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Localization of two loci that confer resistance to soybean cyst nematode from Glycine soja PI 468916.

SOYBEAN CYST NEMATODE is the most important soybean pathogen in the United States (Riggs and Niblack, 1999). Heterodera glycines is a diverse, sexually reproducing pathogen that causes decreased shoot vigor, reduced nodulation, and root necrosis in soybean plants (Rao-Arelli et al., 1992; Riggs and Niblack, 1999). The most efficient way to control SCN is to rotate nonhost crops with resistant soybean cultivars. While resistant soybean cultivars suppress the reproduction of nematodes, damage caused by SCN infestations is not completely eliminated (Rao-Arelli and Anand, 1988).

The soybean germplasm collection is a valuable source of genes for the genetic improvement of soybean; however, molecular marker analyses have shown that there are few SCN-resistance genes deployed in elite germplasm and G. max PIs often have resistance genes in common (Skorupska et al., 1994; Diers et al., 1997; Diers and Arelli, 1999; Wang et al., 2001; Concibido et al., 2004). For example, PI 437654 (Webb et al., 1995), PI 209332, PI 88788, PI 90763, PI 89772, and Peking (Concibido et al., 1996, 1997; Chang et al., 1997; Yue et al., 2001b) all have the major SCN-resistance gene, rhg1, on LG G (Cregan et al., 1999b). This locus controls a large proportion of the total variation for resistance and is effective against several HG Types of SCN (Concibido et al., 1996, 1997). In addition, Peking (Matson and Williams, 1965; Mahalingam and Skorupska, 1995; Chang et al., 1997), PI 209332 (Concibido et al., 1994), and PI 437654 (Webb et al., 1995) have the resistance gene Rhg4 that maps near the I locus (black seed-coat pigmentation) on linkage group A2 (Cregan et al., 1999a). Because of the diverse nature of SCN, nematode populations may overcome the resistance genes that are currently deployed (Rao-Arelli et al., 1992).

Evidence exists that G. soja, the wild ancestor of soybean, has genetic diversity not present within domesticated soybean germplasm (Keim et al., 1989; Maughan et al., 1995). Recently, Wang et al. (2001) found G. soja PI 468916 to be resistant to populations of SCN with race 3, 5, and 14 phenotypes. Evaluating a population of [F.sub.2]-derived lines and confirmed in a population developed through one backcross, two major QTL that confer resistance to a HG Type 0 (Niblack et al., 2002) (Race 3) SCN isolate were identified. One QTL was mapped between Satt598 and Satt491 on LG E of the soybean genetic map (Cregan et al., 1999a), and the second QTL was mapped between Satt288 and Satt472 on LG G. The QTL on LG G maps to a position where no other SCN resistance QTL has been reported and is over 100 cM from the major SCN-resistance gene rhg1 from G. max (soybase.ncgr.org, verified 14 June 2005; Concibido et al., 2004). However, a SCN-resistance QTL has been reported from G. max PI 438489B at the same location as the LG E QTL from G. soja. The PI 438489B QTL was shown to confer resistance to SCN isolates with race 2 and 14 phenotypes (Yue et al., 2001a).

Marker-assisted selection (MAS) of the SCN-resistance QTL from G. soja PI 468916 would be more efficient if the intervals containing the QTL were better defined and additional markers linked to the QTL were identified. Markers tightly linked to the resistance QTL would lessen linkage drag, decrease frequency of crossover events between marker and the resistance genes, and help distinguish between effects of pleiotrophy, epistasis, and linkage (Keim et al., 1997). Closely linked markers would also more accurately define the location of the resistance genes for map-based cloning, which could lead to a better understanding of the mechanisms controlling SCN resistance in soybean.

One strategy to more accurately define the location of the resistance loci from G. soja PI 468916 combines both genetic and molecular methods. The first step involves identifying additional molecular markers within the regions where each resistance QTL maps. Amplified fragment length polymorphism (Vos et al., 1995) coupled with BSA (Michelmore et al., 1991) has been a successful method for adding molecular markers to targeted regions. Using this approach, AFLP markers tightly linked to two SCN-resistance genes (rhg1 and Rhg4) from G. max have been identified and converted into sequence-tagged-site markers (Meksem et al., 2001a, 2001b). The second step involves the development of populations that segregate for different recombinational events within the genetic regions where each resistance QTL resides. Evaluation of this material with molecular markers and for response to SCN would localize the positions of the two SCN-resistance QTL described by Wang et al. (2001).

