Quantitative Trait Loci for Partial Resistance to Phytophthora ... - USDA

Quantitative Trait Loci for Partial Resistance to Phytophthora sojae in Soybean K. D. Burnham, A. E. Dorrance,* T. T. VanToai, and S. K. St. Martin ABSTRACT

In addition to the Rps genes, soybean has partial resistance (also referred to as general, rate-reducing resistance, and tolerance) to P. sojae (Buzzell and Anderson, 1982; Schmitthenner, 1985). Partial resistance appears to be controlled by several genes (Walker and Schmitthenner, 1984; Glover and Scott, 1998). St. Martin et al. (1994) reported that partial resistance does not have a negative impact on yield in the absence of disease. Tooley and Grau (1984a,b) proposed that this type of resistance works by limiting the lesion growth rate of the pathogen in host tissues which, in turn, limits yield losses. Buzzell and Anderson (1982) proposed combining partial resistance with specific Rps genes to provide long-term management of Phytophthora root and stem rot as well as to avoid the boom-and-bust cycle of single gene deployment. The challenge that faces soybean breeders and pathologists alike is to identify the most efficient means of incorporating this polygenic resistance into soybean cultivars. Molecular markers can facilitate selection for both single gene traits as well as polygenic inherited traits for agronomic crop improvement (Bent and Yu, 1999; Kumar, 1999). Simple sequence repeat DNA markers have recently been used to identify single genes, including genes for disease resistance (Cregan et al., 1999b; Mian et al., 1999; Hegstad et al., 2000; Arahana et al., 2001). Simple sequence repeat markers have also been used to identify loci linked to quantitative traits. QTLs have been identified for resistance to a number of soybean diseases including brown stem rot [caused by Phialophora gregata (Allington & D.W. Chamberlain) W. Gams] (Lewers et al., 1999), Sclerotinia stem rot [caused by Sclerotinia sclerotiorum (Lib.) de Bary] (Kim and Diers, 2000; Arahana et al., 2001); soybean cyst nematode (Heterodera glycines Ichinohe) (Schuster et al., 2001); sudden death syndrome [caused by Fusarium solani (Mart.) Sacc. f. sp. glycines (Burkholder) W.C. Synd. & H.N. Hans.] (Njiti et al., 1998; Iqbal et al., 2001), and root knot nematodes (Meloidogyne spp.) (Tamulonis et al., 1997a,b). The objective of this study was to identify SSR markers associated with putative QTLs for partial resistance to P. sojae.

Partial resistance to Phytophthora sojae Kauffmann and Gerdemann in soybean [Glycine max (L.) Merr.] is expressed as a reduced level of root rot and is effective against all populations of the pathogen. The objective of this study was to identify simple sequence repeat (SSR) markers associated with putative quantitative trait loci (QTLs) for partial resistance to P. sojae in the soybean ‘Conrad’. Three recombinant inbred soybean populations, Conrad ⫻ ‘Sloan’, Conrad ⫻ ‘Harosoy’, and Conrad ⫻ ‘Williams’, were evaluated for root lesion growth rate in growth chamber experiments following inoculation with P. sojae and with SSR markers to identify putative QTLs. The three populations segregated for root lesion growth rate after root inoculations. Two putative QTLs donated by Conrad were identified in all three populations and were positioned on soybean molecular linkage groups (MLGs) F and D1b⫹W. The QTL on MLG F explained 32.4, 35.0, and 21.4% of the genotypic variation for Conrad ⫻ Sloan, Conrad ⫻ Harosoy, and Conrad ⫻ Williams populations, respectively. The QTL on MLG D1b⫹W explained 10.6, 15.9, and 20.7% of the genotypic variation for the same three populations, respectively. The QTL on MLG F appears to be of more value based on the percentage of genotypic variation explained. Because the results indicate that QTLs for partial resistance to P. sojae map to different regions in soybean compared with the known Rps genes poses a challenge to soybean breeders. Marker-assisted selection may expedite the process of combining both Rps genes with partial resistance into high-yielding cultivars.

