HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (8) Citing Articles via Google Scholar Google Scholar Articles by De Koeyer, D. L. Articles by Stuthman, D. D. Search for Related Content PubMed Articles by De Koeyer, D. L. Articles by Stuthman, D. D. Agricola Articles by De Koeyer, D. L. Articles by Stuthman, D. D. Related Collections Other Grain Crops Crop Genetics

CELL BIOLOGY & MOLECULAR GENETICS

Allelic Shifts and Quantitative Trait Loci in a Recurrent Selection Population of Oat

^a Potato Research Centre, Agriculture & Agri-Food Canada, Fredericton, NB E3B 4Z7 Canada
^b Dep. of Agronomy and Plant Genetics, Univ. of Minnesota, St. Paul, MN 55108

* Corresponding author (dekoeyerd{at}em.agr.ca)

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Recurrent selection to enhance grain yield of oat (Avena sativa L.) has been ongoing at the University of Minnesota since 1968. Grain yield was increased by 21.7% after seven cycles of recurrent selection. The objectives of this study were to monitor the long-term genetic changes in this recurrent selection population using restriction fragment length polymorphisms (RFLPs). Ninety-seven RFLP loci detected by 73 cDNA clones were used to evaluate changes in allelic frequencies during the recurrent selection process. Significant allelic shifts were detected in eight genomic regions. Four linkage groups were studied in greater detail to localize putative quantitative trait loci (QTL). In total, seven primary or major QTL regions were identified using allelic shift, correlation, and single-factor analysis of variance (ANOVA) data. Six of these regions were associated with grain yield and one was associated with plant height. Thirty-three other minor QTL were detected using correlation and/or ANOVA data. Multiple regression models for grain yield, heading date, and plant height indicated that associated markers accounted for 30, 38, and 27% of the phenotypic variance, respectively. Our results indicate that we have identified genomic regions containing favorable alleles selected during the recurrent selection process. Thirteen of the 40 QTL identified for the individual traits in the recurrent selection population were previously identified in the Kanota x Ogle recombinant inbred mapping population. Therefore, these QTL may be generally important in oat.

Abbreviations: ANOVA, analysis of variance • cM, centimorgan • K x O, Kanota x Ogle • QTL, quantitative trait locus (or loci) • RIL, recombinant inbred line • RFLP, restriction fragment length polymorphism

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
MOLECULAR MARKERS are providing a tool for plant breeders to more effectively select important regions of a plant genome. A current challenge is efficiently identifying markers associated with traits of interest. Detection of allelic shifts in long-term selection experiments, such as recurrent selection programs, can be used to localize genes governing agronomic traits.

Most studies have used allozymes to examine changes in allelic frequencies associated with recurrent selection. Allelic frequencies at isozyme loci have been studied in recurrent selection experiments with common bean (Phaseolus vulgaris L.) (Delaney and Bliss, 1991b) and maize (Zea mays L.) (Brown and Allard, 1971; Stuber and Moll, 1972; and Stuber et al., 1980). Stuber et al. (1980) documented the changes in allelic frequency at eight enzyme loci in long-term full-sib family and reciprocal recurrent selection in two open-pollinated maize varieties. Alleles at all eight loci showed frequency changes that were greater than expected due to random drift alone in at least one selection experiment. In a subsequent study, selection of allozymes with linkage to loci putatively affecting grain yield was more effective in some environments than direct selection for grain yield employing full-sib family recurrent selection (Stuber et al., 1982).

Restriction fragment length polymorphisms should be more effective for identifying allelic shifts in recurrent selection populations, due to enhanced ability to detect DNA sequence variation. Changes in allelic frequencies have been studied in the Illinois long-term maize selection experiments using enzyme systems and RFLPs. Neutral drift was the predominant observation at six enzyme loci after 68 generations of low and high oil and protein selection (Brown, 1971). Sughroue and Rocheford (1994) detected differences in RFLP genotypic frequencies among advanced generations of the Illinois high oil, Illinois low oil, reverse high oil, and reverse low oil maize strains. They reported that three RFLP loci, associated with QTL for oil concentration in an Illinois high protein x Illinois low protein F₂ population (Goldman et al., 1994) showed a putative association with response to reverse selection for oil concentration. Rocheford (1994) reported that ribosomal DNA intergenic spacer-length composition also changed following recurrent selection in Iowa Stiff Stalk Synthetic maize populations.