The objectives of this research were to confirm the SCN-resistance QTL from G. soja PI 468916 in a domestic soybean background and to localize, or better define, the positions of these QTL. This objective was reached by adding molecular markers to the regions harboring these QTL through AFLP-BSA, and by developing and testing populations that segregate for different intervals from the regions where the resistance QTL map.

MATERIALS AND METHODS

Population Development

A population of B[C.sub.4][F.sub.3:4] lines was developed to confirm the SCN-resistance QTL in a domestic soybean background and to map the locations of AFLP markers using BSA. The G. soja PI 468916 was used as a donor parent and the soybean experimental line A81-356022 was the recurrent parent during the backcrossing. Genetic markers flanking the LGs E and (3 SCN-resistance QTL were used to select the G. soja QTL alleles during each cycle of backcrossing. A single B[C.sub.4][F.sub.1] plant that was heterozygous for both SCN-resistance QTL was selected and single-seed descent was used to develop a population of 93 B[C.sub.4][F.sub.3:4] lines. This population is referred to as LDX01-1. The LDX01-1 population differs from the population of B[C.sub.1][F.sub.2] plants used to confirm the SCN-resistance QTL in Wang et al. (2001) due to its more advanced backcross generation. The LDX01-1 population had a normal soybean phenotype typical of elite soybean breeding populations. This is in contrast to the B[C.sub.1] population which had many wild soybean characteristics. Each line within LDX01-1 has a theoretical G. soja PI 468916 genome content of approximately 3%, as opposed to 25% in each line of the Wang et al. (2001) backcross population.

Populations that segregated for regions near the SCN-resistance QTL alleles from G. soja P1468916 were created through backcrossing and selecting plants with recombination near the QTL. The B[C.sub.4][F.sub.2] populations, A81-1-5 and A81-1-2, were developed from a B[C.sub.2][F.sub.1] plant that was used in the development of LDX01-1. Using the B[C.sub.2][F.sub.1] as a male parent, B[C.sub.3][F.sub.1] seed was produced using A81-356022 as the recurrent parent. The seeds were planted and plants with recombination near the resistance genes were selected based on markers. A fourth backcross was made to produce B[C.sub.4][F.sub.1] seed. These seed were sown and the presence of the recombinational events were confirmed by marker analysis. The two B[C.sub.4][F.sub.2] populations were developed from seed harvested from two B[C.sub.4][F.sub.1] confirmed plants. Approximately 100 B[C.sub.4][F.sub.2] plants segregating for regions near the QTL were grown from each population and individually harvested to produce B[C.sub.4][F.sub.2:3] lines.

The B[C.sub.4][F.sub.4] populations, A81-1-2-14, A81-2-7-20, A81-2-11-18, and A81-2-7-60, were developed to identify populations segregating for additional regions near the SCN-resistance QTL. These were developed from the same backcross germplasm as the [C.sub.4][F.sub.2] populations. B[C.sub.4][F.sub.2:3] lines were tested with markers and those lines with recombination near the resistance QTL were selected. B[C.sub.4][F.sub.3] plants from each selected line were grown and plants heterozygous for different regions near the QTL were identified with markers and selected. Approximately 150 B[C.sub.4][F.sub.4] plants were grown from each selected B[C.sub.4][F.sub.3] plant. The B[C.sub.4][F.sub.4] plants were individually harvested to produce B[C.sub.4][F.sub.4:5] lines. In each B[C.sub.4][F.sub.2] and B[C.sub.4][F.sub.4] population, lines were tested with genetic markers and 8 to 15 lines that were homozygous for alleles from each parent were selected for use in SCN bioassays.

SSR Analysis

Genomic DNA was extracted from leaf tissue of eight greenhouse-grown seedlings per line for each population evaluated in this study according to Keim et al. (1988) with modifications as described by Kisha et al. (1997). The SSR markers used in this study were developed by P.B. Cregan (USDA-ARS, Beltsville, MD). All SSR markers available within and surrounding the genetics regions on LGs E and G harboring the G. soja SCN-resistance QTL were tested for polymorphism. Those markers that were polymorphic were used in the analysis. Polymerase chain reactions (PCR) were performed according to Cregan and Quigley (1997). The PCR products were analyzed by electrophoresis in 6% nondenaturing polyacrylamide gels (Sambrook et al., 1989; Wang et al., 2003) and stained with 1 [micro]g m[L.sup.-1] ethidium bromide.