P

hytophthora root and stem rot of soybean has been managed with single resistance genes (Rps genes), which confer a hypersensitive response following infection by this pathogen (Schmitthenner, 1985). However, as in many host–pathogen systems where single genes are widely deployed, the pathogen adapts, and the host is no longer resistant. Shifts in P. sojae physiologic races have occurred following widespread deployment of cultivars with Rps genes (Schmitthenner et al., 1994; Abney et al., 1997). Fifty-five physiologic races of P. sojae have been reported, although a number of pathotypes of P. sojae have been identified in the north central USA that can have a susceptible interaction with many of the commonly deployed Rps genes, including some Rps genes that have not knowingly been deployed (Schmitthenner et al., 1994; Yang et al., 1996; Abney et al., 1997; Leitz et al., 2000; Kaitany et al., 2001; Dorrance et al., 2003a).

MATERIALS AND METHODS K.D. Burnham, Dep. of Horticulture and Crop Sci., and A.E. Dorrance, Dep. of Plant Pathology, The Ohio State Univ., Wooster, OH 44691; T.T. VanToai, USDA ARS Soil Drainage Research Unit, and S.K. St. Martin, Dep. of Horticulture and Crop Science, The Ohio State University, Columbus, OH, 43210. Salaries and research support provided by State and Federal funds appropriated to the Ohio Agricultural Research and Development Center, The Ohio State University. This research project was supported by Ohio’s Soybean Producers’ check-off dollars through the Ohio Soybean Council. Received 19 July 2002. *Corresponding author ([email protected]).

Three soybean recombinant inbred line populations were developed by crossing susceptible cultivars Sloan, Williams, and Harosoy (Weiss and Stevenson, 1955; Bernard and Lindahl, 1972; Bahrenfus and Fehr, 1980) to a common parent, Conrad (Fehr et al., 1989), with a high level of partial resistance. The populations were advanced by single-seed descent without selection to the F4 generation, where single plants, Abbreviations: BLUP, best linear unbiased predictor; cM, centimorgans; LSM, least square means; MLG, molecular linkage group; PCR, polymerase chain reaction; QTL, quantitative trait locus; SSR, simple sequence repeat.

Published in Crop Sci. 43:1610–1617 (2003).  Crop Science Society of America 677 S. Segoe Rd., Madison, WI 53711 USA

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BURNHAM ET AL.: QTL FOR RESISTANCE TO PHYTOPHTHORA IN SOYBEAN

each descended from a different F4 plant, were selected at random. The mapping population consisted of F4–derived lines, 66 lines from Conrad ⫻ Sloan, 64 lines from Conrad ⫻ Harosoy, and 79 lines from Conrad ⫻ Williams. Use of small populations with a common resistant parent is more likely to provide reliable information than a single resistant ⫻ susceptible population, regardless of size, if the results focus on a resistance QTL that appears in all three populations. The cultivars chosen for this study are standards commonly used in greenhouse, laboratory, and field assays to measure partial resistance to P. sojae. There is only one Rps gene known in this material, and that is Rps7 in Harosoy (Anderson and Buzzell, 1992).

Phenotypic Analysis The F4–derived lines, parents, and checks were inoculated with P. sojae via the slant board test, which is suitable for evaluation of partial resistance to P. sojae in soybean (Olah and Schmitthenner, 1985; McBlain et al., 1991). Seedlings of each recombinant inbred line, parents, and checks were grown in the greenhouse in vermiculite-filled 1.2-L polystyrene containers with bottom drainage. To assure higher levels of germination, lines were treated with benomyl (Benlate 0.4 g L⫺1) after placing the seed on the vermiculite but before covering. After 7 d, the seedlings were removed from the containers and the vermiculite washed from the roots under running tap water. Ten plants from each line were placed on a slant board (polyester cloth on top of a wicking pad on a food service tray which had the raised side of one end removed) (McBlain et al., 1991). The tops of the plants extended over the top of the tray and the roots were on the cloth base. At 20 mm below the initiation of the rooting zone, a scrape wound (≈5 mm in length) was made on each seedling. Cultures of 7-d-old P. sojae grown on half-strength lima bean (Phaseolus lunatus L.) (12 g L⫺1) agar were macerated through an 18-gauge syringe, and ≈0.5 mL of the mycelium-agar slurry was placed on the wound. Phytophthora sojae isolate OH25 (with virulence to Rps1a, 1b, 1c, 1k, 7), which was shown in other studies to be aggressive (Dorrance and Schmitthenner, 2000), was used in all experiments. Sixteen trays were stacked together and bound with a large rubber band and placed in a 25-L rubber square bucket. Hoagland’s solution, 2 L per bucket, was added to the bottom and changed every 2 d. The buckets were placed in a growth chamber at 25⬚C and a 14-h light:10-h dark cycle. Seven days following inoculation, the buckets were removed from the growth chamber and stems above the wound were cut to visualize the total stem colonization. Measurements (mm) were taken on the length of the lesion from the inoculation point upward and on the length of the stem from the cotyledon to the top of the plant. Both lesion length and stem length were used as measures of disease severity since plant growth was inhibited by disease. The three mapping populations for each generation were evaluated in separate slant-board tests, each time with parents, and checks (‘Flint’ and ‘Defiance’) and three replications. A replication consisted of one tray with 10 plants for each line or cultivar. Flint has moderate levels of partial resistance and Defiance is resistant to the OH25 isolate of P. sojae. In the first test, using 1998 seed, the F4:5 lines were evaluated in sets of 10 to 30 lines, from 28 Jan. 1999 until 14 May 1999. Each set was evaluated in a randomized complete block design. Parents and checks common to each set were used as the basis for a combined analysis that included all sets. With seed produced in the 1999 growing season, F4:6 lines from each population along with parents and checks were evaluated in a second experiment from 23 Nov. 1999 until 8 Feb. 2000.

