Avirulence genes identified through linkage mapping and region-specific association studies in the wheat leaf rust pathogen Puccinia triticina

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Joly, Barbara Mulock, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7264203/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Feb, 2026 Read the published version in BMC Genomics → Version 1 posted 11 You are reading this latest preprint version Abstract Background Wheat rust fungi can cause significant damage to wheat crops, leading to reduced yields and economic losses. To combat disease, certain plant varieties can trigger defense responses upon recognition of specific pathogen effector proteins, causing avirulence. Identifying such avirulence ( Avr ) genes is crucial for developing strategies to protect crops from devastating losses, from identifying matching resistance genes to designing diagnostic assays for monitoring pathogen populations. Puccinia triticina ( Pt ) causes wheat leaf rust and is an obligate biotrophic fungus, and because of its life cycle and mode of reproduction, it is difficult to study genetically. Results To identify Avr genes in Pt , a F 2 population of fifty-seven progeny was generated from a sexual cross of race 9 (SBDG) and race 161 (FBDJ) on the alternate host Thalictrum speciosissimum under controlled conditions. The population segregated for avirulent/virulent traits screened at the seedling stage on thirteen single gene resistance lines in the wheat host cultivar Thatcher background. The genomes of the parents, F 1 , and progeny were sequenced and mapped onto an assembled parental race 9 phased haplotype B genome, resulting in the generation of 21,154 high-quality SNP markers suitable for genetic mapping of the F 2 population. A genetic map composed of 61 linkage groups was obtained, containing a total of 10,923 markers, and spanning 10,730.5 centimorgans. Effector loci correlating with avirulence to specific leaf rust resistance ( Lr ) genes, PtAvrLr14a , PtAvrLr11 and PtAvrLr2a , were mapped to chromosome 1, chromosome 3 and chromosome 4, respectively. To strengthen the identification of candidate Avr genes, a region-specific association study was done on a natural population of fifty-nine Pt isolates that were collected in Canada and whose genomes were sequenced using Illumina. Conclusion Significant markers and corresponding candidate effector genes were identified for these mapped Avr loci. The identification of these candidate genes is an essential step towards cloning Avr and subsequentially their matching host resistance genes, and for studying the molecular mechanisms underlying pathogen-host interactions and host defense. Puccinia triticina Avirulence Genetic linkage map Association mapping Wheat leaf rust Whole-genome sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Wheat rust diseases, including stem, leaf and stripe rust, pose a major threat to global wheat production. Among these, wheat leaf rust caused by the fungal pathogen Puccinia triticina Eriks. ( Pt ) is the most common and widely distributed [ 1 , 2 ]. In North America, yield losses ranging from 5–10% are common depending on the wheat variety and growing conditions [ 2 , 3 ]. Although rust diseases can be controlled by fungicides, genetic resistance is the most effective, economical and environmentally sustainable method [ 4 ]. Significant progress has been made in developing resistant wheat cultivars. However, rust fungi evolve rapidly and can often evade plant immune systems, leading to ineffective host resistance [ 5 ]. Therefore, there is great interest in understanding the molecular mechanisms underlying host-pathogen interactions, in particular as they pertain to pathogens evading recognition by host resistance genes. The genetics of plant-pathogen interactions were initially studied by Harold Flor with the flax-rust system and described in the ‘gene-for-gene’ theory [ 6 ]. In this genetic concept, the interaction of specific avirulence ( Avr ) genes in the pathogen with corresponding resistance ( R ) genes in the host activates host defense responses. Various molecular mechanisms underpinning these interactions have been revealed over the last decade. R genes can code for plant receptors on plant cell surfaces responding to Avr effectors secreted by the pathogen in the apoplast, but many R genes encode intracellular immune receptor proteins of the nucleotide binding leucine rich repeat (NB-LRR) class [ 7 – 10 ] that recognize small effector proteins delivered by the pathogen into host cells to suppress host basal defenses and to assist in the establishment of pathogen infection [ 11 , 12 ]. R proteins can interact directly with effector proteins or guard other cellular targets of effectors and indirectly sense their actions [ 13 ]. Since the outcome is pathogen arrest and ‘avirulence’, such effectors correspond to the Avr genes in the genetic concept. In wheat rust fungi, three stem rust pathogen, P. graminis f.sp. tritici ( Pgt ) Avr genes have been successfully cloned, namely AvrSr27 [ 14 ], AvrSr35 [ 15 ] and AvrSr50 [ 16 ]. Several Avr effector candidates for Pt have been reported with two, PtAvrLr15 and PtAvrLr21 identified [ 17 – 22 ]. Functional characterization of such effectors will further our understanding of host-pathogen interactions and allow for more rational deployment of resistance genes in crop resistance breeding. One approach to identify and clone Avr genes is through genetic mapping. This approach has been successfully employed to clone Avr genes of the flax rust fungal pathogen, Melampsora lini [ 23 , 24 ], which is an autoecious fungus. However, wheat rust fungi are heteroecious, meaning they require different host species to complete their life cycle. This makes sexual crosses more difficult to achieve. Pt cycles asexually on wheat but to complete its sexual cycle, requires alternate hosts, Thalictrum species including Thalictrum speciosissimum L. (common meadow rue), which is the most susceptible alternate host of Pt and found in southern Europe and west Asia [ 1 , 25 ]. In North America, Pt reproduces by the continuous production of asexually produced urediniospores and the sexual cycle does not occur naturally since the native North American Thalictrum species have limited susceptibility to infection by Pt basidiospores [ 18 ]. Starting in 1968, Samborski and Dyck conducted a series of studies on the genetics of pathogenicity in Pt . They produced populations of progeny that segregated for avirulence on various wheat cultivars by sexually crossing Pt races. These investigations formed the basis for identifying the genetic background in the generation of the standard differential wheat varieties and led to the early development of several near-isogenic wheat lines specific to leaf rust [ 26 – 28 ]. Since then, Dr. Peter Dyck produced additional near-isogenic wheat lines, allowing for continued and expanded research on the pathogenicity of the wheat leaf rust fungus. The rapid advancement of genome sequencing technologies and data analysis tools have accelerated Avr gene identification and have promoted our understanding of various aspects of rust biology [ 29 , 30 ]. However, compared with most other plant pathogens, rust fungi have larger genome sizes, with assembled genomes ranging from 53 Mbp to 1.25 Gbp [ 31 – 34 ]. In addition, rust fungi have large numbers of up to 93% repetitive sequences and transposable elements (TEs) in their genomes, among the largest known for plant pathogens [ 29 , 34 – 36 ]. Moreover, the biological materials easiest to increase and collect for genomics study are the urediniospores which are dikaryotic with two highly heterozygous nuclei in one cell [ 35 ], making genome assembly particularly challenging. In Pt , a draft genome sequence of race 1 (BBBD) first became available in 2017 [ 37 ]. This genome contained 135 Mb of DNA, with 51% TEs and repetitive elements and an estimated 14,800 genes, which has been useful as a reference genome. In recent years, the combination of long-read and Hi-C sequencing data has helped achieve chromosome-level and haplotype-phased assemblies for some rust species including Pt [ 38 – 43 ]. The generation of complete and phased genomes has proved to be important not only for identifying intrinsic differences between two nuclei, but also for elucidating the structure of rust genomes and allowing for a deeper understanding of the role of TEs in rust virulence and evolutionary processes [ 44 ]. In this study, we made use of a sexual cross between Pt race 9 (SBDG) and race 161 (FBDJ), an F 1 and 57 selected progeny, and recent genome sequencing and assembly techniques. Phased genomes were constructed for the parental isolates whereby race 9 haplotype B was used as a reference for read mapping. The F 1 , progeny, and a natural population of 59 isolates collected from common wheat in Canada were sequenced and compared to this Pt race 9 haplotype B reference genome. The objective of this study was to generate a genetic map and identify Pt Avr genes and lay the basis for their cloning and characterization. Material and methods Fungal material For the bi-parental mapping population, the parental isolates, race 9 (SBDG) and race 161 (FBDS), were originally selected by Samborski and Dyck [ 45 ]. Race 9 was a prevalent race throughout North America prior to the 1940’s, and race 161 was a predominant race in the Pacific region in the 1960’s [ 54 ]. For the natural population used for association studies, 59 isolates representing different race phenotypes were collected in Canada from different years (1998 to 2012). To diversify the population, race 9 and race 161 were also included in association studies. Isolates were increased via single pustule purification and stored at -80 o C in glass tubes sealed under vacuum. Developing a sexual population Samborski and Dyck purified urediniospores for race 9 and race 161 via single pustule increases. Teliospores of each race were produced and subsequently used to infect the alternate host, T. speciosissimum . Aeciospores, generated from the reciprocal transfer of nectar between isolated pycnia from each parental isolate, were used to infect the rust susceptible wheat cultivar ‘Little Club’. F 1 hybrids produced in this manner were similarly self-fertilized to produce the four F 2 populations (43 F 2 1, 63 F 2 2, 39 F 2 3, 76 F 2 4). Among the four F 2 populations, F 2 1 and F 2 3 were derived from one same F 1 , while F 2 2 and F 2 4 were derived from another shared F 1 . Urediniospores from parents, F 1 and the progeny were stored at -80 o C in glass tubes sealed under vacuum. To initiate this study, the F 2 1 and F 2 3 populations generated by Samborski and Dyck, F 1 and both parents were revived and viability was assessed. Glass tubes were opened and urediniospores allowed to rehydrate for 24 hr prior to heat shock treatment (suspension of the tube in a 40 o C water bath for 5–10 min). Urediniospores were resuspended in a light mineral oil (Bayol, Esso Canada) and inoculated to individual 8 day-old seedlings of rust-susceptible wheat cultivar Thatcher. Inoculated plants were incubated in dew chambers (100% RH; 20 o C) overnight prior to transfer to a greenhouse (20 ± 4 o C). At 14 days post inoculation, urediniospores from all viable isolates were collected from individual plants. Parents, F 1 and 57 isolates of the F 2 progeny resulted in infection and the production of fresh urediniospores. Depending on the amount of urediniospores produced in the initial increase of viable cultures, successive inoculations were carried out to provide sufficient urediniospores for the completion of the study. Virulence phenotyping and genetic analysis All of the 59 isolates collected in Canada and stored at -80 o C in glass tubes sealed under vacuum were revived and increased as described above. For virulence profiling, urediniospores from each of these 59 isolates, race 9, race 161, the F 1 and 57 F 2 progeny were inoculated to 8 day-old germlings of a set of twenty near- isogenic lines (NILs) in the Thatcher background, each harboring a single leaf rust resistance gene: Lr1 , Lr2a , Lr2c , Lr3 , Lr9 , Lr16 , Lr24 , Lr26 , Lr3ka , Lr11 , Lr17 , Lr30 , LrB , Lr10 , Lr14a , Lr18 , Lr3bg , Lr14b , Lr20 and Lr28 . Twelve to 14 days after inoculation, plants were examined. Infection types were rated based on the appearance and size of the rust pustules. Hypersensitive flecks (;), small pustules with necrosis (1), and small to medium sized pustules with chlorosis (2) were considered avirulent infection types. Virulent infection types were medium and large sized pustules without chlorosis or necrosis (rating of 3 and 4, respectively). Rust isolates found to produce more than one infection type on a single isogenic line were considered to be contaminated and were purified by single pustule increases. To achieve this, a small amount of urediniospores was inoculated to the susceptible wheat cultivar ‘Little Club’. Seven days after inoculation, leaves were trimmed to isolate single uredinia. Urediniospores were collected from separately spaced pustules and subsequently tested for purity on the differential NILs. Virulence ratings were repeated for each isolate at least twice. The rust infection type on each isogenic line was converted to a binary code where an avirulent rating (IT < 3) was equal to 0 and a virulent rating (IT ≥ 3) was equal to 1. The virulence profile was then converted to a 4 or 5-letter code as per convention [ 55 ]. Segregation ratios of avirulence to virulence for each host Lr gene were determined for the F 2 population. Genotypes were determined by comparing observed ratios with ratios expected based on Mendelian genetics. Chi-square values were calculated to determine goodness of fit for segregation ratios; p < 0.05 was the level for rejecting the null hypothesis that data did not fit the expected values. DNA extraction and whole-genome sequencing Approximately 200 mg of urediniospores from each isolate were dispensed over individual Petri plates containing 10 ml H 2 O treated with Gramacidin D (0.006 mg/ml). To enhance germination, filter paper treated with the plant volatile, Nonanol, (250 ul 0.06%) (Sigma, MO) was suspended over each plate. The following day, viable urediniospores had germinated to form mats over the surface of the plates. Mats were removed, air-dried on filter paper, and lyophilized for 24 hour. Freeze-dried mats were finely ground with glass beads and incubated for 3 h in buffer (1.0 M Tris/HCl, 0.5 M EDTA, 5.0 M NaCl, 10% cetyltrimehtylammonium bromide (CTAB)), containing protease K (10 mg/ml), and SDS (2%). DNA was extracted by the phenol/coloroform/isoamyl alcohol method as described by Anikster et al. [ 56 ] and precipitated. The resulting pellet was resuspended in TE buffer, treated with RNase and re-extracted with phenol/coloroform/isoamyl alcohol. The precipitated gDNA was resuspended in 50 µl sterile H 2 O. Sequencing services were performed in 2012 at the Michael Smith Genome Sciences Centre in Vancouver, BC, Canada. DNA quality was assessed and quantified using an Agilent DNA 1000 series II assay and Quant-iT dsDNA HS Assay Kit using a Qubit fluorometer (Invitrogen). Plate-based Illumina PET adapter ligation followed. Products were purified using Ampure XP SPRI beads and then PCR-amplified with Phusion DNA Polymerase (Thermo Fisher Scientific Inc. USA) using Illumina’s PE indexed primer sets, with cycle condition 30 sec at 98˚C, followed by 10 cycles of 98˚C for 10 sec, 65˚C for 30 sec and 72˚C for 30 sec, and 72˚C for 5 min. The PCR products were purified using Ampure XP SPRI beads, and checked with Caliper LabChip GX for DNA samples, using the High Sensitivity Assay (PerkinElmer, Inc. USA). PCR products of desired size range were purified on a 8% PAGE and DNA quality was assessed and quantified as described above, then diluted to 8 nM. The final concentration was double checked and determined by Quant-iT dsDNA HS Assay again. Clusters were generated on a cBot and equimolar amounts from 6–7 isolates were pooled to be sequenced per lane on an Illumina HiSeq 2000 to 76 bases in paired-end reads following standard Illumina protocols. Genomic variation analysis Short-read sequencing data were quality-filtered and trimmed to remove adapter sequences using fastp v0.23.4 [ 57 ]. Reads were then aligned to the phased Pt race 9 haplotype B reference genome (S. Formby, G. Bakkeren et al., manuscript in preparation; see Data Availability) using BWA-MEM2 [ 58 ], a performance-optimized implementation of the original BWA-MEM algorithm [ 59 ]. Alignments were filtered with SAMtools v1.14 [ 60 ] to exclude unmapped, secondary, and low-quality alignments (-q 10 -F 2316), followed by coordinate sorting and indexing. Variant calling was performed using bcftools v1.21 [ 61 ]. bcftools mpileup was