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CELL BIOLOGY & MOLECULAR GENETICS

Marker-Based Selection of QTL Affecting Grain and Malt Quality in Two-Row Barley

^a Dep. of Plant Science, McGill Univ., 21111 Lakeshore, Ste-Anne-de-Bellevue, QC, Canada, H9X 3V9
^b Grain Research Laboratory, 1404-303 Main St., Winnipeg, MB, Canada R3C 3G8
^c Crop Development Centre, Univ. of Saskatchewan, Saskatoon, SK, Canada S7N 5A8
^d Agriculture and Agri-Food Canada, P.O. Box 39088, St. John's, NF, Canada A1E 5Y7
^e Agriculture and Agri-Food Canada, Brandon, MB, Canada R7A 5Y3
^f Dep. of Plant Sciences, Univ. of Saskatchewan, Saskatoon, SK, Canada S7N 5A8
^g Monsanto, 67 Scurfield Blvd., Winnipeg, MB, Canada R3Y 1G4
^h Agriculture and Agri-Food Canada, Eastern Cereal and Oilseed Research Centre, Ottawa, ON, Canada K1A 0C6
ⁱ Dep. of Agricultural, Food and Nutritional Science, Univ. of Alberta, Edmonton, AB, Canada T6G 2P5
^j Dep. of Plant Agriculture, Univ. of Guelph, Guelph, ON Canada, N1G 2W1

mather{at}macdonald.mcgill.ca

	ABSTRACT

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion REFERENCES

 
Malt quality traits of barley (Hordeum vulgare L.) may be suitable candidates for marker-assisted selection, as their evaluation involves laborious and costly procedures. Four regions of the genome were previously reported to affect several grain and malt quality traits in the two-row barley cross `Harrington'/`TR306'. This study used an independent set of lines derived from the same cross to verify the existence of quantitative trait loci (QTL) in these regions. Molecular marker genotypes were used to select 47 lines from among 410 Harrington/TR306 lines that had not been used in the original mapping experiment. Four groups of lines were selected on the basis of their genotype at marker loci in two regions on chromosome 7 (5H) with QTL affecting kernel weight and plumpness, grain protein, extract ß-glucan content, the difference between fine-grind and coarse-grind extract, soluble protein, diastatic power, -amylase activity and fine-grind extract, and in regions on chromosomes 3 (3H) and 6 (6H) with QTL affecting extract ß-glucan content and fine-coarse difference. Grain and malt quality traits of these lines were determined from grain grown in five field environments in western Canada. The results confirmed the presence of QTL on chromosome 7 affecting all traits previously reported. Marker-based selection for two regions on chromosome 7 was effective in identifying phenotypically superior lines, and the magnitudes of the combined effects for these regions were close to the estimates calculated in the mapping experiment. The presence of QTL on chromosomes 3 and 6 could not be confirmed as categorically, but combined selection for extract ß-glucan content and fine-coarse difference at all four QTL regions was more effective than selection for only the two regions on chromosome 7.

Abbreviations: centimorgan, cM • QTL, quantitative trait locus or loci • DH, doubled haploid • RFLP, restriction fragment length polymorphism

	INTRODUCTION

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion REFERENCES

 
MALTING is an important end use of barley, with barley malt used mainly for brewing beer. Standard methods for assessing the suitability of barley for malting purposes involve analyses of grain characters, followed by micromalting and laboratory analyses of malt quality traits. Barley grain and malt quality characters generally exhibit quantitative variation and are influenced by genetic and environmental factors and by genotype x environment interactions (Sparrow, 1971; Briggs, 1978; Han et al., 1997; Mather et al., 1997). Grain and malt quality analyses are time consuming and costly, and they may require larger grain samples than are available in early generations of a breeding program. These factors limit the effectiveness of phenotypic selection to maintain or improve malting quality. Thus, grain and malt quality traits may be suitable candidates for the implementation of marker-assisted selection. Marker-assisted selection for QTL affecting these traits could allow for the use of larger populations, increasing the probability of generating superior genetic combinations. The number of selections to be malted could be substantially reduced by selecting first for favorable genotypes via molecular markers, and then assessing grain and malt quality only in the selected sub-sample (Han et al., 1997; Romagosa et al., 1999).

