S. E. Ullrich

Quantitative trait locus effects and environmental interaction in a sample of North American barley germ plasm

Quantitative trait locus (QTL) and QTL x environment (E) interaction effects for agronomic and malting quality traits were measured using a 123-point linkage map and multi-environment phenotype data from an F1-derived doubled haploid population of barley (Hordeum vulgare). The QTL × E interactions were due to differences in magnitude of QTL effects. Highly significant QTL effects were found for all traits at multiple sites in the genome. Yield QTL peaks and support intervals often coincided with plant height and lodging QTL peaks and support intervals. QTL were detected in the vicinity of a previously mapped Mendelian maturity locus and known function probes forα- andβ-amylase genes. The average map density (9.6 cM) should be adequate for molecular marker-assisted selection, particularly since there were few cases of alternative favorable alleles for different traits mapping to the same or adjacent intervals.

QTL analysis of malting quality in barley based on the doubled-haploid progeny of two elite North American varieties representing different germplasm groups

Abstract Characterization of the determinants of economically important phenotypes showing complex inheritance should lead to the more effective use of genetic resources. This study was conducted to determine the number, genome location and effects of QTLs determining malting quality in the two North American barley quality standards. Using a doubled-haploid population of 140 lines from the cross of Harrington×Morex, malting quality phenotype data sets from eight environments, and a 107-marker linkage map, QTL analyses were performed using simple interval mapping and simplified composite interval mapping procedures. Seventeen QTLs were associated with seven grain and malting quality traits (percentage of plump kernels, test weight, grain protein percentage, soluble/total protein ratio, α-amylase activity, diastatic power and malt-extract percentage). QTLs for multiple traits were coincident. The loci controlling inflorescence type [vrs1 on chromosome 2(2H) and int-c on chromosome 4(4H)] were coincident with QTLs affecting all traits except malt-extract percentage. The largest effect QTLs, for the percentage of plump kernels, test weight protein percentage, S/T ratio and diastatic power, were coincident with the vrs1 locus. QTL analyses were conducted separately for each sub-population (six-rowed and two-rowed). Eleven new QTLs were detected in the subpopulations. There were significant interactions between the vrs1 and int-c loci for grain-protein percentage and S/T protein ratio. Results suggest that this mating of two different germplasm groups caused a disruption of the balance of traits. Information on the number, position and effects of QTLs determining components of malting quality may be useful for maintaining specific allele configurations that determine target quality profiles.

Mixed models including environmental covariables for studying QTL by environment interaction

The study of the phenotypic responses of a set of genotypes in their dependence on the environment has always been an important area of research in plant breeding. Non-parallelism of those responses is called genotype by environment interaction (GEI). GEI especially affects plant breeding strategies, when the phenotypic superiority of genotypes changes in relation to the environment. The study of the genetic basis of GEI involves the modelling of quantitative trait locus (QTL) expression in its dependence on environmental factors. We present a modelling framework for studying the interaction between QTL and environment, using regression models in a mixed model context. We integrate regression models for QTL main effect expression with factorial regression models for genotype by environment interaction, and, in addition, take care to model adequately the residual genetic variation. Factorial regression models describe GEI as differential genotypic sensitivity to one or more environmental covariables. We show how factorial regression models can be generalized to make also QTL expression dependent on environmental covariables. As an illustrative example, we reanalyzed yield data from the North American Barley Genome Project. QTL by environment interaction for yield, as identified at the 2H chromosome could be described as QTL expression in relation to the magnitude of the temperature range during heading.

Mapping of β-glucan content and β-glucanase activity loci in barley grain and malt

Genetic study of β-glucan content and β-glucanase activity has been facilitated by recent developments in quantitative trait loci (QTL) analysis. QTL for barley and malt β-glucan content and for green and finished malt β-glucanase activity were mapped using a 123-point molecular marker linkage map from the cross of Steptoe/Morex. Three QTL for barley β-glucan, 6 QTL for malt β-glucan, 3 QTL for β-glucanase in green malt and 5 QTL for β-glucanase in finished malt were detected by interval mapping procedures. The QTL with the largest effects on barley β-glucan, malt βglucan, green malt β-glucanase and finished malt βglucanase were identified on chromosomes 2,1,4 and 7, respectively. A genome map-based approach allows for dissection of relationships among barley and malt βglucan content, green and finished malt β-glucanase activity, and other malting quality parameters.