run in GVCF mode (--gvcf 1) with a minimum mapping quality of 20, and annotated with allele depth (AD), strand-aware read depth (ADF, ADR), total depth (DP), and strand bias (SP) from both FORMAT and INFO fields. Variant calls were then generated using bcftools call with multiallelic calling (-m) and genotype quality output (-f GQ). VCFtools (version 0.1.16) was used to filter samples and markers in vcf format. Isolates with more than 10% missing data were filtered out and only biallelic markers with a minimum quality of 1,000, a minimum mean depth of 10, a maximum mean depth of 60, less than 10% missing data and minor allele frequency greater than 1% were selected. For the bi-parental mapping population, GATK SelectVariants was used to further select SNPs of different types (AA/BB, AA/AB, AB/AB, AB/BB). SNP effects were annotated by SnpEff (version 4.3) [ 62 ]. Genetic mapping After filtering samples and SNPs, 53 progeny and 310,544 SNPs were retained in the bi-parental mapping population for the genetic map construction. Prior to map construction, a Chi-squared test was performed. SNPs that did not fit the expected 1 (homozygous AA):2 (heterozygous AB):1 (homozygous BB) segregation ratio at P > 0.05 were excluded. In addition, only one of the identical SNPs was retained. In the end, 11,138 SNPs were used for genetic map construction by ASMap (version 1.0–4) [ 63 ] in the R program. Avr genes showing an A/V segregation ratio with P > 0.05, including PtAvrLr1 , PtAvrLrB , PtAvrLr14a , PtAvrLr3bg , PtAvrLr14b , PtAvrLr11 , PtAvrLr2c , and PtAvrLr28 , were included in the linkage map construction. The minimum spanning tree algorithm was used to assign linkage groups, and the Kosambi mapping function was used to calculate genetic distances in CentiMorgans (cM). Linkage groups were initially determined using a p.value = 1e-10 and further selected by a genetic distance of 30 cM to ensure consistency with different chromosomes. Linkage groups with less than three markers were excluded. The number of observed crossovers per individual was estimated using the ASMap package. Linkages without Avr genes and the A/V segregation phenotypes of Avr genes in the F 2 population were also used for the QTL analysis. This analysis was performed in R/qtl using the EM algorithm (method = "em") and a binary model (model = "binary"), which is appropriate for binary phenotypic data. A LOD threshold of 3 was applied for all traits. Region-specific association studies To strengthen identification of candidate Avr genes, a complementary approach using region-specific association studies was performed for PtAvrLr14a , PtAvrLr11 , PtAvrLr1 and PtAvrLr2a , which were identified by the linkage mapping and QTL analysis. Genomic DNA-derived Illumina reads were generated and treated for each of the 59 Pt Canadian isolates as described above for the progeny. Sequence reads were also aligned to the Pt race 9 haplotype B assembly as described above. Sample TJBJK_98_MB5-2 was eliminated from the study due to the high percentage of missing data (Table S1 ) and 58 isolates were retained in this natural population to be used for association studies. After filtering samples, variants were called as above yielding 408,473 high-quality markers and 58 isolates were retained in this natural population to be used for GWAS. Markers on contig16, contig3 and contig13 were used for PtAvrLr14a , PtAvrLr1 , and PtAvrLr3bg association analysis, respectively. Missing data were imputed with BEAGLE 5.1 [ 64 ]. The CMLM model [ 65 ] implemented in GAPIT (version 3) [ 66 ] was used to perform association analysis with three principal components (PCs) as covariates. The associations between SNPs and virulence phenotypes were considered significant if the p value was below the 5% significance threshold after Bonferroni correction [ 67 ]. Manhanttan plots were drawn using the CMplot package (version 4.2.0) [ 68 ] in the R program. FIMO (version 5.5.8) was used to search for regulatory motifs within 50 bp upstream and downstream of significant SNPs, using the JASPAR CORE Fungi database [ 69 ]. Results Virulence phenotyping Samborski and Dyck originally established four F 2 populations (consisting of 43 progeny in F 2 1, 63 in F 2 2, 39 in F 2 3, 76 in F 2 4). Among the four F 2 populations, F 2 1 and F 2 3 were derived from one same F 1 , while F 2 2 and F 2 4 were derived from another shared F 1 . Segregation data of avirulence/virulence (A/V) in the four F 2 populations on different near-isogenic lines (NILs) is presented in Table S2 . For this study, 57 F 2 progeny were revived from the F 2 1 and F 2 3. Parental Pt isolates race 9, race 161, F 1 and the 57 F 2 progeny were tested on 20 NILs in the Thatcher background. All isolates were avirulent to the NILs harboring Lr9 , Lr16 , Lr24 , Lr26 , Lr3ka and Lr30 , indicating that race 9 and race 161 were homozygous for avirulence on these Lr genes. When tested on Lr20 , all isolates showed virulence, suggesting that the parental isolates were homozygous for virulence towards Lr20 . As a result, it was not possible using this cross to map these loci responsible for avirulence or virulence using linkage mapping. Race 161 was avirulent and race 9 was virulent towards Lr1 , while the opposite was observed towards Lr14a (Table S2 ). The F 2 progeny segregated for A/V on both Lr1 and Lr14a , fitting a 3:1 ratio, suggesting that avirulence towards Lr1 and Lr14a was each controlled by a single dominant gene. Race 9 and race 161 were both avirulent towards Lr11 , and a 3:1 A/V segregation ratio was observed in the F 2 progeny, indicating that avirulence towards Lr11 was also controlled by a single dominant gene, with parental isolates each being heterozygous avirulent. Even though parental isolates had different phenotypes towards Lr2c , LrB , Lr14b and Lr28 (Table S2 ), segregation ratios of A/V in the F 2 progeny fitted a 1:3 ratio, indicating that avirulence to these genes was each controlled by a single recessive gene. On the NIL containing Lr2a , the observed A/V ratio of 7:9 in the F 2 progeny indicated that two independent recessive genes controlled avirulence. On Lr3 , Lr10 , Lr17 and Lr18 , only a small number of isolates exhibited avirulence/virulence traits different from most isolates in the population. It is very likely that these F 2 progeny did not segregate on these NILs and that some of the isolates are contaminants (see below), or their responses to these NILs were misinterpreted. The segregation of virulence towards Lr3bg more closely fits an A/V ratio of 13:3 ( P = 0.21), rather than a ratio of 3:1 ( P = 0.03). However, considering the entire isolate population (F 2 1 + F 2 3), which yields more precise outcomes, the segregation better conformed to a 3:1 ratio (P = 0.90) (Table S2 ). Consequently, it can be inferred that avirulence towards Lr3bg is under the control of a single dominant gene. Detailed phenotypes of progeny isolates are provided in Table S3 . The fifty-nine Pt isolates in the natural population collected in Canada were also screened on the same 20 wheat differential NILs. Their virulence phenotypes are provided in Table S1 . On the 20 isogenic lines tested, all Pt isolates were virulent to Lr1 and Lr3 . Therefore, in the association study, we were not able to identify SNP markers linked to these avirulence or virulence loci corresponding to Lr1 and Lr3 . Genotyping by whole-genome sequencing Four complete phased haplotype genomes were generated for the two parental isolates Pt race 9 and 161 through the combination of Hi-C and long-reads. The genome of Pt race 9 haplotype B selected for read mapping is of high quality and comprises 18 main contigs that correspond to the 18 predicted Pt chromosomes. It contains 121.3 Mb of DNA and has 24,520 annotated genes (S. Formby, G. Bakkeren et al., manuscript in preparation). To produce genome-wide molecular markers, Illumina HiSeq 2000 technology was used to generate whole genomic DNA-derived sequences of the F 1 and 57 progeny in the bi-parental mapping population from the race 9 x race 161 sexual cross, as well as of the 59 isolates in the natural population collected in Canada (see Material and methods). For Pt isolates in the bi-parental mapping population, an average of 31.1 million pairs of filtered sequence reads were generated for each isolate, of which 90.2% were mapped to the parental race 9 phased 121.3 Mbp haplotype B reference genome. The mapping coverage ranged from 13.0 to 47.5x with a mean coverage of 34.1x (Table S4 ). Using the sequence data, 838,419 SNPs were identified, and 310,544 high-quality SNPs were kept after filtering (Fig. 1). Only SNPs that were heterozygous in the F 1 were selected, and among them, 5,866 were homozygous in each parental isolate but heterozygous between the two parents (AA/BB type), 19,880 were heterozygous in each parental isolate (AB/AB type), and 46,099 were heterozygous in only one parental isolate (AA/AB or AB/BB type). To identify potentially contaminated isolates within the bi-parental mapping population, a Principal Component Analysis (PCA) was performed using a subset of 90K SNP markers. The results revealed that four progeny (19A, 19B, S22, S47) were clearly separated from the main group (Fig. 2). These were judged to be contaminants and eliminated from the study (Table S3 ). For the 59 isolates in the natural population, an average of 28.9 million pairs of filtered sequence reads were generated for each isolate, with 93.5% of them mapped to the reference genome. The mapping coverage ranged from 22.1 to 49.3x, with a mean coverage of 35.9x (Table S4 ). To diversify the population, Illumina reads from race 9 and race 161 were also included in the population and a total of 1,210,015 SNPs were identified. After filtering, 408,473 high-quality SNPs were kept and used for the association studies. Genetic linkage mapping After removing the four contaminated isolates, a total of 21,135 filtered and robust SNPs with a segregation ratio of P > 0.05 were selected for constructing a genetic map. Only one of redundant SNPs (SNPs that show the same segregation) was kept and inadequate linkage groups with less than three SNPs were removed. A final genetic map was created revealing 61 linkage groups, comprising a total of 10,923 SNPs and spanning 10,730.5 cM (Fig. 1). The individual linkage groups ranged in size from 5.7 to 490.5 cM, and the average genetic distance between SNPs was 1.0 cM throughout the genome (Table 2 ). Comparison between linkage groups and the reference haplotype B genome showed one chromosome could be represented by multiple linkage groups (Fig. 1, Table 2 ). Detailed genetic map information is listed in Table S5 . Table 2 Linkage groups in the Puccinia triticina genetic map Linkage Group (LG) Number of Markers Genetic Distance (cM) Mean distance between markers (cM) Mean recombination rate (cM/10 kb) Chromosome LG1 413 490.5 1.2 1.3 chr1 LG2 477 455.1 1.0 1.0 chr10 LG3 559 428.2 0.8 1.0 chr12 LG4 465 418.0 0.9 1.1 chr3 LG5 482 380.3 0.8 1.4 chr6 LG6 289 360.9 1.2 1.3 chr7 LG7 379 354.1 0.9 0.5 chr9 LG8 475 345.8 0.7 1.1 chr4 LG9 320 342.7 1.1 0.8 chr13 LG10 471 329.8 0.7 0.7 chr4 LG11 210 324.8 1.5 0.7 chr11 LG12 218 312.6 1.4 0.6 chr5 LG13 291 309.4 1.1 0.8 chr8 LG14 445 309.3 0.7 0.8 chr2 LG15 364 289.3 0.8 1.5 chr10 LG16 173 276.3 1.6 0.6 chr17 LG17 317 266.3 0.8 0.4 chr1 LG18 118 245.5 2.1 0.8 chr1 LG19 186 228.9 1.2 0.5 chr9 LG20 271 224.5 0.8 1.1 chr7 LG21 159 217.9 1.4 0.9 chr5 LG22 186 212.1 1.1 0.7 chr15 LG23 196 203.2 1.0 0.6 chr13 LG24 274 188.9 0.7 0.9 chr14 LG25 253 186.1 0.7 1.1 chr15 LG26 108 176.7 1.6 0.6 chr6 LG27 263 175.0 0.7 1.0 chr4 LG28 142 166.7 1.2 0.6 chr15 LG29 228 159.7 0.7 0.9 chr18 LG30 179 144.5 0.8 1.4 chr6 LG31 95 144.2 1.5 0.6 chr16 LG32 73 143.0 2.0 1.0 chr3 LG33 147 132.1 0.9 0.7 chr7 LG34 130 127.9 1.0 2.3 chr8 LG35 71 118.8 1.7 0.6 chr4 LG36 57 115.7 2.0 0.2 chr7 LG37 99 114.7 1.2 1.0 chr18 LG38 53 111.1 2.1 1.1 chr9 LG39 178 109.1 0.6 1.8 chr10 LG40 26 100.9 3.9 0.5 chr16 LG41 24 90.1 3.8 0.5 chr8 LG42 52 87.2 1.7 0.3 chr16 LG43 54 83.5 1.5 0.5 chr14 LG44 144 72.7 0.5 0.6 chr3 LG45 72 62.9 0.9 0.5 chr6 LG46 59 62.2 1.1 0.5 chr12 LG47 81 58.1 0.7 0.5 chr13 LG48 24 57.6 2.4 0.3 chr1 LG49 56 54.5 1.0 0.6 chr2 LG50 31 51.7 1.7 0.5 chr9 LG51 49 42.8 0.9 1.0 chr2 LG52 52 41.1 0.8 0.4 chr3 LG53 42 39.7 0.9 0.7 chr10 LG54 45 38.1 0.8 0.6 chr11 LG55 49 35.5 0.7 0.5 chr3 LG56 105 27.9 0.3 0.3 chr2 LG57 26 23.4 0.9 1.5 chr1 LG58 29 22.8 0.8 0.3 chr2 LG59 27 19.0 0.7 0.8 chr5 LG60 40 13.5 0.3 0.3 chr18 LG61 22 5.7 0.3 0.1 chr8 Total 10923 10730.5 1.0 0.8 Markers were used to anchor the race 9 haplotype B reference genome onto the genetic map. All 18 chromosomes were tagged by SNPs and a total of 107.2 Mb (81.3% of the total genome assembly length) were covered by SNPs. A total of 10,831 single-crossover and 765 double-crossover events were detected in the 53 members of the F 2 population (Fig. 3) and the average recombination rate across these linkage groups was estimated to be 0.8 cM/10 kb. Out of the 20 wheat NILs that were tested, segregation of virulence phenotype among the F 2 progeny was observed in only 13 of them. Among these 13 NILs, it was found that both race 9 and race 161 displayed the same virulence phenotype on Lr2c , Lr11 , Lr17 , Lr10 , Lr18 , and Lr28 (Table 1 ). To map all possible Avr genes corresponding to these Lr genes, we attempted both linkage phases, testing whether the Avr allele was from race 9 or race 161. This way, PtAvrLr11 was successfully mapped to chromosome 3, with the closest marker being chr3_6726200 (Fig. 4), under the assumption that the Avr allele derived from race 161. Among the remaining segregating Avr genes, PtAvrLr14a was mapped to the end of chromosome 1, with the closest marker being chr1_8705360 (Fig. 4). To map additional Avr genes, the segregation of A/V in the 53 F₂ progeny was treated as a binary phenotype and analyzed using QTL mapping. For PtAvrLr14a , one QTL was identified on chromosome 1, with the closely linked marker chr1_8705360, consistent with results from linkage mapping (Fig. 5A). For PtAvrLr11 , three QTL were detected on chromosomes 3, 4, and 18, with closely linked SNPs chr3_6726200 (consistent with linkage mapping), chr4_1557250, and chr18_3996934, respectively (Figs. 5B-5D). Additional QTLs were also detected for PtAvrLr1 and PtAvrLr2a . A single QTL for PtAvrLr1 was mapped to chromosome 1, with marker chr1_6500516 (Fig. 5E). Two QTLs were detected for PtAvrLr2a , located on LG8 and LG10, which both reside on chromosome 4 (Fig. 5F and 5G). The closely linked SNPs for these QTLs were chr4_4153557 and chr4_4105933, respectively. These two loci most likely represent the same QTL, indicating that PtAvrLr2a maps to chromosome 4. Candidate genes predicted to be secreted and hence are potential (avirulence) effectors, and located within the QTL regions for PtAvrLr14a , PtAvrLr11 (on chromosomes 4 and 18), and PtAvrLr2a (on chromosome 4) were identified and are listed in Table S6 . In contrast, no secreted genes were found within the QTL regions for PtAvrLr1 or PtAvrLr11 on chromosome 3. Table 1 Phenotypes of parental and F 1 isolates and segregation of avirulent/virulent in the F 2 progeny generated from the sexual cross of Pt race 9 x race161 on differential wheat NILs Phenotypes No. of progeny isolates exp. ratio Lr gene race9 race161 F 1 Avirulent Virulent (A/V) P b Lr1 1 a 0 0 41 16 3:1 0.59 Lr2a 1 0 0 21 36 7:9 0.29 Lr2c 1 1 1 18 39 1:3 0.25 Lr3 0 1 0 52 5 HA c Lr11 0 0 0 46 11 3:1 0.32 Lr17 1 1 1 1 56 HV d LrB 0 1 1 17 40 1:3 0.40 Lr10 1 1 1 1 56 HV Lr14a 0 1 0 41 16 3:1 0.59 Lr18 0 0 0 54 3 HA Lr3bg 0 1 0 50 7 3:1 0.03 Lr14b 1 0 1 16 41 1:3 0.59 Lr28 1 1 1 10 47 1:3 0.19 a 1 = virulence (V); 0 = avirulence (A) b P , probability of goodness of fit by a Chi-square test. c HA, homozygous avirulent d HV, homozygous virulent Region-specific association study Although four Pt Avr loci were identified by linkage mapping and QTL analysis, the corresponding genomic regions are relatively large. To refine the position of these potential avirulence effectors at these genomic loci, a region-specific association study was performed using a natural population of 58 isolates collected in Canada (Table S1 ). In this approach, SNPs from corresponding genomic regions were assessed for correlation with the specific A/V on the four respective Lr gene-containing NILs. After the generation of Illumina genomic DNA reads, filtering and aligning to the same Pt race 9 haplotype B assembly, variants were called (see Materials and methods). A total of 408,473 high-quality SNPs were generated for the whole genome. Specific SNPs on chromosomes 1, 3, 4, and 18 were selected to perform the region-specific association studies for PtAvrLr14a , PtAvrLr11 and PtAvrLr2a ; the association study could not be performed for PtAvrLr1 , since all of the 58 isolates were virulent