Introduction

Spring wheat is a major cereal crop of Pakistan (GOP 2020). The genetic improvement is the result of global wheat improvement efforts, but currently its production is stagnant and further enhancement is confronted by biotic (rusts, smuts and powdery mildew) (Rattu et al. 2011) and abiotic (terminal heat, salinity, drought, hailstorms, winds, fogs, and extreme cloud cover during cropping season) stresses (Jellis 2009). The rust diseases pose a severe biotic stress to wheat productivity caused by the members of genus Puccinia (Hovmøller et al. 2010; Zeng et al. 2019), it is also a major threat to Pakistani wheat (Babar et al. 2010). The stripe rust disease induced by a fungus Puccinia striiformis f. spp. tritici is a devastating disease of wheats grown in the temperate climate (Wellings 2011; Beddow et al. 2015; Ayliffe and Soerensen 2019), it reduces wheat production up to 70% (Chen 2007). Because of its epidemics inflicted during 2005 and 2012 in Pakistan, high yielding wheat varieties became susceptible (Hussain et al. 2015). Similarly, the Puccinia graminis f. spp. Tritici (Pgt) produces stem rust (Saari and Prescott 1985), a destructive disease of wheat causing 48–50% yield losses (Sokoet al. 2018). While, Puccinia triticina produces leaf rust, regarded as a significant problem of wheat in different countries (Singh et al. 2008). Wheat leaf rust resulted in yield loss up to 74% when plants are infected at the initial stages of their growth (Herrera-Foessel et al. 2006).

To cope with wheat rust pathogen several methods are in practice, application of fungicides is costly, unfriendly to the environment and leads to the development of pathogen resistance (Chen 2007). The genetic resistance is considered as an economical, effective, long-term, and eco-friendly approach (Liu et al. 2019). It can be used as a long-term tactic to avoid crop losses. Therefore, wheat rust damage can be avoided by identifying effective rust resistant gene(s) (Babar et al. 2010) and their deployment in future wheat cultivars. Gene postulation as well as molecular markers could be utilized to enhance wheat rust resistance by the detection of high-temperature adult-plant stage rust resistance genes and pyramiding them in a single cultivar (Lagudah et al. 2009). New evidence suggested that the durable or non-host resistance prohibit the pathogens to colonize the plants because of the molecular incompatibility among the pathogenic factors and cellular target sites of host plant. The non-host resistance is durable and remains effective for a longer duration (Ayliffe and Soerensen 2019).

Disease resistant genes provide durable resistance against pathogen and their detection by the use of molecular markers makes the selection easy. The SSR markers are widely used short tandem repeats, abundantly exist in the entire genome and more polymorphic than any other marker systems (Miah et al. 2013). Automation and co-dominant behaviour are additional benefits when compared to other markers (Mornkham et al. 2016). Several studies have been utilized to illustrate the application of phenotypic and molecular approaches for the identification of rust resistant alleles in wheat germplasm collections, but a few of the earlier reports aimed at the spring wheat varieties grown in Pakistan. In the present study, we utilized a group of 26 spring wheat varieties representing both recent and old varieties using the phenotypic and molecular data for the already reported alleles. The specific objective was to identify rust resistance genes utilized in these varieties, especially to detect genes that were not formerly reported and to report durable rust resistance sources. The other objectives included phenotyping of varieties for yellow rust resistance. The durable resistance sources and alleles should be beneficial for the development of future cultivars with effective resistance, this genetic material should be utilized immediately for the disease management.

Materials and Methods

The authenticated seed of 26 elite spring wheat varieties were obtained from Barani Agricultural Research Institute-Chakwal, National Agriculture Research Center-Islamabad, and Ayub Agricultural Research Institute-Faisalabad (Table 1).

