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GENOMICS, MOLECULAR GENETICS & BIOTECHNOLOGY

Genetic Analysis of Quantitative Trait Loci for Groat Protein and Oil Content in Oat

^a Center for Applied Genetic Technologies, the University of Georgia, Athens, GA 30602, USA
^b Crop Development Centre, University of Saskatchewan, Saskatoon, SK S7N 5A8, Canada
^c Department of Agronomy, University of Wisconsin, Madison, WI 53706, USA

^* Corresponding author (hfkaeppl{at}wisc.edu).

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Groat protein and oil content are major quality traits in oat (Avena sativa L.). Information regarding the number, genomic location, and effect of quantitative trait loci (QTL) for protein and oil content, and epistasis between these QTL would facilitate the development of oat cultivars with desirable levels of the two traits. QTL for protein and oil content were mapped and characterized in an oat population consisting of 152 recombinant inbred lines from the cross of ‘Ogle’ (low)/MAM17-5 (high). Groat protein and oil were measured for samples harvested from field hill plots across two years. Composite interval mapping was used for QTL analysis with a framework map consisting of 272 molecular markers. Seventeen and six regions were identified significantly (LOD score threshold of 3.5) associated with protein and oil, respectively. Significant additive x additive gene interactions were detected for both protein and oil. In particular, the interactions between nonparental alleles played an important role in conferring high oil for most progeny of the cross. The final models best for single years, due to either the main effect or the interaction, explained 29 to 42% and 42 to 52% of the total phenotypic variation for protein and oil content, respectively. The QTL on OM6 and OM19 for protein and the QTL on OM3 and OM6 for oil, which were consistently identified, could serve as starting points for more intense scrutiny of genomic regions controlling groat protein or oil content in oat.

Abbreviations: AACC, American Association of Cereal Chemist(s) • AFLP, amplified fragment length polymorphism • CIM, composite interval mapping • KO, Kanota/Ogle • LOD, log likelihood of odds • OM, Ogle/MAM17-5 • QTL, quantitative trait locus/loci • RFLP, restriction fragment length polymorphism • RIL, recombinant inbred line • SSR, simple sequence repeat

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
GROAT PROTEIN AND OIL CONTENT are major quality traits in oat. Oat protein has a well-balanced amino acid profile, which varies little with an increase in groat protein content (Robbins et al., 1971). High-protein oat is valuable as both a livestock feed and a raw material for the food industry. Whole oat grain is low in energy when used as a feed because of its high fiber content. An increase in groat oil content is desirable for making oat a high-energy feed. On the other hand, a decrease in oil content would make oat more attractive to food processors since low oil content could reduce rancidity problems (Youngs, 1986). Genetic manipulation of the two traits would, thus, benefit both the food and the feed markets.

Classical studies of groat protein and oil content have been largely limited to estimates of heritability, gene action, and correlation. Additive effects and additive x additive interactions were significant for protein content; however, dominance was not important (Campbell and Frey, 1972; Iwig and Ohm, 1978). Broad sense heritabilities for protein content in various studies ranged from 0.09 to 0.90, with an overall average of about 0.41 (Campbell and Frey, 1972; Frey, 1975). Gene action in determining oil content was primarily additive, and neither dominance nor epistasis was important (Thro and Frey, 1985). Heritabilities were generally high, ranging from 0.63 to 0.93 and averaging approximately 0.73 (Baker and McKenzie, 1972; Brown et al., 1974). Both negative and positive correlations have been reported between oil and protein content (Gullord, 1986; Youngs and Forsberg, 1979). To our knowledge, the number of genetic loci and the effect of individual loci have not been determined for groat oil content in oat until a recent mapping study (Kianian et al., 1999).