on the Lr1 line. Three significant SNPs—chr1_8762635, chr1_8776624, and chr1_9064782—were identified for PtAvrLr14a (Fig. 4A; Table 3 ). Among these, chr1_8762635 is an upstream_gene_variant of PTTG_R9hB_001601, which is predicted to encode a secreted hypothetical protein and chr1_8776624 is in two regulatory motifs (Table 3 ). Similarly, three significant SNPs, chr3_6565157, chr3_6569082, and chr3_6616613, were detected for PtAvrLr11 on chromosome 3 (Fig. 4B; Table 3 ). While none of these were associated with genes encoding secreted proteins, chr3_6565157 overlaps with a C6 zinc cluster transcription factor (Table 3 ). Additionally, two significant SNPs were identified for PtAvrLr2a on chromosome 4 (Fig. 6, Table 3 ), but neither was associated with secreted protein-coding genes. However, both were located within regulatory motifs, including a CCAAT-binding factor and a C6 zinc cluster factor site. No significant SNPs were identified for PtAvrLr11 on chromosome 4 and 18. Table 3 SNPs significantly associated with PtAvrLr14a, PtAvrLr11 and PtAvrLr2a Avr gene SNP Annotation Associated Genes Gene Function Predicted DNA motifs overlapping the SNP PtAvrLr14a chr1_8762635 3_prime_UTR_variant PTR9hB_001599 hypothetical protein None upstream_gene_variant PTR9hB_001600 hypothetical protein upstream_gene_variant PTR9hB_001601 hypothetical protein; SECRETED: SignalP(1–31) upstream_gene_variant PTR9hB_001602 hypothetical protein downstream_gene_variant PTR9hB_001597 Arf GTPase downstream_gene_variant PTR9hB_001598 hypothetical protein chr1_8776624 upstream_gene_variant PTR9hB_001603 Aminomethyl-transferase IXR1: High-mobility group (HMG) domain factors; MATALPHA2: Homeo domain factors upstream_gene_variant PTR9hB_001605 hypothetical protein upstream_gene_variant PTR9hB_001607 hypothetical protein downstream_gene_variant PTR9hB_001604 54S ribosomal protein L7 downstream_gene_variant PTR9hB_001606 tRNA-Pro chr1_9064782 downstream_gene_variant PTR9hB_001661 hypothetical protein None PtAvrLr11 chr3_6565157 missense_variant PTR9hB_003527 hypothetical protein UME6: C6 zinc cluster factors upstream_gene_variant PTR9hB_003529 hypothetical protein upstream_gene_variant PTR9hB_003526 hypothetical protein downstream_gene_variant PTR9hB_003528 hypothetical protein chr3_6569082 downstream_gene_variant PTR9hB_003528 hypothetical protein None downstream_gene_variant PTR9hB_003527 hypothetical protein downstream_gene_variant PTR9hB_003526 hypothetical protein downstream_gene_variant PTR9hB_003525 hypothetical protein downstream_gene_variant PTR9hB_003524 hypothetical protein chr3_6616613 upstream_gene_variant PTR9hB_003514 metalloendopeptidase None upstream_gene_variant PTR9hB_003511 hypothetical protein upstream_gene_variant PTR9hB_003510 hypothetical protein upstream_gene_variant PTR9hB_003508 hypothetical protein upstream_gene_variant PTR9hB_003506 hypothetical protein PtAvrLr2a chr4_4288311 missense_variant PTR9hB_005386 hypothetical protein HAP5 and HAP3: Heteromeric CCAAT-binding factors upstream_gene_variant PTR9hB_005387 hypothetical protein downstream_gene_variant PTR9hB_005385 hypothetical protein chr4_4248321 upstream_gene_variant PTR9hB_005373 hypothetical protein YPR196W: C6 zinc cluster factors upstream_gene_variant PTR9hB_005375 hypothetical protein downstream_gene_variant PTR9hB_005374 hypothetical protein downstream_gene_variant PTR9hB_005376 34-kDa subunit of RNA polymerase III Discussion In our cross, segregation for avirulence was observed for Lr1 , Lr2a , Lr2c , Lr11 , LrB , Lr14a , Lr3bg , Lr14b and Lr28 . In terms of inheritance patterns, avirulence in the pathogen seemed to be controlled by single dominant genes towards Lr1 , Lr11 , Lr14a and Lr3bg . Conversely, avirulence appeared to be controlled by single recessive genes towards Lr2c , LrB , Lr14 b, and Lr28 . The inheritance of avirulence towards Lr2a did not fit single gene models, suggesting that multiple genes may be involved in this case. Previous studies [ 28 , 45 , 46 ] have reported similar inheritance patterns for avirulence to Lr1 , Lr11 , Lr14a , and Lr14b . However, there is notable variability in the inheritance patterns of the remaining Avr genes between our study and previous studies. In our study, segregation of F 2 progeny on Lr2c fit a 1:3 ratio, while isolates from the entire population (F 2 1 + F 2 3) followed a 7:9 segregation ratio (Table S2 ), suggesting two independent recessive genes for avirulence. Samborski and Dyck [ 45 ], as well as Statler [ 47 ] found that avirulence to Lr2c and Lr2a was governed by single dominant genes in different sexual crosses of Pt , which differs from the findings of our study. Samborski and Dyck [ 45 ] reported that two genes seemed to condition virulence on LrB , while in our study the segregation ratio suggested a single recessive gene for avirulence towards LrB . Similarly, Statler [ 47 ] in a different sexual cross, suggested avirulence on Lr28 was determined by a single dominant gene, whereas our study revealed that avirulence on Lr28 was controlled by a recessive gene in the F 2 population. Haggag et al . [ 27 ] found that segregation of virulence towards Lr3 fit a 3:1 and 13:3 ratio in two F 2 populations, suggesting that avirulence was governed by a dominant gene and an additional gene in the pathogen, possibly PtAvr3bg . More recently, Statler [ 47 ], based on his own cross, identified a digenic ratio of virulence towards Lr3 . In our study, F 2 progeny did not segregate on Lr3 . However, when examining isolates from the entire population (F 2 1 + F 2 3), their segregation followed a 13:3 ratio (Table S2 ), consistent with the findings by Haggag et al . [ 27 ]. The segregation fit a 3:1 ratio on Lr3bg , indicating the involvement of a single dominant gene. The inconsistent inheritance patterns of avirulence in Pt observed across various studies can be attributed to the isolate-dependent nature of avirulence inheritance, a phenomenon that has also been reported in other rust fungi [ 48 – 51 ]. Avirulence to a host resistance gene can be controlled by a single gene in one isolate but by two or more genes in another isolate, or exhibit a switch from dominant to recessive inheritance. Additionally, it is possible that some of the wheat cultivars used to test Pt populations were not pure Lr single-gene lines, which would compound the interactions between such host lines and Pt races. Lastly, it should be noted that when the size of the test population is small, misclassification of segregation is more likely to occur. For instance, the misplacement of intermediate interactions can have a larger impact on segregation ratios in a small population. In general, the markers belonging to each chromosome exhibited proximity in the genetic map, aligning well with the physical map (Table S5 ). However, certain inconsistencies were observed. For example, although markers from the same chromosome were often positioned closely in the genetic map, their locations did not always show a linear correlation. Furthermore, one chromosome is represented by multiple linkage groups. These inconsistencies could potentially be attributed to two factors: firstly, the highly repetitive nature of the Pt genome can complicate the mapping process, and secondly, the presence of structural variations between the two parental isolates used in the study. In this study, the generated genetic map of Pt spanned a total genetic distance of 10,730.5 cM, which is comparable to other rust fungi. For instance, in the pine fusiform rust fungus Cronartium quercuum f. sp. fusiforme , a genetic map spanning 3006 cM was constructed for its 76.6 Mb genome [ 52 ]. Similarly, Anderson et al . [ 24 ] generated a genetic map spanning 5,860 cM for the 189.5 Mb genome of the flax rust fungus M . lini . Another example is from the wheat stripe rust fungus P. striiformis f. sp. tritici , for which Xia et al . [ 46 ] generated a genetic map spanning 7,715 cM for its 84.5 Mb genome. The construction of the linkage map in this study involved selecting markers without segregation distortion. This selection criterion resulted in a substantial reduction in the number of markers, leading to some parts of the genome not being tagged by markers. The resulting 61 linkage groups representing the 18 chromosomes of the Pt haploid genome can be attributed to this factor. It is likely that regions lacking developed markers caused the fragmentation of linkage groups. Additionally, the presence of genetic gaps exceeding the 30 cM threshold used in map construction might have occurred in regions characterized by repetitive DNA sequences. These factors contribute to the understanding of the challenges faced in achieving complete and contiguous linkage groups for Pt . The recombination rate in Pt exhibited significant variations among different linkage groups as well as within regions of the same linkage group (Table 2 and Fig. 3). In the F 2 population, an average of 204.4 single-crossover and 14.4 double-crossover events per individual were detected, which was higher compared to the 115 crossover events in M . lini [ 24 ] and 133.2 events in P. striiformis f. sp. tritici [ 49 ]. Previous studies have suggested that the recombination rate is influenced by factors such as repetitive DNA content and the percentage of CpG island [ 24 , 49 ]. However, further research is needed to gain a deeper understanding of the regulatory mechanisms governing recombination in filamentous fungi. In this study, a total of four Avr loci were found using multiple methods. PtAvrLr14a was mapped to the telomeric region of chromosome 1 by both linkage mapping and QTL analysis. Region-specific association studies using a natural Pt population also identified significant SNPs at the telomere of chromosome 1, further supporting this finding. PtAvrLr11 on chromosome 3 was similarly mapped by both linkage mapping and QTL analysis. However, the QTL associated with PtAvrLr11 on chromosome 3 had the lowest LOD score among the three QTLs identified on chromosomes 3, 4, and 18 by QTL analysis. In addition, segregation of A/V phenotypes indicated that avirulence towards Lr11 is controlled by a single dominant gene, suggesting that only one of these three QTLs represents the true PtAvrLr11 locus. Significant SNPs were identified for PtAvrLr14a , PtAvrLr2a and PtAvrLr11 (on chromosome 3). Only one SNP (chr1_8762635) associated with PtAvrLr14a , was linked to a gene encoding a predicted secreted protein, indicating its potential role as an ( Avr ) effector. Interestingly, a majority of these significant SNPs were found in intergenic regions, in between candidate predicted genes/ORFs. Studies have shown that non-coding SNPs associated with diseases are often located in or near regulatory regions, suggesting their potential to disrupt or modify the binding sites of transcription factors and other regulatory proteins [ 53 ]. Consequently, these SNPs may influence gene expression patterns to impact phenotypic traits. Thus, the significant SNPs identified in the intergenic regions of this study and located within regulatory motifs, such as chr1_8776624, chr3_6565157, chr4_4248321 and chr4_4288311, could potentially interfere with the normal functioning of regulatory elements, leading to altered gene expression and the observed phenotypic variations. Conclusions A comprehensive genetic map was successfully constructed for Pt , providing a valuable resource for genomics research in this pathogen. By utilizing this genetic map in conjunction with the complete phased Pt genome, genomic features such as recombination rate were estimated. By integrating linkage mapping and region-specific association approaches, significant SNPs associated with PtAvrLr14a were identified with high confidence. These findings represent a significant advancement in our quest to clone and characterize Avr genes and shed light on the molecular mechanisms underlying the complex interactions between this pathogen and its host. Declarations Data availability Sets of sequence read data from this study were deposited in the National Center for Biotechnology Information’s Sequence Read Archive and are accessible through the BioProject Accession IDs PRJNA1111826 (Canadian isolate reads, Table S1; confidential for now and for reviewers only: https://dataview.ncbi.nlm.nih.gov/object/PRJNA1111826?reviewer=4qrfvpevd52i466ej7jega1g9m) and PRJNA1259536 (progeny reads, Table S3; confidential for now and for reviewers only: https://dataview.ncbi.nlm.nih.gov/object/PRJNA1259536?reviewer=4cogjl39o7c4h7jls2iingt6dv). The Pt race9 haplotype B genome and its annotation can be found at NCBI under project number PRJNA1298919 (provisional and confidential link for now and for reviewers only: https://drive.google.com/drive/folders/1sMUGtqqWc_DbjLHgOIJTk7j2rT15XeMU?usp=sharing). [Reviewers, data will be released at the NCBI upon publication of this study) Contributions This work was designed by BMc and GB, and co-funded by BMc, BS and GB. BM and BMc were responsible for isolate collections and performed phenotyping, and BM and DLJ initial mapping. BM performed gDNA isolations. SF assembled and haplophased the rust genomes, and S-HK, ML and SF performed genome annotations. LL performed all genetic map constructions and GWAS. GB and LL wrote the manuscript, and all authors read and approved the final version of the manuscript. Acknowledgements We thank Curt McCartney for support with the initial map constructions, and Rob Linning for his outstanding technical assistance. The Michael Smith Genome Sciences Centre in Vancouver, BC, Canada, is acknowledged for their expert advice and sequencing of all samples, under supervision of Dr. Richard Moore. Funding This project was funded partly through Canada’s Digital Technology Supercluster Program, project “Computational Biochemistry Platform for Crop Health,” the Genome BC Strategic Opportunities Fund, SOF131 project “Poplar and cereal rust comparative genomics: identification of pathogen determinants to prevent and predict epidemics”, the Natural Resources Canada’s Genomics Research and Development Initiative (both, joint R. Hamelin and G. Bakkeren), and an Ontario Ministry of Research and Innovation grant #RE-03-056, “Genomics Approaches to Mitigate Fungal Threats to Crops” (joint B. Saville and G. Bakkeren). We also gratefully acknowledge the support of the Agriculture and Agri-Food Canada Genomics Initiative. References Bolton MD, Kolmer JA, Garvin DF. Wheat leaf rust caused by Puccinia triticina. Mol Plant Pathol. 2008;9(5):563–75. Huerta-Espino J, Singh RP, Germán S, McCallum BD, Park RF, Chen WQ, Bhardwaj SC, Goyeau H. 