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 (F_3:6) 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.

Understanding the population structure and genetic diversity is a very important goal to improve the economic value of crops. In rice, a loss of genetic diversity in the last few centuries is observed. To address this challenge, a set of 22 lines from three different regions – India (two), and Philippines (six), and Egypt (14) – were used to assess the genetic diversity and the features of population structure. These genotypes were analyzed using 106 SSR alleles that showed a clear polymorphism among the lines. Genetic diversity was estimated based on the number of different alleles, polymorphism information content (PIC), and gene diversity. A total of 106 SSR alleles was identified from the 23 SSR loci and used to study the population structure and carry out a cluster analysis. All SSR loci showed a wide range of the number of different alleles extended from two (one loci) to seven alleles (three loci). Five and eight loci showed high PIC and gene diversity (≥ 0.70), respectively. The results of population structure are in agreement with cluster analysis results. Both analyses revealed two different subpopulations (G1 and G2) with different genetic properties in number of private alleles, number of different alleles (Na), number of effective alleles (Ne), expected heterozygosity (He), and Shannon's Information Index (SII). Our findings indicate that five SSR loci (RM 111, RM 307, RM 22, RM 19, and RM 271) could be used in breeding programs to enhance the marker-assisted selection through QTL mapping and association studies. A high genetic diversity found between genotypes which can be exploited to improve and produce rice cultivars for important traits (e.g. high agronomic features and tolerance to biotic or/and abiotic stresses).

Quantitative trait loci (QTL) analysis was carried out with a set of 114 recombinant inbred lines (RILs) from the International Triticeae Mapping Initiative (ITMI) population of ‘W7984’ × ‘Opata 85’ to identify genomic regions controlling traits related to post-anthesis drought tolerance of wheat (\ud Triticum aestivum\ud L.). In two experiments performed in Gatersleben in 2001 and 2003, the amount stem reserves mobilisation was estimated by measuring of changes in 1000-grain weight after chemical desiccation treatment. QTLs for stem reserves mobilisation \ud (Srm)\ud were mapped on chromosomes 2D, 5D and 7D. The mapping positions obtained in the present investigation are discussed with respect to studies on drought tolerance performed in wheat previously. QTLs for drought tolerance preferentially appeared in homoeologous regions at distal parts of the group 7 chromosomes

Background and objective: Investigation on genetic variability and correlation study between yield and its components of genotypes on rice may increase the opportunity to exploit its potential which will help meet the demand of high grain yield and nutrition supply. The current study aimed to determine correlation and path coefficients between twenty-two Egyptian and exotic rice genotypes to establish selection criteria which might help to develop genotypes for high yielding.Materials and methods: Twenty-two Egyptian and exotic rice genotypes were evaluated through seven agronomic traits. Agronomic data were collected during the two successive rice growing seasons, 2017 and 2018. The matrix of phenotypic correlations was estimated and analyzed into direct and indirect effects through path coefficient analysis.Results: Results showed that grain yield per plant had a high positive and significant correlation (p ≤ 0.01) with panicle number per plant, full grain number per panicle, and 1000 grain weight, 0.791**, 0.670**, and0.766**, respectively. As expected, there was a negative correlation (p ≤ 0.05) between days to heading and panicle number per plant (r = – 0.496*) and with1000 grain weight (r = – 0.433*). Path coefficient analysis showed that despite high positive and significant correlation (p ≤ 0.01) between grain yield per plant and many variables, a small number of these correlations was verified to have a relationship of cause and effect. Variables with positive and significant correlation and with a high direct effect on grain yield per plant were 1000 grain weight (0.5107 direct effects) followed by panicle number per plant (0.4003), and full grain number per panicle (0.3028).Conclusion: The three traits (1000 grain weight, panicle number per plant, and full grain number per panicle) are the most important variables for use in grain yield per plant assessment programs as selection indices because they have positive and significant correlations and direct and/or indirect effect on the correlation value of the increased rice grain yield production. Hence, for increasing grain yield, the direct selection of genotypes based on positively correlated traits will be more fruitful while planning any rice breeding program to achieve higher grain yield in rice.