Training population selection and use of fixed effects to optimize genomic predictions in a historical USA winter wheat panel.

KEY MESSAGE: The optimization of training populations and the use of diagnostic markers as fixed effects increase the predictive ability of genomic prediction models in a cooperative wheat breeding panel. Plant breeding programs often have access to a large amount of historical data that is highly unbalanced, particularly across years. This study examined approaches to utilize these data sets as training populations to integrate genomic selection into existing pipelines. We used cross-validation to evaluate predictive ability in an unbalanced data set of 467 winter wheat (Triticum aestivum L.) genotypes evaluated in the Gulf Atlantic Wheat Nursery from 2008 to 2016. We evaluated the impact of different training population sizes and training population selection methods (Random, Clustering, PEVmean and PEVmean1) on predictive ability. We also evaluated inclusion of markers associated with major genes as fixed effects in prediction models for heading date, plant height, and resistance to powdery mildew (caused by Blumeria graminis f. sp. tritici). Increases in predictive ability as the size of the training population increased were more evident for Random and Clustering training population selection methods than for PEVmean and PEVmean1. The selection methods based on minimization of the prediction error variance (PEV) outperformed the Random and Clustering methods across all the population sizes. Major genes added as fixed effects always improved model predictive ability, with the greatest gains coming from combinations of multiple genes. Maximum predictabilities among all prediction methods were 0.64 for grain yield, 0.56 for test weight, 0.71 for heading date, 0.73 for plant height, and 0.60 for powdery mildew resistance. Our results demonstrate the utility of combining unbalanced phenotypic records with genome-wide SNP marker data for predicting the performance of untested genotypes.

Genomic selection for wheat traits and trait stability.

KEY MESSAGE: Based on the estimates of accuracy, genomic selection would be useful for selecting for improved trait values and trait stability for agronomic and quality traits in wheat. Trait values and trait stability estimated by two methods were generally independent indicating a breeder could select for both simultaneously. Genomic selection (GS) is a new marker-assisted selection tool for breeders to achieve higher genetic gain faster and cheaper. Breeders face challenges posed by genotype by environment interaction (GEI) pattern and selecting for trait stability. Obtaining trait stability is costly, as it requires data from multiple environments. There are few studies that evaluate the efficacy of GS for predicting trait stability. A soft winter wheat population of 273 lines was genotyped with 90 K single nucleotide polymorphism markers and phenotyped for four agronomic and seven quality traits. Additive main effect and multiplicative interaction (AMMI) model and  Eberhart and Russell regression (ERR) were used to estimate trait stability. Significant GEI variation was observed and stable lines were identified for all traits in this study. The accuracy of GS ranged from 0.33 to 0.67 for most traits and trait stability. Accuracy of trait stability was greater than trait itself for yield (0.44 using AMMI versus 0.33) and heading date (0.65 using ERR versus 0.56). The opposite trend was observed for the other traits. GS did not predict the stability of the quality traits except for flour protein, lactic acid and softness equivalent. Significant GS accuracy for some trait stability indicated that stability was under genetic control for these traits. The magnitude of GS accuracies for all the traits and most of the trait stability index suggests the possibility of rapid selection for these trait and trait stability in wheat breeding.

Identification of milling and baking quality QTL in multiple soft wheat mapping populations.

KEY MESSAGE: Two mapping approaches were use to identify and validate milling and baking quality QTL in soft wheat. Two LG were consistently found important for multiple traits and we recommend the use marker-assisted selection on specific markers reported here. Wheat-derived food products require a range of characteristics. Identification and understanding of the genetic components controlling end-use quality of wheat is important for crop improvement. We assessed the underlying genetics controlling specific milling and baking quality parameters of soft wheat including flour yield, softness equivalent, flour protein, sucrose, sodium carbonate, water absorption and lactic acid, solvent retention capacities in a diversity panel and five bi-parental mapping populations. The populations were genotyped with SSR and DArT markers, with markers specific for the 1BL.1RS translocation and sucrose synthase gene. Association analysis and composite interval mapping were performed to identify quantitative trait loci (QTL). High heritability was observed for each of the traits evaluated, trait correlations were consistent over populations, and transgressive segregants were common in all bi-parental populations. A total of 26 regions were identified as potential QTL in the diversity panel and 74 QTL were identified across all five bi-parental mapping populations. Collinearity of QTL from chromosomes 1B and 2B was observed across mapping populations and was consistent with results from the association analysis in the diversity panel. Multiple regression analysis showed the importance of the two 1B and 2B regions and marker-assisted selection for the favorable alleles at these regions should improve quality.