Genotyping with SSR markers

For the extraction of genomic DNA, seed were grown in pots comprising of a mixture of leaf compost and sandy loam topsoil in equal amount. The seedlings germinated inside an incubator (Memmert-GmbH) at 24°C in the department of Plant Breeding and Molecular Genetics and later transferred to greenhouse, watered regularly, and kept at 24°C. The seedlings were harvested at 3 leaf stages and stored at -80°C (SANYO-Japan, MDF-293). The genomic DNA was isolated from seedlings by means of CTAB method of Doyle and Doyle (1987) with a little modification. The confirmation of genomic DNA was done by electrophoresis using 0.8% agarose gel, followed by quantification with the help of UV-VIS spectrophotometer (Shimadzu, UV-1201). A 10x dilution of the genomic DNA was prepared to enhance the volume and ease of mixing. The genomic DNA comprising 50 ng/μL was used for PCR.

Twelve SSR primers were utilized to screen rust resistant alleles (Table 2). The primer sequences were acquired online from MAS wheat UCDAVIS (http://maswheat.ucdavis.edu). The PCR reaction was carried out in a 10 µL reaction comprising 0.5 µL genomic DNA, pre-mix (Thermo Scientific^TM) 5.78 µL, double distilled water 5.70 µL and 0.4125 µL of primers both reverse and forward. The PCR reactions were carried out inside a Thermo cycler (BioRad MJ Mini) with protocols given in Table 2. The PCR products of CAPS marker S30-13 were washed, re-precipitated and restricted using BamHI. The 10x reaction buffer (2 μL) and 0.5 μL of BamHI (Thermo Scientific^TM) were added to re-suspended PCR product and incubated at 37^oC for 30 min. The PCR products were confirmed on 2.5% agarose gel (Invitrogen UltraPure^TM, USA). For the quantification of bands on agarose gel, 5 µL of 100bp DNA ladder (Thermo Scientific™) was used. In the end, the gels were photographed for genetic analysis inside a UVIDOC gel documentation system (UVITEC, UK).

Field testing and phenotyping

The varieties were phenotyped for reaction to yellow rust under natural conditions at University of Poonch Rawalakot (Latitude: 33°51'28.15"N, longitude: 73°45'37.55"E, elevation: 1737 m) for 03 seasons i.e., 2016–2017, 2017–2018 and 2018–2019. The trials were non-replicated and planted as single row per entry (1.0 m long and 30 cm apart), with susceptible spring wheat variety ‘Morocco’ as an inoculum spreader. The Morocco was planted in rows perpendicular and adjacent to the rows as Wei et al. (2015). The natural infection permitted us to record data on stripe rust disease without artificial inoculation as Cheng et al. (2014). Ten flag leaves were randomly selected form each variety when the leaves of Morocco were fully infected and the grains were at the milk stage (Feekes 10.54–11.1). Disease surveys were repeated twice with 10 days interval. The infection and disease severity were scored according to the modified Cobb scale (Peterson et al. 1948). The disease severity of varieties was observed as single value and later averaged for each variety as Zeng et al. (2019).

Table 1: List of spring wheat varieties used for phenotypic and molecular characterization of rust resistance

S. No.	Varieties	Sr. No.	Varieties	S. No.	Varieties
1.	Attila	10.	Mehran 89	19.	Pirsabak 2004
2.	Blue Silver	11.	Bakhtawar 93	20.	Pirsabak 2005
3.	Sarsabz	12.	Noshera 96	21.	Raskoo 2005
4.	PBW 343	13.	BWL 97	22.	Fareed 2006
5.	Yecora 70	14.	Chakwal 97	23.	Sehar 2006
6.	Lylpure 73	15.	BWL 2000	24.	Lasani 2008
7.	Tandojam 83	16.	Wafaq 2001	25.	Chakwal 50
8.	Punjab 85	17.	Bakhar 2002	26.	Panjab 11
9.	Chakwal 86	18.	SH 2002

Table 2: The primers used to detect wheat rust resistance alleles in 26 spring wheat varieties

