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Crop Science 40:375-382 (2000)
© 2000 Crop Science Society of America

CROP BREEDING, GENETICS & CYTOLOGY

Soybean Quantitative Trait Loci for Resistance to Insects

L.I. Terrya, K. Chasea, T. Jarvika, J. Orfb, L. Mansurc and K.G. Larka

a Dep. of Biology, University of Utah, Salt Lake City, UT 84112 USA
b Dept. of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108 USA
c Facultad de Agronomia, Universidad Catholica de Valpariso, Casilla 4-D, Quillota, Chile

terry{at}biology.utah.edu


   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 Materials and methods
 Results and discussion
 REFERENCES
 
Resistance to insects was found in a recombinant inbred (RI) population of soybean derived from nonresistant parents, `Minsoy' and `Noir 1' (MN) (240 RI). The objectives of this study were to determine quantitative trait loci (QTLs) associated with this resistance by linkage to either restriction fragment length polymorphism (RFLP) or simple sequence repeat (SSR) markers and to confirm these loci in a new population derived from Minsoy crossed with the elite cultivar Archer (MA) (233 RI). Corn earworm (Helicoverpa zea Boddie) larvae were reared on individual lines of the MN and MA RI and several larval traits were measured. Of the 20 linkage groups (LG) of the composite genetic soybean map, QTLs were found on five LGs in the MN and four in the MA population. The QTL on LG U2 is associated with major effects on larval development in both the MN (r2 > 0.12) and the MA population (r2 > 0.28). All other QTLs had lesser effects (r2 < 0.10). The U2 QTL associated with resistance to insects is of major importance in that: (i) it has been identified in different genetic backgrounds; (ii) it is associated with several larval growth parameters; and (iii) it explains a large proportion of the phenotypic variation. All other QTLs were observed to segregate in only one population. Most of the resistance alleles were associated with the Minsoy parent. Consistent with this observation, Archer and Noir 1 were better corn earworm larval host plants than Minsoy.

Abbreviations: cM, centimorgans • QTLs, quantitative trait loci • RI, recombinant inbreds • RFLP, restriction fragment length polymorphism • SSR, simple sequence repeat • MA, Minsoy x Archer cross • MN, Minsoy x Noir1 cross • LG, linkage group • LOD, log of the odds


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
Materials and methods
 Results and discussion
 REFERENCES
 
THE IDENTIFICATION OF PLANT GENES associated with specific insect resistance has mainly involved qualitative traits, controlled by one or a few genes (Khush and Brar, 1991). By contrast, many important plant traits, including their chemical defenses, such as inducible isoflavanoids, may involve quantitative traits, for example, 2-tridecanone in tomato (Lycopersicon esculentum Miller and L. hirsutum f. glabratum C.M. Miller; Nienhuis et al., 1987), that result from the effects of numerous QTL.

Generally, each QTL is thought to contribute to only a small portion of the total variation in the trait (Tanksley, 1993). Moreover, this contribution may be altered by changes in the environment. As a result, trait values vary continuously and often are distributed normally. Methods for mapping QTL have been developed using qualitative molecular markers, such as RFLPs and SSRs, to which QTL may be linked (Lander and Botstein, 1989; for review, see Paterson, 1996).

Recombinant inbred populations (comprised of fully inbred descendants of F2 segregants derived from inbred lines) can facilitate the QTL mapping process and have been used in both animal and plant systems (Takahashi et al., 1994). As a result of segregation and recombination, unique genetic combinations of alleles are produced during formation of the RI population, each line of which is a different genetic mosaic derived from the two parents. Through this process of combining new alleles, segregants with much higher and lower trait values than their parents may be produced (transgressive segregation). Although this approach has been recognized as having great potential for determining the genetic basis for plant resistance to insects (Smith, 1989; Khush and Brar, 1991), few studies have involved such a systematic approach.

