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a Monsanto Company, 800 N. Lindbergh Blvd., St. Louis, MO 63167
b Department of Crop Sciences, University of Illinois at Urbana–Champaign, 1101 W. Peabody Dr., Urbana, IL 61801
c USDA-ARS, 605 Airways Blvd., Jackson, TN 38301
* Corresponding author (vergel.c.concibido{at}monsanto.com).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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Abbreviations: AFLP, amplified fragment length polymorphism • BAC, bacterial artificial chromosome • LG, linkage group • LRR, leucine-rich repeat • MAS, marker-assisted selection • QTL, quantitative trait locus • R-gene, resistance gene • SCN, soybean cyst nematode • SNP, single nucleotide polymorphism • SSR, simple sequence repeat
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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The genetically diverse field populations of H. glycines combined with the limited germplasm base of commercial soybean for resistance could potentially lead to population shifts over time (Colgrove et al., 2002). Diversity in SCN has been described with a physiological race system that utilizes four resistant soybean genotypes and a susceptible standard as differential lines (Golden et al., 1970). However, this race system does not account for all of the diversity present in SCN. For example, Rao-Arelli et al. (1992b) showed that several isolates of H. glycines were initially classified as one race by this scheme. However, when later tested with resistant genotypes other than the standard differentials, the isolates behaved as different races. To describe diversity better within the nematode, the race system has been replaced with a new scheme that includes additional differentials or indicator lines and classifies nematode populations as "H. glycines types" (HG types) (Niblack et al., 2002). In this review, SCN populations used in mapping studies will be referred to by race designations because most of this work was done before the development of the new HG type system.
The primary methods for controlling SCN include planting resistant cultivars and rotation with nonhost crops. Breeders and nematologists have been successful in developing SCN resistant cultivars. Host plant resistance has allowed soybean production to continue in many growing areas where production could no longer be profitable because of SCN infestations. It was estimated that the resistant cultivar Forrest alone prevented crop losses worth $405 million from 1975 to 1980 (Bradley and Duffy, 1982).
Plant introductions from the USDA Soybean Germplasm Collection have been screened for resistance to nematode populations and resistant lines have been identified (Ross and Brim, 1957; Epps and Hartwig, 1972; Anand and Gallo, 1984; Anand et al., 1988; Young, 1990, Rao-Arelli et al., 1997). Arelli et al. (2000) identified 118 exotic soybean PIs resistant to combinations of SCN races 1, 2, 3, 5, or 14. Anand et al. (1988) reported that the only PI they found with resistance to nearly all SCN races tested was PI 437654, a claim that was later validated by the work of Diers et al. (1997b). Diers et al. (1997b) evaluated a set of 38 SCN resistant PIs with H. glycines races 1, 2, 3, 5, and 14 in the greenhouse. Among these 38 PIs, only PI 437654 and PI 438489B were classified as resistant to all five SCN races in their test. PI 437654 was the more resistant of the two, with a higher number of cysts produced on PI 438489B. In addition, previous work showed that PI 438489B was susceptible to other isolates of races 2 and 14 (Rao-Arelli et al., 1992b). Diers et al. (1997b) also evaluated the genetic relationships among the PIs with 201 genomic clones used as restriction fragment length polymorphism (RFLP) markers. They found that the clustering of the PIs based on markers was consistent with resistance responses to H. glycines. A cluster of PIs that most likely share resistance genes with ‘Peking’ and PI 88788 was also identified.
To date, breeders have incorporated resistance genes from only a few PIs into commercial soybean cultivars. The genetic vulnerability of current soybean germplasm to SCN was illustrated by Anand (1991), who conducted a survey among soybean breeders in North America to determine the SCN resistance sources employed in their breeding programs. The survey showed that of 130 SCN resistant cultivars developed, 57 came from the public sector and 73 from the private sector. The resistance in 69 of these cultivars can be traced to Peking, 24 to PI 88788, 31 to both Peking and PI 88788, and two to PI 90763. In the Midwest, where the majority of the U.S. soybean production is located, PI 88788 is the predominant source of SCN resistance (Diers and Arelli, 1999). In 2001, among the 760 maturity group (MG) I to IV cultivars listed as carrying SCN resistance, 705 had their resistance from PI 88788 alone (Marion Shier, personal communication). More emphasis is now being directed to breeding with additional sources of resistance, such as PI 437654 and PI 89772 (Anand, 1992; Nickell et al., 1999) and PI 209332 (Orf and MacDonald, 1995).