Characterization of Fusarium Head Blight Resistance and Deoxynivalenol Accumulation in Hulled and Hulless Winter Barley.

Fusarium head blight (FHB), caused by Fusarium graminearum, is one of the most serious diseases impacting the U.S. barley (Hordeum vulgare) industry. The mycotoxin deoxynivalenol (DON), produced by the pathogen, renders grain unmarketable if concentrations exceed threshold values set for end-use markets. Development of cultivars with improved FHB resistance and reduced DON accumulation is necessary to ensure minimal losses. Elite hulled and hulless genotypes developed by the Virginia Tech winter barley breeding program were screened in inoculated, mist-irrigated FHB nurseries over 2 years at two locations in Virginia to validate resistance levels over years and locations. Results demonstrated that barley genotypes varied significantly for resistance to FHB and DON accumulation. The hulled 'Nomini', hulless 'Eve', and hulless line VA06H-48 were consistently resistant across locations to both FHB and DON accumulation. Screening the genotypes with molecular markers on chromosomes 2H and 6H for FHB and DON revealed quantitative trait loci regions which may confer resistance in the Virginia Tech germplasm. Ongoing and future work with mapping populations seeks to identify novel regions for resistance to FHB and DON accumulation unique to the Virginia Tech breeding program.

Marker-trait associations in Virginia Tech winter barley identified using genome-wide mapping.

Genome-wide association studies (GWAS) provide an opportunity to examine the genetic architecture of quantitatively inherited traits in breeding populations. The objectives of this study were to use GWAS to identify chromosome regions governing traits of importance in six-rowed winter barley (Hordeum vulgare L.) germplasm and to identify single-nucleotide polymorphisms (SNPs) markers that can be implemented in a marker-assisted breeding program. Advanced hulled and hulless lines (329 total) were screened using 3,072 SNPs as a part of the US. Barley Coordinated Agricultural Project (CAP). Phenotypic data collected over 4 years for agronomic and food quality traits and resistance to leaf rust (caused by Puccinia hordei G. Otth), powdery mildew [caused by Blumeria graminis (DC.) E.O. Speer f. sp. hordei Em. Marchal], net blotch (caused by Pyrenophora teres), and spot blotch [caused by Cochliobolus sativus (Ito and Kuribayashi) Drechsler ex Dastur] were analyzed with SNP genotypic data in a GWAS to determine marker-trait associations. Significant SNPs associated with previously described quantitative trait loci (QTL) or genes were identified for heading date on chromosome 3H, test weight on 2H, yield on 7H, grain protein on 5H, polyphenol oxidase activity on 2H and resistance to leaf rust on 2H and 3H, powdery mildew on 1H, 2H and 4H, net blotch on 5H, and spot blotch on 7H. Novel QTL also were identified for agronomic, quality, and disease resistance traits. These SNP-trait associations provide the opportunity to directly select for QTL contributing to multiple traits in breeding programs.

Molecular characterization of field resistance to Fusarium head blight in two US soft red winter wheat cultivars.

