Slow stripe rusting in Chinese wheat Jimai 44 conferred by Yr29 in combination with a major QTL on chromosome arm 6AL

doi:10.21203/rs.3.rs-2880723/v1

“Slow rusting” (SR) is a type of adult plant resistance (APR) that can provide non-specific durable resistance to stripe rust in wheat. Chinese elite wheat cultivar Jimai 44 (JM44) has maintained SR to stripe rust in China since its release despite exposure to a changing and variable pathogen population. An F_2:6 population comprising 295 recombinant inbred lines (RILs) derived from a cross between JM44 and susceptible cultivar Jimai 229 (JM229) was used in genetic analysis of the SR. The RILs and parent lines were evaluated for stripe rust response in five field environments and genotyped using the Affymetrix Wheat55K SNP array and 13 allele-specific quantitative PCR-based (AQP) markers. Two stable QTL on chromosome arms 1BL and 6AL were identified by inclusive composite interval mapping. The 1BL QTL was probably the pleiotropic gene Lr46/Yr29. QYr.nwafu-6AL (hereafter named YrJ44), mapped in a 3.5-cM interval between AQP markers AX-109373479 and AX-109563479, was more effective than Yr29 in reducing disease severity and relative area under the disease progress curve (rAUDPC). RILs harboring both YrJ44 and Yr29 displayed levels of SR equal to the resistant parent JM44. The AQP markers linked with YrJ44 were highly polymorphic and significantly correlated with stripe rust resistance in a panel of 1,019 wheat cultivars and breeding lines. These results suggested that adequate SR resistance can be obtained by combining YrJ44 and Yr29 and the AQP markers can be used in breeding for durable stripe rust resistance.

Durable resistance

Triticum aestivum

yellow rust

YrJ44, a more effective slow rusting gene than Yr29, was localized to a 3.5-cM interval between AQP markers AX-109373479 and AX-109563479 on chromosome 6AL.

Wheat, provides more than 20% of calories required by humans and significant growth in wheat production plays an important role in global food security (Shewry and Hey 2015). It is predicted that biotic stresses will increase with global warming, implying that epidemics will be more frequent with greater effects on food production (Savary et al. 2019). Among diseases caused by fungi, stripe rust or yellow rust caused by Puccinia striiformis f. sp. tritici (Pst) continues to threaten wheat production worldwide (Singh et al. 2016). Without fungicide application, the yield of current cultivars would be more than 20% less (Chen 2014). Although fungicide application is widely used for control of stripe rust, resistant cultivars are a superior economical, effective and environmentally friendly option (Chen 2005; Wellings 2011).

More than 80 stripe rust resistance genes (Yr1-Yr84) have been cataloged (Klymiuk et al. 2022; McIntosh et al. 2017). Many of them confer all-stage resistance that is prone to loss of effectiveness due to the occurrence new pathogen races (Han and Kang 2018) or to selective increase in previously rare races. Breeders and farmers have found that adult plant resistance (APR) is more durable although often less effective (Chen et al. 2013). “Slow rusting” or partial resistance, defined as slow disease development despite a susceptible infection type by Caldwell (1968), is a characteristic of APR. Features of slow rusting include lower receptivity (infection efficiency), longer latent period, smaller uredinia, and reduced sporulation on host genotypes. The consequence is that such genotypes exhibit lower disease severity and lower yield losses. Many independent studies have shown that effective levels of APR are determined by multiple genetic factors with additive or complementary effects (Singh et al. 2013; Herrera-Foessel et al. 2011, 2006; Rosewarne et al. 2008). From the practical stand point, combining several slow rusting APR genes in a variety can lead to near-immunity (Singh et al. 2011).

Three of the named Yr genes in wheat are described as genes for slow rusting; including Yr18, Yr29 and Yr46 (Fu et al. 2009; Krattinger et al. 2009; Moore et al. 2015). All three have conferred resistance to multiple diseases including stripe rust, leaf rust (Puccinia triticina), stem rust (Puccinia graminis f. sp. tritici) and powdery mildew (Blumeria graminis f. sp. tritici) over a long period of time (more than 50 years) in different environments. They have been variously named as Yr18/Lr34/Sr57/Pm38 (Krattinger et al. 2009), Yr29/Lr46/Sr58/Pm39 (Singh et al. 2013) and Yr46/Lr67/Sr55/Pm46 (Herrera-Foessel et al. 2011; Moore et al. 2015) and have been cloned or fine-mapped. Yr18 was first described as LrT2 (later Lr34) in the wheat accession PI 58548 and located on short arm of wheat chromosome 7D (Dyck 1987). This gene codes an ATP-binding cassette (ABC) transporter of the pleiotropic drug resistance class (Krattinger et al. 2009) and can be detected by gene-specific Yr18 markers cssfr1-cssfr7 in molecular marker-assisted selection (Lagudah et al. 2009). Yr46 located on chromosome arm 4DL codes an H+/monosaccharide transporter (Moore et al. 2015). This gene is common in older, tall wheat cultivars and landraces but is rare in modern wheat cultivars (Chhetri et al. 2016), possibly due to its repulsion linkage with the reduced height gene RhtD1b. Yr29, first identified Pavon 76 with durable resistance to leaf rust (William et al. 2003), is present in many varieties worldwide, including Attila (Mexico, Rosewarne et al. 2006), Qinnong142 (China, Zeng et al. 2019) and Klein Chajá (Argentina, Cobo et al. 2019). Although this gene has not been isolated now, a marker csLV46G22 that tightly linked to Yr29 was developed and applied in marker assisted selection (MAS) (Rosewarne et al. 2006). Moreover, QYr.ucw-1BL, an adult-plant stripe rust resistance considered the same as Yr29 was fine-mapped in a within a 0.24-cM region on chromosome arm 1BL and multiple high-throughput markers including ucw.k23 were obtained (Cobo et al. 2019). These results will accelerate the map-based cloning and deployment of Yr29.

The Chinese elite wheat cultivar Jimai 44 (JM44) was developed by Shandong Academy of Agricultural Sciences from the cross Ji 954072 × Ji’nan 17. JM44 has high yield, high gluten content and cold tolerance and is becoming a leading cultivar with planting area over 1 million hectares. It has displays SR with susceptible infection types but low disease severity since its release in 2014. The objectives this study were to: (1) elucidate the genetic basis of slow rusting in JM44 using a recombinant inbred line (RIL) population tested in multiple environments; (2) identify tTL associated with SR using the Wheat55K SNP array; (3) evaluate the effect sizes of the target QTL and its combination with SR gene Yr29; and (4) develop and validate AQP markers closely linked to the major QTL.

