{"paper_id":"00a5c60e-86d1-4a4c-99c9-d19dafd74e9c","body_text":"Genetic mapping, marker development , and identification of candidate \ngenes for powdery mildew resistance in Malus baccata 'Jackii' \nAuthors: Matthias Pfeifer1,2, Leonard Kurzweg3, Buist Muçaj1,4, Tom Burkhardt5, Andreas Peil1, Henryk \nFlachowsky1, Ofere Francis Emeriewen1 & Thomas Wöhner1 \n \n1Julius Kühn-Institut (JKI) - Federal Research Centre for Cultivated Plants, Institute for Breeding Research on Fruit Crops, \nDresden-Pillnitz, Germany \n2Institute of Plant Genetics, Department of Molecular Plant Breeding, Leibniz University Hannover, Hannover, Germany \n3Faculty of Biology, Technical University of Dresden, Dresden, Germany \n4Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany \n5Faculty of Agriculture/Environment/Chemistry, University of Applied Sciences, Dresden, Germany \n \nCorrespondence: ofere.emeriewen@julius-kuehn.de; thomas.woehner@julius-kuehn.de \n \n \nAbstract \nPowdery mildew, caused by Podosphaera leucotricha, is one of the most important fungal diseases in \napple cultivation worldwide. Malus baccata 'Jackii', however, exhibits resistance to this pathogen, and \na previous study demonstrated that this resistance co -segregates with an AFLP marker  on linkage \ngroup 10. The objectives of this study were to construct genetic linkage maps, develop molecular \nmarkers, and identify candidate genes associated with this powdery mildew resistance, making use of \nthe Malus baccata 'Jackii' genome sequence. An F1 population derived from the cross 'Idared' × Malus \nbaccata 'Jackii' was phenotyped from 2009-11 and 2023-24 and genotyped with SNPs generated from \ntGBS and SSRs. Genetic linkage maps of Malus baccata 'Jackii' were constructed, and QTL mapping \nconfirmed the presence of the powdery mildew resistance locus Plbj on linkage group 10. In addition, \na minor QTL was detected on linkage group five. Closely linked SSR and KASP markers were developed, \nand the Plbj locus was delimited to a 3,287,286-bp region on haplotype one of the Malus baccata \n'Jackii' genome, in which resistance gene candidates were identified. This study supports the direct \napplication of molecular markers in breeding program mes and provides an essential background for \nfuture functional studies of Plbj. \n \nIntroduction \nThe domesticated apple ( Malus domestica Borkh.) is an important temperate fruit crop that faces \nmultiple biotic stresses, and changes in climate and pathogen populations may further increase disease \nimpact (Hanke et al. 2020; Strickland et al. 2021).  Among the most significant pathogen s is powdery \nmildew, caused by species of the genus Podosphaera. These fungi are highly adaptable and can infect \nover 10,000 plant species with frequent reports of host jumps and host range expansions (Kusch et al. \n2024). Consequently, a perpetual race eme rges between the fungus and plant breeders, who must \npersistently monitor and seek novel resistances. Podosphaera leucotricha (Ellis & Everh.), the primary \npowdery mildew pathogen of apple, has also been observed on other hosts such as Photinia × fraserii, \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nPrunus africana and Pyrus calleryana (Garibaldi et al. 2005; Minnis et al. 2010; Mwanza et al. 2001). \nThis obligate biotrophic, ascomycetous, heterothallic, ectoparasitic fungus  causes considerable \neconomic losses and increases production costs in apple cultivation each year (Coyier 1974; Takamatsu \n2013; Yoder 2000). The mycelium overwinters inside buds and, after bud burst, initiates primary \ninfections, which cause delayed growth and deformations of shoots, leaves, flowers and fruits  \n(Strickland et al. 2021). Sexual reproduction via ascospores is possible but appears to play a minor role \nin disease spread, whereas the formation of asexual conidia can drive multiple secondary infection \ncycles within a single season  (Strickland et al. 2021).  Management strategies to prevent yield losses \ninclude crop cultural practices, as well as chemical and biological measures (Strickland et al. 2021). The \nfungicides currently used in apple cultivation remain effective against the pathogen (Strickland et al. \n2023). Their use in consistent rotation is essential to prevent resistance development (Strickland et al. \n2023), especially since the emergence of fungicide resistance in powdery mildew has been frequently \nobserved (Lesemann et al. 2006; Vielba -Fernández et al. 2020).  T he most desirable and \nenvironmentally sustainable strategy to control apple powdery mildew is the growing of resistant \ncultivars. This approach can also make apple production more economical by reducing both the risk of \nyield losses and the costs of control measures. \nVarious major resistances to powdery mildew, defined as single genes or clusters of genes with large \neffects providing qualitative resistance, are present in the genus Malus. Pl-1 and Pl-2 were identified \nin Malus × robusta and Malus × zumi (Knight and Alston 1968) , P-lw in 'White Angel' (Gallott et al. \n1985), Pl-d in accession D12 (Visser and Verhaegh 1980), Pl-m in Mildew Immune Selection (Bus et al. \n2010; Dayton 1977) and Plbj in Malus baccata 'Jackii' (Dunemann and Schuster 2009) . Furthermore, \npowdery mildew resistance has also been reported in the apple clone U 211 (Stankiewicz‐Kosyl et al. \n2005) and in Malus florentina and Malus sieboldii (Schuster 2000). Moreover, the knock-down of the \nexpression of Mildew Locus 0 (MLO) genes could have the potential to make apple trees more resistant \nto powdery mildew, though further research is required to fully understand the mechanisms involved \n(Pessina et al. 2016; Pessina et al. 2017). As observed in apple, powdery mildew resistance genes can \nbe overcome, as shown for Pl-1 (Kellerhals et al. 2013; Krieghoff 1995)  and Pl-2 (Caffier and Laurens \n2005; Caffier and Parisi 2007). Therefore, the combination (pyramiding) of different powdery mildew \nresistance genes in a cultivar should be the objective, as this has the potential to increase the durability \nof the resistance  (Mundt 2018) . Consequently, it remains of great importance not only to identify \nadditional resistance genes, but also  to facilitate th e utilisation of existing ones.  A previous study \nreported the presence of the Plbj resistance locus on linkage group (LG) 10 in Malus baccata 'Jackii' \n(Dunemann and Schuster 2009) . T he primary objective s of this study  were to generate a \nhigher-resolution map of LG 10, further narrow down the genetic region containing the Plbj resistance \nlocus, and verify whether Plbj is still effective in our experimental field . Therefore, offspring from a \ncross between 'Idared' and M. baccata 'Jackii' (hereafter referred to as Mbj) were genoty ped using \nvarious marker systems and phenotyped for susceptibility to powdery mildew over several years in the \nexperimental field at the Julius Kühn-Institut (JKI) in Dresden-Pillnitz, Germany. An additional aim was \nto develop molecular markers tightly linked to Plbj for application in marker-assisted selection (MAS) \nand to identify resistance gene candidates using the haplotype -resolved genome sequence of Mbj \n(Pfeifer et al. 2025, preprint). \n \nResults \nPhenotyping results of the 'Idared' × Mbj F1 populations \nAn overview of the phenotyping results is presented in Table 1. In the primary mapping population in \nthe field (122 F1 individuals of 'Idared' × Mbj, designated 05225 and 06228) the highest mean powdery \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nmildew score was observed in summer 2023 (2.76), whereas the lowest mean score occurred in spring \n2010 (1.34). Maximum disease severity a mong the offspring ranged from seven to nine , indicating \nconsistently high infection pressure  in the field . Across all years, 71 individuals were classified as \nresistant, while 51 were scored as susceptible at least once. In 2023 and 2024 , only 120 individuals \ncould be evaluated due to the loss of two genotypes. Spearman correlation coefficients between field \nassessments ranged from 0.61 (summer 2010 vs.  spring 2011) t o 0.97 (spring 2023 vs.  spring 2024). \nPhenotypic distributions consistently showed a right-skewed pattern. In the secondary F1 population \n(127 individuals, designated 24230) from the same cross combination, phenotyped in the greenhouse \nin 2025, 46 individuals were resistant and 81 were susceptible.  