Recently, molecular markers associated with insect resistance in tomato [L. pennelli (Corr.)], wheat (Triticum aestivum L.), rice (Oryza sativa L.), corn (Zea mays L.), and potato [Solanum tuberosum (L.) and S. berthaultii Hawkes] have been found (Nienhuis et al., 1987; Schön et al., 1993; Bonierbale et al., 1994; Ishii et al., 1994; Nieto-Lopez and Blake, 1994; Maliepaard et al., 1995; Byrne et al., 1996; Mutschler et al., 1996; Nair et al., 1996; Yencho et al., 1996; Dweikat et al., 1997). These studies examined specific plant crosses to determine QTLs affecting aspects of plant chemistry, such as maysin in corn and acyl sugars in tomato, or aspects of plant morphology (trichomes), traits already known to affect resistance to insects.

The majority of resistance studies to insects in soybean, Glycine max (L.) Merr., has stemmed from a discovery of three cultivars resistant to Mexican bean beetle (Epilachna varivestis Mulsant) (PI 171451, 229358, and 227687) (Van Duyn et al., 1971, 1972; Khush and Brar, 1991). Early efforts demonstrated that the resistance involved both antixenosis (nonpreference) and antibiosis (adverse effects on insect growth and development) to numerous insect pests of soybean. Later studies demonstrated the existence in these lines of numerous potential inducible and/or constitutive plant products that might be associated with resistance (Binder and Waiss, 1984; Smith, 1985; Lin and Kogan, 1990; Lin et al., 1990; Wheeler and Slansky, 1991; Liu et al., 1992). Despite efforts to understand the specific resistance traits of these lines, little is known about the genetic basis for their overall resistance or specific resistance traits. Breeding experiments to determine the number of genes, the heritability of the resistance, and the effects of the environment have produced mixed results (Khush and Brar, 1991). Rufener et al. (1989) concluded that despite the evidence for a low number of genes (or even only one) involved in soybean resistance to Mexican bean beetle, progress in breeding with PI 171451 and PI 229358 would be best obtained by treating the resistance as a quantitative trait. In their study, there were no easily identifiable markers that could be associated with the resistance, making breeding for resistance difficult and inefficient.

A soybean RI population has been developed for genetic mapping purposes from the relatively susceptible but genetically unrelated parents, Noir 1 from Hungary and Minsoy from China. This population varied in resistance and susceptibility to two insect species beyond the range of the nonresistant parental phenotypes (Terry et al., 1999). For the corn earworm, the average larval weight at 12 d reared on the most susceptible RI was more than five times that of the most resistant RI line. Pupal weight, developmental rates, survival, and nutritional indices also differed between the RI lines. The parents were intermediate in their effect on larval performance. Within this population were RI lines comparable in resistance to the resistant PI lines studied by Van Duyn et al. (1971, 1972). Evidence for independent molecular markers associated with insect resistance were presented and QTLs were identified for larval weight, pupal weight, survival, and nutritional indices (Terry et al., 1999).

The objectives of this study were to complete a detailed study of the MN RI population QTLs associated with larval development, including the amount of heritable variation that the QTL determine, and to confirm these QTLs in another RI population that comprises a different genetic background.


   Materials and methods
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
Results and discussion
 REFERENCES
 
Recombinant Inbred Soybean Populations
The RI soybean populations and the genetic marker data have been described previously (Mansur and Orf, 1995; Mansur et al., 1996; Orf et al., 1999). In brief, 240 RI lines were derived using a single-seed descent from F2 segregants produced on reciprocal crosses of Noir 1 (PI 290136) and Minsoy (PI 27890) (MN population). We used F13 or F14 generation seed stock from the MN population for the bioassay experiments. A new RI population was derived from reciprocal crosses of the parents, Archer (an elite cultivar) and Minsoy (MA RI population), using similar methods (Orf et al., 1999). The MA population has been advanced to the F10 generation and has 233 RI segregants. We used F10 generation seed stock from the MA population for the bioassay experiments.

