Genetic analysis of a quantitative trait locus associated with resistance to the root-lesion nematode Pratylenchus neglectus in triticale

Genetic analysis of a quantitative trait locus associated with resistance to the root-lesion nematode Pratylenchus neglectus in triticale | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetic analysis of a quantitative trait locus associated with resistance to the root-lesion nematode Pratylenchus neglectus in triticale Gurminder Singh, Krishna Acharya, Bonventure Mumia, Siddant Ranabhat, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7585385/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jan, 2026 Read the published version in Theoretical and Applied Genetics → Version 1 posted 5 You are reading this latest preprint version Abstract Root-lesion nematode ( Pratylenchus neglectus , RLN) poses a significant threat to global wheat production. High levels of RLN resistance are rare in wheat. Triticale, an amphiploid generated by combining wheat and rye genomes that naturally carries rye-derived defense alleles, offers an untapped reservoir of nematode resistance. Here, we evaluated the response to RLN in 137 recombinant inbred lines (RILs) derived from a cross between two triticale cultivars: Siskiyou (susceptible) and Villax St. Jose (resistant). Genotyping-by-sequencing identified 1,054 high-quality single-nucleotide polymorphism (SNP) markers, which, along with seven simple sequence repeat (SSR) markers, were assembled into 21 linkage groups covering the triticale genome. A single quantitative trait locus (QTL) on the rye-derived chromosome 5R was identified that explained approximately 20% of the phenotypic variance across experiments. A high-throughput Kompetitive allele-specific PCR (KASP) assay based on the most significant SNP marker was developed, providing a rapid genotyping platform for selecting the resistance allele and reducing reliance on labor-intensive phenotyping for P. neglectus resistance in triticale. This study reports the first mapped RLN-resistance QTL in triticale, laying the fundamental foundation for introgressing the 5R resistance allele into wheat via marker-assisted selection combined with chromosome engineering, thereby broadening the genetic basis for nematode resistance in cereal crops. Pratylenchus neglectus QTL mapping resistance root-lesion nematode rye triticale and wheat Figures Figure 1 Figure 2 Figure 3 Figure 4 Key Message A QTL from rye chromosome 5R confers resistance to root-lesion nematode in triticale. Introduction Root-lesion nematodes (RLNs; Pratylenchus spp.) are migratory endoparasites that attack plant roots and are recognized as widespread pathogens of wheat and other small grains worldwide (Castillo and Vovlas 2007 ; Smiley and Nicol 2009 ). These nematodes invade and cause lesions in root tissues, impairing water and nutrient uptake, and can cause substantial yield losses in infested fields (Smiley 2021 ). In rainfed wheat-growing regions, P. neglectus has been reported to reduce grain yields by up to 30% in Australia and 37% in the United States (Vanstone et al. 2008 ; Smiley and Machado 2009 ). Along with P. thornei , P. neglectus is among the most prevalent RLN species in temperate cereal production zones (Smiley and Nicol 2009 ), posing a significant economic threat to global cereal production. Effective management of RLNs in the field is notoriously challenging (Vanstone et al. 2008 ; Dababat et al. 2016 ). Crop rotation with non-host or poor-host species can suppress nematode populations, but this strategy is constrained by the broad host range of RLNs and the need for profitable rotation crops (Smiley 2021 ). In many cereal-based production systems worldwide, common rotation crops such as barley, corn, soybean, and field pea can still serve as hosts for P. neglectus , thereby limiting the long-term efficacy of crop rotation as a control strategy (Vanstone et al. 2008 ; May et al. 2016 ; Thompson et al. 2016 ; Mokrini et al. 2019 ). Therefore, deploying host resistance is viewed as the most economical and sustainable approach for managing P. neglectus in cereal-based production systems (Smiley and Nicol 2009 ; Smiley 2021 ; Singh et al. 2023 ). Resistant cultivars can suppress nematode reproduction, reducing population densities to below economic injury level and mitigating damage over time (Cook and Evans 1987 ). Extensive phenotypic surveys have revealed that high-level resistance to P. neglectus is rare in bread wheat (Vanstone et al. 1998 ; Taylor et al. 1999 ; Mulki et al. 2013 ; Dababat et al. 2016 ; Singh et al. 2023 ). Most modern cultivars are susceptible hosts, and even tolerant lines permit substantial nematode multiplication, perpetuating soil inoculum (Thompson et al. 2016 ; Singh et al. 2023 ). Genetic analyses indicate that resistance in wheat is typically quantitative, controlled by multiple loci of small to moderate effect (Zwart et al. 2010 ; Dababat et al. 2016 ). To date, only one locus of major effect, Rlnn1 on chromosome 7AL, has been identified (Williams et al. 2002 ; Jayatilake et al. 2013 ). Although the Rlnn1 locus significantly reduces nematode multiplication, its deployment is complicated by linkage to the high-yellow pigment allele Psy-A1 , which is undesirable in bread-making wheat (Jayatilake et al. 2013 ). Additional quantitative trait loci (QTL) have been mapped on wheat chromosomes 1A, 2A, 2B, 4D, 5A, 6B, and 7D, but explained < 15% of the phenotypic variation (Mulki et al. 2013 ; Dababat et al. 2016 ; Thompson et al. 2017 ). Despite progress in QTL discovery, breeding uptake in wheat has been slow because: (i) extraction and microscopic counting of nematodes from soil and root samples based on morphological characteristics is laborious (Smiley 2021 ), and (ii) wheat has a complex polyploid genome and a scarcity of favorable alleles in elite gene pools, necessitating introgression from closely related or wild germplasm (Wen et al. 2018 ). Consequently, there is a critical need for the development of molecular markers linked to nematode resistance to facilitate marker-assisted selection and accelerate breeding efforts (Singh et al. 2023 ). Triticale (× Triticosecale Wittm., 2n = 6x = 42, AABBRR genomes), a synthetic hybrid generated by combining the genomes of wheat ( Triticum spp., AABB genomes) and rye ( Secale cereale L., RR genomes), represents a promising yet underexploited reservoir of nematode resistance for cereal improvement (Ayalew et al. 2018 ; Mergoum et al. 2019 ). In particular, rye is known for its broad resistance to various biotic and abiotic stresses, which triticale inherits to a large extent (Zeller and Hsam 1983 ; Mergoum et al. 2004 ; Saulescu et al. 2011 ). Breeders have long utilized triticale as a bridge to introgress valuable rye-derived traits, including resistance to pests and pathogens, into wheat germplasm (Friebe et al. 1996 ; Wang et al. 2023 ). Despite this potential, triticale remains a relatively underutilized cereal crop globally, grown on limited acreage and often overlooked in major wheat improvement programs (Mergoum et al. 2019 ). Several studies have demonstrated the potential of triticale as a source of resistance to RLNs. Farsi et al. ( 1995 ) reported that triticale cultivars (Abacus and Muir) had significantly fewer nematodes per gram of root and per plant compared to susceptible wheat cultivars. In Australian field trials, Vanstone et al. ( 1998 ) observed that triticale varieties harbored lower populations of P. neglectus than wheat, barley, and oats, indicating inherent resistance mechanisms. Taylor et al. ( 2001 ) confirmed that all triticale cultivars screened were resistant to P. neglectus , whereas resistance in wheat was limited. Our recent greenhouse experiments have further validated the resistance potential of triticale, with the cultivar Villax St. Jose consistently demonstrating significantly lower nematode reproduction than a panel of elite wheat cultivars and germplasm lines (Singh et al. 2023 ). Building on this observation, the present study utilizes the Siskiyou × Villax St. Jose (Wen et al. 2018 ) recombinant inbred line (RIL) population to (i) identify and map QTL associated with reduced nematode reproduction and (ii) convert tightly linked single-nucleotide polymorphisms (SNPs) into Kompetitive Allele-Specific PCR (KASP) assays. These assays constitute a rapid genotyping resource that can be further validated and integrated into triticale and wheat breeding pipelines aimed at enhancing RLN resistance. By filling a critical gap in our understanding of RLN resistance genetics in an under-utilized cereal, this work aims to broaden the genetic foundation for sustainable nematode management in cereal production. Materials and methods Nematode population collection, processing, and species confirmation Soil samples were collected from North Dakota wheat fields known to be infested with P. neglectus following a protocol previously described by Singh et al. ( 2023 ). In brief, sampling occurred during the cropping season or immediately after harvest of the crop. Using a standard soil probe (2.5 cm diameter and 30 cm depth), samples were taken in a zig-zag pattern across the fields, with approximately 25–30 soil cores per field. Samples were combined into a composite and transported to the Nematology Laboratory at North Dakota State University (NDSU), Fargo, ND. Ten subsamples of 200 grams (g) each were taken from the well-mixed composite soil for nematode extraction using the Whitehead tray method (Whitehead and Hemming 1965 ) to determine initial population densities. This technique relies on the active migration of nematodes from moist soil into water. Each subsample was filtered through a 250 µm aperture sieve, and nematodes were collected on a 20 µm sieve, which was then concentrated to 20–25 mL in a 50 mL vial (Capitol Vial Inc., Auburn, AL, USA). Nematodes were observed and identified to the genus level based on morphological features using a compound microscope (Zeiss Axiovert 25, Carl Zeiss Microscopy, NY, USA) and a Peters 1 mL gridded slide (Chalex Corporation, Portland, OR, USA). Molecular identification was performed by using P. neglectus -specific PCR primers as described in Yan et al. ( 2008 ). Rearing pure populations of P. neglectus Pure cultures of P. neglectus were generated and maintained in monoxenic carrot disc cultures following Lawn and Noel ( 1986 ) with minor modifications. Organically grown and fresh, unblemished carrots were washed, rinsed, and surface-sterilized in 10% bleach for 30 minutes in a laminar-flow hood. Using sterile instruments, carrots were peeled and sliced into 6–10 mm discs, placed in sterile Petri dishes, sealed, and incubated at 22°C in the dark. Discs were preconditioned for 1–2 weeks until calli formed. Individual nematodes were surface-sterilized in 0.01% streptomycin at 4°C overnight, selected under a dissecting microscope, and transferred to discs. The discs were placed in sterile Petri dishes (Thermo Fisher Scientific, Waltham, MA, USA), sealed with Parafilm, and incubated in the dark at 22°C. The carrot cultures were incubated in the dark at 22°C for up to six months, with weekly evaluations of carrot disc stability and nematode reproduction. Once the carrot discs reached six months or before decayed, nematodes were harvested. The discs were thinly sliced and soaked in distilled water in a Petri dish. After 3 to 4 hours, the water containing the nematodes was filtered through a 20 µm sieve, and the nematodes were collected in a 50 mL vial. The nematode suspension was refrigerated (~ 4°C) until use. To increase inoculum, pre-germinated seeds of the spring wheat cultivar Alpowa (susceptible to P. neglectus ; Smiley et al. 2014 ; Singh et al. 2023 ) were used. Plants were grown in plastic pots containing 1 kg of pasteurized sandy-loam soil (67% sand, 18% silt, 15% clay). The soil was prepared in-house by blending river sand with field soil, and its particle-size distribution was verified by a commercial laboratory (Agvise Laboratories, Northwood, ND, USA). One week after planting, nematodes harvested from carrot cultures were inoculated near the roots by pipetting the suspension into four small holes around each plant; holes were backfilled with moist soil. Pots were watered lightly immediately after inoculation to settle the inoculum, then maintained at moderate moisture for 48–72 hours to support nematode movement while avoiding leaching. Thereafter, pots were top watered (with low pressure) as needed to keep soil moisture consistent. Plants were grown for 14 weeks in the Jack Dalrymple Agricultural Research Complex, NDSU, Fargo, ND, USA at 22°C under a 16-hour photoperiod. Plant materials We used a triticale mapping population segregating for P. neglectus to map resistance loci (Singh et al. 2023 ). The population was derived from a cross between the susceptible triticale cultivar Siskiyou (L12G09) and the moderately resistant triticale accession Villax St. Jose (L12G18). Both parents are hexaploid (2 n = 6 x = 42, AABBRR) spring types. Siskiyou, developed collaboratively by the International Maize and Wheat Improvement Center in Mexico (CIMMYT) and the University of California, Davis, was released as a cultivar in California (Qualset et al. 1985 ). Villax St. Jose (PI 428848) is a Moroccan cultivar (Kuleung et al. 2006 ). The development of this mapping population was previously detailed by Wen et al. ( 2018 ). In this study, 137 F 6 RILs were screened for resistance to P. neglectus . The P. neglectus -susceptible wheat cultivar Alpowa, the resistant Iranian wheat landrace AUS28451, and unplanted inoculated and non-inoculated controls were used as control standards (Smiley and Machado 2009 ; Singh et al. 2023 ). Experimental design and assessment for P. neglectus resistance The phenotypic evaluations of the RIL population for resistance to P. neglectus were performed in two independent greenhouse experiments in 2020 and 2024 at the Jack Dalrymple Agricultural Research Complex, NDSU, Fargo, ND, USA. A single pre-germinated