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This time, all entries were included in a common experiment, conducted in a randomized complete block design, with extra entries of Conrad and Sloan appearing systematically approximately every 20 entries.

Genotypic Analysis Following lesion and stem length measurements, leaf tissue from each line was pooled and frozen in liquid N. Plant tissue was lyophilized and stored at ⫺80⬚C until used. The lyophilized leaf tissue was used to extract DNA according to the protocol previously described (Burnham et al., 2002). Three hundred thirty five SSR primer pairs (Research Genetics Inc., Huntsville, AL) were used to screen all four parents, Conrad, Harosoy, Williams, and Sloan, to detect polymorphisms. The four parents were screened with 220 random SSR markers, and the remaining 115 SSR markers were selected based on polymorphism data for two of the four cultivars found on SoyBase (Grant et al., 2002). Simple sequence repeat markers that were polymorphic between Williams and Harosoy were selected from this list and tested on the three crosses used in this study. Additionally, SSR markers revealing polymorphism between the parents of each cross were used to score the progeny from that cross. Simple sequence repeat markers were selected to be spaced evenly over all MLGs with ≈40 to 50 centimorgans (cM) between each SSR marker screened (Table 1). Polymerase chain reactions (PCRs) were performed as recommended by the manufacturers in a total volume of 25 ␮L containing 30 ng of genomic DNA. Amplified PCR products were resolved on 5% high-resolution agarose gels (Amresco, Solon, OH) and stained with ethidium bromide for visualization of the DNA products.

Statistical Analysis The two generations (F4:5 and F4:6) of each population were analyzed separately because of differences in average level of disease severity. Mainly because of incomplete germination, fewer than 10 seedlings were measured in many experimental units in the F4:5 generation. In addition, the set structure used in the F4:5 and the repeated checks in the F4:6 contributed to imbalance in the data set. Because of this, we used a mixed models analysis to obtain the best linear unbiased predictor (BLUP) for each inbred line (Stroup, 1989). The model for both experiments was

Yijkl ⫽ ␮ ⫹ Si ⫹ Cj ⫹ G(C)jk ⫹ SCij ⫹ SG(C)ijk ⫹ εijkl, where ␮ ⫽ overall mean, Si ⫽ effect of the ith set (F4:5) or complete block (F4:6), Cj ⫽ class of entry (j ⫽ 0 for recombinant line and j ⫽ 1, 2, 3, 4, 5, and 6 for the 6 parents and checks), G(C)jk ⫽ genotype within class for recombinant lines only (genotypic variance), SCij ⫽ set ⫻ class, SG(C)ijk ⫽ set ⫻ genotype within class (experimental error), and εijkl refers to sampling variation from plant to plant within an experimental unit. Class of entry was assumed to be a fixed effect, and all other terms random. This model permitted an analysis in which checks and parents were fixed effects and recombinant lines were random. Variance components were estimated using restricted maximum likelihood. Heritability, on a family mean basis, was calculated as:

␴ 2G(C)

␴ 2G(C) ␴2 ␴2 ⫹ SG(C) ⫹ ε 3 30

Epistasis was evaluated by comparing the generalized least squares means of the population means to the midparent

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Table 1. Number of simple sequence repeat markers tested, polymorphisms found, distribution of markers across the soybean genome, and genome coverage in three soybean populations. No. of polymorphisms

