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a Swiss Federal Research Station for Agroecology and Agriculture (FAL) Zürich-Reckenholz, Reckenholzstr. 191, CH-8046 Zürich, Switzerland
b Institute of Plant Sciences, Swiss Federal Institute of Technology (ETH), Universitätstr. 2, CH-8092 Zürich, Switzerland
c Institute of Plant Biology, Univ. of Zürich, Zollikerstr. 107, CH-8008 Zürich, Switzerland
d Pharmaceutical Institute, Univ. of Basel, Benkenstr. 254, CH-4108 Witterswil, Switzerland
silvia.zanetti{at}fal.admin.ch
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ABSTRACT |
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 TOPNOTES ABSTRACT INTRODUCTIONMaterials and methodsResultsDiscussionConclusionsREFERENCES |
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-amylase activity (AA) of 226 F5 recombinant inbred lines (RILs) originating from a cross between the Swiss wheat cultivar Forno and the Swiss spelt cultivar Oberkulmer in four environments. QTL analysis was performed with 204 RILs and based on a genetic map of 183 loci. Across environments, 12 and 13 QTL were detected for FN and AA, respectively. Altogether the QTL explained more than 75% of the phenotypic variance. The two traits were highly correlated (r = -0.91) and of the 13 QTL for AA, nine coincided with QTL for FN. Three of the six QTL with major effects (R2 
15%) on PHS resistance coincided with QTL for ear length. The QTL with the strongest impact had the positive allele from Oberkulmer and was located on 5AL at the q locus, which is responsible for the typical ear morphology of spelt. The QTL on 6A (with the positive allele from Forno), 3B, and 7B (both with the positive allele from Oberkulmer) improve PHS resistance without changing the ear morphology. Thus, these QTL could be important for marker assisted selection for PHS resistance in both the wheat and the spelt germplasm.
Abbreviations: AA, -amylase activity • ABA, abscisic acid • Add, additive effect • CIM, composite interval mapping • cM, centimorgan • DH, doubled haploid • FN, falling number • h2, heritability • ICC, international association for cereal science and technology • LOD, log of the odds • partR2 squared partial correlation coefficient • PHS, pre-harvest sprouting • Nmin, amount of mineralized nitrogen in the soil • QTL, quantitative trait loci • RFLP, restriction fragment length polymorphism • RILs, recombinant inbred lines • U, unit for -amylase activity
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INTRODUCTION |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionConclusionsREFERENCES |
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-amylase activity (AA) (Stoy, 1982). Both of them are indicators for starch degradation before appearance of any visible symptoms. A low FN reflects a pronounced starch degradation resulting from high levels of AA. FN is a relevant quality parameter for the crop processing industry, therefore, breeders should use FN to select for PHS resistance.
Three gene sets are responsible for the production of -amylase (for review see Flintham and Gale, 1988). During germination, the products of the two gene families -Amy-1 and -Amy-2 are present. A subset of -Amy-2 is also active in immature grains (Gale and Ainsworth, 1984). The products of the third gene set -Amy-3 can be found exclusively during the early grain development (Baulcombe et al., 1987). The three gene sets were mapped to the long arms of chromosomal group six, seven, and five, respectively (McIntosh et al., 1998). Besides physiological processes involved in PHS this trait is also influenced by ear morphology (Brinkman and Luk, 1979; King and Richards, 1984) and/or physico-chemical aspects of water imbibition by the grain (King, 1984). Abscisic acid and gibberellin-insensitive dwarfing genes affect PHS (Flintham and Gale, 1982; Gale, 1989; Bhagwat and Bhatia, 1994). In addition, high resistance to PHS has been reported to be associated with the red grain color which results from either linkage or pleiotropy (reviewed by Gale, 1989).
Improving PHS is difficult on the phenotypic basis since PHS is a quantitatively inherited trait and strongly affected by environmental factors. Moreover, the screening for PHS resistance is hampered by the existence of genotype x environment interactions. DNA markers linked to genes involved in PHS, thus, represent a promising, environment-insensitive tool for selecting genotypes being more resistant against PHS. The availability of adequate genetic markers and segregating populations is the prerequisite for the detection of markers linked to PHS resistance genes. Barley populations have been intensively investigated to localize the genes for AA, an important characteristic of malting quality (Hayes et al., 1993; Thomas et al., 1996; Mather et al., 1997) and for seed dormancy (Ullrich et al., 1993). However, the QTL studies in hexaploid cereals, such as wheat and spelt, are still limited because of the complexity of their genome. To our knowledge currently only one QTL study was performed focusing on PHS of wheat (Anderson et al., 1993). In that study, physiologically mature spikes were exposed to simulated rainfall and scored for visible sprouting symptoms. Thus, there is a need to enlarge the knowledge of the genetic basis of PHS of hexaploid cereals.