seed of each line was planted in a cone container filled with 150 g of pasteurized sandy loam soil (67% sand, 18% silt, and 15% clay; as described above) with approximately 2 g of ‘Osmocote Plus’ 15-19-12 fertilizer (Scotts Sierra Horticultural Product Company, Maysville, OH, USA). Within each experiment, five biological replicates were grown per RIL and control. Each cone container served as one experimental replicate. In total, we evaluated 141 lines per experiment (137 F 6 RILs, two parents [Siskiyou and Villax St. Jose], and two wheat checks [Alpowa and AUS28451]). In addition, two unplanted controls (inoculated and non-inoculated) were included, each with five replicates. The cone containers were placed in RL98 trays (Stuewe & Sons, Inc., Corvallis, OR, USA) and arranged in a completely randomized design. This design yielded 715 planted experimental units per experiment and 1,430 units across both experiments. Plants were maintained in the greenhouse for 14 weeks at an average temperature of 22°C with a 16-hour photoperiod. In both experiments, inoculum consisted of mixed life stages of P. neglectus (eggs, second-stage juveniles, and adults) pooled from two sources: monoxenic carrot-disc cultures and greenhouse-propagated populations maintained on susceptible wheat (cv. Alpowa) in pasteurized soil (described above). Seven days after planting, two 2 cm wells were made beside each seedling and inoculated with water suspensions of 300 ± 10 P. neglectus (eggs, J2, and adults) per cone for each experiment. Cone containers were top watered (with low pressure) as needed to keep soil moisture consistent for the first 7 days and then resumed carefully to avoid leaching of the nematodes. After 14 weeks, the entire root systems and the surrounding soil were harvested, stored at 4°C, thoroughly mixed, and processed on trays using the Whitehead tray extraction method (Whitehead and Hemming 1965 ; Singh et al. 2023 ). After 48 hours, nematodes were collected and counted under a compound microscope (Zeiss Axiovert 25, Carl Zeiss Microscopy, NY, USA) to determine the final (postharvest) population densities (Pf) of P. neglectus . Following the standardized phenotyping strategy proposed by Singh et al. ( 2023 ), Pf values were converted to relative values by normalizing against the susceptible check Alpowa within each experiment. When single experiments were analyzed, the numerator and denominator were the replicate means of Pf; in the combined analysis, they were the best linear unbiased predictors (BLUPs) described below. This standardization helps account for experiment-specific variability and allows consistent comparison across genotypes and runs. Relative Pf (%) was calculated as: $$\:Relative\:Pf\:or\:BLUPs=\frac{Pf\:\left(or\:BLUPs\right)\:from\:tested\:genotype\times\:100}{Pf\:\left(or\:BLUPs\right)\:from\:susceptible\:check\:Alpowa}$$ Phenotypic data analysis To determine whether data from the two greenhouse experiments could be analyzed together, the homogeneity of error variances with Levene’s test (PROC GLM, SAS 9.4, SAS Institute, Cary, NC, USA) was examined. First, variance among the five replicates of every RIL was examined within each experiment; no significant heterogeneity was detected ( P > 0.05). Second, genotype means were compared between experiments, and again Levene’s test revealed no variance differences ( P > 0.05). Because both within- and between-experiment variances were homogeneous, replicate values were averaged to give one phenotype per RIL per experiment. Genotype means from Experiments 1 and 2 were then correlated with Pearson’s r using ‘ cor.test ’ in R Studio v4.3.2 (R Core Team, 2024) to quantify stability of the trait across experiments. A two-way analysis of variance (ANOVA) was performed to quantify the effects of experiment, genotype and their interaction: $$\:{{Y}_{ijk}=\:\mu\:\:+{E}_{i}\:+{G}_{j}\:+{(G\times\:E)}_{ij}\:+\:Ɛ}_{ijk}$$ where Y ijk ​ is the relative Pf of the k th replicate of genotype j in experiment i ; µ is the overall mean; E i is the fixed effect of the i th experiment; G j ​ is the fixed effect of genotype j ; (G×E) ij ​ is the fixed interaction term; and Ɛ ijk ​ is the residual error. ANOVA revealed highly significant effects ( P < 0.0001) of experiment, genotype, and their interaction, indicating that genotypes responded differentially across years. Although the experiment effect influenced trait means, replicate variances remained homogeneous, validating subsequent mixed-model adjustment. To account for experimental effect and genotype × experiment (G×E) interaction, we calculated BLUPs for each RIL or genotype using a linear mixed model fitted in the lme4 package in R Studio v4.3.2: $$\:{{Y}_{ijkl}=\:\mu\:\:+{E}_{i}\:+{G}_{j}\:+{{(E\times\:R)}_{ik}+\:(G\times\:E)}_{ij}\:+\:Ɛ}_{ijkl}$$ where E i is a fixed effect (experiment), (E×R) ik ​ is replication nested within experiment, G j ​ is a random genotypic effect, and (G×E) ij ​ is a random genotype by experiment interaction. Parents and check cultivars were retained during model fitting to stabilize variance estimates but were excluded for downstream analysis. The resulting BLUPs provide experiment-adjusted, shrinkage-corrected estimates of genotypic performance and were used as phenotypic input in QTL analysis. Variance components from the mixed model were also used to compute broad-sense heritability ( H 2 ) on a line-mean basis, $$\:{H}^{2}\:=\:\frac{{\sigma\:}_{G}^{2}}{{\sigma\:}_{G}^{2}+\:\frac{{\sigma\:}_{GE}^{2}}{e}+\:\frac{{\sigma\:}_{\epsilon\:}^{2}}{re}}$$ where \(\:{\sigma\:}_{G}^{2}\) represents a genotypic variance, \(\:{\sigma\:}_{GE}^{2}\) ​ is a genotype × experiment interaction variance, \(\:{\sigma\:}_{\epsilon\:}^{2}\) is the residual variance, r is the number of replicates per experiment, and e represents the number of experiments. Genotyping-by-sequencing, SNP filtering, and linkage map construction Raw genotyping-by-sequencing (GBS) reads for RILs derived from the Siskiyou × Villax St. Jose cross, together with both parents, were retrieved from the NCBI Sequence Read Archive (SRA accession: SRR5821028). The data were then compared to two reference genomes. The first genome was an artificial triticale genome generated by combining the ‘A’ and ‘B’ genomes of the wheat landrace Chinese Spring (IWGSC CS v1.0) and the ‘R’ genome of the rye line Lo7 version 2 (Bauer et al. 2017 ). The first artificial triticale genome provides valuable context relative to established, well-curated, and gene-annotated reference genomes of wheat and rye. The second genome used a newly assembled genome of the triticale cultivar Siskiyou (unpublished, Dr. Zhaohui Liu). The second genome provides a more accurate analysis of genomic information in the context of a true triticale cultivar and one of the parental lines of the mapping population. The data for the artificial triticale genome were analyzed with the reference-free TASSEL UNEAK pipeline (Wen et al. 2018 ). The genome of Siskiyou was analyzed using the TASSEL 5.0 GBSv2 pipeline (Glaubitz et al. 2014 ). Barcode demultiplexing, tag generation, alignment to the reference genome using Bowtie2 (version 2.4.5), SNP discovery, and variant calling were performed within the TASSEL (version 5.2.96) GBSv2 command-line interface (Glaubitz et al. 2014 ). The resulting variant call file (VCF) was filtered using VCFtools (version 0.1.16) and TASSEL (version 5.2.96; Bradbury et al. 2007 ) software. SNPs were retained if they met the following criteria: (i) minor allele frequency (MAF) ≥ 0.35, (ii) missing data ≤ 50%, and (iii) heterozygosity ≤ 10%. Individuals with > 70% missing data were excluded, and any residual heterozygous genotype calls were converted to missing calls (Singh 2025 ). Co-segregating and redundant loci were removed to retain unique, high-confidence SNPs for linkage analysis. Linkage maps were constructed using MapDisto v2.1.7 (Heffelfinger et al. 2017 ), following the procedures described by Wen et al. ( 2018 ). Marker grouping was performed using the command with a logarithm of odds (LOD) threshold of 3.0 and a maximum recombination frequency ( R max ) of 30.0. The Kosambi mapping function (Kosambi 1944 ) was used to convert recombination frequencies into genetic distances. Within each linkage group, marker ordering and map refinement were done using , , , and commands as described by Wen et al. ( 2018 ) and Acharya et al. ( 2024 ). KASP marker development and QTL analysis SNP-containing GBS tags flanking the 5R QTL peak were converted into KASP assays with PolyMarker (Ramírez-González et al. 2015). PolyMarker facilitated the alignment of GBS tag sequences to Lo7 v2 genomic assembly, resulting in the generation of two allele-specific primers and one common primer for each assay. Primer candidates were screened in silico against both the Lo7 and Weining rye genomes (Rabanus-Wallace et al. 2021 ; Li et al. 2021 ) to confirm their single-copy specificity. For tags that failed PolyMarker’s design criteria, primers were manually redesigned using Primer3 (Seneviratne et al. 2024 ; Running et al. 2025 ), again anchored to orthologous regions in the Lo7 and Weining genomic assemblies. All primer pairs were remapped to the triticale genome of Siskiyou to confirm their unique placement and correct orientation. The results showed complete concordance with the rye-based designs. The resulting KASP assays were evaluated in the parental lines and the RIL population, and then incorporated into the chromosome 5R linkage map for the final QTL analysis. To compare nematode reproduction between allelic classes at diagnostic markers, Welch’s t -tests were performed on relative Pf or BLUP values using the function ‘ scipy.stats.ttest_ind ’ (SciPy v1.11.4 in Python), with unequal variances assumed ( equal_var = False ) for each experiment and for the combined dataset. QTL mapping was performed in QGene v4.3.10 (Joehanes and Nelson 2008 ) using default parameters, with the scanning interval set to 10 (equivalent to a 1.0 cM step size) to enable high-resolution detection of QTL across the linkage map (Singh 2025 ). The single-trait multiple interval mapping (STMIM) function was used to identify QTLs significantly associated with P. neglectus resistance. Phenotypic inputs were relative Pf (%) for the single-experiment analyses and relative BLUPs (%) for the combined analysis. A permutation test consisting of 1,000 iterations was used to determine a LOD threshold for STMIM at a significance level of 0.05. The coefficient of determination ( R 2 ) was used to estimate the phenotypic variation that the identified QTL explained. Results Reactions of triticale parents and RILs to P. neglectus The phenotypic assay confirmed the expected reaction classes of the reference genotypes: AUS28451 exhibited a highly resistant response (relative Pf = 8.8%), Alpowa was susceptible (100.0%), Villax St. Jose was moderately resistant (29.7%), and Siskiyou was susceptible (80.3%) (Table 1 ). Among the 137 RILs, relative Pf ranged from 2.7 to 113.4% in Experiment 1 and 2.9 to 109.8% in Experiment 2, with population means of 47.0% and 42.7%, respectively (Supplementary Table S1 ). Environment-adjusted BLUPs, integrating both experiments, ranged from 7.5 to 93.4% with a mean of 46%. The distribution of relative Pf or BLUP values approximated a normal distribution, with transgressive segregants observed on both tails of the curve (Fig. 1 ). Genotype performance was strongly conserved across years ( r = 0.796, P < 0.001), and the mixed-model analysis yielded a broad-sense heritability ( H 2 ) of 0.903. Table 1 The response of parental lines and RIL to Pratylenchus neglectus in the Siskiyou × Villax St. Jose triticale population Category Descriptor x Exp-1 (%) y Exp-2 (%) y Combined (%) z Reaction of parental lines Siskiyou (Susceptible) 85.00 75.62 80.27 Villax St. Jose (Resistant) 29.14 30.74 29.72 Reaction of recombinant inbred lines (RILs) Minimum value 5.46 3.42 7.53 Maximum value 105.79 107.45 93.43 Mean value 46.98 42.37 43.93 x RIL statistics summarize RILs; each entry (parents, checks, and RILs) had five biological replicates per experiment. y Exp = Experiment. Experiment-1 and Experiment-2 were independent greenhouse assays conducted at the Jack Dalrymple Agricultural Research Complex, North Dakota State University (Fargo, ND, USA) in 2020 and 2024, respectively. Exp-1 (%) and Exp-2 (%) are Relative Pf (%), calculated within each experiment as: 100 × [Pf of the genotype] / [Pf of Alpowa]. Pf is the postharvest P. neglectus population densities. z Combined (%) are relative BLUPs from a linear mixed model across both experiments: Relative BLUP (%) = 100 × [genotype BLUP] / [Alpowa BLUP]. The model used genotype as a random effect, experiment as a fixed effect, and replicate nested within experiment as a random term. Linkage map construction Re-analysis of the raw fastq files originally reported by Wen et al. ( 2018 ) generated 120.5 million reads, which, after alignment to the Siskiyou reference genome, yielded 1.04 million unique 64-bp tags. SNP discovery identified 118,903 biallelic sites. Sequential filtering for genotype call-rate (≥ 50%), minor-allele frequency (≥ 0.35), and residual heterozygosity (≤ 10%) (5,750 polymorphic SNPs; Supplementary Table S2 ), followed by the removal of redundant or co-segregating loci, yielded 1,054 non-redundant, high-confidence SNPs (Supplementary Table S3). These SNPs, together with seven chromosome-5R SSRs, provided 1,061 markers for linkage analysis. The marker set resolved into the expected 21 linkage groups, comprising 14 wheat (AA and BB genomes) and 7 rye (RR genome), which spanned 2,745.9 cM (Supplementary Figure S1 ). The composite map contained 1,111.7 cM in the AA genome, 915.4 cM in the BB genome, and 718.9 cM in the RR genome, resulting in a genome-wide mean spacing of 2.58 cM per marker (Table 2 ). Individual linkage groups ranged from 80.6 cM (2R) to 213.2 cM (7A). Marker density varied from 2.13 cM/marker (5R) to 3.80 cM/marker (5A). Table 2 Summary of genetic linkage map constructed from the Siskiyou × Villax St. Jose triticale RIL population w Chromosome Markers mapped x Genetic distance (cM) y Marker density (cM/marker) z 1A 43 116.85 2.72 1B 58 155.09 2.67 1R 36 83.57 2.32 2A 54 148.57 2.75 2B 58 149.34 2.57 2R 31 80.63 2.60 3A 85 183.90 2.16 3B 69 180.52 2.62 3R 51 108.53 2.13 4A 62 187.78 3.03 4B 35 85.99 2.46 4R 66 143.26 2.17 5A 38 144.53 3.80 5B 59 146.97 2.49 5R 54 114.94 2.13 6A 33 116.87 3.54 6B 38 91.23 2.40 6R 36 94.31 2.62 7A 81 213.17 2.63 7B 37 106.25 2.87 7R 37 93.65 2.53 A-genome 396 1,111.67 2.81 B-genome 354 915.39 2.59 R-genome 311 718.89 2.31 Total 1,061 2,745.95 2.58 w Genetic linkage map was constructed from 137 F 6 recombinant inbred lines (RILs) derived from Siskiyou × Villax St. Jose. x Number of mapped, non-redundant markers at unique positions per chromosome. y Total map length per chromosome, computed as the sum of intervals between adjacent markers after ordering; intervals were derived from recombination fractions and converted to cM using the Kosambi mapping function used in this study. z Marker density (cM/marker) is the average spacing between mapped markers on a chromosome. It is calculated as the total genetic distance divided by the number of mapped, non-redundant markers at unique positions. Smaller values indicate denser coverage and finer mapping resolution. QTL identification on chromosome 5R A genome-wide scan with STMIM detected a single locus exceeding the 5% experiment-wise permutation threshold (LOD = 3.2) (Fig. 2 ). The peak occurred at 11 cM with a LOD of 6.5 and a generalized R 2 of 0.196 in the combined analysis. Adjacent positions 9–12 cM also surpassed the threshold (LOD ≥ 6.3), delimiting a 4 cM interval that accounted for ~ 20% of the phenotypic variance in BLUPs and ~ 16–17% in the individual experiment means. No additional significant loci were detected elsewhere in the genome, indicating that a single, moderate-effect QTL largely conditions resistance in this population on 5R, hereafter designated as QRln.ndsu-5R . KASP marker associated with QRln.ndsu-5R Of the five chromosome-5R SNPs converted to KASP assays (Table 3 ), fcp1070 (derived from GBS tag TP4673 ) is the most informative for P. neglectus resistance. This marker lies only ~ 3 cM from the maximum-LOD position of QRln.ndsu-5R and falls well inside the 4 cM interval defined by a one-LOD drop from the peak. Genotyping all 137 RILs and both parents produced unambiguous biallelic clusters (Fig. 3 ). Lines that possessed the Villax St. Jose allele exhibited a mean relative BLUP of 35.5%, whereas lines with the Siskiyou allele averaged 53.0%. The difference in nematode reproduction was highly significant (Welch’s t -statistic = -4.18, P = 6.7 × 10⁻ 5 ) (Fig. 4 ). A similar separation between genotype classes was also observed when the two greenhouse experiments were analyzed separately, confirming the stability of the marker effect across environments. Table 3 Kompetitive Allele Specific PCR (KASP) markers mapped to chromosome 5R in the Siskiyou × Villax St. Jose triticale recombinant inbred line population. KASP marker w SNP x Primer names Primer sequences (5’→3’) y Physical position (Mbp) z fcp1072 fcp1072 -FAM gaaggtgaccaagttcatgctTGCTGCAGATTCATGAAGTGG A/G fcp1072 -HEX gaaggtcggagtcaacggattTGCTGCAGATTCATGAAGTG A 20,200,087 fcp1072 -Com GTTGGTTCTCTGTCCTCTGTATCC fcp1070 fcp1070 -FAM gaaggtgaccaagttcatgctGATTGGGTGCGTGTGACAT C C/G fcp1070 -HEX gaaggtcggagtcaacggattGATTGGGTGCGTGTGACATG 26,708,526 fcp1070 -Com CCCACCATGTGCCAAAATAATTC fcp1071 fcp1071 -FAM gaaggtgaccaagttcatgctGCCTGGACGCCTATTTATCC A A/G fcp1071 -HEX gaaggtcggagtcaacggattGCCTGGACGCCTATTTATCCG 365,423,142 fcp1071 -Com GGTTTCTTTGGTGCTGCAGAT fcp1075 fcp1075 -FAM gaaggtgaccaagttcatgctAAGGTTGTCTGCAGCTCTC T C/T fcp1075 -HEX gaaggtcggagtcaacggattAAGGTTGTCTGCAGCTCTCC 561,038,158 fcp1075 -Com CCTATGGGAGTCTTGGCGAC fcp1073 fcp1073 -FAM gaaggtgaccaagttcatgctGTCAACGTCTCTGCAGCCT A/T fcp1073 -HEX gaaggtcggagtcaacggattGTCAACGTCTCTGCAGCC A 739,373,203 fcp1073 -Com AGCTCTGCTGAAACCCGAATAT w KASP = Kompetitive allele specific PCR, a fluorescence-based genotyping method using two allele-specific forward primers (labeled with FAM or HEX tails) and one common reverse primer. x SNP = single nucleotide polymorphism. The variant base is shown for each marker. y Primer sequences are shown in the 5′→3′ direction. Lowercase letters at the beginning of FAM- and HEX-labeled forward primers represent the standard tail sequences recommended by the KASP chemistry for fluorophore binding; uppercase letters represent the locus-specific portion of the primer sequence. z Physical positions (in megabase pairs, Mbp) are based on the Siskiyou triticale reference genome assembly. Discussion RLNs continue to impose substantial yield penalties in rainfed cereals because nematicides are expensive and environmentally concerning, and crop rotation is unreliable since P. neglectus can survive on a wide range of hosts (Smiley 2021 ). Therefore, genetic resistance remains the most durable defense strategy (Singh et al. 2023 ). After decades of screening, wheat breeding still relies on a single major locus ( Rlnn1 ) along with a few small-effect QTLs, which together leave significant nematode populations in the soil (Williams et al. 2002 ; Zwart et al. 2010 ; Mulki et al. 2013 ; Dababat et al. 2016 ). Rye ( S. cereale ) is well known for broad disease resistance, and its amphiploid derivative, triticale (AABBRR genome), offers a practical bridge for deploying rye alleles into wheat (Wen et al. 2018 ). To our knowledge, no RLN resistance locus has been genetically mapped in rye or triticale. In this study, we identified QRln.ndsu-5R on chromosome 5R, which helped address this gap and provided genetic evidence from a rye-derived resistance source for cereal improvement. Although QRln.ndsu-5R explained about 20% of the phenotypic variance, the near-normal distribution of the phenotypic data, together with transgressive RILs that exceeded both parents, indicated that additional loci likely contributed to resistance. Such transgression is consistent with complementary small-effect alleles from both parents. We used the existing Siskiyou × Villax St. Jose population, which contains 137 F 6 RILs as previously described (Wen et al. 2018 ). RLN phenotyping is very labor- and space-intensive in that each line required five biological replicates and a 14-week greenhouse cycle in containment conditions, which constrained the feasibility of increasing the number of lines in this study. This design provided stable Pf estimates but offered limited power to detect very small-effect loci, so some modifiers may have remained below the detection threshold. The consistent signal on chromosome 5R across experiments supports a major locus with additional small-effect contributors. In the future, expanding population size, increasing marker density around 5R, and evaluating across additional environments will help resolve minor-effect loci and test for possible epistasis with QRln.ndsu-5R . Screening for nematode resistance is laborious, time-consuming, and expensive, which is the major constraint in nematode resistance breeding (Smiley 2021 ). Depending upon the availability of resources, a single screening experiment may require 5–6 months to generate phenotypic data (Singh 2020). Thus, genotypic selection using molecular markers can be a valuable alternative to the lengthy and labor-intensive process of resistance phenotyping (Singh et al. 2023 ). The KASP markers we have developed can serve as valuable tools for monitoring the introgression of resistance QTL in P. neglectus. Genotyping with fcp1070 partitioned the 137 RILs into two allelic classes, whose mean nematode multiplications differed by ~ 33% ( P < 0.001), closely matching the variance attributed to QRln.ndsu-5R . Genotypic analysis, in conjunction with phenotypic screenings for resistance to P. neglectus in greenhouse environments, is expected to facilitate the development of germplasm exhibiting nematode resistance. Further fine-mapping and cloning of this QTL can help in developing robust diagnostic markers for marker-assisted selection in breeding programs (Singh 2025 ) and gaining a deeper understanding of the genetic mechanisms underlying nematode resistance. The physical interval defining QRln.ndsu-5R spans ~ 10 Mbp (20.20 Mbp to 30.96 Mbp) on the triticale (Siskiyou) reference genome. It contains 140 high-confidence genes (unpublished, Dr. Zhaohui Liu), which include three nucleotide-binding leucine-rich repeat (NLR)-type resistance-gene analogues and two coiled-coil receptor-like protein kinases (CC-RLKs). Similar gene groups have been repeatedly implicated in nematode resistance loci across various crops, including cereals. In wheat, for example, the Rlnn1 region on 7AL and the fine-mapped QRlnt intervals on 6D and 2B each harbor NLR or kinase clusters (Rahman et al. 2020 ). Major cyst-nematode genes such as Cre1 and Cre3 likewise reside in NLR-rich blocks on wheat group-2 chromosomes, and the principal P. thornei QTL on barley 7H contains two defense-related RLKs that are constitutively expressed in resistant lines (Mather et al. 2024 ). Beyond cereals, single-gene resistances such as tomato Mi-1 (for root-knot nematodes), potato Gpa2 (potato cyst nematode), and the Arabidopsis pattern-recognition receptor NILR1 all encode NLRs or RLKs, underscoring the functional relevance of these classes against endoparasitic nematodes (Vos et al. 1998 ; Qi et al. 2022 ; Mendy et al. 2017 ). Taken together, the recurrence of NLRs and kinase-type genes in independent nematode QTLs strongly suggests that these genes in the 5R interval could be potential candidates determining P. neglectus resistance. Rye chromatin has repeatedly lifted wheat disease resistance to new plateaus; for example, the 1RS.1BL/1AL translocations carrying Lr26 (leaf rust), Sr31 (stem rust), Pm8 (powdery mildew), and Yr9 (yellow rust) are now present in > 1,000 cultivars worldwide (Schlegel 2023 ; Wang et al. 2023 ). Moreover, the rye gene CreR on chromosome 6R has been introgressed to combat cereal cyst nematodes (Dundas et al. 2001 ). Meanwhile, a 5R segment harboring Xct1 confers dominant resistance to bacterial leaf streak in triticale and could also be transferred into bread wheat via ph1b -mediated homoeologous recombination (Wen et al. 2018 ). QRln.ndsu-5R , therefore, joins a growing list of rye-derived factors that tackle otherwise recalcitrant threats in wheat. Because QRln.ndsu-5R lies within a modest ~ 10-Mb interval, there is a realistic prospect of moving only a minimal rye fragment, mitigating the linkage drag that has occasionally accompanied larger translocations such as 1RS (Wang et al. 2023 ). Marker-assisted backcrossing with fcp1070 , followed by targeted recombination in ph1b or CRISPR-enabled chromosome-engineering backgrounds, should enable precise introgression and subsequent trimming of unwanted rye DNA. If, as our preliminary data indicate, the 5R segment also retains proximity to Xct1 (data not shown), breeders could co-deploy nematode and bacterial resistance in a single introgression. In a broader context, this work exemplifies how strategic mining of the wheat secondary gene pool, coupled with contemporary genomics, can diversify the resistance landscape beyond the narrow set of loci currently available in bread wheat. In conclusion, we identified and mapped a novel QTL, QRln.ndsu-5R , associated with resistance to P. neglectus in triticale. To our knowledge, no RLN-resistance locus had previously been mapped in this crop. The tightly linked KASP assay we provided should enable efficient marker-assisted introgression of the 5R resistance allele into triticale and wheat breeding programs, thereby reducing the time and cost associated with phenotypic screening of nematodes. By incorporating rye-derived defense genetics into the cereal improvement pipeline, these results expand the allelic repertoire available for nematode control and contribute to the development of more resilient cultivars. Declarations Competing interests The authors have no relevant financial or non-financial interests to disclose. Ethics approval NA Consent to participate NA Consent to publish NA Author contribution statement GS and GY conceived and designed the experiments; GS, KA, BM, SR, and EO conducted the experiments and collected the data; GS, KA, and GY analyzed and interpreted the data; GY, JF, XL, SW, HSC, and ZL provided resources, materials, and analysis tools; GS drafted the manuscript; GS, KA, BM, SR, EO, JS, UG, SW, HSC, XL, JF, ZL, and GY revised the manuscript. All authors read and approved the final version of the manuscript. Acknowledgements The authors would like to thank Jason Fielder, Santosh Gudi, and Addison Plaisance for their technical assistance. We also appreciate the computational assistance provided by the Center for Computationally Assisted Science and Technology (CCAST) at North Dakota State University, Fargo, ND, USA. 