In the soft red winter wheat (Triticum aestivum L.) regions of the US, Fusarium head blight (FHB, caused by Fusarium spp.) resistance derived from locally adapted germplasm has been used predominantly. Two soft red winter wheat cultivars, Massey and Ernie, have moderate resistance to FHB. Mapping populations derived from Becker/Massey (B/M) and Ernie/MO 94-317 (E/MO) were evaluated for FHB resistance and other traits in multiple environments. Eight QTL in B/M and five QTL in E/MO were associated with FHB variables including incidence, severity (SEV), index (IND), Fusarium damaged kernels (FDK), deoxynivalenol (DON), and morphological traits flowering time and plant height. Four QTL were common to both populations. Three of them were located at or near known genes: Ppd-D1 on chromosome 2DS, Rht-B1 on 4BS, and Rht-D1 on 4DS. Alleles for dwarf plant height (Rht-B1b and Rht-D1b) and photoperiod insensitivity (Ppd-D1a) had pleiotropic effects in reducing height and increasing FHB susceptibility. The other QTL detected for FHB variables were on 3BL in both populations, 1AS, 1DS, 2BL, and 4DL in B/M, and 5AL (B1) and 6AL in E/MO. The additive effects of FHB variables ranged from 0.4 mg kg(-1) of DON to 6.2 % for greenhouse (GH) SEV in B/M and ranged from 0.3 mg kg(-1) of DON to 8.3 % for GH SEV in E/MO. The 4DS QTL had epistasis with Ppd-D1, Qdon.umc-6AL, and Qht.umc-4BS, and additive × additive × environment interactions with the 4BS QTL for SEV, IND, and FDK in E/MO. Marker-assisted selection might be used to enhance FHB resistance through selection of favorable alleles of significant QTL, taking into account genotypes at Rht-B1b, Rht-D1a and Ppd-D1a.

Resistance to Fusarium Head Blight and Deoxynivalenol Accumulation in Virginia Barley.

Fusarium graminearum (teleomorph Gibberella zeae), is a devastating disease of barley (Hordeum vulgare) in the United States. Recent epidemics of FHB in the mid-Atlantic region have underscored the need to develop new commercial varieties of barley that are resistant to FHB and restrict accumulation of the mycotoxin deoxynivalenol (DON). FHB incidence, FHB index, and DON levels of Virginia hulled and hulless barley genotypes were evaluated over five years (2006 to 2010) in FHB nurseries in Virginia. FHB incidence ranged from 22.5% (2010) to 80.1% (2008), and mean DON levels ranged from 0.5 ± 0.4 (2008) to 2.4 ± 2.1 ppm (2010). Barley genotype played a significant role in determining FHB resistance in 2006 to 2009. DON levels were significantly different among barley genotypes in 2007, 2008, and 2009. FHB incidence was positively correlated with FHB index in all 5 years studied. In 2006 and 2010, FHB incidence and index were positively correlated with DON. Early spike emergence resulted in higher FHB incidence and index in 2007, 2008, and 2010. This preliminary work has identified some promising hulled and hulless barley genotypes for targeted breeding and commercialization efforts in FHB nurseries in the future; 'Eve' (hulless) and 'Thoroughbred' (hulled) ranked among the most FHB resistant genotypes.

Utilizing genomics and historical data to optimize gene pools for new breeding programs: A case study in winter wheat.

With the rapid generation and preservation of both genomic and phenotypic information for many genotypes within crops and across locations, emerging breeding programs have a valuable opportunity to leverage these resources to 1) establish the most appropriate genetic foundation at program inception and 2) implement robust genomic prediction platforms that can effectively select future breeding lines. Integrating genomics-enabled breeding into cultivar development can save costs and allow resources to be reallocated towards advanced (i.e., later) stages of field evaluation, which can facilitate an increased number of testing locations and replicates within locations. In this context, a reestablished winter wheat breeding program was used as a case study to understand best practices to leverage and tailor existing genomic and phenotypic resources to determine optimal genetics for a specific target population of environments. First, historical multi-environment phenotype data, representing 1,285 advanced breeding lines, were compiled from multi-institutional testing as part of the SunGrains cooperative and used to produce GGE biplots and PCA for yield. Locations were clustered based on highly correlated line performance among the target population of environments into 22 subsets. For each of the subsets generated, EMMs and BLUPs were calculated using linear models with the 'lme4' R package. Second, for each subset, TPs representative of the new SC breeding lines were determined based on genetic relatedness using the 'STPGA' R package. Third, for each TP, phenotypic values and SNP data were incorporated into the 'rrBLUP' mixed models for generation of GEBVs of YLD, TW, HD and PH. Using a five-fold cross-validation strategy, an average accuracy of r = 0.42 was obtained for yield between all TPs. The validation performed with 58 SC elite breeding lines resulted in an accuracy of r = 0.62 when the TP included complete historical data. Lastly, QTL-by-environment interaction for 18 major effect genes across three geographic regions was examined. Lines harboring major QTL in the absence of disease could potentially underperform (e.g., Fhb1 R-gene), whereas it is advantageous to express a major QTL under biotic pressure (e.g., stripe rust R-gene). This study highlights the importance of genomics-enabled breeding and multi-institutional partnerships to accelerate cultivar development.