To investigate the genetic basis of PHS resistance, we used a segregating population of a cross between wheat and spelt (Triticum spelta L.). Spelt, an interesting crop for marginal regions, has positive effects on the taste and on the tenability of the bread. A long, lax ear, tight glumes, and a brittle rachis are the most important features that distinguish spelt from wheat (Winzeler et al., 1994). A broad overview including the relationship of spelt to wheat, its production, and end-use characteristics is given by Campbell (1997). Recently, Messmer et al. (1999) constructed a genetic map (230 loci) for 226 F5 recombinant inbred lines (RILs) of a wheat x spelt cross. The same segregating population was utilized for our investigation which was aimed at (i) determining the number, localization, and effect of genomic regions involved in the phenotypic expression of PHS by evaluating FN and AA, (ii) elucidating genetic differences between wheat and spelt in regard to PHS, and (iii) providing markers linked to the QTL for marker assisted selection in wheat and spelt germplasm. The knowledge about the genetic basis of PHS will not only contribute to improve the efficiency of selecting for PHS resistance within the two gene pools wheat and spelt, but also in inter-specific crosses.
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Materials and methods |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionConclusionsREFERENCES |
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-lattice design with two replications comprising 50 incomplete blocks with 10 genotypes each. In 1996, two field trials were carried out: the first one at the Swiss Federal Research Station for Agroecology and Agriculture (FAL) at Zurich (Fal96, 450 m above sea level) and the second one at Eschikon (Esc96, 20 km north-east of Zurich at an altitude of 550 m above sea level). In 1997 and in 1998, the field trials were conducted at Rossberg (Ros97, 25 km north-east of Zurich at an altitude of 520 m above sea level) and at Oensingen (Oen98, 60 km west-south of Zurich at an altitude of 460 m above sea level), respectively. All field tests were sown between beginning of October and middle of November. The plots (size 6 m2) were separated by 1.25 m from each other within tracks. Between all tracks an isolation track was sown with a lodging resistant cultivar in order to avoid interference of neighboring plots due to lodging. Seed density was 350 naked kernels per m2. Seeds were treated with Fenpiclonil (4 mL kg-1 Beret 050FS; Novartis Agro, Dielsdorf, Switzerland). Nitrogen fertilization was applied as NH4NO3 according to the recommendation for spelt production (110 kg N ha-1) taking into account the Nmin content in the spring in the top 100 cm of the soil. The plant material was treated against eyespot at DC 33 (decimal code according to Zadoks et al., 1974) with Prochloraz (1 l/ha Sportak; Bayer, Zollikofen, Switzerland). Weeds were controlled by herbicide application.
The plots were harvested with a combiner. At a moisture level of 140 g kg-1, the harvested material was dehulled (dehulling machine: Mühlenbau, Bad Friedrichshall-Kochendorf, Germany). A sub-sample of naked kernels of each entry was processed to grit with a laboratory mill 3100 (Perten Instruments, Huddinge, Sweden). The grit was used for the determination of the degree of PHS resistance of the genotypes. As indicators for PHS falling number (FN) and -amylase activity (AA) were assessed according to ICC-standards methods (1996) and to the ceralpha method (-amylase activity assay kit, Megazyme, Wicklow, Ireland), respectively. For the latter, extraction buffer provided with the kit was added to 0.5 g of grit and after 5 min the samples were centrifuged (1000 g for 10 min). The supernatants were allowed to react with a dye-labeled Ceralpha substrate for 5 min. The reaction was stopped by adding Trizma base and absorbance was measured at 410 nm. Absorbance was converted into Ceralpha units (U) according to the provided formula. After every 22 samples a wheat standard of known -amylase activity (delivered by Megazyme, Wicklow, Ireland) and a sample of Forno were included. One unit of activity, called Ceralpha unit (U), is defined as the amount of enzyme, in the presence of excess -glucosidase and glucoamylase, required to release 1 µmol of p-nitrophenol from blocked p-nitrophenyl maltoheptaoside in 1 min under defined assay conditions.
Phenotypic data of lodging resistance, plant height, days to ear emergence, and flowering were assessed in the same field trials (Keller et al., 1999). In addition, the length (cm) of three representative ears per plot were measured in a separate field trial in 1995 (unpublished data, 2000). These additional data were used to test if they are of any relevance to the traits investigated in this study.