It is apparent that markers associated with agronomic traits in recurrent selection populations offer potential for use in marker-assisted selection. Because one of the goals of QTL analysis is to provide the foundation for marker-assisted selection programs, it may be useful to identify QTL that have already been selected in a population. Use of DNA markers for retrospective QTL analysis has not been reported in any crop other than maize.

In oat, only a few QTL studies have been reported. Siripoonwiwat et al. (1996) identified several QTL affecting agronomic traits using recombinant inbred lines (RILs) derived from a cross between ‘Kanota’, an A. byzantina L. cultivar, and ‘Ogle’, an A. sativa L. cultivar. Quantitative trait loci controlling grain quality and kernel morphology have been detected in the Kanota x Ogle (K x O) RIL mapping population (Kianian et al., 1994, 1996). Subsequent QTL studies need to be conducted using populations that are more agronomically elite to increase the usefulness of this technology for oat breeders.

Recurrent selection to enhance grain yield of oat has been ongoing at the University of Minnesota since 1968 (Stuthman and Stucker, 1975). Grain yield was increased by 21.7% after seven cycles of selection (De Koeyer and Stuthman, 1998). The identification of changes in allelic frequencies in this oat population could provide insight into the effectiveness of recurrent selection, and identify important genes in the oat genome. Oat breeders may ultimately benefit from this knowledge by incorporating marker-assisted selection into their breeding programs.

The objectives of this study were to: (i) measure changes in allelic frequencies during seven cycles of recurrent selection for grain yield, (ii) identify the genomic location of putative QTL governing grain yield, heading date, and plant height in the recurrent selection population, and (iii) compare the QTL located in the recurrent selection population with those previously identified in a Kanota x Ogle RIL population.

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Recurrent Selection
Five cultivars and seven breeding lines were selected primarily on the basis of high grain yield to be parents for the original population. The first cycle of selection was based on the yield performance of 640 F₄-derived F₆ and F₇ lines developed from a diallel cross among the 12 original parents (Stuthman and Stucker, 1975). The highest yielding line from each of the 21 highest yielding families were selected as parents for the second cycle of selection.

Each subsequent cycle (2–7) involved intermating 21 parents in a circulant partial diallel, with each parental line crossed to six others for a total of 63 crosses per cycle. One plant from each parental line was used for each cross combination. Single-seed descent was used to advance 15 to 25 lines from each cross to the F₄ generation. Seed from individual F₄ plants was increased in 1.5-m rows and 10 lines were randomly chosen per cross for evaluation in the F_4.6 generation. A total of 630 F_4.6 lines were evaluated in hill plots (Frey, 1965) at St. Paul, MN, in a single year. Hill plots with 30 seeds per hill were arranged in a 30 cm grid using a randomized complete block design with four or five replicates. Grain yield (g hill^-1), heading date (d after planting) and plant height (cm) were evaluated in each cycle. For the first three cycles, the selection criterion was primarily grain yield of the F_4.6 lines. After Cycle 3, the 21 highest yielding crosses were selected and the most agronomically desirable line within each cross was chosen to be a parent for the subsequent cycle. Earlier heading date and shorter plant height were emphasized during within-cross selection.

Evaluation of Parents for Cycles 0 through 7
One hundred and fifty-nine parents (12 from Cycle 0, and 21 from each of Cycles 1 through 7) and five check cultivars (Dane, Jerry, Milton, Jim, and Troy) were planted in hill plots at Rosemount and St. Paul, MN, in 1994 and 1995 (De Koeyer and Stuthman, 1998). The parents were F₄-derived lines in at least the F₆ generation. A randomized complete block design with four replicates was used in each environment. Grain yield (g hill^-1), heading date (d after planting), and plant height (cm) were determined in each environment.

Restriction Fragment Length Polymorphism Analysis
DNA was isolated from 2- to 3-wk-old seedlings. The tissue samples were bulks of 25 seedlings per genotype. A modified method of Hu and Quiros (1991), described in De Koeyer et al. (1999), was used for DNA extraction. DNA was digested using the restriction enzymes EcoRI, EcoRV, or DraI. Procedures for Southern blotting, DNA hybridizations, and autoradiograph exposures are described in De Koeyer et al. (1999).