Genetic markers for mapping within the RI population consisted of 150 RFLPs, 238 SSRs, and two of the soybean classical morphological markers. Procedures for developing these markers have been detailed previously (Apuya et al., 1988; Keim and Shoemaker, 1988; Akkaya et al., 1992, 1995; Lark et al., 1993; Cregan et al., 1994a, 1994b; Mansur et al., 1996). Minsoy and Noir 1 were screened for RFLPs. Polymorphic probes were then hybridized against Southern blots of restriction fragments of DNA from RI lines. Primer sequences of polymorphic SSR loci have been presented elsewhere (Mansur et al., 1996; Cregan et al., 1999). From the genetic marker data set, a composite genetic map of the RI populations (the two RI described above as well as a population derived from a cross of Noir 1 x Archer) was prepared (Cregan et al., 1999; Orf et al., 1999). Linkage of loci and mapped distances were determined using two programs, Mapmaker 3.0 (Lander et al., 1987; Lincoln and Lander, 1993) and Join-Map (Stam, 1993) as reported by Cregan et al. (1999). The RFLP markers were developed during the F9 generation. Heterozygous lines were eliminated from the QTL analysis. No distorted segregation ratios were observed for alleles of any RFLP or SSR marker in either RI population.

Herbivore Bioassays
The corn earworm, a polyphagous New World foliage and fruit feeding species and a major pest of soybean (Fitt, 1989; McPherson and Moss, 1989), was used as the test herbivore in the study. Eggs were obtained from the USDA-ARS Insect Biology and Population Management Research Laboratory in Tifton, GA. Eggs were held at 15°C until 1 d before test initiation and were then transferred to 27°C until hatching. Details of the bioassay method have been described previously (Terry et al., 1999). In summary, larvae were reared on excised leaf tissue from greenhouse-grown RI plants to determine relative effects of each RI on larval development. Larvae were reared two per cup in 400-mL plastic cups until Day 3 of development. After Day 3, larvae were reared individually in cups to prevent cannibalism. Each larva was reared on only a single RI line throughout development. Leaves were changed at least every 48 h.

Because of time and space constraints, only 18 to 24 RI lines were tested in a single experiment, with 10 larvae tested per line in each experiment. The number of lines tested in each experiment depended on whether parents were included in the set of randomly selected 20 RI, and whether some lines failed to germinate or grow adequately in one set (some sets as low as 18). Lines not growing in one set were added to another set of lines (up to 24 lines). At least two experiments were performed on each set of RI lines. Many sets were repeated up to four times, with the last two repeats occurring during a different season from the first two. This amount of repetition would minimize problems associated with seasonal variation in greenhouse plant growth, which could affect larval development.

Data recorded were larval weight at 8, 10 and 12 d; pupal weight at 24 h after pupation; number of days to reach prepupal and pupal stage transformed to development rate (1/number of days) to linearize the relationship; survival percentage to Day 12 of larval growth, to the prepupal period, and to the pupal stage. All 240 of the MN RI and 228 of the 233 MA RI have been tested. Resistant and susceptible RI controls from the MN population were included in each experiment. Across all tests and both RI populations, the larval weight of the resistant control was highly correlated with values of the average for RIs of each test ( , P < 0.0001) and with the susceptible standard ( , P < 0.001), and correlations between the susceptible control and the average larval weight values of RI in each test were high ( ), suggesting relative homogeneity of the results among tests. In addition, 104 RI lines of the MN population were also tested on another H. zea culture from the North Carolina State University Rearing Facility. Similar resistance rankings were observed among the repeated lines, especially of the standards used (Terry et al., 1999), which indicates consistency in the estimation of resistance.

Determination of Linkage of Traits to Genetic Markers and Statistical Analyses
Normalized trait values were used to identify plant QTLs. Although plant stage and bioassay conditions were similar across all experiments, average larval weights at 12 d after hatch and developmental rates varied from test to test, possibly due to variations in plant growth and greenhouse conditions across seasons. Therefore, trait values within each test were standardized by normalizing the data within each test; for example, normalized larval weight = (larval weight - average larval weight for test)/each test's weight standard deviation. These adjusted trait values are correlated with their respective trait's unadjusted data ( , P < 0.0001). This normalization procedure would minimize effects of environmental variation.

Transgressive segregation for each trait within each RI population was determined by calculating whether the number of RI outside the combined parental 95% confidence limits for each trait exceeded the number predicted by chance (P < 0.05, binomial distribution).

