mb on chromosome 1BL, coincides with the pleiotropic Yr29/Lr46 region [44], known for conferring APR to stripe rust and leaf rust [52,53]. Yr29 is flanked by its linked markers WMC44 and BAC17R [54], which are located at 662.2MB and 675.7MB, respectively, on Chinese Spring according to IWGSC refseq v1.0, which is the physical range covered by the QYrlt.swust-1B fragment. Despite the absence of reported Yr29 introgression in Lantian 31’s pedigree (Long Bow/Lantian 10), the shared physical interval and phenotypic effects—29.9% IT variance reduction—suggest allelic variation in or historical recombination of this locus. Allelic testing via comparative mutagenesis (e.g., CRISPR knockout of Lr46 homologs) or haplotype-specific KASP assays is warranted to resolve this.

4.2. QYrlt.swust-1D Is a Novel ASR Gene

QTL QYrlt.swust-1D was mapped between 470.73 and 483.46 Mb on the long arm region of chromosome 1D, flanking a physical region of 12.73 Mb. Given that the length of chromosome 1D in IWGSC wheat refseq v1.0 is 495.45 Mb, QYrlt.swust-1D is located very close to the distal end of the 1DL arm. To date, a total of ten QTLs have been reported on chromosome 1D, including QYr.sun-1D in synthetic hexaploid CPI133872 [55], QYr.caas-1DS in Naxos [56], QYrst.orr-1DS in Stephens [57], QYrdr.wgp-1DS in Druchamp [58], QYr.wpg-1D.1 [59], Qyr.ucw-1D [60], Yrcen in Centrum [61], Qyr.nwafu-1DS.1 [62], YrH122 [63], and Yr25 [64].
Out of the ten QTLs on chromosome 1D mentioned above, the first eight are located on the short arm of chromosome 1D. YrH122 was mapped on chromosome 1DL [63], flanked by SSR markers Xbrac229 and Xwmc339, with a total genetic distance of 12 cM. Using the flanking sequences of the molecular marker Xwmc339 linked to Yr122H and performing a blastn comparison with the IWGSC wheat refseq v1.0, it was found that Yr122H is located near 195.99 Mb on chromosome 1D. Given that the physical interval of the centromere on chromosome 1D is between 166.0 Mb and 174.6 Mb [65], although Yr122H is positioned on the 1DL arm, it is closer to the centromere. So, YrH122 was mapped differently from QYrlt.swust-1D due to its physical location. Yr25 is the only designated seedling resistance gene on chromosome 1D; its more detailed chromosomal location is unknown because Yr25 was assigned to chromosome 1D with Chinese Spring monosomic analysis [64]. Research showed that Yr25 is virulent to CRY32 [66], whereas a single gene line in our study, RIL-131, which carries only QYrlt.swust-1D, was highly resistant to CRY32 (IT: 2) in the seedling stage. QYrlt.swust-1D exhibited a high resistance level at the adult-plant stage only in the 2021YLIT and 2021YLDS environments, suggesting that its ASR is specific to CRY32.
In summary, QYrlt.swust-1D is a novel ASR gene, offering strong resistance to CRY32 but showing susceptibility to CRY34. Located at the distal end of chromosome 1DL, it benefits from a high recombination rate, facilitating its introgression into other wheat varieties. It is recommended to use this gene in combination with other resistance genes targeting different pathotypes, such as those conferring resistance to CRY34, through gene pyramiding to maximize its effectiveness.

