I. Romagosa

Genotype × environment interaction and adaptation

This chapter has two objectives: first, to discuss implications of genotype by environment interaction (G×E) for breeding and second, to present major statistical models for assessing genotypic adaptation. We concentrate on widely used methodologies and on that which we believe will be extensively applied, but acknowledge the subjective element in such decisions.

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.

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.

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.

INTEGRATING STATISTICAL AND ECOPHYSIOLOGICAL ANALYSES OF GENOTYPE BY ENVIRONMENT INTERACTION FOR GRAIN FILLING OF BARLEY. II. GRAIN GROWTH

In Mediterranean areas, grain growth of temperate cereals often progresses under the harmful influence of drought and high temperature. Genotypic responses are mediated by the specific occurrence of these constraints, thus causing genotype by environment (G × E) interaction. Field experiments were carried out in 12 environments of northern Spain to characterize G × E on grain growth of five six-rowed and five two-rowed barley (Hordeum vulgare L.) cultivars. Grain growth was defined as the result of two components: grain-filling rate (GFR) and grain-filling duration (GFD). Genotypic and environmental descriptors were used as concomitant variables at the levels of the genotypic and environmental factor to partition G × E. For a first exploration of G × E, AMMI (additive main effects and multiplicative interaction) models were used. Subsequently, separate factorial regression models were fitted for GFR and GFD. G × E for GFR could be partially attributed to the joint effect of two pre-anthesis climatic variables (rainfall during heading, and average maximum temperature during jointing). The factorial regression model for GFR explained more than half of the analysis of variance G × E sum of squares with a quarter of its degrees of freedom (d.f.). Overall, six-rowed cultivars were more affected by low rainfall at heading and high temperature during jointing than two-rowed types. The inclusion of these pre-anthesis variables suggests that G × E for GFR could be related to large differences in source/sink balance between two- and six-rowed genotypes at anthesis. The factorial regression model for GFD contained the pre-anthesis climatic covariable ratio of rainfall to total evapotranspirative demand during heading, and the genotypic covariable anthesis date, suggesting that G × E for GFD was related to differences in phenology among genotypes. This model retained about 35% of the analysis of variance G × E sum of squares with fifth of its d.f. The success of the integration of statistical and ecophysiological tools for the explanation of grain filling in barley is discussed.

Inheritance and fine mapping of a major barley seed dormancy QTL

Abstract A major barley seed dormancy locus, SD1, was previously identified along with three others by quantitative trait locus (QTL) analysis in a Steptoe×Morex mapping population. Located in the centromere region of barley chromosome 7 (5H), SD1 shows the largest and most consistent effect on dormancy. Steptoe contributes the dormancy allele at SD1. The objective of this study was to determine the inheritance of and a more precise map location for SD1. A segregating population was designed and generated by marker assisted mating in which only SD1 segregated. The segregation ratio suggested a single Mendelian gene in which the dormancy allele is dominant to the non-dormancy allele at SD1. In addition, near isogenic lines (NIL) for the SD1 chromosome region were generated by molecular marker assisted backcrossing. Statistical analysis of germination percentages of these NIL revealed that there may be a gene cluster of at least three genes in the SD1 locus region. The dormancy locus, presumably SD1 or a part of the SD1 complex, was resolved into a ≈4.4 cM region.

The Spanish barley core collection

Spanish barleys constitute a germplasm group of particular interest for breeding purposes, as Spain has been proposed as a possible centre of origin of the crop. The Spanish National Germplasm Bank (Banco Nacional de Germoplasma, BNG), holds a collection of about 2000 barley accessions, mostly landraces collected in Spain prior to extensive introduction of modern varieties. The objective of this work is to create a core collection of barleys representative of old barley genotypes grown in Spain. The core collection will be constituted by three groups of germplasm: successful old varieties (15); entries in common with previously existing barley core collections (15); and 2-row (8) and 6-row (122) entries from the BNG, for a total of 160 entries. Entries were allocated by stratified sampling in agro-ecological uniform zones of barley cultivation in Spain. Classification of agro-ecological regions for barley was based on historical yield records for Spanish provinces. The number of entries for each region was determined in proportion to the logarithm of historical barley acreage. Final choice of accessions within provinces tried to maximize the diversity and avoid duplications by looking at passport data, and to agronomic evaluation data available for a group of about 900 accessions.

Further evidence supporting Morocco as a centre of origin of barley

Abstract Thirty-five populations of H. spontaneum from nine countries, encompassing almost all the known range of distribution of the species, Afghanistan, Crete (Greece), Cyprus, Iran, Iraq, Israel, Libya, Morocco and Turkey, were studied utilizing RFLP markers (21 probes with three restriction enzymes) distributed across all seven barley chromosomes in an attempt to unveil the genetic dissimilarities existing among them. UPGMA clustering, based on the Nei and Li (1979) similarity coefficient, produced a dendrogram where three clusters could be defined: two with a clear geographical distinction (Morocco and Cyprus) and another one grouping all the Asian/Middle Eastern populations, except for an accession from Iran that clustered separately. These results confirm our previous work and suggest that barley domestication could also have taken place outside the Fertile Crescent, particularly in Morocco.