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Published online 27 May 2005
Published in Crop Sci 45:1441-1447 (2005)
© 2005 Crop Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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CROP BREEDING, GENETICS & CYTOLOGY

Inheritance and Genetic Mapping of Resistance to Rhizoctonia Root and Hypocotyl Rot in Soybean

G. Zhaoa, G. R. Abletta, T. R. Andersonb, I. Rajcanc,* and A. W. Schaafsmaa

a Ridgetown College, Univ. of Guelph, Main St. E., Ridgetown, ON, Canada N0P 2C0
b Greenhouse and Processing Crop Research Center, Agric. & Agri-Food Canada, Harrow, ON, Canada N0R 1G0
c Dep. of Plant Agriculture, Crop Science Bldg., Univ. of Guelph, Guelph, ON, Canada N1G 2W1

* Corresponding author (irajcan{at}uoguelph.ca)


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION AND CONCLUSIONS
 REFERENCES
 
Rhizoctonia root and hypocotyl rot, caused by Rhizoctonia solani Kühn [teleomorph Thanatephorus cucumeris (Frank) Donk], is an important disease of soybean [Glycine max (L.) Merr.]. Planting resistant cultivars would be an effective and environmentally sound strategy to minimize economic losses from this disease. To facilitate developing resistant cultivars, a study was conducted to: (i) investigate inheritance of resistance to Rhizoctonia root and hypocotyl rot in the moderately resistant soybean PI 442031, and four moderately susceptible commercial cultivars and (ii) identify simple sequence repeat (SSR) markers associated with resistance to Rhizoctonia root and hypocotyl rot. Genetic analysis of several segregating populations indicated that resistance to Rhizoctonia root and hypocotyl rot in soybean was quantitatively inherited and controlled by both major and minor genes with additive gene effects. The estimates of broad sense heritability of resistance were low to moderately high. Transgressive segregants with enhanced levels of resistance were developed by crossing adapted but moderately susceptible commercial soybean cultivars. Three SSR markers (Satt281, Satt177, and Satt245) were significantly associated with host resistance in both F2 and F4:5 populations of PI 442031 x Sterling, wherein both parents contributed resistant alleles. This is the first report on mapping of Rhizoctonia root and hypocotyl rot resistance genes in soybean. Our results indicate that marker assisted selection, coupled with phenotypic selection in later generations, should help to facilitate the development of soybean cultivars resistant to Rhizoctonia root and hypocotyl rot.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION AND CONCLUSIONS
 REFERENCES
 
RHIZOCTONIA ROOT AND HYPOCOTYL ROT is a major disease of soybean (Sinclair and Dhingra, 1975; Yang, 1999). Rhizoctonia solani is predominantly soilborne with a wide host range (Menzies, 1970), making chemical, cultural, and biological controls difficult (Sumner and Bell, 1986; Burpee, 1989; Kataria and Gisi, 1996). Planting resistant cultivars would be an effective and environmentally sound strategy to manage this disease (Khan et al., 1994). To facilitate breeding of resistant cultivars, it is important to understand the genetics of resistance in soybean.

In previous studies (Zhao et al., 2004; Schaafsma et al., unpublished data), a soybean accession, PI 442031, consistently displayed moderate resistance to Rhizoctonia root and hypocotyl rot caused by a number of isolates of anastomosis group (AG)-4, the most common group isolated from diseased soybean plants (Sinclair and Backman, 1989; Yang, 1999) and the group prevalent in many soybean-growing areas (Nelson et al., 1996; Rizvi and Yang, 1996). PI 442031 provides the opportunity to investigate the inheritance of resistance to Rhizoctonia root and hypocotyl rot in soybean.

The conventional method to select for resistant genotypes by inoculating plants with R. solani isolates is time-consuming, laborious, and destructive. In addition, phenotypic data are not always reliable because of substantial environmental influence. Marker assisted selection (MAS) may help to overcome some of these barriers (Melchinger, 1990; Young, 1996). Simple sequence repeat (SSR) markers are highly polymorphic, reproducible, codominant, distributed throughout the soybean genome (Cregan et al., 1999), and have become useful for molecular studies in soybean.

Bulked segregant analysis (BSA) (Michelmore et al., 1991) has made the process of identifying molecular markers linked with traits of interest more efficient; and it has been used successfully to detect molecular markers associated with disease resistance genes or quantitative trait loci (QTL) in many plant species, including soybean (Michelmore et al., 1991; Barua et al., 1993; Poulsen et al., 1995).