Number of Markers Tested

Linkage Group A1 A2 B1 B2 C1 C2 D1a ⫹ Q D1b ⫹ W D2 E F G H I J K L M N O Total Polymorphism, % Genome Coverage, %†

Conrad ⫻ Sloan

Conrad ⫻ Harosoy

Conrad ⫻ Williams

3 0 3 2 1 4 4 2 7 3 4 4 2 0 2 3 2 3 6 4 59 17.6 15.6

2 2 4 3 1 7 4 2 8 3 5 6 3 3 2 2 3 3 7 5 75 22.6 25.2

4 4 3 3 1 7 4 3 5 3 6 2 1 3 2 2 3 1 5 3 65 19.7 17.1

22 10 15 16 15 13 10 24 19 20 10 28 18 12 14 21 12 15 25 16 335

† Coverage based on total genome size of 3000 cM.

Table 2. Variance components and family mean heritability estimates for lesion length and plant height of soybean recombinant inbred line seedlings infected with Phytophthora sojae in slant-board tests. Trait

Generation

Genotypic variance

Experimental error variance

Sampling variance

Heritability

1.618 1.836 4.941 8.902

0.67 0.62 0.71 0.60

1.225 1.021 5.070 7.846

0.83 0.87 0.70 0.62

1.178 0.921 6.478 11.669

0.76 0.59 0.74 0.71

2

Lesion length† Plant height‡

Lesion length Plant height

Lesion length Plant height

F4:5 F4:6 F4:5 F4:6

0.187 0.426 1.198 1.871

F4:5 F4:6 F4:5 F4:6

0.431 0.407 1.735 1.571

F4:5 F4:6 F4:5 F4:6

0.301 0.277 2.383 2.424

mm Conrad ⫻ Sloan 0.113 0.608 0.940 2.850 Conrad ⫻ Harosoy 0.145 0.081 1.705 2.124 Conrad ⫻ Williams 0.166 0.490 1.839 1.759

† Root lesions were measured 7 d after inoculation with P. sojae from the point of inoculation up the stem. ‡ Plant height was measured from the cotyledons to the top of the plant.

mean. If the population mean is significantly different from the midparent mean, then epistatic gene action may be present. To obtain relative parent values to compare with the populations, the following model was used:

in more Type I errors, the design of the study should minimize the risk of falsely declaring QTL because, with a common parent, it is unlikely that a false positive QTL would be identified in all three populations.

Parent values ⫽ (Parent LSM ⫺ Population LSM) ⫻ Heritability.

RESULTS AND DISCUSSION

Linkage analysis between SSR markers was performed with Mapmaker 3.0 (Lander et al., 1987). A LOD value of 3.0 was the threshold for inferring linkage. The linkage maps generated with Mapmaker were then used for interval analysis with Mapmaker/QTL. The data were treated as recombinant inbred lines with any heterozygous marker scores recorded as missing data. A LOD score of 2.5 was used as the threshold in this analysis to identify potential QTLs influencing lesion size. Although choosing a less stringent LOD value can result

As measured by the BLUP values, there was significant genotypic variation for both root lesion size and plant height among the lines for both generations (F4:5 and F4:6) in all three populations (Table 2). Heritability estimates for the F4:6 root lesion were 0.62, 0.87, and 0.59 for Conrad ⫻ Sloan, Conrad ⫻ Harosoy, and Conrad ⫻ Williams, respectively. These estimates suggest that resistance for reduced lesion length can be effectively selected based on these growth chamber assays for par-


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Fig. 1. Frequency distribution of the best linear unbiased predictor (BLUP) values for root lesion length in F4:5 and F4:6 from three soybean populations.

tial resistance to P. sojae. Expression of partial resistance to P. sojae is dependent on several factors: the complexity (number of virulence genes) in the P. sojae population, the environment, and the growth stage when the plant is infected. Inoculations of seeds and seedlings with zoospores demonstrated that when cotyledons had emerged (7 d after planting) partial resistance was effective as measured by plant stand (Dorrance and McClure, 2001). In contrast, field evaluations of resistance to P. sojae are dependent on yield or development of stem rot as traits to measure partial resistance to this root pathogen. From repeated field evaluations, Conrad rarely develops stem rot symptoms (Dorrance et al., 2003b), plus yield is impacted by a number of nonpathogenic factors such as maturity (Johnson and Bernard,