Considering both populations, a total \nof 117 were classified as resistant and 132 as susceptible. \n \nTable 1  Overview of phenotyping results from the 'Idared' × Malus baccata  'Jackii' F1 populations in the field and the \ngreenhouse \nGenotypes Time point of \npowdery mildew \nassessment \nLocation Mean score \nin offspring \nMax. value \nin offspring \nResistant \ngenotypesa \nSusceptible \ngenotypesb \n05225 and 06228  Spring 2009 Field 1.89 9 94 28 \n Summer 2009  2.32 9 81 41 \n Spring 2010  1.34 7 109 13 \n Summer 2010  1.51 7 109 13 \n Spring 2011  1.82 7 103 19 \n Summer 2011  2.40 7 92 30 \n Spring 2023  2.08 7 75 45 \n Summer 2023  2.76 9 71 49 \n  Spring 2024  2.20 8 74 46 \n24230 Summer 2025 Greenhouse / / 46 81 \na Resistant genotypes: scores 0-3 in 2009-11, score 1 in 2023-24. b Susceptible genotypes:  scores 4-9 in 2009-11, scores 2-9 \nin 2023-24. Different phenotyping scales were applied in 2009 -11 and 2023-24; in 2025 plants were only classified as either \nresistant or susceptible. \n \nGenetic linkage map of Mbj haplotype 1 \nA genetic linkage map was constructed for Mbj haplotype 1 (HT1), comprising 17 linkage groups with \na total length of 1,071 centimorgans ( cM). From the 324,420 non -imputed single-nucleotide \npolymorphism (SNP) markers, 261,000 were excluded as they were either homozygous in Mbj or were \ninconsistent across the four Mbj replicates. From the remaining 63,420 SNPs (19.6%), those with > 10% \nmissing data in the progeny and chi -square values ≥ 10 were discarded, resulting in 29, 245 SNP \nmarkers. From the imputed data of these markers , a total of 2,043 with the largest inter-marker \ndistances were loaded into JoinMap 5, and after excluding identical markers, this resulted in 948 SNP \nmarkers being distributed across the 17 LGs. Of the 63 simple sequence repeat (SSR) markers selected \nfrom the HiDRAS website (HiDRAS 2025), 58 could be assigned to the 17 LGs , with three of them \ndisplaying multilocus alleles. Of the seven newly developed SSRs, five were mapped to LG 10, and one \neach to LG 5 and LG 7. Table S1 provides an overview of the number of markers per LG and their genetic \nlengths. Figure S1 shows the 17 LGs, including marker names and their respective positions in cM. \n \nQTL analysis reveals the major Plbj resistance locus and a novel minor locus \nKruskal-Wallis (KW) analysis using the phenotypic data of the primary F1 mapping population, together \nwith the constructed genetic linkage map, revealed a consistent and significant association of markers \non LG 10 and LG 5 with resistance to powdery mildew across all the phenotyped time points in 2009, \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \n2010, 2011, 2023, and 2024. The highest KW values for markers on LG 10 ranged from 51.15 to 109.04 \n(df = 1 or 3; significance level: p < 0.0001), whereas those for LG 5 ranged from 9.67 to 17.96 (df = 1; \nsignificance level: p < 0.005). Interval mapping confirmed significant associations on both LGs 10 and \n5. Table 2 presents the markers with the highest  LOD scores on these LGs. The major QTL on LG 10 \nshowed LOD scores ranging from 16.34 to 35.73, while the minor QTL on LG 5 had scores between 2.49 \nand 4.63. A permutation test showed that the QTL on LG 10 consistently exceeded the genome-wide \nthreshold, whereas the QTL on LG 5 surpassed the genome-wide significance threshold only with data \nfrom spring 2009. In spring 2011 and 2023, as well as in the summers of 2009-11, LOD scores on LG 5 \nonly exceeded the chromosome-wide significance threshold. Figure 1 shows the LOD score profiles for \nthe identified QTLs on LGs 10 and 5. Whereas the QTL on LG 10 explained up to 74% of the phenotypic \nvariance, th e Q TL on LG  5 explained between 9.1 % and 16.0 % of the phenotypic variance. Newly \ndeveloped SSR markers LKSSRchr10_1478 and LKSSRchr10_ 2718 were found to flank the QTL region \non LG  10, with LKSSRchr10_1998 and LKSSRchr10_2318B being highly linked to the QTL  peak. \nLKSSRchr5_Mbj2 was associated with resistance conferred by the minor QTL on LG 5. \n \nTable 2 Markers with the highest LOD scores on linkage groups 10 and 5 \nTime point of \npowdery mildew \nassessment \nLinkage \ngroup \nMarker with highest LOD \nscore \nLOD \nscore \nExplained \nvariance (%) \nAverage \nphenotypic score \nwith/without \nresistance allele \nSignificance with \npermutation test at a 95% \nconfidence level \nSpring 2009 10 HT1_LG10_25523367 26.92 63.8 0.39 / 3.92 Genome-wide \nSummer 2009  LKSSRchr10_2318B 35.73 74.0 0.43 / 4.96 Genome-wide \nSpring 2010  LKSSRchr10_2318B 20.39 53.7 0.19 / 2.88 Genome-wide \nSummer 2010  LKSSRchr10_1978 19.87 52.8 0.43 / 2.84 Genome-wide \nSpring 2011  LKSSRchr10_2318B 16.34 46.0 0.78 / 3.37 Genome-wide \nSummer 2011  LKSSRchr10_2318B 21.24 55.1 1.22 / 4.22 Genome-wide \nSpring 2023  LKSSRchr10_2318B 25.50 62.4 1.03 / 3.56 Genome-wide \nSummer 2023  LKSSRchr10_2318B 34.27 73.2 1.00 / 5.28 Genome-wide \nSpring 2024  LKSSRchr10_2318B 26.56 63.9 1.05 / 3.90 Genome-wide \nSpring 2009 5 HT1_LG05_33612433 4.63 16.0 2.50 / 4.48a Genome-wide \nSummer 2009  HT1_LG05_31890599 3.85 13.5 3.93 / 5.42a Chromosome-wide only \nSpring 2010  HT1_LG05_23262271 2.92 10.5 2.13 / 3.27a Not significant \nSummer 2010  HT1_LG05_31890599 4.00 14.0 2.18 / 3.34a Chromosome-wide only \nSpring 2011  HT1_LG05_31890599 4.09 14.3 2.43 / 3.65a Chromosome-wide only \nSummer 2011  HT1_LG05_31890599 3.24 11.5 3.62 / 4.25a Chromosome-wide only \nSpring 2023  HT1_LG05_31890599 2.78 10.1 2.87 / 3.93a Chromosome-wide only \nSummer 2023  HT1_LG05_31890599 2.49 9.1 4.56 / 5.66a Not significant \nSpring 2024  HT1_LG05_31890599 2.62 9.6 3.12 / 4.24a Not significant \na For linkage group 5 only offspring without Plbj were considered to avoid distortion in the average phenotypic score. \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \n \nFigure 1 LOD score profiles of the identified QTLs on linkage group 10 (A) and 5 (B) of Malus baccata 'Jackii', derived from \npowdery mildew infection data at various time points, indicating the approximate position of Plbj. T1: time point 1 (spring), \nT2: time point 2 (summer). The dotted line represents the genome-wide significance threshold. SSRs developed in this \nproject are shown in bold and SSRs selected from the HiDRAS website (HiDRAS 2025) in italics. For a better readability, only \na subset of markers is presented. \n \nPlbj is located between markers LKSSRchr10_1998 and LKSSRchr10_2318B \nIn the primary mapping population in the field ( 122 F1 individuals), all plants lacking the resistance-\nassociated SSR allele of LKSSRchr10_2318B were phenotyped as susceptible to powdery mildew in the \n2023-24 dataset, whereas only one individual carrying the resistance alleles of all five newly developed \nSSRs on LG 10 was also phenotyped as susceptible. Phenotyping in 2009-11 identified seven individuals \ncarrying susceptibility alleles of these five SSRs that were nonetheless phenotyped as resistant. In the \nsecondary population ( 127 greenhouse-grown F1 individuals), three  individuals also showed \ngenotype-phenotype incongruence  as they carried only resistance -associated SSR alleles but were \nphenotyped as susceptible, whereas all individuals lacking resistance-associated marker alleles were \nphenotyped as susceptible. Among the 45 Mbj seedlings (pollinated by F 1 individuals derived from \n'Idared' × Mbj), five individuals with recombinations between LKSSRchr10_1478 and LKSSRchr10_2718 \nwere identified.  