Plant materials

A total of 295 F₆ RILs derived from a cross between JM229 (Gaocheng 9411/Ji 200040919) and JM44 (Ji 954072/Jinan 17) was used in QTL mapping. Mingxian 169 (MX169), an old Chinese winter wheat landrace susceptible to all Chinese Pst races, was grown as the disease spreader in field experiments. Australian spring wheat line Avocet S (AvS) and Chinese cultivar Xiaoyan 22 (XY22) were used as susceptible controls. Wheat 660K SNP genotypic data and phenotypic data for an independent diversity panel of 1,019 wheat accessions evaluated for stripe rust response at Yangling, Tianshui and Jiangyou in 2021 was used to validate AQP markers linked with the major QTL for molecular-assisted selection (MAS).

Field trials and phenotyping

Seedling and adult-plant tests in a previous study showed that JM229 and JM44 were susceptible to a panel of Pst races at the seedling stage, but JM44 showed slow-rusting at the adult-plant stage whereas JM229 was highly susceptible of (Yu et al. 2020). To evaluate stripe rust reactions in the field, JM44, JM229 and 295 RILs were planted at Yangling in Shaanxi province (34°17’N, 108°04’E) during the 2019-2020 (20YL), 2020-2021 (21YL) and 2021-2022 (22YL) cropping seasons, Mianyang in Sichuan province (31°39’N, 104°82’E) and Wuhan in Hubei province (30°34’N, 114°72’E) in 2019-2020 (20MY and 20WH). Mianyang and Wuhan are locations with regular natural occurrence of stripe rust. As Yangling experiences only occasional natural infection all MX169 control plants were inoculated with a urediniospore mixture of prevalent races (CYR32, CYR33 and CYR34) suspended in liquid paraffin (1:300) during late March every year. A randomized complete block design with two replications was used in all environments. Each plot was a 1-m row with a 25 cm row spacing; 15-20 seeds were planted in each plot. Two rows of highly susceptible cultivar XY22 were planted after every 20 rows and MX169 was planted adjacent to the plot area to ensure uniform disease development. Disease severity (DS) based on the modified Cobb scale (Peterson et al. 1948). was recorded for each line beginning when the disease severities on susceptible controls XY22 and MX169 were about 30% and 60%, and then recorded each week until the disease reached maximum levels. Disease severities for each line at 22YL test trial were converted to relative area under the disease progress curve (rAUDPC) values (Lin and Chen 2007).

Phenotypic data analysis

Mean DS data from each environment were used in analysis. Analysis of variance (ANOVA) and Person’s correlation coefficients (r) among environments were calculated with the “AOV” function in QTL IciMapping version 4.2 with the default parameters (Meng et al. 2015). t-tests were made in Excel 2019. Broad-sense heritability (h2b) of resistance to stripe rust was estimated based on:

DNA extraction and genotyping with high-throughput SNP array

The genomic DNA from the F₆ RILs and parental lines were extracted by a modified CTAB protocol and genotyped by Affymetrix Wheat55K SNP array at CapitalBio Corporation (Beijing; http://www.capitalbio.com) (Liu et al. 2022). SNP genotype calling and allele clustering were processed with Affymetrix Genotyping Console^TM (GTC) software. Monomorphic and poor-quality SNP loci with >10% missing values, ambiguous SNP calling, significantly deviating 1:1 segregation ratios confirmed by χ² tests (P ≤0.001) and minor allele frequencies <5% were excluded from further analysis. Parental lines were also genotyped by the Affymetrix Wheat 660K SNP array to identify additional SNPs (Sun et al. 2022).

Genetic map construction and QTL analysis

Remaining polymorphic SNPs were divided different linkage groups using JoinMap v4.0 with a logarithm of odds (LOD) score threshold of 3.0~10.0 (Van Ooijen 2006) and a genetic map of each group was constructed by the " Map " module in IciMapping v4.2 (Meng et al. 2015). Genetic distances (cM) were calculated by recombination fractions using the Kosambi function (Kosambi 1943). Based on SNPs from the 660K SNP array genotypes of JM44 and JM229, 13 AQP markers on chromosome arms 1BL and 6AL were developed to enrich the genetic map. The PCR amplification procedure was described previously (Liu et al. 2022). KASP marker ucw.k23 was used to determine presence of Lr46/Yr29 (Cobo et al. 2019).

Inclusive composite interval mapping with the additive tool (ICIM-ADD) in IciMapping v4.2 was performed to detect QTL using DS and BLUP data (Meng et al. 2015). A likelihood-of-odds (LOD) value of 3.2 was confirmed by 1000 permutations to declare significant QTL. A walk speed of 1.0 cM with a stepwise regression probability of 0.001 was set for QTL detection. The phenotypic variances explained (PVE) by individual QTL and additive effects at the LOD peaks were also obtained. The physical positions of QTL in CS RefSeq v1.1 were obtained based on blast using flanking marker sequences (http://wheatomics.sdau.edu.cn/) (Ma et al. 2021).

Comparisons with previously reported stripe rust resistance genes and QTL

To clarify the relationships between the loci identified in this study and previously reported Pst resistance genes and QTL, all loci were projected onto a wheat genetic map that provided by Dr. Fa Cui, Ludong University. The map integrated more than 10K SNP, DArT, SSR, STS, EST, RAPD and RFLP markers derived from a series of studies (Liu et al. 2022). The closest flanking markers were used to generate confidence intervals for previously reported stripe rust resistance genes and QTL.

Disease resistance test in greenhouse

To further validate the slowing-rust resistance of YrJ44, RILs carrying different resistance genes and the parent lines were tested in greenhouse. For each line, 10-15 seeds were planted in 20×20×15 cm plastic pots and were inoculated at the booting stage with the mixture of three races (CYR32:CYR33:CYR34≈1:1:1) for adult-plant tests. Details of inoculum refer to Wu et al. (2016). After inoculation, leave the plants in a dark dew chamber at 10 ℃ for 24 h. And then transferred to a greenhouse with a daily cycle of light (20,000 lx) at 16 ± 2 ℃ for 14 h and darkness at 10±2 ℃ for 10 h. After the disease severity developed 100% in the susceptible parent JM229, DS data and resistance response of each line were recorded.