The objectives of this study were to: (i) investigate the inheritance pattern of resistance in the soybean accession PI 442031 to Rhizoctonia root and hypocotyl rot caused by AG-4 through genetic analysis of several segregating populations derived from crosses between PI 442031 and moderately susceptible soybean cultivars; (ii) determine whether transgressive segregants with enhanced levels of resistance can be developed through crosses between moderately susceptible commercial soybean cultivars; and (iii) identify SSR markers associated with resistance to Rhizoctonia root and hypocotyl rot in the F2 and F4:5 populations of crosses between PI 442031 and Sterling, a moderately susceptible commercial soybean cultivar, using both conventional genetic linkage mapping and BSA.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION AND CONCLUSIONS
 REFERENCES
 
Plant Materials
The soybean accession PI 442031 and four commercial soybean cultivars (RCAT Staples, Sterling, Evans, and PS 83) were used as parents in this study. In previous studies (Zhao et al., 2004; Schaafsma et al., unpublished data), PI 442031 was moderately resistant to a number of AG-4 isolates, and the four commercial cultivars were moderately susceptible. In the winter of 1998, reciprocal crosses of PI 442031 x RCAT Staples and PI 442031 x Sterling were made in the growth room at the University of Guelph, Guelph, ON. The F1s were advanced to F2 by selfing, and some F1s were backcrossed to the susceptible parent to develop the BC1F1 generations, which were subsequently advanced to BC1F2s. Some F2s of PI 442031 x Sterling and RCAT Staples x PI 442031 were advanced to the F4 generation by single seed descent. The F4s were increased in the summer of 2000 at Ridgetown, ON. Seeds were harvested from each F4 plant to obtain F4:5 recombinant inbred lines (RILs). Unfortunately, because of adverse conditions, seeds from only 23 F4 plants of PI 442031 x Sterling and 32 F4 plants of RCAT Staples x PI 442031 were harvested. Reciprocal crosses of PI 442031 x Evans and Evans x PS 83 were made in 2000, and the F2 generations were subsequently developed. The F2 and BC1F2 populations were used for conventional genetic analysis of resistance to Rhizoctonia root and hypocotyl rot. The F2 and F4:5 populations of PI 442031 x Sterling were used to identify SSR markers linked with resistance to Rhizoctonia root and hypocotyl rot, and the F4:5 population of RCAT Staples x PI 442031 was used to verify the linkage.

In July 2000, parents, reciprocal F1s, F2s, and BC1F2s of PI 442031 x Sterling, and PI 442031 x RCAT Staples were evaluated for resistance to Rhizoctonia root and hypocotyl rot in the greenhouse. Twenty-five seeds of each parent, one to six seeds of each F1, 60 to 170 seeds of each F2, and 50 to 80 seeds of each BC1F2 were planted in plastic trays (27 x 27 x 6 cm) filled with Sunshine LA4 Mix Aggregate Plus soil containing 550 to 650 g kg–1 of fine Canadian sphagnum peat moss and 350 to 450 g kg–1 of perlite (Sun Gro Horticulture Canada Ltd.). Each tray was planted with 10 seeds if available. Trays were placed on the greenhouse benches and arranged randomly within each cross. One week later, a second replication was planted with 20 seeds of each parent, 60 to 170 seeds of each F2, and 70 to 90 seeds of each BC1F2. Because of the lack of seeds, the F1s of all crosses were not included in the second trial.

In June 2001, parents, reciprocal F1s, reciprocal F2s of PI 442031 x Evans, parents and F2 of Evans x PS 83 were evaluated with 20 seeds of each parent, three or four seeds of each F1, and 203 to 250 seeds of each F2 planted in the greenhouse. Trays were completely randomized within crosses. The F4:5 RILs of PI 442031 x Sterling and RCAT Staples x PI 442031, together with their parents, were planted as well in June 2001 in a randomized complete block design with two replications. Twenty seeds of each RIL and parent were planted in each replication with 10 seeds per tray.