AFLP Analysis

The AFLP protocol is according to Vos et al. (1995) with the following modifications. Genomic DNA was isolated using the DNeasy DNA isolation kit (Qiagen Inc., Valencia, CA) according to the manufacturer's instructions. The purified DNA was digested with EcoRI and MseI restriction enzymes with digestion performed in a final volume of 25 [micro]L in 10 mM TRIS-HCl (pH 7.5), 10 mM MgAc, 50 mM KAc, 5 mM DTT, 6 U EcoRI (Invitrogen Life Technologies, Carlsbad, CA), 4 U MseI (New England BioLabs, Inc., Beverly, MA), and 250 ng of genomic DNA for 2 h at 37[degrees]C, 15 rain at 70[degrees]C, and held at 4[degrees]C. Adaptors were ligated to the DNA by adding 25 [micro]L of a mixture containing 5 [micro]M EcoRI adaptor, 50 [micro]M MseI adaptor, 0.4 mM ATP, 10 mM TRIS-HCl (pH 7.5), 10 mM MgAc, 50 mM KAc, and 1 U T4 DNA ligase (Invitrogen Life Technologies, USA) to the digestion product. The ligation reactions were incubated for 2 h at 20[degrees]C and held at 4[degrees]C. The 50-[micro]L aliquot of the ligation reaction was then diluted (1:10) with 450 [micro]L of sterile water.

The first PCR amplification was performed using EcoRI + A and MseI + C primers (MWG-Biotech, High Point, NC) in a 50-[micro]L volume of 20 mM TRIS-HCl (pH 8.4), 50 mM KCI, 1.5 mM Mg[Cl.sub.2], 1.25 mM of each dNTP, 10 [micro]M of each primer, and 1.25 U Taq DNA polymerase (Invitrogen Life Technologies, USA). The reactions were performed in a DNA thermal cycler (MJ Research Inc., Waltham, MA) and subjected to the following cycling parameters: 72[degrees]C for 2 min, with a subsequent 25 cycles of 94[degrees]C denaturation for 30 s, 56[degrees]C annealing for 60 s, and 72[degrees]C extension for 60 s, with a final step of 60[degrees]C for 10 min. The amplification products were diluted (1:20) by adding 950 [micro]L sterile water and used as DNA template for the second PCR amplification.

For the second PCR amplification, EcoRI and MseI primers (MWG-Biotech, USA) with three selective nucleotides were used with the EcoRI primer being fluorescently labeled. The PCR reaction was performed in a 20-[micro]L volume of 200 mM TRIS-HCl (pH 8.4), 500 mM KCl, 15 mM Mg[Cl.sub.2], 10 [micro]M EcoRI primer, 10 [micro]M MseI primer, 1.25 mM of each dNTP, 1 U Taq DNA polymerase, and 5 [micro]L of diluted DNA template. The PCR cycling parameters consisted of: 94[degrees]C for 2 min, followed by 12 cycles of 30 s denaturation at 94[degrees]C, annealing for 30 s at 65[degrees]C, reduced by 0.7[degrees]C per cycle for 30 s, annealing at 56[degrees]C for 30 s, and extension at 72[degrees]C for 1 min. An additional extension step of 72[degrees]C for 10 min was completed and the reactions were held at 4[degrees]C.

At the end of the second PCR amplification, 2 [micro]L of each sample were denatured by adding 4 [micro]L of filtered formamide containing Gene-Scan-500 ROX size standard (Applied Biosystems, USA). The samples were heated for 3 min at 95[degrees]C and quick-chilled on ice. Four microliters of each sample were loaded on a 4.8% acrylamide/bis-acrylamide (20:1), 8 M urea, and 1 x TBE gel (25 by 42 cm). The samples were then electrophoresed at a constant 200 W for 2.5 h using an ABI Prism 377 DNA Sequencer (Applied Biosystems, Foster City, CA). The AFLP markers were designated by their primer combination and by their fragment size (e.g., [E.sub.AGA][M.sub.ACC]158: EcoRI + AGA/MseI + ACC, fragment size 158 base pairs).

