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a Dep. of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, 1991 Upper Buford Circle, St. Paul, MN 55108
b Dep. of Plant Pathology, University of Minnesota, 495 Borlaug Hall, 1991 Upper Buford Circle, St. Paul, MN 55108
c Genome Dynamics, Scottish Crop Research Institute, Invergowie, Dundee DD2 5DA, Scotland
* Corresponding author (muehl003{at}tc.umn.edu)
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Abbreviations: cM, centimorgan • DON, deoxynivalenol • FHB, Fusarium head blight • QTL, quantitative trait locus • RFLP, restriction fragment length polymorphism, SSR, simple sequence repeat
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Resistant cultivars are the most cost effective measure for controlling the disease but breeding for FHB resistance has been difficult for two reasons. First, genetic resistance is complex. There seem to be many QTL that have relatively small effects and are subject to genotype x environment interactions. Most QTL are also associated with morphological and agronomic traits, which confound measurement of disease resistance. Second, assessing FHB severity in the field and greenhouse is difficult. Both of these problems necessitate identification of molecular markers linked to QTL for FHB resistance that can be used in marker-assisted breeding. However, because of the complex nature of genetic resistance to FHB, QTL identification is not always very robust. Therefore, validation of these QTL is important before implementing marker-assisted selection in a breeding program.
QTL providing resistance to FHB and DON accumulation in barley have been identified on all seven chromosomes. QTL for FHB resistance were identified on chromosomes 1(7H), 2(2H), 3(3H), 4(4H), 5(1H), and 7(5H) in the Chevron (resistant)/M69 (susceptible) population (de la Peña et al., 1999). A major QTL on chromosome 2(2H) explains 13.5% of the phenotypic variation for FHB resistance. However, this QTL is also associated with heading date and the resistant allele is linked to late heading. Ma et al. (2000) used a population derived from the cross Chevron/Stander and reported nine QTL for FHB resistance located on chromosomes 1(7H), 2(2H), 3(3H), 6(6H), and 7(5H). A QTL on chromosome 2(2H) was consistently detected in five environments and explained 11.8 to 20.7% of the phenotypic variation for FHB resistance. This QTL, in addition to the QTL on chromosome 2(2H) discovered by de la Peña et al. (1999), is also associated with days to heading. Using a population derived from the two-rowed parents, Gobernadora and CMB643, Zhu et al. (1999) found QTL for FHB resistance on all barley chromosomes except chromosome 7 (5H). The largest QTL explained 33% of the phenotypic variation and was found on chromosome 2(2H). The QTL on chromosome 4(4H) explains 4 to 12% of the phenotypic variation for FHB resistance. This QTL was also significantly associated with morphological traits including plant height, seeds per inflorescence, inflorescence density, and lateral floret size. In each of the previous mapping studies, QTL for accumulation of DON in harvested grain were also detected. These QTL were also distributed throughout the genome and were, in some cases, coincident with FHB QTL. Taken together, these studies indicate resistance is conditioned by many loci and that there is a strong association between certain morphological traits and FHB resistance.
Two major traits associated with FHB severity are spike type and heading date. The Vrs1 and Int-c loci control lateral floret fertility and hence determine whether a spike is two-rowed (Vrs1; int-c/int-c) (Lundqvist and Franckowiak, 1997) or six-rowed (vrs1/vrs1; Int-c/Int-c) (Hockett and Nilan, 1985). In several studies, two-rowed spike type has been associated with FHB resistance (Takeda and Heta, 1989; Chen et al., 1991; Zhou et al., 1991; Steffenson et al., 1996). In a genetic study, Takeda (1990) demonstrated an association between the Vrs1 locus and FHB resistance. In two-rowed barley (Vrs1) with the Int-c/Int-c genotype, the laterals can be inflated and lateral floret size has been associated with FHB severity (Zhu et al., 1999). The FHB mapping studies published to date have used populations derived from either six-rowed x six-rowed or two-rowed x two-rowed crosses (de la Peña et al., 1999; Zhu et al., 1999; Ma et al., 2000). Therefore, the Vrs1 locus was not segregating in these populations. Heading date may also strongly influence the severity of FHB on barley, and QTL for heading date and FHB resistance are coincident (de la Peña et al., 1999; Ma et al., 2000). Generally, late heading plants tend to have lower severity while early heading plants have higher severity, indicating that the late heading plants are exposed to the inoculum for a shorter period of time (Steffenson, 2002). However, the low resolution of the mapping populations has resulted in a limited assessment of the impact of heading date on FHB severity.
