High density mapping of wheat stripe rust resistance gene QYrXN3517-1BL using QTL mapping, BSE-Seq and candidate gene analysis

Fine mapping of a major stripe rust resistance locus QYrXN3517-1BL to a 336 kb region that includes 12 candidate genes. Utilization of genetic resistance is an effective strategy to control stripe rust disease in wheat. Cultivar XINONG-3517 (XN3517) has remained highly resistant to stripe rust since its release in 2008. To understand the genetic architecture of stripe rust resistance, Avocet S (AvS) × XN3517 F6 RIL population was assessed for stripe rust severity in five field environments. The parents and RILs were genotyped by using the GenoBaits Wheat 16 K Panel. Four stable QTL from XINONG-3517 were detected on chromosome arms 1BL, 2AL, 2BL, and 6BS, named as QYrXN3517-1BL, QYrXN3517-2AL, QYrXN3517-2BL, and QYrXN3517-6BS, respectively. Based on the Wheat 660 K array and bulked segregant exome sequencing (BSE-Seq), the most effective QTL on chromosome 1BL is most likely different from the known adult plant resistance gene Yr29 and was mapped to a 1.7 cM region [336 kb, including twelve candidate genes in International Wheat Genome Sequencing Consortium (IWGSC) RefSeq version 1.0]. The 6BS QTL was identified as Yr78, and the 2AL QTL was probably same as QYr.caas-2AL or QYrqin.nwafu-2AL. The novel QTL on 2BL was effective in seedling stage against the races used in phenotyping. In addition, allele-specifc quantitative PCR (AQP) marker nwafu.a5 was developed for QYrXN3517-1BL to assist marker-assisted breeding.


Introduction
Domestication and selection for over 10,000 years led to productive plant species that are better suited for human use and adapated to various environments, and bread wheat (Triticum aestivum L.) emerged as one of the world's most important food crops (Pont et al. 2019). However, wheat production is continuously challenged by numerous diseases among which stripe rust, caused by Puccinia striiformis tritici (Pst), is one of the most important (Wellings 2011;Steiner et al. 2019). The most preferred economical and environmentally safe strategy for control of stripe rust is the cultivation of resistant cultivars (Chen 2013).
Stripe rust resistance is usually described as all stage resistance (ASR) and adult plant resistance (APR) or hightemperature adult-plant resistance based on effectiveness at different growth stages. ASR is usually race-specific, qualitatively inherited and controlled either by a single gene or in combinations, whereas APR or HTAP-R is conferred by multiple genes with minor or major effects that are often Communicated by Hermann Buerstmayr. Shuo Huang, Yibo Zhang, and Hui Ren contributed equally to this work. race non-specific, durable, pleotropic and quantitively inherited (Chen 2005(Chen , 2013. Cultivars with ASR are vulnerable to breakdown with the evolution of new virulent races and therefore not recommended for cultivation which can lead to boom and bust cycles. On the contrary, cultivars with only APR or HTAP resistance controlled by multiple genes are susceptible at the seedling stage, but gradually become resistant as plants grow and temperatures increase (Chen and Line 1995). Therefore, identification and utilization of APR or HTAP resistance gene in wheat cultivars, not only enrich the stripe rust resistance gene pool, but also can assist development of new cultivars with multiple resistance genes (Chen 2013;Liu et al. 2018;Mu et al. 2019;Wu et al. 2018).
In order to enhance durable resistance within breeding germplasm, it is important to enhance the diversity of APR genes for deployment which underscores the need to identify and characterize new APR genes, their interactions with other genes and their broad effectiveness against multiple pathogen races and across different environments. XINONG-3517 (XN3517; http:// wheat pedig ree. net/), a high-yielding cultivar with good quality, has shown a high level of resistance to stripe rust for many years. The objectives of this study were to (1) investigate the genetic basis of stripe rust resistance in an Avocet S (AvS) × XINONG-3517 recombinant inbred line (RIL) population grown in several environments, (2) identify and map QTL conferring resistance to stripe rust in XINONG-3517 using the wheat 16 K chip, (3) construct linkage map and identify markers closely linked to QYrXN3517-1BL, (4) predict a candidate gene for QYrXN3517-1BL, and (5) validate molecular marker for marker-assisted selection (MAS).