Statistical Analysis
Lattice analysis of single environment and ANOVA over environments were performed using the computer program PLABSTAT (Utz, 1995). The adjusted entry means (i.e., mean values of the genotypes adjusted for block effects) and effective error mean squares obtained from the lattice analysis were used for a combined ANOVA over environments in order to estimate the genotypic (
2g), the environmental (2e) as well as the genotype x environment interaction (2ge) variance components. On the basis of the variance components of the ANOVA, the heritability (h2) of FN and AA was estimated according to Hallauer and Miranda (1981). Using SAS (SAS Institute, 1988) the phenotypic data were tested for their normal distribution by the Shapiro-Wilk statistic. In addition, Pearson and Spearman rank correlation between phenotypic data was performed over all environments as well as in single environments.
QTL Analysis
The marker genotype of the 226 RILs was assessed by 176 RFLP probes and nine wheat microsatellites (Messmer et al., 1999) and one additional wheat microsatellite (R1F2) within the coding region of a 
-gliadin pseudo gene (Devos et al., 1995) mapped to 1BS. Linkage analysis was performed with the program MAPMAKER (Lander et al., 1987) by the Haldane mapping function. In areas of the genetic map where two or more markers were closely linked (<1 cM), only one marker was considered to represent this region for the QTL analysis. As a result, the map used for the QTL analysis consisted of 183 loci and spanned a distance of 2478 cM, which corresponds approximately to two thirds of the entire wheat genome. QTL analysis was performed for each experimental location and over all environments by the software-package PLABQTL (Utz and Melchinger, 1996). The computation was based on the composite interval mapping (CIM) and was carried out with the data set of 204 genotypes (excluding genotypes with more than 10% of the markers being heterozygous). Cofactors were assessed by the procedure cov SELECT. The threshold for the detection of the QTL was fixed at LOD 3.0. The phenotypic variance explained by a single QTL and its additive effect were calculated. In a simultaneous fit, the total percentage of phenotypic variance explained by all QTL as well as the squared partial correlation coefficient (partR2) of individual QTL taking all other QTL as fixed effects were obtained. Besides the additive model, we ran a model for the detection of epistatic effects between QTL and for the detection of the QTL x environment interaction.
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Results |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionConclusionsREFERENCES |
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-Amylase Activity (AA)
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The distribution of FN averaged across four environments (Fig. 1A) did not deviate significantly from a normal distribution in the F5 population; however, the AA values (Fig. 1B) were not normally distributed (Shapiro-Wilk statistic of SAS). For AA values, skewness and kurtosis were 1.06 (P < 0.01) and 0.55 (P < 0.10), respectively.
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2e, 2g, 2ge) highly significant among RILs (P < 0.01). For FN, the environmental variance (2e = 5888) was the one which contributed most to the phenotypic variance and was followed by genotypic variance (2g = 3908) and the one of the genotype x environment interaction (2ge = 2273). On the basis of the components of variance, the heritability (h2) of FN on a line mean basis was estimated to be 0.85 (h2 on a plot basis ranged from 41–44%). For AA the most important component was also the 2e (0.2435). Since the variance component of the genotype x environment interaction (2ge = 0.1958) was higher than the genotypic variance (2g = 0.1141), the heritability of AA (h2 = 0.68) was lower in comparison to the one of FN.
The field trials were exposed to very contrasting growing and harvesting conditions, which is confirmed by the high 2e values of FN and AA. Unfavorable weather delayed the harvest in 1996, especially in Fal96. The population tended to sprout before harvest as evident from the generally low FN and the generally high AA values in Fal96. In contrast, in Ros97 the optimal weather conditions before and during the harvest period prevented the plant material from sprouting. As a result, the environment Fal96 was suitable for the differentiation of genotypes with a high level of pre-harvest sprouting resistance due to its generally low FN, whereas Ros97 differentiated for genotypes with a low resistance to pre-harvest sprouting (Fig. 1A). The population grown in 1998 was harvested relatively early and under very dry conditions. The relatively high value of 2ge indicated that genotypes differ in their response to contrasting environments. As a result, FN were more highly correlated between locations grown in the same year (Fal96 and Esc96) (r = 0.84) than between those of different seasons (r-values ranged from 0.33–0.72). Rank correlation of AA between environments ranged from 0.28 (Fal96 and Oen98) to 0.73 (Fal96 and Esc96). The FN of the most contrasting environments (Fal96 and Ros97) were correlated with an r-value of 0.65 (Fig. 1C). RILs with high FN in Fal96 showed also a high FN in Ros97, whereas FN of genotypes with a FN below 100 s in Fal96 ranged from 100 to 480 s in Ros97. The FN of these two contrasting environments were highly correlated with their corresponding AA values (r = -0.90 and r = -0.88 for Fal96 and Ros97, respectively). Despite the high correlation, AA and FN differ in their discrimination power (Fig. 1E and 1F). Assessment of AA differentiated well among sprouted material of Fal96 (AA> 1 U; FN< 100 s) (Fig. 1E). However, the differentiation of AA was weaker among the non sprouted material of Ros97 (AA< 0.3 U; FN> 300 s) (Fig. 1F).
