A population of 96 doubled haploid lines (DHLs) was prepared from F1 plants of the hexaploid wheat cross Chinese Spring x SQ1 (a high abscisic acid-expressing breeding line) and was mapped with 567 RFLP, AFLP, SSR, morphological and biochemical markers covering all 21 chromosomes, with a total map length of 3,522 cM. Although the map lengths for each genome were very similar, the D genome had only half the markers of the other two genomes. The map was used to identify quantitative trait loci (QTLs) for yield and yield components from a combination of 24 site x treatment x year combinations, including nutrient stress, drought stress and salt stress treatments. Although yield QTLs were widely distributed around the genome, 17 clusters of yield QTLs from five or more trials were identified: two on group 1 chromosomes, one each on group 2 and group 3, five on group 4, four on group 5, one on group 6 and three on group 7. The strongest yield QTL effects were on chromosomes 7AL and 7BL, due mainly to variation in grain numbers per ear. Three of the yield QTL clusters were largely site-specific, while four clusters were largely associated with one or other of the stress treatments. Three of the yield QTL clusters were coincident with the dwarfing gene Rht-B1 on 4BS and with the vernalisation genes Vrn-A1 on 5AL and Vrn-D1 on 5DL. Yields of each DHL were calculated for trial mean yields of 6 g plant(-1) and 2 g plant(-1) (equivalent to about 8 t ha(-1) and 2.5 t ha(-1), respectively), representing optimum and moderately stressed conditions. Analyses of these yield estimates using interval mapping confirmed the group-7 effects on yield and, at 2 g plant(-1), identified two additional major yield QTLs on chromosomes 1D and 5A. Many of the yield QTL clusters corresponded with QTLs already reported in wheat and, on the basis of comparative genetics, also in rice. The implications of these results for improving wheat yield stability are discussed.

Previous studies with 95 bread wheat doubled haploid lines (DHLs) from the cross Chinese Spring (CS)xSQ1 trialled over 24 yearxtreatmentxlocations identified major yield quantitative trait loci (QTLs) in homoeologous locations on 7AL and 7BL, expressed mainly under stressed and non-stressed conditions, respectively. SQ1 and CS contributed alleles increasing yield on 7AL and 7BL, respectively. The yield component most strongly associated with these QTLs was grains per ear. Additional results which focus on the 7AL yield QTL are presented here. Trials monitoring agronomic, morphological, physiological, and anatomical traits revealed that the 7AL yield QTL was not associated with differences in flowering time or plant height, but with significant differences in biomass at maturity and anthesis, biomass per tiller, and biomass during tillering. In some trials, flag leaf chlorophyll content and leaf width at tillering were also associated with the QTL. Thus, it is likely that the yield gene(s) on 7AL affects plant productivity. Near-isogenic lines (NILs) for the 7AL yield QTL with CS or SQ1 alleles in an SQ1 background showed the SQ1 allele to be associated with >20% higher yield per ear, significantly higher flag leaf chlorophyll content, and wider flag leaves. Epidermal cell width and distance between leaf vascular bundles did not differ significantly between NILs, so the yield-associated gene may influence the number of cell files across the leaf through effects on cell division. Interestingly, comparative mapping with rice identified AINTEGUMENTA and G-protein subunit genes affecting lateral cell division at locations homologous to the wheat 7AL yield QTL.

The classical Osborne wheat protein fractions (albumins, globulins, gliadins, and glutenins), as well as several proteins from each of the four subunits of gliadin using SDS-PAGE analyses, were determined in the grain of five bread (T. aestivum L.) and five durum wheat (T. durum Desf.) genotypes. In addition, content of tryptophan and wet gluten were analyzed. Gliadins and glutenins comprise from 58.17% to 65.27% and 56.25% to 64.48% of total proteins and as such account for both quantity and quality of the bread and durum wheat grain proteins, respectively. The ratio of gliadin/total glutenin varied from 0.49 to 1.01 and 0.57 to 1.06 among the bread and durum genotypes, respectively. According to SDS-PAGE analysis, bread wheat genotypes had a higher concentration of α + β + γ-subunits of gliadin (on average 61.54% of extractable proteins) than durum wheat (on average 55.32% of extractable proteins). However, low concentration of ω-subunit was found in both bread (0.50% to 2.53% of extractable proteins) and durum (3.65% to 6.99% of extractable proteins) wheat genotypes. On average, durum wheat contained significantly higher amounts of tryptophan and wet gluten (0.163% dry weight (d.w.) and 26.96% d.w., respectively) than bread wheat (0.147% d.w. and 24.18% d.w., respectively).

Genetic analyses and association mapping were performed on a winter wheat core collection of 96 accessions sampled from a variety of geographic origins. Twenty-four agronomic traits were evaluated over 3 years under fully irrigated, rainfed and drought treatments. Grain yield was the most sensitive trait to water deficit and was highly correlated with above-ground biomass per plant and number of kernels per m2. The germplasm was structured into four subpopulations. The association of 46 SSR loci distributed throughout the wheat genome with yield and agronomic traits was analyzed using a general linear model, where subpopulation information was used to control false-positive or spurious marker-trait associations (MTAs). A total of 26, 21 and 29 significant (P < 0.001) MTAs were identified in irrigated, rainfed and drought treatments, respectively. The marker effects ranged from 14.0 to 50.8%. Combined across all treatments, 34 significant (P < 0.001) MTAs were identified with nine markers, and R2 ranged from 14.5 to 50.2%. Marker psp3200 (6DS) and particularly gwm484 (2DS) were associated with many significant MTAs in each treatment and explained the greatest proportion of phenotypic variation. Although we were not able to recognize any marker related to grain yield under drought stress, a number of MTAs associated with developmental and agronomic traits highly correlated with grain yield under drought were identified.