Molecular markers have been mapped in barley (e.g., Heun et al., 1991; Graner et al., 1991; Kleinhofs et al., 1993; Kasha et al., 1995) and used to detect and map QTL contributing to the phenotypic expression of grain and malt quality traits in several crosses (Hayes et al., 1993; Thomas et al., 1995; Mather et al., 1997). Information on the estimated positions and effects of such QTL can be used in marker-assisted selection. One approach is to map QTL in a limited sample of progeny from a cross, use the QTL map information to choose markers linked to QTL of interest, and apply marker-based selection in a larger independent sample of progeny from the same cross. This has been done for malting quality traits (Han et al., 1996, 1997) and agronomic traits (Romagosa et al., 1999; Zhu et al., 1999) in six-row barley, and for agronomic traits in two-row barley (Spaner et al., 1999). In all cases, marker-based selection was effective for some, but not all, QTL.

Here, we report on a marker-based selection experiment involving grain and malt quality traits in the two-row barley cross between the cultivar Harrington and the breeding line TR306. Kasha et al. (1995) developed a molecular marker map for this cross, which was then used to detect and map QTL for traits related to agronomic performance (Tinker et al., 1996), grain and malt quality (Mather et al., 1997), and disease resistance (Spaner et al., 1998). The objectives of the present study were to verify the existence of QTL in four regions of the genome that were reported (Mather et al., 1997) to affect several grain and malt quality traits and to assess the effectiveness of marker-based selection for these traits.

	Materials and methods

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion REFERENCES

 
QTL Position and Effects
Four QTL regions were considered in this experiment. These regions were as follow: near marker Upg2 on the plus arm of chromosome 3 (3H); near marker Nar1 on the plus arm of chromosome 6 (6H); near marker MWG502 on the plus arm of chromosome 7 (5H); and near marker MWG632 on the minus arm of chromosome 7 (Fig. 1) . A total of six marker loci were chosen to represent the four QTL regions of interest: MWG014 (1.2 cM from Upg2) on chromosome 3; Nar1 on chromosome 6; MWG502 and ABG610 (14.4-cM interval) on the plus arm of chromosome 7; and ABC622 and MWG632 (20.8 cM interval) on the minus arm of chromosome 7 (Table 1) .

View larger version (23K): [in this window] [in a new window]   Fig. 1 Linkage maps of chromosomes 3, 6, and 7 (5H) of the Harrington/TR306 barley cross, oriented with the plus arms at the top of the figure, and showing the approximate centimorgan positions (Kosambi function) of marker loci (mostly RFLP). Markers indicated in bold type are those used to represent or flank the QTL regions in this study. The 5H chromosome designation is that proposed by Shepherd and Islam (1992)

For other grain and malt quality traits, Mather et al. (1997) detected effects in the regions on chromosome 7 but not in those on chromosomes 3 and 6. In the region on the plus arm of chromosome 7, the TR306 allele(s) favored heavier and plumper kernels and the Harrington allele(s) favored better malting quality: lower grain protein and higher fine-grind extract. In the region on the minus arm of chromosome 7, the Harrington allele(s) had favorable effects on malt quality, conferring higher soluble protein, diastatic power, -amylase activity, and fine-grind extract. Thus, lines with Harrington alleles in both regions on chromosome 7 would be expected to have smaller kernels, lower grain protein, and higher soluble protein, diastatic power, -amylase activity, and fine-grind extract than lines with TR306 alleles in those regions.

Sample Population
Five hundred-sixty doubled haploid (DH) lines were derived from the F₁ generation of the Harrington/TR306 cross. A random sample of 150 lines was used for marker map development (Kasha et al., 1995). We determined the genotypes for the marker loci MWG014, Nar1, MWG502, ABG610, ABC622, and MWG632 for the 410 DH lines that had not been used for mapping. We selected four groups of DH lines on the basis of these marker genotypes: a group of 12 `T-H' lines with TR306 alleles in the QTL regions on chromosomes 3 and 6 and Harrington alleles in the QTL regions on chromosome 7; a group of 11 `H-T' lines with Harrington alleles on chromosomes 3 and 6 and TR306 alleles on chromosome 7; a group of 12 `H-H' lines with Harrington alleles at all six marker loci; and a group of 12 `T-T' lines with TR306 alleles at all six marker loci (Table 1). Thus, each of the selected lines had known marker genotypes in the four QTL regions, and should carry a random assortment of Harrington and TR306 alleles elsewhere in the genome.