4.3. QYrlt.swust-2D Is a Novel ASR Gene

QYrlt.swust-2D was mapped at 650.32–651.67 Mb on chromosome 2DL, flanking a physical region of 1.35 Mb. Given that the length of chromosome 2D in IWGSC wheat refseq v1.0 is 651.85 Mb, QYrlt.swust-2D is located very close to the distal end of the 2DL arm. Four formally designated genes are known stripe rust resistance genes/QTLs, Yr16, Yr37, Yr54, and Yr55, located on chromosome 2D. The previously reported QTLs for stripe rust on chromosome 2DL include a QTL from the Japanese cultivar Fukuho-komugi flanked by marker Xgwm349 [67]; QPst.jic-2D from the UK wheat cultivar Guardian [68]; QYr.niab-2D.1 (638.38 Mb) and QYr.niab-2D.2 (637.65–645.99 Mb) contributing to stripe rust adult-plant resistance identified in the UK winter wheat cultivar Claire [69]; Qyr.wpg-2D.2 flanked by marker IWA5211 at 638.15 Mb [59]; QPst.jic-2D from German winter wheat cultivar Alcedo flanked by marker gwm320 at 644.28 Mb [70]; QYr.cim-2DL.1 at 634.65 Mb; and QYr.cim-2DL.2 at 635.17 Mb [71]. Among these, QYr.niab-2D.2 and QPst.jic-2D from Alcedo are the closest (6.04 Mb) to QYrlt.swust-2D.
According to the different physical locations of other QTLs, there is a possibility that QYrlt.swust-2D may be a novel QTL. By using molecular markers linked to QYrlt.swust-2D, we identified a total of 17 RIL population lines containing only QYrlt.swust-2D. These lines exhibited an average resistance level of IT 2.4 to CRY32 at the seedling stage but were susceptible to CRY34, similar to the behavior of QYrlt.swust-1D, indicating that it is an ASR gene. Its location at the distal end of chromosome 2D facilitates its introgression into other wheat varieties through genetic recombination. In breeding programs, it is recommended to employ gene pyramiding, combining it with other resistance genes targeting different pathotypes for more effective breeding outcomes.

4.4. QYrlt.swust-6B Is an APR Gene

QYrlt.swust-6B was mapped at 77.46–78.57 Mb on the short arm of chromosome 6B and explained 5.89–20.27% of the variation in IT and 9.34–11.03% of the variation in DS. Five Yr genes are located on chromosome arm 6B, namely Yr4a, Yr4b, Yr35, Yr36, Yr78, and YrLM168a. According to the physical location of each gene, Yr35 is the nearest gene to QYrlt.swust-6B, which was located at 40.97–199.00 Mb determined by its flanking markers Xcfd1 and Xgwm191 [72]. Yr4a and Yr4b were reported on wheat chromosome 6B through monosomic analysis and conferred all-stage resistance [73]. Yr35 providing all-stage resistance, Yr36 conferring HTAP resistance, and YrLM168a conferring APR were located on chromosome 6BL [17,72,74,75]. Other stripe rust resistance QTLs have been mapped on chromosome 6BS as follows: QYr.caas-6BS.2 in the interval Xwmc104-XwPt-0259 [76], QYr.caas-6BS.3 in the interval Xwmc487-Xcfd13 [56], QYr.inra-6B flanked by SSR markers Xgwm518 and Xgwm608 [77], QYrst.wgp-6BS.2 flanked by SSR markers Xgwm132 and Xgdm113 [78], QYr.caas-6BS.1 in the interval Xwmc487-Xgwm768 [79], QYr.tam-6BS flanked by markers wPt3733-wPt4742 [80], and QYr.ufs-6B flanked by markers js14m69E-wPt7745 [81]. Among these QTLs, QYr.inra-6B coincided with QYrlt.swust-6B. Using the information obtained above, determining the novelty of QYrlt.swust-6B is not possible.
By using molecular markers linked to QYrlt.swust-6B, we identified a total of 12 RIL population lines containing only QYrlt.swust-6B. These lines exhibited an average resistance level of IT 6.3 to CRY32 and IT 6.7 to CRY 34 at the seedling stage, indicating that QYrlt.swust-6B confers adult-plant resistance to stripe rust.