Stripe rust responses in the field

JM44 displayed low DS (10–20%) (Fig. 1a) whereas JM229 was highly susceptible with DS of 90–100%) in all experiments (Fig. 1b). The stripe rust severities of the RILs showed approximate normal distributions, ranging from 0 to 100%, implying that the SR resistance in JM44 was polygenically controlled (Fig. 1c, d). ANOVA revealed lines and environments were the main determinants of phenotypic variation (P < 0.001). No significant variation (P = 0.289) was detected among replications in each environment. Broad-sense heritability of DS was 0.87 (Table 1). Pearson’s correlation coefficients among the phenotype data from five environments ranged from 0.34 to 0.75 (P < 0.001) (Fig. 1d). These results suggested that major SR genes/QTL may be involved in RIL population.

Table 1

Variance components of disease severity (DS) scores for the JM44/JM229 RIL population obtained across five environments
Source of variation	DF	Mean square	F value	P-value
RILs	294	2232	22.5	< 0.0001
Environments	4	157615.5	1586.6	< 0.0001
Lines×Environments	1176	331.8	8.4	< 0.0001
Replicates	1	833.6		0.298
Error	882	99.34
h2 b	0.87

Genetic linkage map

After removing SNPs with > 10% missing data and distorted segregation, 13,926 (26.27%) among all 53,007 SNPs showing polymorphism in parent lines and RILs remained. By using the “BIN” function in QTL IciMapping v4.2, and removing redundancies and 2,336 SNPs representing each "Bin" were chosen to construct genetic linkage maps covering all chromosomes. The map contained 35 linkage groups spanning 3,227.20 cM. The A, B, and D genomes had 813 (34.80%), 933 (39.94%), and 590 (25.26%) markers covering lengths of 1,072.22, 1,040.00, and 1,114.98 cM with average " Bin " marker intervals of 1.32, 1.11, and 1.89 cM, respectively. Chromosomes 1B, 1D, 2A, 2D, 3B, 3D, 4D, 6A and 6D were represented by single linkage group; the others two or three (Table S2).

QTL analysis

Five QTL for DS with additive effect on chromosome arms 1DS and 2BC in JM229 and 1BL, 6AL and 7DL in JM44 were identified using the ICIM method and a 3.2 LOD value (Fig. 2, Table 2). Two had consistent effects across all five field trials and were named QYr.nwafu-1BL.3 and QYr.nwafu-6AL (hereafter, YrJ44).

Table 2

Quantitative trait loci (QTL) for stripe rust resistance detected in the JM229/JM44 RIL population using disease severity (DS) data from five environments
QTL, environment^a	Flanking marker	Genetic position^b(cM)	Physical interval^c(Mb)	LOD^d	PVE^e	ADD^f
QYr.nwafu-1BL.3 (Yr29)
20YL	AX-94871279-AX-108800083	146	670.4-670.5	17.9	13.4	-9.2
20MY	AX-109423718-AX-111104551	150	675.6-675.7	4.2	6.2	-7.5
20WH	AX-109423718-AX-111104551	150	675.6-675.7	9.4	11.9	-3.8
21YL	AX-94871279-AX-108800083	146	670.4-670.5	13	18.5	-9.6
22YL	AX-109898596-AX-109346236	149	673.9-675.8	6.5	9.6	-8.1
Qyr.nwafu-1DS
20YL	AX-111540850-AX-111594357	0	8.4–10.6	8.1	15.9	6.3
20WH	AX-111040861-AX-109330851	14	18.4–20.3	4.8	6.7	4.6
21YL	AX-109141822-AX-111853381	22	21.8–22.9	4.4	5.2	3.8
Qyr.nwafu-2BC
20YL	AX-111559203-AX-109577269	22	154.6-158.4	2.7	4.4	4.6
20WH	AX-94480449- AX-112285965	28	211.9-214.6	5.6	7.8	4.8
22YL	AX-94480449- AX-112285965	28	211.9-214.6	3.5	4.4	4.6
QYr.nwafu-6AL (YrJ44)
20YL	AX-109373479-AX-109563479	141	606.6-611.9	13.5	19.4	-11.6
20MY	AX-109373479-AX-109563479	148	606.6-611.9	5.2	6.5	-10.1
20WH	AX-109373479-AX-109563479	149	606.6-611.9	18.1	25.2	-5.6
21YL	AX-109373479-AX-109563479	150	606.6-611.9	13.1	18.9	-8.5
22YL	AX-109373479-AX-109563479	150	606.6-611.9	15.5	22	-10.8
Qyr.nwafu-7DL
21YL	AX-110967909- AX-108909298	128	449.1-453.6	4.9	3.9	-4.4
^aYL, MY and WH represent Yangling, Mianyang and Wuhan. 20, 21 and 22 represent growing seasons 2019–2020, 2020–2021 and 2021–2022.
^bPeak position in centimorgans (cM) from the first linked marker in the relevant linkage group
^cPhysical location in mega bases (Mb) from linked markers in the wheat genome
^dLogarithm of odds score
^ePercentages of phenotypic variation explained by individual QTL
^fAdditive effect of the allele. Negative signs indicate that the favorable allele is from JM44.

QYr.nwafu-1BL.3 (Yr29) was represented by a 4.6-cM interval flanked by AX-94871279 and AX-111104551 and explained 6.2–18.5% of the variation in DS (Fig. 3b, Table 2). According to positions of expressed sequence tags in the 1B deletion bin map, QYr.nwafu-1BL.3 was located in deletion bin 1BL3-0.85-1.00 (Fig. 3a). By aligning the flanking sequences of linked SNPs with IWGSC RefSeq v1.1, the QYr.nwafu-1BL.3 region corresponded genomic interval 670.4-675.7 Mb in chromosome 1B (Fig. 3c).

YrJ44 was limited in a 3.1-cM interval spanned by AX-109373479 and AX-109563479 and placed in deletion bin 6AL8-0.90-1.00 (Fig. 4a, b, Table 2). The physical position of its confidence interval was 606.6-611.8 Mb on chromosome 6AL (Fig. 4c). YrJ44 explained 18.9–25.2% of the phenotypic variation during 2020, 2021 and 2022 seasons at Yangling and the 2020 season at Wuhan, but only 6.5% during the 2020 season at Mianyang (Table 2).

The other three QTL were named Qyr.nwafu-1DS, Qyr.nwafu-2BC and Qyr.nwafu-7DL, respectively (Table 2). These loci had minor effects on stripe rust response (explained phenotypic variation < 10%) and were detected in only one or two environments.