Genetic Characterization of Barley Net Blotch Resistance Genes.

Net blotch, caused by Pyrenophora teres f. teres, is one of the most devastating diseases of barley (Hordeum vulgare). Efficient utilization of available resistance sources is dependent upon successful characterization of genes conditioning resistance in diverse sources. Five net-blotch-resistant parents and one susceptible parent were intercrossed to identify novel resistance genes and postulate gene number and mode of inheritance. Seedling response to isolate ND89-19 was evaluated in a greenhouse test. Results indicate that the resistant spring barley lines CIho 2291 and CIho 5098 and the winter barley cv. Nomini each have single dominant genes for resistance. Resistance in CIho 5098 is governed by the same dominant gene conferring resistance in Nomini. Resistance in CIho 2291 is controlled by one dominant gene which, putatively, is the same gene conferring resistance in ND B112 but differs from the resistance genes carried by the other parents in this study. The resistance gene in Nomini or CIho 5098 could be pyramided with the resistance gene in CIho 2291 or ND B112 to enhance the durability of resistance against a wide spectrum of P. teres isolates.

Physiological and Molecular Traits Associated with Nitrogen Uptake under Limited Nitrogen in Soft Red Winter Wheat.

A sufficient nitrogen (N) supply is pivotal for high grain yield and desired grain protein content in wheat (Triticum aestivum L.). Elucidation of physiological and molecular mechanisms underlying nitrogen use efficiency (NUE) will enhance our ability to develop new N-saving varieties in wheat. In this study, we analyzed two soft red winter wheat genotypes, VA08MAS-369 and VA07W-415, with contrasting NUE under limited N. Our previous study demonstrated that higher NUE in VA08MAS-369 resulted from accelerated senescence and N remobilization in flag leaves at low N. The present study revealed that VA08MAS-369 also exhibited higher nitrogen uptake efficiency (NUpE) than VA07W-415 under limited N. VA08MAS-369 consistently maintained root growth parameters such as maximum root depth, total root diameter, total root surface area, and total root volume under N limitation, relative to VA07W-415. Our time-course N content analysis indicated that VA08MAS-369 absorbed N more abundantly than VA07W-415 after the anthesis stage at low N. More efficient N uptake in VA08MAS-369 was associated with the increased expression of genes encoding a two-component high-affinity nitrate transport system, including four NRT2s and three NAR2s, in roots at low N. Altogether, these results demonstrate that VA08MAS-369 can absorb N efficiently even under limited N due to maintained root development and increased function of N uptake. The ability of VA08MAS-369 in N remobilization and uptake suggests that this genotype could be a valuable genetic material for the improvement of NUE in soft red winter wheat.

Identification of quantitative trait loci associated with nitrogen use efficiency in winter wheat.