4.5. Four QTLs Provide a High Level of Stripe Rust Resistance in Lantian 31

Different combinations of QTLs are expressed in different environments (Table 4), possibly due to the differing predominant races of stripe rust, variations in Pst virulence compositions, the quantity of natural Pst inoculum present, climate conditions, etc. The influence of environmental factors on QTL expression cannot be overlooked; even with all four QTLs expressed, the severity can vary greatly across environments, likely due to inoculum quantity. For instance, in Mianyang in 2022, despite the expression of all four QTLs, the average severity in the RIL population reached 78.7% (Table S1) due to high inoculum levels. Conversely, in Mianyang in 2023, with much lower inoculum levels, even the expression of just two QTLs resulted in better resistance (DS: 27.3%) (Table S1). Different virulence frequencies of Pst also impact stripe rust resistance. The virulence compositions in Mianyang and Yangling differ significantly due to their distinct ecological zones [82], affecting the expression of QYrlt.swust-1B and QYrlt.swust-6B in these regions. QYrlt.swust-1B was not expressed in 2023 in Mianyang, while QYrlt.swust-6B was not expressed in 2023 in Yangling.
The level of Lantian 31’s resistance to wheat stripe rust depends on the combination of different types of resistance genes. We identified two ASR (QYrlt.swust-1B, -6B) and APR (QYrlt.swust-1D, -2D) QTLs, which provide complementary effects in disease resistance across different environments. For example, due to the distinct ecological zones of Mianyang and Yangling, the virulence compositions differ significantly, leading to the unstable expression of the two APR genes. However, the stable expression of the two ASR genes compensates for the instability of the APR genes.
In summary, the identification of four additive QTLs (QYrlt.swust-1B, -1D, -2D, -6B) in Lantian 31 provides a genetic blueprint for its decade-long field resistance against evolving Puccinia striiformis f. sp. Tritici (Pst) populations in China. While seedling susceptibility to CYR33 and CYR34 suggests the absence of all-stage resistance (ASR) against these races, the robust adult-plant resistance (IT 1–2; DS < 30%) across all tested races underscores the cultivar’s reliance on adult-plant resistance (APR) mechanisms. This dichotomy aligns with the emerging model of “layered defense” in wheat, where APR complements residual ASR to delay pathogen adaptation [51].

4.6. QTLs for Agronomic Traits

PH and SL are important traits associated with wheat plant architecture and yield potential [83,84]. In this study, we identified one QTL associated with PH that was consistent across all four trials. QPH.swust-4B was mapped to the same region as QPh.cib-4B.1 [85] between the SNP markers AX-111497396 and AX-110928817 (21.94–36.01 Mb) on chromosome 4B. It is reported that Rht-B1b (Rht1) is located at 30.86 Mb on chromosome 4B [86]. In this study, QPH.swust-4B was located in the physical interval of 27.53–31.88 Mb, and the correlation between them needs to be further studied. One QTL designated as QSL.swust-2D was detected for SL, explaining from 14.62 to 24.54% of the phenotypic variance with a corresponding LOD of 7.87–14.73. Furthermore, QSL.swust-2D reduced wheat SL as the negative additive effect. Many QTLs have been reported on 2DS, including Qsl.sau.2D.1, Qsl.nwsuaf-2D, Qsl-2D, QSl.wa -2DS.e1, and qSL-2D.1 [87,88,89,90]. They are flanked with QSL.swust-2D detected in the current study.
Grain size is an important factor in increasing grain yield and providing space for grain filling [91]. QTL mapping in the current study revealed that three QTLs associated with grain size were located on chromosomes 1B, 2D, and 5A. Several QTLs for KL were identified distal from QKL.swust-2D [92,93,94,95]. No previous QTL for KL was identified in this genomic region of 2D. Whether QKL.swust-2D is a new QTL still needs to be verified through fine-mapping and gene cloning. QKW.swust-5A was considered preliminarily as a novel QTL, as no previous QTL was identified at this genomic region.
The TKW plays an important role in increasing wheat yield. In our study, QTLs for the TKW were mapped on chromosomes 1B and 4B. Previous studies have also found QTLs for the TKW on chromosome 4B. Among them, QTkwpk.cimmyt-4BL [96], QTgw.wa-4BL.e2 [97], TaGW4B [98], and QGw.nau-4B [99] were located on the long arm of chromosome 4B. Patil et al. (2013) identified one QTL associated with grain weight in the same region as QTKW.swust-4B [100].
The co-localization of TKW, KW, and KA QTLs on 1B underscores the potential for simultaneous improvement in multiple yield components via marker-assisted selection. However, the moderate phenotypic variances (5.81–15.34% PV) and inconsistent environment-specific effects (e.g., QTKW.swust-4B’s 6.43–19.99% PV) caution against overreliance on individual loci. Instead, pyramiding these QTLs with major-effect genes like Rht-B1 and Yr29 homologs could amplify their contributions while buffering against G×E interactions.

