Fusarium head blight (FHB) is a devastating fungal disease of small-grain cereals that results in severe yield and quality losses. FHB resistance is controlled by resistance components including incidence, field severity, visual rating index, Fusarium damaged kernels (FDKs), and the accumulation of the mycotoxin deoxynivalenol (DON). Resistance conferred by each of these components is partial and must be combined to achieve resistance sufficient to protect wheat from yield losses. In this study, two biparental mapping populations were analyzed in Canadian FHB nurseries and quantitative trait loci (QTL) mapped for the traits listed above. Nine genomic loci, on 2AS, 2BS, 3BS, 4AS, 4AL, 4BS, 5AS, 5AL, and 5BL, were enriched for the majority of the QTL controlling FHB resistance. The previously validated FHB resistance QTL on 3BS and 5AS affected resistance to severity, FDK, and DON in these populations. The remaining seven genomic loci colocalize with flowering time and/or plant height QTL. The QTL on 4B was a major contributor to all field resistance traits and plant height in the field. QTL on 4AL showed contrasting effects for FHB resistance between Eastern and Western Canada, indicating a local adapted resistance to FHB. In addition, we also found that the 2AS QTL contributed a major effect for DON, and the 2BS for FDK, while the 5AL conferred mainly effect for both FDK/DON. Results presented here provide insight into the genetic architecture underlying these resistant components and insight into how FHB resistance in wheat is controlled by a complex network of interactions between genes controlling flowering time, plant height, local adaption, and FHB resistance components.

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Grain protein concentration (GPC) is an important trait in durum cultivar development as a major determinant of the nutritional value of grain and end-use product quality. However, it is challenging to simultaneously select both GPC and grain yield (GY) due to the negative correlation between them. To characterize quantitative trait loci (QTL) for GPC and understand the genetic relationship between GPC and GY in Canadian durum wheat, we performed both traditional and conditional QTL mapping using a doubled haploid (DH) population of 162 lines derived from Pelissier × Strongfield. The population was grown in the field over 5 years and GPC was measured. QTL contributing to GPC were detected on chromosome 1B, 2B, 3A, 5B, 7A, and 7B using traditional mapping. One major QTL on 3A (QGpc.spa-3A.3) was consistently detected over 3 years accounting for 9.4–18.1% of the phenotypic variance, with the favorable allele derived from Pelissier. Another major QTL on 7A (QGpc.spa-7A) detected in 3 years explained 6.9–14.8% of the phenotypic variance, with the beneficial allele derived from Strongfield. Comparison of the QTL described here with the results previously reported led to the identification of one novel major QTL on 3A (QGpc.spa-3A.3) and five novel minor QTL on 1B, 2B and 3A. Four QTL were common between traditional and conditional mapping, with QGpc.spa-3A.3 and QGpc.spa-7A detected in multiple environments. The QTL identified by conditional mapping were independent or partially independent of GY, making them of great importance for development of high GPC and high yielding durum.

Durum wheat is an economically important crop for Canadian farmers. Fusarium head blight (FHB) is one of the most destructive diseases that threatens durum production in Canada. FHB reduces yield and end-use quality and most commonly contaminates the grain with the fungal mycotoxin deoxynivalenol, also known as DON. Serious outbreaks of FHB can occur in durum wheat in Canada, and combining genetic resistance with fungicide application is a cost effective approach to control this disease. However, there is limited variation for genetic resistance to FHB in elite Canadian durum cultivars. To explore and identify useful genetic FHB resistance variation for the improvement of Canadian durum wheat, we assembled an association mapping (AM) panel of diverse durum germplasms and performed genome wide association analysis (GWAS). Thirty-one quantitative trait loci (QTL) across all 14 chromosomes were significantly associated with FHB resistance. On 3BS, a stable QTL with a larger effect for resistance was located close to the centromere of 3BS. Three haplotypes of Fhb1 QTL were identified, with an emmer wheat haplotype contributing to disease susceptibility. The large number of QTL identified here can provide a rich resource to improve FHB resistance in commercially grown durum wheat. Among the 31 QTL most were associated with plant height and/or flower time. QTL 1A.1, 1A.2, 3B.2, 5A.1, 6A.1, 7A.3 were associated with FHB resistance and not associated or only weakly associated with flowering time nor plant height. These QTL have features that would make them good targets for FHB resistance breeding.