1962). Therefore, this growth chamber assay, that allows for qualitative measurements for resistance to P. sojae based on reduced root lesion size and increased plant height following inoculation without the added encumbrances of additional factors that impact yield, is highly suitable to identify QTLs. Generalized LSMs of each population were not significantly different from the midparent values, indicating that directional epistasis was not present. This test cannot rule out epistasis between specific pairs of loci. It is sensitive only to cumulative epistatic effects that tend to work in the same direction. Transgressive segregation for root lesion size was observed for all three populations in the F4:6 generation (Fig. 1). The F4:5 generation of Conrad ⫻ Sloan did not

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Table 3. Phenotypic correlation of root lesion length (root) and plant height (top) of F4:5 compared with F4:6 soybean populations of crosses Conrad ⫻ Sloan, Conrad ⫻ Harosoy, and Conrad ⫻ Williams to measure the effect of partial resistance to Phytophthora sojae. Conrad ⫻ Sloan

F4:5 Root Top F4:6 Root Top

Conrad ⫻ Harosoy

F4:6

Conrad ⫻ Williams

F4:6

F4:6

F4:5 Top

Root

Top

F4:5 Top

Root

Top

F4:5 Top

Root

Top

⫺0.64** 1.00

0.17 ⫺0.19

⫺0.25* 0.31**

⫺0.06 1.00

0.68** ⫺0.44**

⫺0.70** 0.60

⫺0.54** 1.00

0.62** ⫺0.55**

⫺0.46** 0.55**

1.00

⫺0.78** 1.00

1.00

⫺0.81** 1.00

1.00

⫺0.70** 1.00

* Significant at the 0.05 probability level. ** Significant at the 0.01 probability level.

have lines that were more resistant than the resistant parent, Conrad, which may be because of the reduced lesion size in this test and the high sampling variance, although the heritability was still 0.67 (Table 2). The correlation between the two generations of each population exceeded 0.6 (P ⬍ 0.001) for Conrad ⫻ Harosoy and Conrad ⫻ Williams (Table 3), indicating that the recombinant lines reacted similarly in each generation. Conrad ⫻ Sloan root lesion values were not significantly correlated between generations. However, the plant height measurements were highly correlated. The genetic variances were also greater in the F4:6 than F4:5 for all three of the populations. Thus, we chose to conduct QTL analysis with the F4:6 data. Each population had a different percentage of polymorphic SSR markers. The Conrad ⫻ Sloan population had the least polymorphism at 17.6%, Conrad ⫻ Williams showed 19.7% polymorphism, and Conrad ⫻ Harosoy had the highest level of polymorphism with 22.6%. The SSR markers that were used in this analysis are located on MLGs that are consistent with the previously published maps of the soybean genome (Cregan et al., 1999a; Grant et al., 2002). Previous maps differ with regard to map order and distance for these SSR markers, which could reflect their construction from interspecific crosses (Cregan et al., 1999a; Grant et al., 2002). For example, Satt252 is found at 16.2 cM on the F-ISU map (G. max ⫻ G. soja Siebold & Zucc.; Cregan et al., 1999a) and Satt423 is found at 16.4 cM. However, on the F-CH21 map (‘Clark’ ⫻ Harosoy; Cregan et al., 1999a) from the University of Nebraska, Satt252 is found at 19.9 cM and Satt423 is found at 17 cM. The map generated in this study found Satt252 and Satt423 to be consistent in map order with the F-ISU map, but our recombination distances were larger. The discrepant map distances may have arisen because of our relatively small populations or because of variation in map distance from cross to cross, as reported by Pfeiffer and Vogt (1990). Two P. sojae partial resistance QTLs on two MLGs were detected in all three populations (Fig. 2). One QTL was found on MLG F between SSR markers Satt252 and Satt374. In the Conrad ⫻ Sloan population, the QTL was located in an interval of 15.9 cM between Satt252 and Satt149 with the QTL positioned 4.0 cM from Satt252. The LOD score for this QTL was 3.25 and it accounted for 32.4% of the genotypic variation in this cross. In the Conrad ⫻ Williams population, the same