5. Conclusions

Our study dissected the genetic architecture of stripe rust resistance and agronomic excellence in the Chinese winter wheat cultivar Lantian 31, leveraging a recombinant inbred line (RIL) population and integrated genotyping–phenotyping strategies. Four stable QTLs (QYrlt.swust-1B, -1D, -2D, -6B) collectively underpin Lantian 31’s durable resistance to prevalent Chinese Pst races (CYR31–CYR34). Among these, QYrlt.swust-1D represents the first documented APR locus on chromosome 1DL, while QYrlt.swust-1B likely corresponds to the pleiotropic Yr29/Lr46 complex, suggesting its historical but uncharacterized introgression into Chinese germplasm. The methodological pipeline—combining 15K SNP chip-based QTL discovery, 660K SNP fine-mapping, and KASP marker validation—precisely delimited QYrlt.swust-1B to a 1.5 Mb interval, demonstrating a cost-effective framework for resolving complex traits in polyploid wheat.
Eight agronomic QTLs were identified, including a pleiotropic cluster on 1B (QTKW.swust-1B, QKW.swust-1B, QKA.swust-1B) that co-localizes with TaGW2-6B, a key regulator of kernel morphology. The negative correlation between stripe rust susceptibility (IT/DS) and thousand-kernel weight (r = −0.59 to −0.62) underscores the yield penalty imposed by disease, emphasizing the need for resistance pyramids to mitigate trade-offs.
The KASP markers developed here (e.g., AX-111488534 for QYrlt.swust-1B, AX-111092902 for QYrlt.swust-1D) provide breeder-friendly tools for gene tracking in gene pyramiding breeding, enabling the efficient introgression of these loci into elite genetic backgrounds. By bridging gene discovery with practical breeding methodologies, this work positions Lantian 31 as a genomic resource for developing climate-resilient wheat cultivars tailored to China’s evolving pathogen landscape.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/agriculture15131444/s1: Figure S1. Identification of resistance to stripe rust in greenhouse. (A) Seedling-stage stripe rust reactions of AvS. (B) Stripe rust reactions of Lantian 31. (C) Adult-plant-stage stripe rust reactions of AvS. (D) Adult-plant-stage stripe rust reactions of AvS. Figure S2. Agronomic traits of AvS and Lantian 31 under field evaluation. Significance was set at p ≤ 0.05 (*), p ≤ 0.01 (**), and p ≤ 0.001 (***); ns (non-significance) at p > 0.05. Figure S3: Kompetitive Allele-Specific PCR array in the validation population. Blue dots represent the Lantian 31-like genotypes, red dots represent the AvS-like genotypes, green dots represent the heterozygous genotypes, and black dots are water controls. Table S1. The sowing date, harvesting, and weather conditions for AvS/Lantian 31 RIL population growing environments. Table S2. Summary of disease severity in the AvS × Lantian 31 RIL population tested for stripe rust responses in Mianyang, Yangling, and Guangyuan from 2022 to 2024. Table S3. Pearson correlation coefficients (r) of infection type (IT) and disease severity (DS) for AvS/Lantian 31 RILs tested in different environments. Table S4. Primers of KASP and SSR markers. Table S5. The 1000 permutation tests result for a total of ten traits on each chromosome (columns 3 and 4) and QTL scan result for each trait on 4 wheat chromosomes (columns 5 and 6).