With QTL mapping, which is based on molecular marker technology, a variety of traits in a number of crops (Phillips and Vasil, 1994; Young, 1996; Zhu and Kaeppler, 2003b) have been studied, including groat oil content in oat (Kianian et al., 1999). Three genomic regions for oil content were identified in a population from the cross of ‘Kanota’/‘Ogle’ (KO), and three regions in a population from the cross of Kanota/‘Marion’ (Kianian et al., 1999); however, only one major QTL located on linkage group 11 (KO11) was consistently detected in both populations. Kianian et al. (1999) contended that the populations were chosen on the basis of having a common parent, Kanota, to provide a sense of "biological replication." Cultivated oat is a hexaploid and has three subgenomes. A linkage group is potentially similar to other two homeologous linkage groups in terms of marker composition. This would confound the comparison of QTL detected in two hexaploid oat populations. Detection of common QTL would be expected in two populations with a common parent, since the populations share at least one allele. QTL analysis for oil content in populations with Ogle or Marion as one of the parents would provide more opportunity to confirm the QTL detected.

With additive gene action, standard plant-breeding procedures, especially recurrent selection, would be useful to improve both groat protein and oil content (Campbell and Frey, 1972). However, low heritabilities and the difficulty in obtaining enough seed for protein and oil analysis have limited selection of individual plants in early generations, especially protein. Direct measurement by American Association of Cereal Chemist (AACC) methods (AACC, 2000) is not efficient for screening large numbers of genotypes. Moreover, the methods require the grinding of seed, and therefore the seed cannot be used for planting. Seed analyzed via whole-seed analyzers can be used for planting; however, the analyzers often require an amount of seed which cannot be obtained from a single plant. As an alternative, molecular markers are insensitive to environment and can be used in plant breeding to identify desirable recombinants among the progeny from a cross (Tanksley et al. 1989). Therefore, marker-assisted selection may provide an attractive approach for indirect selection of protein and oil content to speed the accumulation of favorable alleles in single oat lines.

Information concerning the number, position, and effect of QTL for groat protein and oil content, and epistasis between these QTL would facilitate the development of oat cultivars with desirable protein and oil levels. Mapping QTL for groat protein and oil content should also be useful to gain a better understanding of the organization of genes for the quality traits in the hexaploid oat genome. This study was conducted, therefore, to identify the number, linkage map position and effect of QTL, and QTL interactions associated with oat groat protein and oil content.

	MATERIALS AND METHODS

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Plant Materials
A mapping population of 152 F_5:6 recombinant inbred lines (RIL) developed using the single-seed descent method was derived from a cross of two hexaploid, cultivated oat genotypes, ‘Ogle’ and MAM17-5, with different groat protein content and oil content (Table 1). Ogle has low protein and oil, and was developed in the spring oat breeding program at the University of Illinois (Brown and Jedlinski, 1983). MAM17-5 has high protein, and is higher in oil than Ogle, and was selected in the spring oat breeding program at the University of Wisconsin-Madison (Moustafa et al., 1992).

DNA Markers and Linkage Map
Sources of restriction fragment length polymorphism (RFLP) clones, microsatellite, or simple sequence repeat (SSR) primers and amplified fragment length polymorphism (AFLP) primers were reported elsewhere (Zhu and Kaeppler 2003a). AFLP analysis was performed according to the protocol provided by the manufacturer (Gibco-BRL Life Technology, Inc., Gaithersburg, MD) with minor modifications (Zhu and Kaeppler, 2003a). SSR analysis was conducted according to Chin et al. (1996), except that separation and detection of the amplified products were conducted on polyacrylamide sequencing gels. RFLP analysis followed a standard protocol (Zhu and Kaeppler, 2003a). For QTL analysis, a framework linkage map with 272 molecular markers was developed from the most informative markers (Zhu, 2002), and the map was used in this study. The genetic distance in the map, however, was in the Haldane centimorgan units preferred by PlabQTL (Utz and Melchinger, 1996).

Groat Protein and Oil Concentrations
A random sample (10 g) of each of the RILs was taken from seeds grown in each of the two years. Similarly, eight samples for each of the two parents were randomly drawn from the parental hill plots, respectively. Groat protein and oil concentration were measured using a Tecator 1255 Food and Feed Analyzer (Foss North America, Eden Prairie, MN) on whole grains at the Crop Development Centre, University of Saskatchewan, Canada. The instrument was calibrated from a range of samples which varied widely for groat protein content as determined by the Micro-Kjedhal method (AACC, 2000), and for groat oil content as determined by the Soxtech method (AACC, 2000). Multiple readings were done for each of the RILs; however, only one stable reading was collected for each of the RILs in each year. Similarly, one reading was recorded on each of the eight samples for each of the two parents in each year.

