The availability of information on the genetic diversity and population structure in wheat (Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity (I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars.

Background Improving grain yield in cereals especially in wheat is a main objective for plant breeders. One of the main constrains for improving this trait is the G × E interaction (GEI) which affects the performance of wheat genotypes in different environments. Selecting high yielding genotypes that can be used for a target set of environments is needed. Phenotypic selection can be misleading due to the environmental conditions. Incorporating information from phenotypic and genomic analyses can be useful in selecting the higher yielding genotypes for a group of environments. Results A set of 270 F3:6 wheat genotypes in the Nebraska winter wheat breeding program was tested for grain yield in nine environments. High genetic variation for grain yield was found among the genotypes. G × E interaction was also highly significant. The highest yielding genotype differed in each environment. The correlation for grain yield among the nine environments was low (0 to 0.43). Genome-wide association study revealed 70 marker traits association (MTAs) associated with increased grain yield. The analysis of linkage disequilibrium revealed 16 genomic regions with a highly significant linkage disequilibrium (LD). The candidate parents’ genotypes for improving grain yield in a group of environments were selected based on three criteria; number of alleles associated with increased grain yield in each selected genotype, genetic distance among the selected genotypes, and number of different alleles between each two selected parents. Conclusion Although G × E interaction was present, the advances in DNA technology provided very useful tools and analyzes. Such features helped to genetically select the highest yielding genotypes that can be used to cross grain production in a group of environments.

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Wheat stripe rust (caused by Puccinia striiformis f. sp. tritici) is a major disease that damages wheat plants and affects wheat yield all over the world. In recent years, stripe rust became a major problem that affects wheat yield in Egypt. New races appeared and caused breakdowns in the resistant genotypes. To improve resistance in the Egyptian genotypes, new sources of resistance are urgently needed. In the recent research, a set of 95 wheat genotypes collected from 19 countries, including Egypt, were evaluated for their resistance against the Egyptian race(s) of stripe rust under field conditions in the two growing seasons 2018/2019 and 2019/2020. A high genetic variation was found among the tested genotypes. Single marker analysis was conducted using a subset of 71 genotypes and 424 diversity array technology (DArT) markers, well distributed across the genome. Out of the tested markers, 13 stable markers were identified that were significantly associated with resistance in both years (p-value ≤ 0.05). By using the sequence of the DArT markers, the chromosomal position of the significant DArT markers was detected, and nearby gene models were identified. Two markers on chromosomes 5A and 5B were found to be located within gene models functionally annotated with disease resistance in plants. These two markers could be used in marker-assisted selection for stripe rust resistance under Egyptian conditions. Two German genotypes were carrying the targeted allele of all the significant DArT markers associated with stripe rust resistance and could be used to improve resistance under Egyptian conditions.

Stem rust caused by Puccinia graminis f. sp. tritici Eriks. is an important disease of common wheat globally. The production and cultivation of genetically resistant cultivars are one of the most successful and environmentally friendly ways to protect wheat against fungal pathogens. Seedling screening and genome-wide association study (GWAS) were used to determine the genetic diversity of wheat genotypes obtained on stem rust resistance loci. At the seedling stage, the reaction of the common stem rust race QFCSC in Nebraska was measured in a set of 212 genotypes from F3:6 lines. The results indicated that 184 genotypes (86.8%) had different degrees of resistance to this common race. While 28 genotypes (13.2%) were susceptible to stem rust. A set of 11,911 single-nucleotide polymorphism (SNP) markers was used to perform GWAS which detected 84 significant marker-trait associations (MTAs) with SNPs located on chromosomes 1B, 2A, 2B, 7B and an unknown chromosome. Promising high linkage disequilibrium (LD) genomic regions were found in all chromosomes except 2B which suggested they include candidate genes controlling stem rust resistance. Highly significant LD was found among these 59 significant SNPs on chromosome 2A and 12 significant SNPs with an unknown chromosomal position. The LD analysis between SNPs located on 2A and Sr38 gene reveal high significant LD genomic regions which was previously reported. To select the most promising stem rust resistant genotypes, a new approach was suggested based on four criteria including, phenotypic selection, number of resistant allele(s), the genetic distance among the selected parents, and number of the different resistant allele(s) in the candidate crosses. As a result, 23 genotypes were considered as the most suitable parents for crossing to produce highly resistant stem rust genotypes against the QFCSC.

