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a Dep. of Plant Agriculture, Crop Science Division, Univ. of Guelph, Guelph, ON, Canada N1G 2W1
b Agric. and Agri-Food Canada, 2585 Highway 20 East, Harrow, ON, Canada N0R 1G0
c Ridgetown College, Univ. of Guelph, Ridgetown, ON, Canada N0P 2C0
d Guelph Center for Functional Foods, Lab. Services Division, Univ. of Guelph, 95 Stone Road West, Guelph, ON, Canada N1H 8J7
* Corresponding author (irajcan{at}uoguelph.ca)
| ABSTRACT |
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Abbreviations: HPLC, high performance liquid chromatography NIR, near infra-red reflectance PDA, photodiode array RIL, recombinant inbred line SAS, statistical analysis software
| INTRODUCTION |
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Breeding soybean for desirable individual or total isoflavone content in the seed is difficult since isoflavone content is greatly influenced by the environment. Eldridge and Kwolek (1983) reported that total isoflavone content in soybean seed varied from 1160 to 3090 µg g1 among four soybean cultivars grown in the same environment and from 460 to 1950 µg g1 among four Illinois locations for the same cultivar. Wang and Murphy (1994) planted Vinton 81 over 3 yr at three locations and reported year to have a greater influence on isoflavone content than location. Carrao-Panizzi and Kitamura (1995) tested 22 soybean cultivars at one location in Brazil over 2 yr and attributed the significant differences in total isoflavone content to differences between years in temperature, precipitation and harvest date. Total isoflavone content ranged from 1900 to 3700 µg g1 for the 100 RILs of the Essex x Forrest population (Njiti et al., 1999; Meksem et al., 2001; Kassem et al., 2004); however, the authors did not note year effect. Hoeck et al. (2000) tested six soybean cultivars at eight Iowa locations over 2 yr and Lee et al. (2002) planted 15 cultivars at three sites in Korea over 3 yr. In these two studies, genotype, genotype x year, genotype x location, and genotype x year x location interactions were significant for both total and individual isoflavone concentrations.
Several factors have been shown to contribute to environmental effects. Kitamura et al. (1991) observed that high temperatures during the pod filling period significantly decreased isoflavone concentrations in soybean seeds. Tsukamoto et al. (1995) also observed similar effects on soybean plants grown in temperature controlled growth chambers. Vyn et al. (2002) showed that both individual and total isoflavones were positively correlated with leaf and seed K concentrations on low-K soils.
The relationship between isoflavone content and agronomic characteristics is important to breeders. Currently, there is little information on the relationships among these traits. Wang et al. (2000) found that daidzein and genistein content were negatively correlated with yield, days to maturity, and plant height, while total isoflavone content was positively correlated with yield (r = 0.20) among 210 soybean cultivars with a wide genetic range. In contrast, the current study used RIL populations segregating for isoflavone content in an attempt to control background effects. Recently, a mapping study has shown that a QTL for glycitein was closely associated with three seed storage protein genes (Kassem et al., 2004). Furthermore, the mapping population (Essex x Forrest) did not segregate for maturity (less than 7 d) and yet agronomic (yield, height, and lodging) and isoflavone QTLs were correlated (Meksem et al., 2001; Kassem et al., 2004).
The main objective of this study was to determine if isoflavone content was associated with agronomic and seed quality traits in three different RIL populations.
| MATERIALS AND METHODS |
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Agronomic Data Collection
The following agronomic traits were measured on all plots at each location: seed yield, days to maturity, lodging, and plant height. Seed quality, seed weight, oil content and protein content were measured on an entry mean basis at each location by bulking approximately 150 g of seed from each plot. Seed yield was converted to kg ha1 adjusted to 130 g kg1 moisture. Maturity (R8), was recorded when 95% of the pods matured (Fehr et al., 1977). Lodging was scored from 1 (all plants in a plot erect) to 5 (all plants in a plot prostrate). Plant height was estimated as the distance from the soil surface to the tip of the main stem of a representative plant at maturity. Seed size was recorded as the weight of 100 random seeds from a bulk at each location. Seed quality was rated from 1 (seed surface smooth with no evidence of shriveling; disease-free) to 5 (seed very shriveled, cracked seeds, discoloration, evidence of disease). Approximately 300 g of seed, at seed moisture, was used to measure oil and protein contents using near-infrared reflectance (NIR) on a GrainSpec B1126 from FOSS North America Incorporated (Brampton, ON).