Gene	Primer	Sequence of primers (5'-3')	Reference
Lr32	WMC43	TAGCTCAACCACCACCCTACTG	Thomas et al. (2010)
		ACTTCAACATCCAAACTGACCG
Lr39	GDM35	CCTGCTCTGCCCTAGATACG	Cox et al. (1994)
		ATGTGAATGTGATGCATGCA
Lr46	GWM259	AGGGAAAAGACATCTTTTTTTTC	Suenaga et al. (2003)
		CGACCGACTTCGGGTTC
Lr50	GWM382	GTCAGATAACGCCGTCCAAT	Brown-Guedira et al. (2003)
		CTACGTGCACCACCATTTTG
Lr51	S30-13L	GCATCAACAAGATATTCGTTATGACC	Dvorak (1977)
		TGGCTGCTCAGAAAACTGGACC
Lr67	Xcfd71-4D	CAATAAGTAGGCCGGGACAA	Singh et al. (2008)
		TGTGCCAGTTGAGTTTGCTC
Sr28 Flanking Markers	wPt-7004-PCR	CTCCCACCAAAACAGCCTAC	Rouse et al. (2012)
		AGATGCGAATGGGCAGTTAG
	WMC332	CATTTACAAAGCGCATGAAGCC	Rouse et al. (2012)
		GAAAACTTTGGGAACAAGAGCA
SrCad	FSD_RSA	GTTTTATCTTTTTATTTC	Hiebert et al. (2010)
		CTCCTCCCCCCA
SrWeb	GWM47 (WMS47)	TTGCTACCATGCATGACCAT	Hiebert et al. (2010)
		TTCACCTCGATTGAGGTCCT
Yr17	VENTRIUP-LN2	AGGGGCTACTGACCAAGGCT	Helguera et al. (2003)
		TGCAGCTACAGCAGTATGTACACAAAA
Yr18	csLV34	GTTGGTTAAGACTGGTGATGG	Lagudah et al. (2009)
		TGCTTGCTATTGCTGAATAGT

Statistical analysis

The band size was assessed with the help of UVI-soft Image Analysis Software, Version 12.8 for Windows. Then the existence and non-existence of the DNA fragments visualized on gel was written in a binary data matrix in MS Excel sheet. Depending upon the effects of electrophoretic fragment spectra, the cluster diagram was prepared using Unweighted Pair Group Method with Arithmetic Mean (UPGMA) algorithm with the help of computer software MEGA5 (Tamura et al. 2011).

Results

Twelve microsatellite markers related to 11 rust resistance alleles were utilized to identify the Yr, Lr and Sr alleles in the 26 spring wheat varieties (Table 2). The molecular markers showed that the Lr32 allele was found in three wheat varieties Tandojam-83, Punjab-85 and Chakwal-86, it conferred a race-specific resistance (Fig. 1a). In addition, 03 alleles Lr39, Lr50 and Lr51 were not present in the twenty-six varieties. The Lr46/Yr29 allele was the most prevalent, found in 13 varieties like Bakhtawar-93, Noshera-96, BWL-2000, BWL-97, Chakwal-97, Bakhar-2002, Pirsabak-2004, SH-2002, Pirsabak-2005, Punjab-11, Raskoo-2005, Sehar-2006, and Lasani-2008. The slow rusting allele Lr67/Yr46 was identified in Noshera-96 using the molecular marker test.

The WMC332 marker amplified Sr28 allele in three varieties viz., BWL-2000, SH-2002 and Raskoo-2005 while that of wPt-7004-PCR marker was found in Pirsabak-2005 (Fig. 1b and c). The SSR markers also indicated that stem rust resistance alleles SrCad and SrWeb were absent among the tested varieties (Fig. 1d). The presence of Yr17 allele was not high in the tested varieties; however, it was identified in BWL-97. Similarly, Yr18/Lr34 was present in Attila, Sarsabz, Chakwal-97, Bakhar-2002, Fareed-2006, and Lasani-2008 (Fig. 1e). However, Yr18/Lr34 can present low infection type in combination with all-stage resistance alleles. The allele has conferred leaf rust resistance in excess of 50 years and is extensively used in wheat breeding (McIntosh et al. 1995; Krattinger et al. 2009; Wei et al. 2015).