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Mol Breed 26:107–124. https://doi.org/10.1007/s11032-009-9381-9 Supplementary Files RLNSinghetalFigureS1TriticalegeneticmapvS9825.pdf RLNSinghetalSupplementaryTablesvS9825.xlsx Cite Share Download PDF Status: Published Journal Publication published 05 Jan, 2026 Read the published version in Theoretical and Applied Genetics → Version 1 posted Editorial decision: Minor revisions 21 Oct, 2025 Reviewers agreed at journal 29 Sep, 2025 Reviewers invited by journal 13 Sep, 2025 Editor assigned by journal 11 Sep, 2025 First submitted to journal 10 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Agriculture","correspondingAuthor":false,"prefix":"","firstName":"Justin","middleName":"","lastName":"Faris","suffix":""},{"id":514644175,"identity":"23ec76dd-7246-4a7c-8cbc-6b8aadb2be7a","order_by":11,"name":"Zhaohui Liu","email":"","orcid":"","institution":"North Dakota State University","correspondingAuthor":false,"prefix":"","firstName":"Zhaohui","middleName":"","lastName":"Liu","suffix":""},{"id":514644176,"identity":"4fb9bb8d-5994-4ba7-913b-fe050a868f96","order_by":12,"name":"Guiping Yan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5UlEQVRIiWNgGAWjYFACxgaGBCjrAQMbmGFAtBZmAyK1IACbBFFa5COS2x483FHLYHD87LHqgrK6xAb25m0S+LQY3khsN0g8c5zB4Exe2u0Z5w4nNvAcK8OvZUZim0Ri2zEGgwM5Zrd52w4kNkjkmBGp5fwbs2LeNqDD5N/g1yIvAdZSw2BwI8eMmbeNGWgLD34tBjwPgX5pO8AjeeONsTTPucPGbTxpxRZ4bWlPf/bwZ1udHN/5HMPPPGV1sv3shzfewGvLAXBcHOZROAAVYcOnHGxLA1hNHYgxCkbBKBgFowA7AAA4ZksRpDqVBwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-6181-0558","institution":"North Dakota State University","correspondingAuthor":true,"prefix":"","firstName":"Guiping","middleName":"","lastName":"Yan","suffix":""}],"badges":[],"createdAt":"2025-09-10 18:08:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7585385/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7585385/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00122-025-05112-6","type":"published","date":"2026-01-05T15:58:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":91717996,"identity":"67bde0e7-8d5a-4505-98e8-29d0f9253f52","added_by":"auto","created_at":"2025-09-19 13:39:33","extension":"xml","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":14091,"visible":true,"origin":"","legend":"","description":"","filename":"taagTAAGD2500829.xml","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/f2595d04f12f3084a861b08e.xml"},{"id":91716807,"identity":"151e53a7-3482-41bb-b99e-93cf28eec90a","added_by":"auto","created_at":"2025-09-19 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13:39:33","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":102695,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/fa3881fda51b607ba97a4d09.png"},{"id":91718000,"identity":"4ad21f40-95fa-401a-8a04-fa05d9b121ae","added_by":"auto","created_at":"2025-09-19 13:39:33","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":233554,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/9c5b865d15f56a67691ad644.png"},{"id":91718743,"identity":"f8d592cb-fad6-47cb-8d21-4c7449a3439b","added_by":"auto","created_at":"2025-09-19 13:47:33","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":262301,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/3c1671fb3ebbac6675accf18.png"},{"id":91716817,"identity":"6f71b98b-eb39-49d4-a1e2-5f7b1cd6178f","added_by":"auto","created_at":"2025-09-19 13:31:33","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":175769,"visible":true,"origin":"","legend":"","description":"","filename":"TAAGD25008290structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/0352d0eef55e28c26be3dc58.xml"},{"id":91716816,"identity":"30935764-5da7-4936-90de-cc6e6b0bafa2","added_by":"auto","created_at":"2025-09-19 13:31:33","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":187533,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/d8111fd578f9b2349f8f41c5.html"},{"id":91716808,"identity":"8ca6e647-1666-4519-a38c-9c3425e1532d","added_by":"auto","created_at":"2025-09-19 13:31:33","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":282384,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of recombinant inbred lines (RILs) from the Siskiyou × Villax St. Jose triticale population across four resistance classes to \u003cem\u003ePratylenchus neglectus\u003c/em\u003e. Classes were defined relative to the susceptible wheat check Alpowa as: resistant (\u0026lt; 25%), moderately resistant (25-50%), moderately susceptible (50-75%), and susceptible (\u0026gt; 75%) of Alpowa’s postharvest nematode population density (as described in Singh et al. 2023). Values for Experiment 1 (orange) and Experiment 2 (blue) represent relative Pf (%) from individual greenhouse assays; values for the combined dataset (green) represent relative BLUPs (%) from a mixed model across both experiments. Brackets mark the approximate class positions of the moderately resistant parent (Villax St. Jose) and the susceptible parent (Siskiyou).\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/c8d1686f9db44a6958071429.jpeg"},{"id":91717997,"identity":"3eefc5a3-adb7-4be9-adb2-f33c77ab9a10","added_by":"auto","created_at":"2025-09-19 13:39:33","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":510385,"visible":true,"origin":"","legend":"\u003cp\u003eSingle-trait multiple-interval mapping (STMIM) of a quantitative trait locus (QTL) associated with resistance to \u003cem\u003ePratylenchus neglectus\u003c/em\u003e on chromosome 5R in the Siskiyou × Villax St. Jose RIL population. LOD profiles are presented for Experiment-1 (orange), Experiment-2 (blue), and the combined dataset (green). Marker names are shown below the chromosome axis, with corresponding genetic distances (in cM) indicated above. The horizontal dashed line represents the significance threshold (LOD = 3.2) at a genome-wide α = 0.05.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/2e9ce24833ee29efc152522d.jpeg"},{"id":91716805,"identity":"3cf6aa86-3528-41ae-9be2-815dc5fa5f61","added_by":"auto","created_at":"2025-09-19 13:31:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1455597,"visible":true,"origin":"","legend":"\u003cp\u003eAllelic discrimination plots of the five KASP markers mapped on chromosome 5R in the Siskiyou × Villax St. Jose population (a: fcp1070, b: fcp1071, c: fcp1072, d: fcp1073, and e: fcp1075). Each panel displays relative fluorescence units (RFU) for Allele 1 (FAM) on the x-axis and Allele 2 (HEX) on the y-axis. The orange dots and blue squares represent homozygous allele 1 and homozygous allele 2, respectively, and the green triangles represent heterozygote alleles.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/4b33cc0ecf623d14717677f1.png"},{"id":91716815,"identity":"a8b08879-4424-4fd7-aaa4-1d43cb0469a8","added_by":"auto","created_at":"2025-09-19 13:31:33","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1328720,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots showing the effect of fcp1070 alleles on Pratylenchus neglectus resistance in the Siskiyou × Villax St. Jose recombinant inbred line (RIL) population. RILs were grouped by genotype at marker fcp1070 and evaluated for relative nematode population (%), where values represent the final nematode population density (Pf) relative to the susceptible parent for Experiment-1 and Experiment-2, and relative best linear unbiased predictors (BLUPs) for the combined dataset. Blue boxes indicate individuals carrying the Villax St. Jose allele, and orange boxes indicate those with the Siskiyou allele. Horizontal lines within boxes represent medians, black crosses denote means, and individual dots represent RIL values. P-values are from Welch’s t-tests, indicating significant differences in nematode resistance between genotypic groups (P \u0026lt; 0.0001) across all datasets.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/6b81f313ed132ce3fcf521af.png"},{"id":100070908,"identity":"7b42d5fd-a738-4e1b-afc6-d22a15eb5b9c","added_by":"auto","created_at":"2026-01-12 16:18:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3624840,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/347085ff-4e41-4fb0-8971-c53457387d06.pdf"},{"id":91716814,"identity":"6f0f3ef9-0ee0-4a59-9440-ad47793b0baa","added_by":"auto","created_at":"2025-09-19 13:31:33","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":7146186,"visible":true,"origin":"","legend":"","description":"","filename":"RLNSinghetalFigureS1TriticalegeneticmapvS9825.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/02acb5bace45ac2b1588b11d.pdf"},{"id":91717998,"identity":"64095ae9-9841-4bbd-bd4b-e66ba46555e0","added_by":"auto","created_at":"2025-09-19 13:39:33","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":800988,"visible":true,"origin":"","legend":"","description":"","filename":"RLNSinghetalSupplementaryTablesvS9825.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7585385/v1/b4a66801fac887d41e48f64d.xlsx"}],"financialInterests":"","formattedTitle":"Genetic analysis of a quantitative trait locus associated with resistance to the root-lesion nematode Pratylenchus neglectus in triticale","fulltext":[{"header":"Key Message","content":"\u003cp\u003eA QTL from rye chromosome 5R confers resistance to root-lesion nematode in triticale.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eRoot-lesion nematodes (RLNs; \u003cem\u003ePratylenchus\u003c/em\u003e spp.) are migratory endoparasites that attack plant roots and are recognized as widespread pathogens of wheat and other small grains worldwide (Castillo and Vovlas \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Smiley and Nicol \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). These nematodes invade and cause lesions in root tissues, impairing water and nutrient uptake, and can cause substantial yield losses in infested fields (Smiley \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In rainfed wheat-growing regions, \u003cem\u003eP. neglectus\u003c/em\u003e has been reported to reduce grain yields by up to 30% in Australia and 37% in the United States (Vanstone et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Smiley and Machado \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Along with \u003cem\u003eP. thornei\u003c/em\u003e, \u003cem\u003eP. neglectus\u003c/em\u003e is among the most prevalent RLN species in temperate cereal production zones (Smiley and Nicol \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), posing a significant economic threat to global cereal production.\u003c/p\u003e\u003cp\u003eEffective management of RLNs in the field is notoriously challenging (Vanstone et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Dababat et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Crop rotation with non-host or poor-host species can suppress nematode populations, but this strategy is constrained by the broad host range of RLNs and the need for profitable rotation crops (Smiley \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In many cereal-based production systems worldwide, common rotation crops such as barley, corn, soybean, and field pea can still serve as hosts for \u003cem\u003eP. neglectus\u003c/em\u003e, thereby limiting the long-term efficacy of crop rotation as a control strategy (Vanstone et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; May et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Thompson et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mokrini et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Therefore, deploying host resistance is viewed as the most economical and sustainable approach for managing \u003cem\u003eP. neglectus\u003c/em\u003e in cereal-based production systems (Smiley and Nicol \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Smiley \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Resistant cultivars can suppress nematode reproduction, reducing population densities to below economic injury level and mitigating damage over time (Cook and Evans \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1987\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eExtensive phenotypic surveys have revealed that high-level resistance to \u003cem\u003eP. neglectus\u003c/em\u003e is rare in bread wheat (Vanstone et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Taylor et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Mulki et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Dababat et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Most modern cultivars are susceptible hosts, and even tolerant lines permit substantial nematode multiplication, perpetuating soil inoculum (Thompson et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Genetic analyses indicate that resistance in wheat is typically quantitative, controlled by multiple loci of small to moderate effect (Zwart et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Dababat et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). To date, only one locus of major effect, \u003cem\u003eRlnn1\u003c/em\u003e on chromosome 7AL, has been identified (Williams et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Jayatilake et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Although the \u003cem\u003eRlnn1\u003c/em\u003e locus significantly reduces nematode multiplication, its deployment is complicated by linkage to the high-yellow pigment allele \u003cem\u003ePsy-A1\u003c/em\u003e, which is undesirable in bread-making wheat (Jayatilake et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Additional quantitative trait loci (QTL) have been mapped on wheat chromosomes 1A, 2A, 2B, 4D, 5A, 6B, and 7D, but explained\u0026thinsp;\u0026lt;\u0026thinsp;15% of the phenotypic variation (Mulki et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Dababat et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Thompson et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Despite progress in QTL discovery, breeding uptake in wheat has been slow because: (i) extraction and microscopic counting of nematodes from soil and root samples based on morphological characteristics is laborious (Smiley \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and (ii) wheat has a complex polyploid genome and a scarcity of favorable alleles in elite gene pools, necessitating introgression from closely related or wild germplasm (Wen et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Consequently, there is a critical need for the development of molecular markers linked to nematode resistance to facilitate marker-assisted selection and accelerate breeding efforts (Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTriticale (\u0026times; \u003cem\u003eTriticosecale\u003c/em\u003e Wittm., 2n\u0026thinsp;=\u0026thinsp;6x\u0026thinsp;=\u0026thinsp;42, AABBRR genomes), a synthetic hybrid generated by combining the genomes of wheat (\u003cem\u003eTriticum\u003c/em\u003e spp., AABB genomes) and rye (\u003cem\u003eSecale cereale\u003c/em\u003e L., RR genomes), represents a promising yet underexploited reservoir of nematode resistance for cereal improvement (Ayalew et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mergoum et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In particular, rye