| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
a Dep. of Agronomy, Univ. of Nebraska, Lincoln, NE 68583-0915
b Dep. of Plant Pathology, Univ. of Nebraska, Lincoln, NE 68583-0915
c Dep. of Biometry, Univ. of Nebraska, Lincoln, NE 68583-0915
Corresponding author (ggraef1{at}unl.edu)
 |
ABSTRACT |
|---|
 TOPNOTES ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
Abbreviations: PCR, polymerase chain reaction • PDA, potato dextrose agar • QTL, quantitative trait locus • RAPD, random amplified polymorphic DNA • RFLP, restriction fragment length polymorphism • RIL, recombinant inbred line • SSR, simple sequence repeat
|
INTRODUCTION |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
Screening for resistance to S. sclerotiorum has been difficult because of the interaction of escape mechanisms and physiological resistance. The detached leaf assay measures the size of a lesion produced by placing a mycelial plug on the trifoliolate leaf and presumably measures physiological resistance and not escape mechanisms. This method, developed in our laboratory for use on soybean, is nondestructive, allows multiple assays per year, and has consistent environmental control. In a comparison of the field evaluation, detached leaf assay, and other nonfield screening techniques, the detached leaf assay showed a significant correlation with field results (Kim et al., 2000).
The advent of DNA markers has facilitated mapping of agriculturally important genes and QTLs in soybean, including genes and QTLs for disease resistance. Markers tightly linked to resistance genes would help to identify resistant soybean lines on the basis of the genotype as well as phenotype, maximizing the effectiveness of selection. Combining resistance genes in one cultivar also could be facilitated by using DNA markers. With QTL mapping, resistance loci whose alleles exert smaller effects on phenotype also may be manipulated more effectively (Young, 1996). One obvious goal would be to develop soybean lines that have resistance alleles at all QTLs of interest.
Recent development of an integrated linkage map of soybean (Cregan et al., 1999) based on simple sequence repeat (SSR) markers greatly facilitates QTL mapping. These SSRs, or microsatellites, provide more information than previous DNA-based genetic markers, such as restriction fragment length polymorphism (RFLP) and random amplified polymorphic DNA (RAPD) (Cregan et al., 1995; Morgante et al., 1994). The codominant, multiallele, single-locus SSR markers are distributed throughout the soybean genome and the frequency of occurrence is of one SSR every 10 kilobases, though some clustering of markers is observed (Cregan et al., 1999). Furthermore, the single banding patterns make genotyping an unambiguous and highly reproducible endeavor (Moore et al., 1991).
Previous attempts to map QTLs for Sclerotinia stem rot resistance in soybean with molecular markers have been partially successful. Huff et al. (1995), using RAPD markers, were unable to identify genomic regions involved in resistance to Sclerotinia stem rot in a population segregating for resistance to the disease. Delaney et al. (1997) detected one QTL on Linkage Group E in a Williams 82 x Corsoy 79 F2 population using RAPD markers. Kim and Diers (2000) reported three QTLs on Linkage Groups C2, K, and M associated with Sclerotinia stem rot resistance in a Williams x S19-90 F3-derived population. All these putative QTLs have yet to be confirmed, since the mapping was confined to single populations of F2 plants or F3-derived lines by RAPD markers or a small number of RFLP markers. For QTL mapping studies, it is important to have marker loci distributed throughout the genome, to have good phenotypic data, and to evaluate a large number (
500) of progeny (Beavis, 1998). The objective of this study was to identify putative QTLs associated with Sclerotinia stem rot resistance in soybean. The 500 RILs used in this study were comprised of 100 RILs from each of five soybean populations developed with a common susceptible parent. Identification of putative QTLs in the same chromosomal region for multiple populations lessens the probability of a Type I error, thus providing strong evidence that the putative QTL does indeed affect the disease resistance reaction.
|
MATERIALS AND METHODS |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
Five F1 seeds were obtained for each cross in the field during 1995. Hybridity was confirmed by flower color of the F1 plants in the greenhouse at Lincoln, NE, during 1995-1996, and F2 seeds were harvested in bulk from each cross.
Generation advance from the F2 to F5 generation was accomplished by single-seed descent. The F2 seeds were planted in May 1996 at the East Campus Nurseries of the University of Nebraska—Lincoln Agronomy Research Farm. The F3 and F4 generations were grown at the USDA Tropical Agriculture Research Station at Isabela, Puerto Rico. The F5 generation was planted at the East Campus Nurseries in May, 1997.