Inoculum and Inoculation
An AG-4 isolate (RS86), collected in 1986 from a diseased soybean, was used to produce inoculum for the 2000 tests; and a new AG-4 isolate (RS13), collected in the Summer of 2000 from a diseased soybean at Elora, ON, was used to produce inoculum for the 2001 tests. Isolates of R. solani may lose aggressiveness after a long-term storage in vitro (Butler, 1980; Agrios, 1997). RS86 had been in storage on potato-dextrose agar (PDA) and transferred annually since 1986. There was concern that it might have lost some aggressiveness. When a new aggressive AG-4 isolate (RS13) was available, it was decided to replace the old isolate with the expectation that it would have greater aggressiveness and help to distinguish segregating materials. Previous studies indicated that PI 442031 was moderately resistant to both RS86 (Schaafsma et al., unpublished data) and RS13 (Zhao et al., 2004).

Inoculum was prepared as described previously (Zhao et al., 2004). Hull-less oats were soaked in 20% (v/v) V8 (Campbell Soup Company, Camden, NJ) juice in l-L flasks for 1 h. The oats were drained and autoclaved at 121°C for 30 min each on two successive days. Five 5-mm-diam mycelial disks cut from the margins of a 3- to 5-d-old culture were added into each flask. Cultures were incubated at 22 to 25°C, and the mixture was stirred manually every 3 to 4 d to distribute the inoculum evenly. After 2 wk, the fresh inoculum was added to a 4% (w/v) sodium alginate–water solution at a 1:7 ratio and ground with a blender (Waring, New Hartford, CT) at high speed for 30 s.

At soybean growth stage V1 (Fehr et al., 1971), plants were inoculated as described previously (Zhao et al., 2004). A 1-cm layer of soil around each plant was removed to expose the lower stem of the plant, and 5 mL of inoculum was placed around the plant stem and then covered with soil. Plants were watered twice a day, once in the morning and once in the evening, to maintain the soil moisture near field capacity. One week before disease evaluation, plants were watered lightly to induce a slight drought stress. Temperature in the greenhouse ranged from 20 to 32°C and was commonly between 24 to 27°C for most of the testing period.

Disease Evaluation
Two weeks after inoculation, when symptoms of Rhizoctonia root and hypocotyl rot were evident on susceptible parental plants, disease severity of each plant was evaluated by a 0-to-8 rating scale, where 0 = no symptoms, 1 = slight discoloration, 2 = lesion(s) < 0.5 cm long (up-down) and < 25% stem girdling, 3 = lesion(s) 0.5 to 1.0 cm long and < 25% stem girdling, 4 = lesion(s) > 1.0 cm long and < 25% stem girdling, 5 = lesion(s) < 1.0 cm long and 25-50% stem girdling, 6 = lesion(s) > 1.0 cm long and 25-50% stem girdling, 7 = deep necrotic lesion(s) and > 50% stem girdling, and 8 = plant wilted or dead.

Leaf Sampling and DNA Extraction
Leaf discs were sampled from the two F4:5 populations and 189 F2 individuals of PI 442031 x Sterling, including 96 and 93 individuals selected at random from Replications 1 and 2, respectively. Before inoculation with R. solani, four leaf discs were taken from each F2 plant and four F4:5 plants (one leaf disc/plant) of each RIL and the parents using a paper single hole-punch. Genomic DNA was extracted from two leaf discs of each sample using the Fast DNA Kit (MP Biomedicals, Irvine, CA) following the manufacturer's instructions.

BSA and SSR Analyses
DNA from the five most resistant RILs of PI 442031 x Sterling, which had disease scores significantly lower than the susceptible parent Sterling (Table 1), was pooled at an equal amount to create the resistant DNA bulk. Similarly, DNA from the four most susceptible RILs, which had disease scores significantly higher than the resistant parent PI 442031 (Table 1), was pooled to create the susceptible DNA bulk. A total of 300 SSR markers, spanning the 20 chromosomes of the soybean genome, were used to screen for polymorphism between PI 442031 and Sterling. Markers polymorphic between the two parents were screened against the two DNA bulks. Markers polymorphic between the two DNA bulks were screened against the entire F4:5 population. Parental polymorphic markers were also screened against the 189 F2 individuals of PI 442031 x Sterling. PCR amplifications with SSR primers were performed using a Robocycler 96 Temperature Cycler (Stratagene, La Jolla, CA) following the protocol of SoyBase (2004) with some modification. The 15-µL PCR reaction mixture contained 20 ng of template DNA, 1x PCR buffer (20 mM Tris-HCl pH8.4, 50 mM KCl), 2.5 mM MgCl2, 5 pmol each of forward and reverse primers, 0.5 U Taq DNA polymerase (Invitrogen, Carlsbad, CA), and 0.2 mM each of dNTP (Amersham Biosciences Inc., Piscataway, NJ). The mixture was covered with a drop of mineral oil. The PCR amplification conditions were an initial denaturation at 94°C for 2 min, followed by 40 cycles of denaturation at 92°C for 45 s, annealing at 47°C for 45 s, and extension at 68°C for 45 s. The amplification was terminated by a final extension at 72°C for 5 min. PCR products were separated on 5% (w/v) MetaPhor (Cambrex Corporation, East Rutherford, NJ) agarose gels in 1x TBE buffer. Gels were stained with ethidium bromide, and bands were visualized under UV light and photographed.