Susceptibility to PHS is dependent on the environment, and any factor which results in a delay of the grain ripening will enhance the risk of PHS. Lodged crops are as well susceptible to PHS due to the high humidity. Thus, one might expect that FN and AA are correlated to traits such as lodging resistance, plant height, ear emergence, and flowering date. However, in our population, FN was only weakly correlated (r < 0.2) to traits that could influence pre-harvest sprouting such as heading and flowering time as well as plant height or lodging scores. In contrast, ear length was significantly (P < 0.01) correlated to FN (r = 0.42).
QTL for Falling Number
In the QTL analysis over single environments, nine QTL (LOD> 3.0) for FN were found in Fal96, 11 QTL in Esc96, six QTL in Ros97, and 12 QTL in Oen98 (Table 2)
. In the model fitting all QTL, the percentage of explained phenotypic variation ranged between 57% in Oen98 to 70% in Esc96. Across all environments, 12 QTL for FN were found explaining altogether 76.3% of the phenotypic variation (Table 2, Fig. 2)
. At eight chromosomal regions, the allele of the wheat parent Forno contributed to an increase in FN. Eight QTL found in the overall analysis were confirmed by at least two single-environment analysis and the QTL on 3B (marker interval: Xglk80-Xpsr1054) was detected in all four environments. Of the 12 QTL for FN, three (on 3B, 54 cM; 5A, 202 cM; and 7B, 88 cM) each explained more than 15% of the phenotypic variation in composite interval mapping comprising the cofactors. At all of these three QTL, the positive allele came from the spelt parent Oberkulmer and their additive effects ranged from +21 s to +32 s. The QTL with the most pronounced impact on FN (R2 = 26.4%) was found on 5A (Xpsr1194-Xpsr918b). The additive effect of this QTL varied considerably between the environments (from +31 s in Esc96 to +64 s in Ros97). No significant digenic epistasis could be detected between QTL for FN (data not shown). Significant QTL x environment interactions were detected for the QTL on 3A (42 cM) and the two QTL on 5A (14 and 202 cM).
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-Amylase Activity
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Discussion |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionConclusionsREFERENCES |
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PHS resistance is a difficult breeding target due to the considerable genotype x environment interactions, with genotype x year interactions being larger than genotype x location interactions. Consequently, it is important to study not only several locations but also different growing seasons to obtain reliable data on PHS resistance. One might expect that morphological and phenological plant characteristics contribute to the variation in PHS. For example, variation in heading time could mean that ears of different genotypes experience different weather conditions during critical periods for PHS (Flintham and Gale, 1988). In addition, lodged genotypes are exposed to more humid conditions favorable for PHS. However, in our population, PHS was not correlated to heading time or to lodging scores, although genotypes strongly differentiated in lodging susceptibility. As a result, genomic regions responsible for lodging resistance (Keller et al., 1999) generally differed from those for PHS in our population. This is in agreement with results of barley showing low coincidences between genomic regions involved in AA and those of lodging resistance or heading date (Hayes et al., 1993). Therefore, lodging resistant cultivars are no guarantee for high level of PHS resistance.
The high heritability values, the highly significant variation within the population (2g) for FN and AA, and high correlation between replications and between environments are all crucial indications that the phenotypic data of our investigation is an ideal basis for QTL analysis. Thus, the QTL findings of this study are of an adequate robustness.