Plant materials
The 161 F 6 RIL population derived from the cross of susceptible Avocet S (AvS) × resistant XINONG-3517 (XN3517) was developed for mapping studies at Northwest A&F University. A panel of 760 wheat lines was evaluated for resistance to stripe rust across multiple environments and used to determine the prevalence of resistance genes identified in XN3517 based on the flanking single nucleotide polymorphism (SNP) markers which also included a set of Chinese wheat cultivars and breeding lines, and Yr gene carrying testers were used as checks (Table S1) and two Cultivars Mingxian 169 (MX169) and Xiaoyan 22 (XY22) which were used as susceptible controls.

Greenhouse evaluation
Seedlings of the RIL population and parents were tested in greenhouse against three Pst races (PST-Lab.1, PST-Lab.2 and PST-V26) following the procedure described in Wu et al. (2018). The virulence/avirulence information for the three races was previously provided by Huang et al. (2021) and listed in Table S2. Infection types (ITs) on all lines were recorded 18-21 days after inoculation when the disease had fully developed on the susceptible controls (AvS and MX169); these were based on a 0-9 scale as previously described (Line and Qayoum 1992). The tests were repeated three times to ensure reliability of the IT data.

Field experiments
The field experiments were first scored for stripe rust response during April at Jiangyou (JY) in Sichuan province and May at Yangling (YL) in Shaanxi province during both 2017-2018 and 2018-2019, and June at Tianshui (TS) in Gansu province during 2018-2019, when AvS and XY22 had reached approximately 80% severity. An individual trial at each site in each year was considered a single environment and the 161 F 6 RILs were evaluated in the five environments and three field nurseries. AvS, XN3517, and lines carrying Yr29 [i.e., Pavon 76, Sujata, Attila, and Avocet-Yr29] were included as checks. The locations in Sichuan and southern Gansu experience cool, wet weather that is ideal for natural stripe rust survival and spread. Trials at Yangling were inoculated with a mixed urediniospores of prevalent races ((PST-Lab.1, PST-Lab.2 and PST-V26) suspended in a lightweight mineral oil (1:300) and sprayed onto MX169 and XY22 at jointing stage. RILs in all trials were arranged in randomized complete blocks with two replicates. Each line at each location was sown as 30 seeds per 1 m row with 30 cm between rows. A mixture of susceptible spreaders MX169 and XY22 was sown to favor disease development and spread. Lines were assessed for IT and DS. IT was recorded using a 0 (resistant) to 9 (susceptible) scale (Line and Qayoum 1992); disease severity was scored based on the modified Cobb Scale (Peterson et al. 1948). Non-segregating lines were recorded as single values; segregating lines were scored as two or more values that were later averaged to reach a final value. Disease assessment was made at least twice, and the highest IT and disease severity (DS) were used for phenotypic and QTL analyses.

Phenotypic analysis
Based on the mean IT and DS data for RILs across each environment, analysis of variance (ANOVA) was used to determine the effects of genotype (G), environment (E), and G × E interaction. Pearson's correlation coefficient (r) analysis and ANOVA were conducted using the "AOV" function in QTL IciMapping software 4.1 with the default parameters (Meng et al. 2015). Estimation of broad-sense heritability (h2 b) of resistance used the equation h2 b = σ2 g/(σ2 g + σ2 ge/e + σ2 ε/re), where σ2 g, σ2 ge and σ2 r represented for genotypic (RILs), G × E and error variances, respectively, and e and r were the numbers of environments and replicates. In addition, the mean values of phenotypic data from all five environments in IT and DS were used to evaluate the genetic effects and detect QTL.

SNP calling and clustering
Pooled genomic DNA from the parents and RILs of approximately 10-15 plants per line at the jointing stage was extracted by the CTAB protocol (Clarke et al. 2009), and DNA quality was assessed using a NanoDrop ND-2000 (Thermo Scientific, Wilmington, DE, USA). The RILs and parents were genotyped using wheat 16 K SNP array. In addition, the parents and equal amounts pooled DNA from 25 resistant lines (IT 1-2, DS ≤ 10) and 27 susceptible lines (IT 8-9, DS ≥ 80) were used for BSE-Seq. The wheat 16 K SNP array and BSE-Seq experiment were from Mol Breeding (Shijiazhuang in Hebei province; http:// www. molbr eeding. com). The wheat 660 K SNP array from CapitalBio Corporation (Beijing; http:// www. capit albio. com) was used to genotype the parents. The distribution of SNPs identified by the 16 K array is shown in Table S1. The procedure for marker clustering was performed as described by Huang et al. (2021).

