CDC Terrain Canada Prairie Spring Red Wheat

CDC Terrain, a hard red spring wheat (Triticum aestivum L.), is adapted to the wheat growing regions of Western Canada and is eligible for the Canada Prairie Spring Red (CPSR) market class. This conventional height wheat combines high grain yield with early maturity, intermediate resistance to Fusarium head blight (FHB), and outstanding milling properties. CDC Terrain is resistant to leaf rust, stripe rust and loose smut, moderately resistant to stem rust and common bunt, and demonstrated end-use quality suitable for the CPSR market class.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author

CDC Evident durum wheat

CDC Evident durum wheat (Triticum turgidum L. subsp. durum) is adapted to the durum production area of the Canadian prairies. This conventional height durum wheat cultivar combines high grain yield with acceptable time to maturity, straw strength, disease resistance, and end-use suitability. CDC Evident is resistant to leaf, stem and stripe rusts, and common bunt, and expresses end-use quality suitable for the Canada Western Amber Durum (CWAD) class.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author

Multi-locus genome-wide association studies reveal the genetic architecture of Fusarium head blight resistance in durum wheat

Durum wheat is more susceptible to Fusarium head blight (FHB) than other types or classes of wheat. The disease is one of the most devastating in wheat; it reduces yield and end-use quality and contaminates the grain with fungal mycotoxins such as deoxynivalenol (DON). A panel of 265 Canadian and European durum wheat cultivars, as well as breeding and experimental lines, were tested in artificially inoculated field environments (2019–2022, inclusive) and two greenhouse trials (2019 and 2020). The trials were assessed for FHB severity and incidence, visual rating index, Fusarium-damaged kernels, DON accumulation, anthesis or heading date, maturity date, and plant height. In addition, yellow pigment and protein content were analyzed for the 2020 field season. To capture loci underlying FHB resistance and related traits, GWAS was performed using single-locus and several multi-locus models, employing 13,504 SNPs. Thirty-one QTL significantly associated with one or more FHB-related traits were identified, of which nine were consistent across environments and associated with multiple FHB-related traits. Although many of the QTL were identified in regions previously reported to affect FHB, the QTL QFhb-3B.2, associated with FHB severity, incidence, and DON accumulation, appears to be novel. We developed KASP markers for six FHB-associated QTL that were consistently detected across multiple environments and validated them on the Global Durum Panel (GDP). Analysis of allelic diversity and the frequencies of these revealed that the lines in the GDP harbor between zero and six resistance alleles. This study provides a comprehensive assessment of the genetic basis of FHB resistance and DON accumulation in durum wheat. Accessions with multiple favorable alleles were identified and will be useful genetic resources to improve FHB resistance in durum breeding programs through marker-assisted recurrent selection and gene stacking

Qtl Mapping Of Resistance To Race Ug99 Of Puccinia Graminis F. Sp Tritici In Durum Wheat (Triticum Durum Desf.)

Stem rust caused by Puccinia graminis f. sp. tritici was historically one of the most destructive diseases of wheat worldwide. The evolution and rapid migration of race TTKSK (Ug99) and derivatives, first detected in Uganda in 1999, are of international concern due to the virulence of these races to widely used stem rust resistance genes. In attempts to identify quantitative trait loci (QTL) linked with resistance to stem rust race Ug99, 95 recombinant inbred lines that were developed from a cross between two durum wheat varieties, Kristal and Sebatel, were evaluated for reaction to stem rust. Seven field trials at two locations were carried out in main and off seasons. In addition to the natural infection, the nursery was also artificially inoculated with urediniospores of stem rust race Ug99 and a mixture of locally collected stem rust urediniospores. A genetic map was constructed based on 207 simple sequence repeat (SSR) and two sequence tagged site loci. Using composite interval mapping, nine QTL for resistance to stem rust were identified on chromosomes 1AL, 2AS, 3BS, 4BL, 5BL, 6AL 7A, 7AL and 7BL. These results suggest that durum wheat resistance to stem rust is oligogenic and that there is potential to identify previously uncharacterized resistance genes with minor effects. The SSR markers that are closely linked to the QTL can be used for marker-assisted selection for stem rust resistance in durum wheat