The molecular data of rust resistance alleles were validated by field testing for 03 consecutive Rabi seasons (Table 3). The varieties Chakwal-86, Pirsabak-2005, Fareed-2006, Sehar-2006 showed moderate resistance under field tests. These findings suggested the existence of at least 01 adult-plant resistance (APR) allele in the varieties. Molecular markers showed that resistance conferred by Pirsabak-2005, Fareed-2006 and Sehar-2006 was conditioned by APR alleles, but Chakwal-86 did not contain currently used APR markers, suggesting that the slow rusting in this variety was conditioned by other APR allele(s). While Yecora-70 (80S), Lylpure-73 (90S) and Tandojam-83 (90S) showed highly susceptible phenotype (IT) depicting the absence of effective Yr alleles against prevalent pathotypes at the adult stage. Most of the varieties contain slow rusting alleles produced moderately susceptible response.

Table 3: Rust resistance alleles observed in spring wheat varieties via SSR markers and their 03 years field response against stripe rust

S. No	Varieties	Alleles Identified through SSR Markers	Yr Response
S. No	Varieties	Alleles Identified through SSR Markers	2016-2017	2017-2018	2018-2019
1	Attila	Yr18/Lr34	40MS	30MS	50MS
2	Blue Silver	-	60MSS	20MSS	60MSS
3	Sarsabz	Yr18/Lr34	70MS	60MS	80MS
4	PBW-343	-	40MSS	30MSS	40MSS
5	Yecora-70	-	40S	60S	80S
6	Lylpure-73	-	50S	90S	60S
7	Tandojam-83	Lr32	70S	90S	60S
8	Punjab-85	Lr32	70MSS	60MSS	70MSS
9	Chakwal-86	Lr32	30RMR	40RMR	50RMR
10	Mehran-89	-	30MSS	90MS	60MS
11	Bakhtawar-93	Lr46/Yr29	80MS	10MS	70MS
12	Noshera-96	Lr46/Yr29, Lr67/Yr46	60MS	80MS	70MS
13	BWL-97	Lr46/Yr29, Yr17	40MS	60MS	40MS
14	Chakwal-97	Lr46/Yr29, Yr18/Lr34	5MSS	10MSS	60MSS
15	BWL-2000	Lr46/Yr29, Sr28 (WMC332)	20MS	5MS	20MS
16	Wafaq-2001	-	30MSS	40MSS	80MSS
17	Bakhar-2002	Lr46/Yr29, Yr18/Lr34	70MS	20MS	50MS
18	SH-2002	Lr46/Yr29, Sr28 (WMC332)	80MSS	60MSS	80MSS
19	Pirsabak-2004	Lr46/Yr29	20MSS	40MSS	50MSS
20	Pirsabak-2005	Lr46/Yr29, Sr28 (wPt-7004-PCR)	5MR	10MR	40MR
21	Raskoo-2005	Lr46/Yr29, Sr28 (WMC332)	30MSS	40MSS	60MSS
22	Fareed-2006	Yr18/Lr34	10RMR	5RMR	30MR
23	Sehar-2006	Lr46/Yr29	20MR	20MR	60MR
24	Lasani-2008	Lr46/Yr29, Yr18/Lr34	10MS	70MS	60MS
25	Chakwal-50	-	40MSS	60MSS	70MSS
26	Panjab-11	Lr46/Yr29	50MSS	90MSS	60MSS

The cluster diagram based on molecular evidence for wheat rust resistance genes could be divided into 02 distinct clades, I and II (Fig. 2). The clade I could be sub-divided into 03 distinct clusters, the sub-cluster 1 comprised of the varieties in which all the alleles under study were absent. The varieties in sub-cluster 2 had Yr18/Lr34, a slow rusting allele while the varieties of sub-cluster 3 had a seedling resistance allele (Lr32). The clade II constituted the most important group of varieties showing preponderance of Lr46/Yr29 allele. The cluster 2

