Reaction of wheat lines to BLS
Greenhouse evaluations of the 101 wheat lines for BLS resistance showed that Boost was the most resistant line with an IT score of 1.15 (Fig. 2, Table S1). Nine lines (8%) were moderately resistant with scores between 1.50 and 2.50, and the remaining lines were moderately to highly susceptible with IT scores greater than 2.5. For LAI, five lines showed less than 10% BLS and were considered highly resistant. Another six lines showed between 10 and 20% BLS and were considered moderately resistant. All remaining lines showed more than 20% BLS and were considered moderately to highly susceptible.
The five most resistant lines overall were Boost, W-7984, SW86, SW87, and Mace. As mentioned in the materials and methods, Boost is a HRSW variety and W-7984 is a synthetic hexaploid wheat line. SW86 and SW87 are both synthetic hexaploid wheat lines as well, and they were derived by crossing the durum lines 8155-B1 and 8155-B2 with Ae. tauschii accession CIae 26 (Szabó-Hevér et al. 2018). Mace is an Australian-bred HRSW (Table S1). Because Boost and W-7984 were resistant to Xtu (Figs. 3 and 4) and RIL populations derived from both lines were available, we pursued the evaluation of the BoostND and ITMI populations to identify QTLs associated with BLS resistance derived from these two highly resistant lines.
Evaluation of the BoostND population for BLS
In the greenhouse experiments, significant differences (P < 0.05) were observed among the average disease scores (IT and LAI) for the RILs of the BoostND population in each of the experiments (Fig. 5, Table S3). In these two experiments, Boost was highly resistant with average IT scores of 1.33 and 1.50 and percentage of LAI scores of 2.33 and 5.80%, whereas ND830 was susceptible with average IT scores of 3.50 and 3.75 and LAI scores of 45.00 of 55.83% in the Fall 2022 and Spring 2023 greenhouse experiments, respectively. The average IT scores of the BoostND RILs ranged from 1.33 to 4.08 and 1.31 to 4.09 in Fall 2022 and Spring 2023, respectively, and the average percentage of LAI scores for the RILs ranged from 1.83 to 57.70% and 2.47 to 68.16% for Fall 2022 and Spring 2023, respectively (Table S3).
In the field experiments at Fargo and Prosper, Boost showed strong resistance with an average DS score of 3.00 (ranging from 2 to 5), whereas ND830 was susceptible with average DS scores ranging from 6.00 to 8.00 in the two locations (Fig. 5). Significant differences (P < 0.5) were observed among the RILs of the BoostND population with average DS scores ranging from 2.33 to 8.00 and 2.33 to 9.00 for the field experiments in Fargo and Prosper, respectively (Table S3).
Evaluation of the ITMI population for BLS
In the greenhouse experiment, significant differences (P < 0.5) were observed among the ITMI RILs for both IT and LAI (Fig. 6). The average scores for W-7984 were 1.42 and 7.83% for IT and LAI, respectively, whereas Opata 85 had IT and LAI scores of 3.92 and 52.50%, respectively (Fig. 6, Table S4). The average IT scores among the RILs of the ITMI population ranged from 0.58 to 4.67, and the average percentage of LAI was from 1.50–73.33% in the spring 2023 greenhouse experiment.
In the field experiment at Prosper, ND, W-7984 showed strong resistance with a DS score of 1.33, whereas Opata 85 had a DS score of 5.00. Significant differences (P < 0.5) were observed among the RILs of the ITMI population (Fig. 6, Table S4) where the average DS scores ranged from 1.00 to 6.50.
Correlation of BLS with days to heading
For the BoostND population, mean values for DTH collected in the greenhouse experiment and the field experiment at Prosper were assessed for correlation with their respective BLS scores. Whereas the BLS and DTH scores in the field experiment were collected from the same plants, the greenhouse data for DTH was collected in an experiment different from the ones used to evaluate BLS. The lines are highly inbred, so this should not affect the ability to analyze data from different experiments. The average DTH was 50 and 49 days for Boost and 41 and 44 days for ND830 in the greenhouse and field, respectively (Table S3). The average DTH among the BoostND population ranged from 38 to 58 and 43 to 53 in the greenhouse and field experiments, respectively.
A strong positive correlation was observed between DTH in the greenhouse and DTH in Prosper with coefficient of correlation (r) of 0.70 (Table S5). The BLS scores in the greenhouse experiments showed a positive correlation (r: 0.42 to 0.43) with the BLS scores in the field. A weak negative correlation (r: -0.15 to -0.25) was observed between the BLS scores and DTH in the greenhouse experiments, and a strong negative correlation (r = -0.76) between BLS scores and DTH in the field experiment was observed. Further analysis revealed a negative correlation (r: -0.19 to − 0.25) between the DTH in the field experiment and the BLS scores in the greenhouse.