QTL was located in a 11.0-cM interval between markers Satt252 and Satt149, with the QTL positioned 10.0 cM from Satt252. The LOD score for the QTL in this population was 3.5, and it accounted for 21.4% of the genotypic variation in this cross. Finally, in the Conrad ⫻ Harosoy population, the QTL was positioned between Satt252 and Satt423 in an interval of 11.7 cM. Satt149 was not polymorphic in this population. The QTL was positioned 9.0 cM from Satt252 toward Satt423. The LOD score for the Conrad ⫻ Harosoy QTL was 2.93 and it accounted for 35.0% of the genotypic variation. The second QTL was identified on MLG D1b⫹W (Fig. 2). This QTL was identified in the Conrad ⫻ Sloan and Conrad ⫻ Williams populations between Satt579 and Satt600. This is a very small interval of only 3 cM in the Conrad ⫻ Williams populations and 6.3 cM in the Conrad ⫻ Sloan population. Satt600 was not polymorphic in the Conrad ⫻ Harosoy population, so the QTL falls in the larger interval of 15.1 cM between Satt266 and Satt579. Overall, the LOD scores for this QTL were lower than the one identified on MLG F, but exceeded 2.5 for all three populations. The genotypic variation explained by the QTL on MLG D1b⫹W was 20.7% for Conrad ⫻ Williams, 10.6% for Conrad ⫻ Sloan, and 15.9% for Conrad ⫻ Harosoy. Overall, the QTL associated with partial resistance to P. sojae found on MLG F appears to be a more significant QTL than the one detected on D1b⫹W. The QTL found on MLG F accounted for a larger percentage of the genotypic variation in all populations. Soybean breeders interested in introgressing a QTL for partial resistance from Conrad would likely want to introgress the region on MLG F. Marker-assisted selection could then be employed using the SSR markers Satt252, Satt149, and Satt423, found on MLG F. Resistance genes to P. sojae have been placed on MLGs, A2 (Rps8), G (Rps4, Rps6, and possibly Rps5), J (Rps2), and N (Rps1 and Rps7) (Diers et al., 1992; Lohnes and Schmitthenner, 1997; Demirbas et al., 2001; Burnham et al., 2003). In addition, Rps3 is located on MLG F at Positions 59 and 106 (Diers et al., 1992; Demirbas et al., 2001). Whereas the QTL identified on MLG F mapped to an interval between SSR markers Satt252 and Satt149 (Positions 19 and 20; Grant et al., 2002) in two populations and Satt252 and Satt423 (Position 19; Grant et al., 2002) in one population. None of the P. sojae partial resistance QTLs identified in this


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Fig. 2. Molecular linkage groups associated with partial resistance to Phytophthora sojae. Significant markers are shown in bold. The discrepant map distances may have arisen because of our relatively small populations or because of variation in map distance from cross to cross.

study were found within ⬍3 cm of the Rps loci, which is in contrast to resistance to P. infestans in potato (Solanum tuberosum L.), in which QTLs have been identified near resistance loci (Gebhardt and Valkonen, 2001). This is not surprising in that an earlier study did not find any overlapping effects from defeated Rps genes when challenged with compatible races of P. sojae (Young et al., 1994). Quantitative trait loci for partial resistance to P. sojae may in fact be unique locations, and possibly have alternative mechanisms that are controlled by genes unrelated to the resistance genes that have been identified to date. In addition, resistance gene analogs, or conserved sequences of resistance gene motifs have been identified and mapped in a number of soybean populations (Graham et al., 2000; Yu et al., 1996). None of these resistance gene analogs have been mapped to loci near the putative QTLs identified in this study. Further analysis of these populations with

additional markers, as well as further analysis of the mechanisms of partial resistance may elucidate the types of genes that contribute to this trait. This study identified two putative P. sojae partial resistance QTLs which are present in the partially resistant parent Conrad. Because BLUPs, which are free of nongenetic effects, were used in the QTL mapping program in place of family means, the percentages of variation attributable to each QTL are expressed in terms of the total genotypic variation rather than the phenotypic variation. Together, the two QTLs accounted for ≈30 to 50% of the genotypic variation, which indicates the likely presence of additional QTLs not detected in our study. More importantly, other sources of partial resistance should be screened to identify QTLs with major effects to broaden this resistance. Combinations of multiple QTLs could potentially lead to even higher levels of expression of this disease resistance trait.

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ACKNOWLEDGMENTS We wish to thank Birsen Gecioglu, Therese Miller, and SueAnn Berry for technical assistance with disease screening and marker analysis of the populations; Glenn Mills for technical assistance with population development; as well as C. Sneller and E. van der Knaap for critically reviewing the paper.

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