Maintaining winter wheat (Triticum aestivum L.) productivity with more efficient nitrogen (N) management will enable growers to increase profitability and reduce the negative environmental impacts associated with nitrogen loss. Wheat breeders would therefore benefit greatly from the identification and application of genetic markers associated with nitrogen use efficiency (NUE). To investigate the genetics underlying N response, two bi-parental mapping populations were developed and grown in four site-seasons under low and high N rates. The populations were derived from a cross between previously identified high NUE parents (VA05W-151 and VA09W-52) and a shared common low NUE parent, 'Yorktown.' The Yorktown × VA05W-151 population was comprised of 136 recombinant inbred lines while the Yorktown × VA09W-52 population was comprised of 138 doubled haploids. Phenotypic data was collected on parental lines and their progeny for 11 N-related traits and genotypes were sequenced using a genotyping-by-sequencing platform to detect more than 3,100 high quality single nucleotide polymorphisms in each population. A total of 130 quantitative trait loci (QTL) were detected on 20 chromosomes, six of which were associated with NUE and N-related traits in multiple testing environments. Two of the six QTL for NUE were associated with known photoperiod (Ppd-D1 on chromosome 2D) and disease resistance (FHB-4A) genes, two were reported in previous investigations, and one QTL, QNue.151-1D, was novel. The NUE QTL on 1D, 6A, 7A, and 7D had LOD scores ranging from 2.63 to 8.33 and explained up to 18.1% of the phenotypic variation. The QTL identified in this study have potential for marker-assisted breeding for NUE traits in soft red winter wheat.

Multi-Trait Genomic Prediction of Yield-Related Traits in US Soft Wheat under Variable Water Regimes.

The performance of genomic prediction (GP) on genetically correlated traits can be improved through an interdependence multi-trait model under a multi-environment context. In this study, a panel of 237 soft facultative wheat (Triticumaestivum L.) lines was evaluated to compare single- and multi-trait models for predicting grain yield (GY), harvest index (HI), spike fertility (SF), and thousand grain weight (TGW). The panel was phenotyped in two locations and two years in Florida under drought and moderately drought stress conditions, while the genotyping was performed using 27,957 genotyping-by-sequencing (GBS) single nucleotide polymorphism (SNP) makers. Five predictive models including Multi-environment Genomic Best Linear Unbiased Predictor (MGBLUP), Bayesian Multi-trait Multi-environment (BMTME), Bayesian Multi-output Regressor Stacking (BMORS), Single-trait Multi-environment Deep Learning (SMDL), and Multi-trait Multi-environment Deep Learning (MMDL) were compared. Across environments, the multi-trait statistical model (BMTME) was superior to the multi-trait DL model for prediction accuracy in most scenarios, but the DL models were comparable to the statistical models for response to selection. The multi-trait model also showed 5 to 22% more genetic gain compared to the single-trait model across environment reflected by the response to selection. Overall, these results suggest that multi-trait genomic prediction can be an efficient strategy for economically important yield component related traits in soft wheat.

Genome-wide association studies for yield-related traits in soft red winter wheat grown in Virginia.

Grain yield is a trait of paramount importance in the breeding of all cereals. In wheat (Triticum aestivum L.), yield has steadily increased since the Green Revolution, though the current rate of increase is not forecasted to keep pace with demand due to growing world population and increasing affluence. While several genome-wide association studies (GWAS) on yield and related component traits have been performed in wheat, the previous lack of a reference genome has made comparisons between studies difficult. In this study, a GWAS for yield and yield-related traits was carried out on a population of 322 soft red winter wheat lines across a total of four rain-fed environments in the state of Virginia using single-nucleotide polymorphism (SNP) marker data generated by a genotyping-by-sequencing (GBS) protocol. Two separate mixed linear models were used to identify significant marker-trait associations (MTAs). The first was a single-locus model utilizing a leave-one-chromosome-out approach to estimating kinship. The second was a sub-setting kinship estimation multi-locus method (FarmCPU). The single-locus model identified nine significant MTAs for various yield-related traits, while the FarmCPU model identified 74 significant MTAs. The availability of the wheat reference genome allowed for the description of MTAs in terms of both genetic and physical positions, and enabled more extensive post-GWAS characterization of significant MTAs. The results indicate a number of promising candidate genes contributing to grain yield, including an ortholog of the rice aberrant panicle organization (APO1) protein and a gibberellin oxidase protein (GA2ox-A1) affecting the trait grains per square meter, an ortholog of the Arabidopsis thaliana mother of flowering time and terminal flowering 1 (MFT) gene affecting the trait seeds per square meter, and a B2 heat stress response protein affecting the trait seeds per head.