Slowing rusting and additive effects of YrJ44

To investigate the effects of YrJ44, the RILs were classified into two groups (with and without YrJ44) based on the presence/absence of flanking markers AX-109373479 and AX-109563479 (Fig. 5a). The mean DS for RILs carrying YrJ44 was 36.5% compared with 53.8% RILs without the QTL (Fig. 5a, Table S4). To assess the additive effective between YrJ44 and Yr29, The RILs were further divided into four groups based with the additional use of KASP marker ucw.k23 tightly linked with Yr29/QYr.ucw-1BL (Fig. 5b, Table 3). The group lacking Yr29 and YrJ44 had the highest mean DS (60.5%) in all environments and the group with both genes had the lowest DS (29.5%); the other groups were intermediate in mean response (Fig. 5b Table 3). The combination of YrJ44 and Yr29 reduce DS by 22.5–40.6% relative to the none group across environments (Table 3). DS of the Yr29 and YrJ44 groups were reduced by 4.5–20% and 9.7–24.7%, respectively, compared to the group lacking both genes. These results indicated that combining YrJ44 and Yr29 should be an effective breeding strategy for improving resistance to stripe rust. Moreover, lower DS values for the YrJ44 group in environments 20WH, 20YL and 21YL indicated that YrJ44 was a more effective than Yr29 reducing stripe rust levels.

Table 3

Comparison of stripe rust severities and the relative area under the disease progress curve (rAUDPC) among JM44/JM229 RIL grouped based on QTL status defined by flanking molecular markers
Group	No. of RILs	Disease Severity						rAUDPC 22YL
Group	No. of RILs	20WH	20MY	20YL	21YL	22YL	Mean	rAUDPC 22YL
None	48	45.0^a	62.0^a	63.2^a	75.4^a	56.7^a	60.5^a	0.8^a
Yr29	72	40.5^a	51.3^b	57.5^a	60.8^b	36.7^b	49.4^b	0.5^b
YrJ44	75	24.0^b	52.3^b	49.8^b	55.1^c	32.0^b	42.7^c	0.5^b
YrJ44 + Yr29	65	17.1^c	39.5^c	37.3^c	37.5^d	16.1^c	29.5^d	0.2^c
Mean disease severities and rAUDPC followed by different letters (a, b, c, and d) are significantly different (p < 0.01) based on tests of least significant difference. YL, MY and WH, Yangling, Mianyang and Wuhan. 20, 21 and 22, growing seasons 2019–2020, 2020–2021 and 2021–2022.

In addition, the dynamic development progress of Pst on several selected RILs were recorded in the 2022YL environment at 42, 45, 48, 52, 58 days after inoculation and the relative area under the disease progress curve (rAUDPC) were calculated, respectively (Fig. 5c, Table 3&S4). The none group with the highest rAUDPC value showed significant difference with the other three groups. The Yr29 and YrJ44 group with a mean rAUDPC of 0.5 showed no significant difference. The YrJ44 + Yr29 group showed the lowest rAUDPC and can reduce 0.3–0.5 rAUDPC value compared with other groups. These results indicated that both Yr29 and YrJ44 retard the growth of Pst races and more effective slow rusting can be obtained by combination of them.

To further validate the slowing-rust resistance of YrJ44, RIL018 (neither gene), RIL003 (Yr29), RIL037 (YrJ44), RIL064 (Yr29 + YrJ44), and the parents were inoculated with a mixture of CYR32, CYR33 and CYR34 in greenhouse. JM229 showed a highly susceptible response and JM44 showed a low DS. The responses of RIL064 and RIL018 were similar to JM44 and JM229, respectively; RIL003 and RIL037 exhibited intermediate levels of response compared with RIL037 having a lower DS (Fig. 5d).

YrJ44 AQP markers for molecular-assisted selection

Flanking AQP markers AX-109373479 and AX-109563479 were chosen for molecular-assisted selection (MAS) of YrJ44. The validation study showed that both AX-109373479 and AX-109563479 were polymorphic in the worldwide panel of 1,019 wheat accessions (Fig. 6a, b; Table S1). According to presence/absence of the JM44-alelle for AX-109373479 and AX-109563479 panel members were haplotyped as 651 (63.9%) CC-CC (JM44), 77 (7.5%) CC-TT, 226 (22.2%) TT-CC and 65 (6.4%) TT-TT (JM229) (Fig. 6c, Table S5). The high frequency of the CC-CC haplotype implied that YrJ44 was widely distributed in wheat. The significant difference on the significantly different mean DS scores between panel members with CC-CC and TT-TT haplotypes indicated that AX-109373479 and AX-109563479 were associated with resistance to stripe rust (Fig. 6c) and that these AQP markers could be used in marker assisted selection of YrJ44 in wheat breeding programs.

The QTL in chromosome 1BL

QYr.nwafu-1BL.3 was mapped in the same region as the pleiotropic locus YR29/LR46/SR58/PM39 for response to rusts and powdery mildew (Singh et al. 2013). The Yr29 allele confers slow rusting, adult plant resistance and was identified as a durable resistance gene (Ellis et al. 2014). Numerous QTL in wheat varieties or lines were reported in this genomic region in previous research reports (Fig. 3d). Based on the tightly linked marker csLV46G22, QYrqi.nwafu-1BL.1 in Qinnong 142 (Zeng et al. 2019), QYrsn.nwafu-1BL.2 in Shannong 33 (Huang et al. 2021), QYrcp.sun-1B in CPI133872 (Zwart et al. 2010), QYr.ucw-1BL in Klein Chajá (Cobo et al. 2019), QYrgu.jic-1B in Guardian (Melichar et al. 2008), QYrqu.tam-1B in Quaiu3 (Basnet et al. 2014), and QYrSaar-1B in Saar (Lillemo et al. 2008) were identified as Yr29 (Chen and Kang 2017). QYrex.wgp-1BL in Express (Lin and Chen 2009), QYrku.sun-1B in Kukri (Bariana et al. 2010) and QYrwo.sun-1B in Wollaroi durum (Bansal et al. 2014) were also mapped in expanded interval (more than 12 cM) based on the integrated genetic map (Fig. 3d). QYr.ucw-1B was identified in a by genome-wide association study of a worldwide hexaploid spring wheat panel (Maccaferri et al. 2015). These results imply that the genomic region of Yr29 was widely selected in breeding programs. In this study, QYr.nwafu-1BL.3 was identified as a slow-rusting QTL with similarities to Yr29. Moreover, JM44 has marker csLV46G22 strongly indicating that QYr.nwafu-1BL.3 is Yr29.