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  		Table 1. Mean disease scores (MDS) for the F4:5 RILs used to create the resistant DNA bulk (RB) and the susceptible DNA bulk (SB), for the moderately resistant parent (PI 442031) and the moderately susceptible parent (Sterling). Disease severity was rated by a 0-to-8 scale, where 0 = no symptoms and 8 = plant wilted or dead.

 
Data Analysis
Frequency Distribution of the F2 and BC1F2 Populations
Environmental conditions may have been different during disease development between replications 1 and 2 in the 2000 tests due to a one-week difference in planting date, which might have resulted in heterogeneity between replications. Therefore, the frequency distributions of the two replications within each segregating population were compared with the Kolmogorov-Smirnov two-sample test (Bowley, 1999). When no heterogeneity was detected, the data of the two replications were pooled. Otherwise, the data were analyzed separately. PROC UNIVARIATE of SAS 8.0 (SAS Institute, 1999, SAS, Cary, NC) was used to test for normality of these distributions. Type I error of {alpha} = 0.05 was used to test for significance in this and all following statistical analyses.

Generation Means and Generation Mean Analysis
For the 2000 tests, disease scores of individuals were pooled and averaged to calculate the mean disease score for each generation within each replication. These mean disease scores were used for analysis of variance to generate generation means and to test the significance of differences between generation means. Because of a single replication and different numbers of subsamples, the data of 2001 (except the data of F4:5 populations) were analyzed by PROC UNIVARIATE of SAS 8.0 to generate means and variances. The Student's t test with unequal variance was used to compare mean differences between generations (Bowley, 1999).

Generation mean analysis was conducted to estimate gene effects. If the means of F1 in direct and reciprocal crosses were not significantly different from each other, the average score of the direct and reciprocal F1 was calculated and used as the mean of F1 in the generation mean analysis. A three-parameter model (m, a, and d) was used to estimate the gene effects, where m, a, and d were mean using the F2 as a reference, pooled additive gene effects, and pooled dominance gene effects, respectively (Gamble, 1962; Cherif and Harrabi, 1990). The goodness of fit of the three-parameter model was evaluated by the joint scaling test (Cavalli, 1952; Mather and Jinks, 1982).

The data of F4:5 populations were analyzed by PROC GLM of SAS 8.0. When a significant effect (P < 0.05) was found, the means were separated with Fisher's protected least significant difference (LSD).

Broad Sense Heritability
Broad sense heritability (BSH) of each F2 and BC1F2 population was estimated with Eq. [1] and [2], respectively (Falconer, 1960).


[1]

[2]
where VF2, VBC1F2, and VE were the variances of F2, BC1F2 and environment. The environmental variance VE was estimated using the Eq. [3] (Falconer, 1960).


[3]
where VP1 and VP2 were the variances of parents in each cross. PROC UNIVARIATE of SAS 8.0 was used to estimate VP1, VP2, VF2, and VBC1F2 in each cross.

BSH of the F4:5 population of PI 442031 x Sterling was estimated with Eq. [4] (Lewers et al., 1999).


[4]
where {delta}2g was the genotypic variance within the F4:5 RILs; {delta}2e was the error variance; and r was number of replications. The {delta}2g and {delta}2e were estimated by PROC VARCOMP of SAS 8.0.