We used the simple interval mapping feature of the computer package PLABQTL (Utz and Melchinger, 1996) for detecting QTL. This program uses a multiple regression approach to interval mapping with marker order and distances determined by Mapmaker. We established empirical log of the odds (LOD) thresholds for QTL detection using permutation tests (Churchill and Doerge, 1994). A LOD of >=3.8 has an experiment-wise significance of P <= 0.05. The PLABQTL program was used to perform a simultaneous fit of all QTL detected above a threshold of 2.5. We report all QTL detected above a threshold LOD of 2.5. However, where LOD score peaks are broad across linked markers, it is difficult to exactly locate QTLs in these intervals (see discussion by Liu, 1998), and more fine scale mapping is needed to determine if there is one or more QTL and their locations. The total amount of variation explained by the simultaneous fit of all significant QTLs and that due to each parent was calculated from the partial sums of squares using the PLABQTL program. In our data, significant loci on the same linkage group were considered as separate QTL if they were >50 centimorgans (cM) apart, if markers between had significantly lower LOD scores and probability values (Mansur et al., 1996), if they affect different traits, or if the parental origin of the resistant allele reversed from one marker to the other.

Direct effects of each QTL identified by interval mapping were determined using EPISTAT (Chase et al., 1997), a program that uses Maximum Likelihood models to determine the effect associated with a marker (QTL) as opposed to its occurrence by random chance (null model). The individual effects of each QTL are reported as r2 values, and the parental allele associated with resistance is indicated. Monte Carlo simulations (1 million runs each) were used to calculate the probability of the direct effect of each marker.

Lines within a set of tests were selected randomly. We found close to 1:1 segregation of alleles in almost all sets of tests in each population for the significant QTL, thereby minimizing the potential for false positive identification of QTLs because of segregation ratio distortion.

Analyses of variance (GLM models; SAS Institute, 1988) were used to obtain genetic and error variance components to calculate the broad sense heritability estimates (Burton and DeVane, 1953). The genetic and error variance components for each population were obtained from the pooled sums of squares for genotype and for error across all sets of RI lines divided by their respective pooled degrees of freedom.


   Results and discussion
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
REFERENCES
 
The values for the two RI populations reflect the differences in trait values between parents, Archer being a better corn earworm host than Noir 1 (Table 1) . In both populations the larval weight segregated in a transgressive manner (P < 10-4) as did the pupal weight in the MN population (P < 10-6). For example, 26 lines in the MA and 27 lines in the MN were outside the 95% confidence limits set for larval weight by the values of the parental lines.


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  		Table 1 Means, standard errors, and ranges of the corn earworm larval developmental traits measured when reared on the two recombinant inbred soybean populations, Minsoy x Noir 1 or Minsoy x Archer

 
Previous results had indicated that significant QTLs detected in the MN population were associated primarily with LGs U2 and U10 (Terry et al., 1999) of the 20 LGs of the composite soybean map (Cregan et al., 1999). The cumulative distributions of larval weights associated with parental alleles of loci on these linkage groups show the degree of difference between larval weights associated with each allele (Fig. 1) . Evidence for a QTL associated with LG U2 is found in both populations (Fig. 1A and 1C) confirming this QTL. In contrast, our data identified a QTL in LG U10 in the MN population (Fig. 1B) but not in the MA population (Fig. 1D).



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  		Fig. 1 Segregation of QTLs associated with larval weight at Day 12 of development as shown by the cumulative frequency distribution of recombinant inbred (RI) values; subpopulations correspond with alleles at (A) Sat_112 or (C) Satt575 on Linkage Group U2 or at (B and D) Satt302 on Linkage Group U10. Data for the Minsoy x Noir 1 population are presented in (A) and (B) and for the Minsoy x Archer population in (C) and (D). Parental values are indicated

 
Not all of the molecular markers segregated in both the MN and MA populations (Fig. 2) . Where markers segregated, it was possible to test for segregation of linked QTLs. In LG U2 markers segregated in both populations and QTLs also were shown to segregate in both populations (Fig. 1 and 3 , Table 2) . In LG U10, Satt302 segregated in both populations (Fig. 2), but a QTL linked to this marker only segregated in the MN population (Fig. 1 and 3, Table 2). Several other QTLs were identified in either the MN or MA populations (Fig. 3, Table 2). Many of these were linked to markers that segregated in both populations. In these cases, it was possible to determine that a QTL segregating in one population was not segregating in the other. Thus a QTL for survival identified on LG U8 in the MN population (linked to Satt507) did not segregate in the MA population (Fig. 3, Table 2). Similarly, a QTL associated with Satt365 in LG U9 in the MA population did not segregate in the MN population, nor did QTLs found in LG U11 linked to Satt567. In other cases, QTLs linked to segregating markers in one population could not be tested for linkage in the other, because segregating markers were not available. This was the case for QTLs linked to R013_2 in LG U8 and to Satt353 in LG U10 (Fig. 3, Table 2).