Genetic Basis for PHS Resistance
On the basis of our QTL results of FN and AA in a wheat x spelt cross at least 16 genomic regions are involved in the phenotypic expression of PHS resistance (Fig. 2). The high coincidence between QTL for FN and AA indicate that these traits are controlled predominantly by identical genomic regions. We found six QTL with major impacts on PHS. Kaeppler and Rasmusson (1991) concluded from the similarly high heritability values of AA on both F2 and F5 barley lines that major genes may be important for this trait. In the investigated population, both parental cultivars contributed alleles to an improved PHS resistance. This is confirmed by a pronounced transgressive segregation. Thus, transgression breeding is a possible strategy to improve PHS resistance in both germplasms. In contrast, in the study of Hayes et al. (1993), only one barley parent contributed to an improved AA at nine genomic regions. Mather et al. (1997) found no transgression for AA among 145 DH barley lines, and Anderson et al. (1993) only towards the susceptible side for PHS in two wheat populations. In our investigation, the mean of the RILs did not deviate significantly from the parental mean, thus, it is concluded that predominately additive gene effects are involved in the expression of FN and AA. Indeed, no significant epistatic effects could be detected. This is in contrast to the findings in a barley population where significant epistatic effects on FN resulted in a significant difference between the population mean and the parental mean (Thomas et al., 1996).
The QTL detected for PHS resistance were relatively consistent in the different environments. We detected more QTL in the overall analysis than in the single- environment analysis (Table 2 and 3). This result indicates that some genomic regions are of minor importance under specific environmental condition. In the environment Fal96, suitable for the differentiation of RILs with high PHS resistance, four genomic regions were found to be involved in FN which remained undetected in the overall analysis (Table 2). For AA only one genomic region was not found in the overall analysis (Table 3). All these QTL found exclusively in Fal96 but not in the overall analysis had minor impacts on PHS (R2 
7.5%). From these data and from the high correlation between environments we can conclude that QTL from the overall analysis are certainly more reliable and, thus, relevant for practical breeding.
The number of QTL found in our study was similar to the one reported by Hayes et al. (1993) and Ullrich et al. (1993). Hayes et al. (1993) detected nine QTL for AA by investigating 150 DH barley lines grown in four environments. Ullrich et al. (1993) found 10 genes with consistently significant effects across two to six germination tests for seed dormancy in a barley population of 150 DH lines. In contrast, lower number of QTL for PHS in wheat populations and for AA in barley populations were reported by Anderson et al. (1993), Thomas et al. (1996) and Mather et al. (1997). Mather et al. (1997) detected two minor and two major QTL for AA in a barley population of 145 DH lines grown in six environments with a genetic map of 127 loci. Thomas et al. (1996) assessed FN of 59 DH barley lines grown at one location and found two QTL for FN. Anderson et al. (1993) found four genomic regions for visible PHS damage in each of the two wheat populations (78 and 138 RILs) cultivated in three locations in 2 yr with less than 40 probes per population. Reasons for the lower number of QTL found in these studies might be the genetic background, the population size, the limited number of environments and/or a low marker coverage. In our investigation, the high percentage of phenotypic variation explained by all QTL together (R2tot> 75%) indicates that the phenotypic data as well as the genetic map were an adequate basis for the QTL analysis.
Coincidences of QTL for PHS with Candidate Genes Involved in Germination
Since -amylase activity is a major parameter involved in PHS, one might expect coincidences of QTL for PHS with mapped -amylase genes that are active during germination. On 6D and 7B, we detected a QTL for PHS, which corresponds to the location of -Amy-1 and -Amy-2 genes, respectively. Flintham and Gale (1988) argued that the chromosomal group six is the most significant one in regard to FN. Indeed, Mather et al. (1997) detected a QTL for AA on 6H with -amylase-1 probe as linked marker and Anderson et al. (1993) found a genomic region on 6BL associated with PHS in one of the two investigated wheat populations. It is likely that we did not detect all QTL for PHS on the chromosome group six due to the low polymorphism of this group resulting in a low marker density. The QTL for PHS on 7B (marker interval: Xpsr350-pwir232b) is close to the -Amy-2 gene according to genetic maps of wheat (McGuire and Qualset, 1997). This gene was also relevant for the phenotypic expression of AA in a barley population (Hayes et al., 1993). Han et al. (1997) demonstrated that marker assisted selection for this QTL (flanking markers Brz and Amy2) was highly effective in improving AA but also other malting characteristics. A gene for -Amy-3 has been mapped on the chromosome group 5 (Baulcombe et al., 1987). According to wheat maps of McGuire and Qualset (1997), the -Amy-3 gene is close to the QTL for PHS (202 cM) found in our population. Since this gene family is only expressed in immature grains (Baulcombe et al., 1987), we conclude that it plays a less predominant role for PHS. Abscisic acid (ABA) was described to be an effective inhibitor of germination. On 5AL a QTL for ABA was mapped between the loci Xpsr575 and Xpsr426 (Quarrie et al., 1994). The latter is less than 20 cM from the QTL for PHS. The QTL of ABA could, thus, contribute to the strong impact of this genomic region on PHS.