One method to account for differences in heading date is to apply inoculum to each progeny at heading in a controlled environment. Screening for FHB resistance in barley is conducted mainly in the field and to date no attempts to identify FHB resistance QTL in the greenhouse have been published. In contrast to barley, screening for FHB resistance in wheat (Triticum aestivum L.) is done primarily in the greenhouse (Procunier et al., 1998; Bai et al., 1999; Waldron et al., 1999; and Anderson et al., 2001). Screening barley for FHB resistance in the greenhouse could be extremely useful in breeding programs; however, it is first necessary to determine whether greenhouse screening selects for genes that provide resistance in the field.
The objectives of this study were to: (i) identify the location of QTL for resistance to FHB in a two-rowed x six-rowed population, (ii) examine the association of QTL for FHB resistance with late heading date and the Vrs1 locus, (iii) validate the genomic regions associated with the major QTL for FHB resistance primarily detected in the field in another population, and (iv) identify SSR markers linked to FHB resistance QTL.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Isolates and Inoculum Preparation
Fusarium graminearum isolates, collected from different geographical locations within the Red River Valley of Minnesota, were used for field screening in Minnesota. One isolate of F. graminearum (Butte86ADA-11) was used for the greenhouse screening. Macroconidia of these F. graminearum isolates were produced by culturing on mung bean agar (MBA) as described in Evans et al. (2000).
FHB Evaluation in the Field
In 1999 and 2000, the Fredrickson/Stander F4:6 population and parents were evaluated in four field environments in Minnesota (St. Paul 1999, St. Paul 2000, Crookston 2000, and Morris 2000). In 1998 and 1999, the Fredrickson/Stander//M81 population was tested in five environments (St. Paul 1998, St. Paul 1999, Crookston 1998, Crookston 1999, and Hangzhou (China) 1998). Both populations were evaluated by means of a randomized complete block design with three replications. Each plot consisted of a 1.6-m row spaced 0.30 m apart. Field inoculation was conducted by two methods: (i) colonized grain inoculum spread on the soil surface (grain spawn) and (ii) macroconidial suspensions sprayed on heads at a postanthesis stage (spray) according to the procedures as described by Dill-Macky (2002).
Grain Spawn Inoculation
At Crookston and Morris, inoculation was conducted by infecting autoclaved corn seed (Zea mays L.) with isolates of F. graminearum collected in Minnesota and spreading the seeds in the experimental plots 2 wk before flowering. At Hangzhou, inoculation was done by spreading maize and barley grain colonized by isolates of F. graminearum collected in China. Automated overhead mist irrigation was provided after spreading the inoculum to help promote formation of perithicia and ascospores and to provide an environment conducive for infection.
Spray Inoculation
At the St. Paul nurseries, plots were placed into four inoculation groups. Each group was inoculated on the basis of its heading date with a macroconidial suspension of F. graminearum with a CO2–pressured backpack sprayer. Each plot was sprayed either two (St. Paul 2000) or three (St. Paul 1999) times with 3-d intervals between spraying. Plots were inoculated when at least 90% of the heads were emerged from the boot. Mist irrigation was supplied after plots were inoculated.
In all the locations except St. Paul 2000, severity of FHB infection was scored by visual estimation of 10 arbitrarily selected spikes from each plot. At St. Paul 2000, FHB severity was determined by counting the number of total and infected kernels in each of the 10 arbitrarily selected spikes. Severity scores were assessed 18 to 21 d after inoculation and the data reported as the percentage of infected kernels per spike.