The QTL in chromosome 6AL

QYr.nwafu-6AL was flanked by AQP markers AX-109373479 and AX-109563479, corresponding to the 80.9-86.6 cM interval in the integrated linkage map. Given the tightly linked markers eight QTL were located near this genomic region in previous studies (Fig. 4d). QYr-6AL and QYr.ufs-6A were reported in the Australian wheat cultivar Avocet and line Avocet S (selected for susceptibility to stripe rust in multiple international environments), respectively (William et al. 2006; Prins et al. 2011), and explained with 3.2-4.8% of the phenotypic variation that was so minor effect on stripe rust resistance compared with YrJ44 (18.9-25.2%) that Avocet S was often used as susceptible parent line in genetic analysis (William et al. 2006). Based on the flanking markers of YrJ44, Avocet S contains a CC-TT haplotype different from JM44 (Table S5). Thus, we concluded that QYr-6AL and QYr.ufs-6A were not the same gene with YrJ44. It is worth mentioning that Avocet S carries a 6AS.6AeL translocation harboring stem rust resistance gene Sr26 (Zhang et al. 2021), but the slow rusting resistance on chromosome 6AL was unlikely contributed by the 6AeL segment as William et al. (2006) have reported that Avocet R, which also carries the translocation, is more susceptible than Avocet S. QYrpl.orr-6AL in cultivar Platte and QYren.orz-6AL in cultivar Einstein also showed a effect on slow-rusting (Vazquezet al. 2015, 2012). QYrpl.orr-6AL explaining 6% of the phenotypic variance which is significantly lower than YrJ44 and maybe was same with QYr-6AL and QYr.ufs-6A (William et al. 2006; Prins et al. 2011). QYren.orz-6AL explained 19% of the phenotypic variance have an similar effect with YrJ44 on reduce DS. In Einstein/Tubbs RIL population, QYren.orz-6AL interacted additively and epistatically with QYrtb.orz-2AS (Yr17) from parent line Tubbs and RILs with both QTL showed 5% or less disease severity (Vazquezet al. 2015). Similarly, YrJ44 showed favorable additive effect with Yr29 in JM44/JM229 population. These results indicated that QYren.orz-6AL was probably same with YrJ44. QYr.jki-6A, contributed 10-16% PVE, was found in founder lines Bayp4535 and Julius of a multiparent advanced generation intercross wheat population (MAGIC) that was constructed by intercrossing of eight wheat from German and Danish wheat breeding programs. The other three QTL identified in recent GWAS studies: QYr.lfl-6A from current European winter wheat germplasm (Shahinnia et al. 2022), QYr.3028443D from 270 winter wheat cultivars from eight European countries (Miedaner et al. 2020) and QYr.wsu-6A came from a subset of 1,175 winter wheat germplasm collection accessions originated from 67 countries in six continents (Bulli et al. 2016). In this study, 651 of 1,019 wheat lines have been identified as CC-CC (JM44) haplotype according to presence/absence of the JM44-alelle of for AX-109373479 and AX-109563479 (Fig 6). These lines were originated from more than 48 countries across multiple continents including Africa, the Americas, Asia, Australia, and Europe and almost all wheat growing areas (Table S5). These results indicated that the genomic region of YrJ44 might be play an important role in shape of modern wheat resistance to stripe rust in worldwide.

The combination of Yr29 and YrJ44 enhances slow rusting resistance

Combination of APR or SR resistance genes is a recommended priority of strategy in developing durable stripe rust resistance (Chen 2013; Singh et al. 2011). Genotypes with 1 or 2 slow rusting genes can express significant delays in disease development but become susceptible under high disease pressure. According to William et al. (2006) adequate levels of protection can be achieved by pyramiding of 3-5 slow rusting genes. Although several previous research projects separately identified Yr29 and possibly YrJ44 none considered their combination. In this study, we discovered Yr29 and YrJ44 were present in Chinese elite cultivar Jimai 44 that has maintained resistance since released in 2014. This provided an opportunity to evaluate the resistance conferred by Yr29 and YrJ44 in common genetic backgrounds and environmental conditions. YrJ44 was more effective in reducing disease severity than Yr29 in three (20WH, 20YL, and 21YL) of five environments and BLUP (Fig. 5a, b). RILs carrying both YrJ44 and Yr29 exhibited a lower mean stripe rust severity than those RILs with Yr29 or YrJ44 alone, and with neither resistance haplotype in each field environment (Fig. 5, Table 3), indicating the combined YrJ44 and Yr29 was effective in reducing stripe rust severity. This likely explains why JM44 with high yield potential and good quality is a widely accepted cultivar that continues to increase. The AQP markers linked with YrJ44 developed in this study will facilitate selection of YrJ44 in breeding programs.

Authors’ contribution statement

SJ Liu and JH Wu designed and conducted the experiments, analyzed the data, and wrote the manuscript. XY Cao and X Gao participated in creation of the genetic populations and assisted in analysis of the SNP array data. D Liu, ZW Mi, WJ Zhang, Y Ren, CX Lan, XK Liu and XT Wang participated in greenhouse and field experiments and contributed to genotyping and data analysis. DJ Han, BF Su, CF Wang and ZS Kang participated in revision of the manuscript. XY Cao and JH Wu conceived and directed the project and revised the manuscript.

Conflict of interest The authors declare that they have no conflicts of interest.

Data availability All data, models, or codes generated or used during the study are available by request from the corresponding authors.

Acknowledgments

The authors are grateful to Prof. R.A. McIntosh, Plant Breeding Institute, University of Sydney, for language editing and proofreading of this manuscript and Dr. Xueling Huang, State Key Laboratory of Crop Stress Biology for Arid Areas, Northwest A&F University, for providing a genotyping platform of AQP. This study was ﬁnancially supported by National Key R&D Program of China (2021YFD1200600 and 2021YFD1401000), National Natural Science Foundation of China (Grant no. 32272088), the Key R&D Program of Shaanxi Province (2021ZDLNY0-01), the Key R&D Program of Qinghai Province (2022-NK-125), the China Postdoctoral Science Foundation (2022T150538), the Agriculture Research System of China (CARS-03-06), Taishan Industrial Experts Programme (LJNY202006) and Shandong Provincial Natural Science Foundation (ZR2022MC155).