In the ITMI population, DTH data were collected only from the field experiment at Prosper, ND. A strong negative correlation (r = -0.68) was observed between the BLS scores and DTH in that environment (Table S6).
Genotyping and linkage mapping
A total of 1,275 SNPs were polymorphic between Boost and ND830 (Table S7). After filtering, a total of 518 SNPs remained for use in linkage analysis (Table S8), which resulted in a total of 27 linkage groups corresponding to 20 of the 21 wheat chromosomes covering a total of 1,337 cM of genetic distance. Only chromosome 4D had no polymorphic markers. Chromosomes 2A, 5A, 7A, 1B, 4B, 1D, and 2D were represented by two unlinked linkage groups for each (Fig. S1).
A total of 21 KASP markers were developed from the SNPs previously mapped in the ITMI population. Of these, 12 showed clear polymorphism between W-7984 and Opata 85 and were subsequently used to genotype the ITMI population and placed on the genetic linkage map for chromosome 7D (Table S9). These KASP markers were given the designations fcp995-fcp1006.
QTL analysis in the BoostND population
QTLs associated with DTH were identified on chromosomes 3B, 4A, 5A, and 7B and designated as QHd.fcu-3B.2, QHd.fcu-4A, QHd.fcu-5A, and QHd.fcu-7B, respectively (Table S10, Fig. S2). QHd.fcu-3B.2 and QHd.fcu-7B were detected only in the greenhouse experiment where they explained 7.60 and 17.00% of phenotypic variation, respectively, whereas QHd.fcu-4A and QHd.fcu-5A were detected in both environments with the two QTLs explaining 8.30 and 7.00% of the variation in the greenhouse and 8.40 and 6.60% of the variation in the field experiment at Prosper, respectively. Earliness at QHd.fcu-3B.2, QHd.fcu-4A, and QHd.fcu-5A was contributed by ND830, whereas earliness at QHd.fcu-7B was contributed by Boost.
BLS analysis in the BoostND population evaluated in greenhouse experiments revealed four QTLs located on chromosomes 3B (2), 5A, and 5B designated as QBls.fcu-3B.1, QBls.fcu-3B.2, QBls.fcu-5A, and QBls.fcu-5B.1 (Table 1, Fig. 7). QBls.fcu-3B.2 was associated with BLS resistance in only one of the two greenhouse experiments where it explained 7.00 and 7.60% of the phenotypic variation for IT and LAI, respectively. The other three QTLs were significantly associated with BLS resistance in both greenhouse experiments and for both LAI and IT scores. The phenotypic variation explained by QBls.fcu-3B.1, QBls.fcu-5A, QBls.fcu-5B.1 for IT was 37.10 and 37.40, 12.70 and 22.60, and 13.30% and 14.50% for the Fall 2022 and Spring 2023 greenhouse seasons, respectively. For LAI, QBls.fcu-3B.1, QBls.fcu-5A, and QBls.fcu-5B.1 explained 34.50 and 34.70, 11.16 and 23.70, and 11.30 and 16.10% of the phenotypic variation for the Fall 2022 and Spring 2023 greenhouse environments, respectively. In all cases, the alleles conferring BLS resistance at these loci were contributed by Boost.
Table 1
QTLs associated with bacterial leaf streak resistance caused by Xanthomonas transulcens pv. undulosa strain P3 identified in the BoostND and ITMI populations.
QTL Name | Peak markers | Greenhouse experiments | Field experiments | Donor parent for beneficial allele |
IT_Fall 2022 | LAI_Fall 2022 | IT_Spring 2023 | LAI_Spring 2023 | DS_Fargo_2023 | DS_Prosper_2023 | |
LODa | (R2 × 100) b | LODa | (R2 × 100) b | LODa | (R2 × 100) b | LODa | (R2 × 100) b | LODa | (R2 × 100) b | LODa | (R2 × 100) b | |
QBls.fcu-3B.1 | IWB51224 IWB12193 | 19.11 | 37.10 | 17.44 | 34.50 | 19.32 | 37.40 | 17.55 | 34.70 | 5.80 | 13.10 | 5.60 | 12.70 | Boost |
QBls.fcu-3B.2 | IWB6915 | 3.01 | 7.00 | 3.24 | 7.60 | - | - | - | - | - | - | - | - | Boost |
QBls.fcu-4A | IWA54 | - | - | - | - | - | - | - | - | - | - | 4.05 | 9.40 | Boost |
QBls.fcu-5A | IWB47624 IWA2837 | 5.58 | 12.70 | 4.80 | 11.00 | 10.59 | 22.60 | 11.16 | 23.70 | 14.04 | 28.90 | 14.38 | 29.40 | Boost |
QBls.fcu-5B.1 | IWB1196 IWA6773 IWB7549 | 5.88 | 13.30 | 4.92 | 11.30 | 6.44 | 14.50 | 7.25 | 16.10 | - | - | - | - | Boost |
QBls.fcu-5B.2 | IWB35252 IWB73479 IWB7342 | - | - | - | - | - | - | - | - | 4.78 | 10.90 | 5.54 | 12.60 | ND830 |
QBls.fcu-7D | Xbarc121-7D IWB39179 IWB41457 | NA | NA | NA | NA | 13.94 | 43.10 | 15.36 | 46.20 | NA | NA | 5.08 | 18.60 | W-7984 |
a Logarithm of odds. |
b Proportion of phenotypic variation explained by QTLs, expressed in percentage. |
- Not significant. |
NA: Experiment were not conducted. |