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JASPAR 2024: 20th anniversary of the open-access database of transcription factor binding profiles. Nucleic Acids Res. 2024;52(D1):D174–82. Additional Declarations No competing interests reported. Supplementary Files TableS1.xlsx Table S1. Phenotypes of Puccinia triticina isolates in a natural population collected in Canada and screened on differential wheat NILs harboring the indicated Lr resistance gene. Includes gDNA Illumina sequencing information on the samples (see Formby et al., 2025). TableS2.xlsx Table S2. F1 virulence phenotypes on differential near-isogenic wheat lines and segregation of avirulent/virulent in four F2 populations generated from a sexual cross of Puccinia triticina race 9 x race 161. TableS3.xlsx Table S3. Virulence phenotypes of the Puccinia triticina parental isolates of the sexual cross race 9 x race 161 and the resulting F1 and 57 F2 progeny (row 2), scored on 20 differential near-isogenic wheat lines (NILs) having the corresponding single Lr resistance gene (column A). TableS4.docx Table S4. Sequencing and genetic marker summary. TableS5.xlsx Table S5. Genetic map of Puccinia triticina . TableS6.xlsx Table S6. Candidate genes that are secreted within PtAvrLr14a , PtAvrLr11 and PtAvrLr2a QTL regions. TableS7.xlsx Table S7. Detailed information on regulatory motifs overlapping the significant SNPs. Cite Share Download PDF Status: Published Journal Publication published 04 Feb, 2026 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 09 Sep, 2025 Reviews received at journal 08 Sep, 2025 Reviews received at journal 29 Aug, 2025 Reviews received at journal 23 Aug, 2025 Reviewers agreed at journal 20 Aug, 2025 Reviewers agreed at journal 18 Aug, 2025 Reviewers agreed at journal 16 Aug, 2025 Reviewers invited by journal 15 Aug, 2025 Editor assigned by journal 14 Aug, 2025 Submission checks completed at journal 12 Aug, 2025 First submitted to journal 12 Aug, 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7264203","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":503305257,"identity":"cd1351a1-3faf-45cc-88b8-40f3e43ca7d5","order_by":0,"name":"Lu Liu","email":"","orcid":"","institution":"Agriculture and Agri-Food Canada","correspondingAuthor":false,"prefix":"","firstName":"Lu","middleName":"","lastName":"Liu","suffix":""},{"id":503305258,"identity":"5e146195-879a-43ea-80b6-29008866e5ad","order_by":1,"name":"Sean Formby","email":"","orcid":"","institution":"University of British Columbia","correspondingAuthor":false,"prefix":"","firstName":"Sean","middleName":"","lastName":"Formby","suffix":""},{"id":503305259,"identity":"b9987b53-9adf-4be6-b47e-f9fc6db06589","order_by":2,"name":"Sang Hu Kim","email":"","orcid":"","institution":"Agriculture and Agri-Food Canada","correspondingAuthor":false,"prefix":"","firstName":"Sang","middleName":"Hu","lastName":"Kim","suffix":""},{"id":503305260,"identity":"c625f0c8-6898-4e14-b548-d1f93cfcad5f","order_by":3,"name":"David L. Joly","email":"","orcid":"","institution":"Agriculture and Agri-Food Canada","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"L.","lastName":"Joly","suffix":""},{"id":503305261,"identity":"a5abb3a2-3c7f-4b70-947f-38b20da455ed","order_by":4,"name":"Barbara Mulock","email":"","orcid":"","institution":"Morden Research and Development Center, Agriculture and Agri-Food Canada","correspondingAuthor":false,"prefix":"","firstName":"Barbara","middleName":"","lastName":"Mulock","suffix":""},{"id":503305262,"identity":"50a7f3af-d452-441f-8a56-c32e06ad7bfe","order_by":5,"name":"Mark Lubberts","email":"","orcid":"","institution":"Agriculture and Agri-Food Canada","correspondingAuthor":false,"prefix":"","firstName":"Mark","middleName":"","lastName":"Lubberts","suffix":""},{"id":503305263,"identity":"dc2e2ae8-f195-4c9e-a072-e431c6ae3ce5","order_by":6,"name":"Barry Saville","email":"","orcid":"","institution":"Trent University","correspondingAuthor":false,"prefix":"","firstName":"Barry","middleName":"","lastName":"Saville","suffix":""},{"id":503305264,"identity":"02a60e5b-fec9-4040-840a-58f964b3792b","order_by":7,"name":"Brent McCallum","email":"","orcid":"","institution":"Morden Research and Development Center, Agriculture and Agri-Food Canada","correspondingAuthor":false,"prefix":"","firstName":"Brent","middleName":"","lastName":"McCallum","suffix":""},{"id":503305265,"identity":"d3cf99a4-865d-4dd7-8aca-4c2566e4be11","order_by":8,"name":"Guus Bakkeren","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYLACxgYGAwkwq4J0LWdI1sLYRoRq+Ygc4w+MO+yMJdt7Hz4unGdnt72B/eIHhho7nFoMb+SYSTCeSTaT5jlubDxzW3LynAM8xRIMx5Jxa5mRYwZ0D7ONnEQamzTvNuZkCQaeNKBTmfFpATqsrd5GTv4Z+2/eOfUwLfW4/SKRYyDB2HbYTFqCjY2Zt+GwnQQD+zGglsM4tRjwPCuTSDxz3FiyJ41ZmufY8QQJZh5miYRjx3Hb0p68+cPHHdWGM44fY/zMU1NtL8He/vDDh5pq3LYcABIJSAKJDcw8BigiGLY0oAnYMzCwP8CjYRSMglEwCkYgAADg3UkOW5fqkwAAAABJRU5ErkJggg==","orcid":"","institution":"Agriculture and Agri-Food Canada","correspondingAuthor":true,"prefix":"","firstName":"Guus","middleName":"","lastName":"Bakkeren","suffix":""}],"badges":[],"createdAt":"2025-07-31 16:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7264203/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7264203/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-026-12579-0","type":"published","date":"2026-02-04T15:58:22+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89680258,"identity":"1dee7b7a-d828-42c7-bb81-2435466534b3","added_by":"auto","created_at":"2025-08-22 14:29:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1216624,"visible":true,"origin":"","legend":"\u003cp\u003eChromosomes of the race 9 haplotype B genome with aligned linkage groups (LGs, shown as green bars). Marker densities are calculated using 1 Mb sliding windows across the genomic regions.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/68c3e6ef5333bd693607303f.png"},{"id":89680595,"identity":"22bd544f-e2b3-479d-be6f-f955da0b67ad","added_by":"auto","created_at":"2025-08-22 14:37:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":165369,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis (PCA) for parental isolates of the sexual cross race 9 x race 161 and the resulting F\u003csub\u003e1\u003c/sub\u003e and F\u003csub\u003e2\u003c/sub\u003e progeny. The circle indicates four contaminated isolates.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/2775a3e7fbddda8d7acca769.png"},{"id":89680192,"identity":"29983535-407e-4c63-aa06-f03746c084ac","added_by":"auto","created_at":"2025-08-22 14:29:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":208007,"visible":true,"origin":"","legend":"\u003cp\u003eGenotype profiles of missing values, single and double crossover events during recombination for the F\u003csub\u003e2\u003c/sub\u003e progeny isolates generated from the sexual cross of \u003cem\u003ePt \u003c/em\u003erace 9 x race161.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/19ea6cca6d088db09bc0956d.png"},{"id":89680188,"identity":"058189aa-4831-4ccf-b6ae-4c2b4198599d","added_by":"auto","created_at":"2025-08-22 14:29:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2212778,"visible":true,"origin":"","legend":"\u003cp\u003eQTL mapping identified loci associated with \u003cem\u003ePtAvrLr14a \u003c/em\u003e(A), \u003cem\u003ePtAvrLr11\u003c/em\u003e (B-D), \u003cem\u003ePtAvrLr1\u003c/em\u003e (E), and \u003cem\u003ePtAvrLr2a \u003c/em\u003e(F,G).\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/e242a4dcaaed0f154df96bd6.png"},{"id":89680209,"identity":"fd5f8587-a314-4ade-8bd9-5d33e2ff2cc4","added_by":"auto","created_at":"2025-08-22 14:29:01","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":602311,"visible":true,"origin":"","legend":"\u003cp\u003eLinkage maps and Manhattan plots for \u003cem\u003ePtAvrLr14a\u003c/em\u003e (A) and \u003cem\u003ePtAvrLr11\u003c/em\u003e (B). Only part of the linkage groups or chromosomes are shown. Significant SNPs are indicated with red dots. The bar plots beside the Manhattan plots represent SNP densities within 1Mb window size across the regions.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/c68f01f3ca1ef73c5aaab9d0.png"},{"id":89680593,"identity":"2795e1cb-99b1-41d1-8001-c8a0bd0e714c","added_by":"auto","created_at":"2025-08-22 14:37:00","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":512282,"visible":true,"origin":"","legend":"\u003cp\u003eManhattan plot showing significant SNPs on chromosome 4 for \u003cem\u003ePtAvrLr2a\u003c/em\u003e. Only a portion of chromosome 4 is displayed. Significant SNPs are highlighted in red. The bar plot beside the Manhattan plot represents SNP density within 1Mb window size across the region.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/3851f061cfe26dc8f43bc0f4.png"},{"id":102235006,"identity":"391001a1-823c-4e8f-a5d1-d4e24fe6b090","added_by":"auto","created_at":"2026-02-09 16:14:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7568634,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/6a2b81df-796e-4697-9694-dd8f2a8587c4.pdf"},{"id":89680183,"identity":"2ae3a63f-ce16-4923-845f-0b9dd189df14","added_by":"auto","created_at":"2025-08-22 14:29:00","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":18135,"visible":true,"origin":"","legend":"\u003cp\u003eTable S1. Phenotypes of \u003cem\u003ePuccinia triticina\u003c/em\u003e isolates in a natural population collected in Canada and screened on differential wheat NILs harboring the indicated \u003cem\u003eLr\u003c/em\u003eresistance gene. Includes gDNA Illumina sequencing information on the samples (see Formby et al., 2025).\u003c/p\u003e","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/49989e694bdd0e5e280d87a9.xlsx"},{"id":89680181,"identity":"c134de45-e8aa-4d9b-85e9-38136a268484","added_by":"auto","created_at":"2025-08-22 14:29:00","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":13287,"visible":true,"origin":"","legend":"\u003cp\u003eTable S2. F1 virulence phenotypes on differential near-isogenic wheat lines and segregation of avirulent/virulent in four F2 populations generated from a sexual cross of \u003cem\u003ePuccinia triticina\u003c/em\u003e race 9 x race 161.\u003c/p\u003e","description":"","filename":"TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/a510d40ce49e735369ac5e91.xlsx"},{"id":89681667,"identity":"9b55cc7c-0f27-4f9d-9ece-23da25be7ce9","added_by":"auto","created_at":"2025-08-22 14:45:00","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":18901,"visible":true,"origin":"","legend":"\u003cp\u003eTable S3. Virulence phenotypes of the \u003cem\u003ePuccinia triticina\u003c/em\u003e parental isolates of the sexual cross race 9 x race 161 and the resulting F1 and 57 F2 progeny (row 2), scored on 20 differential near-isogenic wheat lines (NILs) having the corresponding single Lr resistance gene (column A).\u003c/p\u003e","description":"","filename":"TableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/368c5ed5f4395d632deadc2c.xlsx"},{"id":89680193,"identity":"bc2e69b6-52a5-4c09-8d8f-c815aa99503a","added_by":"auto","created_at":"2025-08-22 14:29:00","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":30206,"visible":true,"origin":"","legend":"\u003cp\u003eTable S4. Sequencing and genetic marker summary.\u003c/p\u003e","description":"","filename":"TableS4.docx","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/b88ec60022d6d7b270b7cf9a.docx"},{"id":89680216,"identity":"73bd3790-e5ef-4b92-aaf8-266faf1000b1","added_by":"auto","created_at":"2025-08-22 14:29:01","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":450095,"visible":true,"origin":"","legend":"\u003cp\u003eTable S5. Genetic map of \u003cem\u003ePuccinia triticina\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"TableS5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/a81e9a41536c364ab8dd4627.xlsx"},{"id":89680202,"identity":"5b5d00c2-29b6-4c77-bf77-d40135592953","added_by":"auto","created_at":"2025-08-22 14:29:01","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":52684,"visible":true,"origin":"","legend":"\u003cp\u003eTable S6. Candidate genes that are secreted within \u003cem\u003ePtAvrLr14a\u003c/em\u003e, \u003cem\u003ePtAvrLr11\u003c/em\u003e and \u003cem\u003ePtAvrLr2a\u003c/em\u003e QTL regions.\u003c/p\u003e","description":"","filename":"TableS6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/2a62c14ddda0cb32470a0559.xlsx"},{"id":89680195,"identity":"5aba54ff-c101-4190-b1b1-fe0be365b628","added_by":"auto","created_at":"2025-08-22 14:29:00","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":10673,"visible":true,"origin":"","legend":"\u003cp\u003eTable S7. Detailed information on regulatory motifs overlapping the significant SNPs.\u003c/p\u003e","description":"","filename":"TableS7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7264203/v1/1e2a76aae9ce513992ff362d.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Avirulence genes identified through linkage mapping and region-specific association studies in the wheat leaf rust pathogen Puccinia triticina","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWheat rust diseases, including stem, leaf and stripe rust, pose a major threat to global wheat production. Among these, wheat leaf rust caused by the fungal pathogen \u003cem\u003ePuccinia triticina\u003c/em\u003e Eriks. (\u003cem\u003ePt\u003c/em\u003e) is the most common and widely distributed [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In North America, yield losses ranging from 5\u0026ndash;10% are common depending on the wheat variety and growing conditions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although rust diseases can be controlled by fungicides, genetic resistance is the most effective, economical and environmentally sustainable method [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Significant progress has been made in developing resistant wheat cultivars. However, rust fungi evolve rapidly and can often evade plant immune systems, leading to ineffective host resistance [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, there is great interest in understanding the molecular mechanisms underlying host-pathogen interactions, in particular as they pertain to pathogens evading recognition by host resistance genes.\u003c/p\u003e\u003cp\u003eThe genetics of plant-pathogen interactions were initially studied by Harold Flor with the flax-rust system and described in the \u0026lsquo;gene-for-gene\u0026rsquo; theory [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In this genetic concept, the interaction of specific avirulence (\u003cem\u003eAvr\u003c/em\u003e) genes in the pathogen with corresponding resistance (\u003cem\u003eR\u003c/em\u003e) genes in the host activates host defense responses. Various molecular mechanisms underpinning these interactions have been revealed over the last decade. \u003cem\u003eR\u003c/em\u003e genes can code for plant receptors on plant cell surfaces responding to Avr effectors secreted by the pathogen in the apoplast, but many \u003cem\u003eR\u003c/em\u003e genes encode intracellular immune receptor proteins of the nucleotide binding leucine rich repeat (NB-LRR) class [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] that recognize small effector proteins delivered by the pathogen into host cells to suppress host basal defenses and to assist in the establishment of pathogen infection [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. R proteins can interact directly with effector proteins or guard other cellular targets of effectors and indirectly sense their actions [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Since the outcome is pathogen arrest and \u0026lsquo;avirulence\u0026rsquo;, such effectors correspond to the \u003cem\u003eAvr\u003c/em\u003e genes in the genetic concept. In wheat rust fungi, three stem rust pathogen, \u003cem\u003eP. graminis\u003c/em\u003e f.sp. \u003cem\u003etritici\u003c/em\u003e (\u003cem\u003ePgt\u003c/em\u003e) \u003cem\u003eAvr\u003c/em\u003e genes have been successfully cloned, namely \u003cem\u003eAvrSr27\u003c/em\u003e [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], \u003cem\u003eAvrSr35\u003c/em\u003e [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and \u003cem\u003eAvrSr50\u003c/em\u003e [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Several \u003cem\u003eAvr\u003c/em\u003e effector candidates for \u003cem\u003ePt\u003c/em\u003e have been reported with two, \u003cem\u003ePtAvrLr15\u003c/em\u003e and \u003cem\u003ePtAvrLr21\u003c/em\u003e identified [\u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Functional characterization of such effectors will further our understanding of host-pathogen interactions and allow for more rational deployment of resistance genes in crop resistance breeding.\u003c/p\u003e\u003cp\u003eOne approach to identify and clone \u003cem\u003eAvr\u003c/em\u003e genes is through genetic mapping. This approach has been successfully employed to clone \u003cem\u003eAvr\u003c/em\u003e genes of the flax rust fungal pathogen, \u003cem\u003eMelampsora lini\u003c/em\u003e [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], which is an autoecious fungus. However, wheat rust fungi are heteroecious, meaning they require different host species to complete their life cycle. This makes sexual crosses more difficult to achieve. \u003cem\u003ePt\u003c/em\u003e cycles asexually on wheat but to complete its sexual cycle, requires alternate hosts, \u003cem\u003eThalictrum\u003c/em\u003e species including \u003cem\u003eThalictrum speciosissimum L.\u003c/em\u003e (common meadow rue), which is the most susceptible alternate host of \u003cem\u003ePt\u003c/em\u003e and found in southern Europe and west Asia [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In North America, \u003cem\u003ePt\u003c/em\u003e reproduces by the continuous production of asexually produced urediniospores and the sexual cycle does not occur naturally since the native North American \u003cem\u003eThalictrum\u003c/em\u003e species have limited susceptibility to infection by \u003cem\u003ePt\u003c/em\u003e basidiospores [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Starting in 1968, Samborski and Dyck conducted a series of studies on the genetics of pathogenicity in \u003cem\u003ePt\u003c/em\u003e. They produced populations of progeny that segregated for avirulence on various wheat cultivars by sexually crossing \u003cem\u003ePt\u003c/em\u003e races. These investigations formed the basis for identifying the genetic background in the generation of the standard differential wheat varieties and led to the early development of several near-isogenic wheat lines specific to leaf rust [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Since then, Dr. Peter Dyck produced additional near-isogenic wheat lines, allowing for continued and expanded research on the pathogenicity of the wheat leaf rust fungus.