Near-infrared analysis of whole kernel barley: comparison of three spectrometers.

This study was conducted to develop calibration models for determining quality parameters of whole kernel barley using a rapid and nondestructive near-infrared (NIR) spectroscopic method. Two hundred and five samples of whole barley grains of three winter-habit types (hulled, malt, and hull-less) produced over three growing seasons and from various locations in the United States were used in this study. Among these samples, 137 were used for calibration and 68 for validation. Three NIR instruments with different resolutions, one Fourier transform instrument (4 cm(-1) resolution), and two dispersive instruments (8 nm and 10 nm bandpass) were utilized to develop calibration models for six components (moisture, starch, beta-glucan, protein, oil, and ash) and the results were compared. Partial least squares regression was used to build models, and various methods for preprocessing of spectral data were used to find the best model. Our results reveal that the coefficient of determination for calibration models (NIR predicted versus reference values) ranged from 0.96 for moisture to 0.79 for beta-glucan. The level of precision of the model developed for each component was sufficient for screening or classification of whole kernel barley, except for beta-glucan. The higher resolution Fourier transform instrument gave better results than the lower resolution instrument for starch and beta-glucan analysis. The starch model was most improved by the increased resolution. There was no advantage of using a higher resolution instrument over a lower resolution instrument for other components. Most of the components were best predicted using first-derivative processing, except for beta-glucan, where second-derivative processing was more informative and precise.

Near-infrared analysis of ground barley for use as a feedstock for fuel ethanol production.

The objective of this study was to explore the potential of near-infrared spectroscopy for determining the compositional quality properties of barley as a feedstock for fuel ethanol production and to compare the prediction accuracy between calibration models obtained using a Fourier transform near-infrared system (FT-NIR) and a dispersive near-infrared system. The total sample set contained 206 samples of three types of barley, hull-less, malt, and hulled varieties, which were grown at various locations in the eastern U.S. from 2002 to 2005 years. A new hull-less barley variety, Doyce, which was specially bred for potential use in ethanol production, was included in the sample set. One hundred and thirty-eight barley samples were used for calibration and sixty-eight were used for validation. Ground barley samples were scanned on both a FTNIR spectrometer (10 000 to 4000 cm(-1) at 4 cm(-1) resolution) and a dispersive NIR spectrometer (400 to 2498 nm at 10 nm resolution), respectively. Six grain components, moisture, starch, beta-glucan, protein, oil, and ash content, were analyzed as parameters of barley quality. Principal component analysis showed that barley samples could be classified by their types: hull-less, malt, and hulled. Partial least squares regression indicated that both FT-NIR and dispersive NIR spectroscopy have the potential to determine quality properties of barley with an acceptable accuracy, except for beta-glucan content. There was no predictive advantage in using a high-resolution FT-NIR instrument over a dispersive system for most components of barley.

Antioxidant properties of Fusarium head blight-resistant and -susceptible soft red winter wheat grains grown in Virginia.

Fusarium head blight (FHB) has emerged as a major threat to wheat crops around the world, and it has been hypothesized that wheat antioxidants may play a role against Fusarium infections. The current study aimed to determine antioxidant properties of FHB-resistant wheat grains as compared to susceptible wheat. The wheat samples were collected from a single growing location (Warsaw, VA) and the same growing season. The results showed that both FHB-resistant and -susceptible wheat grains exerted strong radical scavenging activities against DPPH* radical [0.91-1.53 micromol of Trolox equivalents (TE)/g], peroxyl radical (15.5-24.5 micromol of TE/g), and hydroxyl radical (15.7-35.8 micromol of TE/g). Their total phenolic contents ranged from 888 to 1117 microg of gallic acid equivalents (GAE)/g. Five phenolic acids including ferulic, syringic, vanillic, caffeic, and p-coumaric acids were determined in soluble and insoluble fractions of wheat grains, altogether with a range of 219-389 microg/g. On average, the FHB-resistant wheat group showed significantly higher average values in DPPH* and hydroxyl radicals scavenging activities (30 and 41% higher, respectively) than the FHB-susceptible wheat group.