is known for its broad resistance to various biotic and abiotic stresses, which triticale inherits to a large extent (Zeller and Hsam \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e1983\u003c/span\u003e; Mergoum et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Saulescu et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Breeders have long utilized triticale as a bridge to introgress valuable rye-derived traits, including resistance to pests and pathogens, into wheat germplasm (Friebe et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite this potential, triticale remains a relatively underutilized cereal crop globally, grown on limited acreage and often overlooked in major wheat improvement programs (Mergoum et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Several studies have demonstrated the potential of triticale as a source of resistance to RLNs. Farsi et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e1995\u003c/span\u003e) reported that triticale cultivars (Abacus and Muir) had significantly fewer nematodes per gram of root and per plant compared to susceptible wheat cultivars. In Australian field trials, Vanstone et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) observed that triticale varieties harbored lower populations of \u003cem\u003eP. neglectus\u003c/em\u003e than wheat, barley, and oats, indicating inherent resistance mechanisms. Taylor et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) confirmed that all triticale cultivars screened were resistant to \u003cem\u003eP. neglectus\u003c/em\u003e, whereas resistance in wheat was limited. Our recent greenhouse experiments have further validated the resistance potential of triticale, with the cultivar Villax St. Jose consistently demonstrating significantly lower nematode reproduction than a panel of elite wheat cultivars and germplasm lines (Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Building on this observation, the present study utilizes the Siskiyou \u0026times; Villax St. Jose (Wen et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) recombinant inbred line (RIL) population to (i) identify and map QTL associated with reduced nematode reproduction and (ii) convert tightly linked single-nucleotide polymorphisms (SNPs) into Kompetitive Allele-Specific PCR (KASP) assays. These assays constitute a rapid genotyping resource that can be further validated and integrated into triticale and wheat breeding pipelines aimed at enhancing RLN resistance. By filling a critical gap in our understanding of RLN resistance genetics in an under-utilized cereal, this work aims to broaden the genetic foundation for sustainable nematode management in cereal production.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eNematode population collection, processing, and species confirmation\u003c/h2\u003e\u003cp\u003eSoil samples were collected from North Dakota wheat fields known to be infested with \u003cem\u003eP. neglectus\u003c/em\u003e following a protocol previously described by Singh et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In brief, sampling occurred during the cropping season or immediately after harvest of the crop. Using a standard soil probe (2.5 cm diameter and 30 cm depth), samples were taken in a zig-zag pattern across the fields, with approximately 25\u0026ndash;30 soil cores per field. Samples were combined into a composite and transported to the Nematology Laboratory at North Dakota State University (NDSU), Fargo, ND. Ten subsamples of 200 grams (g) each were taken from the well-mixed composite soil for nematode extraction using the Whitehead tray method (Whitehead and Hemming \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1965\u003c/span\u003e) to determine initial population densities. This technique relies on the active migration of nematodes from moist soil into water. Each subsample was filtered through a 250 \u0026micro;m aperture sieve, and nematodes were collected on a 20 \u0026micro;m sieve, which was then concentrated to 20\u0026ndash;25 mL in a 50 mL vial (Capitol Vial Inc., Auburn, AL, USA). Nematodes were observed and identified to the genus level based on morphological features using a compound microscope (Zeiss Axiovert 25, Carl Zeiss Microscopy, NY, USA) and a Peters 1 mL gridded slide (Chalex Corporation, Portland, OR, USA). Molecular identification was performed by using \u003cem\u003eP. neglectus\u003c/em\u003e-specific PCR primers as described in Yan et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eRearing pure populations of\u003c/b\u003e \u003cb\u003eP. neglectus\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePure cultures of \u003cem\u003eP. neglectus\u003c/em\u003e were generated and maintained in monoxenic carrot disc cultures following Lawn and Noel (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1986\u003c/span\u003e) with minor modifications. Organically grown and fresh, unblemished carrots were washed, rinsed, and surface-sterilized in 10% bleach for 30 minutes in a laminar-flow hood. Using sterile instruments, carrots were peeled and sliced into 6\u0026ndash;10 mm discs, placed in sterile Petri dishes, sealed, and incubated at 22\u0026deg;C in the dark. Discs were preconditioned for 1\u0026ndash;2 weeks until calli formed. Individual nematodes were surface-sterilized in 0.01% streptomycin at 4\u0026deg;C overnight, selected under a dissecting microscope, and transferred to discs. The discs were placed in sterile Petri dishes (Thermo Fisher Scientific, Waltham, MA, USA), sealed with Parafilm, and incubated in the dark at 22\u0026deg;C. The carrot cultures were incubated in the dark at 22\u0026deg;C for up to six months, with weekly evaluations of carrot disc stability and nematode reproduction. Once the carrot discs reached six months or before decayed, nematodes were harvested. The discs were thinly sliced and soaked in distilled water in a Petri dish. After 3 to 4 hours, the water containing the nematodes was filtered through a 20 \u0026micro;m sieve, and the nematodes were collected in a 50 mL vial. The nematode suspension was refrigerated (~\u0026thinsp;4\u0026deg;C) until use. To increase inoculum, pre-germinated seeds of the spring wheat cultivar Alpowa (susceptible to \u003cem\u003eP. neglectus\u003c/em\u003e; Smiley et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) were used. Plants were grown in plastic pots containing 1 kg of pasteurized sandy-loam soil (67% sand, 18% silt, 15% clay). The soil was prepared in-house by blending river sand with field soil, and its particle-size distribution was verified by a commercial laboratory (Agvise Laboratories, Northwood, ND, USA). One week after planting, nematodes harvested from carrot cultures were inoculated near the roots by pipetting the suspension into four small holes around each plant; holes were backfilled with moist soil. Pots were watered lightly immediately after inoculation to settle the inoculum, then maintained at moderate moisture for 48\u0026ndash;72 hours to support nematode movement while avoiding leaching. Thereafter, pots were top watered (with low pressure) as needed to keep soil moisture consistent. Plants were grown for 14 weeks in the Jack Dalrymple Agricultural Research Complex, NDSU, Fargo, ND, USA at 22\u0026deg;C under a 16-hour photoperiod.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePlant materials\u003c/h3\u003e\n\u003cp\u003eWe used a triticale mapping population segregating for \u003cem\u003eP. neglectus\u003c/em\u003e to map resistance loci (Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The population was derived from a cross between the susceptible triticale cultivar Siskiyou (L12G09) and the moderately resistant triticale accession Villax St. Jose (L12G18). Both parents are hexaploid (2\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6\u003cem\u003ex\u003c/em\u003e\u0026thinsp;=\u0026thinsp;42, AABBRR) spring types. Siskiyou, developed collaboratively by the International Maize and Wheat Improvement Center in Mexico (CIMMYT) and the University of California, Davis, was released as a cultivar in California (Qualset et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). Villax St. Jose (PI 428848) is a Moroccan cultivar (Kuleung et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The development of this mapping population was previously detailed by Wen et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In this study, 137 F\u003csub\u003e6\u003c/sub\u003e RILs were screened for resistance to \u003cem\u003eP. neglectus\u003c/em\u003e. The \u003cem\u003eP. neglectus\u003c/em\u003e-susceptible wheat cultivar Alpowa, the resistant Iranian wheat landrace AUS28451, and unplanted inoculated and non-inoculated controls were used as control standards (Smiley and Machado \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eExperimental design and assessment for\u003c/b\u003e \u003cb\u003eP. neglectus\u003c/b\u003e \u003cb\u003eresistance\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe phenotypic evaluations of the RIL population for resistance to \u003cem\u003eP. neglectus\u003c/em\u003e were performed in two independent greenhouse experiments in 2020 and 2024 at the Jack Dalrymple Agricultural Research Complex, NDSU, Fargo, ND, USA. A single pre-germinated seed of each line was planted in a cone container filled with 150 g of pasteurized sandy loam soil (67% sand, 18% silt, and 15% clay; as described above) with approximately 2 g of \u0026lsquo;Osmocote Plus\u0026rsquo; 15-19-12 fertilizer (Scotts Sierra Horticultural Product Company, Maysville, OH, USA). Within each experiment, five biological replicates were grown per RIL and control. Each cone container served as one experimental replicate. In total, we evaluated 141 lines per experiment (137 F\u003csub\u003e6\u003c/sub\u003e RILs, two parents [Siskiyou and Villax St. Jose], and two wheat checks [Alpowa and AUS28451]). In addition, two unplanted controls (inoculated and non-inoculated) were included, each with five replicates. The cone containers were placed in RL98 trays (Stuewe \u0026amp; Sons, Inc., Corvallis, OR, USA) and arranged in a completely randomized design. This design yielded 715 planted experimental units per experiment and 1,430 units across both experiments. Plants were maintained in the greenhouse for 14 weeks at an average temperature of 22\u0026deg;C with a 16-hour photoperiod.\u003c/p\u003e\u003cp\u003eIn both experiments, inoculum consisted of mixed life stages of \u003cem\u003eP. neglectus\u003c/em\u003e (eggs, second-stage juveniles, and adults) pooled from two sources: monoxenic carrot-disc cultures and greenhouse-propagated populations maintained on susceptible wheat (cv. Alpowa) in pasteurized soil (described above). Seven days after planting, two 2 cm wells were made beside each seedling and inoculated with water suspensions of 300\u0026thinsp;\u0026plusmn;\u0026thinsp;10 \u003cem\u003eP. neglectus\u003c/em\u003e (eggs, J2, and adults) per cone for each experiment. Cone containers were top watered (with low pressure) as needed to keep soil moisture consistent for the first 7 days and then resumed carefully to avoid leaching of the nematodes. After 14 weeks, the entire root systems and the surrounding soil were harvested, stored at 4\u0026deg;C, thoroughly mixed, and processed on trays using the Whitehead tray extraction method (Whitehead and Hemming \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1965\u003c/span\u003e; Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). After 48 hours, nematodes were collected and counted under a compound microscope (Zeiss Axiovert 25, Carl Zeiss Microscopy, NY, USA) to determine the final (postharvest) population densities (Pf) of \u003cem\u003eP. neglectus\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eFollowing the standardized phenotyping strategy proposed by Singh et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Pf values were converted to relative values by normalizing against the susceptible check Alpowa within each experiment. When single experiments were analyzed, the numerator and denominator were the replicate means of Pf; in the combined analysis, they were the best linear unbiased predictors (BLUPs) described below. This standardization helps account for experiment-specific variability and allows consistent comparison across genotypes and runs. Relative Pf (%) was calculated as:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Relative\\:Pf\\:or\\:BLUPs=\\frac{Pf\\:\\left(or\\:BLUPs\\right)\\:from\\:tested\\:genotype\\times\\:100}{Pf\\:\\left(or\\:BLUPs\\right)\\:from\\:susceptible\\:check\\:Alpowa}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003ePhenotypic data analysis\u003c/h3\u003e\n\u003cp\u003eTo determine whether data from the two greenhouse experiments could be analyzed together, the homogeneity of error variances with Levene\u0026rsquo;s test (PROC GLM, SAS 9.4, SAS Institute, Cary, NC, USA) was examined. First, variance among the five replicates of every RIL was examined within each experiment; no significant heterogeneity was detected (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Second, genotype means were compared between experiments, and again Levene\u0026rsquo;s test revealed no variance differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Because both within- and between-experiment variances were homogeneous, replicate values were averaged to give one phenotype per RIL per experiment. Genotype means from Experiments 1 and 2 were then correlated with Pearson\u0026rsquo;s \u003cem\u003er\u003c/em\u003e using \u0026lsquo;\u003cem\u003ecor.test\u003c/em\u003e\u0026rsquo; in R Studio v4.3.2 (R Core Team, 2024) to quantify stability of the trait across experiments. A two-way analysis of variance (ANOVA) was performed to quantify the effects of experiment, genotype and their interaction:\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\:{{Y}_{ijk}=\\:\\mu\\:\\:+{E}_{i}\\:+{G}_{j}\\:+{(G\\times\\:E)}_{ij}\\:+\\:Ɛ}_{ijk}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cem\u003eY\u003c/em\u003e\u003csub\u003e\u003cem\u003eijk\u003c/em\u003e\u003c/sub\u003e​ is the relative Pf of the \u003cem\u003ek\u003c/em\u003e\u003csup\u003eth\u003c/sup\u003e replicate of genotype \u003cem\u003ej\u003c/em\u003e in experiment \u003cem\u003ei\u003c/em\u003e; \u003cem\u003e\u0026micro;\u003c/em\u003e is the overall mean; \u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e is the fixed effect of the \u003cem\u003ei\u003c/em\u003e\u003csup\u003eth\u003c/sup\u003e experiment; \u003cem\u003eG\u003c/em\u003e\u003csub\u003e\u003cem\u003ej\u003c/em\u003e\u003c/sub\u003e​ is the fixed effect of genotype \u003cem\u003ej\u003c/em\u003e; \u003cem\u003e(G\u0026times;E)\u003c/em\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e​ is the fixed interaction term; and Ɛ\u003csub\u003e\u003cem\u003eijk\u003c/em\u003e​\u003c/sub\u003e is the residual error. ANOVA revealed highly significant effects (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) of experiment, genotype, and their interaction, indicating that genotypes responded differentially across years. Although the experiment effect influenced trait means, replicate variances remained homogeneous, validating subsequent mixed-model adjustment. To account for experimental effect and genotype \u0026times; experiment (G\u0026times;E) interaction, we calculated BLUPs for each RIL or genotype using a linear mixed model fitted in the \u003cem\u003elme4\u003c/em\u003e package in R Studio v4.3.2:\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$\\:{{Y}_{ijkl}=\\:\\mu\\:\\:+{E}_{i}\\:+{G}_{j}\\:+{{(E\\times\\:R)}_{ik}+\\:(G\\times\\:E)}_{ij}\\:+\\:Ɛ}_{ijkl}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e is a fixed effect (experiment), \u003cem\u003e(E\u0026times;R)\u003c/em\u003e\u003csub\u003e\u003cem\u003eik\u003c/em\u003e​\u003c/sub\u003e is replication nested within experiment, \u003cem\u003eG\u003c/em\u003e\u003csub\u003e\u003cem\u003ej\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e​\u003c/em\u003e is a random genotypic effect, and \u003cem\u003e(G\u0026times;E)\u003c/em\u003e\u003csub\u003e\u003cem\u003eij\u003c/em\u003e\u003c/sub\u003e​ is a random genotype by experiment interaction. Parents and check cultivars were retained during model fitting to stabilize variance estimates but were excluded for downstream analysis. The resulting BLUPs provide experiment-adjusted, shrinkage-corrected estimates of genotypic performance and were used as phenotypic input in QTL analysis. Variance components from the mixed model were also used to compute broad-sense heritability (\u003cem\u003eH\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) on a line-mean basis,\u003cdiv id=\"Equd\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equd\" name=\"EquationSource\"\u003e\n$$\\:{H}^{2}\\:=\\:\\frac{{\\sigma\\:}_{G}^{2}}{{\\sigma\\:}_{G}^{2}+\\:\\frac{{\\sigma\\:}_{GE}^{2}}{e}+\\:\\frac{{\\sigma\\:}_{\\epsilon\\:}^{2}}{re}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{G}^{2}\\)\u003c/span\u003e\u003c/span\u003e represents a genotypic variance, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{GE}^{2}\\)\u003c/span\u003e\u003c/span\u003e​ is a genotype \u0026times; experiment interaction variance, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sigma\\:}_{\\epsilon\\:}^{2}\\)\u003c/span\u003e\u003c/span\u003e is the residual variance, \u003cem\u003er\u003c/em\u003e is the number of replicates per experiment, and \u003cem\u003ee\u003c/em\u003e represents the number of experiments.\u003c/p\u003e\n\u003ch3\u003eGenotyping-by-sequencing, SNP filtering, and linkage map construction\u003c/h3\u003e\n\u003cp\u003eRaw genotyping-by-sequencing (GBS) reads for RILs derived from the Siskiyou \u0026times; Villax St. Jose cross, together with both parents, were retrieved from the NCBI Sequence Read Archive (SRA accession: SRR5821028). The data were then compared to two reference genomes. The first genome was an artificial triticale genome generated by combining the \u0026lsquo;A\u0026rsquo; and \u0026lsquo;B\u0026rsquo; genomes of the wheat landrace Chinese Spring (IWGSC CS v1.0) and the \u0026lsquo;R\u0026rsquo; genome of the rye line Lo7 version 2 (Bauer et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The first artificial triticale genome provides valuable context relative to established, well-curated, and gene-annotated reference genomes of wheat and rye. The second genome used a newly assembled genome of the triticale cultivar Siskiyou (unpublished, Dr. Zhaohui Liu). The second genome provides a more accurate analysis of genomic information in the context of a true triticale cultivar and one of the parental lines of the mapping population.\u003c/p\u003e\u003cp\u003eThe data for the artificial triticale genome were analyzed with the reference-free TASSEL UNEAK pipeline (Wen et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The genome of Siskiyou was analyzed using the TASSEL 5.0 GBSv2 pipeline (Glaubitz et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Barcode demultiplexing, tag generation, alignment to the reference genome using Bowtie2 (version 2.4.5), SNP discovery, and variant calling were performed within the TASSEL (version 5.2.96) GBSv2 command-line interface (Glaubitz et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The resulting variant call file (VCF) was filtered using VCFtools (version 0.1.16) and TASSEL (version 5.2.96; Bradbury et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) software. SNPs were retained if they met the following criteria: (i) minor allele frequency (MAF)\u0026thinsp;\u0026ge;\u0026thinsp;0.35, (ii) missing data\u0026thinsp;\u0026le;\u0026thinsp;50%, and (iii) heterozygosity\u0026thinsp;\u0026le;\u0026thinsp;10%. Individuals with \u0026gt;\u0026thinsp;70% missing data were excluded, and any residual heterozygous genotype calls were converted to missing calls (Singh \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eCo-segregating and redundant loci were removed to retain unique, high-confidence SNPs for linkage analysis. Linkage maps were constructed using MapDisto v2.1.7 (Heffelfinger et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), following the procedures described by Wen et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Marker grouping was performed using the \u0026lt;\u0026thinsp;Find Linkage Groups\u0026thinsp;\u0026gt;\u0026thinsp;command with a logarithm of odds (LOD) threshold of 3.0 and a maximum recombination frequency (\u003cem\u003eR\u003c/em\u003e\u003csub\u003emax\u003c/sub\u003e) of 30.0. The Kosambi mapping function (Kosambi \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1944\u003c/span\u003e) was used to convert recombination frequencies into genetic distances. Within each linkage group, marker ordering and map refinement were done using\u0026thinsp;\u0026lt;\u0026thinsp;Order a linkage group \u0026gt;, \u0026lt; Check inversions \u0026gt;, \u0026lt; Ripple order \u0026gt;, and \u0026lt;\u0026thinsp;Drop locus\u0026thinsp;\u0026gt;\u0026thinsp;commands as described by Wen et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Acharya et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eKASP marker development and QTL analysis\u003c/h3\u003e\n\u003cp\u003eSNP-containing GBS tags flanking the 5R QTL peak were converted into KASP assays with PolyMarker (Ram\u0026iacute;rez-Gonz\u0026aacute;lez et al. 2015). PolyMarker facilitated the alignment of GBS tag sequences to Lo7 v2 genomic assembly, resulting in the generation of two allele-specific primers and one common primer for each assay. Primer candidates were screened \u003cem\u003ein silico\u003c/em\u003e against both the Lo7 and Weining rye genomes (Rabanus-Wallace et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Li et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) to confirm their single-copy specificity. For tags that failed PolyMarker\u0026rsquo;s design criteria, primers were manually redesigned using Primer3 (Seneviratne et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Running et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), again anchored to orthologous regions in the Lo7 and Weining genomic assemblies. All primer pairs were remapped to the triticale genome of Siskiyou to confirm their unique placement and correct orientation. The results showed complete concordance with the rye-based designs. The resulting KASP assays were evaluated in the parental lines and the RIL population, and then incorporated into the chromosome 5R linkage map for the final QTL analysis. To compare nematode reproduction between allelic classes at diagnostic markers, Welch\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-tests were performed on relative Pf or BLUP values using the function \u0026lsquo;\u003cem\u003escipy.stats.ttest_ind\u003c/em\u003e\u0026rsquo; (SciPy v1.11.4 in Python), with unequal variances assumed (\u003cem\u003eequal_var\u0026thinsp;=\u0026thinsp;False\u003c/em\u003e) for each experiment and for the combined dataset.\u003c/p\u003e\u003cp\u003eQTL mapping was performed in QGene v4.3.10 (Joehanes and Nelson \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) using default parameters, with the scanning interval set to 10 (equivalent to a 1.0 cM step size) to enable high-resolution detection of QTL across the linkage map (Singh \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The single-trait multiple interval mapping (STMIM) function was used to identify QTLs significantly associated with \u003cem\u003eP. neglectus\u003c/em\u003e resistance. Phenotypic inputs were relative Pf (%) for the single-experiment analyses and relative BLUPs (%) for the combined analysis. A permutation test consisting of 1,000 iterations was used to determine a LOD threshold for STMIM at a significance level of 0.05. The coefficient of determination (\u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) was used to estimate the phenotypic variation that the identified QTL explained.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eReactions of triticale parents and RILs to\u003c/b\u003e \u003cb\u003eP. neglectus\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe phenotypic assay confirmed the expected reaction classes of the reference genotypes: AUS28451 exhibited a highly resistant response (relative Pf\u0026thinsp;=\u0026thinsp;8.8%), Alpowa was susceptible (100.0%), Villax St. Jose was moderately resistant (29.7%), and Siskiyou was susceptible (80.3%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among the 137 RILs, relative Pf ranged from 2.7 to 113.4% in Experiment 1 and 2.9 to 109.8% in Experiment 2, with population means of 47.0% and 42.7%, respectively (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Environment-adjusted BLUPs, integrating both experiments, ranged from 7.5 to 93.4% with a mean of 46%. The distribution of relative Pf or BLUP values approximated a normal distribution, with transgressive segregants observed on both tails of the curve (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Genotype performance was strongly conserved across years (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.796, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the mixed-model analysis yielded a broad-sense heritability (\u003cem\u003eH\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e) of 0.903.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe response of parental lines and RIL to \u003cem\u003ePratylenchus neglectus\u003c/em\u003e in the Siskiyou \u0026times; Villax St. Jose triticale population\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDescriptor\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eExp-1 (%)\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eExp-2 (%)\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCombined (%)\u003csup\u003ez\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eReaction of parental lines\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSiskiyou (Susceptible)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e85.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e75.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e80.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVillax St. Jose (Resistant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e29.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eReaction of recombinant inbred lines (RILs)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMinimum value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e7.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMaximum value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e105.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e107.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e93.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e42.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e43.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ex\u003c/sup\u003e RIL statistics summarize RILs; each entry (parents, checks, and RILs) had five biological replicates per experiment.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ey\u003c/sup\u003e Exp\u0026thinsp;=\u0026thinsp;Experiment. Experiment-1 and Experiment-2 were independent greenhouse assays conducted at the Jack Dalrymple Agricultural Research Complex, North Dakota State University (Fargo, ND, USA) in 2020 and 2024, respectively. Exp-1 (%) and Exp-2 (%) are Relative Pf (%), calculated within each experiment as: 100 \u0026times; [Pf of the genotype] / [Pf of Alpowa]. Pf is the postharvest \u003cem\u003eP. neglectus\u003c/em\u003e population densities.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ez\u003c/sup\u003e Combined (%) are relative BLUPs from a linear mixed model across both experiments: Relative BLUP (%)\u0026thinsp;=\u0026thinsp;100 \u0026times; [genotype BLUP] / [Alpowa BLUP]. The model used genotype as a random effect, experiment as a fixed effect, and replicate nested within experiment as a random term.