\u003c/p\u003e\u003cp\u003eThe rapid advancement of genome sequencing technologies and data analysis tools have accelerated \u003cem\u003eAvr\u003c/em\u003e gene identification and have promoted our understanding of various aspects of rust biology [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. However, compared with most other plant pathogens, rust fungi have larger genome sizes, with assembled genomes ranging from 53 Mbp to 1.25 Gbp [\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In addition, rust fungi have large numbers of up to 93% repetitive sequences and transposable elements (TEs) in their genomes, among the largest known for plant pathogens [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Moreover, the biological materials easiest to increase and collect for genomics study are the urediniospores which are dikaryotic with two highly heterozygous nuclei in one cell [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], making genome assembly particularly challenging. In \u003cem\u003ePt\u003c/em\u003e, a draft genome sequence of race 1 (BBBD) first became available in 2017 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. This genome contained 135 Mb of DNA, with 51% TEs and repetitive elements and an estimated 14,800 genes, which has been useful as a reference genome. In recent years, the combination of long-read and Hi-C sequencing data has helped achieve chromosome-level and haplotype-phased assemblies for some rust species including \u003cem\u003ePt\u003c/em\u003e [\u003cspan additionalcitationids=\"CR39 CR40 CR41 CR42\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The generation of complete and phased genomes has proved to be important not only for identifying intrinsic differences between two nuclei, but also for elucidating the structure of rust genomes and allowing for a deeper understanding of the role of TEs in rust virulence and evolutionary processes [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn this study, we made use of a sexual cross between \u003cem\u003ePt\u003c/em\u003e race 9 (SBDG) and race 161 (FBDJ), an F\u003csub\u003e1\u003c/sub\u003e and 57 selected progeny, and recent genome sequencing and assembly techniques. Phased genomes were constructed for the parental isolates whereby race 9 haplotype B was used as a reference for read mapping. The F\u003csub\u003e1\u003c/sub\u003e, progeny, and a natural population of 59 isolates collected from common wheat in Canada were sequenced and compared to this \u003cem\u003ePt\u003c/em\u003e race 9 haplotype B reference genome. The objective of this study was to generate a genetic map and identify \u003cem\u003ePt Avr\u003c/em\u003e genes and lay the basis for their cloning and characterization.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003eFungal material\u003c/p\u003e\u003cp\u003eFor the bi-parental mapping population, the parental isolates, race 9 (SBDG) and race 161 (FBDS), were originally selected by Samborski and Dyck [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Race 9 was a prevalent race throughout North America prior to the 1940\u0026rsquo;s, and race 161 was a predominant race in the Pacific region in the 1960\u0026rsquo;s [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. For the natural population used for association studies, 59 isolates representing different race phenotypes were collected in Canada from different years (1998 to 2012). To diversify the population, race 9 and race 161 were also included in association studies. Isolates were increased via single pustule purification and stored at -80 \u003csup\u003eo\u003c/sup\u003eC in glass tubes sealed under vacuum.\u003c/p\u003e\u003cp\u003eDeveloping a sexual population\u003c/p\u003e\u003cp\u003eSamborski and Dyck purified urediniospores for race 9 and race 161 via single pustule increases. Teliospores of each race were produced and subsequently used to infect the alternate host, \u003cem\u003eT. speciosissimum\u003c/em\u003e. Aeciospores, generated from the reciprocal transfer of nectar between isolated pycnia from each parental isolate, were used to infect the rust susceptible wheat cultivar \u0026lsquo;Little Club\u0026rsquo;. F\u003csub\u003e1\u003c/sub\u003e hybrids produced in this manner were similarly self-fertilized to produce the four F\u003csub\u003e2\u003c/sub\u003e populations (43 F\u003csub\u003e2\u003c/sub\u003e1, 63 F\u003csub\u003e2\u003c/sub\u003e2, 39 F\u003csub\u003e2\u003c/sub\u003e3, 76 F\u003csub\u003e2\u003c/sub\u003e4). Among the four F\u003csub\u003e2\u003c/sub\u003e populations, F\u003csub\u003e2\u003c/sub\u003e1 and F\u003csub\u003e2\u003c/sub\u003e3 were derived from one same F\u003csub\u003e1\u003c/sub\u003e, while F\u003csub\u003e2\u003c/sub\u003e2 and F\u003csub\u003e2\u003c/sub\u003e4 were derived from another shared F\u003csub\u003e1\u003c/sub\u003e. Urediniospores from parents, F\u003csub\u003e1\u003c/sub\u003e and the progeny were stored at -80 \u003csup\u003eo\u003c/sup\u003eC in glass tubes sealed under vacuum.\u003c/p\u003e\u003cp\u003eTo initiate this study, the F\u003csub\u003e2\u003c/sub\u003e1 and F\u003csub\u003e2\u003c/sub\u003e3 populations generated by Samborski and Dyck, F\u003csub\u003e1\u003c/sub\u003e and both parents were revived and viability was assessed. Glass tubes were opened and urediniospores allowed to rehydrate for 24 hr prior to heat shock treatment (suspension of the tube in a 40 \u003csup\u003eo\u003c/sup\u003eC water bath for 5\u0026ndash;10 min). Urediniospores were resuspended in a light mineral oil (Bayol, Esso Canada) and inoculated to individual 8 day-old seedlings of rust-susceptible wheat cultivar Thatcher. Inoculated plants were incubated in dew chambers (100% RH; 20 \u003csup\u003eo\u003c/sup\u003eC) overnight prior to transfer to a greenhouse (20\u0026thinsp;\u0026plusmn;\u0026thinsp;4 \u003csup\u003eo\u003c/sup\u003eC). At 14 days post inoculation, urediniospores from all viable isolates were collected from individual plants. Parents, F\u003csub\u003e1\u003c/sub\u003e and 57 isolates of the F\u003csub\u003e2\u003c/sub\u003e progeny resulted in infection and the production of fresh urediniospores. Depending on the amount of urediniospores produced in the initial increase of viable cultures, successive inoculations were carried out to provide sufficient urediniospores for the completion of the study.\u003c/p\u003e\u003cp\u003eVirulence phenotyping and genetic analysis\u003c/p\u003e\u003cp\u003eAll of the 59 isolates collected in Canada and stored at -80 \u003csup\u003eo\u003c/sup\u003eC in glass tubes sealed under vacuum were revived and increased as described above. For virulence profiling, urediniospores from each of these 59 isolates, race 9, race 161, the F\u003csub\u003e1\u003c/sub\u003e and 57 F\u003csub\u003e2\u003c/sub\u003e progeny were inoculated to 8 day-old germlings of a set of twenty near- isogenic lines (NILs) in the Thatcher background, each harboring a single leaf rust resistance gene: \u003cem\u003eLr1\u003c/em\u003e, \u003cem\u003eLr2a\u003c/em\u003e, \u003cem\u003eLr2c\u003c/em\u003e, \u003cem\u003eLr3\u003c/em\u003e, \u003cem\u003eLr9\u003c/em\u003e, \u003cem\u003eLr16\u003c/em\u003e, \u003cem\u003eLr24\u003c/em\u003e, \u003cem\u003eLr26\u003c/em\u003e, \u003cem\u003eLr3ka\u003c/em\u003e, \u003cem\u003eLr11\u003c/em\u003e, \u003cem\u003eLr17\u003c/em\u003e, \u003cem\u003eLr30\u003c/em\u003e, \u003cem\u003eLrB\u003c/em\u003e, \u003cem\u003eLr10\u003c/em\u003e, \u003cem\u003eLr14a\u003c/em\u003e, \u003cem\u003eLr18\u003c/em\u003e, \u003cem\u003eLr3bg\u003c/em\u003e, \u003cem\u003eLr14b\u003c/em\u003e, \u003cem\u003eLr20\u003c/em\u003e and \u003cem\u003eLr28\u003c/em\u003e. Twelve to 14 days after inoculation, plants were examined. Infection types were rated based on the appearance and size of the rust pustules. Hypersensitive flecks (;), small pustules with necrosis (1), and small to medium sized pustules with chlorosis (2) were considered avirulent infection types. Virulent infection types were medium and large sized pustules without chlorosis or necrosis (rating of 3 and 4, respectively). Rust isolates found to produce more than one infection type on a single isogenic line were considered to be contaminated and were purified by single pustule increases. To achieve this, a small amount of urediniospores was inoculated to the susceptible wheat cultivar \u0026lsquo;Little Club\u0026rsquo;. Seven days after inoculation, leaves were trimmed to isolate single uredinia. Urediniospores were collected from separately spaced pustules and subsequently tested for purity on the differential NILs. Virulence ratings were repeated for each isolate at least twice. The rust infection type on each isogenic line was converted to a binary code where an avirulent rating (IT\u0026thinsp;\u0026lt;\u0026thinsp;3) was equal to 0 and a virulent rating (IT\u0026thinsp;\u0026ge;\u0026thinsp;3) was equal to 1. The virulence profile was then converted to a 4 or 5-letter code as per convention [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSegregation ratios of avirulence to virulence for each host \u003cem\u003eLr\u003c/em\u003e gene were determined for the F\u003csub\u003e2\u003c/sub\u003e population. Genotypes were determined by comparing observed ratios with ratios expected based on Mendelian genetics. Chi-square values were calculated to determine goodness of fit for segregation ratios; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was the level for rejecting the null hypothesis that data did not fit the expected values.\u003c/p\u003e\u003cp\u003eDNA extraction and whole-genome sequencing\u003c/p\u003e\u003cp\u003eApproximately 200 mg of urediniospores from each isolate were dispensed over individual Petri plates containing 10 ml H\u003csub\u003e2\u003c/sub\u003eO treated with Gramacidin D (0.006 mg/ml). To enhance germination, filter paper treated with the plant volatile, Nonanol, (250 ul 0.06%) (Sigma, MO) was suspended over each plate. The following day, viable urediniospores had germinated to form mats over the surface of the plates. Mats were removed, air-dried on filter paper, and lyophilized for 24 hour. Freeze-dried mats were finely ground with glass beads and incubated for 3 h in buffer (1.0 M Tris/HCl, 0.5 M EDTA, 5.0 M NaCl, 10% cetyltrimehtylammonium bromide (CTAB)), containing protease K (10 mg/ml), and SDS (2%). DNA was extracted by the phenol/coloroform/isoamyl alcohol method as described by Anikster et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] and precipitated. The resulting pellet was resuspended in TE buffer, treated with RNase and re-extracted with phenol/coloroform/isoamyl alcohol. The precipitated gDNA was resuspended in 50 \u0026micro;l sterile H\u003csub\u003e2\u003c/sub\u003eO.\u003c/p\u003e\u003cp\u003eSequencing services were performed in 2012 at the Michael Smith Genome Sciences Centre in Vancouver, BC, Canada. DNA quality was assessed and quantified using an Agilent DNA 1000 series II assay and Quant-iT dsDNA HS Assay Kit using a Qubit fluorometer (Invitrogen). Plate-based Illumina PET adapter ligation followed. Products were purified using Ampure XP SPRI beads and then PCR-amplified with Phusion DNA Polymerase (Thermo Fisher Scientific Inc. USA) using Illumina\u0026rsquo;s PE indexed primer sets, with cycle condition 30 sec at 98˚C, followed by 10 cycles of 98˚C for 10 sec, 65˚C for 30 sec and 72˚C for 30 sec, and 72˚C for 5 min. The PCR products were purified using Ampure XP SPRI beads, and checked with Caliper LabChip GX for DNA samples, using the High Sensitivity Assay (PerkinElmer, Inc. USA). PCR products of desired size range were purified on a 8% PAGE and DNA quality was assessed and quantified as described above, then diluted to 8 nM. The final concentration was double checked and determined by Quant-iT dsDNA HS Assay again. Clusters were generated on a cBot and equimolar amounts from 6\u0026ndash;7 isolates were pooled to be sequenced per lane on an Illumina HiSeq 2000 to 76 bases in paired-end reads following standard Illumina protocols.\u003c/p\u003e\u003cp\u003eGenomic variation analysis\u003c/p\u003e\u003cp\u003eShort-read sequencing data were quality-filtered and trimmed to remove adapter sequences using fastp v0.23.4 [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Reads were then aligned to the phased \u003cem\u003ePt\u003c/em\u003e race 9 haplotype B reference genome (S. Formby, G. Bakkeren et al., manuscript in preparation; see Data Availability) using BWA-MEM2 [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], a performance-optimized implementation of the original BWA-MEM algorithm [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Alignments were filtered with SAMtools v1.14 [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] to exclude unmapped, secondary, and low-quality alignments (-q 10 -F 2316), followed by coordinate sorting and indexing.\u003c/p\u003e\u003cp\u003eVariant calling was performed using bcftools v1.21 [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. bcftools mpileup was run in GVCF mode (--gvcf 1) with a minimum mapping quality of 20, and annotated with allele depth (AD), strand-aware read depth (ADF, ADR), total depth (DP), and strand bias (SP) from both FORMAT and INFO fields. Variant calls were then generated using bcftools call with multiallelic calling (-m) and genotype quality output (-f GQ).\u003c/p\u003e\u003cp\u003eVCFtools (version 0.1.16) was used to filter samples and markers in vcf format. Isolates with more than 10% missing data were filtered out and only biallelic markers with a minimum quality of 1,000, a minimum mean depth of 10, a maximum mean depth of 60, less than 10% missing data and minor allele frequency greater than 1% were selected. For the bi-parental mapping population, GATK SelectVariants was used to further select SNPs of different types (AA/BB, AA/AB, AB/AB, AB/BB). SNP effects were annotated by SnpEff (version 4.3) [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGenetic mapping\u003c/p\u003e\u003cp\u003eAfter filtering samples and SNPs, 53 progeny and 310,544 SNPs were retained in the bi-parental mapping population for the genetic map construction. Prior to map construction, a Chi-squared test was performed. SNPs that did not fit the expected 1 (homozygous AA):2 (heterozygous AB):1 (homozygous BB) segregation ratio at P\u0026thinsp;\u0026gt;\u0026thinsp;0.05 were excluded. In addition, only one of the identical SNPs was retained. In the end, 11,138 SNPs were used for genetic map construction by ASMap (version 1.0\u0026ndash;4) [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] in the R program. \u003cem\u003eAvr\u003c/em\u003e genes showing an A/V segregation ratio with P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, including \u003cem\u003ePtAvrLr1\u003c/em\u003e, \u003cem\u003ePtAvrLrB\u003c/em\u003e, \u003cem\u003ePtAvrLr14a\u003c/em\u003e, \u003cem\u003ePtAvrLr3bg\u003c/em\u003e, \u003cem\u003ePtAvrLr14b\u003c/em\u003e, \u003cem\u003ePtAvrLr11\u003c/em\u003e, \u003cem\u003ePtAvrLr2c\u003c/em\u003e, and \u003cem\u003ePtAvrLr28\u003c/em\u003e, were included in the linkage map construction. The minimum spanning tree algorithm was used to assign linkage groups, and the Kosambi mapping function was used to calculate genetic distances in CentiMorgans (cM). Linkage groups were initially determined using a p.value\u0026thinsp;=\u0026thinsp;1e-10 and further selected by a genetic distance of 30 cM to ensure consistency with different chromosomes. Linkage groups with less than three markers were excluded. The number of observed crossovers per individual was estimated using the ASMap package. Linkages without \u003cem\u003eAvr\u003c/em\u003e genes and the A/V segregation phenotypes of \u003cem\u003eAvr\u003c/em\u003e genes in the F\u003csub\u003e2\u003c/sub\u003e population were also used for the QTL analysis. This analysis was performed in R/qtl using the EM algorithm (method = \"em\") and a binary model (model = \"binary\"), which is appropriate for binary phenotypic data. A LOD threshold of 3 was applied for all traits.