For ease of reference throughout this paper, the populations will be referred to by the name of the resistant parent (e.g., Corsoy 79 population = Williams 82 x Corsoy 79).
Tissue Sampling and DNA Extraction
Forty-five days after planting, 100 F5 plants from each of the five populations were randomly chosen and tagged with an identification number. Leaf tissue was collected from the tagged plants, including the six parents. The leaf tissue was taken to the laboratory on ice and stored at -80°C for two days before lyophilization. The lyophilized tissue was ground to a fine powder with a mortar, and stored in a freezer at -20°C.
DNA extraction was performed by the miniextraction CTAB method (based on Saghai-Maroof et al., 1984). Half of a 1.5 mL eppendorf tube was filled with ground tissue and 800 µL of CTAB buffer containing 1% (v/v) mercaptoethanol was added. Incubation at 62°C for 1 h was followed by two chloroform-octanol (24:1) extractions, precipitation with cold isopropanol, three alcohol rinses [76% (v/v) ethanol–0.2 M NaOAc, 76% (v/v) ethanol–10 mM NH4OAc and 70% (v/v) ethanol] and resuspension in 1x TE pH 8.0 buffer. This procedure yielded about 300 µg of DNA, enough for repetitive PCR analyses.
Genotypic Analysis
Five hundred seven SSR primer pairs were used in an initial screen designed to detect polymorphism between Williams 82 and the five less-susceptible soybean cultivars. The number of markers tested per linkage group ranged from 15 for Linkage Group B1 to 38 for Linkage Group D1a (Table 1).
|
The initial screen of the parental cultivars identified SSR primers that gave clear, polymorphic, and unambiguously different bands in the agarose gel. The percentage of polymorphic markers detected per population varied from 26.6 to 18.5%. Partial genome coverage was achieved in all populations, ranging from 16.0% in the DSR 173 population to 28.4% in the Dassel population (Table 1). To calculate the genome coverage, the distances in centimorgans (cM) among linked markers were summed. For unlinked markers, the average distance in centimorgans among the linked markers was added twice to account for both sides of an unlinked marker (Knetkovsky et al., 1996). The total genome size was assumed to be 3000 cM (Cregan et al., 1999). In each population, those polymorphic SSRs that were spaced about 30 cM apart in the Integrated Soybean Linkage Map (Cregan et al., 1999) were chosen for use in the final screen involving the 100 F5 individuals of each population (Table 1). This screen generated the SSR segregation data for subsequent mapping and QTL detection. The DNA extraction and PCR amplification were performed under the same conditions as described for parental polymorphism analysis.
Phenotypic Analysis
The100 F5 plants tagged and sampled for DNA extraction from each population were harvested and evaluated as F5:6 lines for resistance to Sclerotinia stem rot by the detached leaf method (Steadman et al., 1997; Leone and Tonneijck, 1990). The parents and F5:6 lines were grown in the greenhouse between December 1997 and May 1998 on different planting dates, 2 wk apart, in 29.5-cm pots. To make four measurements of the lesion size, six seeds per pot were planted and later thinned to four plants. When the plants had reached the V4 stage (Fehr and Caviness, 1977), the most recently developed fully expanded trifoliolate leaf of each plant was detached and wrapped in a wet paper towel for transferring to the laboratory. Aluminum roasting pans were lined on the bottom with paper towels, and four petri plates were inverted and placed on the bottom of each pan. The detached leaves were placed over the inverted petri dishes, and each petiole was inserted in rubber stoppered orchid tubes containing distilled water.
Experimental design for each population was an alpha lattice. In each replication, the 100 RILs and parental lines for a population were randomized in 26 pans, four leaves per pan. Pans were considered incomplete blocks. One replicate consisted of one leaf from an F6 plant of each F5:6 RIL, plus one leaf from a single plant of each parent in the population. Plants sampled for one replication were tagged so they were not sampled again. Four replications were tested for each population.
A potato dextrose agar (PDA) plug from a culture of S. sclerotiorum isolate 143 from soybean, was placed near the center but not directly on the midvein of the middle leaflet. The 8-mm plug was taken from the advancing edge of the mycelium. After adding 300 mL of water to the bottom of each pan, a plastic film wrap was used to cover each pan to provide a humid environment. After 48 h of incubation at a constant temperature of 22 ± 1°C, the length and width of each lesion was measured with a ruler and the lesion area determined by calculating the area of an elliptical circle as 
(d1 x d2)/4 (where: d1 = Diameter 1, d2 = Diameter 2).