Twenty-eight cDNA clones were initially used to screen the 12 original parents for polymorphisms. These probes detected 57 loci, 47 of which mapped to 34 of the reported 38 linkage groups in hexaploid oat (O'Donoughue et al., 1995). The K x O linkage map location of loci discussed through the remainder of this paper is based on the map developed by O'Donoughue et al. (1995). Linkage groups 1, 6, 11, and 28 were studied in greater detail to localize putative QTL. Thirty-three cDNA clones were screened for polymorphisms and these clones detected 33 loci on these four linkage groups and 20 additional loci. Twelve other RFLP probes were selected to test 13 loci that were associated with grain yield, heading date, or plant height in the K x O population (Siripoonwiwat et al., 1996). These probes revealed 5 loci in other genomic regions. All probes that revealed polymorphisms among the 12 original parents were tested on blots with digested DNA from each of the 21 parents for each of the seven cycles.

Allelic Shifts
Allelic frequencies were determined for each loci in each cycle of selection. The statistical methods of Nei (1987) were used to detect allelic shifts that were significantly greater than those expected by random drift alone. Assumptions used for this test were random mating, no selection, and a population size of 21. This test provided baseline thresholds for identifying alleles that may have undergone selection in an idealized population similar in structure to the recurrent selection population in this study. The crossing scheme for the population is not random mating per se, but it ensures equal contribution by all parents for a given cycle in a systematic design. The population size was assumed to be 2N = 21; but in fact it can be considered slightly larger since the parental lines are F₄ derived and not completely homogeneous. These discrepancies between the test assumptions and the population structure result in a very conservative test for allelic shifts. Some of the thresholds for determining significant changes in allelic frequencies are given in Table 1. Regression analysis was performed on allelic frequencies across cycles of selection to determine the average change in allelic frequency per cycle for each locus.

Multiple linear regression models were tested using RFLP loci that were associated (P < 0.01) with any of the three agronomic traits based on ANOVA. Models in which all markers were simultaneously significant (P < 0.05) for each trait were constructed. The proportion of phenotypic variance explained by these loci was given by the coefficient of determination (R²). SAS software (SAS Institute, 1985) was used for the regression and correlation analyses, and for the ANOVA (GLM procedure).

Initial QTL studies in oat have been conducted using the K x O population. This population can be used as a reference to determine the general importance of QTL regions for a broader range of oat germplasm. The map location of markers associated with agronomic traits in the K x O population (Siripoonwiwat et al., 1996) was compared with QTL regions identified in the recurrent selection population.

	RESULTS AND DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Allelic Shifts
Ninety-seven of the 128 markers screened were polymorphic and were tested on restricted DNA from the 147 parents of cycles 1 through 7 of the recurrent selection population. Representative RFLP patterns for the original parents and for the Cycle 7 parents are shown in Fig. 1a and 1b, respectively. Based on fragment size, only three loci in the recurrent selection population had RFLP alleles that appeared to be different than those mapped in the K x O population by O'Donoughue et al. (1995). Allelic variation and genetic diversity in the recurrent selection population was examined in greater detail in a previous study (De Koeyer et al., 1999).

View larger version (76K): [in this window] [in a new window]   Fig. 1. (A) Restriction fragment length polymorphism banding patterns for DraI - digested DNA from the 12 original recurrent selection parents hybridized with the oat cDNA clone CDO 82. Arrows designated (a) represent alleles of an unmapped locus and arrows designated (b) represent alleles of a locus that maps to linkage group 6. (B) Restriction fragment length polymorphism banding patterns for DraI - digested DNA from the 21 Cycle 7 parents hybridized with the oat cDNA clone CDO 82. Arrows designated (a) represent alleles of an unmapped locus and arrows designated (b) represent alleles of a locus that maps to linkage group 6.

View this table: [in this window] [in a new window]   Table 4. Summary of quantitative trait loci (QTL) detected for three agronomic traits in the Minnesota oat recurrent selection population and their relationship to QTL detected in a ‘Kanota’ x ‘Ogle’ RIL population.

Heading Date
None of the regions showing an allelic shift (P < 0.05) after seven cycles was associated with heading date based on correlation analysis (Table 2). However, two regions were significant based on correlation analysis (P < 0.05) and single factor ANOVA (P < 0.01), and 11 were identified as being associated with heading date using only ANOVA (P < 0.01) (Table 4). Xog41 on linkage group 3 showed an allelic shift after five cycles of selection. Six of the QTL affecting heading date were also associated with grain yield and/or plant height (Table 4 and Fig. 2). Two other QTL for heading date, on linkage groups 6 and 17, were identified within 20 cM of QTL for grain yield and plant height.