\u003c/p\u003e\u003cp\u003eRegion-specific association studies\u003c/p\u003e\u003cp\u003eTo strengthen identification of candidate \u003cem\u003eAvr\u003c/em\u003e genes, a complementary approach using region-specific association studies was performed for \u003cem\u003ePtAvrLr14a\u003c/em\u003e, \u003cem\u003ePtAvrLr11\u003c/em\u003e, \u003cem\u003ePtAvrLr1\u003c/em\u003e and \u003cem\u003ePtAvrLr2a\u003c/em\u003e, which were identified by the linkage mapping and QTL analysis. Genomic DNA-derived Illumina reads were generated and treated for each of the 59 \u003cem\u003ePt\u003c/em\u003e Canadian isolates as described above for the progeny. Sequence reads were also aligned to the \u003cem\u003ePt\u003c/em\u003e race 9 haplotype B assembly as described above. Sample TJBJK_98_MB5-2 was eliminated from the study due to the high percentage of missing data (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) and 58 isolates were retained in this natural population to be used for association studies. After filtering samples, variants were called as above yielding 408,473 high-quality markers and 58 isolates were retained in this natural population to be used for GWAS. Markers on contig16, contig3 and contig13 were used for \u003cem\u003ePtAvrLr14a\u003c/em\u003e, \u003cem\u003ePtAvrLr1\u003c/em\u003e, and \u003cem\u003ePtAvrLr3bg\u003c/em\u003e association analysis, respectively. Missing data were imputed with BEAGLE 5.1 [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. The CMLM model [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] implemented in GAPIT (version 3) [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] was used to perform association analysis with three principal components (PCs) as covariates. The associations between SNPs and virulence phenotypes were considered significant if the \u003cem\u003ep\u003c/em\u003e value was below the 5% significance threshold after Bonferroni correction [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Manhanttan plots were drawn using the CMplot package (version 4.2.0) [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] in the R program. FIMO (version 5.5.8) was used to search for regulatory motifs within 50 bp upstream and downstream of significant SNPs, using the JASPAR CORE Fungi database [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eVirulence phenotyping\u003c/p\u003e\u003cp\u003eSamborski and Dyck originally established four F\u003csub\u003e2\u003c/sub\u003e populations (consisting of 43 progeny in F\u003csub\u003e2\u003c/sub\u003e1, 63 in F\u003csub\u003e2\u003c/sub\u003e2, 39 in F\u003csub\u003e2\u003c/sub\u003e3, 76 in F\u003csub\u003e2\u003c/sub\u003e4). Among the four F\u003csub\u003e2\u003c/sub\u003e populations, F\u003csub\u003e2\u003c/sub\u003e1 and F\u003csub\u003e2\u003c/sub\u003e3 were derived from one same F\u003csub\u003e1\u003c/sub\u003e, while F\u003csub\u003e2\u003c/sub\u003e2 and F\u003csub\u003e2\u003c/sub\u003e4 were derived from another shared F\u003csub\u003e1\u003c/sub\u003e. Segregation data of avirulence/virulence (A/V) in the four F\u003csub\u003e2\u003c/sub\u003e populations on different near-isogenic lines (NILs) is presented in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e. For this study, 57 F\u003csub\u003e2\u003c/sub\u003e progeny were revived from the F\u003csub\u003e2\u003c/sub\u003e1 and F\u003csub\u003e2\u003c/sub\u003e3. Parental \u003cem\u003ePt\u003c/em\u003e isolates race 9, race 161, F\u003csub\u003e1\u003c/sub\u003e and the 57 F\u003csub\u003e2\u003c/sub\u003e progeny were tested on 20 NILs in the Thatcher background. All isolates were avirulent to the NILs harboring \u003cem\u003eLr9\u003c/em\u003e, \u003cem\u003eLr16\u003c/em\u003e, \u003cem\u003eLr24\u003c/em\u003e, \u003cem\u003eLr26\u003c/em\u003e, \u003cem\u003eLr3ka\u003c/em\u003e and \u003cem\u003eLr30\u003c/em\u003e, indicating that race 9 and race 161 were homozygous for avirulence on these \u003cem\u003eLr\u003c/em\u003e genes. When tested on \u003cem\u003eLr20\u003c/em\u003e, all isolates showed virulence, suggesting that the parental isolates were homozygous for virulence towards \u003cem\u003eLr20\u003c/em\u003e. As a result, it was not possible using this cross to map these loci responsible for avirulence or virulence using linkage mapping.\u003c/p\u003e\u003cp\u003eRace 161 was avirulent and race 9 was virulent towards \u003cem\u003eLr1\u003c/em\u003e, while the opposite was observed towards \u003cem\u003eLr14a\u003c/em\u003e (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). The F\u003csub\u003e2\u003c/sub\u003e progeny segregated for A/V on both \u003cem\u003eLr1\u003c/em\u003e and \u003cem\u003eLr14a\u003c/em\u003e, fitting a 3:1 ratio, suggesting that avirulence towards \u003cem\u003eLr1\u003c/em\u003e and \u003cem\u003eLr14a\u003c/em\u003e was each controlled by a single dominant gene. Race 9 and race 161 were both avirulent towards \u003cem\u003eLr11\u003c/em\u003e, and a 3:1 A/V segregation ratio was observed in the F\u003csub\u003e2\u003c/sub\u003e progeny, indicating that avirulence towards \u003cem\u003eLr11\u003c/em\u003e was also controlled by a single dominant gene, with parental isolates each being heterozygous avirulent. Even though parental isolates had different phenotypes towards \u003cem\u003eLr2c\u003c/em\u003e, \u003cem\u003eLrB\u003c/em\u003e, \u003cem\u003eLr14b\u003c/em\u003e and \u003cem\u003eLr28\u003c/em\u003e (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e), segregation ratios of A/V in the F\u003csub\u003e2\u003c/sub\u003e progeny fitted a 1:3 ratio, indicating that avirulence to these genes was each controlled by a single recessive gene.\u003c/p\u003e\u003cp\u003eOn the NIL containing \u003cem\u003eLr2a\u003c/em\u003e, the observed A/V ratio of 7:9 in the F\u003csub\u003e2\u003c/sub\u003e progeny indicated that two independent recessive genes controlled avirulence. On \u003cem\u003eLr3\u003c/em\u003e, \u003cem\u003eLr10\u003c/em\u003e, \u003cem\u003eLr17\u003c/em\u003e and \u003cem\u003eLr18\u003c/em\u003e, only a small number of isolates exhibited avirulence/virulence traits different from most isolates in the population. It is very likely that these F\u003csub\u003e2\u003c/sub\u003e progeny did not segregate on these NILs and that some of the isolates are contaminants (see below), or their responses to these NILs were misinterpreted. The segregation of virulence towards \u003cem\u003eLr3bg\u003c/em\u003e more closely fits an A/V ratio of 13:3 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.21), rather than a ratio of 3:1 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03). However, considering the entire isolate population (F\u003csub\u003e2\u003c/sub\u003e1\u0026thinsp;+\u0026thinsp;F\u003csub\u003e2\u003c/sub\u003e3), which yields more precise outcomes, the segregation better conformed to a 3:1 ratio (P\u0026thinsp;=\u0026thinsp;0.90) (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Consequently, it can be inferred that avirulence towards \u003cem\u003eLr3bg\u003c/em\u003e is under the control of a single dominant gene. Detailed phenotypes of progeny isolates are provided in Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eThe fifty-nine \u003cem\u003ePt\u003c/em\u003e isolates in the natural population collected in Canada were also screened on the same 20 wheat differential NILs. Their virulence phenotypes are provided in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. On the 20 isogenic lines tested, all \u003cem\u003ePt\u003c/em\u003e isolates were virulent to \u003cem\u003eLr1\u003c/em\u003e and \u003cem\u003eLr3\u003c/em\u003e. Therefore, in the association study, we were not able to identify SNP markers linked to these avirulence or virulence loci corresponding to \u003cem\u003eLr1\u003c/em\u003e and \u003cem\u003eLr3\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eGenotyping by whole-genome sequencing\u003c/p\u003e\u003cp\u003eFour complete phased haplotype genomes were generated for the two parental isolates \u003cem\u003ePt\u003c/em\u003e race 9 and 161 through the combination of Hi-C and long-reads. The genome of \u003cem\u003ePt\u003c/em\u003e race 9 haplotype B selected for read mapping is of high quality and comprises 18 main contigs that correspond to the 18 predicted \u003cem\u003ePt\u003c/em\u003e chromosomes. It contains 121.3 Mb of DNA and has 24,520 annotated genes (S. Formby, G. Bakkeren et al., manuscript in preparation). To produce genome-wide molecular markers, Illumina HiSeq 2000 technology was used to generate whole genomic DNA-derived sequences of the F\u003csub\u003e1\u003c/sub\u003e and 57 progeny in the bi-parental mapping population from the race 9 x race 161 sexual cross, as well as of the 59 isolates in the natural population collected in Canada (see Material and methods).\u003c/p\u003e\u003cp\u003eFor \u003cem\u003ePt\u003c/em\u003e isolates in the bi-parental mapping population, an average of 31.1\u0026nbsp;million pairs of filtered sequence reads were generated for each isolate, of which 90.2% were mapped to the parental race 9 phased 121.3 Mbp haplotype B reference genome. The mapping coverage ranged from 13.0 to 47.5x with a mean coverage of 34.1x (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). Using the sequence data, 838,419 SNPs were identified, and 310,544 high-quality SNPs were kept after filtering (Fig.\u0026nbsp;1). Only SNPs that were heterozygous in the F\u003csub\u003e1\u003c/sub\u003e were selected, and among them, 5,866 were homozygous in each parental isolate but heterozygous between the two parents (AA/BB type), 19,880 were heterozygous in each parental isolate (AB/AB type), and 46,099 were heterozygous in only one parental isolate (AA/AB or AB/BB type).\u003c/p\u003e\u003cp\u003eTo identify potentially contaminated isolates within the bi-parental mapping population, a Principal Component Analysis (PCA) was performed using a subset of 90K SNP markers. The results revealed that four progeny (19A, 19B, S22, S47) were clearly separated from the main group (Fig.\u0026nbsp;2). These were judged to be contaminants and eliminated from the study (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor the 59 isolates in the natural population, an average of 28.9\u0026nbsp;million pairs of filtered sequence reads were generated for each isolate, with 93.5% of them mapped to the reference genome. The mapping coverage ranged from 22.1 to 49.3x, with a mean coverage of 35.9x (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). To diversify the population, Illumina reads from race 9 and race 161 were also included in the population and a total of 1,210,015 SNPs were identified. After filtering, 408,473 high-quality SNPs were kept and used for the association studies.\u003c/p\u003e\u003cp\u003eGenetic linkage mapping\u003c/p\u003e\u003cp\u003eAfter removing the four contaminated isolates, a total of 21,135 filtered and robust SNPs with a segregation ratio of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05 were selected for constructing a genetic map. Only one of redundant SNPs (SNPs that show the same segregation) was kept and inadequate linkage groups with less than three SNPs were removed. A final genetic map was created revealing 61 linkage groups, comprising a total of 10,923 SNPs and spanning 10,730.5 cM (Fig.\u0026nbsp;1). The individual linkage groups ranged in size from 5.7 to 490.5 cM, and the average genetic distance between SNPs was 1.0 cM throughout the genome (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Comparison between linkage groups and the reference haplotype B genome showed one chromosome could be represented by multiple linkage groups (Fig.\u0026nbsp;1, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Detailed genetic map information is listed in Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e.\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 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLinkage groups in the \u003cem\u003ePuccinia triticina\u003c/em\u003e genetic map\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLinkage Group (LG)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Markers\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGenetic Distance (cM)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean distance between markers (cM)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean recombination rate (cM/10 kb)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eChromosome\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e413\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e490.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e477\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e455.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e559\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e428.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e465\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e418.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e482\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e380.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e289\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e360.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e379\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e354.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e475\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e345.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e320\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e342.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e471\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e329.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e324.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e312.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e309.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e445\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e309.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e364\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e289.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e276.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e266.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e245.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e228.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e271\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e224.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e217.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e186\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e212.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e203.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e274\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e188.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e253\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e186.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e176.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e175.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e166.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e159.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e179\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e144.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e144.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e143.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e147\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e132.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e130\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e127.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e118.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e115.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e114.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e111.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e109.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e90.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e87.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG43\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\u003e83.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e72.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG46\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\u003e62.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG47\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\u003e58.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG50\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\u003e51.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e42.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e41.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e38.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e27.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLG61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003echr8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10923\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10730.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eMarkers were used to anchor the race 9 haplotype B reference genome onto the genetic map. All 18 chromosomes were tagged by SNPs and a total of 107.2 Mb (81.3% of the total genome assembly length) were covered by SNPs. A total of 10,831 single-crossover and 765 double-crossover events were detected in the 53 members of the F\u003csub\u003e2\u003c/sub\u003e population (Fig.\u0026nbsp;3) and the average recombination rate across these linkage groups was estimated to be 0.8 cM/10 kb.\u003c/p\u003e\u003cp\u003eOut of the 20 wheat NILs that were tested, segregation of virulence phenotype among the F\u003csub\u003e2\u003c/sub\u003e progeny was observed in only 13 of them. Among these 13 NILs, it was found that both race 9 and race 161 displayed the same virulence phenotype on \u003cem\u003eLr2c\u003c/em\u003e, \u003cem\u003eLr11\u003c/em\u003e, \u003cem\u003eLr17\u003c/em\u003e, \u003cem\u003eLr10\u003c/em\u003e, \u003cem\u003eLr18\u003c/em\u003e, and \u003cem\u003eLr28\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). To map all possible \u003cem\u003eAvr\u003c/em\u003e genes corresponding to these \u003cem\u003eLr\u003c/em\u003e genes, we attempted both linkage phases, testing whether the \u003cem\u003eAvr\u003c/em\u003e allele was from race 9 or race 161. This way, \u003cem\u003ePtAvrLr11\u003c/em\u003e was successfully mapped to chromosome 3, with the closest marker being chr3_6726200 (Fig.