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eLinkage map construction\u003c/h3\u003e\n\u003cp\u003eRe-analysis of the raw fastq files originally reported by Wen et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) generated 120.5\u0026nbsp;million reads, which, after alignment to the Siskiyou reference genome, yielded 1.04\u0026nbsp;million unique 64-bp tags. SNP discovery identified 118,903 biallelic sites. Sequential filtering for genotype call-rate (\u0026ge;\u0026thinsp;50%), minor-allele frequency (\u0026ge;\u0026thinsp;0.35), and residual heterozygosity (\u0026le;\u0026thinsp;10%) (5,750 polymorphic SNPs; Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e), followed by the removal of redundant or co-segregating loci, yielded 1,054 non-redundant, high-confidence SNPs (Supplementary Table S3). These SNPs, together with seven chromosome-5R SSRs, provided 1,061 markers for linkage analysis. The marker set resolved into the expected 21 linkage groups, comprising 14 wheat (AA and BB genomes) and 7 rye (RR genome), which spanned 2,745.9 cM (Supplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The composite map contained 1,111.7 cM in the AA genome, 915.4 cM in the BB genome, and 718.9 cM in the RR genome, resulting in a genome-wide mean spacing of 2.58 cM per marker (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Individual linkage groups ranged from 80.6 cM (2R) to 213.2 cM (7A). Marker density varied from 2.13 cM/marker (5R) to 3.80 cM/marker (5A).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of genetic linkage map constructed from the Siskiyou \u0026times; Villax St. Jose triticale RIL population\u003csup\u003ew\u003c/sup\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChromosome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarkers mapped\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGenetic distance (cM)\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMarker density (cM/marker)\u003csup\u003ez\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e116.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e155.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e83.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e148.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e149.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e80.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e183.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e180.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e108.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e187.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e85.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e143.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e144.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.80\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e146.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.49\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e114.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e116.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e91.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e94.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e213.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e106.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e93.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA-genome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e396\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,111.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eB-genome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e915.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR-genome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e311\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e718.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.31\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,745.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ew\u003c/sup\u003e Genetic linkage map was constructed from 137 F\u003csub\u003e6\u003c/sub\u003e recombinant inbred lines (RILs) derived from Siskiyou \u0026times; Villax St. Jose.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ex\u003c/sup\u003e Number of mapped, non-redundant markers at unique positions per chromosome.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ey\u003c/sup\u003e Total map length per chromosome, computed as the sum of intervals between adjacent markers after ordering; intervals were derived from recombination fractions and converted to cM using the Kosambi mapping function used in this study.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003ez\u003c/sup\u003e Marker density (cM/marker) is the average spacing between mapped markers on a chromosome. It is calculated as the total genetic distance divided by the number of mapped, non-redundant markers at unique positions. Smaller values indicate denser coverage and finer mapping resolution.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eQTL identification on chromosome 5R\u003c/h3\u003e\n\u003cp\u003eA genome-wide scan with STMIM detected a single locus exceeding the 5% experiment-wise permutation threshold (LOD\u0026thinsp;=\u0026thinsp;3.2) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The peak occurred at 11 cM with a LOD of 6.5 and a generalized \u003cem\u003eR\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e of 0.196 in the combined analysis. Adjacent positions 9\u0026ndash;12 cM also surpassed the threshold (LOD\u0026thinsp;\u0026ge;\u0026thinsp;6.3), delimiting a 4 cM interval that accounted for ~\u0026thinsp;20% of the phenotypic variance in BLUPs and ~\u0026thinsp;16\u0026ndash;17% in the individual experiment means. No additional significant loci were detected elsewhere in the genome, indicating that a single, moderate-effect QTL largely conditions resistance in this population on 5R, hereafter designated as \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eKASP marker associated with\u003c/b\u003e \u003cb\u003eQRln.ndsu-5R\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOf the five chromosome-5R SNPs converted to KASP assays (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), \u003cem\u003efcp1070\u003c/em\u003e (derived from GBS tag \u003cem\u003eTP4673\u003c/em\u003e) is the most informative for \u003cem\u003eP. neglectus\u003c/em\u003e resistance. This marker lies only\u0026thinsp;~\u0026thinsp;3 cM from the maximum-LOD position of \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e and falls well inside the 4 cM interval defined by a one-LOD drop from the peak. Genotyping all 137 RILs and both parents produced unambiguous biallelic clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Lines that possessed the Villax St. Jose allele exhibited a mean relative BLUP of 35.5%, whereas lines with the Siskiyou allele averaged 53.0%. The difference in nematode reproduction was highly significant (Welch\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-statistic = -4.18, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.7 \u0026times; 10⁻\u003csup\u003e5\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e). A similar separation between genotype classes was also observed when the two greenhouse experiments were analyzed separately, confirming the stability of the marker effect across environments.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKompetitive Allele Specific PCR (KASP) markers mapped to chromosome 5R in the Siskiyou \u0026times; Villax St. Jose triticale recombinant inbred line population.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKASP marker\u003csup\u003ew\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSNP\u003csup\u003ex\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePrimer names\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePrimer sequences (5\u0026rsquo;\u0026rarr;3\u0026rsquo;)\u003csup\u003ey\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePhysical position (Mbp)\u003csup\u003ez\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cem\u003efcp1072\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1072\u003c/em\u003e-FAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtgaccaagttcatgctTGCTGCAGATTCATGAAGTGG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA/G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1072\u003c/em\u003e-HEX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtcggagtcaacggattTGCTGCAGATTCATGAAGTG\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eA\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e20,200,087\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1072\u003c/em\u003e-Com\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGTTGGTTCTCTGTCCTCTGTATCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cem\u003efcp1070\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1070\u003c/em\u003e-FAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtgaccaagttcatgctGATTGGGTGCGTGTGACAT\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eC\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC/G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1070\u003c/em\u003e-HEX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtcggagtcaacggattGATTGGGTGCGTGTGACATG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e26,708,526\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1070\u003c/em\u003e-Com\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCCCACCATGTGCCAAAATAATTC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cem\u003efcp1071\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1071\u003c/em\u003e-FAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtgaccaagttcatgctGCCTGGACGCCTATTTATCC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eA\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA/G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1071\u003c/em\u003e-HEX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtcggagtcaacggattGCCTGGACGCCTATTTATCCG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e365,423,142\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1071\u003c/em\u003e-Com\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGGTTTCTTTGGTGCTGCAGAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cem\u003efcp1075\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1075\u003c/em\u003e-FAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtgaccaagttcatgctAAGGTTGTCTGCAGCTCTC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eT\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC/T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1075\u003c/em\u003e-HEX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtcggagtcaacggattAAGGTTGTCTGCAGCTCTCC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e561,038,158\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1075\u003c/em\u003e-Com\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCCTATGGGAGTCTTGGCGAC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cem\u003efcp1073\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1073\u003c/em\u003e-FAM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtgaccaagttcatgctGTCAACGTCTCTGCAGCCT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA/T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1073\u003c/em\u003e-HEX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003egaaggtcggagtcaacggattGTCAACGTCTCTGCAGCC\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eA\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e739,373,203\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003efcp1073\u003c/em\u003e-Com\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAGCTCTGCTGAAACCCGAATAT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ew\u003c/sup\u003e KASP\u0026thinsp;=\u0026thinsp;Kompetitive allele specific PCR, a fluorescence-based genotyping method using two allele-specific forward primers (labeled with FAM or HEX tails) and one common reverse primer.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ex\u003c/sup\u003e SNP\u0026thinsp;=\u0026thinsp;single nucleotide polymorphism. The variant base is shown for each marker.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ey\u003c/sup\u003e Primer sequences are shown in the 5\u0026prime;\u0026rarr;3\u0026prime; direction. Lowercase letters at the beginning of FAM- and HEX-labeled forward primers represent the standard tail sequences recommended by the KASP chemistry for fluorophore binding; uppercase letters represent the locus-specific portion of the primer sequence.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003ez\u003c/sup\u003e Physical positions (in megabase pairs, Mbp) are based on the Siskiyou triticale reference genome assembly.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eRLNs continue to impose substantial yield penalties in rainfed cereals because nematicides are expensive and environmentally concerning, and crop rotation is unreliable since \u003cem\u003eP. neglectus\u003c/em\u003e can survive on a wide range of hosts (Smiley \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Therefore, genetic resistance remains the most durable defense strategy (Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). After decades of screening, wheat breeding still relies on a single major locus (\u003cem\u003eRlnn1\u003c/em\u003e) along with a few small-effect QTLs, which together leave significant nematode populations in the soil (Williams et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Zwart et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Mulki et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Dababat et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Rye (\u003cem\u003eS. cereale\u003c/em\u003e) is well known for broad disease resistance, and its amphiploid derivative, triticale (AABBRR genome), offers a practical bridge for deploying rye alleles into wheat (Wen et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). To our knowledge, no RLN resistance locus has been genetically mapped in rye or triticale. In this study, we identified \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e on chromosome 5R, which helped address this gap and provided genetic evidence from a rye-derived resistance source for cereal improvement.