Search

Key message Malt for craft “all-malt” brewing can have high quality, PHS resistance, and malted in normal timeframes. Canadian style adjunct malt is associated with PHS susceptibility. Abstract Expansion of malting barley production into non-traditional growing regions and erratic weather has increased the demand for preharvest sprouting (PHS) resistant, high quality malting barley cultivars. This is hindered by the relatively unknown relationships between PHS resistance and malting quality. Here we present a three-year study of malting quality and germination at different after-ripening durations post physiological maturity. Malting quality traits alpha amylase (AA) and free amino nitrogen (FAN) and germination rate at six days post PM shared a common association with a SNP in HvMKK3 on chromosome 5H in the Seed Dormancy 2 (SD2) region responsible for PHS susceptibility. Soluble protein (SP) and soluble over total protein (S/T) both shared a common association with a marker in the SD2 region. Significant genetic correlations between PHS resistance and the malting quality traits AA, FAN, SP, S/T were detected across and within HvMKK3 allele groups. High adjunct malt quality was related to PHS susceptibility. Selection for PHS resistance led to a correlated response in malting quality traits. Results strongly suggest pleiotropy of HvMKK3 on malting quality traits and that the classic “Canadian-style” malt is caused by a PHS susceptible allele of HvMKK3. PHS susceptibility appears to benefit the production of malt intended for adjunct brewing, while PHS resistance is compatible with all-malt brewing specifications. Here we present our analysis on the effect of combining complexly inherited and correlated traits with contrasting goals to inform breeding practice in malting barley, the general principles of which can be extended to other breeding programs.

KEY MESSAGE HvMKK3 alleles are temperature sensitive and are major contributors to environmental stability of preharvest sprouting in barley. Preharvest sprouting (PHS) can severely damage barley (Hordeum vulgare L.) malting quality, but PHS resistance is often negatively correlated with malting quality. Seed dormancy is closely related to PHS. Increased temperature during grain fill can decrease seed dormancy in barley, but genetic components of seed dormancy temperature sensitivity are poorly understood. Six years of PHS data were used to fit quantitative trait locus (QTL) x environment mixed models incorporating marker data from seed dormancy genes HvAlaAT1, HvGA20ox1, and HvMKK3 and weather covariates in spring and winter two-row malting barley. Variation in winter barley PHS was best modeled by average temperature range during grain fill and spring barley PHS by total precipitation during grain fill. Average high temperature during grain fill also accurately modeled PHS for both datasets. A highly non-dormant HvMKK3 allele determined baseline PHS susceptibility and HvAlaAT1 interactions with multiple HvMKK3 alleles conferred environmental sensitivity. Polygenic variation for PHS within haplotype was detected. Residual genotype and QTL by environment interaction variance indicated additional environmental and genetic factors involved in PHS. These models provide insight into genotype and environmental regulation of barley seed dormancy, a method for PHS forecasting, and a tool for breeders to improve PHS resistance.

Genomic selection (GS) models have been validated for many quantitative traits in wheat (Triticum aestivum L.) breeding. However, those models are mostly constrained within the same growing cycle and the extension of GS to the case of across cycles has been a challenge, mainly due to the low predictive accuracy resulting from two factors: reduced genetic relationships between different families and augmented environmental variances between cycles. Using the data collected from diverse field conditions at the International Wheat and Maize Improvement Center, we evaluated GS for grain yield in three elite yield trials across three wheat growing cycles. The objective of this project was to employ the secondary traits, canopy temperature, and green normalized difference vegetation index, which are closely associated with grain yield from high-throughput phenotyping platforms, to improve prediction accuracy for grain yield. The ability to predict grain yield was evaluated reciprocally across three cycles with or without secondary traits. Our results indicate that prediction accuracy increased by an average of 146% for grain yield across cycles with secondary traits. In addition, our results suggest that secondary traits phenotyped during wheat heading and early grain filling stages were optimal for enhancing the prediction accuracy for grain yield.