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  		Fig. 2 Composite Minsoy x Noir1 cross (MN) and Minsoy x Archer cross (MA) genetic maps of the relevant portions of the linkage groups with significant quantitative trait loci for corn earworm larval development traits. The symbols to the left of the marker names indicate the mapping populations in which the marker segregated (i.e., was polymorphic). The number to the right of the marker names indicates the map distance to the next marker (in centimorgans). Markers listed in Table 2 are indicated in bold. Linkage groups are labeled with both the Utah names and, in parentheses, the Iowa names (e.g., J)

 

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  		Table 2 Listing of all quantitative trait loci (QTLs) associated with corn earworm larval development detected with a log of the odds (LOD) > 2.5. The QTLs are grouped by recombinant inbred (RI) population, either Minsoy x Noir 1 or Minsoy x Archer. Within each population, each QTL is characterized by the most significant linked marker, the linkage group on which it is located, the P value associated with the linkage, the amount of variation explained by the QTL (R2), and which allele is associated with resistance to larval development

 


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  		Fig. 3 Simple interval mapping of log of the odds (LOD) scores associated with corn earworm larval development traits for Linkage Groups U2, U8, U9, U10, and U11 in both recombinant inbred populations. Linkage groups are drawn to scale. The linkage group position (x-axis) is graphed against the LOD score (y-axis) for each population. A threshold line for significant quantitative trait loci (QTL) at a LOD score of 2.5 is presented. The first column of graphs represents the linkage groups with significant QTLs in the Minsoy x Noir1 cross (MN) population only; the second column, those with significance in both RI populations; and the third, those with significance in the Minsoy x Archer cross (MA) population only. Markers are labeled along the x-axis of each linkage group and correspond with the markers and distances listed in Fig. 2

 
Most of the resistance alleles are derived from the Minsoy parent (Table 2). These include resistance alleles associated with LGs U2 and U10, as well as one for pupal weight on LG U11. The tests lack enough sensitivity to determine conclusively if the QTLs on LG U10 are separate, but based on the point mapping P values of individual markers (Table 2) we have chosen to fit three QTL to the region. One of these (linked to Satt353) primarily affects larval weight, and 42.7 cM distance away is another (linked to Satt192) that affects larval weight, pupal weight, and development rate. A third QTL (linked to Satt302) primarily affects larval weight and development rate, but not pupal weight.

The most important QTL is found on LG U2. It is observed in both populations, accounts for the largest fraction of phenotypic variation, and affects three traits: larval weight, pupal weight, and development rate (Table 2). This QTL, linked to Satt575 and Sat_112, was first detected in the MN RI population. It was confirmed in a different genetic background (the MA RI population) derived from the elite soybean cultivar, Archer. Because Minsoy is a somewhat exotic PI, it seems unlikely that this resistance allele is present in most of the elite germplasm currently in use. Because the allele remains active when crossed with Archer, it is likely that the resistance will not be lost if introgressed into other elite germplasm. These results have a direct application in developing insect resistant germplasm. QTLs for many agronomic traits have been identified and mapped in these RI soybean populations (Mansur et al., 1996; Orf et al., 1999). As yet, no important agronomic QTL has been found that is linked to the major resistance QTL on LG U2. This information will be useful in planning breeding strategies to minimize the effects on important agricultural traits while gaining resistance. It also suggests that the direct cost of resistance to the plant in terms of yield, or other traits, may be minor.

Some minor resistance alleles, derived from the Noir 1 parent, are found on LGs U1, U8, and U12 (Table 2). The most important of these are two for survival located on LG U8 and separated by more than 25 cM from each other (Fig. 2, Table 2). No resistance alleles were detected from the Archer parent. However, the fact that many MA RI segregants are more resistant than the Minsoy parent (Fig. 1) suggests that additional resistance genes derived from Archer may exist.