One showed visible powdery mildew  symptoms, while the rema ining four were \npresumed resistant;  however, confirmation under higher powdery mildew pressure  is required . \nMapping of Plbj as a single qualitative trait using the 2023 -24 phenotypic dataset of the primary \nmapping population positioned the locus between SSR markers  LKSSRchr10_1998 and \nLKSSRchr10_2318B (Figure 2). To validate this, 26 individuals with recombinations between \nLKSSRchr10_1478 and LKSSRchr10_2718 from different populations were examined. A comparison of \nthese recombinants ( Figure 3) revealed that genotypes possess ing the resistance alleles of \nLKSSRchr10_1998 and LKSSRchr10_2318B exhibited a resistant phenotype, whereas genotypes lacking \nthe resistance alleles at both markers exhibited a susceptible phenotype. In contrast, the presence of \nonly one resistance allele at either of the two markers could result in either a resistant or a susceptible \nphenotype due to recombination events. Individuals 06228-068, 24230-043 and Jackii-OA-115 indicate \nthat Plbj lies downstream of  LKSSRchr10_1998, whereas 24230-039 and Jackii -OA-81 suggest it is \nupstream of LKSSRchr10_2318B. Taken together, these findings delimit Plbj to the interval  between \nLKSSRchr10_1998 and LKSSRchr10_2318B. \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \n \nFigure 2 Genetic linkage map of linkage group 10 of haplotype 1 of Malus baccata 'Jackii', showing the approximate position \nof Plbj. SSRs developed in this project are shown in bold, SSRs selected from the HiDRAS website (HiDRAS 2025) in italics, \nand Plbj is indicated with a bold red italic label. \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \n \nFigure 3 Graphical representation of the Plbj region based on SSR markers. Twenty-six individuals show recombination \nevents between SSR markers LKSSRchr10_1478 and LKSSRchr10_2718, suggesting that Plbj is located between the SSR \nmarkers LKSSRchr10_1998 and LKSSRchr10_2318B. Genotypes 05225 and 06228 are recombinant individuals from the \nprimary F1 mapping population maintained in the field, whereas genotypes 24230 (secondary F1 population) and Jackii-OA \n(Malus baccata 'Jackii' seedlings pollinated by F1 individuals derived from 'Idared' × Malus baccata 'Jackii') are maintained in \nthe greenhouse. R: resistance allele, S: susceptibility allele. For the Plbj locus/phenotype R denotes a resistant and S \ndenotes a susceptible phenotype; an asterisk indicates resistance presumed due to low powdery mildew pressure. \n \nSNP and BLAST-supported SSR marker analysis identifies resistance-associated haplotypes \nA comparison between  the expected PCR product sizes of the newly developed SSRs and  those \nobserved in the fragment length analysis revealed differences of up to five bp. Nevertheless, the size \ndifferences between resistance - and susceptibility -associated alleles within each marker were \nconsistent with the expected values. When phenotypic data were included, it became evident that Plbj \nis linked to the marker alleles assigned to HT1. In contrast, lower average disease scores in individuals \nlacking Plbj were associated with allele 111 from LKSSRchr5_Mbj2, indicating that the minor QTL on \nLG 5 is located on HT 2. SSR LKSSRchr10_1438, designed for LG 10 based on the GDDH13 genome \n(Daccord et al. 2017) , amplified fragments that were not linked to powdery mildew resistance and \ninstead mapped to LG 7 in Mbj. An overview of the results for the six newly developed SSRs linked to \npowdery mildew resistance is provided in Table S2. The assignment of Plbj and the minor QTL on LG 5 \nto their respective haplotypes was further confirmed by examining selected SNP markers linked to the \ntwo resistance loci. Based on the known parental alleles and the segregation pattern in the F₁ progeny, \nthe resistance-associated SNPs contributed by Mbj could be assigned to the corresponding haplotypes. \nAs shown in Table 3, Plbj is located on HT1, while the minor QTL on LG 5 is located on HT2. \n \n \n \n \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nTable 3 SNP marker-based identification of resistance-associated haplotypes in Malus baccata 'Jackii' \nMarker SNP-alleles in \n'Idared' \nSNP-allele in \nMalus baccata \n'Jackii' \nhaplotype 1 \nSNP-allele in \nMalus baccata \n'Jackii' \nhaplotype 2 \nResistance-\nassociated \nSNP-allele \ncombination in \noffspring \nResistance-\nassociated \nSNP-allele in \nMalus baccata \n'Jackii' \nHT1_LG10_22316956 GG C G CG C \nHT1_LG10_24866698 CC T C TC T \nHT1_LG10_25523367 TT T C TT T \nHT1_LG05_29627853 GG A G GGa G \nHT1_LG05_33612433 AA A T ATa T \nHT1_LG05_33849016 AA G A AAa A \na For linkage group 5 only offspring without Plbj were considered to avoid distortion in identifying the resistance-associated \nSNP-allele combination. \n \nValidation of KASP markers through comparison to SSR markers \nThe newly developed Kompetitive Allele Specific PCR (KASP) markers KASP_HT1_LG10_20042456 and \nKASP_HT1_LG10_23962775, located between LKSSRchr10_1478 and LKSSRchr10_1978, and between \nLKSSRchr10_1998 and LKSSRchr10_2318B, respectively, showed complete concordance with the SSR \nmarker data. No  apparent double recombination events were observed between the flanking SSR \nmarkers in any individual of the  primary F 1 mapping population . Specifically, for \nKASP_HT1_LG10_20042456, the resistance-associated allele was consistently linked to the THex allele, \nand for KASP_HT1_LG10_23962775, resistance was associated with the G Hex allele. Moreover, the  \nKASP-assays were tested on nine founders of apple  'Idared', 'Golden Delicious', 'Granny Smith', \n'Delicious', 'Cox Orange', 'Jonathan', 'Mcintosh', 'Braeburn' and 'Gala'  and all of them consistently \nexhibited the FAM-labeled C-allele linked to susceptibility to powdery mildew in Mbj. \n \nResistance gene candidates within the Plbj locus on HT1 \nThe region of interest, defined as the interval  between markers LKSSRchr10_1998 and \nLKSSRchr10_2318B on HT1 ( specifically from position 21,391,236 to 24,678,521 bp, spanning \n3,287,286 bp ), contains a total of 209 annotated genes  (Table S3 ). Among these, 29 genes were \nidentified as the most likely resistance gene candidates (Table S4). \n \nDiscussion \nPowdery mildew is one of the most important fungal diseases in apple, and its impact may further \nincrease in the future (García-Gómez et al. 2024; Strickland et al. 2021). At the same time, demand for \nreduced pesticide use is  steadily growing, making genetic host resistance increasingly important  in \nsustainable apple production. P yramiding different resistance genes not on ly has the potential to \nincrease durability but  can even reduce disease severity beyond that of the single most effective \nresistance gene (Mundt 2018). Consequently, substantial efforts in apple breeding aim to combine \nhigh fruit quality with multiple resi stance genes targeting either the same pathogen or different \ndiseases simultaneously  (Baumgartner et al. 2015; Kellerhals et al. 2013) . For powdery mildew, \ngenotypes carrying Pl-1 and Pl-2 have been bred (Kellerhals et al. 2013) . However, both of these \nresistance genes have already been overcome when deployed individually (Caffier and Laurens 2005; \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nCaffier and Parisi 2007; Kellerhals et al. 2013; Krieghoff 1995) . This highlights the urgent need to \nincorporate additional, more robust sources of powdery mildew resistance into apple cultivars. \nIn the present study, a genetic linkage map of Mbj HT1 was generated, spanning a total length of 1,071 \ncM, which is comparable to previously published genetic linkage maps in apple  (Celton et al. 2009; \nEmeriewen et al. 2020; Norelli et al. 2017) . Most of the SNP markers were ordered consistently with \ntheir physical positions, supporting the overall accuracy of the map. Moreover, nearly all mapped SSR \nmarkers correspond ed well with p ositions reported on the HiDRAS website  (HiDRAS 2025) . When \ncomparing the physical positions of SNP markers of each chromoso me to the position of  the \ncorresponding linkage group, it became  evident that the SNPs typically started within the first few \nmegabases and ex tended toward the chromosome ends , while gaps remain in some intermediate \nregions. One notable exception was LG 7, where the first mapped SNP marker was located at 31 Mb, \nand the linkage group itself measured only  19.1 cM. This suggests that the proximal region of \nchromosome 7 is a recombination -poor region in the studied population, likely resulting in the \nexclusion of markers up to 31 Mb during linkage map construction. Importantly, this linkage map \nallowed the detection of loci associated with powdery mildew resistance on LG 5 and LG 10. \nBecause powdery mildew in apple is caused by various pathogen strains (Gañán-Betancur et al. 2021; \nLesemann et al. 2004; Urbanietz and Dunemann 2005) , phenotypic evaluation under  natural, \nhigh-disease-pressure field conditions over multiple years can be considered a robust method to assess \nthe durability and effectiveness of a resistance gene . Therefore, the result of this study, namely that \nPlbj was consistently detected in an F 1 population from 2009-11 and 2023-24 under field conditions \nwithout fungicide application, assessed by two different