Experimental Design and Analysis
One plot of each of the 47 selected DH lines, and four plots of each of the two parents, were grown in each of two randomized blocks at field sites in western Canada: an irrigated trial grown at Saskatoon, SK (52°10' N; 106° 40' W) in 1996, and dryland trials grown at Saskatoon and Brandon, MB (49° 50' N; 99° 57' W) in 1996 and 1997. Field plots were grown using local variety testing methods and agricultural practices for barley. Trials at Saskatoon were grown on soils with high natural fertility, after fallow, and received 100 kg ha^-1 of 11-51-0 fertilizer (11 kg ha^-1 N) before planting. Trials at Brandon received 110 and 120 kg ha^-1 of 46-0-0 before planting in 1996 and 1997, respectively. At planting, 20 kg ha^-1 of 11-51-0 were applied in both years. These additions brought the available N to about 70 kg ha^-1 for both years. Grain of Harrington, TR306, and each of 47 DH progeny was bulked over the two blocks to form two samples of each parent and one sample of each DH entry per environment. Grain samples (from a bulk of the two blocks for the DH lines, and from each block for the parents) were analyzed at the Grain Research Laboratory, Winnipeg, MB, Canada, by procedures of the American Society of Brewing Chemists (ASBC, 1992), as summarized by Mather et al. (1997).

Data for nine grain and malt quality traits (Tables 2 and 3) were analyzed in mixed models by PROC MIXED of SAS (Littell et al., 1996). Statistical tests were conducted at the 0.05 level of probability. Parents and genotypic groups were considered fixed effects, while environments and lines within each genotypic group were considered random effects. Likelihood-ratio statistics (Littell et al., 1996, p. 44) were used to test the significance of parent x environment and genotypic-group x environment interactions. It was not possible to test DH-line x environment interactions because individual DH lines were not replicated within trials. Tests of differences among parents and among genotypic groups were conducted by separate models. Tests of comparison between parents and genotypic groups were conducted in models including random environment and fixed genotype (two parents and four genotypic groups) effects. The line-within-genotypic group mean square was used as the error term for testing the significance of the genotype effect. Simple effects of genotypic group were estimated by best linear unbiased prediction methods (Littell et al., 1996). Six single-degree-of-freedom contrasts were calculated to compare the four groups of DH lines with each other. These contrasts were tested with the lines-within-genotypic-groups mean square as the error term. Additional single-degree-of-freedom contrasts were calculated to compare Harrington vs. TR306 genotypes at regions on chromosome 7 (T-H and H-H vs. T-T and H-T), and at regions on chromosomes 3 and 6 (H-T and H-H vs. T-H and T-T), with the appropriate lines-within-groups mean squares as error terms.

	Results

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion REFERENCES

 
In this experiment, the parents had lower kernel weight and higher kernel plumpness (Table 2) than in the QTL mapping experiment (Mather et al. 1997). Grain protein was not very different between experiments; soluble protein, -amylase activity, and fine–coarse difference were higher in this experiment, while fine-grind extract and extract ß-glucan levels were higher in the mapping experiment (Table 3 and Mather et al., 1997). The averages of the DH lines were close to the mid-parent value for all traits (Tables 2 and 3), suggesting that the effect of the QTL regions analyzed is additive.

Interaction between genotypic groups and environments was significant for six of the nine variables (all but fine–coarse difference, kernel weight, and diastatic power), but was not very large for any variable. Across four of the environments, the ranking of the genotypes was very consistent for all variables, but in the trial grown at Brandon in 1997, different rankings were observed for some variables. In that environment, there was less variation among the groups than in the other environments and differences among the groups were significant only for kernel weight and plumpness and soluble protein. In samples from the 1997 trial at Brandon, kernel weights were low, probably due to combined effects of net blotch, lodging, and dry conditions during grain filling (only 5 mm of rain in the second half of July). Soluble protein values were high and extract ß-glucan values were low, both consistent with overmodification of the endosperm in the presence of low amounts of starch and good levels of enzymatic activity, which are typical of poorly filled kernels. Thus, the significant interaction with environments was mostly caused by a reduction of variance among genotypic groups in the 1997 Brandon trial and the underlying cause was likely poor grain filling due to biotic and/or abiotic environmental stress. A new analysis excluding the 1997 data from Brandon revealed significant interaction only for kernel plumpness. This interaction was due to larger differences among groups in the 1996 dryland trial at Saskatoon than in other environments, with no rank changes of the groups. Contrasts between alleles at the four QTL regions were very similar whether or not the 1997 Brandon data were included in the analysis, and those data were maintained in the analysis. Parent x environment interaction followed a similar pattern; significant interaction for six traits overall, but only for two without the 1997 data from Brandon.