Pleiotropic Effects of PHS and Ear Morphology
The QTL with the strongest effect (R2 25%) on PHS was found on the long arm of 5A (marker interval: Xpsr1194-Xpsr918b). At this chromosomal region the allele derived from the spelt parent contributed to an improved PHS resistance. This genomic region is known to contain the q locus, which is responsible for speltoid suppression (Tsujimoto and Noda, 1990; McIntosh et al., 1998). Therefore, the positive effect of this QTL on PHS might result from pleiotropic effects of the typical ear morphology of spelt. This assumption was confirmed by the detection of a major QTL for ear length at the same location (R2 = 59%; unpublished data, 2000) in our population and by the high, positive correlation between ear length and FN or AA, respectively. In addition, we found four other genomic regions (2A, 3A, 4A, and 5AS) inherited from the wheat parent Forno, where increased PHS resistance was associated with longer ears. Thus, a longer ear associated with a lower spikelet density might enhance the PHS resistance by improving the drying of the ear. King and Richards (1984) could show that club head character accounted for a 25% increase in ear water uptake. Indeed, we found in our population that genotypes with a short, compact ear morphology showed visible sprouting symptoms in a paralleled field trial at Reckenholz in 1996 (data not shown). Since ear length is only relevant in unfavorable conditions, no QTL at this chromosomal region was detected in Oen98 (Table 2 and 3). Longer ears usually have also a more pronounced nodding angle which diminishes water penetration. Brinkman and Luk (1979) showed that nodding angle greater than 120° from the upright position reduced water damage in barley. These results demonstrate the importance of considering also morphological characteristics for the interpretation of detected QTL.
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Conclusions |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionConclusionsREFERENCES |
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While AA sensitively discriminates plant material strongly affected by PHS, FN is more suitable to characterize material with a less pronounced degree of PHS and, therefore, more relevant for breeding programs. In our population, ear length was the only morphological parameter showing a significant, positive correlation to PHS resistance. Thus, lodging resistant plants alone are no guarantee for low levels of PHS. However, ear length can be considered for indirect selection for PHS resistance in the spelt germplasm.
Of the six QTL with major effects on PHS three QTL were associated with ear length. The QTL on 5AL (Xpsr1194-Xpsr918b) with the strongest effect coincided with the q locus of the spelt parent Oberkulmer, while the QTL on 2A (Xglk699a-PL_AP) and 5A (Xpsr644a-Xpsr945a) were inherited from the wheat parent Forno. These regions are very interesting because they could be useful in improving PHS resistance in the spelt germplasm, where long lax ears with tight glumes and brittle rachis are desired, but are of no interest for the wheat gene pool. The QTL on 6A (Xpsr008-Xpsr563a) inherited from wheat as well as the QTL on 3B (Xglk80-Xpsr1054) and 7B (Xpsr350-pwir232b) both inherited from spelt represent valuable sources for PHS resistance and could be useful also in wheat germplasm since they are not associated with any undesired alternation of the ear type of wheat. Therefore, the flanking markers of these three regions are suitable for marker assisted selection in wheat and spelt breeding programs.ICC-standard methods. 1996
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ACKNOWLEDGMENTS |
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NOTES |
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionConclusionsREFERENCES |
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Received for publication October 27, 1999.
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TOPNOTESABSTRACTINTRODUCTIONMaterials and methodsResultsDiscussionConclusionsREFERENCES |
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-amylase gene (-Amy3). Mol. Gen. Genet. 1987;209:33-40.[Medline]-amylase species found in developing and germinating wheat grain. Biochem. Gen. 1984;22:1031-1036.[Medline]This article has been cited by other articles:
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  M. Imtiaz, F. C. Ogbonnaya, J. Oman, and M. van Ginkel Characterization of Quantitative Trait Loci Controlling Genetic Variation for Preharvest Sprouting in Synthetic Backcross-Derived Wheat Lines Genetics, March 1, 2008; 178(3): 1725 - 1736. [Abstract] [Full Text] [PDF]
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 P. Langridge, N. Paltridge, and G. Fincher Functional genomics of abiotic stress tolerance in cereals Brief Funct Genomic Proteomic, February 1, 2006; 4(4): 343 - 354. [Abstract] [Full Text] [PDF]
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