FHB Evaluation in the Greenhouse
In winter 2000 and fall 2000, the Fredrickson/Stander F4:6 population was evaluated in the greenhouse by a completely randomized design with five replications in fall 2000 and six replications in winter 2000. Each replicate consisted of a single pot with two plants, and two heads were scored per replicate. The F4:6 lines and parents were grown in the greenhouse in clay pots (12.7-cm diam by 12.7-cm height) containing commercial rooting medium (Metromix 200, Scott-Sierra Hort. Prod. Co., Marysville, OH) at a temperature of 20 to 25°C. Plants were watered as needed and seedlings were fertilized at the three-leaf stage with 3 g of slow-release 14-14-14 (N-P-K) fertilizer/pot.
When two heads per pot were fully emerged, they were spray inoculated with macroconidia of F. graminearum with a CO2–pressured air brush. Between 500 to 800 µL (1.0 x 10-5 macroconidia mL-1) was dispensed while spraying the head. Inoculated plants were placed in a dew chamber near 100% relative humidity with continuous lighting [two 40-W fluorescent lights (6 µmol m-2 s-1)] for 3 d and then moved to the greenhouse. Two weeks after inoculation, spikes were scored for FHB severity by counting the number of total and infected kernels in each spike.
Determination of DON Concentration
For each nursery in which we collected grain, 25 g of cleaned grain from each line and parent was used for DON analysis. DON concentration was determined by gas chromatography and expressed as parts per million (ng/µg) according to the procedures of Mirocha et al. (1998).
Agronomic Traits
Days to heading was recorded as the number of days from seeding to the date when approximately 50% of the heads were completely emerged from the boot. Spike morphology was recorded for the individual F4 plants and confirmed in replicated rows for the F4:6 lines as either six-row, two-row, or segregating in the row. Fredrickson has the Vrs1/Vrs1; int-c/int-c genotype (two-rowed, small lateral florets) and Stander has the vrs1/vrs1; Int-c/Int-c genotype (six-rowed, inflated lateral florets). Int-c was scored as either inflated lateral florets or small lateral florets on two-rowed plants.
DNA Marker Analysis
Leaf tissue from a bulk of at least eight F4:5 plants of each line and the parents was collected for DNA marker analysis. DNA isolation and DNA gel blot analysis were performed according to the procedures of Mesfin et al. (1999). A total of 151 low copy DNA probes from wheat genomic, barley cDNA, barley genomic DNA, and oat cDNA clones were used to identify polymorphism between the parents (Heun et al., 1991; Gill et al., 1991; Graner et al., 1991; and Kleinhofs et al., 1993). Probes were screened by hybridizing membranes containing parental DNA digested with six restriction enzymes (BamHI, DraI, EcoRI, EcoRV, HindIII, and XbaI). Probes revealing polymorphism between the parents were subsequently used on filters containing DNA from each of the 130 lines.
In addition to RFLP probes, 177 microsatellites (SSR) markers (Ramsay et al., 2000; and Liu et al., 1996) were screened to identify polymorphism between the parents. PCR amplification was done according to the procedures of Ramsay et al. (2000). Electrophoresis was conducted on 5% (w/v) polyacrylamide gels and amplified products were visualized by silver staining as described by Bassam et al. (1991). Markers that were polymorphic between the parents were screened on the entire population.
Statistical Analysis
Analyses of variance for FHB severity, heading date, and DON accumulation were conducted for each environment by means of GLM procedures of SAS (SAS Institute, 1988). Error mean squares across all of the environments were not homogeneous as determined by Bartlett's chi-square test (Gomez and Gomez, 1984); thus, combined ANOVA across environments were not conducted. Normality of FHB severity distribution was tested by Proc Univariate procedures of SAS. Correlation analysis was done using SAS, and the line mean of each trait was used for correlation analysis. Heritability estimates were determined on an entry mean basis by the formula h2 = 
g2/(g2 + e2/r), where g and e are genotypic and error variances, respectively, calculated from the means squares from the analysis of variance and r is the number of replications.