Key message Genome-wide association mapping in conjunction with population sequencing map and Ensembl plants was used to identify markers/candidate genes linked to leaf rust, stripe rust and tan spot resistance in wheat. Abstract Leaf rust (LR), stripe rust (YR) and tan spot (TS) are some of the important foliar diseases in wheat (Triticum aestivum L.). To identify candidate resistance genes for these diseases in CIMMYT’s (International Maize and Wheat Improvement Center) International bread wheat screening nurseries, we used genome-wide association studies (GWAS) in conjunction with information from the population sequencing map and Ensembl plants. Wheat entries were genotyped using genotyping-by-sequencing and phenotyped in replicated trials. Using a mixed linear model, we observed that seedling resistance to LR was associated with 12 markers on chromosomes 1DS, 2AS, 2BL, 3B, 4AL, 6AS and 6AL, and seedling resistance to TS was associated with 14 markers on chromosomes 1AS, 2AL, 2BL, 3AS, 3AL, 3B, 6AS and 6AL. Seedling and adult plant resistance (APR) to YR were associated with several markers at the distal end of chromosome 2AS. In addition, YR APR was also associated with markers on chromosomes 2DL, 3B and 7DS. The potential candidate genes for these diseases included several resistance genes, receptor-like serine/threonine-protein kinases and defense-related enzymes. However, extensive LD in wheat that decays at about 5 × 107 bps, poses a huge challenge for delineating candidate gene intervals and candidates should be further mapped, functionally characterized and validated. We also explored a segment on chromosome 2AS associated with multiple disease resistance and identified seventeen disease resistance linked genes. We conclude that identifying candidate genes linked to significant markers in GWAS is feasible in wheat, thus creating opportunities for accelerating molecular breeding. Electronic supplementary material The online version of this article (10.1007/s00122-018-3086-6) contains supplementary material, which is available to authorized users.

Greenbug and Hessian fly are important pests that decrease wheat production worldwide. We developed and validated breeder-friendly KASP markers for marker-assisted breeding to increase selection efficiency. Greenbug (Schizaphis graminum Rondani) and Hessian fly [Mayetiola destructor (Say)] are two major destructive insect pests of wheat (Triticum aestivum L.) throughout wheat production regions in the USA and worldwide. Greenbug and Hessian fly infestation can significantly reduce grain yield and quality. Breeding for resistance to these two pests using marker-assisted selection (MAS) is the most economical strategy to minimize losses. In this study, doubled haploid lines from the Synthetic W7984 × Opata M85 wheat reference population were used to construct linkage maps for the greenbug resistance gene Gb7 and the Hessian fly resistance gene H32 with genotyping-by-sequencing (GBS) and 90K array-based single nucleotide polymorphism (SNP) marker data. Flanking markers were closely linked to Gb7 and H32 and were located on chromosome 7DL and 3DL, respectively. Gb7-linked markers (synopGBS773 and synopGBS1141) and H32-linked markers (synopGBS901 and IWB65911) were converted into Kompetitive Allele Specific PCR (KASP) assays for MAS in wheat breeding. In addition, comparative mapping identified syntenic regions in Brachypodium distachyon, rice (Oryza sativa), and sorghum (Sorghum bicolor) for Gb7 and H32 that can be used for fine mapping and map-based cloning of the genes. The KASP markers developed in this study are the first set of SNPs tightly linked to Gb7 and H32 and will be very useful for MAS in wheat breeding programs and future genetic studies of greenbug and Hessian fly resistance.

Fine mapping by recombinant backcross populations revealed that a preharvest sprouting QTL on 2B contained two QTLs linked in coupling with different effects on the phenotype. Wheat preharvest sprouting (PHS) occurs when grain germinates on the plant before harvest, resulting in reduced grain quality. Previous mapping of quantitative trait locus (QTL) revealed a major PHS QTL, QPhs.cnl-2B.1, located on chromosome 2B significant in 16 environments that explained from 5 to 31 % of the phenotypic variation. The objective of this project was to fine map the QPhs.cnl-2B.1 interval. Fine mapping was carried out in recombinant backcross populations (BC1F4 and BC1F5) that were developed by backcrossing selected doubled haploids to a recurrent parent and self-pollinating the BC1F4 and BC1F5 generations. In each generation, three markers in the QPhs.cnl-2B.1 interval were used to screen for recombinants. Fine mapping revealed that the QPhs.cnl-2B.1 interval contained two PHS QTLs linked in coupling. The distal PHS QTL, located between Wmc453c and Barc55, contributed 8 % of the phenotypic variation and also co-located with a major seed dormancy QTL determined by germination index. The proximal PHS QTL, between Wmc474 and CNL415-rCDPK, contributed 16 % of the variation. Several candidate genes including Mg-chelatase H subunit family protein, GTP-binding protein and calmodulin/Ca2+-dependent protein kinase were linked to the PHS QTL. Although many recombinant lines were identified, the lack of polymorphism for markers in the QTL interval prevented the localization of the recombination breakpoints and identification of the gene underlying the phenotype.