persons with different assessment scales,  \nexhibits the durability and heritability of this resistance . LOD scores on LG  10 exceeded the \ngenome-wide significance threshold at every phenotyping time point. The percentage of explained \nvariance varied between the phenotyping time points, likely due to differences in disease pressure and \nweather conditions , but reached  up to 74%. Since  similarly high LOD scores  (> 25) and explained \nvariances (> 65%) have been reported for major resistance genes against fire blight  (Broggini et al. \n2014; Emeriewen et al. 2014; Emeriewen et al. 2018; Fahrentrapp et al. 2013; Peil et al. 2007),  it can \nbe hypothesised that Plbj also represents a major monogenic resistance gene. Therefore, the precise \nidentification and delimitation of the genomic  region harbouring Plbj is crucial . In this study , the \ncandidate region could be narrowed down to a 3,287,286 bp interval through genetic mapping. Since \nthis region has been sequenced (Pfeifer et al.  2025, preprint ), an initial prediction of 29 potential \nresistance genes was possible. This represents an important first step toward the functional analysis \nof Plbj. Nevertheless, future fine-mapping approaches using more recombinants, combined with the \ndevelopment of additional markers in the candidate region, are expected to further improve resolution \nand narrow down the locus. Moreover, the recent availability of the Podosphaera leucotricha genome \nwill facilitate future r esearch on the fungus itself as well as  host-pathogen interactions (Gañán et al. \n2020), especially once specific resistance genes in Mbj have been identified. \nThe strong effect of Plbj was clearly detectable in all years of the study. However, a few genotype-\nphenotype incongruences were observed. One genotype that carried the resistance marker alleles of \nthe five newly develepod SSRs on LG 10  was nevertheless scored as susceptible, with scores of three \nand four  at two field phenotyping time points  in 2023 and 2024 . As this genotype  was scored as \nresistant in most years, a misclassification in those two years , possibly due to confusion with \nsusceptible neighbouring trees, appears plausible. Conversely, three greenhouse -grown individuals \nfrom the 24230 population carried the resistance marker alleles of Plbj, but still showed noticeable \npowdery mildew symptoms in 2025. Possible explanations include mutations in the resistance gene \nitself, the presence of modifier genes suppress ing resistance expression, or stress -induced \nsusceptibility caused by limited plant spacing, reduced sunlight and partial spider mite infestation  in \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nthe greenhouse. Furthermore, greenhouse conditions are markedly different from field conditions and \nhave an influence on powdery mildew susceptibility  (Jeger et al. 1986) . Interestingly, it has already \nbeen described that genotypes with Pl-m appearing susceptible under artificial conditions still exhibit \nresistance in the field (Bus et al. 2010), suggesting that similar effects may explain these observations. \nIn addition to Plbj, a minor QTL on LG 5 HT2 was identified, showing chromosome-wide significance in \nthree out of five scoring years. This QTL has not been previously reported by Dunemann and Schuster \n(2009). It remains unclear whether this locus represents a single gene or polygenic resistance. \nHowever, as the phenotypic variance explained by this locus was only up to 16%, compared to 74% for \nPlbj, and the LOD p eak was noticeably flatter, it can be hypothesi sed that resistance at this locus is \npolygenic. Polygenic resistance is often more durable than monogenic major resistance genes  \n(Parlevliet 2002) . Therefore, minor QTL s such as the one detected  on LG 5 should  not be \nunderestimated. Indeed, it has been reported that QTLs for powdery mildew resistance on LGs 1, 8, \n10, 14, and 17 are sometimes identified only in specific years , with phenotypic variation explained \nranging from 5.1 to 19.5 %, i n contrast to stable QTLs on LGs 2 and 13 , for which the  phenotypic \nvariation explained ranges from 7.5 to 27.4 % across years (Calenge and Durel 2006) . In our study, a \nQTL peak on LG 5  was observed in all years, even when it did not consistently exceed the \nchromosome-wide significance threshold  in interval mapping . This , together with  a significant KW \nassociation, suggests that the underlying  resistance effect was present across  all years but varied  in \nstrength between years. \nMolecular markers are nowadays crucial for MAS , allowing selection based solely on genotypic \ninformation. For various powdery mildew resistance genes  in apple, molecular markers have been \nreported (Bus et al. 2010; Dunemann et al. 2007; Dunemann and Schuster 2009; García -Gómez et al. \n2024; Gardiner et al. 2003; James and Evans 2004; Luo et al. 2019; Markussen et al. 1995; Seglias and \nGessler 1997). However, some of these resistance genes, such as Pl-1 (Kellerhals et al. 2013; Krieghoff \n1995) and Pl-2 (Caffier and Laurens 2005; Caffier and Parisi 2007),  have already been overcome and \nfor others, like Plbj, the previously most closely linked marker was an AFLP/SCAR marker. In contrast, \nSSR and KASP markers are now more commonly used.  In this study, we employed the published \nhaplotype-resolved genom e sequence of Mbj (Pfeifer et al . 2025 , preprint ), which facilitate d the \ndevelopment of five SSR and two KASP markers linked to the resistance locus on LG  10 and one SSR \nlinked to the resistance on LG 5. KASP markers are becoming increasingly important, as their analysis \nis relatively cheap and rapid, requiring only a real -time PCR machine  rather than a  costly capillary \nelectrophoresis genetic analyser. The markers reported here can now be readily used in apple breeding \nprogrammes to efficiently select progenies with Plbj resistance.  The potential presence of both a major \nmonogenic resistance locus ( Plbj) and a minor polygenic QTL in Mbj makes this genotype highly \nattractive for breeding, as it may allow  the combination of  both types of resistance, each with its \nrespective advantages, within a single donor genotype. Moreover, Mbj has previously been shown to \nexhibit resistance to apple scab  (Gygax et al. 2004) , several strains of fire blight  (Vogt et al. 2013; \nWöhner et al. 2018), and tolerance to Diplocarpon coronariae (Wöhner et al. 2021). Taken together, \nMbj represents an exceptionally valuable donor for future apple resistance breeding, which is gaining \nin importance for sustainable apple production. \n \nMaterials and methods \nPlant material \nThe apple cultivar 'Idared' and the apple genotype Mbj are susceptible and resistant to powder y \nmildew, respectively (Figure 4). A cross between 'Idared' and Mbj resulted in 122 F1 individuals (05225 \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nand 06228 genotypes ), which served as the primary mapping population for this study. These \nprogenies are cultivated in the experimental field of the Julius Kühn -Institut (JKI) in Dresden -Pillnitz, \nGermany, without fungicide protection.  