Bansal UK, Kazi AG, Singh B, Hare RA, Bariana HS (2014) Mapping of durable stripe rust resistance in a durum wheat cultivar Wollaroi. Mol Breed 33:51–59
Bariana HS, Bansal UK, Schmidt A, Lehmensiek A, Kaur J, Miah H, Howes N, McIntyre CL (2010) Molecular mapping of adult plant stripe rust resistance in wheat and identification of pyramided QTL genotypes. Euphytica 176:251–260
Basnet BR, Singh RP, Ibrahim A, Herrera-Foessel SA, Huerta-Espino J, Lan C, Rudd JC (2014) Characterization of Yr54 and other genes associated with adult plant resistance to yellow rust and leaf rust in common wheat Quaiu 3. Mol Breed 33:385–399
Bulli P, Zhang JL, Chao SM, Chen XM, Pumphrey M (2016) Genetic architecture of resistance to stripe rust in a global winter wheat germplasm collection. G3 (Bethesda) 6:2237–2253
Caldwell RM (1968) Breeding for general and/or specific plant resistance. In Finlay KW and Sphepard KW, eds. Proc 3rd Int Wheat Genet Symp, 5–9 August 1968. Australian Academy of Science, Canberra, Australia, p. 263–272
Chen X (2005) Epidemiology and control of stripe rust [Puccinia striiformis f. sp. tritici] on wheat. Can J plant Pathol 27:314–337
Chen X (2013) Review Article: High-temperature adult-plant resistance, key for sustainable control of stripe rust. Am J Plant Sci 4:608–627
Chen X (2014) Integration of cultivar resistance and fungicide application for control of wheat stripe rust. Can J Plant Pathol 36:311–326
Chen X, Kang Z (2017) Stripe rust. Springer, Netherlands
Chhetri M, Bansal U, Toor A, Lagudah E, Bariana H (2016) Genomic regions conferring resistance to rust diseases of wheat in a W195/BTSS mapping population. Euphytica 209:637–649
Cobo N, Wanjugi H, Lagudah E, Dubcovsky J (2019) A high-resolution map of wheat QYr.ucw‐1BL, an adult plant stripe rust resistance locus in the same chromosomal region as Yr29. The Plant Genome 12:180055
Ellis JG, Lagudah ES, Spielmeyer W, Dodds PN (2014) The past, present and future of breeding rust resistant wheat. Front Plant Sci 5:641
Dyck PL (1987) The association of a gene for leaf rust resistance with the chromosome 7D suppressor of stem rust resistance in common wheat. Genome 29:467–469
Feng J, Chen G, Wei Y, Liu Y, Jiang Q, Li W, Pu Z, Lan X, Dai S, Zheng Y (2014) Identification and genetic mapping of a recessive gene for resistance to stripe rust in wheat line LM168-1. Mol Breed 33:601–609
Han D, Kang Z (2018) Current status and future strategy in breeding wheat for resistance to stripe rust in China. Plant Prot 44:1–12
Herrera-Foessel SA, Lagudah ES, Huerta-Espino J, Hayden MJ, Bariana HS, Singh D, Singh RP (2011) New slow-rusting leaf rust and stripe rust resistance genes Lr67 and Yr46 in wheat are pleiotropic or closely linked. Theor Appl Genet 122:239–249
Herrera-Foessel SA, Singh RP, Huerta-Espino J, Crossa J, Yuen J, Djurle A (2006) Effect of leaf rust on grain yield and yield traits of Durum wheats with race-specific and slow-rusting resistance to leaf rust. Plant Dis 90:1065–1072
Hou L, Chen XM, Wang MN, See DR, Chao SM, Bulli P, Jing JX (2015) Mapping a large number of QTL for durable resistance to stripe rust in winter wheat Druchamp using SSR and SNP markers. PLoS ONE 10(5):e0126794
Huang S, Liu SJ, Zhang YB, Xie YZ, Wang XT, Jiao HX, Wu SS, Zeng QD, Wang QL, Singh RP, Bhavani S, Kang ZS, Wang CS, Han DJ, Wu JH (2021) Genome-wide Wheat55K SNP-based mapping of stripe rust resistance loci in wheat cultivar Shaannong 33 and their alleles frequencies in current Chinese wheat cultivars and breeding lines. Plant Dis 105:1048–1056
Jighly A, Oyiga BC, Makdis F, Nazari K, Youssef O, Tadesse W, Abdalla O, Ogbonnaya FC (2015) Genome-wide DArT and SNP scan for QTL associated with resistance to stripe rust (Puccinia striiformis f. sp tritici) in elite ICARDA wheat (Triticum aestivum L.) germplasm. Theor Appl Genet 128:1277–1295
Klymiuk V, Chawla HS, Wiebe K, Ens J, Fatiukha A, Govta L, Fahima T, Pozniak CJ (2022) Discovery of stripe rust resistance with incomplete dominance in wild emmer wheat using bulked segregant analysis sequencing. Commun Biol 5(1):826
Kosambi DD (1943) The estimation of map distances from recombination values. Ann Eugen 12:172–175
Krattinger SG, Lagudah ES, Spielmeyer W, Singh RP, Huerta-Espino J, McFadden H, Bossolini E, Selter LL, Keller B (2009) A putative ABC transporter confers durable resistance to multiple fungal pathogens in wheat. Science 323:1360–1363
Lagudah ES, Krattinger SG, Herrera-Foessel S, Singh RP, Huerta-Espino J, Spielmeyer W, Brown-Guedira G, Selter LL, Keller B (2009) Gene-specific markers for the wheat gene Lr34/Yr18/Pm38 which confers resistance to multiple fungal pathogens. Theor Appl Genet 119:889–898
Lan C, Rosewarne GM, Singh RP, Herrera-Foessel SA, Huerta-Espino J, Basnet BR, Zhang Y, Yang E (2014) QTL characterization of resistance to leaf rust and stripe rust in the spring wheat line Francolin#1. Mol Breed 34:789–803
Lillemo M, Asalf B, Singh RP, Huerta-Espino J, Chen XM, He ZH, Bjornstad A (2008) The adult plant rust resistance loci Lr34/Yr18 and Lr46/Yr29 are important determinants of partial resistance to powdery mildew in bread wheat line Saar.Theor Appl Genet:1155–1166
Lin F, Chen XM (2007) Genetics and molecular mapping of genes for race-specific all-stage resistance and non-race-specific high-temperature adult-plant resistance to stripe rust in spring wheat cultivar Alpowa. Theor Appl Genet 114:1277–1287