Fig. 1: The PCR products obtained from allele specific markers: Lr32 (a), Sr28 (b, c), SrWeb (d) and Yr18/Lr34 (e) in the 26-spring wheat varieties

Fig. 2: Tree diagram constructed for 26 spring wheat varieties using presence/absence matrix obtained from 11 SSR primers

could be categorized into 05 sub-clusters, the sub-cluster 1 represented Pirsabak-2005 including slow rusting allele Lr46/Yr29 and an unconfirmed Sr28 allele, amplified by primer wPt-7004-PCR, the amplification of another flanking marker was not observed. The resistance conferred by varieties in sub-cluster 2 was furnished by two durable rust resistance alleles Lr46/Yr29 and Yr18/Lr34; it was the most important group of varieties to be utilized for the incorporation of durable rust resistance in future wheat varieties. The sub-cluster 3 stemmed into a single variety Noshera-96 containing another important combination of durable rust resistance comprised of the Lr46/Yr29 and Lr67/Yr46 alleles. The sub-cluster 4 characterized three varieties including Lr46/Yr29 and Sr28 alleles, the Sr28 was amplified only in primer WMC332, while the PCR amplification of other flanking marker was missing. The sub-cluster 5 characterized the variety BWL-97 including non-host durable resistance alleles Lr46/Yr29 and Yr17, could be used as a source of durable rust resistance alleles.

Discussion

A set of 26 wheat varieties was screened for resistance against wheat stem rust, stripe rust, and leaf rust diseases using 12 SSR markers. The marker WMC-43 produces a 346bp fragment linked to the occurrence of Lr32 allele (Thomas et al. 2010), only Tandojam-83, Punjab-85 and Chakwal-86 amplified the correct band (Fig. 1a.). Thomas et al. (2010) reported that the influence of Lr32 includes: test weight, yield increase, straw strength, grain size and hardness. The allele has shown worldwide resistance, but virulence has been spotted in South Africa (Singh 1991; Pretorius and Bender 2010). The primer GDM-35 was used to identify Lr39 allele among the tested varieties. The 185bp band indicates the presence of Lr39 gene (Cox et al. 1994) but the PCR products ranged from 206 to 255bp indicating the absence of allele.

The GWM259 amplifies a PCR fragment of 100–120 bp indicating the presence of slow rusting allele Lr46/Yr29 (Suenaga et al. 2003). This allele was the most prevalent reported in 13 varieties constituting 50% of the varieties. Similarly, the primer GWM-382 was used for the identification of Lr50, it amplifies 139bp diagnostic allele (Brown-Guedira et al. 2003). But the alleles ranging from 623bp to 768pb were amplified indicating absence of allele. A combination Lr50 and other alleles could be used as a leaf rust management strategy (Brown-Guedira et al. 2003). The Lr51 was amplified by the CAPS marker S30-13L primer, amplifies 672-bp and 111-bp alleles (Dvorak 1977). The Lr39, Lr50 and Lr51 are useful all-stage resistance alleles, their virulence has been observed in some parts of the world, but they are effective in combination with APR alleles (Raupp et al. 2001; Huang and Gill 2001). The PCR products of correct size for Lr39, Lr50 and Lr51 alleles had not been observed in the varieties suggesting the absence of alleles. After PCR amplification the Lr67/Yr46 produces 214 bp product (Singh et al. 2008). Since this APR allele was present in Noshera-96 it could be utilized as a source for future breeding.