IT: Infection type score (0–5) |
LAI: Leaf area infected (%) |
DS: Disease severity score (0–9) |
In the field experiments, a total of four QTLs located on chromosomes 3B, 4A, 5A, and 5B were associated with BLS resistance (Table 1, Fig. 7). QBls.fcu-3B.1 and QBls.fcu-5A, which were associated with BLS resistance in the greenhouse experiments, were also associated with BLS resistance in both field environments. QBls.fcu-5B.1, was not significant under field conditions, but a second locus on chromosome 5B specific to BLS in the field experiments was identified and designated QBls.fcu-5B.2. The phenotypic variation explained by QBls.fcu-3B.1, QBls.fcu-5A, and QBls.fcu-5B.2 was 13.10 and 12.70, 28.90 and 29.40, and 10.90 and 12.65% in Fargo and Prosper, respectively. The QTL on chromosome 4A, designated QBls.fcu-4A, was significantly associated with BLS resistance in the Prosper experiment where it explained 9.40% of the phenotypic variation, but it was not significant in the Fargo field experiment. Resistance alleles for QBls.fcu-3B.1, QBls.fcu-5A, and QBls.fcu-4A were contributed by Boost. However, the resistance allele at QBls.fcu-5B.2 was contributed by the susceptible parent, ND830.
Using the most significant SNP marker associated with each environmentally stable QTL, i.e. QTLs that were significant in both field environments and in both greenhouse seasons, we calculated the average BLS scores for different allelic combinations to further assess their relative effects in the field and greenhouse environments. This included the QTLs QBls.fcu-3B.1 and QBls.fcu-5A. In general, lines that had resistance alleles for both QTLs had lower disease scores compared to lines with resistance alleles for one or no QTLs, indicating their effects were largely additive. In the greenhouse experiments, RILs with resistance alleles at QBls.fcu-3B.1 and QBls.fcu-5A showed the strongest BLS resistance reactions and were nearly as resistant as Boost. Lines that had only one of the two resistance QTLs had higher levels of BLS susceptibility, and RILs with ND830 alleles at both QTLs showing similar levels of susceptibility as ND830 (Fig. 4S). Similar results were observed for the field environments at Fargo and Prosper (Fig. 8).
QTLs in the ITMI population
Data for DTH in the ITMI population was collected in the field experiment at Prosper and subjected to QTL analysis. QTLs identified on chromosomes 2D and 5D were associated with DTH and designated QHd.fcu-2D and QHd.fcu-5D. These two QTLs explained 13.50 and 23.30% of the phenotypic variation, respectively. (Table S10, Fig. S3). The early heading effects at QHd.fcu-2D and QHd.fcu-5D were contributed by Opata 85.
For BLS resistance in the ITMI population, a QTL on chromosome 7D designated as QBls.fcu-7D had LOD values of 13.94 and 15.36 and accounted for 43.10 and 46.20% of the phenotypic variation for IT and LAI scores, respectively, in the greenhouse experiment (Table 1, Fig. 9). Resistance effects for QBls.fcu-7D were contributed by the synthetic hexaploid parent, W-9874. The same QTL was identified in the Prosper field experiment where it explained 18% of phenotypic variation.
ITMI RILs that possessed the W-7984 allele at QBls.fcu-7D had lower average disease scores compared to the lines with the Opata 85 allele in both the greenhouse and field experiments. In the greenhouse, the average BLS scores among the lines having the 7D resistance allele was 2.09 for IT and 15.33% for LAI compared to 3.51 and 44.40% for IT and LAI, respectively, among RILs lacking the resistance allele. Similar results were observed in the field experiment, where the average BLS score of the lines having the W-7984 allele on 7D was 2.3, whereas lines with the Opata 85 allele had an average score of 3.71 (Fig. 10)
KASP Markers
In addition to the 12 KASP markers developed for chromosome 7D in the ITMI population, of which fcp1001 was the most closely associated with the peak of QBls.fcu-7D, four KASP markers closely associated with the peaks of QBls.fcu-3B.1, QBls.fcu-5A, QBls.fcu-5B.1, and QBls.fcu-5B.2 were developed for the BoostND QTLs. These four markers, designated fcp1007-fcp1010, were evaluated on the parents and the entire BoostND population to verify that they detected their respective original SNP loci and hence, their corresponding QTLs (Table S11, Fig. S5).