Initial screening of soybean lines was conducted using S. sclerotiorum isolate number 143 from soybean (J. Steadman). After identification of parents for this study, determined on the basis of their more consistent ranking for partial resistance (smaller lesion size), a screen of the parental cultivars was conducted comparing reaction to two soybean S. sclerotiorum isolates. These isolates were selected from a group of about 20 soybean isolates based on their virulence on Corsoy 79, and represent isolates with moderate and high virulence (Steadman et al., 1998). In addition, a screen of the RILs from the Corsoy 79 population was conducted with both isolates. No crossover interactions in reaction to the two isolates were observed, and Isolate 143 was chosen because of the greater separation in lesion size between the resistant parents and Williams 82 (unpublished data).
Data Analysis
LSMEANS for lesion area were calculated for each RIL in a population by the PROC MIXED procedure of SAS (SAS Institute, Inc., 1989), with PAN(REP) declared a random effect. A t-test comparing line means with parental means was performed in PROC MIXED, and RILs whose LSMEANS were significantly smaller than those of the resistant parent (P = 0.05), or significantly greater than those of the susceptible parent were considered to be transgressive segregates. To identify genomic regions associated with Sclerotinia resistance, the Sclerotinia disease response of the two F5 homozygous genotypic classes for each DNA marker were compared by single-degree-of-freedom contrasts in PROC MIXED. A significance criterion of 
= 0.05 was used to declare a significant association between a DNA marker and lesion size. Linkage analysis was performed by Mapmaker (Lander et al., 1987). Interval analysis, using Mapmaker/QTL (Lincoln and Lander, 1990), was performed for those markers that comprised linkage groups of two or more markers. The data were run as RILs with heterozygous marker genotypes treated as missing data. A LOD score of 2.5 was chosen as a significance criterion. Our choice of a liberal significance criterion may lead to more false positives, or Type I errors, but since this research is in an exploratory phase and involves multiple populations, Type II errors (false negatives) could be a greater impediment to future research.
|
RESULTS AND DISCUSSION |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
|
|
|
Another finding of this study is that alleles associated with smaller lesion size originated from both the less-susceptible and the more-susceptible parents. For example, Satt424 on Linkage Group A2 and Satt191 on Linkage Group G were significant in the S19-90 and Vinton 81 populations, with the favorable allele coming from Williams 82, the susceptible parent (Table 2). This suggests that resistance to Sclerotinia stem rot is incomplete and can be improved. It also indicates that some cultivars susceptible to Sclerotinia stem rot, such as Williams 82, may be useful sources of resistance alleles. Several studies have shown that favorable alleles for partial resistance to fungal pathogens coming from the susceptible parent are frequently detected with molecular markers (Mestries et al., 1998; Knetkovsky et al., 1996; Young et al., 1994; Wang et al., 1994).
Kim and Diers (2000) reported three QTLs on Linkage Groups C2, K, and M for resistance to Sclerotinia stem rot in a soybean population of F3-derived lines from a cross between S19-90 and Williams 82. None of the linkage groups reported by Kim and Diers (2000) to be involved in Sclerotinia stem rot resistance in the S19-90 population were significantly associated with this trait in our study. The reason for this, in the case of Linkage Groups C2 and M, was the lack of polymorphic SSR markers in that region of the genome in our study. In addition, the markers on Linkage Group C2 and M were associated with escape mechanisms in the field (maturity and lodging) and not physiological resistance (Kim and Diers, 2000). On Linkage Group K, Satt046 was polymorphic but difficult to score unambiguously in our study. The marker Satt167, coincident with Satt046 (Cregan et al., 1999), was polymorphic but was not associated with a significant reduction in lesion size. We did identify two putative QTLs on Linkage Group K in the Corsoy 79 population marked by Satt260 and Satt588 (Fig. 2, Table 2), but these were not significant in any of the other four populations in our study.