The flanking markers, wPt-7004-PCR and WMC332, were utilized to identify the existence of the Sr28 allele (Fig. 1b and c). Because of the partial resistance conferred by Sr28 allele, it is recommended as a part of gene pyramiding strategy. The PCR products of 220, 217 and 214bp for marker WMC332 linked to the Sr28 allele were produced. While a 194bp band associated with wPt-7004-PCR indicated the existence of Sr28 allele (Rouse et al. 2012). The stem rust resistance conferred by Sr28 allele shows a low IT at seedling stage (Jin et al. 2007). The WMC332 allele was amplified in BWL-2000, SH-2002, and Raskoo-2005. While, wPt-7004-PCR allele was present in Pirsabak-2005. Since both the alleles amplified by flanking markers were not present in any of the varieties, therefore they are not recommended to be used as a source of Sr28 allele.

The SrCad allele produces low infection type against stem rust resistance when combined with Yr18/Lr34 allele, otherwise it offers moderate resistance against the Ug99 and related stem rust races. While, the GWM47 marker mapped near Sr9 on chromosome 2BL, is utilized to identify SrWeb allele that presents resistance against Ug99. The allele size for WMS47 is 207 bp (Hiebert et al. 2010). But the tested varieties yielded a DNA band of 275 bp suggesting the absence of allele (Fig. 1d).

The primers VENTRIUP-LN2 and csLV34 were utilized to identify the slow rusting alleles Yr17 and Yr18/Lr34 respectively. The slow rusting allele Yr17 was less prevalent among the varieties found only in BWL-97. More varieties must be explored to identify the sources for this allele for future breeding. Similarly, the csLV34 amplifies a 150 bp positive allele and a 229 bp product which is a null allele (Lagudah et al. 2009; Awan et al. 2017). The allele was of moderate occurrence observed in Bakhar-2002, Attila, Sarsabz, Fareed-2006, Chakwal-97 and Lasani-2008 (Fig. 1e).

Identification of stripe rust resistance alleles and hybridization of resistant lines is an efficient technique to reduce rust susceptibility in wheat (Li et al. 2006). The objective of wheat breeding targeting rust resistance is to obtain durable genetic resistance, found in adult-plant stage slow-rusting alleles (Singh et al. 2008; Liu et al. 2020). When wheat cultivars with all-stage rust resistance are cultivated over a large area, selection pressure is exerted on the pathogen to mutate and produce new races to the break the resistance of host plant (Khan et al. 2011; Brar and Kutcher 2016). Gene stacking or merging many resistance alleles into a single cultivar can be used to produce durable resistance so that the pathogen can not overcome it easily (Ali et al. 2018). Therefore, a continuous search for new alleles for rust resistance is needed (Jiang et al. 1994; Abebele and Admasu 2020).

Half of the varieties indicated the incidence of Lr46/Yr29 allele offering high-temperature resistance. The latency period of the infected plant increases when it carries Lr46/Yr29 allele. In addition, it causes an early abortion of fungal colonies and produces a low IT but the resistance conferred is reduced in effect when compared to Yr18/Lr34 allele (Martinez et al. 2001). Five varieties constituting 19.23% showed slow rusting allele Lr46/Yr29 in combination with other durable resistance alleles (Table 3). The virulence against Yr17 and Yr18/Lr37 has been reported (Helguera et al. 2003; Sufyan et al. 2021) they confer moderate resistance against different physiological races and are used in combination with other rust resistance alleles. The allele Yr17 was found in BWL-97 in combination with Lr46/Yr29. The Yr18/Lr34 allele provides APR against wheat stripe/leaf rust disease and powdery mildew (Pm38) as reported by Juliana et al. (2015). Its genetic mechanism is specified as an ABC transporter (Martinez et al. 2001). The Yr18/Lr37 in combination with Lr46/Yr29 allele was present in varieties Chakwal-97, Bakhar-2002 and Lasani-2008. The Lr67/Yr46 is an APR allele that provides a lesser level of leaf rust protection compared to Yr18/Lr34 allele (Lagudah et al. 2009). It has been reported that Lr67/Yr46 also confers APR to stem rust and powdery mildew in wheat (Herrera-Foessel et al. 2014; Esse et al. 2020). The Noshera-96 having allele Lr67/Yr46 in combination with Lr46/Yr29 could be a valuable source of APR for future cultivars.