Linkage maps were constructed by means of the computer program G-Mendel, version 3.0 (Holloway and Knapp, 1994). A minimum LOD score of 5.0 was used for pairwise linkage analysis. Three of the 130 lines in the mapping population were removed from the marker-trait analysis because of missing marker data due to poor image quality on gels. To identify significant associations between DNA markers and traits, regression analyses were performed by SAS. To identify QTL, we conducted composite interval mapping (CIM) analyses using the software package PLABQTL (Utz and Melchinger, 1996) with the following options: additive genetic model, cov select, F-to-enter = 3.5, RAIC = 3, and scanning interval of 2 centimorgans (cM). PLABQTL uses a stepwise regression procedure to select cofactors and between 9 and 12 cofactors were selected for each of our analyses. The location of a QTL is defined as the position where the LOD score reaches its maximum over the region being studied. We identify the QTL by markers that flank the peak of the QTL LOD score. In some cases, we selected markers that flank several closely linked peaks and therefore may not be the exact flanking markers for a specific peak. We report QTL detected with a LOD score >3.42, corresponding to P < 0.05 and P < 0.0004 experiment-wise and comparison-wise error rate, respectively. For each QTL, the average effect of an allele from Fredrickson (
) was calculated as the regression coefficient for the corresponding QTL genotype in a multi-locus regression model, assuming no dominance.
The two major QTL primarily detected in the field in the mapping population (Fredrickson/Stander) were validated in the breeding population (Fredrickson/Stander//M81). Since the breeding population was not structured to permit linkage map construction, we analyzed QTL regions using marker x marker regression. We selected a single marker within each of the QTL regions to be tested and used Proc GLM (SAS Institute, 1988) to determine significant (P < 0.05) effects of genotypic classes on the traits FHB, DON and HD. We evaluated each environment separately and report the R2 values for all significant associations.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Genetic Linkage Map
Three hundred twenty-eight DNA markers (151 RFLP probes and 177 SSR markers) were screened for polymorphism between the parents. A total of 143 markers were mapped (85 RFLP, 57 SSR, and 1 morphological), yielding 10 linkage groups (Fig. 1). These linkage groups provide a total genetic distance of 1170 cM, which is similar to the Steptoe/Morex map (1245 cM) (Kleinhofs et al., 1993). The markers placed in this map are consistent with respect to order on the chromosomes with the Chevron/M69 RFLP map (de la Peña et al., 1999), and with other published or consensus barley maps (Kleinhofs et al., 1993; Qi et al., 1996; Ramsay et al., 2000; Costa et al., 2001) with a few minor differences. To determine the genome coverage of the map, we aligned it against the barley BIN map (http://barleygenomics.wsu.edu/; verified August 13, 2002). The genetic linkage map constructed for the Fredrickson/Stander population provides good genome coverage except for chromosome 5(1H) where there is a gap in the telomeric region containing BIN 1-5. There is also a gap on chromosome 4(4H) in the area spanning BIN 3-5. The poor coverage in these regions is due to a lack of polymorphism for the RFLP and SSR markers screened in these regions.
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Two of the major FHB resistance QTL were coincident with QTL for low DON accumulation (Fig. 2, Table 6). The QTL in the Vrs1-Bmag0125 interval was detected in two of the three environments (St. Paul 1999 and Morris 2000) where DON accumulation was determined. The DON QTL flanked by ABC252 and ABC153 was detected in the St. Paul 1999 environment. At the St. Paul 2000 environment, there was a significant (P < 0.01) and positive association of DON accumulation with FHB resistance; however, no QTL for low DON accumulation was detected.