Quantitative traits are traditionally viewed as being controlled by a large number of loci each with a small effect (r2 <= 0.05) that in the aggregate affect the phenotype (Tanksley, 1993). However, many of the QTLs directly associated with the variation in insect growth and development are not minor (Table 2). In the MN RI population, the largest of these, linked to SAT_112 on LG U2, accounts for 17% of the variation in larval weight and 12% of the developmental rate. In the MA RI population the QTL on LG U2 accounts for 28 and 29% of the variation in the developmental rate and the larval weight. Moreover, in the MN population there were several other QTL associated with resistance traits, each accounting for more than 5% of the total variation. However, where multiple QTL are associated with a trait, the sum of the individual QTL effects may not be additive. The VQTL (R2), determined through multiple regression models, adjusts for multicolinearity among QTLs and gives a measure of the total percentage of the variation explained by all the QTL. In most traits (Table 3) , the total VQTL is similar to the sum of the individual QTL effects in Table 2.


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  		Table 3 Summary statistics for the analysis of corn earworm larval development traits in the recombinant inbred (RI) populations. For each trait within each RI population, the heritability (H2); the percentage of variation (VQTL) explained by all the quantitative trait loci (QTL) in total and that due to either Minsoy, Archer, or Noir (R2); the number of QTL detected with log of the odds (LOD) > 4.0; and the number of QTL explaining >10% of the variation (QTL with R2 > 10%) are listed. For specific distances and ordering of markers see Fig. 2

 
The broad sense heritability values are moderate (range of 42–65) (Table 3) and suggest that the expected gain due to selection would be moderate. Except for pupal weight, the heritabilities between the populations are similar. In the MA population most of the variation in larval and development rate is associated with the LG U2 locus while several loci contribute to the variation in the MN population, but the U2 QTL is the only major locus (r2 > 0.10, Table 2 and 3) in either population. These data further support the conclusion that the resistance associated with the Minsoy allele of QTL on LG U2 is of primary importance. In addition, the other MN QTL alleles may prove useful to breeders when placed in the context of elite genetic backgrounds other than Archer, as may the survival QTL alleles (LG U8) derived from the Noir 1 parent.

Resistance modalities to herbivores are broadly grouped into one of the following categories: antibiosis, antixenosis, or tolerance of the pest. Our bioassays tested for antibiosis factors, demonstrating that the resistance gene on LG U2 affected both larval weight gain and development rates (Table 2, Fig. 1 and 3). However, we also have evidence that the most resistant lines are less preferred (Terry, 1996, unpublished data), which may increase the rate of larval spin-down from the plant. While these effects may seem inadequate for pest control in production agriculture, germplasm with these traits may be more durable than those that produce high mortality. In addition, these traits may promote the effectiveness of biological controls (Kogan, 1982; Isenhour et al., 1989; Johnson and Gould, 1992). The durability of a particular resistant germplasm depends on a number of interacting factors, primarily the pest species' biology and host range, the selection intensity on the pest by the resistance factors, and the cropping system (Kennedy et al., 1987). In addition, the deployment strategy is important (pyramiding genes; sequential release of different resistant germplasm, mixing susceptible and resistant seed) (Gould, 1986a, 1986b, 1988, 1998). Those strategies or traits, which impose the greater selection pressure (e.g., a high rate of mortality on a monophagous pest), generally have a shorter effective period across many pest generations. Clearly, the effectiveness of these traits requires thorough pest control evaluation under field conditions as a prerequisite to their further development into breeding stock. Because the most resistant lines also appear to be resistant to other pests (Terry et al., 1999), field studies should be conducted in different regions where each pest is a problem.


   ACKNOWLEDGMENTS
 
We thank Danielle Bodrero, Tristan Lam, Tom Leitner, and Lori Stutz for their assistance in the laboratory bioassays. This research was supported by the NRI Competitve Grants Program, USDA award 96-35302-3638.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
 REFERENCES
 
Work in part supported by USDA NRI competitve grants program.

Received for publication January 4, 1999.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 Materials and methods
 Results and discussion
 REFERENCES
 




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