Lin F, Chen XM (2008) Molecular mapping of genes for race-specific overall resistance to stripe rust in wheat cultivar Express. Theor Appl Genet 116:797–806
Lin F, Chen XM (2009) Quantitative trait loci for non-race-specific, high-temperature adult-plant resistance to stripe rust in wheat cultivar Express. Theor Appl Genet 118:631–642
Liu JD, He ZH, Wu L, Bai B, Wen WE, Xie CJ, Xia XC (2015) Genome-wide linkage mapping of QTL for adult-plant resistance to stripe rust in a Chinese wheat population Linmai 2 x Zhong 892. PLoS ONE 10(12):e0145462
Liu S, Wang X, Zhang Y, Jin Y, Xia Z, Xiang M, Huang S, Qiao L, Zheng W, Zeng Q, Wang Q, Yu R, Singh RP, Bhavani S, Kang Z, Han D, Wang C, Wu J (2022) Enhanced stripe rust resistance obtained by combining Yr30 with a widely dispersed, consistent QTL on chromosome arm 4BL. Theor Appl Genet 135:351–365
Ma J, Qin NN, Cai B, Chen GY, Ding PY, Zhang H, Yang CC, Huang L, Mu Y, Tang HP, Liu YX, Wang JR, Qi PF, Jiang QT, Zheng YL, Liu CJ, Lan XJ, Wei YM (2019) Identification and validation of a novel major QTL for all-stage stripe rust resistance on 1BL in the winter wheat line 20828. Theor Appl Genet 132:1363–1373
Ma S, Wang M, Wu J, Guo W, Chen Y, Li G, Wang Y, Shi W, Xia G, Fu D, Kang Z, Ni F (2021) WheatOmics: A platform combining multiple omics data to accelerate functional genomics studies in wheat. Mol Plant 14:1965–1968
Maccaferri M, Zhang J, Bulli P, Abate Z, Chao S, Cantu D, Bossolini E, Chen X, Pumphrey M, Dubcovsky J (2015) A genome-wide association study of resistance to stripe rust (Puccinia striiformis f. sp. tritici) in a worldwide collection of hexaploid spring wheat (Triticum aestivum L.). G3. 5(Bethesda):449–465
McIntosh RA, Dubcovsky J, Rogers J, Morris C, Appels R, And Xia X (2017) Catalogue of gene symbols for wheat: 2017 Supplement. http://www.shigen.nig.ac.jp/wheat/komugi/genes/macgene/supplement2017.pdf
Melichar JP, Berry S, Newell C, MacCormack R, Boyd LA (2008) QTL identification and microphenotype characterisation of the developmentally regulated yellow rust resistance in the UK wheat cultivar Guardian. Theor Appl Genet 117:391–399
Miedaner T, Akel W, Flath K, Jacobi A, Taylor M, Longin F, Würschum T (2020) Molecular tracking of multiple disease resistance in a winter wheat diversity panel. Theor Appl Genet 133:419–431
Meng L, Li HH, Zhang LY, Wang JK (2015) QTL IciMapping: Integrated software for genetic linkage map construction and quantitative trait locus mapping in biparental populations. Crop J 3:269–283
Moore JW, Herrera-Foessel S, Lan C, Schnippenkoetter W, Ayliffe M, Huerta-Espino J, Lillemo M, Viccars L, Milne R, Periyannan S, Kong X, Spielmeyer W, Talbot M, Bariana H, Patrick JW, Dodds P, Singh R, Lagudah E (2015) A recently evolved hexose transporter variant confers resistance to multiple pathogens in wheat. Nat Genet 47:1494–1498
Naruoka Y, Garland-Campbell KA, Carter AH (2015) Genome-wide association mapping for stripe rust (Puccinia striiformis f. sp. tritici) in US Pacific Northwest winter wheat (Triticum aestivum L). Theor Appl Genet 128:1083–1101
Peterson RF, Campbell AB, Hannah AE (1948) A diagrammatic scale for estimating rust intensity on leaves and stems of cereals. Can J Res 26:496–500
Prins R, Pretorius ZA, Bender CM, Lehmensiek A (2011) QTL mapping of stripe, leaf and stem rust resistance genes in a Kariega x Avocet S doubled haploid wheat population. Mol Breed 27:259–270
Rollar S, Geyer M, Hartl L, Mohler V, Ordon F, Serfling A (2021) Quantitative trait loci mapping of adult plant and seedling resistance to stripe rust (Puccinia striiformis Westend.) in a multiparent advanced generation intercross wheat population. Front Plant Sci 12:684671
Rosewarne GM, Singh RP, Huerta-Espino J, Herrera-Foessel SA, Forrest KL, Hayden MJ, Rebetzke GJ (2012) Analysis of leaf and stripe rust severities reveals pathotype changes and multiple minor QTL associated with resistance in an Avocet x Pastor wheat population. Theor Appl Genet 124:1283–1294
Rosewarne GM, Singh RP, Huerta-Espino J, Rebetzke GJ (2008) Quantitative trait loci for slow-rusting resistance in wheat to leaf rust and stripe rust identified with multi-environment analysis. Theor Appl Genet 116:1027–1034
Rosewarne GM, Singh RP, Huerta-Espino J, William HM, Bouchet S, Cloutier S, McFadden H, Lagudah ES (2006) Leaf tip necrosis, molecular markers and beta1-proteasome subunits associated with the slow rusting resistance genes Lr46/Yr29. Theor Appl Genet 112:500–508
Savary S, Willocquet L, Pethybridge SJ, Esker P, McRoberts N, Nelson A (2019) The global burden of pathogens and pests on major food crops. Nat Ecol Evol 3:430
Shahinnia F, Geyer M, Schurmann F, Rudolphi S, Holzapfel J, Kempf H, Stadlmeier M, Loschenberger F, Morales L, Buerstmayr H, Sanchez J, Akdemir D, Mohler V, Lillemo M, Hartl L (2022) Genome-wide association study and genomic prediction of resistance to stripe rust in current Central and Northern European winter wheat germplasm. Theor Appl Genet 135:3583–3595
Shewry PR, Hey SJ (2015) The contribution of wheat to human diet and health. Food Energy Secur 4:178–202
Singh A, Pandey MP, Singh AK, Knox RE, Ammar K, Clarke JM, Clarke FR, Singh RP, Pozniak CJ, DePauw RM, McCallum BD, Cuthbert RD, Randhawa HS, Fetch TG (2013) Identification and mapping of leaf, stem and stripe rust resistance quantitative trait loci and their interactions in durum wheat. Mol Breed 31:405–418