Transgressive Segregation and Marker Genotypes
Possible transgressive segregates were identified for resistance in the Dassel population, and for susceptibility in the DSR 173 population (Fig. 1, Table 3). A transgressive segregate was defined as a line whose phenotype (LSMEAN for lesion area) was significantly (P 
0.05) smaller than that of the resistant parent, or significantly greater than that of the susceptible parent. In the DSR 173 population, six RILs had mean lesion sizes of 6.2 to 7.5 cm2 compared with 4.1 cm2 for the susceptible parent Williams 82. Genotypes at significant marker loci showed that these susceptible recombinants had unfavorable alleles from both parents (Table 3). One segregate that was more resistant than the resistant parent was identified in the Dassel population. The recombinant, Line 35, inherited the favorable allele from both parents at seven of the nine significant marker loci and had a mean lesion size of 1.2 cm2 compared with 3.6 cm2 for Dassel, the resistant parent (Table 3).
|
There are no known genes with major effects conditioning resistance to this disease in soybean; individual gene effects are small and heritability is low. Consequently, identification of chromosomal regions affecting resistance to Sclerotinia stem rot is difficult. This study was designed to help identify potentially significant QTL by comparing across populations. For example, 90 polymorphic markers were scored in the Corsoy 79 population, and 12 putative QTLs were identified at P 0.05. The probability that at least one of those markers is incorrectly identified as related to the trait is 1 - (0.95)90 = 0.99. Employing Bonferroni's correction to control experimentwise error rate, an individual marker in the Corsoy 79 population would need to be significant at P = 0.0006. Clearly none of the individual markers was associated with that level of significance in a single population (Table 1). However, comparing across populations narrows the pool of putative QTLs, and decreases the probability that their identification is a Type I error.
In this study, three putative QTLs were significantly (P 0.05) associated with decreased lesion size in multiple populations on three linkage groups, G, L, and O (Table 2, Fig. 2). Four additional putative QTLs were identified in individual populations using P 0.05, but had marginal significance values in other populations of 0.05 P 0.10 (Linkage groups A2, D1a, D1b, and F; Table 2; Fig. 2). Linkage group D2 contains significant markers from three different populations, but the same marker was not significant in more than one population, and the significant markers in different populations were at least 27 cM apart (Table 2, Fig. 2).
Because the five populations used in this study have Williams 82 as a common parent, a single-factor analysis of variance was performed over the pooled data for those markers that were polymorphic in more than one population. When the pooled analyses were conducted, some of those markers were significantly associated with lesion size across populations. For example, markers Satt147 and Satt129 on Linkage Group D1a were polymorphic in four populations and are tightly linked (Table 2, Fig. 2). Both markers were significantly (P = 0.009 and 0.016) associated with lesion size in the DSR 173 population (Table 2), and marginally significant in the S19-90 population (P = 0.056 and 0.070). These markers were significant (P = 0.03) when data from the four populations in which the markers were polymorphic were pooled.
Significant association with lesion size for one additional marker was detected only when the data were pooled. Marker Satt431 on Linkage Group J, which was polymorphic in two populations, was not significantly associated with lesion size in an individual population. However, when the data from the S 19-90 and Vinton 81 populations were analyzed together, Satt431 showed a significant (P = 0.009) association with decreased lesion size. The marker is located in the same region where other resistance genes and resistance gene analogs have been mapped (Kanazin et al., 1996; Yu et al., 1996) (Fig. 2).
Significant Linkage Groups and Comparisons with Previous Disease Resistance Mapping Studies
Plant resistance genes have been found in several cases to occur in clusters. In soybean, disease resistance genes have been mapped on Linkage Groups F, G, J and N (Lohnes and Schmmitthenner, 1997) and nematode resistance genes or QTLs on Linkage Groups A2, F, G, and O (Tamulonis et al., 1997a,b,c; Mudge et al., 1997). In addition, resistance gene analogs (RGA) in soybean map to the same linkage groups and in close proximity to disease and nematode resistance genes (Kanazin et al., 1996; Yu et al., 1996). In this study, markers that were significantly associated with lesion size on soybean leaves infected with Sclerotinia sclerotiorum also were located on these same linkage groups, as well as on other linkage groups (Table 2, Fig. 2). It is on Linkage Groups D1a, F, and O, however, where significant QTLs for Sclerotinia resistance were identified in multiple populations and in which the favorable allele came from the resistant parent (Fig. 2, Tables 2 and 4). An interesting observation is that putative QTLs for resistance to the fungal pathogen Sclerotinia sclerotiorum on Linkage Groups F, G, J, and N occur in regions where there are concentrations of resistance genes for other fungal pathogens, such as fusarium (SDS), phytophthora (Rps), and powdery mildew (Rmd) (Fig. 2). In addition, on Linkage Group N, markers Satt009 and Satt387 were associated with reduced lesion size with the favorable allele coming from the Williams 82 parent. Williams 82 has the Rps1k allele for resistance to Phytophthora root rot (caused by Phytophthora sojae M.J. Kaufmann & J.W. Gerdemann), which maps in the same region as the two markers (Diers et al., 1992) (Fig. 2).
|
|
CONCLUSIONS |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
Limited polymorphism between Williams 82 and the other parents prevented complete coverage of the soybean genome with SSR markers. Lack of polymorphism for Sclerotinia stem rot resistance and gaps between markers in individual maps may have resulted in some important QTLs being overlooked.