Caldwell et al. (1960) were the first to report on the inheritance of resistance to H. glycines. They found that the inheritance of resistance from Peking fits a three recessive gene model and symbols rhg1, rhg2, and rhg3 were assigned. A later report indicated the presence of a fourth resistance gene from Peking that is closely linked to the i locus (Matson and Williams, 1965), a locus which controls pigment distribution on the seed coat. This fourth gene was reported as a dominant resistance gene and was designated as Rhg4. An additional dominant gene in PI 88788 was identified (Rao-Arelli et al., 1992a) and was later designated as Rhg5 (Rao-Arelli, 1994). Dong et al. (1997) summarized the work that has been done on the genetics of resistance in a number of PIs. These efforts show that some resistance genes are in common among PIs and others were unique (Rao-Arelli and Anand, 1988; Anand and Rao-Arelli, 1989; Rao-Arelli et al., 1989; Myers and Anand, 1991; Rao-Arelli et al., 1992b; Young and Kilen, 1994). The difficulties involved in conducting allelism tests with the established SCN resistance genes make it difficult to prove the novelty of newly discovered genes from PIs in more recent studies.
Genetic marker technology has facilitated the identification, localization, and characterization of QTL associated with important agronomic traits, such as SCN resistance. The first comprehensive genetic maps in soybean were constructed by means of RFLP markers (Keim et al., 1990; Shoemaker and Olson, 1993). Additional mapping has been done with random amplified polymorphic DNA (RAPD) markers (Ferreira et al., 2000), amplified fragment length polymorphism (AFLP) markers (Keim et al., 1997), and simple sequence repeat (SSR) markers (Cregan et al., 1999a). Currently, SSR markers are the most widely used marker system in soybean because they are easy to use, highly polymorphic, and they map to a single locus with each primer pair. This ability to map to a single locus has been especially beneficial because it has made it relatively easy to compare mapping results across genetic populations. The wide availability of genetic marker resources in soybean has led to the publication of numerous papers on the identification and localization of QTL underlying resistance to SCN. This review summarizes these SCN QTL discoveries and discusses how we can better utilize this wealth of genetic mapping information in breeding for SCN resistance. This review also focuses on how these publications have ushered in the new era of breeding and selection for SCN resistant soybean genotypes, also known as marker-assisted selection (MAS), and the eventual sequencing and cloning of candidate rhg1 and Rhg4 resistance alleles.
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SCN QTL Discovery |
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TOPABSTRACTINTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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Concibido et al. (1994) were the first to identify and localize QTL for SCN resistance based on both genotypic and phenotypic data in a segregating population. In a population segregating for resistance from PI 209332, the RFLP markers A085 and B032 were found to be significantly associated with the resistance response to a SCN population with a race 3 phenotype from Minnesota. The two markers together accounted for 51.7% of total phenotypic variation for resistance in the population. The marker A085, located on LG A2 of the soybean RFLP map (Shoemaker and Olson, 1993), was linked to i locus at a distance of 10.9 cM. This finding confirmed the earlier study of Weismann et al. (1992). Later studies with Peking (Mahalingam and Skorupska, 1995; Chang et al., 1997), PI 437654 (Webb et al., 1995), and ‘J87-233’, soybean line with Peking, PI 88788 and PI 90763 in its pedigree (Heer et al., 1998), confirmed the presence of a QTL conferring race 3 resistance near the i locus on LG A2 (Cregan et al., 1999a).