Data Analysis
Statistical differences in groat protein and oil content between the two parents were examined by a t test (Steel and Torrie, 1980). Pearson correlation coefficients were calculated by the Correlation Procedure (Proc Corr) of SAS (SAS, 1990). Average of the 2-yr data was also used to perform QTL analysis since the RIL x year interaction could not have been examined in this study. The Computer program PlabQTL (Utz and Melchinger, 1996) was used for identification of QTL. To determine the critical log likelihood of odds (LOD) threshold, permutation tests were performed with 1000 random reshuffles of observations as recommended by Churchill and Doerge (1994). All regions with LOD > 3.5, corresponding to an experiment-wise error rate of 0.05 (a comparison-wise error of approximately 0.00016), from the QTL analysis were considered significant and included in the final model. Composite interval mapping (CIM) (Zeng, 1994) with the "cov SELECT" option was used for QTL detection. An "F-to-enter" value of 7.0 was used for the step-wise regression to preselect cofactors. The cov SELECT option uses all of the preselected markers as cofactors. The QTL position, given as centimorgans from the top of a linkage group, was determined when the LOD score reached its maximum. A support interval with a LOD fall-off of 1.0 was given for each QTL. QTL with an overlapping support interval are assumed to be the same QTL for the same trait. The additive effect of a QTL was calculated by PlabQTL as (mean of the homozygous MAM17-5 class- mean of the homozygous Ogle class)/2. Additive x additive epistasis was estimated by the "Model AA" command, which only estimates additive effect and additive x additive interaction. The phenotypic variance explained by the QTL model was estimated by the adjusted coefficient of determination , which accounts for the number of predictors in the final model. The phenotypic variance explained by an individual QTL or an individual QTL x QTL interaction (predictor) was calculated as R²_i = Partial R²_i x R²_adj/(sum of Partial R²_i with i = 1 to n), where n = total number of predictors in the final model, and Partial R²_i = partial coefficient of determination, estimated for the ith predictor.

	RESULTS

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Assessment of Groat Protein Content and Groat Oil Content
Significant differences in groat protein and oil concentration were revealed between the two parents, except for oil content in 2001 (Table 1). MAM17-5 consistently showed higher protein and oil than Ogle, suggesting that the two parents differ in genes controlling the two traits. Both groat protein and oil content for the RIL population displayed a relatively continuous, approximately normal distribution (Fig. 1). Transgressive segregation was observed for both traits, indicating both parents contribute alleles for high protein and high oil. The observation that more than 60% of the RILs had higher oil than the high oil parent suggests that, in addition to the main effect of additive gene action, epistasis might play an important role.

View larger version (47K): [in this window] [in a new window]   Fig. 1. Distributions of oat groat protein and oil content for 152 RILs derived from the cross of Ogle/MAM17-5. Values next to the x axis are the upper limit of each category.

QTL for Groat Protein Content
On the basis of CIM, where the LOD score exceeded the threshold of 3.5, 17 QTL significantly associated with groat protein content were identified in the mapping population (Table 2; Fig. 2). Five QTL associated with protein content were detected in 2000, nine in 2001, and nine in the 2-yr combined analysis. The 17 QTL were located on 13 linkage groups with two located on each of the linkage groups OM5, OM6, OM7, and OM14. The QTL on OM6, closely linked to e7m2-10, and the QTL on OM19, closely linked to ISU1146, were consistently identified in both years. Both parents contributed alleles for greater protein content with most contributed by the high protein parent MAM17-5.

View larger version (41K): [in this window] [in a new window]   Fig. 2. Linkage groups from the framework linkage map (Zhu, 2002) developed from the cross of Ogle/MAM17-5 (OM), showing significant QTL for oat groat protein and oil content. Molecular markers beginning with the letter "e" are AFLP-type; with "am" or "wisc" are SSR-type; and with others are RFLP-type markers (Zhu and Kaeppler, 2003a).

	DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

Both parents contributed favorable alleles for greater oil content in this study, whereas no favorable allele from Ogle was found in the previous study (Kianian et al., 1999). Thro and Frey (1985) reported that gene action in determining oil content was primarily additive, and neither dominance nor epistasis was important; however, significant additive x additive gene interactions were identified with four QTL for groat oil in the current research. The interactions only between loci with significant additive effects were tested in this study, rather than between all loci, regardless of their individual effects. Holland et al. (1997) indicated that many significant epistatic interactions might remain undetected if interactions only between significant individual loci were examined. In particular, the interactions detected in this study were all epistasis between nonparental alleles conferring high oil. The contribution of alleles for greater oil content from both parents and the nonparental combination of alleles in the QTL interactions could explain the observation that more than 60% of the RILs had higher oil than the high oil parent.

QTL identified in this study could be compared with previously detected QTL for groat oil content with the Kanota/Ogle (KO) map (O'Donoughue et al., 1995) as a bridge. One major QTL, explaining approximately 30% of total phenotypic variation for groat oil content, was located on linkage group OM3, which is homologous to KO11 (Zhu and Kaeppler, 2003a). Similarly, a major QTL for groat oil content was consistently mapped to KO11 in another study (Kianian et al., 1999). Of note, the major QTL identified in both studies were closely linked to cosegregating markers RZ69 and CDO665 (O'Donoughue et al., 1995; Zhu and Kaeppler, 2003a) in addition to mapping to the same chromosome. Moreover, a partial oat cDNA clone for plastidic acetyl-CoA carboxylase, which catalyzes the first committed step in de novo fatty acid synthesis, identified a polymorphism linked to the major QTL (Kianian et al., 1999). Another QTL for oil content was consistently detected on OM6 or KO2, but not found in the previous study (Kianian et al., 1999). The lack of QTL polymorphism between the two parents, or low QTL detection power, results in a QTL not to be identified in a population. In review of the previous study by Kianian et al. (1999), the QTL on OM6 or KO2 for oil content was not detected most likely because of the lack of QTL polymorphism between the two parents. Other QTL for oil content were not comparable since no clear relationship could be established for the relevant linkage groups between the KO and OM maps. The QTL on OM3 and the QTL on OM6, which were consistently identified, should be very useful in further genetic and breeding research for oat groat oil.

More genetic factors apparently control groat protein content than control groat oil content in oat, and each of the identified QTL has only a small effect. Correspondingly, the relative proportion of the environmental influence on these QTL was high. A significant drought observed in 2001 might contribute to the inconsistency in the QTL detection for groat protein content over the two years. Additional research conducted with different mapping populations and over more environments with a better experimental design is still necessary to confirm the identified QTL for groat protein content. However, the two QTL on OM6 and OM19, which were consistently detected in both years, could be useful in future genetic and breeding studies for oat groat protein.

Both negative and positive correlations between groat oil and protein content in oat have been reported (Gullord, 1986; Youngs and Forsberg, 1979); however, protein content has a positive, significant correlation with oil content in this study. The relationship between the two traits displayed in our study is similar to that reported in maize, Zea mays L., (Dudley and Lambert, 1992). Correlated traits are often associated with the pleiotropic effect of the same QTL or linkage of different QTL. As a result, three QTL for groat oil were linked to QTL for groat protein. In addition, the major QTL for oil content on OM3 may have a pleiotropic effect on protein; however, given the different metabolic pathways leading to synthesis of protein or oil (Dennis and Turpin, 1990), the QTL may be involved in deposition of protein and oil in oat seed. Given that only one QTL may be associated with both traits, it is possible for breeders to increase the level of one trait while holding the other relatively constant or decreasing it. The genomic regions associated with groat protein and oil content, and the association of molecular markers with those regions, should be useful to decipher the genetic control of the traits and provide an aid to breeders in manipulating the traits for oat improvement.

	ACKNOWLEDGMENTS

 
The authors thank Dr. D.R. Walker at the University of Georgia for his great suggestions on this manuscript. We also appreciate the excellent comments and suggestions from the anonymous reviewers. This research was funded by HATCH grant no. WIS03920 and a Plant Breeding and Genetics fellowship from Pioneer Hi-Bred International, Inc.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 
Research was supported by Hatch Grant No. WIS 03920 and a Plant Breeding and Genetics Fellowship from Pioneer Hi-Bred International, Inc.

Received for publication December 23, 2002.

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TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION REFERENCES

 

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