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) located on chromosome 2(2H) were negative for FHB resistance and ranged from -4.1 to –13.4%, indicating that the Fredrickson alleles reduced FHB severity (Table 4). At St. Paul 2000, the value for FHB resistance was positive, and this is most likely due to differences in the environment after inoculation as discussed earlier. As expected, the Fredrickson allele resulted in later heading plants in each of the environments by at least 2.3 d (Table 5). The values for DON accumulation at St. Paul 1999 and Morris 2000 were negative and ranged from -1.8 to -6.1 (Table 6). In addition to the major QTL for FHB resistance identified on chromosome 2(2H), additional minor QTL were also detected explaining between five and 12.2% of the variation per locus (Table 4). All of the minor QTL for FHB were detected in only a single environment. Three of the minor QTL for FHB resistance (HVM54-Ebmac0415, Bmag0606-Bmag0013, HVM20-Bmac0090) were also coincident with HD (Table 5). The latter of the three was similar to the major QTL for FHB in that the late HD allele was associated with the FHB resistant allele. However, the alleles at the former two loci had the opposite effect. In several cases minor QTL for FHB resistance were linked and had opposite allelic effects (MWG503-MWG882b, MWG882b-ABG072, and HVM54-Ebmac0415 on chromosome 2(2H), and MWG887b-MWG2227a and Bmag0173-Bmac0018 on chromosome 6(6H)).
QTL Validation
To verify the two major FHB-resistance QTL detected primarily in the field with the mapping population (Fredrickson/Stander), we used a breeding population derived from the three parents Fredrickson, Stander, and M81 (Fredrickson/Stander//M81). Because Stander and M81 are highly related, the breeding population is essentially a backcross population. Therefore, the lines in this population are more similar to elite germplasm in the breeding program and are more uniform for important agronomic traits like heading date (Tables 1 and 2). Because of the complexity of the population structure, we did not construct a linkage map or conduct interval mapping. The breeding population was scored only on field grown plants for FHB severity, DON accumulation, and heading date, and therefore only the major QTL primarily detected in the field were validated. We selected a single marker (HVBKasi and Vrs1) from each of the two major FHB QTL regions (Ebmac0521a-Bmag0140 and Vrs1-Bmag0125) detected in the field environments and conducted marker x marker regression for the breeding population (Table 7). Both HVBKasi and Vrs1 loci were significantly associated with FHB resistance and heading date in four of the five environments in the breeding population. In addition, the HVBKasi locus was significantly associated with low DON accumulation in the St. Paul 1998 environment. However, the Vrs1 locus was not significantly associated with low DON accumulation in the breeding population.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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We used three different methods to measure disease resistance, each of which attempts to reduce the confounding effect of heading date on disease severity. With the grain spawn method, inoculum was present throughout the season, but disease assessment was done relative to heading date. This method primarily identified the QTL near the Vrs1 locus conferring two-rowed/six-rowed spike type. At St. Paul, we used the spray inoculation method, which provided consistent amounts of inoculum at specific times when plants were heading. This method identified the FHB resistance QTL associated with the heading date QTL. While our results indicate that these two field inoculation methods differentially detect FHB resistance QTLs on chromosome 2, it is also possible that the environment is influencing QTL detection since the spray inoculation method was used at St. Paul and the grain spawn inoculation method was used at Crookston and Morris. The third method, greenhouse screening, offered the most control of heading date and the environment after inoculation and reduced even further the likelihood that plants would appear resistant by escaping infection. This method identified not only the FHB resistance QTL associated with heading date and Vrs1 regions, but also a third QTL in the ABC252-ABC153 region. DON accumulation at the St. Paul 1999 environment was also associated with this region. The fact that all three of the QTL were detected in the greenhouse indicates that the greenhouse environment will be useful for selecting genotypes with resistant alleles at all three QTL in breeding programs.