Molecular marker-assisted selection for malting quality traits in barley

Selection for malting quality in breeding programs by micromalting and micromashing is time-consuming, and resource-intensive. More efficient and feasible approaches for identifying genotypes with good malting quality would be highly desirable. With the advent of molecular markers, it is possible to map and tag the loci affecting malting quality. The objective of this study was to assess the effectiveness of molecular marker assisted selection for malting quality traits. Two major quantitative trait loci (QTL) regions in six-row barley for malt extract percentage, α-amylase activity, diastatic power, and malt β-glucan content on chromosomes 1 (QTL1) and 4 (QTL2) have been previously identified. The flanking markers, Brz and Amy2, and WG622 and BCD402B, for these two major QTL regions were used in marker-assisted selection. Four alternative selection strategies; phenotypic selection, genotypic selection, tandem genotypic and phenotypic selection, and combined phenotypic and genotypic selection, were compared for both single and multiple trait selection in a population consisting of 92 doubled haploid lines derived from ‘Steptoe’ × ‘Morex’ crosses. Marker assisted selection for QTL1 (tandem genotypic and phenotypic selection, and combined phenotypic and genotypic selection) was more effective than phenotypic selection, but for QTL2 was not as effective as phenotypic selection due to a lack of QTL2 effects in the selection population. The effectiveness of tandem genotypic and phenotypic selection makes marker assisted selection practical for traits which are extremely difficult or expensive to measure such as most malting quality traits. It can substantially eliminate undesirable genotypes by early genotyping and keeping only desirable genotypes for later phenotypic selection.

Verification of yield QTL through realized molecular marker- assisted selection responses in a barley cross

Verification of putative quantitative trait loci (QTL) is an essential step towards implementing the use of marker-assisted selection (MAS) in cultivar improvement. In a previous study with 150 doubled haploid lines derived from the 6-row cross Steptoe/Morex (S/M), four regions (QTL1–4) of the barley genome were associated with differential genotypic expression for grain yield across environments. The objectives of this study were to verify the value of these four QTL for selection and to compare the efficiency of alternative MAS strategies using these QTL vs. conventional phenotypic selection for grain yield. A total of 92 DHLs derived from the S/M cross that were not used in the original mapping efforts were used for QTL verification. Confirmation of QTL effects was first accomplished by assessing yield differences between individuals carrying alternative alleles at each putative locus in three environments. QTL1 on chromosome 3 was confirmed as the most important and consistent locus to determine yield across sites, with the S allele being favorable. The M allele at QTL3 on chromosome 6 was beneficial for grain yield across sites, but to a lesser degree than QTL1. Magnitudes of allele effects at QTL2 (chromosome 2) and QTL4 (chromosome 7) were highly influenced by the environment where the genotypes were grown. Verification of QTL effects was best achieved by comparing realized selection response. Genotypic (MAS) and tandem genotypic and phenotypic selection were at least as good as phenotypic selection. Consistent selection responses were detected for QTL1 alone and together with QTL3. Genotypic selection for lines carrying the S allele at QTL1 resulted in the identification of high-yielding genotypes. Selection responses increased when the M allele at QTL3 was combined with the S allele at QTL1. Significant qualitative QTL × environment interactions for QTL2 and QTL4 were detected through differential realized selection responses at different sites. Without a thorough understanding of the physiological and agronomic particulars of any QTL and the target environment, MAS for QTL showing qualitative interactions should be minimized

Use of the additive main effects and multiplicative interaction model in QTL mapping for adaptation in barley

The additive main effects and multiplicative interaction (AMMI) model has emerged as a powerful analytical tool for genotype x environment studies. The objective of the present study was to assess its value in quantitative trait locus (QTL) mapping. This was done through the analysis of a large two-way table of genotype-by-environment data of barley (Hordeum vulgare L.) grain yields, where the genotypes constituted a genetic population suitable for mapping studies. Grain yield data of 150 doubled haploid lines derived from the ‘Steptoe’ x ‘Morex’ cross, and the two parental lines, were taken by the North American Barley Genome Mapping Project (NABGMP) at 16 environments throughout the barley production areas of the USA and Canada. Four regions of the genome were responsible for most of the differential genotypic expression across environments. They accounted for approximately 50% of the genotypic main effect and 30% of the genotype x environment interaction (GE) sums of squares. The magnitude and sign of AMMI scores for genotypes and sites facilitate inferences about specific interactions. The parallel use of classification (cluster analysis of environments) and ordination (principal component analysis of GE matrix) techniques allowed most of the variation present in the genotype x environment matrix to be summarized in just a few dimensions, specifically four QTLs showing differential adaptation to four clusters of environments. Thus, AMMI genotypic scores, when the genotypes constituted a population suitable for QTL mapping, could provide an adequate way of resolving the magnitude and nature of QTL x environment interactions.