Linkage map construction and QTL analysis
A linkage map was constructed using marker data from the wheat 16 K SNP array. Chi-squared (χ2) tests for goodness of fit of 1:1 segregation ratio were performed for each SNP before processing by including markers with < 10% missing values and major allele frequencies (MAF) ≤ 95% (P > 0.001). The linkage map was generated using the remaining SNPs after proceeding the "BIN" and "MAP" functions using IciMapping V4.2, and drawn in Mapchart V2.3 (Meng et al. 2015;Voorrips 2002). Recombination fractions were converted to centiMorgans (cM) using the Kosambi function (Kosambi 1943). The phenotypic variances explained (PVE) by individual QTL and additive effects at the LOD peaks were also obtained. The phenotypic data including IT and DS values from all environments were used to identify QTL. Inclusive composite interval mapping with the additive tool (ICIM-ADD) in IciMapping V4.2 was performed to detect QTL. The phenotypic variances explained (PVE) by individual QTL and additive effects at the LOD peaks were obtained. To further narrow down the flanking intervals of target loci, significant SNPs from BSE-Seq and 660 K SNP array were converted into allele-specific quantitative PCR (AQP) markers to genotype the RIL population.

Phenotypic evaluation
XN3517 was resistant to PST-Lab.1 (IT 2-3), PST-Lab.2 (IT 2-3), and PST-V26 (IT 4-5) at the greenhouse seedling test and the adult plant stage in the field tests, whereas AvS was susceptible (IT 8-9) (Fig. 1). Both IT and maximum disease severity (MDS) data for the RILs showed normal distributions (Fig. S1), indicating that resistance in XN3517 was quantitatively inherited. Pearson's correlation coefficients of pairwise comparisons for IT and DS ranged from 0.68 to 0.89 and 0.72-0.90 (P < 0.001) ( Table 1), respectively. Broad-sense heritabilities for both IT and DS were 0.94 (Table 2). P values in the ANOVA for IT and DS values showed significant variation (P < 0.0001) among RILs, environments, and line × environment interactions. However, the lack of significant variation between replicates suggested that resistance was the main source of phenotypic variation (Table 2). These results indicated that the expression of QTL controlling ASR and APR in XN3517 was consistent across all five environments.  Using the △SNP-indices from BSE-Seq data we detected the same target regions as for the ICIM method (Fig. 2). All the QTL were derived from XN3517 (Table 3).

QTL combinations
The effects of individual QTL and QTL combinations were investigated by classifying the RILs into 12 genotypic groups based on the field tests. RILs with four QTL QYrXN3517-1BL, QYrXN3517-2AL, QYrXN3517-2BL, and QYrXN3517-6BS were more resistant (lower IT and DS) than all others groups displaying almost similar levels of resistance to XN3517.
When present alone or in pyramids QYrXN3517-1BL showed the highest reductions in IT and DS (Fig. 3, Table S5).

A high-density genetic map of QYrXN3517-1BL and marker-assisted selection
QYrXN3517-1BL, f lanked by markers 16 k-2430 (668,939,708 bp) and 16 k-2443 (680,192,269 bp), was initially mapped at 10.8 cM following genotyping by the GenoBaits Wheat 16 K Panel (Fig. 4A). We then identified many RILs with recombination events in the region. Based on the data of BSE-Seq and 660 K array, nine new significant AQP markers were used for fine mapping (Fig. 4B, C). We also added the previously identified markers csLV46G22 (Yr29) and ucw.k31 (QYr.ucw-1BL) to the genetic map. The QYrXN3517-1BL and QYr.ucw-1BL or Yr29 were presented in different genetic and physical regions (Fig. 4C, D)

Validation of the causal candidate location and marker-assisted selection
SNP markers tightly linked to QYrXN3517-1BL were converted to the high-throughput, cost-effective SNP genotyping format known as AQP for use by geneticists and breeders. To determine the robustness of identifed marker nwafu. a5 for QYrXN3517-1BL in XN3517, genotyping of the 760-accession panel suggested it was signifcantly (P < 0.01) associated with stripe rust response (Mean DS data) of the wheat panel during 2018-2019 cropping season in YL, TS, and JY ( Fig. 6; Table S1). The KASP markers AX-89744149 and nwafu.a5 sequences are given in Table S6.