The detached leaf assay measures the host-pathogen interaction under consistently favorable environmental conditions for disease development; it does not measure escape mechanisms. While disease escape, whether by early flowering, maturity, upright, open canopy, or less lodging is a valid and important component in field situations, physiological resistance can offer consistent resistance across environments. Escape mechanisms, on the other hand, can be overcome under favorable environmental conditions for disease development.
Additional studies using these five populations are being conducted to verify the QTLs detected in this study and identify new QTLs. A genetic and phenotypic analysis of the ancestors of Williams 82 and the five more-resistant parents is underway to verify the QTLs identified in this study and to determine the origin of the resistance alleles. Putative QTLs identified in multiple populations are being crossed to Williams 82 to develop lines with different combinations of QTLs in the susceptible parent background. In addition, new markers will be evaluated to provide information in regions where no marker polymorphism currently exists. Our identification of putative resistance genes on seven different linkage groups supports the observations and idea that resistance to Sclerotinia sclerotiorum is genetically complex. Crosses to transfer these QTLs to high-yield cultivars also are underway. Combining QTLs for physiological resistance with plant traits that favor disease escape should enhance resistance levels in the field.
|
ACKNOWLEDGMENTS |
|---|
|
NOTES |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
Received for publication October 25, 1999.
|
REFERENCES |
|---|
|
TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONCONCLUSIONSREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  B. Calla, T. Vuong, O. Radwan, G. L. Hartman, and S. J. Clough Gene Expression Profiling Soybean Stem Tissue Early Response to Sclerotinia sclerotiorum and In Silico Mapping in Relation to Resistance Markers The Plant Genome, July 1, 2009; 2(2): 149 - 166. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. D. Vuong, B. W. Diers, and G. L. Hartman Identification of QTL for Resistance to Sclerotinia Stem Rot in Soybean Plant Introduction 194639 Crop Sci., November 24, 2008; 48(6): 2209 - 2214. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. Zhang, P. Chen, C. Y. Chen, D. Wang, A. Shi, A. Hou, and T. Ishibashi Quantitative Trait Loci Mapping of Seed Hardness in Soybean Crop Sci., July 1, 2008; 48(4): 1341 - 1349. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
X. Guo, D. Wang, S. G. Gordon, E. Helliwell, T. Smith, S. A. Berry, S. K. St. Martin, and A. E. Dorrance Genetic Mapping of QTLs Underlying Partial Resistance to Sclerotinia sclerotiorum in Soybean PI 391589A and PI 391589B Crop Sci., May 1, 2008; 48(3): 1129 - 1139. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. Zhao, G. R. Ablett, T. R. Anderson, I. Rajcan, and A. W. Schaafsma Inheritance and Genetic Mapping of Resistance to Rhizoctonia Root and Hypocotyl Rot in Soybean Crop Sci., May 27, 2005; 45(4): 1441 - 1447. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. D. Burnham, A. E. Dorrance, T. T. VanToai, and S. K. St. Martin Quantitative Trait Loci for Partial Resistance to Phytophthora sojae in Soybean Crop Sci., September 1, 2003; 43(5): 1610 - 1617. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. Rubio, H. Liao, X. Yan, and J. P. Lynch Topsoil Foraging and Its Role in Plant Competitiveness for Phosphorus in Common Bean Crop Sci., March 1, 2003; 43(2): 598 - 607. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. R. Cober, S. Rioux, I. Rajcan, P. A. Donaldson, and D. H. Simmonds Partial Resistance to White Mold in a Transgenic Soybean Line Crop Sci., January 1, 2003; 43(1): 92 - 95. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| The SCI Journals | Agronomy Journal | Vadose Zone Journal | |||
| Journal of Natural Resources and Life Sciences Education |
Soil Science Society of America Journal | ||||
| Journal of Plant Registrations | Journal of Environmental Quality |
The Plant Genome | |||
for lesion area determined using the detached leaf assay