Development of models to predict genotype by environment interactions, in unobserved environments, using environmental covariates, a crop model and genomic selection. Application to a large winter wheat dataset. Genotype by environment interaction (G*E) is one of the key issues when analyzing phenotypes. The use of environment data to model G*E has long been a subject of interest but is limited by the same problems as those addressed by genomic selection methods: a large number of correlated predictors each explaining a small amount of the total variance. In addition, non-linear responses of genotypes to stresses are expected to further complicate the analysis. Using a crop model to derive stress covariates from daily weather data for predicted crop development stages, we propose an extension of the factorial regression model to genomic selection. This model is further extended to the marker level, enabling the modeling of quantitative trait loci (QTL) by environment interaction (Q*E), on a genome-wide scale. A newly developed ensemble method, soft rule fit, was used to improve this model and capture non-linear responses of QTL to stresses. The method is tested using a large winter wheat dataset, representative of the type of data available in a large-scale commercial breeding program. Accuracy in predicting genotype performance in unobserved environments for which weather data were available increased by 11.1 % on average and the variability in prediction accuracy decreased by 10.8 %. By leveraging agronomic knowledge and the large historical datasets generated by breeding programs, this new model provides insight into the genetic architecture of genotype by environment interactions and could predict genotype performance based on past and future weather scenarios.

Association mapping identified quantitative trait loci (QTLs) and the markers linked to pre-harvest sprouting (PHS) resistance in an elite association mapping panel of white winter wheat comprising 198 genotypes. A total of 1,166 marker loci including DArT and SSR markers representing all 21 chromosomes of wheat were used in the analysis. General and mixed linear models were used to analyze PHS data collected over 4 years. Association analysis identified eight QTLs linked with 13 markers mapped on seven chromosomes. A QTL was detected on each arm of chromosome 2B and one each on chromosome arms 1BS, 2DS, 4AL, 6DL, 7BS and 7DS. All except the QTL on 7BS are located in a location similar to previous reports and, if verified, the QTL on 7BS is likely to be novel. Principal components and the kinship matrix were used to account for the presence of population structure but had only a minor effect on the results. Although, none of the QTLs was highly significant across all environments, a QTL on the long arm of chromosome 4A was detected in three different environments and also using the best linear unbiased predictions over years. Although previous reports have identified this as a major QTL, its effects were minor in our biparental mapping populations. The results of this study highlight the benefits of association mapping and the value of using elite material in association mapping for plant breeding programs.

The evolution of a new race of stem rust, generally referred to as Ug99, threatens global wheat production because it can overcome widely deployed resistance genes that had been effective for many years. To identify loci conferring resistance to Ug99 in wheat, a genome-wide association study was conducted using 232 winter wheat breeding lines from the International Winter Wheat Improvement Program. Breeding lines were genotyped with diversity array technology, simple sequence repeat and sequence-tagged site markers, and phenotyped at the adult plant stage for resistance to stem rust in the stem rust resistance screening nursery at Njoro, Kenya during 2009-2011. A mixed linear model was used for detecting marker-trait associations. Twelve loci associated with Ug99 resistance were identified including markers linked to known genes Sr2 and Lr34. Other markers were located in the chromosome regions where no Sr genes have been previously reported, including one each on chromosomes 1A, 2B, 4A and 7B, two on chromosome 5B and four on chromosome 6B. The same data were used for investigating epistatic interactions between markers with or without main effects. The marker csSr2 linked to Sr2 interacted with wPt4930 on 6BS and wPt729773 in an unknown location. Another marker, csLV34 linked to Lr34, also interacted with wPt4930 on 6BS and wPt4916 on 2BS. The frequent involvement of wPt4916 on 2BS and wPt4930 on 6BS in interactions with other significant loci on the same or different chromosomes suggested complex genetic control for adult plant resistance to Ug99 in winter wheat germplasm.

Drought limits cereal yields in several regions of the world and plant water status plays an important role in tolerance to drought. To investigate and understand the genetic and physiological basis of drought tolerance in barley, differentially expressed sequence tags (dESTs) and candidate genes for the drought response were mapped in a population of 167 F8 recombinant inbred lines derived from a cross between "Tadmor" (drought tolerant) and "Er/Apm" (adapted only to specific dry environments). One hundred sequenced probes from two cDNA libraries previously constructed from drought-stressed barley (Hordeum vulgare L., var. Tokak) plants and 12 candidate genes were surveyed for polymorphism, and 33 loci were added to a previously published map. Composite interval mapping was used to identify quantitative trait loci (QTL) associated with drought tolerance including leaf relative water content, leaf osmotic potential, osmotic potential at full turgor, water-soluble carbohydrate concentration, osmotic adjustment, and carbon isotope discrimination. A total of 68 QTLs with a limit of detection scoreor =2.5 were detected for the traits evaluated under two water treatments and the two traits calculated from both treatments. The number of QTLs identified for each trait varied from one to 12, indicating that the genome contains multiple genes affecting different traits. Two candidate genes and ten differentially expressed sequences were associated with QTLs for drought tolerance traits.