Author Contributions

Conceptualization, X.L. and X.Z.; methodology, X.L., X.Z. and C.X.; software, X.L., W.T. and J.F.; validation, W.T., J.F., Q.Y., R.T., Q.C., Q.L. and S.Y.; formal analysis, X.L., W.T. and J.F.; investigation, W.T., J.F., Q.Y., R.T. and Q.C.; resources, S.Y. and X.Z.; data curation, X.L., W.T., J.F., Q.Y., R.T., Q.C., Q.L., S.Z. and S.Y.; writing—original draft preparation, X.L., W.T. and J.F.; writing—review and editing, X.Z. and C.X.; visualization, X.L., W.T. and C.X.; supervision, Q.L., S.Z., X.Z. and C.X.; project administration, X.L., C.X. and X.Z.; funding acquisition, X.L., X.Z., Q.L., S.Z. and C.X. All authors reviewed the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the PhD Foundation of Southwest University of Science and Technology (No. 18zx7159, 19zx7116) and the National Natural Science Foundation of China (No. 32101707, 32101687), the Key Research and Development Program of International Science and Technology Innovation Cooperation of Science and Technology Department of Sichuan Province, China (No. 2022YFH0032), Breakthrough in Wheat Breeding Material and Method Innovation and New Variety Breeding (Breeding Research Project, 2021YFYZ0002), and the Research Program of Chongqing Municipal Education Commission of China (kJZD-K202103601, KJQN202203608).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed toward the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Frequency distribution of Avs/Lantian 31 recombinant inbred lines according to infection type (IT) and disease severity (DS) across five environments: MY22 (Mianyang 2022); MY23 (Mianyang 2023); YL23 (Yangling 2023); MY24 (Mianyang 2024); and GY24 (Guangyuan 2024). Mean values for parents AvS and Lantian 31 are indicated with arrows.
Figure 1. Frequency distribution of Avs/Lantian 31 recombinant inbred lines according to infection type (IT) and disease severity (DS) across five environments: MY22 (Mianyang 2022); MY23 (Mianyang 2023); YL23 (Yangling 2023); MY24 (Mianyang 2024); and GY24 (Guangyuan 2024). Mean values for parents AvS and Lantian 31 are indicated with arrows.
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Figure 2. Grain morphology of two parents (scale bar, 5 mm).
Figure 2. Grain morphology of two parents (scale bar, 5 mm).
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Figure 3. Frequency distribution of Avs/Lantian 31 recombinant inbred lines for plant height (PH), spike length (SL), thousand-kernel weight (TKW), kernel length (KL), kernel width (KW), and kernel area (KA) across four environments: 2023MY (Mianyang 2023); 2023YL (Yangling 2023); 2024MY (Mianyang 2024); and 2024GY (Guangyuan 2024). Mean values for parents AvS and Lantian 31 are indicated with arrows.
Figure 3. Frequency distribution of Avs/Lantian 31 recombinant inbred lines for plant height (PH), spike length (SL), thousand-kernel weight (TKW), kernel length (KL), kernel width (KW), and kernel area (KA) across four environments: 2023MY (Mianyang 2023); 2023YL (Yangling 2023); 2024MY (Mianyang 2024); and 2024GY (Guangyuan 2024). Mean values for parents AvS and Lantian 31 are indicated with arrows.
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Figure 4. Graphical display of QTL locations for stripe rust resistance across five environments. (A) Genetic linkage maps of QYrlt.swust-1B. (B) Genetic linkage maps of QYrlt.swust-1D. (C) Genetic linkage maps of QYrlt.swust-2D. (D) Genetic linkage maps of QYrlt.swust-6B. The QTL region on the genetic linkage maps is filled with red. The x-axis is the centiMorgans (cM) distance; the y-axis is the LOD score; KASP markers are highlighted in green; SSR markers are highlighted in purple; the dashed line on each line chart of the LOD score indicates the LOD threshold for QTL identification.
Figure 4. Graphical display of QTL locations for stripe rust resistance across five environments. (A) Genetic linkage maps of QYrlt.swust-1B. (B) Genetic linkage maps of QYrlt.swust-1D. (C) Genetic linkage maps of QYrlt.swust-2D. (D) Genetic linkage maps of QYrlt.swust-6B. The QTL region on the genetic linkage maps is filled with red. The x-axis is the centiMorgans (cM) distance; the y-axis is the LOD score; KASP markers are highlighted in green; SSR markers are highlighted in purple; the dashed line on each line chart of the LOD score indicates the LOD threshold for QTL identification.
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Figure 5. Effects of combining stripe rust resistance alleles at multiple QTLs. Boxplots of the distribution of disease severity in AvS/Lantian 31 recombinant inbred lines (RILs) in each of the five field trials. Based on the presence of resistance alleles at up to four of the most significant stripe resistance quantitative trait loci (QTLs): on chromosomes 1B (QYrlt.swust-1B), 1D (QYrlt.swust-1D), 2D (QYrlt.swust-2D), and 6B (QYrlt.swust-6B). The black lines without error bars in the subfigures indicate that the corresponding QTL combination has only one plant RIL.
Figure 5. Effects of combining stripe rust resistance alleles at multiple QTLs. Boxplots of the distribution of disease severity in AvS/Lantian 31 recombinant inbred lines (RILs) in each of the five field trials. Based on the presence of resistance alleles at up to four of the most significant stripe resistance quantitative trait loci (QTLs): on chromosomes 1B (QYrlt.swust-1B), 1D (QYrlt.swust-1D), 2D (QYrlt.swust-2D), and 6B (QYrlt.swust-6B). The black lines without error bars in the subfigures indicate that the corresponding QTL combination has only one plant RIL.