Isoflavone Extraction and HPLC Analysis
The soybean seed samples from 2000 were analyzed for isoflavone content on a single plant basis. The samples (about 4 g) were ground in a coffee grinder and sent to University of Guelph Laboratory Services (Guelph, ON) for daidzein, genistein, glycitein, and total isoflavone analysis. Isoflavone concentrations were determined by HPLC as described by Vyn et al. (2002).
Isoflavone analyses of seed samples harvested in 2002 were performed by an alternate, less expensive method developed by Akhtar and Bryan (2002). Briefly, 10 g of soybean seeds from each plot were finely ground in a coffee grinder, with 5 g used for dry matter determination and two grams used for isoflavone extraction. The 2-g samples were mixed with 20 mL of HPLC grade acetonitrile and 4 mL of 0.1 M HCl in a 40-mL screw cap vial. The solutions were heated for 2 h at 60°C in a water bath, and the vials were shaken every 30 min. After cooling, 1 mL aliquots were centrifuged at 21150 x g for 5 min and 100 µL of supernatant and 2 mL of 3N HCl were mixed in a 7-mL glass screw cap vial. The samples were vortexed and hydrolyzed for 24 h at 60°C on a block heater, were allowed to cool, and 2 mL of ethyl ether was added, and the samples were again vortexed. The layers were allowed to separate; the upper ethyl ether layer was removed with a Pasteur pipette, passed through approximately 1 g of sodium sulfate (previously washed with 3 volumes of ethyl ether), and collected in a glass vial. Samples were partitioned with ethyl ether a total of five times, twice with 2 mL and three times with 1 mL. The samples were dried under a gentle stream of nitrogen gas to evaporate the combined ether layers. The dried samples were dissolved in 1 mL of 25% (v/v) acetonitrile, vortexed, and filtered through a 0.45-µm Nylon Cameo 3N syringe filter before HPLC analysis. The Na2SO4 columns were made from 5 3/4 Pasteur pipettes with glass wool used as a plug and approximately 1 g of Na2SO4 used as the column material.
Concentrations of daidzein, genistein, and glycitein were determined by HPLC. The following HPLC apparatus and conditions were used: HPLC, Agilent 1100 binary delivery system from Agilent Technologies Limited (Mississauga, ON) with an auto sampler and a photodiode array (PDA) detector set to collect spectra from 200 to 300 nm; HPLC column, Phenomenex Primesphere C18-HC column (250 x 4.6 mm; 5, 10,15-µm particle size) equipped with a guard cartridge holder (4.0 x 3.0 mm); flow rate, 0.8 mL min1; and injection volume, 20 µL. HPLC mobile phases were solvent A (10% v/v ACN) and solvent B (38% v/v ACN), and the solvent system was as follows (% solvent A/% solvent B): 0 min (0/100), 5 min (10/90), 20 min (0/100), and 25 min (0/100).
Daidzein, glycitein, and genistein peaks on sample chromatographs were confirmed with standards (Sigma Chemical Company, St. Louis, MO). The Hewlett-Packard software associated with the Agilent HPLC instrument was used to calculate peak areas for each isoflavone. Linear calibration curves were generated for each isoflavone by plotting five known concentrations as a function of peak area. High linearity (R > 0.99) was obtained for each curve. The concentration of each isoflavone (µg per g of sample) was calculated by means of the calibration curves, peak area, sample weight, and dilution factors.
Statistical Analysis
The SAS procedure PROC MIXED (SAS 8.02, SAS Institute Inc., 2001) was used to conduct an analysis of variance for individual and total isoflavone content. Phenotypic class, population, environment, and their interaction were considered fixed effects, and rep(environment) and block(rep) were considered random effects. The class, population and environment means of individual and total isoflavones was calculated by the SAS statement LSMEANS. Comparison of the means for daidzein, glycitein, genistein, and all agronomic and seed quality traits between high, intermediate and low isoflavone phenotypic classes were made by contrasts.
| RESULTS |
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Population, Environment, and Phenotypic Class Analysis of Isoflavones
There were significant differences among population, environment, and their interaction for individual isoflavone content (Table 3). Population effects were not significant for total isoflavone content, but environment and population x environment interaction were significant. Daidzein, glycitein, and genistein content of Pop. 3 were significantly different from the other populations (Table 4). In general, the mean daidzein and glycitein content were significantly higher and the mean genistein content was significantly lower across RILs for Pop. 3. The mean total isoflavone content of Pop. 3 was higher than the other populations but not significantly different. The mean and range of individual and total isoflavone content for the three populations grown at three locations (Harrow, Ridgetown, and Woodstock, Ontario) in 2002 is presented in Table 5. In general, Ridgetown had the highest and Harrow had the lowest content of daidzein, genistein and total isoflavone for all three populations. A different trend was observed for glycitein. The highest and lowest glycitein contents were found to be in Harrow and Woodstock, respectively, for Pop. 2 and Pop. 3. For Pop. 1, Ridgetown and Harrow had the highest and lowest glycitein content, respectively.