Genetic variation present in 64 durum wheat accessions was investigated by using three sources of microsatellite (SSR) markers: EST-derived SSRs (EST-SSRs) and two sources of SSRs isolated from total genomic DNA. Out of 245 SSR primer pairs screened, 22 EST-SSRs and 20 genomic-derived SSRs were polymorphic and used for genotyping. The EST-SSR primers produced high quality markers, but had the lowest level of polymorphism (25%) compared to the other two sources of genomic SSR markers (53%). The 42 SSR markers detected 189 polymorphic alleles with an average number of 4.5 alleles per locus. The coefficient of similarity ranged from 0.28 to 0.70 and the estimates of similarity varied when different sources of SSR markers were used to genotype the accessions. This study showed that EST-derived SSR markers developed in bread wheat are polymorphic in durum wheat when assaying loci of the A and B genomes. A minumum of ten EST-SSRs generated a very low probability of identity (0.36x10(-12)) indicating that these SSRs have a very high discriminatory power. EST-SSR markers directly sample variation in transcribed regions of the genome, which may enhance their value in marker-assisted selection, comparative genetic analysis and for exploiting wheat genetic resources by providing a more-direct estimate of functional diversity.

Durum wheat (Triticum turgidum L. var. durum) is an economically and nutritionally important cereal crop in the Mediterranean region. To further our understanding of durum genome organization we constructed a durum linkage map using restriction fragment length polymorphisms (RFLPs), simple sequence repeats (SSRs) known as Gatersleben wheat microsatellites (GWMs), amplified fragment length polymorphisms (AFLPs), and seed storage proteins (SSPs: gliadins and glutenins). A population of 110 F9 recombinant inbred lines (RILs) was derived from an intraspecific cross between two durum cultivars, Jennah Khetifa and Cham 1. The two parents exhibit contrasting traits for resistance to biotic and abiotic stresses and for grain quality. In total, 306 markers have been placed on the linkage map – 138 RFLPs, 26 SSRs, 134 AFLPs, five SSPs, and three known genes (one pyruvate decarboxylase and two lipoxygenases). The map is 3598 cM long, with an average distance between markers of 11.8 cM, and 12.1% of the markers deviated significantly from the expected Mendelian ratio 1:1. The molecular markers were evenly distributed between the A and B genomes. The chromosome with the most markers is 1B (41 markers), followed by 3B and 7B, with 25 markers each. The chromosomes with the fewest markers are 2A (11 markers), 5A (12 markers), and 4B (15 markers). In general, there is a good agreement between the map obtained and the Triticeae linkage consensus maps. This intraspecific map provides a useful tool for marker-assisted selection and map-based breeding for resistance to biotic and abiotic stresses and for improvement of grain quality. L'articolo è disponibile sul sito dell'editore: http://www.springerlink.com

Oat groats are unique among cereals for the high level and the embryo-plus-endosperm localization of lipids. Genetic manipulation of groat quality traits such as oil is desired for optimizing the value of oat in human and livestock diets. A locus having a major effect on oil content in oat groats was located on linkage group 11 by single-factor analysis of variance, simple interval mapping and simplified composite interval mapping. A partial oat cDNA clone for plastidic acetyl-CoA carboxylase (ACCase), which catalyzes the first committed step in de novo fatty acid synthesis, identified a polymorphism linked to this major QTL. Similar QTL and ACCase locus placements were obtained with two recombinant inbred populations, ‘Kanota’בOgle’ (KO) and ‘Kanota’בMarion’ (KM), containing 137 and 139 individual lines, respectively. By having a common parent these populations provide biological replication of the results in that significant genomic regions should be evident in analyses of multiple cross combinations. The KO population was mapped with 150 RFLP loci distributed over the genome and was grown in five diverse environments (locations and years) for measurement of groat oil content. The KM population was mapped with 60 RFLP loci and grown in three environments. The QTL linked to AccaseA on linkage group 11 accounted for up to 48% of the phenotypic variance for groat oil content. These results provide strong support for the hypothesis that ACCase has a major role in determining groat oil content. Other QTLs were identified in both populations which accounted for an additional 10–20% of the phenotypic variance.