Production of Ethanol From Newly Developed and Improved Winter Barley Cultivars.

Winter barley has attracted strong interest as a potential feedstock for fuel ethanol production in regions with mild winter climate such as the mid-Atlantic and northeastern USA. Ten recently developed and improved winter barley cultivars and breeding lines including five hulled and five hull-less lines were experimentally evaluated for potential ethanol production. The five hulled barley lines included three released cultivars (Thoroughbred, Atlantic, and Secretariat) and two breeding lines (VA09B-34 and VA11B-4). The five hull-less lines also included three released cultivars (Eve, Dan, and Amaze 10) and two breeding lines (VA08H-65 and VA13H-34). On the average, the hull-less barley cultivars produced more ethanol per unit mass because of their higher starch and ß-glucan contents. However, since the hulled barley cultivars had higher agronomic yield, the potential ethanol production per acre of land for the two types were approximately equal. Among the ten cultivars tested, the hull-less cultivar Amaze 10 was the best one for ethanol production. The ethanol yield values obtained for this cultivar were 2.61 gal per bushel and 292 gal per acre.

Virulence of Blumeria graminis f. sp. tritici Populations in Morocco.

The incidence and severity of powdery mildew, caused by Blumeria graminis f. sp. tritici, have increased in Morocco during the past decade as a result of the introduction and intensive production of a few semidwarf cultivars of bread wheat (Triticum aestivum) and durum wheat (Triticum turgidum) that are genetically uniform, and the increased utilization of nitrogen fertilizers and irrigation. The virulence of the pathogen population has not been characterized in Morocco, and little is known about the spectra and distribution of virulence in B. graminis populations. Such knowledge will facilitate the identification and utilization of effective resistance genes in cultivar development and deployment. Isolates of B. graminis collected in 1999 and 2000 from three Moroccan wheat production areas were analyzed for virulence using a host differential series comprised of 13 known genes conferring resistance to powdery mildew. Segments of primary leaves from 12-day-old seedlings of the wheat differentials were inoculated with isolates of B. graminis derived from a single pustule. Powdery mildew reactions were assessed on a 0 to 9 scale 12 days after inoculation. Virulence frequencies, complexity, and racial composition of the pathogen population were determined. Data were analyzed for associations among pairs and triplets of virulence genes and for distribution of virulence genes among pathotypes. High frequencies of virulence to genes Pm1, Pm3c, Pm3f, Pm4a, pm5, and Pm7 were found over both years and across all three regions. Frequencies of virulence for Pm17 and Pm2 were intermediate, while virulence frequencies for Pm3a, Pm3b, Pm3d, and Pm4b were low. Virulence to Pm8 increased to high levels, while virulence to Pm4a decreased across the area surveyed from 1999 to 2000. The random distribution of virulence genes among patho-types indicates that sexual reproduction contributes to the variability of the pathogen. The Moroccan population of Blumeria graminis f. sp. tritici is composed of complex and highly variable pathotypes (87% of the isolates had five or more virulence genes), and strategies for deployment of resistance genes should take into account this complexity.

A comparison of two milling strategies to reduce the mycotoxin deoxynivalenol in barley.