DNA Pool for BSA

The DNA bulks used in the BSA each included five selected B[C.sub.4][F.sub.3:4] lines from the LDX01-1 population. The resistant bulk consisted of lines that were resistant to SCN and possessed the G. soja alleles at Satt598, Satt573, Satt491, and Satt263 on LG E, and Satt505, Satt288, and Satt472 on LG G. The susceptible bulk included five lines that were susceptible to SCN and carried the G. max alleles for all seven markers on LGs E and G. Markers that were polymorphic between the resistant and susceptible bulks were mapped by evaluating all lines in the LDX01-1 population with these markers. In addition, lines selected for SCN bioassays from each B[C.sub.4][F.sub.2] and B[C.sub.4][F.sub.4] population were tested with the mapped AFLP markers. This was done to identify the locations of the crossover events in the QTL containing regions in each population.

Heterodera glycines Isolate and SCN Bioassay

Plants were inoculated with the H. glycines isolate PA3 (HG Type 0, Race 3) (Niblack et al., 2002) provided by Dr. P.R. Arelli (USDA-ARS, Jackson, TN). All SCN bioassays were performed in the greenhouse. The SCN inoculation technique has been described previously (Arelli et al., 2000) but was modified slightly. In brief, germinated soybean seeds were sown into separate plastic micropots filled with steam-pasteurized fine sandy soil. Micropots were placed in a polypropylene container and maintained at approximately 27[degrees]C in a thermo-regulated water bath. Light yellow female cysts were crushed to release eggs and larvae. These were collected, transferred to water, centrifuged, resuspended in water, and layered on the surface of a 45% sucrose solution. The egg solution was centrifuged and a clean band of eggs rinsed with water. The SCN inoculum was diluted with water and each seedling was inoculated with 3000 [+ or -] 25 eggs and juveniles. Approximately 30 d after inoculation, plant roots were individually washed with a strong jet of water to dislodge cysts. The cysts were counted under a stereomicroscope and a female index (FI) was calculated. Bioassays were repeated two to five times for each line using a completely randomized design. The experimental unit was an individual inoculated plant. Glycine max host differentials were included in all inoculation studies including the susceptible cultivar Lee 74. A female index was calculated for each plant using the formula (Golden et al., 1970):

FI = (100 x Number of cysts and females per plant)/ (Average number of cyst and females on 'Lee 74')

Ratings of resistant (FI = 0-9) moderately resistant (FI = 10-30), moderately susceptible (FI = 31-60), and susceptible (FI > 60) were used to classify response to SCN inoculation (Schmitt and Shannon, 1992).

Linkage and Marker Analysis

Linkage maps of SSR and AFLP markers within population LDX01-1 were constructed with JoinMap Version 3.0 (Van Ooijen and Voorrips, 2001). Map distances in centimorgans were estimated with the Haldane mapping function. Associations between AFLP and SSR markers and response to SCN within population LDX01-1 were detected using interval mapping with MapQTL Version 4.0 software (Van Ooijen and Maliepaard, 1996). The association was considered significant if the [log.sub.10] of the odds ratio (LOD) was equal to or greater than 3.0. Nonadditive interaction between the SCN-resistance QTL on LGs E and G was determined by two-way analysis of variance with SAS (SAS Institute Inc., Cary, NC). Single-factor analysis of variance using PROC GLM of SAS was done to detect associations between AFLP and SSR markers and SCN resistance in segregating populations. A significant association was declared if P < 0.05. The proportion of total phenotypic variation explained by each marker was revealed by [R.sup.2] values. The total phenotypic variance explained by the two SCN-resistance QTL combined was determined by multifactor analysis of variance.

RESULTS

Marker Saturation and Confirmation of the SCN-Resistance QTL

A total of 704 AFLP primer combinations were analyzed to identify polymorphisms between the two bulks of SCN-resistant and SCN-susceptible B[C.sub.4][F.sub.3:4] lines in the LDX01-1 population. On average, 65 fragments were resolved per primer combination for an approximate total of 45 800 loci evaluated. Forty-three were found to be polymorphic between the two bulks. Upon genotyping the LDX01-1 population, 24 AFLP markers mapped to the region containing the SCN-resistance QTL on LG E (Fig. 1). This genetic region spans a distance of approximately 24 cM from markers [E.sub.AGA]/[M.sub.ACC]158 to Satt263. Twelve AFLP markers mapped to a 49-cM region spanning from markers [E.sub.AGG][M.sub.GCG]79 to Satt472 where the SCN-resistance locus on LG G mapped (Fig. 1). Seven AFLP markers mapped to other genetic regions within the LDX01-1 population.