Additionally, our study included a rece ntly developed \nsecondary population consisting of 127 individuals fr om the same cross combination ( 24230 \ngenotypes), as well as 45 seedlings derived from Mbj pollinated by F 1 individuals of 'Idared' × Mbj \n(designated as Jackii-OA), all of which are maintained under greenhouse conditions without fungicide \napplication. \n \nFigure 4 Symptoms of powdery mildew on 'Idared' (A), and absence of symptoms on Malus baccata 'Jackii' (B). \n \nPowdery mildew phenotyping \nPhenotyping of natural powdery mildew infestation was conducted for the primary mapping \npopulation (05225 and 06228 genotypes) in the field during the spring and summer of 2009, 2010, \n2011 and 2023. In 2024, assessments were performed only in spring, as th e trees were pruned \nafterwards and the prevalence of powdery mildew post-pruning was too low for a reliable evaluation. \nTable 4 shows the phenotyping scales for the assessment of powdery mildew infestation. The scale \napplied in 2023 and 2024 was published by Lateur et al. (2022). For 2009-11, plants with powdery \nmildew infestation scores of zero to three  were classified as resistant, whereas those with scores of  \nfour to nine were classified as susceptible. For 2023 -24, plants with a score of one were considered \nresistant, while those with scores from two to nine  were considered susceptible. Plants grown in the \ngreenhouse (24230 and Jackii -OA genotypes) were classified only as either resistant or susceptible, \nwithout any intermediate categories, based on the presence or absence of disease symptoms resulting \nfrom natural infection. \n \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nTable 4 Used phenotyping scales for powdery mildew infection \nScore Phenotyping scale 2009-11 Phenotyping scale 2023-24 (Lateur et al. 2022) \n0 No visible symptom not applicable \n1 Very few sporulating dots No visible symptom (0%) \n2 Very few to few sporulating dots One or very few organs affected, detectable on close \nscrutiny of the tree (0-1%) \n3 Up to 25% of the tree affected by infected \nleaves/shoots \nInfected organs readily apparent but without \nimportant consequences for the tree (1-5%) \n4 Intermediate rating Intermediate rating \n5 Up to 50% of the tree affected by infected \nleaves/shoots \nPrimary mildew widespread over the branches, \ninducing the infection of a substantial part of the \ncrown (± 25%) \n6 Intermediate rating Intermediate rating \n7 Up to 75% of the tree affected by infected \nleaves/shoots \nHeavy infection; half of the organs are badly affected \n(± 50%) \n8 Intermediate rating Intermediate rating \n9 Up to 100% of the tree affected by infected \nleaves/shoots \nCrown completely affected, nearly all top of the \norgans are infected (> 90%) \n \ntGBS genotyping and SNP identification \nYoung leaves of the 122 F1 individuals of the primary mapping population along with four replicates of \nboth parents were harvested, lyophilised, and sent to Data2Bio (Ames, IA, USA) for DNA extraction and \ntunable genotyping -by-sequencing (tGBS) analysis  (Ott et al. 2017)  using the restriction enzyme \nBsp1286I and an Illumina HiSeq X instrument (Illumina, Inc., San Diego, CA, USA), according to the \ncompany's specifications. tGBS genotyping and SNP identification were performed as described by \nPfeifer et al. (2025, preprint). Briefly, quality-trimmed sequence reads, excluding regions with a PHRED \nscore ≤ 15, were aligned to HT1 of the Mbj genome using GSNAP (Wu and Nacu 2010). Only confidently \nmapped reads that aligned to a unique location in HT1 were used for SNP identification. For \nhomozygous SNPs, the most common allele had to be supported by at least 80% of all aligned reads at \na given position and confirmed by a minimum of five unique reads. For heterozygous SNPs, the two \nmost common alleles each had to be supported by at  least 30% of the aligned reads at that position \nand confirmed by at least five unique reads. The minimum calling rate for SNPs across the population \nwas set to ≥ 50%, and the minor allele frequency had to be ≥ 10%. Finally, SNPs lacking a sufficient \nnumber of reads to make genotype calls were imputed using Beagle v5.4 (Browning et al. 2018). Similar \nempirical parameters, which aim to minimise false positive and false negative SNP calls, have already \nbeen applied in wild Malus species (Emeriewen et al. 2020) and other plants (Li et al. 2018; Zheng et \nal. 2018). \n \nSSR marker sourcing, development and genotyping \nSince tGBS-derived SNPs are not easily transferable to other sample sets, we sourced SSR markers from \nthe literature to serve as anchor markers for the  construction of genetic linkage maps (Celton et al. \n2009; Emeriewen et al. 2014; Emeriewen et al. 2017; Hemmat et al. 2003; Hokanson et al. 1998; \nLiebhard et al. 2002; Silfverberg -Dilworth et al. 2006; Vinatzer et al. 2004; Yamamoto et al. 2002a; \nYamamoto et al. 2002b). Initially, 115 SSRs were selected to be distributed across all 17 chromosomes \nof Malus, from the HiDRAS website (HiDRAS 2025) and tested for polymorphism in the parents 'Idared' \nand Mbj and a subset of six offspring. Of the 71 SSRs showing polymorphisms in Mbj, a total of 63 were \nused in this study (Table S5). In addition, seven new SSRs were developed to flank the resistance loci. \nTherefore, SSR motifs were searched for in the genome sequences of GDDH13 v1.1  (Daccord et al. \n2017) and Mbj (Pfeifer et al. 2025, preprint), in the regions identified by preliminary QTL mapping and \nprimer pairs (Table S6 ) were designed using Primer3web v4.1.0  (Koressaar and Remm 2007; \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nUntergasser et al. 2007) . The 122 F 1 individuals (05225 and 06228 genotypes)  grown in the field and \nboth parents were genotyped with the 63 SSRs selected f rom the HiDRAS website (Table S5) and the \nseven newly developed SSR markers (Table S6). The 127 F1 individuals (24230 genotypes) cultivated in \nthe greenhouse, as well as the 45 Mbj seedlings (Jackii-OA genotypes), were genotyped with only five \nof the newly developed SSR markers. \n \nDNA isolation, PCR and fragment analysis \nDNA was extracted from leaves using the DNeasy Plant Mini Kit (Qiagen, Hilden, Germany) according \nto the manufa cturer's protocol. DNA quantification was performed with the NanoDrop One C \nspectrophotometer (Thermo Fisher Scientific Inc., Waltham, MA, USA). Multiplex-PCR was conducted \nusing the Type-it Microsatellite PCR Kit (Qiagen, Hilden, Germany). The PCR reaction mix consisted of \n1 μl primer or primer mix (each primer at a concentration of 1 pmol/µl), 1 μl ddH 2O, 5 μl Type -it \nMultiplex PCR Master Mix, 1 μl Q-solution, and 2 μl DNA (10 ng/μl). The PCR conditions were as follows: \ninitial denaturation at 95°C for 5 minutes, followed by 32 cycles of 95°C for 1 minute, 60°C for 1 minute \nand 30 seconds, and 72°C for 1 minute, with a final elongation step at 60°C for 30 minutes. The PCR \nproducts were then diluted 1:100 with ddH 2O, and 1 μl of this dilution was mixed with 9  μl of \nABI-solution (a mixture of 1 ml Hi -Di formamide and 6 μl GeneScan-600 LIZ size standard, both from \nApplied Biosystems, Waltham, MA, USA). The samples were then denatured at 95°C for 5 minutes prior \nto analysis using the Applied Biosystems 3500xL Genetic Analyzer (Applied Biosystems, Waltham, MA, \nUSA). GeneMapper Software v6 (Applied Biosystems, Waltham, MA, USA) was used to visualise and \nanalyse the SSR alleles. \n \nConstruction of genetic linkage maps \nPrior to genetic linkage map construction, the 324,420 non-imputed SNP markers for the Mbj HT1 were \nfiltered. In the first step, all SNP markers that did not yield identical results across all four replicates of \n'Idared' and Mbj, were excluded. SNP markers with more than 10% missing values in the progeny were \nalso excluded. For hk×hk and nn×np markers, chi-square values were calculated, and only markers with \nvalues below 10 were retained. For each linkage group, SNPs were ranked  by physical inter -marker \ndistance and all markers with inter -marker distances of 100 kb or greater were included and at least \n120 markers per group were selected. From the selected SNPs, the imputed genotypic data along with \nthe 70 SSRs were used for the construction of the genetic map of Mbj using JoinMap 5  (Van Ooijen \n2018). The final map of Mbj was calculated after the exclusion of identical markers and correcting \nimplausible double-recombinations using the regression mapping algorithm and Kosambi's map ping \nfunction. Linkage maps were visualised using MapChart (Voorrips 2002). \n \nQTL analysis \nThe SNP and SSR genotypic data of the primary F1 mapping population (05225 and 06228 genotypes), \nthe final genetic map of Mbj together with multi -year phenotypic datasets, were used to determine \ngenotype-phenotype associations and conduct QTL analysis using MapQTL 5  (Van Ooijen 2004) . \nKruskal-Wallis analysis was applied to identify markers significantly associated with the phenotypic \ndata, whereas interval mapping was used to localise the corresponding QTL intervals. A permutation \ntest at a 95% confidence level was conducted to assess the significance of identified QTLs by \ndetermining the LOD threshold at both the genome -wide and chromosome -wide levels (Van Ooijen \n2004). \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \n \nMapping resistance as a single qualitative trait \nTo map resistance as a single qualitative trait, named Plbj, phenotypic data from 2023-24 for the 122 \nF1 individuals in the field (05225 and 06228 genotypes) were transformed for each individual into \nresistant (score one) or susceptible (scores two to