Comparative mapping of cDNA clones provides an important foundation for examining structural conservation among the chromosomes of diverse genera and for establishing hypotheses about the relationship between gene structure and function in a wide range of organisms. In this study, “anchor probes” were selected from cDNA libraries developed from rice, oat, and barley that were informative for comparative mapping in the grass family. One thousand eight hundred probes were screened on garden blots containing DNA of rice, maize, sorghum, sugarcane, wheat, barley, and oat, and 152 of them were selected as “anchors” because (1) they hybridized to the majority of target grass species based on Southern analysis, (2) they appeared to be low or single copy in rice, and (3) they helped provide reasonably good genome coverage in all species. Probes were screened for polymorphism on mapping parents, and polymorphic markers were mapped onto existing species-specific linkage maps of rice, oat, maize, and wheat. In wheat, both polymorphic and monomorphic markers could be assigned to chromosomes or chromosome arms based on hybridization to nullitetrasomic and ditelosomic stocks. Linkage among anchored loci allowed the identification of homoeologous regions of these distantly related genomes. Anchor probes were sequenced from both ends, providing an average of 260 bp in each direction, and sequences were deposited in GenBank. BLAST was used to compare the sequences with each other and with a non-redundant protein sequence database maintained at the European Molecular Biology Laboratory (EMBL). Of the anchor probes identified in this study 78% showed significant similarity to protein sequences for known genes with BLASTX scores exceeding 100.

Chromosome 3 displayed the two largest yield QTLs in a previous study of 150 doubled haploid lines derived from a cross of Steptoe and Morex barley varieties. Low-copy number RFLP markers, detected using Southern analysis, are excellent tools for generating robust linkage maps as demonstrated by the Steptoe and Morex map produced by the North American Barley Genome Mapping Project (SM NABGMP). However, this technique can be cumbersome when applied to practically oriented plant breeding programs. In the present report, we demonstrate the conversion of RFLPs to more practically useful PCR-based markers that are co-dominant and allelic to the barley chromosome-3 RFLP markers from which they derive. We have used these sequence-tagged-site (STS) PCR markers to evaluate the putative yield QTL components of the Steptoe chromosome 3 in a Morex backcross population. Headshattering, plant lodging, and yield measurements are reported from five replicated field experiments conducted under diverse growing conditions in Montana. Our study detected significant effects for all three traits in a chromosomal region that evidently corresponds to the larger of the two previously reported chromosome-3 QTLs. However, we failed to detect any yield or other effects which might be coincidental to the second largest yield QTL. The genetic effects of the yield QTL identified in our first backcross breeding population show similar magnitude, environmental interactions, and association with lodging and headshattering QTLs observed in the SM NABGMP experiments. Our study elucidates complex environmental conditioning for headshattering and plant lodging which probably underlie the variable yield effects observed under different growing conditions.

Restriction fragment length polymorphism (RFLP) markers linked to genes controlling Hessian fly resistance from Triticum tauschii (Coss.) Schmal. were identified for two wheat (Triticum aestivum L.) germ plasm lines KS89WGRC3 (C3) and KS89WGRC6 (C6). Forty-six clones with loci on chromosomes of homoeologous group 3 and 28 clones on those of group 6 were surveyed for polymorphisms. Eleven and 12 clones detected T. tauschii loci in the two lines, respectively. Analysis of F2 progenies indicated that the Hessian fly resistance gene H23 identified in C3 is linked to XksuH4 (6.9 cM) and XksuG48 (A) (15.6 cM), located on 6D. The resistance gene H24 in C6 is linked to XcnlBCD451 (5.9 cM), XcnlCD0482 (5.9 cM) and XksuG48 (B) (12.9 cM), located on 3DL.

A chromosomal arm map has been developed for common wheat (Triticum aestivum L. em. Thell.) using aneuploid stocks to locate more than 800 restriction fragments corresponding to 210 low-copy DNA clones from barley cDNA, oat cDNA, and wheat genomic libraries. The number of restriction fragments per chromosome arm correlates moderately well with relative DNA content and length of somatic chromosomes. The chromosomal arm locations of loci detected with 6 different clones support an earlier hypothesis for the occurrence of a two-step translocation (4AL to 5AL, 5AL to 7BS, and 7BS to 4AL) in the ancestral wheat genomes. In addition, 1 clone revealed the presence of a 5AL segment translocated to 4AL. Anomalies in aneuploid stocks were also observed and can be explained by intrahomoeologous recombination and polymorphisms among the stocks. We view the development of this chromosomal arm map as a complement to, rather than as a substitute for, a conventional RFLP linkage map in wheat.