The second marker, B032, tentatively located on LG K of the soybean RFLP map (Shoemaker and Olson, 1993), showed a strong association with SCN disease response in the PI 209332 population and accounted for 38% of the total phenotypic variation for resistance (Concibido et al., 1994). After additional marker data became available, Concibido (1995) revised the position of B032 to its correct position on LG J. In a later study, Concibido et al. (1997) reported that a resistance QTL from PI 90763 also mapped near B032 on LG J.
Concibido et al. (1994) reported a third genomic region, defined by the RFLP marker K069, associated with SCN resistance. The RFLP K069 was previously reported to be associated with SCN resistance in a study using near-isogenic soybean lines (Boutin et al., 1992). They placed the marker on LG G of the soybean RFLP map (Shoemaker and Olson, 1993). This led to the discovery of other markers tightly linked with K069, uncovering a major resistance QTL on LG G (Concibido et al., 1994). Consistent with early genetic studies, the resistant QTL allele on LG G was assigned the gene symbol rhg1.
Follow up research showed that a QTL for race 3 resistance mapped to the location of rhg1 in PI 209332, Peking, PI 88788, and PI 90763 (Concibido et al., 1995; 1997). Additional studies showed that PI 437654 also carried race 3 resistance in the same region on LG G (Webb et al., 1995) and confirmed the presence of a resistance QTL in this region in PI 88788, Peking, and J87-233 (Diers et al., 1997a; Chang et al., 1997; Heer et al., 1998).
Concibido et al. (1996a) later initiated high density mapping around rhg1 to characterize further the region, placing the SCN resistance locus 4.6 cM from the RFLP marker B053 and 2.8 cM from RFLP marker Bng30. More recently, SSR markers have been mapped close to rhg1 (Mudge et al., 1997; Cregan et al., 1999b). This includes the SSR marker Satt309, which is estimated to map 0.4 cM from rhg1 (Cregan et al., 1999b).
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QTL Mapping Inconsistencies |
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TOPABSTRACTINTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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There are several explanations for the discrepancies in the results of the PI 437654 mapping studies of Webb et al. (1995) and Vierling et al. (1996a). Although both groups tested their mapping populations with race 3 nematode populations, their nematode populations could have different parasitism genes that interacted with different resistance genes in PI 437654 (Niblack et al., 2002). Gene duplication (Shoemaker et al., 1996) could provide a second explanation such that Vierling et al. (1996a) might have mapped a duplicate locus for rhg1 in PI 437654. In addition, Vierling et al. (1996a) used Hartwig as a source of resistance in their study, which has Peking in its pedigree. It is possible that Peking could have contributed some of the resistance QTL that Vierling et al. (1996a) mapped. For example, the QTL region on LG F was found significantly associated with SCN phenotypic response in three separate studies involving Peking as one of the sources of SCN resistance (Tables 1–2, Fig. 1). A fourth explanation could be that the inconsistencies were the result of epistatic interactions among the SCN resistance genes and the different genetic backgrounds used in the two studies. These interactions could have resulted in different genes having an effect in each study.
Additional resistance genes have been mapped from PI 437654, and these include a QTL on LG D2 mapped by Schuster et al. (2001). They used a bulk segregant analysis to identify a novel QTL for SCN resistance against race 14 on LG D2 in a cross between Hartwig and a susceptible line, ‘BR-92-31983’. In addition, Webb (2003) found minor QTL on C1, L25 [an unofficial LG with known RFLP markers from LGs B1, B2, and I of the soybean genetic linkage map (Cregan et al., 1999a)], and L26 [presumably LG J due to linkage to an established RFLP marker on LG J of the soybean genetic linkage map (Cregan et al., 1999a)] in PI 437654. Webb (2003) found that these minor QTL were effective against multiple races of SCN (Table 1). Because PI 437654 is reported to be resistant to all known races of H. glycines (Anand et al., 1988), it is not surprising that several resistance QTL have been mapped from this source.