nine ). These data were then  added to the other \nmolecular markers on LG 10, and the genetic map was calculated using JoinMap 5 (Van Ooijen 2018). \n \nAssigning resistance-linked markers to haplotypes of Mbj \nTo identify the resistance-associated haplotypes of Plbj and the minor QTL on LG 5, two independent \napproaches were applied. In the first approach , the primer sequences of the newly developed SSR \nmarkers were aligned to the genome sequences of both haploty pes of Mbj (Pfeifer et al. 2025, \npreprint) using the Basic Local Alignment Search T ool (BLAST; Altschul et al. 1990)  and CLC Main \nWorkbench 25.0 (Qiagen, Venlo, Netherlands). Expected PCR product sizes in base pairs were \ncalculated by considering the distance between the outermost primer positions in the haplotypes and \naccounting for any additional bases present in the primers but absent from the assembled genome. \nThe expected PCR product sizes were then compared with the fragment sizes observed in the fragment \nlength analysis. In the second approach, the alleles of nn×np SNP markers from both parents and the \nprimary mapping population ( 122 F 1 individuals) were examined. Based on the inheritance patterns \nand the assumption that Mbj is the resistance donor, the SNP alleles associated with resistance were \nidentified. In both approaches, resistance -associated markers were determined by comparing the \nmean disease scores of the 122 F 1 individuals for the respective alle le combinations and assigning \nresistance to the markers associated with lower average disease severity. For the assignment of the \nminor QTL on LG 5, only individuals lacking Plbj were taken into account to avoid distortion of the \ndisease score average caused by Plbj when identifying the resistance-associated markers. \n \nKASP marker development and genotyping \nBased on the genetic linkage map, two KASP markers were developed in proximity to Plbj. The SNP \npositions of these KASP markers are reflected in their na mes: KASP_HT1_LG10_20042456 and \nKASP_HT1_LG10_23962775. Primer sequences for these KAS P markers are listed in Table S7 .  KASP \ngenotyping was performed using a reaction mix consisting of the KASP assay mix (a mixture of two \nallele-specific forward primers a nd one common reverse primer), KASP -TF V4.0 2 × Master Mix (LGC \nGroup, Teddington, England) and DNA. Reactions were run on a CFX96 Touch Real-Time PCR Detection \nSystem (Bio-Rad Laboratories, Inc., Hercules, CA, USA). The 10 µl KASP reaction contained 5 μl 2× KASP \nmaster mix, 0.14 μl KASP assay mix, 1 μl DNA (10 ng/μl) and 3.86 μl ddH2O. PCR was performed under \nthe following conditions: an initial activation at 94°C for 15 minutes, followed by 10 cycles of \ndenaturation at 94°C for 20 seconds and annealing/elongation for 1 minute with a temperature \ngradient from 61 to 55°C (decreasing 0.6°C per cycle), and then 26 cycles of 94°C for 20 seconds and \n55°C for 1 minute and finally, a 1-minute step at 37°C for the read stage. Data analysis was performed \nwith CFX Manager v3.1 (Bio-Rad Laboratories, Inc., Hercules, CA, USA). DNA from the cultivars 'Idared', \n'Golden Delicious', 'Granny Smith', 'Delicious', 'Cox Orange', 'Jonathan', 'Mcintosh', 'Braeburn', 'Gala' \nand Mbj were used as control for the validation of the KASP markers. \n \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nIdentification of resistance gene candidates in the genome of Mbj \nResistance geme candidates were identified based on annotation data published by Pfeifer et al. (2025, \npreprint). Genes  that were annotated with an NB -ARC domain ( PF00931), leucine -rich repeat \nN-terminal domain (PF08263), TIR domain (PF01582), Rx N -terminal domain (PF18052) or associated \nwith the Gene Ontology terms defence response (GO:0006952), response to other organism \n(GO:0051707) or protein kinase activity (GO:0004672), as well as proteins whose names contained the \nterm disease resistance, were considered the most likely resistance gene candidates. \n \nAcknowledgements \nParts of this work were supported by the Federal Ministry of Agriculture, Food and Regional Identity \nby decision of the Parliament of the Federal Republic of Germany via the Federal Office for Agriculture \nand Food (BLE) under the innovation support programmes 281D108X21 and 281D109A21. Language \nediting was supported using DeepL Write and ChatGPT (OpenAI), which were used for language \nimprovement only. \n \nAuthor Contributions \nConception: Ofere Francis Emeriewen, Andreas Peil, Thomas Wöhner and Henryk Flachowsky. Strategy \nand design: Matthias Pfeifer, Ofere Francis Emeriewen, Andreas Peil  and Thomas Wöhner. Analyses \nand writing: Matthias Pfeifer. Plant material: Matthias Pfeifer and Andreas Peil. Phenotyping: Matthias \nPfeifer and Andreas Peil . Primer design: Ofere Francis Emeriewen and Leonard Kurzweg. Marker \nanalyses: Matthias Pfeifer,  Ofere Francis Emeriewen, Leonard Kurzweg,  Buist Muçaj and Tom \nBurkhardt. Genetic map  construction: Matthias Pfeifer, Andreas Peil, Ofere Francis Emeriewen and \nLeonard Kurzweg. QTL analyses: Matthias Pfeifer, Ofere Francis Emeriewen, Andreas Peil and Leonard \nKurzweg.  Genomic analyses: Matthias Pfeifer and Thomas Wöhner. Funding: Andreas Peil and Thomas \nWöhner. Supervision: Ofere Francis Emeriewen, Andreas Peil, Thomas Wöhner and Henryk \nFlachowsky. Revision: All authors. All authors read and approved the final manuscript. \n \nData Availability Statement \nThe data underlying this article will be shared on reasonable request to the corresponding author. \n \nConflicts of Interests \nThe authors declare no conflicts of interests. \n \nReferences \nAltschul, S. F., W. Gish, W. Miller, E. W. Myers, and D. J. Lipman. 1990. “Basic local alignment search \ntool.“ Journal of Molecular Biology 215: 403–410. \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nBaumgartner, I. O., A. Patocchi, J. E. Frey, A. Peil, and M. Kellerhals. 2015. “Breeding Elite Lines of \nApple Carrying Pyramided Homozygous Resistance Genes Against Apple Scab and Resistance Against \nPowdery Mildew and Fire Blight.“ Plant Molecular Biology Reporter 33: 1573–1583. \nBroggini, G. A. L., T. Wöhner, et al. 2014. “Engineering fire blight resistance into the apple cultivar \n'Gala' using the FB_MR5 CC-NBS-LRR resistance gene of Malus × robusta 5.“ Plant Biotechnology \nJournal 12: 728–733. \nBrowning, B. L., Y. Zhou, and S. R. Browning. 2018. “A One-Penny Imputed Genome from Next-\nGeneration Reference Panels.“ The American Journal of Human Genetics 103: 338–348. \nBus, V. G. M., H. C. M. Bassett, et al. 2010. “Genome mapping of an apple scab, a powdery mildew \nand a woolly apple aphid resistance gene from open-pollinated Mildew Immune Selection.“ Tree \nGenetics & Genomes 6: 477–487. \nCaffier, V., and F. Laurens. 2005. “Breakdown of Pl2, a major gene of resistance to apple powdery \nmildew, in a French experimental orchard.“ Plant Pathology 54: 116–124. \nCaffier, V., and L. Parisi. 2007. “Development of apple powdery mildew on sources of resistance to \nPodosphaera leucotricha, exposed to an inoculum virulent against the major resistance gene Pl‐2.“ \nPlant Breeding 126: 319–322. \nCalenge, F., and C.-E. Durel. 2006. “Both stable and unstable QTLs for resistance to powdery mildew \nare detected in apple after four years of field assessments.“ Molecular Breeding 17: 329–339. \nCelton, J.-M., D. S. Tustin, D. Chagné, and S. E. Gardiner. 2009. “Construction of a dense genetic \nlinkage map for apple rootstocks using SSRs developed from Malus ESTs and Pyrus genomic \nsequences.“ Tree Genetics & Genomes 5: 93–107. \nCoyier, D. L. 1974. “Heterothallism in the Apple Powdery Mildew Fungus, Podosphaera leucotricha.“ \nPhytopathology 64: 246–248. \nDaccord, N., J.-M. Celton, et al. 2017. “High-quality de novo assembly of the apple genome and \nmethylome dynamics of early fruit development.“ Nature genetics 49: 1099–1106. \nDayton, D. F. 1977. “Genetic Immunity to Apple Mildew Incited by Podosphaera leucotricha.“ \nAmerican Society for Horticultural Science 12: 225–226. \nDunemann, F., A. Peil, A. Urbanietz, and T. Garcia‐Libreros. 2007. “Mapping of the apple powdery \nmildew resistance gene Pl1 and its genetic association with an NBS‐LRR candidate resistance gene.“ \nPlant Breeding 126: 476–481. \nDunemann, F., and M. Schuster. 2009. “Genetic characterization and mapping of the major powdery \nmildew resistance gene Plbj from Malus baccata jackii.