Gluten strength is one of the factors that determine the end-use quality of durum wheat and is an important breeding target for this crop. To characterize the quantitative trait loci (QTL) controlling gluten strength in Canadian durum wheat cultivars, a population of 162 doubled haploid (DH) lines segregating for gluten strength and derived from cv. Pelissier × cv. Strongfield was used in this study. The DH lines, parents, and controls were grown in 3 years and two seeding dates in each year and gluten strength of grain samples was measured by sodium dodecyl sulfate (SDS)-sedimentation volume (SV). With a genetic map created by genotyping the DH lines using the Illumina Infinium iSelect Wheat 90K SNP (single nucleotide polymorphism) chip, QTL contributing to gluten strength were detected on chromosome 1A, 1B, 2B, and 3A. Two major and stable QTL detected on chromosome 1A (QGlu.spa-1A) and 1B (QGlu.spa-1B.1) explaining 13.7-18.7% and 25.4-40.1% of the gluten strength variability respectively were consistently detected over 3 years, with the trait increasing alleles derived from Strongfield. Putative candidate genes underlying the major QTL were identified. Two novel minor QTL (QGlu.spa-3A.1 and QGlu.spa-3A.2) with the trait increasing allele derived from Pelissier were mapped on chromosome 3A explaining up to 8.9% of the phenotypic variance; another three minor QTL (QGlu.spa-2B.1, QGlu.spa-2B.2, and QGlu.spa-2B.3) located on chromosome 2B explained up to 8.7% of the phenotypic variance with the trait increasing allele derived from Pelissier. QGlu.spa-2B.1 is a new QTL and has not been reported in the literature. Multi-environment analysis revealed genetic (QTL) × environment interaction due to the difference of effect in magnitude rather than the direction of the QTL. Eleven pairs of digenic epistatic QTL were identified, with an epistatic effect between the two major QTL of QGlu.spa-1A and QGlu.spa-1B.1 detected in four out of six environments. The peak SNPs and SNPs flanking the QTL interval of QGlu.spa-1A and QGlu.spa-1B.1 were converted to Kompetitive Allele Specific PCR (KASP) markers, which can be deployed in marker-assisted breeding to increase the efficiency and accuracy of phenotypic selection for gluten strength in durum wheat. The QTL that were expressed consistently across

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Macrosclereid cells, which are a layer in the seed coat of Medicago truncatula, accumulate large amounts of phytochemicals during their development. But little is known about the complex and dynamic changes during macrosclereid cell development. To characterize the phytochemicals and the related gene expression during the development of M. truncatula macrosclereid cells, a high performance liquid chromatography-mass spectrometry (HPLC-MS) assay and microarray study were conducted on transcriptome changes from macrosclereid cell during seed development. A total of 16 flavonoids by HPLC-MS and 4861 genes exhibited significant differences at transcript levels by microarray analysis were identified for macrosclerid cells at six different time points during seed development. 815 abiotic and biotic stress genes, 223 transcriptional factors (TFs), and 155 annotated transporter proteins exhibited differential expression during the development of macrosclereid cells. A total of 102 genes were identified as involved in flavonoid biosynthesis, phenypropanoid biosynthesis, and flavone and flavonol biosynthesis. We performed a weighted gene co-regulatory network (WGCNA) to analyze the gene-flavonoid association and rebuilt the gene regulatory network during macrosclereid cell development. Our studies revealed that macrosclereid cells are, beside as the first barrier of defense against diseases, an excellent model system to investigate the regulatory network that governs flavonoid biosynthesis.