\u0026nbsp;4), under the assumption that the \u003cem\u003eAvr\u003c/em\u003e allele derived from race 161. Among the remaining segregating \u003cem\u003eAvr\u003c/em\u003e genes, \u003cem\u003ePtAvrLr14a\u003c/em\u003e was mapped to the end of chromosome 1, with the closest marker being chr1_8705360 (Fig.\u0026nbsp;4). To map additional \u003cem\u003eAvr\u003c/em\u003e genes, the segregation of A/V in the 53 F₂ progeny was treated as a binary phenotype and analyzed using QTL mapping. For \u003cem\u003ePtAvrLr14a\u003c/em\u003e, one QTL was identified on chromosome 1, with the closely linked marker chr1_8705360, consistent with results from linkage mapping (Fig.\u0026nbsp;5A). For \u003cem\u003ePtAvrLr11\u003c/em\u003e, three QTL were detected on chromosomes 3, 4, and 18, with closely linked SNPs chr3_6726200 (consistent with linkage mapping), chr4_1557250, and chr18_3996934, respectively (Figs.\u0026nbsp;5B-5D). Additional QTLs were also detected for \u003cem\u003ePtAvrLr1\u003c/em\u003e and \u003cem\u003ePtAvrLr2a\u003c/em\u003e. A single QTL for \u003cem\u003ePtAvrLr1\u003c/em\u003e was mapped to chromosome 1, with marker chr1_6500516 (Fig.\u0026nbsp;5E). Two QTLs were detected for \u003cem\u003ePtAvrLr2a\u003c/em\u003e, located on LG8 and LG10, which both reside on chromosome 4 (Fig.\u0026nbsp;5F and 5G). The closely linked SNPs for these QTLs were chr4_4153557 and chr4_4105933, respectively. These two loci most likely represent the same QTL, indicating that \u003cem\u003ePtAvrLr2a\u003c/em\u003e maps to chromosome 4. Candidate genes predicted to be secreted and hence are potential (avirulence) effectors, and located within the QTL regions for \u003cem\u003ePtAvrLr14a\u003c/em\u003e, \u003cem\u003ePtAvrLr11\u003c/em\u003e (on chromosomes 4 and 18), and \u003cem\u003ePtAvrLr2a\u003c/em\u003e (on chromosome 4) were identified and are listed in Table \u003cspan refid=\"MOESM6\" class=\"InternalRef\"\u003eS6\u003c/span\u003e. In contrast, no secreted genes were found within the QTL regions for \u003cem\u003ePtAvrLr1\u003c/em\u003e or \u003cem\u003ePtAvrLr11\u003c/em\u003e on chromosome 3.\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 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhenotypes of parental and F\u003csub\u003e1\u003c/sub\u003e isolates and segregation of avirulent/virulent in the F\u003csub\u003e2\u003c/sub\u003e progeny generated from the sexual cross of \u003cem\u003ePt\u003c/em\u003e race 9 x race161 on differential wheat NILs\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003ePhenotypes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eNo. of progeny isolates\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eexp. ratio\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr\u003c/em\u003e gene\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003erace9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003erace161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF\u003csub\u003e1\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAvirulent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eVirulent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e(A/V)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr1\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3:1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr2a\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e7:9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr2c\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1:3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr3\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHA \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr11\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3:1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr17\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHV \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLrB\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1:3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr10\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr14a\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3:1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr18\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr3bg\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3:1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr14b\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1:3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eLr28\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1:3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ea\u003c/sup\u003e 1\u0026thinsp;=\u0026thinsp;virulence (V); 0\u0026thinsp;=\u0026thinsp;avirulence (A)\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003eb\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e, probability of goodness of fit by a Chi-square test.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ec\u003c/sup\u003e HA, homozygous avirulent\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003csup\u003ed\u003c/sup\u003e HV, homozygous virulent\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRegion-specific association study\u003c/p\u003e\u003cp\u003eAlthough four \u003cem\u003ePt Avr\u003c/em\u003e loci were identified by linkage mapping and QTL analysis, the corresponding genomic regions are relatively large. To refine the position of these potential avirulence effectors at these genomic loci, a region-specific association study was performed using a natural population of 58 isolates collected in Canada (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In this approach, SNPs from corresponding genomic regions were assessed for correlation with the specific A/V on the four respective \u003cem\u003eLr\u003c/em\u003e gene-containing NILs. After the generation of Illumina genomic DNA reads, filtering and aligning to the same \u003cem\u003ePt\u003c/em\u003e race 9 haplotype B assembly, variants were called (see Materials and methods). A total of 408,473 high-quality SNPs were generated for the whole genome. Specific SNPs on chromosomes 1, 3, 4, and 18 were selected to perform the region-specific association studies for \u003cem\u003ePtAvrLr14a\u003c/em\u003e, \u003cem\u003ePtAvrLr11\u003c/em\u003e and \u003cem\u003ePtAvrLr2a\u003c/em\u003e; the association study could not be performed for \u003cem\u003ePtAvrLr1\u003c/em\u003e, since all of the 58 isolates were virulent on the \u003cem\u003eLr1\u003c/em\u003e line.\u003c/p\u003e\u003cp\u003eThree significant SNPs\u0026mdash;chr1_8762635, chr1_8776624, and chr1_9064782\u0026mdash;were identified for \u003cem\u003ePtAvrLr14a\u003c/em\u003e (Fig.\u0026nbsp;4A; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among these, chr1_8762635 is an upstream_gene_variant of PTTG_R9hB_001601, which is predicted to encode a secreted hypothetical protein and chr1_8776624 is in two regulatory motifs (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Similarly, three significant SNPs, chr3_6565157, chr3_6569082, and chr3_6616613, were detected for \u003cem\u003ePtAvrLr11\u003c/em\u003e on chromosome 3 (Fig.\u0026nbsp;4B; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). While none of these were associated with genes encoding secreted proteins, chr3_6565157 overlaps with a C6 zinc cluster transcription factor (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Additionally, two significant SNPs were identified for \u003cem\u003ePtAvrLr2a\u003c/em\u003e on chromosome 4 (Fig.\u0026nbsp;6, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), but neither was associated with secreted protein-coding genes. However, both were located within regulatory motifs, including a CCAAT-binding factor and a C6 zinc cluster factor site. No significant SNPs were identified for \u003cem\u003ePtAvrLr11\u003c/em\u003e on chromosome 4 and 18.\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\u003eSNPs significantly associated with PtAvrLr14a, PtAvrLr11 and PtAvrLr2a\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eAvr\u003c/em\u003e gene\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSNP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnnotation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAssociated Genes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGene Function\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePredicted DNA motifs overlapping the SNP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePtAvrLr14a\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echr1_8762635\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3_prime_UTR_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001599\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001601\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein; SECRETED: SignalP(1\u0026ndash;31)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001602\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eArf GTPase\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001598\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echr1_8776624\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001603\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAminomethyl-transferase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eIXR1: High-mobility group (HMG) domain factors; MATALPHA2: Homeo domain factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001605\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001607\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001604\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e54S ribosomal protein L7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001606\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003etRNA-Pro\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echr1_9064782\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_001661\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePtAvrLr11\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echr3_6565157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eUME6: C6 zinc cluster factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003529\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003526\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003528\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echr3_6569082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003528\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003526\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003525\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003524\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echr3_6616613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003514\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003emetalloendopeptidase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003511\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003510\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003508\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_003506\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePtAvrLr2a\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echr4_4288311\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003emissense_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_005386\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eHAP5 and HAP3: Heteromeric CCAAT-binding factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_005387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_005385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003echr4_4248321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_005373\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eYPR196W: C6 zinc cluster factors\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eupstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_005375\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_005374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ehypothetical protein\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003edownstream_gene_variant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePTR9hB_005376\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34-kDa subunit of RNA polymerase III\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our cross, segregation for avirulence was observed for \u003cem\u003eLr1\u003c/em\u003e, \u003cem\u003eLr2a\u003c/em\u003e, \u003cem\u003eLr2c\u003c/em\u003e, \u003cem\u003eLr11\u003c/em\u003e, \u003cem\u003eLrB\u003c/em\u003e, \u003cem\u003eLr14a\u003c/em\u003e, \u003cem\u003eLr3bg\u003c/em\u003e, \u003cem\u003eLr14b\u003c/em\u003e and \u003cem\u003eLr28\u003c/em\u003e. In terms of inheritance patterns, avirulence in the pathogen seemed to be controlled by single dominant genes towards \u003cem\u003eLr1\u003c/em\u003e, \u003cem\u003eLr11\u003c/em\u003e, \u003cem\u003eLr14a\u003c/em\u003e and \u003cem\u003eLr3bg\u003c/em\u003e. Conversely, avirulence appeared to be controlled by single recessive genes towards \u003cem\u003eLr2c\u003c/em\u003e, \u003cem\u003eLrB\u003c/em\u003e, \u003cem\u003eLr14\u003c/em\u003eb, and \u003cem\u003eLr28\u003c/em\u003e. The inheritance of avirulence towards \u003cem\u003eLr2a\u003c/em\u003e did not fit single gene models, suggesting that multiple genes may be involved in this case.\u003c/p\u003e\u003cp\u003ePrevious studies [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] have reported similar inheritance patterns for avirulence to \u003cem\u003eLr1\u003c/em\u003e, \u003cem\u003eLr11\u003c/em\u003e, \u003cem\u003eLr14a\u003c/em\u003e, and \u003cem\u003eLr14b\u003c/em\u003e. However, there is notable variability in the inheritance patterns of the remaining \u003cem\u003eAvr\u003c/em\u003e genes between our study and previous studies. In our study, segregation of F\u003csub\u003e2\u003c/sub\u003e progeny on \u003cem\u003eLr2c\u003c/em\u003e fit a 1:3 ratio, while isolates from the entire population (F\u003csub\u003e2\u003c/sub\u003e1\u0026thinsp;+\u0026thinsp;F\u003csub\u003e2\u003c/sub\u003e3) followed a 7:9 segregation ratio (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e), suggesting two independent recessive genes for avirulence. Samborski and Dyck [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], as well as Statler [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] found that avirulence to \u003cem\u003eLr2c\u003c/em\u003e and \u003cem\u003eLr2a\u003c/em\u003e was governed by single dominant genes in different sexual crosses of \u003cem\u003ePt\u003c/em\u003e, which differs from the findings of our study. Samborski and Dyck [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] reported that two genes seemed to condition virulence on \u003cem\u003eLrB\u003c/em\u003e, while in our study the segregation ratio suggested a single recessive gene for avirulence towards \u003cem\u003eLrB\u003c/em\u003e. Similarly, Statler [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] in a different sexual cross, suggested avirulence on \u003cem\u003eLr28\u003c/em\u003e was determined by a single dominant gene, whereas our study revealed that avirulence on \u003cem\u003eLr28\u003c/em\u003e was controlled by a recessive gene in the F\u003csub\u003e2\u003c/sub\u003e population.\u003c/p\u003e\u003cp\u003eHaggag \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] found that segregation of virulence towards \u003cem\u003eLr3\u003c/em\u003e fit a 3:1 and 13:3 ratio in two F\u003csub\u003e2\u003c/sub\u003e populations, suggesting that avirulence was governed by a dominant gene and an additional gene in the pathogen, possibly \u003cem\u003ePtAvr3bg\u003c/em\u003e. More recently, Statler [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], based on his own cross, identified a digenic ratio of virulence towards \u003cem\u003eLr3\u003c/em\u003e. In our study, F\u003csub\u003e2\u003c/sub\u003e progeny did not segregate on \u003cem\u003eLr3\u003c/em\u003e. However, when examining isolates from the entire population (F\u003csub\u003e2\u003c/sub\u003e1\u0026thinsp;+\u0026thinsp;F\u003csub\u003e2\u003c/sub\u003e3), their segregation followed a 13:3 ratio (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e), consistent with the findings by Haggag \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The segregation fit a 3:1 ratio on \u003cem\u003eLr3bg\u003c/em\u003e, indicating the involvement of a single dominant gene.