“ Acta Horticulturae 814: 791–798. \nEmeriewen, O., K. Richter, et al. 2014. “Identification of a major quantitative trait locus for resistance \nto fire blight in the wild apple species Malus fusca.“ Molecular Breeding 34: 407–419. \nEmeriewen, O. F., A. Peil, K. Richter,E. Zini, M.-V. Hanke, and M. Malnoy. 2017. “Fire blight resistance \nof Malus ×arnoldiana is controlled by a quantitative trait locus located at the distal end of linkage \ngroup 12.“ European Journal of Plant Pathology 148: 1011–1018. \nEmeriewen, O. F., K. Richter, et al. 2020. “Construction of a dense genetic map of the Malus fusca fire \nblight resistant accession MAL0045 using tunable genotyping-by-sequencing SNPs and \nmicrosatellites.“ Scientific Reports 10: 16358. \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nEmeriewen, O. F., K. Richter, et al. 2018. “Towards map-based cloning of FB_Mfu10: identification of \na receptor-like kinase candidate gene underlying the Malus fusca fire blight resistance locus on \nlinkage group 10.“ Molecular Breeding 38: 106. \nFahrentrapp, J., G. A. L. Broggini, et al. 2013. “A candidate gene for fire blight resistance in Malus × \nrobusta 5 is coding for a CC–NBS–LRR.“ Tree Genetics & Genomes 9: 237–251. DOI: 10.1007/s11295-\n012-0550-3. \nGallott, J. C., R. C. Lamb, and H. S. Aldwinckle. 1985. “Resistance to Powdery Mildew from Some \nSmall-fruited Malus Cultivars.“ American Society for Horticultural Science 20: 1085–1087. \nGañán, L., R. A. White III, M. L. Friesen, T. L. Peever, and A. Amiri. 2020. “A Genome Resource for the \nApple Powdery Mildew Pathogen Podosphaera leucotricha.“ Phytopathology 110: 1756–1758. \nGañán-Betancur, L., T. L. Peever, K. Evans, and A. Amiri. 2021. “High Genetic Diversity in \nPredominantly Clonal Populations of the Powdery Mildew Fungus Podosphaera leucotricha from U.S. \nApple Orchards.“ Applied and Environmental Microbiology 87: e00469-21. \nGarcía-Gómez, B. E., S. Bühlmann-Schütz, M. Hodel, A. Patocchi, and M. J. Aranzana. 2024. \n“Development of SNP markers for the powdery mildew resistance gene Pl1 in apple.“ Acta \nHorticulturae 1412: 299–306. \nGardiner, S. E., J. Murdoch, et al. 2003. “Candidate resistance genes from an EST database prove a \nrich source of markers for major genes conferring resistance to important apple pests and diseases.“ \nActa Horticulturae 622: 141–151. \nGaribaldi, A., G. Gilardi, and M. L. Gullino. 2005. “First Report of Powdery Mildew Caused by \nPodosphaera leucotricha on Photinia × fraserii in Italy.“ Plant Disease 89: 1362. \nGygax, M., L. Gianfranceschi, R. Liebhard, M. Kellerhals, C. Gessler, and A. Patocchi. 2004. “Molecular \nmarkers linked to the apple scab resistance gene Vbj derived from Malus baccata jackii“. Theoretical \nand Applied Genetics 109: 1702–1709. \nHanke, M.-V., H. Flachowsky, A. Peil, and O. F. Emeriewen. 2020. “Chapter 19.3—Malus × domestica \nApple.“ In Biotechnology of Fruit and Nut Crops, edited by R. E. Litz, F. Pliego-Alfaro, and J. I. \nHormaza, 440–473. UK: CAB International. \nHemmat, M., N. F. Weeden, and S. K. Brown. 2003. “Mapping and Evaluation of Malus ×domestica \nMicrosatellites in Apple and Pear.“ jashs 128: 515–520. \nHiDRAS: High-quality Disease Resistant Apples for a Sustainable Agriculture (2025). Available at: \nhttps://sites.unimi.it/camelot/hidras/index.php. [Accessed 14 March 2025]. \nHokanson, S. C., A. K. Szewc-McFadden, W. F. Lamboy, and J. R. McFerson. 1998. “Microsatellite (SSR) \nmarkers reveal genetic identities, genetic diversity and relationships in a Malus×domestica borkh. \ncore subset collection.“ Theoretical and Applied Genetics 97: 671–683. \nJames, C. M., and K. M. Evans. 2004. “ Identification of molecular markers linked to the mildew \nresistance genes Pl-d and Pl-w in apple.“ Acta Horticulturae 663: 123–128. \nJeger, M. J., D. J. Butt, and A. A. J. Swait. 1986. “Components of resistance of apple to powdery \nmildew (Podosphaera leucotricha).“ Plant Pathology 35: 477–490. \nKellerhals, M., I. O. Baumgartner, L. Leumann, J. E. Frey, and A. Patocchi. 2013. “Progress in \nPyramiding Disease Resistances in Apple Breeding.“ Acta Horticulturae 976: 487–491. \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nKnight, R. L. and F. H. Alston. 1968. “Sources of field immunity to mildew (Podosphaera leucotricha) \nin apple.“ Canadian Journal of Genetics and Cytology 10: 294–298. \nKoressaar, T., and M. Remm. 2007. “Enhancements and modifications of primer design program \nPrimer3.“ Bioinformatics 23: 1289–1291. \nKrieghoff, O. 1995. “Entwicklung einer In-vitro-Selektionsmethode auf Resistenz von Malus-\nGenotypen gegenüber Podosphaera leucotricha (Ell. et Ev.) Salm. und In-vitro-Differenzierung von \nVirulenzunterschieden des Erregers.“ Doctoral Dissertation, Humboldt-Universität zu Berlin, \nGermany. \nKusch, S., J. Qian, A. Loos, F. Kümmel, P. D. Spanu, and R. Panstruga. 2024. “Long-term and rapid \nevolution in powdery mildew fungi.“ Molecular Ecology 33: e16909. \nLateur, M., E. Dapen, et al. 2022. “ECPGR Characterization and Evaluation Descriptors for Apple \nGenetic Resources.“ European Cooperative Programme for Plant Genetic Resources, Rome, Italy. \nLesemann, S., A. Urbanietz, and F. Dunemann. 2004. “ Determining population variation of apple \npowdery mildew at the molecular level.“ Acta Horticulturae 663: 199–204. \nLesemann, S. S., S. Schimpke, F. Dunemann, and H. B. Deising. 2006. “Mitochondrial heteroplasmy for \nthe cytochrome b gene Controls the level of strobilurin resistance in the apple powdery mildew \nfungus Podosphaera leucotricha (Ell. & Ev.) E.S. Salmon.“ Journal of Plant Diseases and Protection \n113: 259–266. \nLi, T., J. Qu, et al. 2018. “Genetic characterization of inbred lines from Shaan A and B groups for \nidentifying loci associated with maize grain yield.“ BMC Genetics 19: 63. \nLiebhard, R., L. Gianfranceschi, et al. 2002. “Development and characterisation of 140 new \nmicrosatellites in apple (Malus x domestica Borkh.).“ Molecular Breeding 10: 217–241. \nLuo, F., P. Sandefur, K. Evans, and C. Peace. 2019. “A DNA test for routinely predicting mildew \nresistance in descendants of crabapple ‘White Angel’.“ Molecular Breeding 39: 33. \nMarkussen, T., J. Krüger, H. Schmidt, and F. Dunemann. 1995. “Identification of PCR‐based markers \nlinked to the powdery‐mildew‐resistance gene Pl1 from Malus robusta in cultivated apple.“ Plant \nBreeding 114: 530–534. \nMinnis, A. M., A. Y. Rossman, D. L. Clement, M. K. Malinoski, and K. K. Rane. 2010. “First Report of \nPowdery Mildew Caused by Podosphaera leucotricha on Callery Pear in North America.“ Plant \nDisease 94: 279. \nMundt, C. C. 2018. “Pyramiding for Resistance Durability: Theory and Practice.“ Phytopathology 108: \n792–802. \nMwanza, E. J. M., S. K. Waithaka, and S. A. Simons. 2001. “First Report of Powdery Mildew Caused by \nPodosphaera leucotricha on Prunus africana in Kenya.“ Plant Disease 85: 1285. \nNorelli, J. L., M. Wisniewski, et al. 2017. “Genotyping-by-sequencing markers facilitate the \nidentification of quantitative trait loci controlling resistance to Penicillium expansum in Malus \nsieversii.“ PlOS One 12: e0172949. \nOtt, A., S. Liu, et al. 2017. “tGBS® genotyping-by-sequencing enables reliable genotyping of \nheterozygous loci.“ Nucleic Acids Research 45: e178. \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nParlevliet, J. E. 2002. “Durability of resistance against fungal, bacterial and viral pathogens; present \nsituation.“ Euphytica 124: 147–156. \nPeil, A., T. Garcia‐Libreros, et al. 2007. “Strong evidence for a fire blight resistance gene of Malus \nrobusta located on linkage group 3.“ Plant Breeding 126: 470–475. \nPessina, S., D. Angeli, et al. 2016. “The knock-down of the expression of MdMLO19 reduces \nsusceptibility to powdery mildew (Podosphaera leucotricha) in apple (Malus domestica).“ Plant \nBiotechnology Journal 14: 2033–2044. \nPessina, S., L. Palmieri, et al. 2017. “Frequency of a natural truncated allele of MdMLO19 in the \ngermplasm of Malus domestica.“ Molecular Breeding 37: 7. \nPfeifer, M., O. F. Emeriewen, et al. 2025. “High-quality haplotype-resolved genome assembly and \nannotation of Malus baccata ‘Jackii’.“ Preprint available at: \nhttps://www.biorxiv.org/content/10.1101/2025.07.27.667097v1. [Accessed 1 August 2025]. \nSchuster, M. 2000. “ Genetics of powdery mildew resistance in Malus species.“ Acta Horticolturae \n538: 593–595. \nSeglias, N. P., and C. Gessler. 