Singh RP, Huerta-Espino J, Bhavani S, Herrera-Foessel SA, Singh D, Singh PK, Velu G, Mason RE, Jin Y, Njau P, Crossa J (2011) Race non-specific resistance to rust diseases in CIMMYT spring wheats. Euphytica 179:175–186
Singh RP, Herrera-Foessel S, Huerta-Espino J, Lan CX, Basent BR, Bhavani S, Lagudah ES (2013) Pleiotropic gene Lr46/Yr29/Pm39/Ltn2 confers slow rusting, adult plant resistance to wheat stem rust fungus. In: Proceedings of the Borlaug Global Rust Initiative, 2013 Technical Workshop, New Dehli, India. 19–22 Aug. 2013. p. 17.1
Singh RP, Singh PK, Rutkoski J, Hodson DP, He XY, Jorgensen LN, Hovmoller MS, Huerta-Espino J (2016) Disease impact on wheat yield potential and prospects of genetic control. Annu Rev Phytopathol 54:303–322
Singh S, Singh RP, Bhavani S, Huerta-Espino J, Eugenio LE (2013) QTL mapping of slow-rusting, adult plant resistance to race Ug99 of stem rust fungus in PBW343/Muu RIL population. Theor Appl Genet 126:1367–1375
Sun C, Dong Z, Zhao L, Ren Y, Zhang N, Chen F (2020) The Wheat 660K SNP array demonstrates great potential for marker-assisted selection in polyploid wheat. Plant Biotechnol J 18:1635
Van Ooijen JW (2006) JoinMap4, software for the calculation of genetic linkage maps in experimental populations. Kyazma BV, Wageningen
Vazquez MD, Peterson CJ, Riera-Lizarazu O, Chen XM, Heesacker A, Ammar K, Crossa J, Mundt CC (2012) Genetic analysis of adult plant, quantitative resistance to stripe rust in wheat cultivar 'Stephens' in multi-environment trials. Theor Appl Genet 124:1–11
Vazquez MD, Zemetra R, Peterson CJ, Chen X, Heesacker A, Mundt CC (2015) Multi-location wheat stripe rust QTL analysis: genetic background and epistatic interactions. Theor Appl Genet 128:1307–1318
Wellings CR (2011) Global status of stripe rust: a review of historical and current threats. Euphytica 179:129–141
William HM, Singh RP, Huerta-Espino J, Palacios G, Suenaga K (2006) Characterization of genetic loci conferring adult plant resistance to leaf rust and stripe rust in spring wheat. Genome 49:977–990
William M, Singh RP, Huerta-Espino J, Islas SO, Hoisington D (2003) Molecular marker mapping of leaf rust resistance gene Lr46 and its association with stripe rust resistance gene Yr29 in wheat. Phytopathology 93:153–159
Wu J, Wang Q, Chen X, Wang M, Mu J, Lv X, Huang L, Han D, Kang Z (2016) Stripe rust resistance in wheat breeding lines developed for central Shaanxi, an overwintering region for Puccinia striiformis f. sp. tritici in China. Can J Plant Pathol 38:317–324
Xiao J, Liu B, Yao Y, Guo Z, Jia H, Kong L, Zhang A, Ma W, Ni Z, Xu S, Lu F, Jiao Y, Yang W, Lin X, Sun S, Lu Z, Gao L, Zhao G, Cao S, Chen Q, Zhang K, Wang M, Wang M, Hu Z, Guo W, Li G, Ma X, Li J, Han F, Fu X, Ma Z, Wang D, Zhang X, Ling H, Xia G, Tong Y, Liu Z, He Z, Jia J, Chong K (2022) Wheat genomic study for genetic improvement of traits in China. Sci China Life Sci 65:1718–1775
Yu R, Jin Y, Wu S, Wu J, Wang Q, Zeng Q, Liu S, Xia Z, Wang X, Kang Z, Han D (2020) Stripe rust resistance of new varieties (lines) from Huang-Huai valley wheat region in China. J Triticeae Crops 3:278–284
Zegeye H, Rasheed A, Makdis F, Badebo A, Ogbonnaya FC (2014) Genome-wide association mapping for seedling and adult plant resistance to stripe rust in synthetic hexaploid wheat. PLoS ONE 9(8):e105593
Zeng QD, Wu JH, Liu SJ, Chen XM, Yuan FP, Su PP, Wang QL, Huang S, Mu JM, Han DJ, Kang ZS, Chen XM (2019) Genome-wide mapping for stripe rust resistance loci in common wheat cultivar Qinnong 142. Plant Dis 103:439–447
Zeng QD, Zhao J, Wu JH, Zhan GM, Han DL, Kang ZS (2022) Wheat stripe rust and integration of sustainable control strategies in China. Front Agr Sci Eng 9:37–51
Zhang JP, Hewitt TC, Boshoff W, Dundas I, Upadhyaya N, Li JB, Patpour M, Chandramohan S, Pretorius ZA, Hovmoller M, Schnippenkoetter W, Park RF, Mago R, Periyannan S, Bhatt D, Hoxha S, Chakraborty S, Luo M, Dodds P, Steuernagel B, Wulff B, Ayliffe M, McIntosh RA, Zhang P, Lagudah ES (2021) A recombined Sr26 and Sr61 disease resistance gene stack in wheat encodes unrelated NLR genes. Nat Commun 12(1):3378
Zwart RS, Thompson JP, Milgate AW, Bansal UK, Williamson PM, Raman H, Bariana HS (2010) QTL mapping of multiple foliar disease and root-lesion nematode resistances in wheat. Mol Breed 26:107–124

SupplymentaryTable1.xlsx
Table S1 Allele-specific quantitative PCR (AQP) primers used to genotype RILs to enrich the genetic maps of chromosome arms 1BL and 6AL.
SupplymentaryTable2.xlsx
Table S2 Distribution of single-nucleotide polymorphism (SNP) markers from the Wheat55K SNP array on 21 wheat chromosomes derived from the cross between JM44 and JM229.
SupplymentaryTable3.xlsx
Table a in S3 Dataset. Information for the integrated chromosome arm 1BL map. Table b in S3 Dateset. Information for the integrated chromosome arm 6AL map.

Slow stripe rusting in Chinese wheat Jimai 44 conferred by Yr29 in combination with a major QTL on chromosome arm 6AL

Status:

Journal Publication

Version 1

Abstract

Figures

Key message

Introduction

Materials and methods

Results

Stripe rust responses in the field

Genetic linkage map

QTL analysis

Discussion

Declarations

References

Supplementary Files

Status:

Journal Publication

Version 1