Extract ß-Glucan and Fine–Coarse Difference
The two parental lines, Harrington and TR306, did not differ significantly for either extract ß-glucan or fine–coarse difference, though in both cases, the interparental range was more than twice as large as in the original mapping experiment (Table 2). For both of these traits, there were significant differences among the four genotypic groups. As expected, the T-H group had the lowest (best) values, the H-T group had the highest values, and the other groups were intermediate (Table 3 and Fig. 2) . For both traits, the phenotypic distributions of the two extreme groups overlapped (Fig. 2). For both extract ß-glucan and fine–coarse difference, the lines with the best (lowest) values were from the T-H group (Fig. 2). One T-H line (HT408) had both the lowest mean extract ß-glucan and the lowest fine-coarse difference in the experiment. It had low values for both traits in all environments. Unexpectedly, another T-H line (HT403) had the highest mean values for both extract ß-glucan and fine-coarse difference (see the outlier in Fig. 2).

View larger version (29K): [in this window] [in a new window]   Fig. 2 Frequency distributions for mean extract ß-glucan and mean fine-coarse difference for four groups of doubled haploid lines. Marker genotypes defining the T-H, H-T, H-H, and T-T groups are given in Table 1

Selection of the 24 lines with Harrington marker genotypes in the two QTL regions on chromosome 7 (i.e., selection of the T-H and H-H groups) led to the selection of 10 of the 12 DH lines with the best (lowest) extract ß-glucan and fine-coarse difference values in the experiment (Fig. 3A) . The probability of obtaining 10 or more of the best 12 lines by chance is only 0.0095, indicating that selection for the chromosome-7 marker genotypes was effective in identifying superior lines. Selection for Harrington marker genotypes in the two QTL regions on chromosome 7 and TR306 marker genotypes in the QTL regions on chromosomes 2 and 6 (i.e. selection of the T-H group, which should have favorable alleles in all four regions) led to the selection of eight of the best 12 lines for extract ß-glucan and seven of the best 12 lines for fine–coarse difference (Fig. 3B). The probabilities associated with these frequencies are only 0.0005 and 0.0049, respectively. These probabilities do not provide tests of whether selection for all four regions was significantly better than selection only for the two regions on chromosome 7. To conduct such a test, we considered selection of the 12 T-H lines from among the 24 T-H and H-H lines. As indicated above, this set of 24 lines included 10 that were in the best quartile of the 47 lines for both traits. Of these, eight (for extract ß-glucan) or seven (for fine–coarse difference) were T-H lines. The probabilities of chance occurrence of eight or seven T-H lines among these 10 lines indicated that marker-assisted selection for all four regions was significantly more effective than marker-assisted selection for only the chromosome-7 regions for extract ß-glucan, but not for fine–coarse difference.

View larger version (46K): [in this window] [in a new window]   Fig. 3 Schematic representation of selection for specific marker genotypes among 47 doubled haploid lines from the Harrington/TR306 cross. The doubled haploid lines are arranged in rank order on the basis of their phenotypes for mean extract ß-glucan and mean fine–coarse difference, from the most favorable at left to the least favorable at right. Shaded rectangles represent lines that would be selected on the basis of their marker genotypes in (A) QTL regions on chromosome 7 or (B) QTL regions on chromosomes 3, 6, and 7

View larger version (26K): [in this window] [in a new window]   Fig. 4 Frequency distributions for three grain quality traits for four groups of doubled haploid lines. Marker genotypes defining the T-H, H-T, H-H, and T-T groups are given in Table 1

View larger version (25K): [in this window] [in a new window]   Fig. 5 Frequency distributions for four malt quality traits for four groups of doubled haploid lines. Marker genotypes defining the T-H, H-T, H-H, and T-T groups are given in Table 1