Annotated genes in the QYrXN3517-1BL candidate region and expression analysis
Based on wheat 16 K, 660 K and exome capture data, we mapped QYrXN3517-1BL within an interval of 1.7 cM [336 kb in International Wheat Genome Sequencing Consortium (IWGSC) RefSeq version 1.0] on chromosome 1BL. The 336-kb candidate region between the markers AX-89744149 and nwafu.a5 included 12 high confident (HC) annotated genes ( Fig. 4D; Table S7). The proteins produced by these 12 genes included one nucleotide-binding (NB) and leucine-rich repeat (LRR) proteins, one GDSL-like lipase/ acylhydrolase superfamily protein, four additional lipid transfer proteins, two additional Polyol transporters, one B-block binding subunit of TFIIIC, one agenet and bromoadjacent homology (BAH) domain-containing protein, one pfkB-like carbohydrate kinase family protein, and one cardiolipin synthase B.

Discussion
New Pst pathogenic groups such as race CYR34 (Yr26-virulent) that appeared after 2008 are reported to be more aggressive and to have broader virulence profiles (Bai et al. 2018;Han et al. 2015;Liu et al. 2010). The race PST-V26 with a broad virulence originated from race CYR34; PST-Lab.1 and PST-Lab.2 originated from two different collections of race CYR32 (Huang et al. 2021). Wheat line XN3517 has been highly resistant to stripe rust in all field experiments and commercial production fields since its release in 2008.
In the present study, three QTL conferring APR and one QTL for ASR in XN3517 were identified, including a major QTL on 1BL and minor-effect QTL on 2AL, 2BL and 6BS.
The study clearly showed that the high level of resistance in XN3517 was conferred by the combination of one all-stage and three APR genes of varying individual effects.
Catalogued genes Yr3, Yr5, Yr7, Yr43, Yr44, and Yr53, conferring ASR, are located on chr. 2BL (Maccaferri et al. 2015;Chen and Kang 2017). Based on the seedling and field mapping results, QYrXN3517-2BL, consistently mapped between the markers 16 k-5738 and 16 k-5754 by IT and DS data (Table 3). Of these genes, only Yr5 conferred resistance to the isolate PST-V26 (IT '0') (Huang et al. 2021), but lines with QYrXN3517-2BL produced IT '3-4' with only moderate effects on APR. In contrast Yr5 confers immunity both at seedling and in adult plants to the Pst races used in field trials. Based on the clearly different infection types in seedlings and resistance in field, QYrXN3517-2BL is a new gene.
Several resistance genes/QTL are located on the short arm of chromosome 6B, including Yr35, Yr36, and Yr78. Several APR QTL such as QYrMa.wgp-6BS in Madsen, QYrsn. nwafu-6BS in Shaannong 33, QYr.wgp-6B.1 in Stephens, QYr.sun-6BS in Janz, and QYrCW357-6BS in Changwu 357-9 were shown to be Yr78 (Dong et al. 2017;Liu et al. 2018;Huang et al. 2021Huang et al. , 2022 Candidate gene annotation in the QYrXN3517-1BL candidate regions based on RefSeq v1.0 Twelve HC genes have annotated functions in IWGSC Ref-Seq version 1.0 in the candidate region, and these genes were shown to have high genomic synteny using 10 + wheat genomes (http:// wheat. cau. edu. cn/ TGT/) data (Fig. S2). Based on the genes annotated functions, five genes including TraesCS1B01G460000, TraesCS1B01G460100, TraesCS1B01G460200, TraesCS1B01G460300, and TraesCS1B01G460400 were most probably related to the stripe rust resistance. Of these genes, TraesCS1B01G460000, TraesCS1B01G460200, TraesCS1B01G460300, and TraesCS1B01G460400 encode a lipid transfer protein, which functioned in energy metabolism that is similar with Yr36. TraesCS1B01G460100 encodes disease resistance protein (NBS-LRR class) family, which probably confer potential race-specific resistance to pathogens with features of classical R-genes. It is also possible that the causal gene is absent in the CS reference genome.

In conclusion
The stripe rust resistance conferred by the combination of QYrXN3517-1BL, QYrXN3517-2AL, QYrXN3517-2BL, and QYrXN3517-6BS has remained effective in the field for more than a decade. Although we found that QYrXN3517-1BL and Yr29 were in different genetic and physical locations, the possibility that they are the same gene could not be excluded. Sequencing the genome including QYrXN3517-1BL and Yr29 candidate region from wheat cultivars that carry the QYrXN3517-1BL and Yr29 resistance allele, and analysis of resistance to leaf rust or powdery mildew are required for validation. QYrXN3517-1BL from wheat cultivar XN3517 and its closely linked molecular marker nwafu. a5 can be used in marker assisted breeding to achieve durable resistance.