Heading Date and FHB Resistance
In barley, late heading is usually associated with low FHB severity (Steffenson et al., 1996). In their findings, the level of FHB severity in early heading near-isogenic lines was nearly six times greater than the late heading near-isogenic lines. Recent mapping studies also indicated that there are coincidental QTL for FHB severity and heading date (de la Peña et al., 1999; Ma et al., 2000). Our results also indicate that markers were significantly associated with both FHB resistance and late heading (Fig. 2, Table 4, Table 5). One way to minimize the confounding effect of heading date is to inoculate lines on the basis of their days to heading. We used this approach at St. Paul 1999 and St. Paul 2000 and still found QTL for FHB resistance associated with heading date at these environments. In addition, in the fall greenhouse 2000 environment we also detected a FHB resistance QTL at the heading date locus. This result may be due to tight linkage between major genes controlling heading date (eg., Eam6) and FHB resistance or pleiotropic effects of these genes. At St. Paul and in the greenhouse, since inoculation was done on the basis of heading date, the possibility of escape is expected to be minimal. However, it was not possible to determine whether the coincidental association of these traits was due to linkage or pleiotropy.
The Vrs1 Locus and FHB Resistance
The Vrs1 locus in barley is the primary determinant of spike type (two-rowed versus six-rowed), and in general two-rowed cultivars are more resistant to FHB than six-rowed cultivars (Steffenson et al., 1996). Two-rowed genotypes have been employed as the major sources of resistance for FHB (Rudd et al., 2001). The lower disease levels often observed in the two-rowed genotypes may be related to the less favorable condition of the spike for the development of the disease (more aeration and ventilation). Because our population was segregating for two-rowed and six-rowed individuals, it offered us a unique opportunity to examine the association of this trait with FHB resistance. We found the Vrs1 locus is associated with a QTL for FHB resistance (Fig. 2, Table 4). However, because of the lack of precision inherent in QTL studies of this kind, we cannot yet determine if the QTL for FHB resistance in this region is tightly linked to the Vrs1 locus or a pleiotropic effect of the Vrs1 locus. Interestingly, the Vrs1 locus has been associated with a number of agronomic and yield related traits in barley (Jui et al., 1997; Kjaer and Jensen, 1997; Marquez-Cedillo et al., 2001). To resolve this question of pleiotropy versus tight linkage, we have initiated development of near-isogenic lines for this region, and the other two regions of chromosome two, which we intend to use for fine mapping.
Validation of FHB Resistant QTL
Validation of FHB resistance QTL is important for verifying the magnitude of the QTL and the genomic location. In general, QTL are subject to experimental error from three sources: (i) the individual lines sampled from the population; (ii) the sampling of the environments; and (iii) the ability to obtain accurate phenotypic data. With a trait such as FHB resistance, which is subject to large genotype x environment variation and is difficult to obtain accurate phenotypic data, it is necessary to validate QTL before they are used in a breeding program. In barley, several approaches have been used to validate QTL (cf. Spaner et al., 1999). QTL conferring FHB resistance have been validated by means of independent populations with a common parent. Several FHB resistance QTL from the partially resistant cultivar Chevron were found in similar genomic regions in the Chevron/M69 and Chevron/Stander populations (de la Peña et al., 1999; Ma et al., 2000).
In this paper, we used a breeding population (Fredrickson/Stander//M81) to validate the major QTL we detected in the Fredrickson/Stander mapping population. Both the mapping and breeding population were developed with the same resistance source (Fredrickson), enabling verification of the QTL identified in the mapping population. We examined the two major QTL (near HVBKasi and the Vrs1 locus) that were detected in the field in the mapping population. Our results showed that these two QTL for FHB resistance detected in the mapping population were also identified in the breeding population.
SSR Markers Linked to FHB Resistance QTL
One of the ultimate goals of identifying markers that are tightly linked with the gene(s) of interest is to utilize these markers in a breeding program. In the Fredrickson/Stander population, we identified SSR markers that are linked with each FHB resistance QTL. The integration of SSR markers into the RFLP map is also useful to the barley breeding community because these markers can easily be utilized for other genetic studies and in breeding programs for marker-assisted selection. Recently, Costa et al. (2001) also reported the integration of SSR and RFLP markers in the Oregon Wolfe barley population. The identification of SSR markers in our population provides the possibility for the use of these markers in the breeding program for screening of FHB resistant lines in early generations and the potential use of these markers to facilitate the rapid transfer of FHB resistance alleles into adapted germplasm.
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ACKNOWLEDGMENTS |
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Received for publication March 12, 2002.
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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