	Discussion

TOP ABSTRACT INTRODUCTION Materials and methods Results Discussion REFERENCES

It is less clear whether there are QTL affecting extract ß-glucan and fine–coarse difference in the candidate regions on chromosomes 3 and 6. There are several reasons that may explain differences in results between this experiment and the original mapping experiment. First, sample size and thus power of detection differed between the two experiments. Second, tests of statistical significance were necessarily different between the studies. Third, the experiments were carried out in different environments, which could allow genotype x environment interaction to hamper detection of the same QTL (Melchinger et al., 1998; Han et al., 1997). Although the four QTL regions showed consistent effects across environments in the mapping experiment (Mather et al., 1997) and genotypic-group x environment interaction in the present study was quite low, genotype x environment interaction cannot be ruled out as a possible cause of differential results between the experiments. Finally, contrasting results among experiments can stem from overestimation of QTL effects and/or inaccurate estimation of QTL positions in mapping experiments. Some uncertainty must always be expected in mapping QTL for traits with moderate or low heritability, yet these are the traits that could benefit most from marker-assisted selection (van Berloo and Stam, 1998). In this study, expected QTL effects were based on estimates derived from the same sample of progeny that had been used for QTL detection (Mather et al., 1997). This is a common procedure in QTL mapping, but Melchinger et al. (1998) have shown that it can lead to inflation of QTL effect estimates. Thus, the true effects of QTL may have been smaller than was expected. The true positions of the QTL may also have differed from those estimated, especially on chromosome 3, which had no polymorphic marker loci available in a large (34.5 cM) region proximal to the estimated QTL position. Such a large gap in the marker map may have interfered with accurate estimation of the QTL. The desired QTL alleles may have been more efficiently recovered in the intervals on chromosome 7 than in chromosomes 3 and 6, and failure to recover desired QTL alleles may be responsible for the wide distribution of phenotypic values within the T-T genotypic group (Fig. 2). That group included some very good lines, some very poor lines, and a majority of intermediate lines.

It is interesting to note that there was apparent transgressive segregation for extract ß-glucan and fine–coarse difference (Table 2 and Fig. 2). This is not surprising, as the extreme phenotypic groups, T-H and H-T, were designed to be composed of mixtures of alleles from both parents, thus benefitting from additive effects from both parents. When the Harrington/TR306 cross was made, it was not expected that TR306 would carry favorable alleles for malt quality traits, such as those that were detected on chromosomes 3 and 6. Other studies have reported the detection of QTL with allelic effects opposite to those predicted by the phenotype of the parent (review in Tanksley, 1993). Confirmation of the existence of such QTL offers interesting avenues for plant breeding. Grain and malt quality of barley involves many traits, which are influenced by many loci. The genetic make-up of modern malting barley varieties has been achieved by carefully balancing these traits through lengthy breeding processes. Therefore, breeders of malting barley are reluctant to use non-malting germplasm (for instance, feed types such as TR306), for fear of disrupting this genetic balance. They devote much of their attention to elite x elite crosses and, as a consequence, there is little genetic diversity among malting cultivars (Martin et al., 1991; Horsley et al., 1995). Breeders have been very successful in achieving continuous progress even within restricted germplasm boundaries (Rasmusson and Phillips, 1997), but it is not possible to foresee whether this progress will continue in the future. This series of studies confirms that the malting barley variety Harrington carries desirable QTL for malting quality, but also indicates that favorable malting alleles may be found in germplasm not conventionally used in malting barley breeding programs. Marker-assisted selection may be an effective way to introduce new potentially favorable QTL alleles into elite germplasm. Here, we have shown that marker-based selection is effective in selecting a superior sample of genotypes from a population. However, with selection based on marker genotypes alone, some phenotypically inferior genotypes may also be selected (Fig. 2). The use of marker information in selection does not eliminate the need to gather reliable phenotypic data but it should permit breeders to allocate resources to the evaluation of progeny that are more likely to carry favorable alleles at QTL.

In the present study, marker-based selection was conducted among progeny from the same cross for which the QTL had been mapped. The results indicate that this type of selection can be effective, but they give no indication of whether these QTL would be useful beyond this particular cross. This issue is now being investigated by backcrossing QTL into other cultivars.

	ACKNOWLEDGMENTS

 
This research was funded by the Natural Sciences and Engineering Research Council of Canada.

Received for publication October 14, 1999.

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