MOLECULAR BREEDING FOR GRAIN YIELD IN BARLEY: AN EVALUATION OF QTL EFFECTS IN A SPRING BARLEY CROSS

Abstract We report results from a breeding strategy designed to accumulate favorable QTL alleles for grain yield identified in the SteptoeבMorex’ (SM) barley germplasm. Two map lines (SM73 and SM145) from the original mapping population were selected based on their marker genotype and QTL structure. When crossed, these lines would be expected to produce progeny with most favorable QTL alleles. One hundred doubled haploid (DH) lines from the F1 hybrid of this cross were genotyped with ten RFLP markers and one morphological marker defining grain yield to monitor QTL segregation. A subset of 24 lines representing various combinations of putatively favorable and unfavorable QTL alleles, together with Steptoe, ‘Morex’, SM73, and SM145, were phenotyped for grain yield in five environments. Multiple regression procedures were used to explore phenotype and genotype relationships. Most target QTLs showed significant effects. However, significance and magnitude of QTL effects and favorable QTL allele phase varied across environments. All target QTLs showed significant QTL-by-environment interaction (QTL×E), and the QTL on chromosome 2 expressed alternative favorable QTL alleles in different environments. Digenic epistatic effects were also detected between some QTL loci. For traits such as grain yield, marker-assisted selection efforts may be better targeted at determining optimum combinations of QTL alleles rather than pyramiding alleles detected in a reference mapping population.

Association Mapping of Agronomic QTLs in U.S. Spring Barley Breeding Germplasm

The use of genome‐wide association studies (GWAS) to detect quantitative trait loci (QTL) controlling complex traits has become a popular approach for studying key traits in crop plants. The goal of this study was to identify the genomic regions of barley (Hordeum vulgare L.) that impact five agronomic and one quality trait in U.S. elite barley breeding lines, as well as to identify markers tightly linked with these loci for further use in barley improvement. Advanced recombinant inbred lines submitted to the U.S. Barley Coordinated Agricultural Project (CAP) were genotyped using a platform of 3072 single nucleotide polymorphism (SNP) markers from the barley oligonucleotide pool assays (BOPAs) 1 and 2. In each of 4 yr, approximately 770 lines were evaluated in a replicated, randomized complete block design under both irrigated and dryland conditions. This gave an overall population size of >3000 lines, which we analyzed in a hierarchical fashion, including analyzing the lines in aggregate using a mixed model to account for population structure and relatedness among the lines. We identified 41 significant marker–trait associations, of which 31 had been previously reported as QTL using biparental mapping techniques; 10 novel marker‐trait associations were identified. The results of this work show that genes with major effects are still segregating in U.S. barley germplasm and demonstrate the utility of GWAS in barley breeding populations.

Verification of barley seed dormancy loci via linked molecular markers

Seed dormancy is a relatively complex trait in barley (Hordeum vulgare L.). Several dormancy loci were identified previously by quantitative trait locus analysis. Three reciprocal crosses were made in the present study between parents carrying specific dormancy alleles via linked molecular markers to verify individual dormancy locus effects and potential expression. Analyses of F2 progenies revealed that the dormancy allele at the locus flanked by the markers Ale and ABC302 on the long arm of chromosome 7 had a major effect on dormancy, and was at least partly epistatic to the dormancy locus in the ABC309-MWG851 interval near the telomere of the long arm of chromosome 7. In the absence of the dormancy allele in the Ale-ABC302 interval, the allele in the ABC309-MWG851 interval exerted moderate to large effects on dormancy. Cytoplasmic effects on dormancy were also observed. The germination percentages of progeny with relatively high levels of dormancy were more variable than those of non-dormant or less-dormant progeny, apparently due to environmental effects. Removal of the dormancy allele in the Ale-ABC302 interval, or introducing the dormancy allele in the ABC309-MWG851 interval, should suffice for adjusting dormancy levels in breeding programs to suit various production situations and end uses. The verification of dormancy loci via linked molecular markers allows manipulation of these loci in applied breeding programs.