Linkage Analysis
Segregation distortion was detected at each marker locus by the Chi-square test for goodness of fit. The molecular data from the F2 population of PI 442031 x Sterling were analyzed by MAPMAKER/EXP 3.0 (Lander et al., 1987). The Kosambi function was used to obtain centimorgan (cM) values. Markers were assigned to linkage groups by the "group" command with a minimum LOD of 3.0 and a maximum distance of 50 cM. The markers were then arranged by the "order" command. Linkage groups were anchored to soybean chromosomes on the basis of the published maps (Cregan et al., 1999).

Association between Markers and Resistance
Significant association between SSR markers and resistance to Rhizoctonia root and hypocotyl rot was detected by the single-factor analysis of variance with marker genotypic classes as the predictor variable and the disease score as the response variable (Doerge et al., 1997). The coefficient of determination (R2) was used as a measure of the magnitude of association. The proportion of genotypic variance explained by the marker was obtained by the formula: {delta}2g = {delta}2p/BSH (Kim and Diers, 2000), where {delta}2g and {delta}2p were the genotypic variance and phenotypic variance explained by the marker, respectively, and BSH was the estimate of broad sense heritability of the population. To detect epistasis between SSR markers, two-factor analysis of variance was performed on all pairs of significant, unlinked markers (Tanksley, 1993). A multifactor analysis of variance model was used to estimate the total phenotypic variation explained by all significant, unlinked markers (Mestries et al., 1998). The heterozygous marker genotypes in the F4:5 populations were treated as missing data (Arahana et al., 2001).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION AND CONCLUSIONS
 REFERENCES
 
Frequency Distributions
Heterogeneity between replications was detected in the F2 of PI 442031 x Sterling (P = 0.018). Data for the two replications were presented separately. The disease scores in all segregating populations were distributed continuously and could not be classified into discrete resistant and susceptible classes (Fig. 1). However, none of them followed a normal distribution. No transgressive segregation in the resistant direction was observed in all BC1F2 and F2 populations with PI 442031 as a parent or grandparent. Transgressive segregants with enhanced levels of resistance were found in the F2 population derived from the moderately susceptible-moderately susceptible cross of Evans x PS83 (Fig. 1).



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  		Fig. 1. Frequency distributions of the F2 and BC1F2 populations. Arrows show means for parental genotypes in each population. Rhizoctonia root and hypocotyl rot was rated using a 0 to 8 scale, where 0 = no symptoms and 8 = plant wilted or dead.

 
Generation Means and Gene Effects
Significant differences were observed among generation means (Table 2). In all crosses, the moderately resistant parent PI 442031 had significantly lower mean disease scores than the moderately susceptible parents. Most plants of PI 442031 had a disease score in the range of 1 to 4 on the 0-to-8 scale; most plants of the moderately susceptible parents had a disease score ranged from 4 to 7, and no plants with a disease score of 8 were found. The mean disease scores of F1 and F2 generations were intermediate between the scores of the two parents, and the mean disease score of F1 was not significantly different from that of the reciprocal F1. The mean disease score for the BC1F2 was higher than that for the F2 in the cross of PI 442031 x Sterling, but in the cross of PI 442031 x RCAT Staples, the mean disease scores for the BC1F2 and F2 were not different. In the cross of Evans x PS 83, the parents and the F2 population had high disease scores (>5.0), and the scores were not significantly different from each other.


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  		Table 2. Generation means and standard errors (SE) for populations evaluated for resistance to Rhizoctonia root and hypocotyl rot grown in the greenhouse in 2000 and 2001.

 
The nonsignificant Chi-square values indicated that the three-parameter model adequately explained the variation among generation means for Rhizoctonia root and hypocotyl rot resistance in these crosses (Table 3). In all crosses, the m component, which represents the F2 mean, was significantly different from zero. The dominance gene effects were not significant, whereas significant additive gene effects were found in all crosses.


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  		Table 3. Gene effects estimated by generation mean analysis. Five generations (two parents, F1, F2, and BC1F2) were evaluated in crosses PI 442031 x Sterling and PI 442031 x RCAT Staples and four generations (two parents, F1, and F2) were evaluated in crosses PI 442031 x Evans and Evans x PI 442031. The joint scaling test was used to evaluate the goodness of fit of the three-parameter model.

 
Broad Sense Heritability
The estimates of BSH were low to moderately high (Table 4). The BSH for the F2 populations was between 43% and 57%, and between 37 and 58% for the BC1F2 populations. Although heterogeneity was found between the two replications of F2 of PI 442031 x Sterling, the estimates of BSH were similar. The BSH estimated for the F4:5 population of PI 442031 x Sterling was 67%, which was higher than the BSHs for the F2 populations derived from the cross between the two parents.