View larger version (31K): [in this window] [in a new window]   Fig. 2. Linkage map location of primary, secondary, and tertiary QTL affecting grain yield (GY), heading date (HD), and plant height (PH) in a recurrent selection population of oat. Three linkage groups (O'Donoughue et al., 1995) that were analyzed in detail are shown. Primary QTL regions are defined as those identified using allelic shift, correlation, and single-factor ANOVA data. Secondary QTL were localized using correlation and ANOVA data, and tertiary QTL were identified based on ANOVA alone. An * denotes that the QTL region also was detected in a Kanota x Ogle recombinant inbred line population (Siripoonwiwat et al., 1996). m indicates locus was monomorphic in the recurrent selection population.

Multiple Lucus Models
Multiple linear regression models were constructed using loci that were associated (P < 0.01) with the agronomic traits (Table 5). The model for grain yield included Xbcd1230a, Xumn826, Xcdo1385c, and Xcdo665b and accounted for 30% of the phenotypic variance. The loci Xog41, Xisu1146a, Xumn815b, Xcdo665b, and Xcdo669d were included in the model for heading date, accounting for 38% of the phenotypic variance. For plant height, the model included Xumn826, Xbcd1280a, and Xcdo1168b. This model accounted for 27% of the variance. These models generally account for a smaller proportion of the variance compared to the models with R² estimates of 39%, 15 to 52%, and 31 to 34% for grain yield, heading date, and plant height, respectively, obtained by Siripoonwiwat et al. (1996). However, care must be taken when comparing the two studies. Our study involved a less thorough survey of the genome using 97 loci compared to 252 in the K x O study. Also, the parents of the RIL population, Kanota and Ogle, are quite diverse, more so than the recurrent selection parents and thus the expectation would be that some K x O loci could have very large effects on some traits.

To understand the relationships among the QTL identified, they can be grouped into three categories: primary, secondary, and tertiary (Table 4). Figure 2 shows the three QTL types found on linkage groups 6, 11, and 28. Seven primary QTL were identified using allelic shift, correlation, and ANOVA data. These include regions on linkage groups 6, 7, 11, 22, and 29 and the unlinked RFLP marker, Xcdo1174d, associated with grain yield, and another region for plant height on linkage group 28. Ten secondary QTL were localized on linkage groups 6, 13, 17, and 37 using correlation and ANOVA data (Table 4). Six of these regions are associated with grain yield, two with heading date and two with plant height. One tertiary QTL for grain yield, 11 tertiary QTL for heading date, and 11 tertiary QTL for plant height were identified by single factor ANOVA, but not correlation analysis (Table 4). Sixteen tertiary QTL occur in regions designated as primary or secondary QTL for grain yield and/or plant height. This may limit their usefulness in marker-assisted selection for the primary traits, because they may indirectly affect more than one trait.

The nature of the recurrent selection population limits the interpretation about markers that underwent significant allelic shifts early in the selection process, but were not significant or associated with the agronomic traits in later cycles. These loci may be loosely linked to a QTL which was selected in early generations but then approached linkage equilibrium with the QTL due to recombination. Such hypotheses will require further testing in other populations.

Comparison to Kanota x Ogle Quantitative Trait Loci
Thirteen QTL identified in the recurrent selection population were associated with agronomic traits measured in the K x O mapping population by Siripoonwiwat et al. (1996) (Table 4). Two regions, one on linkage group 7 and another on linkage group 17 affected all three traits in both populations. Two regions on linkage group 6 were associated with two traits in both the K x O and the recurrent selection population. The region encompassing Xumn815b and Xcdo1313 showed significant associations with grain yield and heading date, and Xisu1146a was associated with heading date and plant height in both populations. Common QTL also were found on linkage groups 22 and 29 affecting grain yield and on linkage group 24 affecting plant height. Four QTL identified in the recurrent selection population were <10 cM from a K x O QTL for the same trait and six were within 20 cM (Table 4). Figure 2 shows the location of K x O QTL on linkage groups 6, 11, and 28 relative to the recurrent selection QTL identified in this study.

