Ahmed Jahoor

Barley disease resistance gene analogs of the NBS-LRR class: identification and mapping

The majority of verified plant disease resistance genes isolated to date are of the NBS-LRR class, encoding proteins with a predicted nucleotide binding site (NBS) and a leucine-rich repeat (LRR) region. We took advantage of the sequence conservation in the NBS motif to clone, by PCR, gene fragments from barley representing putative disease resistance genes of this class. Over 30 different resistance gene analogs (RGAs) were isolated from the barley cultivar Regatta. These were grouped into 13 classes based on DNA sequence similarity. Actively transcribed genes were identified from all classes but one, and cDNA clones were isolated to derive the complete NBS-LRR protein sequences. Some of the NBS-LRR genes exhibited variation with respect to whether and where particular introns were spliced, as well as frequent premature polyadenylation. DNA sequences related to the majority of the barley RGAs were identified in the recently expanded public rice genomic sequence database, indicating that the rice sequence can be used to extract a large proportion of the RGAs from barley and other cereals. Using a combination of RFLP and PCR marker techniques, representatives of all barley RGA gene classes were mapped in the barley genome, to all chromosomes except 4H. A number of the RGA loci map in the vicinity of known disease resistance loci, and the association between RGA S-120 and the nematode resistance locus Ha2on chromosome 2H was further tested by co-segregation analysis. Most of the RGA sequences reported here have not been described previously, and represent a useful resource as candidates or molecular markers for disease resistance genes in barley and other cereals.

Localising QTLs for leaf rust resistance and agronomic traits in barley (Hordeum vulgare L.)

Abstract The Hordeum vulgare accession ’HOR 1063’ was crossed with the barley cultivar Krona, and 220 doubled haploid lines were produced based on this cross. A molecular map was constructed based on RFLP markers. Field trials were performed over 2 years and at two locations. In field trials, resistance to leaf rust by means of artificial infection, heading date, plant height and Kernel weight were assessed. For leaf rust resistance, 4 QTLs were localised, that explained 96.1% of the genetic variation. One QTL on chromosome 4H confirmed a position found in another genetic background and one mapped to the same position as Rph16 on chromosome 2H. All digenic effects decreased the effects of the respective QTLs. In addition to the denso-locus and the hex-v locus, other QTLs influencing heading date, plant length and kernel weight were found in this cross.

Genetic diversity and population structure analysis of European hexaploid bread wheat (Triticum aestivum L.) varieties.

Progress in plant breeding is facilitated by accurate information about genetic structure and diversity. Here, Diversity Array Technology (DArT) was used to characterize a population of 94 bread wheat (Triticum aestivum L.) varieties of mainly European origin. In total, 1,849 of 7,000 tested markers were polymorphic and could be used for population structure analysis. Two major subgroups of wheat varieties, GrI and GrII, were identified using the program STRUCTURE, and confirmed by principal component analysis (PCA). These subgroups were largely separated according to origin; GrI comprised varieties from Southern and Eastern Europe, whereas GrII contained mostly modern varieties from Western and Northern Europe. A large proportion of the markers contributing most to the genetic separation of the subgroups were located on chromosome 2D near the Reduced height 8 (Rht8) locus, and PCR-based genotyping suggested that breeding for the Rht8 allele had a major impact on subgroup separation. Consistently, analysis of linkage disequilibrium (LD) suggested that different selective pressures had acted on chromosome 2D in the two subgroups. Our data provides an overview of the allele composition of bread wheat varieties anchored to DArT markers, which will facilitate targeted combination of alleles following DArT-based QTL studies. In addition, the genetic diversity and distance data combined with specific Rht8 genotypes can now be used by breeders to guide selection of crossing parents.

Identification of resistance genes against powdery mildew in four accessions of Hordeum vulgare ssp. spontaneum

SummaryFour newly detected accessions of wild barley (Hordeumvulgare ssp. spontaneum) resistant to powdery mildew caused by Blumeriagraminis f. sp. hordei were studied with the aim of finding the number of genes/loci conferring the resistance of individual accessions, the type of inheritance of the genes and their relationships to the Mla locus. F2 populations after crosses between the winter variety ‘Tiffany’ and four wild barley accessions and use of microsatellite DNA markers were focused on the identification of individual resistance genes/loci by means of their chromosomal locations. In PI466495, one locus conferring powdery mildew resistance was identified in highly significant linkage with the marker Bmac0213. This location is consistent with the known locus Mla on chromosome 1HS. In the other three accessions the resistance was determined by two independent loci. In PI466197, PI466297 and PI466461, one locus was identified on chromosome 1HS and three new loci were revealed on chromosomes 2HS (highly significant linkage with Bmac0134), 7HS (highly significant linkage with Bmag0021) and 7HL (significant linkage with EBmac0755). Our prospective aim is identification of further linked DNA markers and the exact location of the resistance genes on the barley chromosomes.