1997. “Genetics of apple powdery mildew resistance from Malus zumi \n(Pl2).“ IOBC-WPRS Bulletins 20: 195–208. \nSilfverberg-Dilworth, E., C. L. Matasci, et al. 2006. “Microsatellite markers spanning the apple (Malus \nx domestica Borkh.) genome.“ Tree Genetics & Genomes 2: 202–224. \nStankiewicz‐Kosyl, M., E. Pitera, and S. W. Gawronski. 2005. “Mapping QTL involved in powdery \nmildew resistance of the apple clone U 211.“ Plant Breeding 124: 63–66. \nStrickland, D. A., K. T. Hodge, and K. D. Cox. 2021. “An Examination of Apple Powdery Mildew and the \nBiology of Podosphaera leucotricha from Past to Present.“ Plant Health Progress 22: 421–432. \nStrickland, D. A., J. P. Spychalla, E. van Zoeren, M. R. Basedow, D. J. Donahue, and K. D. Cox. 2023. \n“Assessment of Fungicide Resistance via Molecular Assay in Populations of Podosphaera leucotricha, \nCausal Agent of Apple Powdery Mildew, in New York.“ Plant Disease 107: 2606–2612. \nTakamatsu, S. 2013. “Molecular phylogeny reveals phenotypic evolution of powdery mildews \n(Erysiphales, Ascomycota).“ Journal of General Plant Pathology 79: 218–226. \nUntergasser, A., I. Cutcutache, et al. 2012. “Primer3—new capabilities and interfaces.“ Nucleic Acids \nResearch 40: e115. \nUrbanietz, A., and F. Dunemann. 2005. “Isolation, identification and molecular characterization of \nphysiological races of apple powdery mildew (Podosphaera leucotricha).“ Plant Pathology 54: 125–\n133. \nVan Ooijen, J. W. 2004. “MapQTL 5, Software for the mapping of quantitative trait loci in \nexperimental populations.“ Kyazma B. V., Wageningen, Netherlands. \nVan Ooijen, J. W. 2018. “JoinMap5, Software for the calculation of genetic linkage maps in \nexperimental populations of diploid species.“ Kyazma B.V., Wageningen, Netherlands. \nVielba-Fernández, A., Á. Polonio, L. Ruiz-Jiménez, A. de Vicente, A. Pérez-García, and D. Fernández-\nOrtuño. 2020. “Fungicide Resistance in Powdery Mildew Fungi.“ Microorganisms 8: 1431. \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nVinatzer, B. A., A. Patocchi, S. Tartarini, L. Gianfranceschi, S. Sansavini, and C. Gessler. 2004. \n“Isolation of two microsatellite markers from BAC clones of the Vf scab resistance region and \nmolecular characterization of scab‐resistant accessions in Malus germplasm*.“ Plant Breeding 123: \n321–326. \nVisser, T., and J. J. Verhaegh. 1980. “Resistance to powdery mildew (Podosphaera leucotricha) of \napple seedlings growing under glasshouse and nursery conditions.“ Proceedings of the Eucarpia \nmeeting of tree fruit breeding, Angers, 1979, 111–120. \nVogt, I., T. Wöhner, et al. 2013. “Gene-for-gene relationship in the host-pathogen system Malus × \nrobusta 5-Erwinia amylovora.“ New Phytologist 197: 1262–1275. \nVoorrips, R. E. 2002. “MapChart: Software for the Graphical Presentation of Linkage Maps and QTLs.“ \nJournal of Heredity 93: 77–78. \nWöhner, T. W., K. Richter, et al. 2018. “Inoculation of Malus genotypes with a set of Erwinia \namylovora strains indicates a gene‐for‐gene relationship between the effector gene eop1 and both \nMalus floribunda 821 and Malus ‘Evereste’.“ Plant Pathology 67: 938–947. \nWöhner, T., O. F. Emeriewen, and M. Höfer. 2021. “Evidence of apple blotch resistance in wild apple \ngermplasm (Malus spp.) accessions.“ European Journal of Plant Pathology 159: 441–448. \nWu, T. D., and S. Nacu. 2010. “Fast and SNP-tolerant detection of complex variants and splicing in \nshort reads.“ Bioinformatics 26: 873–881. \nYamamoto, T., T. Kimura, et al. 2002a. “Simple sequence repeats for genetic analysis in pear.“ \nEuphytica 124: 129–137. \nYamamoto, T., T. Kimura, M. Shoda, Y. Ban, T. Hayashi, and N. Matsuta. 2002b. “Development of \nmicrosatellite markers in the Japanese pear (Pyrus pyrifolia Nakai).“ Molecular Ecology Notes 2: 14–\n16. \nYoder, K. S. 2000. “Effect of Powdery Mildew on Apple Yield and Economic Benefits of Its \nManagement in Virginia.“ Plant Disease 84: 1171-1176. \nZheng, Z., Z. Sun, et al. 2018. “Genetic Diversity, Population Structure, and Botanical Variety of 320 \nGlobal Peanut Accessions Revealed Through Tunable Genotyping-by-Sequencing.“ Scientific Reports \n8: 14500. \n \n \n \n \n \n \n \n \n \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \nSupplementary information \nTable S1 Number of markers and genetic length (cM) of the 17 linkage groups of Malus baccata 'Jackii' haplotype 1 \nLinkage group SNP marker SSR marker Length (cM) \n1 47 5 63.6 \n2 70 4 67.1 \n3 58 5 78.6 \n4 58 2 50.8 \n5 62 4 66.6 \n6 53 2 65.9 \n7 24 2 19.1 \n8 55 4 56.3 \n9 51 4 60.7 \n10 50 10 55.9 \n11 53 3 69.6 \n12 69 1 64.3 \n13 51 7 68.1 \n14 61 2 59.9 \n15 65 3 107.4 \n16 67 5 63.6 \n17 54 6 53.5 \nTotal 948 69 1071.0 \n \nTable S2 Summary of newly developed SSR markers linked to powdery mildew resistance \nMarker Linkage group Predicted genomic \nposition in \nhaplotype 1 / 2 \nExpected PCR \nproduct size in bp of \nhaplotype 1 / 2a \nObserved size in \nfragment length \nanalysis (bp)a \nLKSSRchr5_Mbj2 5 25,400,896-\n25,400,994 / \n25,183,631-\n25,183,741 \n99 / 111 99 / 111 \nLKSSRchr10_1478 10 17,120,061-\n17,120,242 / \n16,946,103- \n16,946,288 \n182 / 186 177 / 181 \nLKSSRchr10_1978 10 21,155,277-\n21,155,449 / \n21,035,950- \n21,036,126 \n175 / 179 176 / 180 \nLKSSRchr10_1998 10 21,391,017-\n21,391,236 / \n21,254,415- \n21,254,632 \n220 / 218 215 / 217 \nLKSSRchr10_2318B 10 24,678,521 -\n24,678,663/ \n24,412,181- \n24,412,327 \n143 / 147 143 / 147 \nLKSSRchr10_2718 10 28,170,148-\n28,170,275 / \n27,895,197- \n27,895,319 \n128 / 123 119 / 124 \na Resistance-associated alleles are shown in bold. \n \nTable S3 Annotated genes in the region of interest in haplotype 1 of linkage group 10 in Malus baccata 'Jackii' (see separate \nsupplementary file). \n \nTable S4 Identified resistance gene candidates for Plbj (see separate supplementary file). \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint \n\n \n \n \nTable S5 Previously published SSR markers selected from the HiDRAS website (HiDRAS 2025) \nReference Marker names \nCelton et al. 2009 NZmsCN943067, NZmsCO754252, NZmsEB137525, NZmsMDAJ1681 \nEmeriewen et al. 2014 FRM4 \nEmeriewen et al. 2017 FRMb251 \nHemmat et al. 2003 GD153, GD158 \nHokanson et al. 1998 GD96, GD142, GD147 \nLiebhard et al. 2002 CH01e01, CH01f03b, CH01f07a, CH01f09, CH01h02, CH01h10, CH02a03, CH02b03b, \nCH02b10, CH02c06, CH02d08, CH02d12, CH02f06, CH02g01, CH02g09, CH02h11a, \nCH03a08, CH03b10, CH03d07, CH03d11, CH03e03, CH03g07, CH03g12, CH04e03, \nCH04f10, CH04h02, CH05b06, CH05c07, CH05e06, Ch05f06, CH05g08 \nSilfverberg-Dilworth et al. 2006 AU223657-SSR, Hi01d05, Hi02c06, Hi02c07, Hi03a10, Hi03d06, Hi03e04, Hi03g06, \nHi04b12, Hi04d02, Hi04e04, Hi04f09, Hi04g05, Hi05b09, Hi07b02, Hi07h02, Hi08f12, \nMDAJ761-SSR \nVinatzer et al. 2004 CH-Vf1 \nYamamoto et al. 2002a KA4b \nYamamoto et al. 2002b NH033b \n \n \nTable S6 Newly developed SSR markers with primer sequences \nMarker name Forward primer sequence (5'-3') Reverse primer sequence (5'-3') \nLKSSRchr5_Mbj2 CTTCTCCCTTGCTTGCTTCC AGGGATCATGATACACTCGGT \nLKSSRchr10_1438 CGATTACAGAGACGGAGCGA TTTATTGGCTGGGACGTCAC \nLKSSRchr10_1478 ACCACTACACCACAACCCAA GGTTTCGGTGTTGGTTGTGA \nLKSSRchr10_1978 TTGGGTGAGGAGAGGGGTAT ATCAGGTTTCGTCAGAGCCA \nLKSSRchr10_1998 ATTGGTTTGGGATGTCACGC ACAAGAGATTGATCACTGGAGAA \nLKSSRchr10_2318B TCTCTCCCTTCCAATCCCAA AGCCTCACTACTATTTAGCCAAT \nLKSSRchr10_2718 TGGAATGTTGTCTAATTAGGGCA GTAACTATTGCTTTCCGGCCC \n \nTable S7 Overview of developed KASP markers \nMarker name FAM \nallele \nHEX \nallele \nAllele-specific \nforward primer 1 \n(5'-3') \nAllele-specific forward \nprimer 2 (5'-3') \nCommone reverse primer \nsequence (5'-3') \nKASP_HT1_LG10_\n20042456  \nC T GTGTAATGGGCTTG\nATCAACCAG \nTCGTGTAATGGGCTTGAT\nCAACCAA \nCATAGTGATTAAATGATCTG\nAAGGGCCAA \nKASP_HT1_LG10_\n23962775 \nC G CAAAAATACCTTCA\nGAACAAGTTCTAGG \nCAAAAATACCTTCAGAAC\nAAGTTCTAGC \nTTGACTTTKGGCATGACACT\nTTACTAGAAT \n \nFigure S1 Genetic linkage maps of haplotype 1 of Malus baccata 'Jackii'. SSRs developed in this project are shown in bold, \nSSRs selected from the HiDRAS website (HiDRAS 2025) in italics, and Plbj is indicated with a bold red italic label (see \nseparate supplementary file). \n \n \n \n.CC-BY 4.0 International licensemade available under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is \nThe copyright holder for this preprintthis version posted August 29, 2025. ; https://doi.org/10.1101/2025.08.26.672377doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}