Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst) is one of the most destructive diseases of wheat (Triticum aestivum L.) worldwide causing huge yield losses every year. Development and deployment of resistant varieties is the most economical and environment friendly approach for controlling this disease. However, because of the continuous evolution of the pathogen, resistant genes are easily overcome by new virulent Pst races, which necessitates a continuous identification and introgression of resistance genes to develop resistant wheat varieties. To identify effective source of resistance, a genome-wide association study was performed using 426 elite bread wheat genotypes based on 5176 polymorphic Diversity Arrays Technology (DArT) markers. Adult-plant-resistance was evaluated under field conditions for yellow rust resistance for two consecutive years (2014 and 2015) at ICARDA Merchouch station, Morocco. Out of the 426 genotypes, 51.17% were highly resistant with 5–10% level of severity to yellow rust. Genome wide association studies (GWAS) using a mixed linear model (MLM) identified three DArT markers on chromosomes 1B, 2B and 7B which are significantly associated with stripe rust resistance at false discovery rate p ≤ 0.05. BLAST analysis confirmed that the marker 412,394 in chromosome 2B overlapped with two previously reported QTLs (QYrlu.cau-2BS1 Luke and QYrid.ui-2B.1_IDO444). However, the two other markers 542,318 (1B) and 583,038 (5B) were not mapped within any of the previously reported gene/QTL regions; therefore, these markers may represent novel resistance loci for yellow rust. The highly resistant elite genotypes and linked molecular markers are recommended for further gene introgression and pyramiding purposes in the wheat breeding programs after validation.

Globally, over 2 billion people suffer from malnutrition due to inadequate intake of micronutrients. Genomic-assisted breeding is identified as a valuable method to facilitate developing new improved plant varieties targeting grain yield and micronutrient-related traits. In this study, a genome-wide association study (GWAS) and single- and multi-trait-based genomic prediction (GP) analysis was conducted using a set of 252 elite wheat genotypes from the International Center for Agricultural Research in Dry Areas (ICARDA). The objective was to identify linked SNP markers, putative candidate genes and to evaluate the genomic estimated breeding values (GEBVs) of grain yield and micronutrient-related traits.. For this purpose, a field trial was conducted at a drought-prone station, Merchouch, Morocco for 2 consecutive years (2018 and 2019) followed by GWAS and genomic prediction analysis with 10,173 quality SNP markers. The studied genotypes exhibited a significant genotypic variation in grain yield and micronutrient-related traits. The GWAS analysis identified highly significantly associated markers and linked putative genes on chromosomes 1B and 2B for zinc (Zn) and iron (Fe) contents, respectively. The genomic predictive ability of selenium (Se) and Fe traits with the multi-trait-based GP GBLUP model was 0.161 and 0.259 improving by 6.62 and 4.44%, respectively, compared to the corresponding single-trait-based models. The identified significantly linked SNP markers, associated putative genes, and developed GP models could potentially facilitate breeding programs targeting to improve the overall genetic gain of wheat breeding for grain yield and biofortification of micronutrients via marker-assisted (MAS) and genomic selection (GS) methods.

Drought is one of the most important yield-limiting factors in Morocco. Identification and deployment of drought-tolerant wheat varieties are important to cope with the challenge of terminal moisture stress and increase wheat productivity. A panel composed of 200 elite spring bread wheat genotypes was phenotyped for yield and agronomic traits for 2 years (2020 and 2021) in Morocco under rainfed and irrigated environments. The panel was genotyped using 20K SNPs and, after filtration, a total of 15,735 SNP markers were used for a genome-wide association study (GWAS) using a mixed linear model (MLM) to identify marker-trait associations (MTA) and putative genes associated with grain yield and yield-related traits under rainfed and irrigated conditions. Significant differences were observed among the elite genotypes for grain yield and yield-related traits. Grain yield performance ranged from 0.97 to 6.16 t/ha under rainfed conditions at Sidi Al-Aidi station and from 3.31 to 9.38 t/h under irrigated conditions at Sidi Al-Aidi station, while Grain yield at Merchouch station ranged from 2.32 to 6.16 t/h under rainfed condition. A total of 159 MTAs (p < 0.001) and 46 genes were discovered, with 67 MTAs recorded under rainfed conditions and 37 MTAs recorded under irrigated conditions at the Sidi Al-Aidi station, while 55 MTAs were recorded under rainfed conditions at Merchouch station. The marker ‘BobWhite_c2988_493’ on chromosome 2B was significantly correlated with grain yield under rainfed conditions. Under irrigated conditions, the marker ‘AX-94653560’ on chromosome 2D was significantly correlated with grain yield at Sidi Al-Aidi station. The maker ‘RAC875_c17918_321’ located on chromosome 4A, associated with grain yield was linked with the gene TraesCS4A02G322700, which encodes for F-box domain-containing protein. The markers and candidate genes discovered in this study should be further validated for their potential use in marker-assisted selection to generate high-yielding wheat genotypes with drought tolerance.