The correspondence between QTL regions in the two populations suggests that selection in the recurrent selection population may be acting at many loci that also are associated with agronomic traits in the K x O population. Because these two populations are so different, the identified QTL may be generally important in oat. Dudley (1993) indicated that QTL repeatability across two populations requires segregation of the marker and the QTL in both populations, the same linkage phase between marker and QTL alleles in both populations, and the same genotypes at other QTL when epistasis is present. These requirements appear to have been met in some cases when comparing QTL regions in the K x O and this recurrent selection population.

Our results suggest that there is an opportunity to identify DNA-markers linked to favorable alleles at loci affecting important agronomic traits while studying long-term selection in plant populations. Using these markers in marker-assisted selection has good potential for improving oat and should be considered by breeders as a strategy for germplasm enhancement. Previous studies using marker-assisted selection with isozymes showing allelic shifts in common bean and maize were quite effective (Delaney and Bliss, 1991a; Stuber et al., 1982, respectively). Studies need to be conducted to verify the effectiveness of the putative QTL regions identified in our study. These experiments should include both recurrent selection material and other unrelated oat populations.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 
Minnesota Agric. Exp. Stn. Journal no. 981130061. The financial support of the Quaker Oats Co. is gratefully acknowledged.

Received for publication November 17, 1998.

	REFERENCES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION REFERENCES

 

• Brown, A.H.D. 1971. Isozyme variation under selection in Zea mays. Nature (London) 232:570–571.[Web of Science][Medline]
• Brown, A.H.D., and R.W. Allard. 1971. Effect of reciprocal recurrent selection for yield on isozyme polymorphisms in maize (Zea mays L.). Crop Sci. 111:888–893.
• De Koeyer, D.L., and D.D. Stuthman. 1998. Continued response through seven cycles of recurrent selection for grain yield in oat (Avena sativa L.). Euphytica 104:67–72.[Web of Science]
• De Koeyer, D.L., R.L. Phillips, and D.D. Stuthman. 1999. Changes in genetic diversity during seven cycles of recurrent selection for grain yield in oat (Avena sativa L.). Plant Breed. 118:37–43.
• Delaney, D.E., and F.A. Bliss. 1991a. Selection for increased percentage phaseolin in common bean. I. Comparison of selection for seed protein alleles and S₁ family recurrent selection. Theor. Appl. Genet. 81:301–305.[Web of Science]
• Delaney, D.E., and F.A. Bliss. 1991b. Selection for increased percentage phaseolin in common bean. II. Changes in frequency of seed protein alleles with S₁ family recurrent selection. Theor. Appl. Genet. 81:306–311.[Web of Science]
• Dudley, J.W. 1993. Molecular markers in plant improvement: manipulations of genes affecting quantitative traits. Crop Sci. 33:660–668.[Abstract/Free Full Text]
• Frey, K.J. 1965. The utility of hill plots in oats research. Euphytica 14:196–208.[Web of Science]
• Goldman, I.L., T.R. Rocheford, and J.W. Dudley. 1994. Molecular markers associated with maize kernel oil concentration in an Illinois high protein x Illinois low protein cross. Crop Sci. 34:908–915.[Abstract/Free Full Text]
• Hu, J., and C.F. Quiros. 1991. Molecular and cytological evidence of deletions in alien chromosomes for two monosomic addition lines of Brassica campestris-oleracea. Theor. Appl. Genet. 81:221–226.[Web of Science]
• Kianian, S.F., R.L. Phillips, R.G. Fulcher, D.D. Stuthman, and F.H. Webster. 1994. Quantitative trait analysis of seed quality characteristics in oat (Avena sativa, 2n = 6x = 42). p. 208. In Agronomy abstracts. ASA, Madison, WI.
• Kianian, S.F., R.L. Phillips, H.W. Rines, R.G. Fulcher, and D.D. Stuthman. 1996. Quantitative trait analysis of seed morphology traits in oat (Avena sativa, 2n = 6x = 42). p. 62 (Abstracts). Poster presented at Plant Genome IV. San Diego, CA.
• Nei, M. 1987. Molecular evolutionary genetics. Columbia Univ. Press, New York.
• O'Donoughue, L.S., S.F. Kianian, P.J. Rayapati, G.A. Penner, M.E. Sorrells, S.D. Tanksley, R.L. Phillips, H.W. Rines, M. Lee, G. Fedak, S.J. Molnar, D. Hoffman, C.A. Salas, B. Wu, E. Autrique, and A. Van Deynze. 1995. A molecular linkage map of cultivated oat. Genome 38:368–380.[Medline]
• Rocheford, T.R. 1994. Change in ribosomal DNA intergenic spacer-length composition in maize recurrent selection populations. 1. Analysis of BS13, BSSS, and BSCB1. Theor. Appl. Genet. 88: 541–547.
• SAS Institute. 1985. SAS user's guide. Statistics. 5th ed. SAS Inst., Cary, NC.
• Siripoonwiwat, W., L.S. O'Donoughue, D. Wesenberg, D. Hoffman, J.F. Barbosa-Neto, and M.E. Sorrells. 1996. Chromosomal regions associated with quantitative traits in oat. J. QTL Vol. 2 Article 3. (see http://www.ncgr.org/ag/jag/papers96/paper396/oatqtl3g.html; verified February 2001).
• Stuber, C.W., M.M. Goodman, and R.H. Moll. 1982. Improvement of yield and ear number resulting from selection at allozyme loci in a maize population. Crop Sci. 22:737–740.[Abstract/Free Full Text]
• Stuber, C.W., and R.H. Moll. 1972. Frequency changes of isozyme alleles in a selection experiment for grain yield in maize (Zea mays L.). Crop Sci. 12:337–340.[Abstract/Free Full Text]
• Stuber, C.W., R.H. Moll, M.M. Goodman, H.E. Schaffer, and B.S. Weir. 1980. Allozyme frequency changes associated with selection for increased grain yield in maize (Zea mays L.). Genetics 95: 225–236.[Abstract/Free Full Text]
• Stuthman, D.D., and R.E. Stucker. 1975. Combining ability analysis of near-homozygous lines derived from a 12-parent cross in oats. Crop Sci. 15:800–803.[Abstract/Free Full Text]
• Sughroue, J.R., and T.R. Rocheford. 1994. Restriction fragment length polymorphism differences among Illinois long-term selection oil strains. Theor. Appl. Genet. 87:916–924.[Web of Science]