\u003c/p\u003e\u003cp\u003eThe inconsistent inheritance patterns of avirulence in \u003cem\u003ePt\u003c/em\u003e observed across various studies can be attributed to the isolate-dependent nature of avirulence inheritance, a phenomenon that has also been reported in other rust fungi [\u003cspan additionalcitationids=\"CR49 CR50\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Avirulence to a host resistance gene can be controlled by a single gene in one isolate but by two or more genes in another isolate, or exhibit a switch from dominant to recessive inheritance. Additionally, it is possible that some of the wheat cultivars used to test \u003cem\u003ePt\u003c/em\u003e populations were not pure \u003cem\u003eLr\u003c/em\u003e single-gene lines, which would compound the interactions between such host lines and \u003cem\u003ePt\u003c/em\u003e races. Lastly, it should be noted that when the size of the test population is small, misclassification of segregation is more likely to occur. For instance, the misplacement of intermediate interactions can have a larger impact on segregation ratios in a small population.\u003c/p\u003e\u003cp\u003eIn general, the markers belonging to each chromosome exhibited proximity in the genetic map, aligning well with the physical map (Table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003eS5\u003c/span\u003e). However, certain inconsistencies were observed. For example, although markers from the same chromosome were often positioned closely in the genetic map, their locations did not always show a linear correlation. Furthermore, one chromosome is represented by multiple linkage groups. These inconsistencies could potentially be attributed to two factors: firstly, the highly repetitive nature of the \u003cem\u003ePt\u003c/em\u003e genome can complicate the mapping process, and secondly, the presence of structural variations between the two parental isolates used in the study.\u003c/p\u003e\u003cp\u003eIn this study, the generated genetic map of \u003cem\u003ePt\u003c/em\u003e spanned a total genetic distance of 10,730.5 cM, which is comparable to other rust fungi. For instance, in the pine fusiform rust fungus \u003cem\u003eCronartium quercuum\u003c/em\u003e f. sp. \u003cem\u003efusiforme\u003c/em\u003e, a genetic map spanning 3006 cM was constructed for its 76.6 Mb genome [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Similarly, Anderson \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] generated a genetic map spanning 5,860 cM for the 189.5 Mb genome of the flax rust fungus \u003cem\u003eM\u003c/em\u003e. \u003cem\u003elini\u003c/em\u003e. Another example is from the wheat stripe rust fungus \u003cem\u003eP. striiformis\u003c/em\u003e f. sp. \u003cem\u003etritici\u003c/em\u003e, for which Xia \u003cem\u003eet al\u003c/em\u003e. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] generated a genetic map spanning 7,715 cM for its 84.5 Mb genome. The construction of the linkage map in this study involved selecting markers without segregation distortion. This selection criterion resulted in a substantial reduction in the number of markers, leading to some parts of the genome not being tagged by markers. The resulting 61 linkage groups representing the 18 chromosomes of the \u003cem\u003ePt\u003c/em\u003e haploid genome can be attributed to this factor. It is likely that regions lacking developed markers caused the fragmentation of linkage groups. Additionally, the presence of genetic gaps exceeding the 30 cM threshold used in map construction might have occurred in regions characterized by repetitive DNA sequences. These factors contribute to the understanding of the challenges faced in achieving complete and contiguous linkage groups for \u003cem\u003ePt\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThe recombination rate in \u003cem\u003ePt\u003c/em\u003e exhibited significant variations among different linkage groups as well as within regions of the same linkage group (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;3). In the F\u003csub\u003e2\u003c/sub\u003e population, an average of 204.4 single-crossover and 14.4 double-crossover events per individual were detected, which was higher compared to the 115 crossover events in \u003cem\u003eM\u003c/em\u003e. \u003cem\u003elini\u003c/em\u003e [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and 133.2 events in \u003cem\u003eP. striiformis\u003c/em\u003e f. sp. \u003cem\u003etritici\u003c/em\u003e [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Previous studies have suggested that the recombination rate is influenced by factors such as repetitive DNA content and the percentage of CpG island [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. However, further research is needed to gain a deeper understanding of the regulatory mechanisms governing recombination in filamentous fungi.\u003c/p\u003e\u003cp\u003eIn this study, a total of four \u003cem\u003eAvr\u003c/em\u003e loci were found using multiple methods. \u003cem\u003ePtAvrLr14a\u003c/em\u003e was mapped to the telomeric region of chromosome 1 by both linkage mapping and QTL analysis. Region-specific association studies using a natural \u003cem\u003ePt\u003c/em\u003e population also identified significant SNPs at the telomere of chromosome 1, further supporting this finding. \u003cem\u003ePtAvrLr11\u003c/em\u003e on chromosome 3 was similarly mapped by both linkage mapping and QTL analysis. However, the QTL associated with \u003cem\u003ePtAvrLr11\u003c/em\u003e on chromosome 3 had the lowest LOD score among the three QTLs identified on chromosomes 3, 4, and 18 by QTL analysis. In addition, segregation of A/V phenotypes indicated that avirulence towards \u003cem\u003eLr11\u003c/em\u003e is controlled by a single dominant gene, suggesting that only one of these three QTLs represents the true \u003cem\u003ePtAvrLr11\u003c/em\u003e locus. Significant SNPs were identified for \u003cem\u003ePtAvrLr14a\u003c/em\u003e, \u003cem\u003ePtAvrLr2a\u003c/em\u003e and \u003cem\u003ePtAvrLr11\u003c/em\u003e (on chromosome 3). Only one SNP (chr1_8762635) associated with \u003cem\u003ePtAvrLr14a\u003c/em\u003e, was linked to a gene encoding a predicted secreted protein, indicating its potential role as an (\u003cem\u003eAvr\u003c/em\u003e) effector. Interestingly, a majority of these significant SNPs were found in intergenic regions, in between candidate predicted genes/ORFs. Studies have shown that non-coding SNPs associated with diseases are often located in or near regulatory regions, suggesting their potential to disrupt or modify the binding sites of transcription factors and other regulatory proteins [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Consequently, these SNPs may influence gene expression patterns to impact phenotypic traits. Thus, the significant SNPs identified in the intergenic regions of this study and located within regulatory motifs, such as chr1_8776624, chr3_6565157, chr4_4248321 and chr4_4288311, could potentially interfere with the normal functioning of regulatory elements, leading to altered gene expression and the observed phenotypic variations.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eA comprehensive genetic map was successfully constructed for \u003cem\u003ePt\u003c/em\u003e, providing a valuable resource for genomics research in this pathogen. By utilizing this genetic map in conjunction with the complete phased \u003cem\u003ePt\u003c/em\u003e genome, genomic features such as recombination rate were estimated. By integrating linkage mapping and region-specific association approaches, significant SNPs associated with \u003cem\u003ePtAvrLr14a\u003c/em\u003e were identified with high confidence. These findings represent a significant advancement in our quest to clone and characterize \u003cem\u003eAvr\u003c/em\u003e genes and shed light on the molecular mechanisms underlying the complex interactions between this pathogen and its host.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSets of sequence read data from this study were deposited in the National Center for Biotechnology Information\u0026rsquo;s Sequence Read Archive and are accessible through the BioProject Accession IDs PRJNA1111826 (Canadian isolate reads, Table S1; confidential for now and for reviewers only: https://dataview.ncbi.nlm.nih.gov/object/PRJNA1111826?reviewer=4qrfvpevd52i466ej7jega1g9m) and PRJNA1259536 (progeny reads, Table S3; confidential for now and for reviewers only: https://dataview.ncbi.nlm.nih.gov/object/PRJNA1259536?reviewer=4cogjl39o7c4h7jls2iingt6dv). The \u003cem\u003ePt\u003c/em\u003e race9 haplotype B genome and its annotation can be found at NCBI under project number PRJNA1298919 (provisional and confidential link for now and for reviewers only: https://drive.google.com/drive/folders/1sMUGtqqWc_DbjLHgOIJTk7j2rT15XeMU?usp=sharing).\u003c/p\u003e\n\u003cp\u003e[Reviewers, data will be released at the NCBI upon publication of this study)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was designed by BMc and GB, and co-funded by BMc, BS and GB. BM and BMc were responsible for isolate collections and performed phenotyping, and BM and DLJ initial mapping. BM performed gDNA isolations. SF assembled and haplophased the rust genomes, and S-HK, ML and SF performed genome annotations. LL performed all genetic map constructions and GWAS. GB and LL wrote the manuscript, and all authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Curt McCartney for support with the initial map constructions, and Rob Linning for his outstanding technical assistance. The Michael Smith Genome Sciences Centre in Vancouver, BC, Canada, is acknowledged for their expert advice and sequencing of all samples, under supervision of Dr. Richard Moore.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded partly through Canada\u0026rsquo;s Digital Technology Supercluster Program, project \u0026ldquo;Computational Biochemistry Platform for Crop Health,\u0026rdquo; the Genome BC Strategic Opportunities Fund, SOF131 project \u0026ldquo;Poplar and cereal rust comparative genomics: identification of pathogen determinants to prevent and predict epidemics\u0026rdquo;, the Natural Resources Canada\u0026rsquo;s Genomics Research and Development Initiative (both, joint R. Hamelin and G. Bakkeren), and an Ontario Ministry of Research and Innovation grant #RE-03-056, \u0026ldquo;Genomics Approaches to Mitigate Fungal Threats to Crops\u0026rdquo; (joint B. Saville and G. Bakkeren). We also gratefully acknowledge the support of the Agriculture and Agri-Food Canada Genomics Initiative.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBolton MD, Kolmer JA, Garvin DF. Wheat leaf rust caused by Puccinia triticina. Mol Plant Pathol. 2008;9(5):563\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuerta-Espino J, Singh RP, Germ\u0026aacute;n S, McCallum BD, Park RF, Chen WQ, Bhardwaj SC, Goyeau H. Global status of wheat leaf rust caused by Puccinia triticina. Euphytica. 2011;179(1):143\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKolmer JA, Jin Y, Long DL. Wheat leaf and stem rust in the United States. Aust J Agric Res. 2007;58(6):631\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcCallum BD, Hiebert CW, Cloutier S, Bakkeren G, Rosa SB, Humphreys DG, Marais GF, McCartney CA, Panwar V, Rampitsch C, et al. 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Bioinformatics. 2009;25(14):1754\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDanecek P, Bonfield JK, Liddle J, Marshall J, Ohan V, Pollard MO, Whitwham A, Keane T, McCarthy SA, Davies RM, Li H. Twelve years of SAMtools and BCFtools. GigaScience. 2021;10(2):giab008.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics. 2011;27(21):2987\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCingolani P, Platts A, Wang le L, Coon M, Nguyen T, Wang L, Land SJ, Lu X, Ruden DM. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso\u0026ndash;2; iso\u0026ndash;3. 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Nucleic Acids Res. 2024;52(D1):D174\u0026ndash;82.\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":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Puccinia triticina, Avirulence, Genetic linkage map, Association mapping, Wheat leaf rust, Whole-genome sequencing","lastPublishedDoi":"10.21203/rs.3.rs-7264203/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7264203/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eWheat rust fungi can cause significant damage to wheat crops, leading to reduced yields and economic losses. To combat disease, certain plant varieties can trigger defense responses upon recognition of specific pathogen effector proteins, causing avirulence. Identifying such avirulence (\u003cem\u003eAvr\u003c/em\u003e) genes is crucial for developing strategies to protect crops from devastating losses, from identifying matching resistance genes to designing diagnostic assays for monitoring pathogen populations. \u003cem\u003ePuccinia triticina\u003c/em\u003e (\u003cem\u003ePt\u003c/em\u003e) causes wheat leaf rust and is an obligate biotrophic fungus, and because of its life cycle and mode of reproduction, it is difficult to study genetically.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eTo identify \u003cem\u003eAvr\u003c/em\u003e genes in \u003cem\u003ePt\u003c/em\u003e, a F\u003csub\u003e2\u003c/sub\u003e population of fifty-seven progeny was generated from a sexual cross of race 9 (SBDG) and race 161 (FBDJ) on the alternate host \u003cem\u003eThalictrum speciosissimum\u003c/em\u003e under controlled conditions. The population segregated for avirulent/virulent traits screened at the seedling stage on thirteen single gene resistance lines in the wheat host cultivar Thatcher background. The genomes of the parents, F\u003csub\u003e1\u003c/sub\u003e, and progeny were sequenced and mapped onto an assembled parental race 9 phased haplotype B genome, resulting in the generation of 21,154 high-quality SNP markers suitable for genetic mapping of the F\u003csub\u003e2\u003c/sub\u003e population. A genetic map composed of 61 linkage groups was obtained, containing a total of 10,923 markers, and spanning 10,730.5 centimorgans. Effector loci correlating with avirulence to specific leaf rust resistance (\u003cem\u003eLr\u003c/em\u003e) genes, \u003cem\u003ePtAvrLr14a\u003c/em\u003e, \u003cem\u003ePtAvrLr11\u003c/em\u003e and \u003cem\u003ePtAvrLr2a\u003c/em\u003e, were mapped to chromosome 1, chromosome 3 and chromosome 4, respectively. To strengthen the identification of candidate \u003cem\u003eAvr\u003c/em\u003e genes, a region-specific association study was done on a natural population of fifty-nine \u003cem\u003ePt\u003c/em\u003e isolates that were collected in Canada and whose genomes were sequenced using Illumina.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eSignificant markers and corresponding candidate effector genes were identified for these mapped \u003cem\u003eAvr\u003c/em\u003e loci. The identification of these candidate genes is an essential step towards cloning \u003cem\u003eAvr\u003c/em\u003e and subsequentially their matching host resistance genes, and for studying the molecular mechanisms underlying pathogen-host interactions and host defense.\u003c/p\u003e","manuscriptTitle":"Avirulence genes identified through linkage mapping and region-specific association studies in the wheat leaf rust pathogen Puccinia triticina","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-22 14:28:55","doi":"10.21203/rs.3.rs-7264203/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-09T07:08:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-08T17:09:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-29T16:01:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-23T13:09:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"336514132430750902291622140341044581399","date":"2025-08-20T07:29:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"56433158978635051322236469753117876542","date":"2025-08-18T18:35:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"94562678051715213178628561526409973537","date":"2025-08-16T16:55:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-15T11:08:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-14T22:29:22+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-12T15:52:06+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2025-08-12T15:48:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c047b7e2-6311-4565-97ca-f8da3dcae400","owner":[],"postedDate":"August 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T16:10:11+00:00","versionOfRecord":{"articleIdentity":"rs-7264203","link":"https://doi.org/10.1186/s12864-026-12579-0","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2026-02-04 15:58:22","publishedOnDateReadable":"February 4th, 2026"},"versionCreatedAt":"2025-08-22 14:28:55","video":"","vorDoi":"10.1186/s12864-026-12579-0","vorDoiUrl":"https://doi.org/10.1186/s12864-026-12579-0","workflowStages":[]},"version":"v1","identity":"rs-7264203","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7264203","identity":"rs-7264203","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}