Changes in allelic frequency over time in European bread wheat (Triticum aestivum L.) varieties revealed using DArT and SSR markers

A collection of 189 bread wheat landraces and cultivars, primarily of European origin, released between 1886 and 2009, was analyzed using two DNA marker systems. A set of 76 SSR markers and ~7,000 DArT markers distributed across the wheat genome were employed in these analyses. All of the SSR markers were found to be polymorphic, whereas only 2,532 of the ~7,000 DArT markers were polymorphic. A Mantel test between the genetic distances calculated based on the SSR and DArT data showed a strong positive correlation between the two marker types, with a Pearson’s value (r) of 0.66. We assessed the genetic diversity and allelic frequencies among the accessions based on spring- versus winter-wheat type as well as between landraces and cultivars. We also analyzed the changes in genetic diversity and allelic frequencies in these samples over time. We observed separation based on both vernalization type and release date. Interestingly, we detected a decrease in genetic diversity in wheat accessions released over the period from 1960 to 1980. However, our results also showed that modern plant breeding have succeeded in maintaining genetic diversity in modern wheat cultivars. Studying allelic frequencies using SSR and DArT markers over time revealed changes in allelic frequencies for a number of markers that are known to be linked to important traits, which should be useful for genomic screening efforts. Monitoring changes in the frequency of molecular DNA markers over time in wheat cultivars may yield insight into alleles linked to important traits that have been the subject of positive or negative selection in the past and that may be useful for marker-assisted breeding programs in the future.

Optimizing Training Population Size and Genotyping Strategy for Genomic Prediction Using Association Study Results and Pedigree Information. A Case of Study in Advanced Wheat Breeding Lines

Wheat breeding programs generate a large amount of variation which cannot be completely explored because of limited phenotyping throughput. Genomic prediction (GP) has been proposed as a new tool which provides breeding values estimations without the need of phenotyping all the material produced but only a subset of it named training population (TP). However, genotyping of all the accessions under analysis is needed and, therefore, optimizing TP dimension and genotyping strategy is pivotal to implement GP in commercial breeding schemes. Here, we explored the optimum TP size and we integrated pedigree records and genome wide association studies (GWAS) results to optimize the genotyping strategy. A total of 988 advanced wheat breeding lines were genotyped with the Illumina 15K SNPs wheat chip and phenotyped across several years and locations for yield, lodging, and starch content. Cross-validation using the largest possible TP size and all the SNPs available after editing (~11k), yielded predictive abilities (rGP) ranging between 0.5–0.6. In order to explore the Training population size, rGP were computed using progressively smaller TP. These exercises showed that TP of around 700 lines were enough to yield the highest observed rGP. Moreover, rGP were calculated by randomly reducing the SNPs number. This showed that around 1K markers were enough to reach the highest observed rGP. GWAS was used to identify markers associated with the traits analyzed. A GWAS-based selection of SNPs resulted in increased rGP when compared with random selection and few hundreds SNPs were sufficient to obtain the highest observed rGP. For each of these scenarios, advantages of adding the pedigree information were shown. Our results indicate that moderate TP sizes were enough to yield high rGP and that pedigree information and GWAS results can be used to greatly optimize the genotyping strategy.

Survey of Barley and Wheat Diseases in the Central Highlands of Eritrea

Annual surveys of barley and wheat diseases were conducted in Eritrea from 2000 to 2002. The surveys covered six zones of the central highlands where barley and wheat are grown. The main diseases of barley were netform net blotch, spot-form net blotch, leaf rust and scald. Other, less important diseases were loose smut, covered smut, barley stripe and septoria leaf blotch. Wheat was mainly affected by yellow rust and leaf rust. Loose smut, septoria leaf spot and tan spot diseases were less prevalent. The average incidence of these diseases varied according to the zone. Among barley diseases, net blotch incidence was high in four of the six zones surveyed. Leaf rust occurred at medium incidence in five zones. Loose smut was more severe in the southern highland plains, while covered smut was more common in the south-eastern highland terraces. For wheat, yellow rust incidence was high in two zones. Areas with a high incidence of yellow rust were not necessarily those with a high incidence of leaf rust. Leaf rust was important in the south-eastern and western highland terraces and in the western highland plains. The number of diseases found in the same field varied from 2 to 5. The south eastern highland terraces, the western highland terraces and the northern highland terraces had the highest proportions of individual barley fields with three or more diseases.

Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines

Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families.

Genome-Wide Association Studies and Comparison of Models and Cross-Validation Strategies for Genomic Prediction of Quality Traits in Advanced Winter Wheat Breeding Lines

The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number), and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.

Population structure and frequency differences of CYP51 mutations in Zymoseptoria tritici populations in the Nordic and Baltic regions

Septoria tritici blotch caused by the fungus Zymoseptoria tritici (formerly Mycosphaerella graminicola) is one of the most yield-reducing diseases worldwide. Effective disease management involves the use of resistant cultivars and application of fungicides. In this study, the population structure and genetic diversity of 183 Z. tritici isolates from Denmark, Sweden, Finland and the Baltic countries were analysed by molecular markers. In population structure analysis, isolates from Denmark and Sweden were grouped together, whereas isolates from the Baltics and Finland were grouped together. Analysis of genetic diversity and ϕ-values confirmed the division of Nordic and Baltic regions. Danish isolates sampled from different regions and different varieties were not genetically different. However, significant genetic differences were detected between isolates sampled from different years in Denmark and for isolates sampled from specific cultivars in different years. Additionally, the frequency of several known point mutations in the gene cyp51, conferring decreased sensitivity to DMI fungicides, was investigated. Several of the examined mutations were detected at a lower frequency in Baltic isolates compared to Danish and Swedish isolates. Analysis of the Danish population revealed a significant increase in specific mutations over the years. Lastly, some mutations were significantly more frequent in isolates derived from certain varieties. By using different resistance sources in breeding programmes and application of a wide range of fungicides, a sustainable and efficient disease management can be obtained.