This article has been cited by other articles:

				R. J. Wisser, S. C. Murray, J. M. Kolkman, H. Ceballos, and R. J. Nelson Selection Mapping of Loci for Quantitative Disease Resistance in a Diverse Maize Population Genetics, September 1, 2008; 180(1): 583 - 599. [Abstract] [Full Text] [PDF]

				F. Condon, C. Gustus, D. C. Rasmusson, and K. P. Smith Effect of Advanced Cycle Breeding on Genetic Diversity in Barley Breeding Germplasm Crop Sci., May 1, 2008; 48(3): 1027 - 1036. [Abstract] [Full Text] [PDF]

				F. Breseghello and M. E. Sorrells Association Analysis as a Strategy for Improvement of Quantitative Traits in Plants Crop Sci., April 25, 2006; 46(3): 1323 - 1330. [Abstract] [Full Text] [PDF]

				X.-S. Zhang and W. G. Hill Predictions of Patterns of Response to Artificial Selection in Lines Derived From Natural Populations Genetics, January 1, 2005; 169(1): 411 - 425. [Abstract] [Full Text] [PDF]

				M. D. Smalley, W. R. Fehr, S. R. Cianzio, F. Han, S. A. Sebastian, and L. G. Streit Quantitative Trait Loci for Soybean Seed Yield in Elite and Plant Introduction Germplasm Crop Sci., March 1, 2004; 44(2): 436 - 442. [Abstract] [Full Text] [PDF]

				J.-L. Jannink Selection Dynamics and Limits under Additive x Additive Epistatic Gene Action Crop Sci., March 1, 2003; 43(2): 489 - 497. [Abstract] [Full Text] [PDF]

This Article Abstract Figures Only Full Text (PDF) Free Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in ISI Web of Science Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (8) Citing Articles via Google Scholar Google Scholar Articles by De Koeyer, D. L. Articles by Stuthman, D. D. Search for Related Content PubMed Articles by De Koeyer, D. L. Articles by Stuthman, D. D. Agricola Articles by De Koeyer, D. L. Articles by Stuthman, D. D. Related Collections Other Grain Crops Crop Genetics