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  		Table 4. Broad sense heritability (BSH) of the F2, the BC1F2 and the F4:5 populations.

 
Linkage Map
Two SSR markers (Sat128 and Sat135) with segregation distortion were detected by the Chi-square test of the F2 molecular data set. Therefore, these two SSR markers were excluded from further analyses (Lewers et al., 1999). Of the remaining 298 SSR markers tested in this study, 50 were polymorphic between the two parents, PI 442031 and Sterling. These markers were assigned to 9 linkage groups with 21 markers remaining unlinked (data not shown). For most linkage groups, the marker order was identical and the map distances were similar or greater than those in the published map (Cregan et al., 1999). All SSR markers were mapped to the same chromosomes as the published map, except Satt251. In this F2 mapping population, Satt251 was mapped to chromosome O at a distance of 1.5 cM from Satt259. However, the published map assigned Satt251 to chromosome B1 using the USDA/Iowa State University population (Cregan et al., 1999). The difference may be due to different mapping populations used, and a possible chromosomal rearrangement occurred in either population.

SSR Markers Associated with Resistance
Three SSR markers (Satt281, Satt177, and Satt245) were significantly associated with resistance to Rhizoctonia root and hypocotyl rot in both F2 and F4:5 populations of PI 442031 x Sterling (Table 5). In the F2 population, Satt281, Satt177, and Satt245 explained 11, 7, and 6.8% of the phenotypic variation, respectively. In the F4:5 population, the three markers explained 39, 23, and 14% of the phenotypic variation, respectively. Together, they accounted for 49% of the phenotypic variation and 73% of the genotypic variation in the F4:5 population. In both populations, no epistasis was detected between any two loci. At locus Satt281, individuals with the marker genotype of PI 442031 had significantly lower disease scores than individuals with the marker genotype of Sterling, suggesting that the resistant allele was derived from the moderately resistant parent PI 442031. At loci Satt177 and Satt245, individuals with the marker genotype of Sterling had significantly lower disease scores than individuals with the marker genotype of PI 442031, suggesting that the resistant allele was derived from the moderately susceptible parent Sterling. In the F2 population, at the three marker loci, the mean disease scores of the heterozygotes were intermediate between the mean disease scores of the two homozygotes, suggesting additive gene effects (Mestries et al., 1998).


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  		Table 5. SSR markers and marker genotype means significantly associated with Rhizoctonia root and hypocotyl rot resistance by the single-factor analysis of variance based on the F2 and F4:5 data of the cross PI 442031 x Sterling.

 
The association of Satt281 with resistance to Rhizoctonia root and hypocotyl rot was confirmed in a second F4:5 population of the cross RCAT Staples x PI 442031. In this population, Satt281 was significantly associated with resistance (P = 0.0009), and explained 18% of the phenotypic variation and 47% of the genotypic variation (data not shown).


   DISCUSSION AND CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION AND CONCLUSIONS
REFERENCES
 
There was evidence from this study that the AG-4 isolate RS13 was more aggressive than RS86. The mean disease score for PI 442031 was 1.9 inoculated with RS86, whereas it was 3.5 inoculated with RS13. However, RS86 was aggressive enough to distinguish the different responses between the moderately resistant PI 442031 and the moderately susceptible Sterling and RCAT Staples, and it was also able to separate the materials in the segregating populations (F2 and BC1F2). That makes isolate RS86 appropriate for identifying SSR markers associated with resistance to Rhizoctonia root and hypocotyl rot based on the phenotypic data from the F2 population of PI 442031 x Sterling.

The genetics of resistance in PI 442031 to both AG-4 isolates (RS86 and RS13) are similar. Although different isolates were used as inoculum, the frequency distribution, gene effects, broad sense heritability of the populations were similar, and the same three SSR markers were found to be significantly linked to host resistance in both F2 (inoculated with RS86) and F4:5 (inoculated with RS13) populations of PI 442031 x Sterling. Isolates of AG-4 have been subdivided into two subgroups (HGI and HGII) on the basis of DNA relatedness. No attempt was made in this study to identify the subgroup of these two isolates. It may be useful in the future to classify these two isolates into subgroups to elucidate whether the model of resistance in soybean obtained from this study is to all subgroups of AG-4 isolates or just specific to one subgroup.