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Table 1. Analysis of variance (ANOVA) of infection type (IT) and disease severity (DS) for AvS × Lantian 31 RILs tested in Mianyang, Yangling, and Guangyuan in 2022–2024.
Table 1. Analysis of variance (ANOVA) of infection type (IT) and disease severity (DS) for AvS × Lantian 31 RILs tested in Mianyang, Yangling, and Guangyuan in 2022–2024.
Source of VariationIT 1DS 2
df 3Mean Square F Valuep ValuedfMean Square F Valuep Value
Lines23312.7515.30<0.0012331855.6518<0.001
Replicates524.7429.69<0.00152917.6428.31<0.001
Environments4914.421097.25<0.0014211,4442051.61<0.001
Lines × Environments9321.802.16<0.0019323493.39<0.001
Error11190.83 1119103.06
σg290.04 93.35
h20.87 0.84
1 IT, infection type; 2 DS, disease severity; 3 df, degrees of freedom; h2, broad-sense heritability; σg2, genetic variance.
Table 2. Analysis of variance of agronomic traits for 234 RILs from across four environments.
Table 2. Analysis of variance of agronomic traits for 234 RILs from across four environments.
Source of VariancedfSum of Squares
PHSLTKWKLKWKA
Lines233229,532.61 ***1246.26 ***48,926.96 ***205.44 ***89.45 ***7338.29 ***
Replicates44429.96 ***23.15 ***5148.67 ***1254.22 ***21.71 ***1861.02 ***
Environments313,799.23 ***68.06 ***9762.49 ***326.15 ***24.96 ***2267.98 ***
Lines× Environments69927,285.99 ***343.18 ***10,146.26 ***35.35 ***22.64 ***1559.23 ***
Error183825,244.54342.8414,569.9546.1628.892164.61
h2 0.960.910.920.940.920.92
*** Significant at p ≤ 0.001; df, degrees of freedom; TKW, thousand-kernel weight; PH, plant height; SL, spike length; KL, kernel length; KW, kernel width; KA, kernel area.
Table 3. Stripe rust resistance QTLs detected in the RIL population with infection type (IT) and disease severity (DS) under natural conditions of five environments in Mianyang in 2022 to 2024, Yangling in 2023, and Guangyuan in 2024.
Table 3. Stripe rust resistance QTLs detected in the RIL population with infection type (IT) and disease severity (DS) under natural conditions of five environments in Mianyang in 2022 to 2024, Yangling in 2023, and Guangyuan in 2024.
QTLEnvironmentMarker IntervalIT 1DS 2
LOD 3PVE 4Add 5LODPVEAdd
QYrlt.swust-1B2022MYKASP.AX-111488534
KASP.AX-109350463		18.2529.93−1.0813.4523.33−9.02
2023MY2.675.17−0.35---
2023YL6.3611.91−0.6110.0718.24−7.64
2024MY6.9512.9−0.447.5214.59−4.41
2024GY---2.936.11−4.04
QYrlt.swust-1D2022MYAX-111092902
AX-94935157		23.8517.44−1.7112.5922.90−9.73
2023MY3.696.76−0.45---
2023YL6.5811.37−1.026.6611.87−7.04
2024MY5.7810.94−0.424.528.58−3.44
2024GY3.436.50−0.333.726.98−4.26
QYrlt.swust-2D2022MYAX-110876453
AX-108909887		---2.695.25−4.72
2023MY6.5112.35−0.535.6310.69−7.22
2023YL6.2011.66−0.535.8710.88−6.08
2024GY---2.575.03−3.49
QYrlt.swust-6B2022MYAX-110442365
AX-111732191		9.7417.39−0.495.8911.00−6.77
2023MY6.6812.29−0.524.989.34−6.71
2023YL2.61 5.92 −0.34 ---
2024MY11.54 20.27−0.54 5.7711.03−4.47
2024GY3.05 5.89 −0.26 ---
1 IT, infection type; 2 DS, disease severity; 3 LOD, logarithm of odds; 4 PVE, percentage of the phenotypic variance explained by individual QTLs; 5 Add, additive effect of the resistance allele.
Table 4. QTLs for agronomic traits detected in RIL population under natural conditions in four environments.
Table 4. QTLs for agronomic traits detected in RIL population under natural conditions in four environments.
QTLEnvironmentMarker IntervalLOD 1PVE 2Add 3
QKL.swust-2D2023MYAX-110535834
AX-176645037		3.427.840.12
2023YL3.546.980.12
2024MY5.3910.340.13
2024GY4.408.730.12
QKW.swust-1B2023MYAX-109273019
AX-111481464		4.278.150.11
2024MY3.606.990.07
2024GY7.0913.170.09
QKW.swust-5A2024MYAX-108730664
AX-111215341		3.806.980.07
2024GY3.727.190.07
QKA.swust-1B2023MYAX-109273019
AX-111481464		4.087.770.87
2024MY3.045.810.56
2024GY6.4211.920.81
QPH.swust-4B2023MYAX-94434500
AX-109286577		22.6335.936.84
2023YL20.0032.836.65
2024MY27.1141.328.92
2024GY21.1034.086.43
QSL.swust-2D2023MYAX-109842248
AX-89728114		8.5215.23−0.39
2023YL7.8714.62−0.41
2024MY11.8020.56−0.47
2024GY14.7324.54−0.43
QTKW.swust-1B2023MYAX-109273019
AX-111481464		3.126.011.82
2024MY3.566.851.66
2024GY8.4615.352.38
QTKW.swust-4B2023MYAX-108992488
AX-111585045		3.296.431.87
2024MY11.1019.992.82
2024GY4.529.221.76
1 LOD, logarithm of odds; 2 PVE, percentage of the phenotypic variance explained by individual QTLs; 3 Add, additive effect of the resistance allele.
Table 5. Pearson correlation coefficients (r) of each agronomy trait for 234 AvS × Lantian 31 RILs.
Table 5. Pearson correlation coefficients (r) of each agronomy trait for 234 AvS × Lantian 31 RILs.
TraitITDSTKWPHSLKLKW
DS0.94 ***
TKW−0.48 ***−0.51 ***
PH0.02−0.030.49 ***
SL−0.18 **−0.18 **0.21 **0.36 ***
KL−0.37 ***−0.44 ***0.63 ***0.37 ***0.34 ***
KW−0.41 ***−0.42 ***0.88 ***0.42 ***0.080.40 ***
KA−0.47 ***−0.51 ***0.92 ***0.47 ***0.23 ***0.78 ***0.88 ***
** and *** represent significance at p ≤ 0.01 and p ≤ 0.001, respectively; IT, infection type; DS, disease severity; TKW, thousand-kernel weight; PH, plant height; SL, spike length; KL, kernel length; KW, kernel width; KA, kernel area.
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Li, X.; Tan, W.; Feng, J.; Yan, Q.; Tian, R.; Chen, Q.; Li, Q.; Zhong, S.; Yang, S.; Xia, C.; et al. Mapping QTLs for Stripe Rust Resistance and Agronomic Traits in Chinese Winter Wheat Lantian 31 Using 15K SNP Array. Agriculture 2025, 15, 1444. https://doi.org/10.3390/agriculture15131444