[FIGURE 1 OMITTED]

A significant (P < 0.05) association was observed between the greenhouse SCN bioassay of the LDX01-1 population and AFLP and SSR markers on LGs E and G (Table 1). These results show that we were successful in both backcrossing and confirming the effect of both QTL in a domestic soybean background. All expected allelic-class combinations were observed. Lines that were homozygous at the peak LOD G. soja PI 468916 marker alleles at both LGs E and G loci exhibited moderate resistance to SCN with a mean FI of 20. Lines that were homozygous at the peak LOD A81-356022 marker alleles at both loci were susceptible to SCN with a mean FI of 89. Lines that were homozygous for only one of the G. soja PI 468916 resistance QTL exhibited moderate resistance (Table 1). Two-way analysis of variance did not detect a significant (P = 0.05) interaction between the two genetic regions. Interval mapping revealed that the LG E QTL at its peak LOD score of 10 explained 20% of the total phenotypic variation for SCN resistance in the LDX01-1 population (Table 1).

At a peak LOD score of 7, the QTL on LG G explained 17% of the total phenotypic variation for SCN resistance. The LG E and G QTL together accounted for 65% of the phenotypic variation for SCN resistance based on two-way analysis of variance.

Localization of the SCN-Resistance Locus on LG E

Three populations segregating for different chromosomal segments near the QTL on LG E were identified and tested with markers and for SCN resistance. This included population A81-1-5, which exhibited a breakpoint between markers Satt491 and [E.sub.ACC][M.sub.TCC]230, population A81-1-2-14, which exhibited a break-point between markers [E.sub.AGG][M.sub.TCG]125 and [E.sub.AGG][M.sub.GGA]213, and population A81-2-7-20, which also exhibited a breakpoint between markers [E.sub.AGG][M.sub.TCG]125 and [E.sub.AGG][M.sub.GGA]213 (Fig. 2). All lines within populations A81-1-2-14 and A81-2-7-20 were fixed for the A81-356022 allele for the resistance QTL on LG G, whereas population A81-1-5 segregated for the resistance QTL at this region.

[FIGURE 2 OMITTED]

Single-factor analysis of variance revealed no statistically significant (P = 0.05) association between the AFLP and SSR markers and SCN resistance within populations A81-1-5 and A81-1-2-14 (Fig. 2). All selected lines evaluated within these two populations were susceptible to SCN. Within population A81-2-7-20, a statistically significant (P < 0.0001) association was detected between SCN resistance and the genetic region that spans 22 AFLP and two SSR markers from centimorgan position 9.8 ([E.sub.AGG][M.sub.TCG]125) to at least centimorgan position 23.7 (Satt263) (Fig. 2). No informative markers were available to determine a genetic breakpoint below Satt263 in this population. Lines homozygous for the G. soja PI 468916 alleles exhibited moderate resistance to SCN with a FI range of 18 to 23 and a mean of 21. Lines homozygous for the A81-356022 alleles exhibited susceptibility to SCN inoculation with a FI range of 61 to 91 and a mean of 69. This genetic region accounted for 94% of the total phenotypic variation for SCN resistance in the population. Based on the marker genotype and the response to SCN inoculation of populations A81-1-5 and A81-2-7-20, the genetic interval containing the G. soja PI 468916 SCN-resistance locus lies between [E.sub.AGG][M.sub.TCG]125 and [E.sub.ACC][M.sub.TCC]230, a distance that spans 13.2 cM.

Localization of the SCN-Resistance Locus on LG G

Three populations segregating for different chromosomal segments near the QTL on LG G were identified and tested with markers and for SCN resistance. This included population A81-2-11-18, which exhibited a breakpoint between markers [E.sub.CAA][M.sub.CGA]137 and [E.sub.CAA][M.sub.TAC]72, population A81-2-7-60, which exhibited a break-point between markers [E.sub.CAA][M.sub.TAC]72 and Satt472, and population A81-1-2, which exhibited a break-point between markers [E.sub.AGC][M.sub.AAG]176 and Satt288 (Fig. 3). All lines within populations A81-2-11-18 and A81-2-7-60 were fixed for the A81-356022 QTL alleles on LG E, whereas lines within population A81-1-2 segregated for the resistance QTL at this genetic region.