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Results for genistein were similar to daidzein. Differences among the three phenotypic classes were significant for genistein in Pop. 1 and Pop. 2 (Table 7). As expected, high phenotypic classes had the highest and the low had the lowest genistein contents for these two populations. For Pop. 3, the high and intermediate phenotypic classes had genistein contents significantly higher than the low class; however, the difference between the high and intermediate classes was not significant.
There were significant differences among the three isoflavone phenotypic classes for the agronomic traits yield, maturity, plant height, and lodging. The significant differences were not consistent among the three populations (Table 7). Yield, maturity, and plant height differed significantly in Pop. 1 and Pop. 2. The high and intermediate phenotypic classes produced significantly more seed, matured significantly later, and were significantly taller than low phenotypic classes (Table 7). Furthermore, differences between high and intermediate classes in the two populations were not significant for these three traits. As in the two other populations, the high phenotypic class matured significantly later than the low phenotypic class for Pop. 3. However, the difference in maturity between the low and intermediate phenotypic classes was not significant for this population. In Pop. 1, lodging was significantly different among the three phenotypic classes. The high phenotypic class lodged the most and the low lodged the least. In Pop. 2, none of the tests were significant. Interestingly, the high and low classes were significantly different from the intermediate class but were not significantly different from each other in Pop. 3.
Contrasts for protein content, oil content, and seed quality for the three populations are given in Table 7. Differences in protein content, oil content, and seed quality for Pop. 2 and Pop. 3 were not significant for a large number of the contrasts. However, there were highly significant differences for Pop. 1. The high and intermediate phenotypic classes had significantly lower protein content and significantly better seed quality than low phenotypic classes (Table 7). Furthermore, differences between high and intermediate classes were not significant for these two traits. Seed weight differences among isoflavone phenotypic classes were not significant in any of the populations.
| DISCUSSION |
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Breeding soybean for high or low isoflavone content in the seed is challenging since isoflavone content is influenced by environment (Eldridge and Kwolek, 1983; Wang and Murphy, 1994; Carrao-Panizzi and Kitamura, 1995; Hoeck et al., 2000; Lee et al., 2002). In this study, the effects of environment on isoflavone content were also evident as there were significant differences among the three locations, Harrow, Ridgetown, and Woodstock, in 2002 (Table 3 and 5). Differences in isoflavone content among the three locations could have been partly attributed to differences in temperature and precipitation since soybean RILs grown in Harrow, a location that had higher temperatures and received the least amount of precipitation during the field season (Table 2) in comparison to Ridgetown and Woodstock, had the lowest concentrations of daidzein, genistein, and total isoflavone. The results supported the conclusion of Kitamura et al. (1991) and Tsukamoto et al. (1995) that high temperatures during the pod filling period significantly decreased isoflavone concentrations in soybean seeds. Environmental factors such as planting date, cultural practices, soil fertility (Vyn et al., 2002), or weed, disease, or insect pressure also could affect isoflavone content but these factors were not investigated in our study.
Although environment had a significant effect on total isoflavone content (Table 3 and 5), phenotypic classification of the RILs did not change significantly. In fact, total isoflavone phenotypic groups remained significantly different for each population (Table 6). It was also noted that very few of the RIL phenotypic classifications changed when the 2000 and 2002 isoflavone contents were compared (data not shown), confirming the validity of the second method of isoflavone analysis. Other studies have also shown relatively consistent ranking of soybean genotypes with different isoflavone content when tested in multiple environments. Lee et al. (2002) found that the genotype Geomjeong had consistently higher total isoflavone content across 3 yr and three locations. Eldridge and Kwolek (1983) found that Corsoy 79 had greater isoflavone contents than Hardin at each of four locations. Chiari et al. (2004) and Meksem et al. (2001) reported high heritability estimates for isoflavone content. Therefore, results from this study and previous research are encouraging to breeders because it should be possible to select soybean lines with relatively high or low isoflavone content in the seeds when tested in multiple environments.