Most of the varieties showed moderately susceptible phenotype at adult plant stage under Rawalakot conditions but the varieties viz., Chakwal-86, Pirsabak-2005, Fareed-2006 and Sehar-2006 were moderately resistant to the prevailing stripe rust races of Rawalakot. Fayyaz et al. (2019) also indicated moderate resistance in these varieties. Our molecular test indicated the prevalence of horizontal resistance alleles, similarly field test depicted a low infection types in these varieties. The complete susceptibility of Yecora-70, Lylpure-73 and Tandojam-83 (Table 3) was supported by Singh and Rajaram (1992) who reported susceptibility in Yecora-70, while Afzal et al. (2010) described Tandojam-83 and Lylpure-73 as susceptible.

The APR genes were effective in producing low infection type in combination with other minor genes, showing moderately susceptible reactions. The Yr18/Lr34 showed lesser susceptibility compared to Lr46/Yr29 allele, as indicated by Martinez et al. (2001). The combination of durable resistance alleles like Lr46/Yr29, Yr18/Lr34 produced low infection type in varieties Lasani-08, Bakhar-2002 and Chakwal-97. Similarly, the slow rusting combination of Lr46/Yr29 & Lr67/Yr46 in Noshera-96 and Lr46/Yr29 & Yr17 in BWL-97 was effective in producing low IT.

Cluster analysis is the name given to a set of techniques which indicates whether data can be grouped into categories based on the similarities or differences (McIntosh et al. 2010; Shengping and Berdine 2018). Cluster analysis based on molecular data is considered useful in identifying genetic diversity and similarities among wheat cultivars (Sobia et al. 2010). The cluster diagram based on presence and absence of alleles indicated two distinct clades (Fig. 2). The clade 1 could be divided into three sub-clusters while clade 2 could be categorized into five sub-clusters. Both the clusters contained equal number of varieties; the varieties of cluster II were comparatively more valuable due to the presence of durable rust resistance alleles.

Conclusion

In summary, using the combination of gene-tagging markers, we detected several alleles for resistance to rust diseases in the panel of 26 spring wheat varieties mainly used in Pakistan and identified them in individual entries. Most of the alleles produced non-race-specific APR. The durable resistance sources will enrich the resources of wheat rust resistance. The effectiveness of each previously reported alleles was assessed, and the cumulative effect of Yr18/Lr34, Lr46/Yr29, Yr17 and Lr67/Yr46 genes was found effective in reducing disease severity. Accumulating multiple rust resistance alleles produced low infection type. However, more effective alleles conferring different types of resistance should be selected in different combinations for incorporation into new wheat cultivars. The identified sources of resistance like Chakwal-97, Bakhar-2002, Lasani-2008, BWL-97 and Noshera-96 should be useful in marker-assisted-selection for incorporating combinations of alleles. Since most of the alleles identified in the present study are present in adapted varieties, their deployment into new cultivars will be relatively easy.

Acknowledgement

Authors would like to acknowledge the Department of Molecular Plant Pathology, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University-UK for providing reagents and Crop Disease Research Institute, National Agriculture Research Center-Islamabad, Ayub Agricultural Research Institute-Faisalabad and Barani Agricultural Research Institute-Chakwal for providing the authenticated seed of wheat varieties.

Author Contribution

Shahid Iqbal Awan designed the experiment. Anisa Intikhab performed field experiments and wrote the initial manuscript. Luis AJ Mur provided input on data analysis. Muhammad Sajjad Saeed provided input on planning of field experiments. Muhammad Shahzad Ahmed curated the molecular data and provided input on collection of field data. All authors contributed to the final draft.

Conflict of Interest

The authors declare that they have no conflict of interest.

Data Availability

Data are available from the authors on request.

Ethics Approval

The research work was conducted after approval from the Human & Animal Ethics Committee of the University and no humans and animals were investigated.

Funding Source

This research was funded by Promotion of Research Fund, University of Poonch Rawalakot, Azad Kashmir-Pakistan.

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