[FIGURE 3 OMITTED]

Single-factor analysis of variance revealed no statistically significant (P = 0.05) association between AFLP and SSR markers and SCN resistance within population A81-2-11-18 (Fig. 3). All evaluated lines were susceptible to SCN. A statistically significant (P < 0.0001) association was detected between SCN resistance and the genetic region that spans 12 AFLP and three SSR markers from centimorgan position 0.0 ([E.sub.AGG][M.sub.GCG]79) to centimorgan position 48.7 (Satt472) within population A812-7-60 (Fig. 3). No informative markers to determine the genetic breakpoint above [E.sub.AGG][M.sub.GCG]79 were available. This genetic region spans a distance of at least 48.7 cM. Lines homozygous for the G. soja PI 468916 alleles exhibited high to moderate levels of resistance to SCN with a FI range of 9 to 21 and a mean of 15. Lines homozygous for the A81-356022 alleles exhibited moderate to high levels of susceptibility to SCN with a FI range of 57 to 82 and a mean of 69. This genetic region accounted for 92% of the total phenotypic variation for SCN resistance in the population.

A statistically significant (P < 0.0001) association was also detected between SCN resistance and the genetic region that spans four AFLP and two SSR markers from centimorgan position 30.2 ([E.sub.AGC][M.sub.AAG]176) to at least centimorgan position 48.7 (Satt472) within population A81-1-2 (Fig. 3). No informative markers were available to determine a genetic breakpoint below Satt472. This genetic region spans a distance of at least 18.5 cM. Lines homozygous for the G. soja PI 468916 alleles exhibited at least moderate resistance to SCN inoculation with a FI range of 19 to 42 and a mean of 30. Lines homozygous for the A81-356022 alleles exhibited variable response to SCN inoculation with a FI range of 37 to 100 and a mean of 76. There was segregation in this population for the resistance QTL on LG E. This may explain the variable response to SCN inoculation among lines homozygous for each LG G QTL allele and the lower [R.sup.2] value than was observed in the A81-2-7-60 population. The genetic region on LG G within this population accounted for 51% of the total phenotypic variation for SCN resistance. Based on the marker genotype and the response to SCN inoculation of populations A81-2-7-60 and A81-1-2, the genetic interval containing the G. soja PI 468916 SCN-resistance locus lies between [E.sub.AGC][M.sub.AAG]176 and Satt472, a distance that spans 18.5 cM.

DISCUSSION

We have better defined the positions of the two G. soja PI 468916 SCN-resistance QTL previously described by Wang et al. (2001) on LGs E and G. In our approach, SSR markers linked to each SCN-resistance QTL were initially useful in detecting recombination in the genetic region where each SCN-resistance QTL mapped and in the development of segregating populations. Our search for additional molecular markers within the region of each SCN-resistance QTL was accomplished using AFLP markers facilitated by the use of BSA (Michelmore et al., 1991). With relatively little effort, AFLP markers tightly linked to the two SCN-resistance QTL were identified. With the addition of AFLP markers linked to these QTL, the location of recombinational breakpoints within each targeted region were identified in our segregating populations. This allowed us to more narrowly define the locations of the two SCN-resistance QTL derived from G. soja PI 468916.

We positioned the SCN-resistance QTL on LG E to a 13.2-cM interval between AFLP markers [E.sub.AGG][M.sub.TCG]125 and [E.sub.ACC][M.sub.TCC]230, and the QTL on LG G to an 18.5-cM interval between AFLP markers [E.sub.AGC][M.sub.AAG]176 and Satt472. This compares to mapped intervals of 58 cM on LG E and the 24 cM on LG G in the [F.sub.2] population described by Wang et al. (2001). We base our localization of the QTL by determining the points of recombination within our populations and by examining their response to SCN inoculation. The 13.2-cM interval on LG E is fairly well saturated with markers. Twenty-three markers have been mapped to this region giving an average marker distance of 0.6 cM. In contrast, additional markers are still needed in the region containing the resistance QTL on LG G. For this 18.5-cM interval, only six markers have been mapped, giving an average marker distance of 3.1 cM. The addition of AFLP markers within each region of the SCN-resistance QTL will aid in map-based cloning of these genes.