The three main isoflavones found in soybean seed, genistein, daidzein, and glycitein, are generally in the concentration ratio 1:1:0.2 (Manach et al., 2004). Since daidzein and genistein account for a majority of the total isoflavone content, it was not unusual to find that contrasts among total isoflavone phenotypic classes for daidzein and genistein were significant in the three populations and that their relationships were linear. Glycitein, on the other hand, does not contribute very much to the total isoflavone content, which resulted in fewer significant contrasts. In fact, there were no significant contrasts among the three phenotypic classes for Pop. 3. This supported the findings of Primomo et al. (2005), who showed that QTL for total isoflavone mapped to similar regions as daidzein and genistein but not glycitein. The results suggested that one could simultaneously breed soybean lines for daidzein and genistein but not for glycitein when breeding for total isoflavone content.
Information on agronomic performance of soybean cultivars with diverse isoflavone content is limited. Wang et al. (2000) reported no significant association between total isoflavone content in soybean seeds and days to maturity or plant height, but they did find a weak, positive correlation with seed yield. There may be two possible reasons for the different results obtained between the two studies. First, RIL populations, lines similar by descent, were used in our study, whereas Wang et al. (2000) used 210 assumedly unrelated soybean cultivars. Second, our study analyzed soybean seeds for the three main aglycones (i.e., daidzein, genistein, and glycitein), whereas Wang et al. (2000) analyzed them for the 12 isoflavone components, the aglycones, and their corresponding glucosides.
In general, soybean cultivars late in maturity have higher yields, are taller, and lodge more than early maturing cultivars. In this study, high and low phenotypic classes were significantly different for maturity in all three populations (Table 7). Hence, it was not surprising to find that the high phenotypic class produced more seeds, were taller, and lodged more than the low in Pop. 1 and Pop. 2. Interestingly, the differences in maturity between the two groups were 10 and 3 d for Pop. 1 and Pop. 2, respectively. Clearly, isoflavone content had a positive effect on agronomic traits. Even though Pop. 2 had very limited segregation in maturity, it was possible to develop individual RILs with high seed yields and desirable isoflavone content. RILs with the highest and lowest total isoflavone content contained 2030 and 970 µg g1 and had seed yields of 4475 and 4222 kg ha1, respectively, when averaged across the three environments (data not shown). Our results support a mapping study that showed a QTL for daidzein content was closely linked to a seed yield QTL in the mapping population Essex x Forrest (Meksem et al., 2001).
Significant differences among the three phenotypic classes were detected for seed quality, oil content, and protein content (Table 7). The lack of a consistent trend, in addition to the minimal differences between the phenotypic classes, suggested that isoflavone content in the seed likely does not have an effect on seed quality and oil content. It was apparent that isoflavone content did not have an effect on seed weight because phenotypic classes were not significantly different for any of the three populations.
In a recent genetic study, Chiari et al. (2004) reported a negative correlation between isoflavone and protein content, ranging from 0.51 to 0.37. In our study, the negative relationship reported by Chiari et al. (2004) was also observed in Pop. 1; however, it was not evident in Pop. 2 and Pop. 3. Two RILs with high isoflavone content, 1851 and 1746 µg g1, also contained high protein content, 431 and 442 g kg1, respectively. This is very encouraging to breeders, because it suggests that high soybean protein is compatible with high isoflavone content, which could be advantageous for the functional soy food industry.
The negative correlation between isoflavone and protein content may be attributed to the result of gene linkage, pleiotropy, or environmental conditions during seed maturation. Recently, two independent mapping studies using different genetic material (Kassem et al., 2004; Primomo et al., 2005) showed that QTL for glycitein and protein content map to common regions of the soybean genome, supporting the hypothesis of genetic linkage.
In conclusion, this study has provided an evaluation of the agronomic performance and seed quality of RILs segregating for isoflavone content in soybean seeds. Our results have indicated that it was possible to develop RILs with high yields and low isoflavone content, despite earlier reports that later maturing cultivars had higher isoflavone content. Similarly, it was possible to develop RILs with high isoflavone and high protein content despite earlier reports of a negative correlation between these two traits. Using traditional breeding methods to select soybean with desirable isoflavone content in the seed requires testing in multiple environments because of the substantial environmental variation for this trait. In addition, applying early selection when breeding for isoflavone content in soybean seeds might not be practical since isoflavone analysis of each RIL could be very expensive. Thus, the use of marker-assisted selection is advantageous in the design of an efficient and cost-effective breeding strategy for developing soybean cultivars with desirable isoflavone content in the seed. Despite a very limited range of maturity in Pop. 2 and Pop. 3, high, intermediate, and low isoflavone RILs were identified with no significant difference for yield, height, and lodging. Clearly, these two populations would be superior for mapping isoflavone and agronomic traits because the maturity effect is removed.
| ACKNOWLEDGMENTS |
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| NOTES |
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Received for publication October 19, 2004.
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