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Recent Submissions
Single- and multi-trait genomic prediction and genome-wide association analysis of grain yield and micronutrient-related traits in ICARDA wheat under drought environment
Author(s): Tadesse, Wuletaw; Zakaria, EL Gataa; Rachdad, Fatima Ezzahra; El-Baouchi, Adil; Kehel, Zakaria; Alemu, Admas (Springer (part of Springer Nature) (Springer Open Choice Hybrid Journals))
Date: 2023-10-18
Type: Journal Article
Status: Open access
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.
Genomic selection in plant breeding: Key factors shaping two decades of progress
Author(s): Alemu, Admas; Astrand, Johanna; Montesinos-Lopez, Osval A.; Sanchez, Julio Isidro y; Fernandez-Gonzalez, Javier; Tadesse, Wuletaw; Vetukuri, Ramesh R.; Carlsson, Anders S.; Ceplitis, Alf; Crossa, Jose; Ortiz, Rodomiro; Chawade, Aakash (Elsevier (12 months), 2024-04-01)
Date: 2024-03-12
Type: Journal Article
Status: Open access
Genomic selection, the application of genomic prediction (GP) models to select candidate individuals, has significantly advanced in the past two decades, effectively accelerating genetic gains in plant breeding. This article provides a holistic overview of key factors that have influenced GP in plant breeding during this period. We delved into the pivotal roles of training population size and genetic diversity, and their relationship with the breeding population, in determining GP accuracy. Special emphasis was placed on optimizing training population size. We explored its benefits and the associated diminishing returns beyond an optimum size. This was done while considering the balance between resource allocation and maximizing prediction accuracy through current optimization algorithms. The density and distribution of single-nucleotide polymorphisms, level of linkage disequilibrium, genetic complexity, trait heritability, statistical machine-learning methods, and non-additive effects are the other vital factors. Using wheat, maize, and potato as examples, we summarize the effect of these factors on the accuracy of GP for various traits. The search for high accuracy in GP—theoretically reaching one when using the Pearson’s correlation as a metric—is an active research area as yet far from optimal for various traits. We hypothesize that with ultra-high sizes of genotypic and phenotypic datasets, effective training population optimization methods and support from other omics approaches (transcriptomics, metabolomics and proteomics) coupled with deep-learning algorithms could overcome the boundaries of current limitations to achieve the highest possible prediction accuracy, making genomic selection an effective tool in plant breeding.
Dissection of the Genetic Basis of Genotype by Environment Interactions for Morphological Traits and Protein Content in Winter Wheat Panel Grown in Morocco and Spain
Author(s): El-Baouchi, Adil; Ibriz, Mohammed; Dreisigacker, Susanne; Lopes, Marta S; Sanchez-Garcia, Miguel (MDPI)
Date: 2024-05-27
Type: Journal Article
Status: Open access
To fulfill the growing demand for wheat consumption, it is important to focus on enhancement breeding strategies targeting key parameters such as yield, thousand kernel weight (TKW), quality characteristics including morphological traits, and protein content. These elements are key to the ongoing and future objectives of wheat breeding programs. Prioritizing these factors will effectively help meet the rising demand for wheat, especially given the challenges posed by unpredictable weather patterns. This study evaluated the morphological traits and protein content of 249 winter wheat varieties and advanced lines grown in eleven different environments in Morocco and Spain incorporating three varied sowing dates. The results showed considerable variability in morphological traits and protein content. Significant correlations were observed among various grain traits, with most grain morphological parameters exhibiting negative correlations with protein content. Differences across environments (p ≤ 0.01) in all traits, genotypes, and genotype by environment interaction were significant. A factorial regression analysis revealed significant impacts of environmental conditions on all grain morphological parameters, protein content, and TKW during the three growth stages. The study identified several high-performing and stable genotypes across diverse environments, providing valuable insights for wheat breeding programs such as genotypes 129, 234, 241, and 243. Genome-Wide Association Studies pinpointed 603 significant markers across 11 environments, spread across chromosomes. Among these, 400 markers were linked with at least two traits or observed in at least two different environments. Moreover, twelve marker-trait associations were detected that surpassed the Bonferroni correction threshold. These findings highlight the importance of targeted breeding efforts to enhance wheat quality and adaptability to different environmental conditions.