Resistance in soybean to Rhizoctonia root and hypocotyl rot caused by AG-4 is a quantitative trait involving both major and minor genes with additive gene effects. The inability to classify disease scores into discrete classes of resistance and susceptibility in the segregating populations is evidence for resistance as a quantitative trait. Genetic analysis of several segregating populations with PI 442031 as a parent indicated that one or a few major genes and minor genes with additive gene effects confer resistance to Rhizoctonia root and hypocotyl rot in PI 442031. Dickson and Boettger (1977) and Silva and Hartmann (1982) also reported that resistance in snap bean (Phaseolus vulgaris L.) to Rhizoctonia root rot caused by R. solani was quantitatively inherited, and that two to three genes with additive gene action were responsible for the resistance.

Resistant cultivars may be developed through crossing two adapted but moderately susceptible commercial soybean cultivars. Transgressive segregants with enhanced levels of resistance were obtained in the cross between the moderately susceptible cultivars PS 83 and Evans, indicating that there were different minor resistance genes with additive gene actions in the two parental lines (Cherif and Harrabi, 1990). The additive gene effects suggest that it is possible to develop soybean cultivars with a higher level of resistance by pyramiding resistance genes from different resistance sources.

Genetic mapping using SSR markers in the F2 and F4:5 populations was additional evidence that both major and minor genes with additive gene action controlled resistance in soybean to Rhizoctonia root and hypocotyl rot, and that moderately susceptible cultivars also contributed resistant alleles. A major locus, detected by Satt281 with the resistant allele coming from PI 442031, explained 11% of the phenotypic variance in the F2 population, and 39% of the phenotypic variance in the F4:5 population. Satt177 and Satt245 each with a relatively small effect were detected in the mapping populations, and favorable alleles at both loci were contributed by the moderately susceptible parent Sterling. Susceptible parents contributing resistance alleles to fungal pathogens have been reported in several crops (Young et al., 1994; Mestries et al., 1998; Arahana et al., 2001).

Selection for resistant soybean genotypes to Rhizoctonia root and hypocotyl rot using the conventional method is possible but should be conducted in later generations. Significant additive gene action was found in all populations in the genetic study, suggesting that later family selection for resistance should be more efficient. In addition, BSH estimated in the F2 and BC1F2 populations was low to moderate, which was improved in the F4:5 generation, suggesting that selection in the F5 or later generation would be more efficient than in the F2 or BC1F2.

SSR markers detected in this study could be valuable in facilitating selection for resistance to Rhizoctonia root and hypocotyl rot in soybean. Phenotypic evaluation for resistance to Rhizoctonia root and hypocotyl rot in soybean is time-consuming, laborious, and destructive. The estimates of BSH were low to moderately high, implying a large impact of environment on the development of Rhizoctonia root and hypocotyl rot. Three SSR markers (Satt281, Satt177, and Satt245) were found to be significantly associated with resistance in both F2 and F4:5 populations of PI 442031 x Sterling, and the association between Satt281 and resistance was verified in a second F4:5 population of RCAT Staples x PI 442031. MAS with these SSR markers could be used to improve the selection efficiency. However, because of the small population size of the mapping population of F4:5 of PI 442031 x Sterling and the verifying population of F4:5 of RCAT Staples x PI 442031, the application of these results may have to be further verified in larger populations.

In conclusion, resistance in soybean to Rhizoctonia root and hypocotyl rot caused by AG-4 is quantitative and conditioned by major and minor genes with additive gene effects. To our knowledge, this is the first report on mapping of Rhizoctonia root and hypocotyl rot resistance genes in soybean. MAS, combined with phenotypic selection in later generations, should improve the progress of developing soybean cultivars resistance to this important disease.


   ACKNOWLEDGMENTS
 
The financial support of the Ontario Soybean Growers, the Adaptation Council of Canada, and the Ontario Ministry of Agriculture and Food is greatly acknowledged. We thank Julia Zilka for making all soybean crosses used in this study, Dr. R.L. Nelson, curator of Soybean Germplasm Collection of USDA, for providing seeds of PI 442031, and Dr. Berlin Neslon of North Dakota State University for helpful discussions and for providing some of the AG isolates used in this research.

Received for publication September 21, 2004.


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