\u003c/p\u003e\u003cp\u003eAlthough \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e explained about 20% of the phenotypic variance, the near-normal distribution of the phenotypic data, together with transgressive RILs that exceeded both parents, indicated that additional loci likely contributed to resistance. Such transgression is consistent with complementary small-effect alleles from both parents. We used the existing Siskiyou \u0026times; Villax St. Jose population, which contains 137 F\u003csub\u003e6\u003c/sub\u003e RILs as previously described (Wen et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). RLN phenotyping is very labor- and space-intensive in that each line required five biological replicates and a 14-week greenhouse cycle in containment conditions, which constrained the feasibility of increasing the number of lines in this study. This design provided stable Pf estimates but offered limited power to detect very small-effect loci, so some modifiers may have remained below the detection threshold. The consistent signal on chromosome 5R across experiments supports a major locus with additional small-effect contributors. In the future, expanding population size, increasing marker density around 5R, and evaluating across additional environments will help resolve minor-effect loci and test for possible epistasis with \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eScreening for nematode resistance is laborious, time-consuming, and expensive, which is the major constraint in nematode resistance breeding (Smiley \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Depending upon the availability of resources, a single screening experiment may require 5\u0026ndash;6 months to generate phenotypic data (Singh 2020). Thus, genotypic selection using molecular markers can be a valuable alternative to the lengthy and labor-intensive process of resistance phenotyping (Singh et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The KASP markers we have developed can serve as valuable tools for monitoring the introgression of resistance QTL in \u003cem\u003eP. neglectus.\u003c/em\u003e Genotyping with \u003cem\u003efcp1070\u003c/em\u003e partitioned the 137 RILs into two allelic classes, whose mean nematode multiplications differed by ~\u0026thinsp;33% (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), closely matching the variance attributed to \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e. Genotypic analysis, in conjunction with phenotypic screenings for resistance to \u003cem\u003eP. neglectus\u003c/em\u003e in greenhouse environments, is expected to facilitate the development of germplasm exhibiting nematode resistance. Further fine-mapping and cloning of this QTL can help in developing robust diagnostic markers for marker-assisted selection in breeding programs (Singh \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) and gaining a deeper understanding of the genetic mechanisms underlying nematode resistance.\u003c/p\u003e\u003cp\u003eThe physical interval defining \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e spans\u0026thinsp;~\u0026thinsp;10 Mbp (20.20 Mbp to 30.96 Mbp) on the triticale (Siskiyou) reference genome. It contains 140 high-confidence genes (unpublished, Dr. Zhaohui Liu), which include three nucleotide-binding leucine-rich repeat (NLR)-type resistance-gene analogues and two coiled-coil receptor-like protein kinases (CC-RLKs). Similar gene groups have been repeatedly implicated in nematode resistance loci across various crops, including cereals. In wheat, for example, the \u003cem\u003eRlnn1\u003c/em\u003e region on 7AL and the fine-mapped \u003cem\u003eQRlnt\u003c/em\u003e intervals on 6D and 2B each harbor NLR or kinase clusters (Rahman et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Major cyst-nematode genes such as \u003cem\u003eCre1\u003c/em\u003e and \u003cem\u003eCre3\u003c/em\u003e likewise reside in NLR-rich blocks on wheat group-2 chromosomes, and the principal \u003cem\u003eP. thornei\u003c/em\u003e QTL on barley 7H contains two defense-related RLKs that are constitutively expressed in resistant lines (Mather et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Beyond cereals, single-gene resistances such as tomato \u003cem\u003eMi-1\u003c/em\u003e (for root-knot nematodes), potato \u003cem\u003eGpa2\u003c/em\u003e (potato cyst nematode), and the \u003cem\u003eArabidopsis\u003c/em\u003e pattern-recognition receptor \u003cem\u003eNILR1\u003c/em\u003e all encode NLRs or RLKs, underscoring the functional relevance of these classes against endoparasitic nematodes (Vos et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Qi et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Mendy et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Taken together, the recurrence of NLRs and kinase-type genes in independent nematode QTLs strongly suggests that these genes in the 5R interval could be potential candidates determining \u003cem\u003eP. neglectus\u003c/em\u003e resistance.\u003c/p\u003e\u003cp\u003eRye chromatin has repeatedly lifted wheat disease resistance to new plateaus; for example, the 1RS.1BL/1AL translocations carrying \u003cem\u003eLr26\u003c/em\u003e (leaf rust), \u003cem\u003eSr31\u003c/em\u003e (stem rust), \u003cem\u003ePm8\u003c/em\u003e (powdery mildew), and \u003cem\u003eYr9\u003c/em\u003e (yellow rust) are now present in \u0026gt;\u0026thinsp;1,000 cultivars worldwide (Schlegel \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, the rye gene \u003cem\u003eCreR\u003c/em\u003e on chromosome 6R has been introgressed to combat cereal cyst nematodes (Dundas et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Meanwhile, a 5R segment harboring \u003cem\u003eXct1\u003c/em\u003e confers dominant resistance to bacterial leaf streak in triticale and could also be transferred into bread wheat via \u003cem\u003eph1b\u003c/em\u003e-mediated homoeologous recombination (Wen et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e, therefore, joins a growing list of rye-derived factors that tackle otherwise recalcitrant threats in wheat. Because \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e lies within a modest\u0026thinsp;~\u0026thinsp;10-Mb interval, there is a realistic prospect of moving only a minimal rye fragment, mitigating the linkage drag that has occasionally accompanied larger translocations such as 1RS (Wang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Marker-assisted backcrossing with \u003cem\u003efcp1070\u003c/em\u003e, followed by targeted recombination in \u003cem\u003eph1b\u003c/em\u003e or CRISPR-enabled chromosome-engineering backgrounds, should enable precise introgression and subsequent trimming of unwanted rye DNA. If, as our preliminary data indicate, the 5R segment also retains proximity to \u003cem\u003eXct1\u003c/em\u003e (data not shown), breeders could co-deploy nematode and bacterial resistance in a single introgression. In a broader context, this work exemplifies how strategic mining of the wheat secondary gene pool, coupled with contemporary genomics, can diversify the resistance landscape beyond the narrow set of loci currently available in bread wheat.\u003c/p\u003e\u003cp\u003eIn conclusion, we identified and mapped a novel QTL, \u003cem\u003eQRln.ndsu-5R\u003c/em\u003e, associated with resistance to \u003cem\u003eP. neglectus\u003c/em\u003e in triticale. To our knowledge, no RLN-resistance locus had previously been mapped in this crop. The tightly linked KASP assay we provided should enable efficient marker-assisted introgression of the 5R resistance allele into triticale and wheat breeding programs, thereby reducing the time and cost associated with phenotypic screening of nematodes. By incorporating rye-derived defense genetics into the cereal improvement pipeline, these results expand the allelic repertoire available for nematode control and contribute to the development of more resilient cultivars.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003ch2\u003eEthics approval\u003c/h2\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003ch2\u003eConsent to participate\u003c/h2\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003ch2\u003eConsent to publish\u003c/h2\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003ch2\u003eAuthor contribution statement\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u0026nbsp;GS and GY conceived and designed the experiments; GS, KA, BM, SR, and EO conducted the experiments and collected the data; GS, KA, and GY analyzed and interpreted the data; GY, JF, XL, SW, HSC, and ZL provided resources, materials, and analysis tools; GS drafted the manuscript; GS, KA, BM, SR, EO, JS, UG, SW, HSC, XL, JF, ZL, and GY revised the manuscript. All authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThe authors would like to thank Jason Fielder, Santosh Gudi, and Addison Plaisance for their technical assistance. We also appreciate the computational assistance provided by the Center for Computationally Assisted Science and Technology (CCAST) at North Dakota State University, Fargo, ND, USA.\u003c/p\u003e\n\u003ch2\u003eData availability\u003c/h2\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available as supplementary materials and/or from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcharya K, Liu Z, Schachterle J, Kumari P, Manan F, Xu SS, Green AJ, Faris JD (2024) Genetic mapping of QTLs for resistance to bacterial leaf streak in hexaploid wheat. Theor Appl Genet 137:265. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00122-024-04767-x\u003c/span\u003e\u003cspan address=\"10.1007/s00122-024-04767-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAyalew H, Kumssa TT, Butler TJ, Ma XF (2018) Triticale improvement for forage and cover crop uses in the Southern Great Plains of the United States. 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Mol Breed 26:107\u0026ndash;124. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11032-009-9381-9\u003c/span\u003e\u003cspan address=\"10.1007/s11032-009-9381-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taag","sideBox":"Learn more about [Theoretical and Applied Genetics](https://www.springer.com/journal/122)","snPcode":"122","submissionUrl":"https://submission.nature.com/new-submission/122/3","title":"Theoretical and Applied Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Pratylenchus neglectus, QTL mapping, resistance, root-lesion nematode, rye, triticale, and wheat","lastPublishedDoi":"10.21203/rs.3.rs-7585385/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7585385/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRoot-lesion nematode (\u003cem\u003ePratylenchus neglectus\u003c/em\u003e, RLN) poses a significant threat to global wheat production. High levels of RLN resistance are rare in wheat. Triticale, an amphiploid generated by combining wheat and rye genomes that naturally carries rye-derived defense alleles, offers an untapped reservoir of nematode resistance. Here, we evaluated the response to RLN in 137 recombinant inbred lines (RILs) derived from a cross between two triticale cultivars: Siskiyou (susceptible) and Villax St. Jose (resistant). Genotyping-by-sequencing identified 1,054 high-quality single-nucleotide polymorphism (SNP) markers, which, along with seven simple sequence repeat (SSR) markers, were assembled into 21 linkage groups covering the triticale genome. A single quantitative trait locus (QTL) on the rye-derived chromosome 5R was identified that explained approximately 20% of the phenotypic variance across experiments. A high-throughput Kompetitive allele-specific PCR (KASP) assay based on the most significant SNP marker was developed, providing a rapid genotyping platform for selecting the resistance allele and reducing reliance on labor-intensive phenotyping for \u003cem\u003eP. neglectus\u003c/em\u003e resistance in triticale. This study reports the first mapped RLN-resistance QTL in triticale, laying the fundamental foundation for introgressing the 5R resistance allele into wheat via marker-assisted selection combined with chromosome engineering, thereby broadening the genetic basis for nematode resistance in cereal crops.\u003c/p\u003e","manuscriptTitle":"Genetic analysis of a quantitative trait locus associated with resistance to the root-lesion nematode Pratylenchus neglectus in triticale","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-19 13:31:28","doi":"10.21203/rs.3.rs-7585385/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revisions","date":"2025-10-21T07:46:51+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-09-29T10:32:51+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-13T17:01:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-11T15:44:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Theoretical and Applied Genetics","date":"2025-09-10T14:07:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"theoretical-and-applied-genetics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taag","sideBox":"Learn more about [Theoretical and Applied Genetics](https://www.springer.com/journal/122)","snPcode":"122","submissionUrl":"https://submission.nature.com/new-submission/122/3","title":"Theoretical and Applied Genetics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"af648773-7bf6-4f5e-8f64-5d667e2d05bd","owner":[],"postedDate":"September 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:15:23+00:00","versionOfRecord":{"articleIdentity":"rs-7585385","link":"https://doi.org/10.1007/s00122-025-05112-6","journal":{"identity":"theoretical-and-applied-genetics","isVorOnly":false,"title":"Theoretical and Applied Genetics"},"publishedOn":"2026-01-05 15:58:12","publishedOnDateReadable":"January 5th, 2026"},"versionCreatedAt":"2025-09-19 13:31:28","video":"","vorDoi":"10.1007/s00122-025-05112-6","vorDoiUrl":"https://doi.org/10.1007/s00122-025-05112-6","workflowStages":[]},"version":"v1","identity":"rs-7585385","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7585385","identity":"rs-7585385","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}