Field response and genetic variability of elite spring bread wheat (Triticum aestivum L.) genotypes for septoria tritici blotch under natural infection in Northwest Ethiopia
Author(s): Kassie, Molla Mekonnen; Dejene, Tiegist; Desta, Ermias Abate; Aseress, Tazebachew; Tadesse, Wuletaw (Wiley (12 months), 2024-08-01)
Date: 2024-03-11
Type: Journal Article
Status: Timeless limited access
Fungal diseases cause significant yield loss to wheat production. Septoria tritici blotch (STB), caused by the ascomycete fungus Zymoseptoria trtici, is one of the major fungal diseases affecting wheat production worldwide. In Ethiopia, STB is a severe problem that causes significant yield loss in high and mid-altitude wheat-growing areas. The use of resistant varieties is one of the sustainable disease management strategies, particularly for resource-poor farmers in developing countries. Two hundred and fifty bread wheat genotypes were evaluated to identify septoria tritici resistant genotypes and estimate the extent of genetic variability for resistance to STB and other economically important traits using alpha lattice design under natural infestation in two STB hotspot environments. Analysis of variance revealed highly significant differences among genotypes, environment, and genotype × environment interaction for all traits measured. The genetic coefficient of variance was lower than the phenotypic coefficient of variance for all traits studied, and both test environments showed the influence of the environment on trait expression. High and moderate heritability values were observed for the septoria disease severity parameters, indicating that the STB resistance trait was less influenced by the environment. The days to heading and plant height were inversely correlated with disease severity. This suggests that genotypes with tall plant height and long maturity period could be resistant to septoria tritici blotch through escape mechanisms. Four of the genotypes, namely, G-215, G-255, G-257, and G-258, were found to be resistant across all locations. These and other promising genotypes will be used in future breeding programmes to select or develop high-yielding and STB-resistant bread wheat genotypes that can be deployed in septoria tritici blotch-prone areas. Highly susceptible genotypes will also be used as controls for STB resistance breeding programmes.
Genome-wide association study of common resistance to rust species in tetraploid wheat
Author(s): Marone, Daniela; Laidò, Giovanni; Saccomanno, Antonietta; Petruzzino, Giuseppe; Azevedo, Cleber V. Giaretta; De Vita, Pasquale; Mastrangelo, Anna Maria; Gadaleta, Agata; Ammar, Karim; Bassi, Filippo; Wang, Meinan; Chen, Xianming; Rubiales, Diego; Matny, Oadi; J. Steffenson, Brian; Pecchioni, Nicola (Frontiers Media, 2024-01-03)
Date: 2024-01-03
Type: Journal Article
Status: Open access
Rusts of the genus Puccinia are wheat pathogens. Stem (black; Sr), leaf (brown; Lr), and stripe (yellow; Yr) rust, caused by Puccinia graminis f. sp. tritici (Pgt), Puccinia triticina (Pt), and Puccinia striiformis f. sp. tritici (Pst), can occur singularly or in mixed infections and pose a threat to wheat production globally in terms of the wide dispersal of their urediniospores. The development of durable resistant cultivars is the most sustainable method for controlling them. Many resistance genes have been identified, characterized, genetically mapped, and cloned; several quantitative trait loci (QTLs) for resistance have also been described. However, few studies have considered resistance to all three rust pathogens in a given germplasm. A genome-wide association study (GWAS) was carried out to identify loci associated with resistance to the three rusts in a collection of 230 inbred lines of tetraploid wheat (128 of which were Triticum turgidum ssp. durum) genotyped with SNPs. The wheat panel was phenotyped in the field and subjected to growth chamber experiments across different countries (USA, Mexico, Morocco, Italy, and Spain); then, a mixed linear model (MLM) GWAS was performed. In total, 9, 34, and 5 QTLs were identified in the A and B genomes for resistance to Pgt, Pt, and Pst, respectively, at both the seedling and adult plant stages. Only one QTL on chromosome 4A was found to be effective against all three rusts at the seedling stage. Six QTLs conferring resistance to two rust species at the adult plant stage were mapped: three on chromosome 1B and one each on 5B, 7A, and 7B. Fifteen QTLs conferring seedling resistance to two rusts were mapped: five on chromosome 2B, three on 7B, two each on 5B and 6A, and one each on 1B, 2A, and 7A. Most of the QTLs identified were specific for a single rust species or race of a species. Candidate genes were identified within the confidence intervals of a QTL conferring resistance against at least two rust species by using the annotations of the durum (cv. ‘Svevo’) and wild emmer wheat (‘Zavitan’) reference genomes. The 22 identified loci conferring resistance to two or three rust species may be useful for breeding new and potentially durable resistant wheat cultivars.