Inconsistencies were also observed for Peking in comparing the QTL mapping results for race 3 resistance across four research groups. Mahalingam and Skorupska (1995) mapped a major resistance QTL from Peking near the i locus, presumably Rhg4, in addition to QTL on LGs F and C2. Concibido et al. (1997) found that the locus on G, presumably rhg1, is the major QTL conditioning resistance in Peking. Later, Qiu et al. (1999) mapped SCN resistance QTL on LGs B2, H, and I. Qiu et al. (1999) stated that the significant QTL markers in the studies on Peking by Concibido et al. (1997) and Mahalingam and Skorupska (1995) did not reach significant levels in their study. However, a later study by Meksem et al. (2001) involving Forrest, which carries resistance from Peking, reaffirmed the importance of rhg1 and Rhg4. The authors proposed a bigenic model for resistance to race 3. This bigenic model is inconsistent with classical genetic studies (Rao-Arelli et al., 1992a; Caldwell et al., 1960; Matson and Williams, 1965) and other QTL mapping studies. However, since Forrest is derived from Peking, it is possible that Forrest only retained the two resistance QTL from Peking, as reported by Meksem et al. (2001). By having only these two QTL segregate in their population, this may have allowed them to better estimate the effects and interactions of these QTL than was possible in other studies.
There are a number of explanations for the inconsistencies in the mapping of resistance QTL from Peking. First, it is likely that each researcher used a different source of Peking. There exist a number of lines named Peking, but they vary in SCN resistance responses and genetic marker analysis has shown that they are genetically diverse (Skorupska et al., 1994). Another explanation is that these groups (Mahalingam and Skorupska, 1995; Qiu et al., 1999; Concibido et al., 1997), except for Meksem et al. (2001), did not have complete genome coverage with their markers, which may have caused some groups to miss QTL detected by others. Most of the explanations given for the inconsistencies in the PI 437654 mapping work of Webb et al. (1995) and Vierling et al. (1996a) also apply here. These explanations include differences in parasitism genes present in the SCN isolates used in each study, gene duplication, and genetic interactions.
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Novel QTL and Sources of Resistance |
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TOPABSTRACTINTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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There have been recent efforts to study whether G. soja has novel SCN resistance genes. Glycine soja is widely distributed in China, Japan, Korea, Taiwan, and eastern Russia and is believed to be the ancestor of cultivated soybean (Hymowitz and Singh, 1987). Wang et al. (2001) were the first to map SCN resistance QTL from G. soja. They mapped SCN resistance QTL in a population developed from a cross between G. max (A81-356022) and G. soja (PI 468916), which is the same population used in generating the public soybean genetic linkage map (Shoemaker and Olson, 1993; Cregan et al., 1999a). They mapped, in the original population and confirmed in a backcross population, a new major QTL in the region between Satt288 and Satt472 on LG G and a second major QTL on LG E. The QTL on LG G maps to a different region from rhg1, and there are no other reports of SCN resistance QTL in this region. The resistance QTL on LG E may not be unique to G. soja as Yue et al. (2001a) mapped a QTL from PI 438489B to the same region as the G. soja QTL.
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Frequency of QTL Discovery among Sources of Resistance |
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TOPABSTRACTINTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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Resistance QTL have been shown to provide resistance to more than one race of SCN. For example, in the ‘Hamilton’ x PI 89772 population (Yue et al., 2001b), the rhg1 region was significantly associated with resistance to four SCN races. There are many additional examples of broad resistance provided by specific QTL, as well as resistance to only specific races. In the Hamilton x PI 89772 population, the QTL on D1a, D2, and E were each significant for only a single SCN race. Broad resistance to many SCN races would be particularly beneficial in breeding to mitigate the catastrophic consequence of potential race shifts in nematode populations in the field.