Genomic selection for grain yield and quality traits in durum wheat

The prediction accuracies of genomic selection depend on several factors, including the genetic architecture of target traits, the number of traits considered at a given time, and the statistical models. Here, we assessed the potential of single-trait (ST) and multi-trait (MT) genomic prediction models for durum wheat on yield and quality traits using a breeding panel (BP) of 170 varieties and advanced breeding lines, and a doubled-haploid (DH) population of 154 lines. The two populations were genotyped with the Infinium iSelect 90K SNP assay and phenotyped for various traits. Six ST-GS models (RRBLUP, G-BLUP, BayesA, BayesB, Bayesian LASSO, and RKHS) and three MT prediction approaches (MTBayesA, MT-Matrix, and MT-SI approaches which use economic selection index as a trait value) were applied for predicting yield, protein content, gluten index, and alveograph measures. The ST prediction accuracies ranged from 0.5 to 0.8 for the various traits and models and revealed comparable prediction accuracies for most of the traits in both populations, except BayesA and BayesB, which better predicted gluten index, tenacity, and strength in the DH population. The MT-GS models were more accurate than the ST-GS models only for grain yield in the BP. Using BP as a training set to predict the DH population resulted in poor predictions. Overall, all the six ST-GS models appear to be applicable for GS of yield and gluten strength traits in durum wheat, but we recommend the simple computational models RR-BLUP or GBLUP for predicating single trait and MT-SI for predicting yield and protein simultaneously

CDC Reign Canada Prairie Spring Red Wheat

CDC Reign, a hard red spring wheat (Triticum aestivum L.), is adapted to the wheat growing regions of Western Canada and is eligible for the Canada Prairie Spring Red (CPSR) market class. This conventional height wheat combines high grain yield and grain protein concentration with strong straw, intermediate resistance to Fusarium head blight (FHB) and excellent milling properties. CDC Reign is resistant to leaf rust and moderately resistant to stem rust and demonstrated end-use quality suitable for the CPSR market class.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author

CDC Vantta durum wheat

CDC Vantta durum wheat (Triticum turgidum L. subsp. durum) is adapted to the durum production area of the Canadian prairies. CDC Vantta combines high grain yield potential, strong straw, and a semi-dwarf growth habit. CDC Vantta is resistant to leaf and stripe rusts and common bunt and expresses high yellow pigment in the grain and superior pasta color compared to check cultivars. CDC Vantta has low cadmium concentration and is eligible for grades of the Canada Western Amber Durum class.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author

Effect of Co-segregating Markers on High-Density Genetic Maps and Prediction of Map Expansion Using Machine Learning Algorithms

Advances in sequencing and genotyping methods have enable cost-effective production of high throughput single nucleotide polymorphism (SNP) markers, making them the choice for linkage mapping. As a result, many laboratories have developed high-throughput SNP assays and built high-density genetic maps. However, the number of markers may, by orders of magnitude, exceed the resolution of recombination for a given population size so that only a minority of markers can accurately be ordered. Another issue attached to the so-called ‘large p, small n’ problem is that high-density genetic maps inevitably result in many markers clustering at the same position (co-segregating markers). While there are a number of related papers, none have addressed the impact of co-segregating markers on genetic maps. In the present study, we investigated the effects of co-segregating markers on high-density genetic map length and marker order using empirical data from two populations of wheat, Mohawk × Cocorit (durum wheat) and Norstar × Cappelle Desprez (bread wheat). The maps of both populations consisted of 85% co-segregating markers. Our study clearly showed that excess of co-segregating markers can lead to map expansion, but has little effect on markers order. To estimate the inflation factor (IF), we generated a total of 24,473 linkage maps (8,203 maps for Mohawk × Cocorit and 16,270 maps for Norstar × Cappelle Desprez). Using seven machine learning algorithms, we were able to predict with an accuracy of 0.7 the map expansion due to the proportion of co-segregating markers. For example in Mohawk × Cocorit, with 10 and 80% co-segregating markers the length of the map inflated by 4.5 and 16.6%, respectively. Similarly, the map of Norstar × Cappelle Desprez expanded by 3.8 and 11.7% with 10 and 80% co-segregating markers. With the increasing number of markers on SNP-chips, the proportion of co-segregating markers in high-density maps will continue to increase making map expansion unavoidable. Therefore, we suggest developers improve linkage mapping algorithms for efficient analysis of high-throughput data. This study outlines a practical strategy to estimate the IF due to the proportion of co-segregating markers and outlines a method to scale the length of the map accordingly