A QTL for SCN resistance, rhgl, has been previously mapped on LG G near the SSR marker Satt309 (Concibido et al., 1996; Danesh et al., 1998; Cregan et al., 1999b). As reported by Wang et al. (2001), the G. soja PI 468916 SCN-resistance QTL, at its highest LOD peak in their [F.sub.2] population, was more than 100 cM from the rhg1 locus. In our study, all populations evaluated did not possess the rhg1 resistance locus. This suggests that the G. soja PI 468916 SCN-resistance QTL on LG G is unique. Further analysis, including cloning of the G. soja SCN-resistance QTL, will be necessary to clarify its relationship with the SCN-resistance gene rhgl. Cloning the G. soja PI 468916 SCN resistance genes could potentially aid in improving our understanding of the soybean-SCN interaction.

A QTL on LG E has been reported from G. max PI 438489B that confers resistance to SCN with race 2 and 14 phenotypes but not race 3 (Yue et al., 2001a). This QTL is at or near the same location as the LG E race 3 resistance QTL from G. soja PI 468916. Glycine soja PI 468916 was found to be resistant to SCN races 5 and 14 in addition to SCN race 3 (Wang et al., 2001). In the [F.sub.2] population derived from G. soja PI 468916 and G. max A81-356022, no QTL were detected for SCN race 5 or 14 resistance on LG E (Wang et al., 2001). The LG E SCN-resistance

QTL from G. soja PI 468916 and G. max PI 438489B may be examples of race-specific SCN resistance.

Soybean cyst nematode is the most important soybean pathogen in the United States and its control relies on genetic resistance (Riggs and Niblack, 1999). Deployment of the G. soja SCN-resistance genes should not only increase the genetic diversity for SCN resistance but may also extend the beneficial effects of currently deployed SCN-resistance genes by providing growers with an alternative source of resistance that can be used in rotations. Our refinement of the positions of the SCN-resistance QTL will be useful in MAS, as we have identified SSR markers that we know flank the resistance QTL. For example, we know that the LG E resistance QTL is between the SSR markers Satt573 and Satt263. The AFLP-BSA technique was very useful in identifying additional molecular markers in the regions harboring each SCN resistance QTL. These closely linked markers will assist in map-based cloning of the G. soja PI 468916 SCN-resistance QTL. The conversion of these AFLP markers into more breeder-friendly PCR-based markers would be most useful in marker-assisted selection.

ACKNOWLEDGMENTS

This research was supported by the Florida Agricultural Experiment Station and a grant from USDA/NRI 2002-01225 and approved for publication as Journal Series R-11058.

Abbreviations: AFLP, amplified fragment length polymorphism; BSA, bulked segregant analysis; cM, centimorgans; FI, female index; LG, linkage group; LOD, likelihood of odds; PI, plant introduction; QTL, quantitative trait loci; SCN, soybean cyst nematode; SSR, simple sequence repeat.

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E. A. Kabelka, * S. R. Carlson, and B. W. Diers

E.A Kabelka, Horticultural Sciences Dep., Univ. of Florida, Gainesville, FL 32611; S.R. Carlson and B.W. Diers, Dep. of Crop Sciences, Univ. of Illinois, Urbana, IL 61801. Received 10 Jan. 2005. * Corresponding author (ekabelka@ifas.ufl.edu).
Table 1. Genetic regions associated with soybean cyst nematode
resistance in the LDX01-1 population based on single-factor analysis of
variance and interval mapping.

Linkage group         Peak LOD ([dagger])    Peak LOD marker   P value

E and G ([section])           --                   --          <0.0001
E                             10                 Satt573       <0.0001
G                              7                 Satt472       <0.0001

                                            Mean female index for
                                             lines homozygous at
                                              peak LOD marker
                                               alleles from:

Linkage group             [R.sup.2]
                      ([double dagger])    PI 468916   A81-356022

E and G ([section])          65%               20           89
E                            20%               28           68
G                            17%               26           59

([dagger]) Likelihood of odds.

([double dagger]) Proportion of total phenotypic variation explained
based on single-factor analysis of variance using SAS (SAS Institute
Inc., Cary, NC).

([section]) Combined effect of the linkage group E and G significant
markers based on multifactor analysis of variance using SAS.
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Author:Kabelka, E.A.; Carlson, S.R.; Diers, B.W.
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Date:Nov 1, 2005
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