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Cloning of Candidate SCN Resistance Genes, rhg1 and Rhg4, and Its Implication to SCN Resistance Breeding |
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TOPABSTRACTINTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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In a patent application, Hauge et al. (2001) claim to have cloned candidate genes for rhg1 and Rhg4. Both candidate genes are Xa21-like receptor kinases. Xa21 belongs to class 5 resistance genes (R-genes), and it confers resistance to bacterial blight [Xanthomonas oryzae pv. oryzae (Ishiyama) Swings et al.] in rice (Oryza sativa L.) (Zaitsev et al., 2001). Xa21 is the only known R-gene in this class. Structurally, both candidate genes have an extracellular leucine-rich repeat (LRR) domain, a transmembrane (TM) region, and a serine–threonine kinase domain (Hauge et al., 2001). The LRR region shows similarity at the amino acid level to the Cf5-like R-gene, Cf2.1 (LRR-TM class) (Dixon et al., 1996), which confers resistance to leaf mold (Cladosporium fulvum Cooke) in tomato (Lycopersicum esculentum Mill.). Lightfoot and Meksem (2002) confirmed these results in another patent application. For the Rhg4 Xa21-like candidate gene, sequence comparison by both research groups reveals clear differences in the haplotypes between SCN resistant and susceptible germplasm. This is not the case with the rhg1 Xa21-like candidate gene, which is monomorphic between PI 88788 and some susceptible southern USA germplasm, such as ‘Lee 74’, ‘Essex’ and ‘Hutcheson’. Hauge et al. (2001) also found an HS-1 Pro-like candidate gene for rhg1. HS-1 Pro provides resistance to sugar beet cyst nematode (Heterodera schactii Schmidt) isolated from sugar beet (Beta vulgaris L.) (Cai et al., 1997). However, the soybean HS-1 Pro candidate gene fails to distinguish between resistant and susceptible soybean germplasm. Neither group has reported complementation studies to confirm that they have the correct candidate genes. Thus, it cannot be over-emphasized that these results are preliminary and warrant further validation.
The cloning and analysis of rhg1 and Rhg4 should provide invaluable insight into the mechanisms of genetic resistance to SCN and might provide the knowledge needed to engineer novel resistance genes.
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SCN Marker-Assisted Selection |
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TOPABSTRACTINTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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Marker-assisted selection using SSR markers is currently cost-effective compared with greenhouse screening and as marker technologies continue to improve, the cost will likely be further reduced (Fig. 3). Concibido et al. (1996b) estimated the cost of genotyping to be about $1.50 per data point and requiring less than a week to accomplish from tissue sampling to actual data point generation using RFLP technology. With PCR-based genotyping, the entire process can be done in a day and current cost estimates range from $0.25 to $1.00 per data point depending on the efficiency and volume of operation. By contrast, the cost of conventional SCN greenhouse screening ranges from $1.50 to $5.00 per plant and still takes 30 d. It is likely that the cost of MAS will further decrease as new genotyping platforms, such as single nucleotide polymorphism (SNP) markers, become more available.
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CONCLUSIONS |
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TOPABSTRACTINTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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Genetic mapping studies have provided information on the locations of major SCN resistance genes in many PIs. Despite the seemingly confusing array of SCN QTL discoveries in over a decade of gene mapping, there is some consistency in the results. In almost all studies, QTL mapping to the rhg1 region on LG G conferred the greatest resistance. Another important region that was common among many sources was the Rhg4 region on LG A2. There were four other regions that were significant in more than one genetic background. Minor genes that were reported were suggested to be involved in race specificity but require further validation. There is concern for our seemingly large dependence on one major resistance gene, rhg1, which appears to be common among major SCN resistance sources that are currently being used by breeders in North America. It is imperative that we determine whether these sources actually share the same resistance allele.
With the apparent narrow genetic base of SCN resistance in North American soybean germplasm and the intellectual property issues surrounding rhg1 and Rhg4, it is imperative that we evaluate current SCN resistance strategies in breeding programs. One approach is to confirm the efficacy of QTL, other than rhg1 and Rhg4, and better estimate the magnitude of their effects. A second strategy is to search vigorously for novel SCN resistance genes and sources. However, any claim of novelty for newly discovered SCN resistance genes should be verified with appropriate mapping analysis or tests of allelism with rhg1 and Rhg4.
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ACKNOWLEDGMENTS |
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Received for publication July 14, 2003.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONSCN QTL DiscoveryQTL Mapping InconsistenciesNovel QTL and Sources...Frequency of QTL Discovery...Cloning of Candidate SCN...SCN Marker-Assisted SelectionCONCLUSIONSREFERENCES |
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