Winter barley (Hordeum vulgare L.), a potential feedstock for fuel ethanol production, may be contaminated with the trichothecene mycotoxin deoxynivalenol (DON). DON is a threat to feed and food safety in the United States and may become concentrated during the production of distillers dried grains with solubles (DDGS). DDGS is a coproduct of fuel ethanol production and is increasingly being used as feed for domestic animals. Therefore, new strategies to reduce the threat of DON in DDGS need to be developed and implemented for grain destined for fuel ethanol production. It is known that large concentrations of DON accumulate in the hulls of wheat and barley. Consequently, improved methods are needed to carefully remove the hull from the grain and preserve the starchy endosperm. Whole kernels from five Virginia winter barley genotypes were used to evaluate the abilities of two different milling strategies (roller milling and precision milling (FitzMill)) for their ability to remove the hull-enriched tissue from the kernel while maintaining starch levels and reducing DON levels in the endosperm-enriched tissue. After whole kernels were milled, DON and starch levels were quantified in the hull-enriched fractions and endosperm-enriched fractions. Initial milling experiments demonstrated that the precision mill system (6 min run time) is able to reduce more DON than the roller mill but with higher starch losses. The average percent DON removed from the kernel with the roller mill was 36.7% ± 5.5 and the average percent DON removed from the dehulled kernel with the precision mill was 85.1% ± 9.0. Endosperm-enriched fractions collected from the roller mill and precision mill contained starch levels ranging from 49.0% ± 12.1 to 59.1% ± 0.5 and 58.5% ± 1.6 to 65.3% ± 3.9, respectively. On average, the precision mill removed a mass of 23.1% ± 6.8 and resulted in starch losses of 9.6% ± 6.3, but produced an endosperm-enriched fraction with relatively very little average DON (5.5 ± 2.7 µg g(-1)). In contrast, on average, the roller mill removed a mass of 12.2% ± 1.6 and resulted in starch losses of 2.1% ± 0.5, but produced an endosperm-enriched fraction with high average DON (20.7 ± 13.5 µg g(-1)). In a time course precision milling experiment, we tested barley genotypes Nomini, Atlantic, and VA96-44-304 and attempted to reduce the starch loss seen in the first experiment while maintaining low DON concentrations. Decreasing the run time of the precision mill from 5 to 2 min, reduced starch loss at the expense of higher DON concentrations. Aspirated fractions revealed that the precision milled hull-enriched fraction contained endosperm-enriched components that were highly contaminated with DON. This work has important implications for the reduction of mycotoxins such as DON in barley fuel ethanol coproducts and barley enriched animal feeds and human foods.

Conversion of deoxynivalenol to 3-acetyldeoxynivalenol in barley-derived fuel ethanol co-products with yeast expressing trichothecene 3-O-acetyltransferases.

BACKGROUND: The trichothecene mycotoxin deoxynivalenol (DON) may be concentrated in distillers dried grains with solubles (DDGS; a co-product of fuel ethanol fermentation) when grain containing DON is used to produce fuel ethanol. Even low levels of DON (≤ 5 ppm) in DDGS sold as feed pose a significant threat to the health of monogastric animals. New and improved strategies to reduce DON in DDGS need to be developed and implemented to address this problem. Enzymes known as trichothecene 3-O-acetyltransferases convert DON to 3-acetyldeoxynivalenol (3ADON), and may reduce its toxicity in plants and animals. RESULTS: Two Fusarium trichothecene 3-O-acetyltransferases (FgTRI101 and FfTRI201) were cloned and expressed in yeast (Saccharomyces cerevisiae) during a series of small-scale ethanol fermentations using barley (Hordeum vulgare). DON was concentrated 1.6 to 8.2 times in DDGS compared with the starting ground grain. During the fermentation process, FgTRI101 converted 9.2% to 55.3% of the DON to 3ADON, resulting in DDGS with reductions in DON and increases in 3ADON in the Virginia winter barley cultivars Eve, Thoroughbred and Price, and the experimental line VA06H-25. Analysis of barley mashes prepared from the barley line VA04B-125 showed that yeast expressing FfTRI201 were more effective at acetylating DON than those expressing FgTRI101; DON conversion for FfTRI201 ranged from 26.1% to 28.3%, whereas DON conversion for FgTRI101 ranged from 18.3% to 21.8% in VA04B-125 mashes. Ethanol yields were highest with the industrial yeast strain Ethanol Red®, which also consumed galactose when present in the mash. CONCLUSIONS: This study demonstrates the potential of using yeast expressing a trichothecene 3-O-acetyltransferase to modify DON during commercial fuel ethanol fermentation.