AMA Style

Li X, Tan W, Feng J, Yan Q, Tian R, Chen Q, Li Q, Zhong S, Yang S, Xia C, et al. Mapping QTLs for Stripe Rust Resistance and Agronomic Traits in Chinese Winter Wheat Lantian 31 Using 15K SNP Array. Agriculture. 2025; 15(13):1444. https://doi.org/10.3390/agriculture15131444

Chicago/Turabian Style

Li, Xin, Wenjing Tan, Junming Feng, Qiong Yan, Ran Tian, Qilin Chen, Qin Li, Shengfu Zhong, Suizhuang Yang, Chongjing Xia, and et al. 2025. "Mapping QTLs for Stripe Rust Resistance and Agronomic Traits in Chinese Winter Wheat Lantian 31 Using 15K SNP Array" Agriculture 15, no. 13: 1444. https://doi.org/10.3390/agriculture15131444

APA Style

Li, X., Tan, W., Feng, J., Yan, Q., Tian, R., Chen, Q., Li, Q., Zhong, S., Yang, S., Xia, C., & Zhou, X. (2025). Mapping QTLs for Stripe Rust Resistance and Agronomic Traits in Chinese Winter Wheat Lantian 31 Using 15K SNP Array. Agriculture, 15(13), 1444. https://doi.org/10.3390/agriculture15131444

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