Shamseldeen Eltaher1,2, P Stephen Baenziger1, Vikas Belamkar1, Hamdy A Emara2, Ahmed A Nower2, Khaled F M Salem2,3, Ahmad M Alqudah4, Ahmed Sallam5. 1. Department of Agronomy & Horticulture, University of Nebraska-Lincoln, Lincoln, USA. 2. Department of Plant Biotechnology, Genetic Engineering and Biotechnology Research Institute (GEBRI), University of Sadat City (USC), Sadat City, Egypt. 3. Department of Biology, College of Science and Humanitarian Studies, Shaqra University, Qwaieah, Saudi Arabia. 4. Institute of Agricultural and Nutritional Sciences, Martin Luther University Halle-Wittenberg, Betty-Heimann-Str. 3, 06120, Halle (Saale), Germany. 5. Department of Genetics, Faculty of Agriculture, Assiut University, Assuit, 71526, Egypt. amsallam@aun.edu.eg.
Abstract
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.
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.
Authors: Johanna L Smith; Miranda L Wilson; Sara M Nilson; Troy N Rowan; Robert D Schnabel; Jared E Decker; Christopher M Seabury Journal: BMC Genomics Date: 2022-07-16 Impact factor: 4.547
Authors: Nouran M Hasseb; Ahmed Sallam; Mohamed A Karam; Liangliang Gao; Richard R C Wang; Yasser S Moursi Journal: Plant Mol Biol Date: 2022-02-25 Impact factor: 4.076