Wheat (Triticum aestivum L.) is one of the most important crops in the world. Four spike-related traits, namely, spike weight (SW), spike length (SL), the total number of spikelets per spike (TSNS), total kernels per spike (TKNS), and thousand-kernel weight (TKW), were evaluated in 270 F3:6 Nebraska winter wheat lines in two environments (Lincoln and North Platte, NE, USA). All genotypes in both locations exhibited high genetic variation for all yield traits. High positive correlations were observed among all yield-related traits in each location separately. No or low correlation in yield-related traits was observed between the two environments. The broad-sense heritability estimates were 72.6, 72.3, 71.2, 72.3, and 56.1% for SW, SL, TSNS, TKNS, and TKW, respectively. A genome-wide association study (GWAS) was used to identify SNPs associated with yield traits. In the Lincoln environment, 44 markers were found to be significantly associated with spike-related traits (SW, SL, TSNS, TKNS, and TKW), while 41 were detected in North Platte. Due to the strong significant genotype x environment, no common SNP markers were found between the two locations. Gene annotation of the significant markers revealed candidate genes encoded for important proteins that are associated directly or indirectly with yield traits. Such high genetic variation among genotypes is very useful for selection to improve yield traits in each location separately.

Background and aims Pb and Sn concentration increase rapidly due to the industrial revolution and cause a significant reduction in wheat production and productivity. Understanding the genetic control of Pb and Sn tolerance is very important to produce wheat cultivars that are tolerant to such metals. Methods Extensive genetic analyses using genome-wide association study, functional annotation, and gene enrichment were investigated in a set of 103 highly diverse spring wheat genotypes. Kernel traits such as kernel length (KL), kernel diameter (KD), kernel width (KW), and 1000-kernel weight (TKW) were measured under each metal as well as under controlled conditions. Results The GWAS identified a total of 131, 126, and 115 markers that were associated with kernel traits under Ctrl, Pb, and Sn. Moreover, the stress tolerance index (STI) for Pb and Sn was calculated and GWAS revealed 153 and 105 significant markers, respectively. Remarkably, one SNP Ku_c269_2643 located within TraesCS2A02G080700 gene model was found to be associated with KL under the three conditions. The results of gene enrichment revealed three, three, and six gene networks that have an association with the processes involved in kernel formation. The target alleles of all significant markers detected by GWAS were investigated in the most tolerant wheat genotypes to truly select the candidate parents for crossing in future breeding programs. Conclusion This is the first study that unlocked the genetic control of kernel yield under controlled and heavy metals conditions. Understanding the genetic control of kernel traits under heavy metals will accelerate breeding programs to improve wheat tolerance to Pb and Sn.

Barley (Hordeum vulgare L.) thrives in the arid and semi-arid regions of the world; nevertheless, it suffers large grain yield losses due to drought stress. A panel of 426 lines of barley was evaluated in Egypt under deficit (DI) and full irrigation (FI) during the 2019 and 2020 growing seasons. Observations were recorded on the number of days to flowering (NDF), total chlorophyll content (CH), canopy temperature (CAN), grain filling duration (GFD), plant height (PH), and grain yield (Yield) under DI and FI. The lines were genotyped using the 9K Infinium iSelect single nucleotide polymorphisms (SNP) genotyping platform, which resulted in 6913 high-quality SNPs. In conjunction with the SNP markers, the phenotypic data were subjected to a genome-wide association scan (GWAS) using Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK). The GWAS results indicated that 36 SNPs were significantly associated with the studied traits under DI and FI. Furthermore, eight markers were significant and common across DI and FI water regimes, while 14 markers were uniquely associated with the studied traits under DI. Under DI and FI, three (11_10326, 11_20042, and 11_20170) and five (11_20099, 11_10326, 11_20840, 12_30298, and 11_20605) markers, respectively, had pleiotropic effect on at least two traits. Among the significant markers, 24 were annotated to known barley genes. Most of these genes were involved in plant responses to environmental stimuli such as drought. Overall, nine of the significant markers were previously reported, and 27 markers might be considered novel. Several markers identified in this study could enable the prediction of barley accessions with optimal agronomic performance under DI and FI.