| 1. |
- Abebe, Admas Alemu, et al.
(författare)
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Genome-Wide Association Analysis and Genomic Prediction for Adult-Plant Resistance to Septoria Tritici Blotch and Powdery Mildew in Winter Wheat
- 2021
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Ingår i: Frontiers in Genetics. - : Frontiers Media SA. - 1664-8021. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Septoria tritici blotch (STB) caused by the fungal pathogen Zymoseptoria tritici and powdery mildew (PM) caused by Blumeria graminis f.sp tritici (Bgt) are among the forefront foliar diseases of wheat that lead to a significant loss of grain yield and quality. Resistance breeding aimed at developing varieties with inherent resistance to STB and PM diseases has been the most sustainable and environment-friendly approach. In this study, 175 winter wheat landraces and historical cultivars originated from the Nordic region were evaluated for adult-plant resistance (APR) to STB and PM in Denmark, Estonia, Lithuania, and Sweden. Genome-wide association study (GWAS) and genomic prediction (GP) were performed based on the adult-plant response to STB and PM in field conditions using 7,401 single-nucleotide polymorphism (SNP) markers generated by 20K SNP chip. Genotype-by-environment interaction was significant for both disease scores. GWAS detected stable and environment-specific quantitative trait locis (QTLs) on chromosomes 1A, 1B, 1D, 2B, 3B, 4A, 5A, 6A, and 6B for STB and 2A, 2D, 3A, 4B, 5A, 6B, 7A, and 7B for PM adult-plant disease resistance. GP accuracy was improved when assisted with QTL from GWAS as a fixed effect. The GWAS-assisted GP accuracy ranged within 0.53-0.75 and 0.36-0.83 for STB and PM, respectively, across the tested environments. This study highlights that landraces and historical cultivars are a valuable source of APR to STB and PM. Such germplasm could be used to identify and introgress novel resistance genes to modern breeding lines.
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| 2. |
- Abebe, Admas Alemu
(författare)
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Genome-wide association study for yield-related traits in sesame (Sesamum Indicum)
- 2022
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Ingår i: Plant Breeding. - : Wiley. - 0179-9541 .- 1439-0523. ; 141, s. 246-256
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Tidskriftsartikel (refereegranskat)abstract
- Sesame is an important oil crop in Ethiopia and other regions in terms of both area coverage and production. However, productivity is low due to biotic and abiotic stresses. Therefore, dissecting the genetic basis of quantitatively inherited yield-related traits is instrumental to developing stable and high-yielding varieties. A genome-wide association study (GWAS) was performed with a diverse set of 300 sesame accessions tested in two environments and 2997 SNP markers. In total, 21 significant marker-trait associations (MTAs) were detected for seven yield-related traits, including days to flower initiation (DFI), days to 50% flowering (DF), days to physiological maturity (DM), capsule length (CAPL), seeds per capsule (SPC), 1000-seed weight (TSW) and bacterial blight (BBL). The majority of MTAs detected on LG 3, 7 and 8 were associated with traits related to physiological periods. Dissecting genetic control of flowering time and maturity has a pivotal contribution to fostering sesame breeding and developing new varieties adaptable to changing climatic conditions. Our GWAS results will assist in incorporating alleles into the elite sesame germplasm through marker-assisted selection.
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| 3. |
- Abebe, Admas Alemu, et al.
(författare)
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Genomic selection in plant breeding: key factors shaping two decades of progress
- 2024
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Ingår i: Molecular Plant. - 1674-2052 .- 1752-9867. ; 17, s. 552-578
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Forskningsöversikt (refereegranskat)abstract
- 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.
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| 4. |
- Abebe, Admas Alemu, et al.
(författare)
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Haplotype-tagged SNPs improve genomic prediction accuracy for Fusarium head blight resistance and yield-related traits in wheat
- 2023
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Ingår i: TAG Theoretical and Applied Genetics. - 0040-5752 .- 1432-2242. ; 136
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Tidskriftsartikel (refereegranskat)abstract
- Genomic prediction is a powerful tool to enhance genetic gain in plant breeding. However, the method is accompanied by various complications leading to low prediction accuracy. One of the major challenges arises from the complex dimensionality of marker data. To overcome this issue, we applied two pre-selection methods for SNP markers viz. LD-based haplotype-tagging and GWAS-based trait-linked marker identification. Six different models were tested with preselected SNPs to predict the genomic estimated breeding values (GEBVs) of four traits measured in 419 winter wheat genotypes. Ten different sets of haplotype-tagged SNPs were selected by adjusting the level of LD thresholds. In addition, various sets of trait-linked SNPs were identified with different scenarios from the training-test combined and only from the training populations. The BRR and RR-BLUP models developed from haplotype-tagged SNPs had a higher prediction accuracy for FHB and SPW by 0.07 and 0.092, respectively, compared to the corresponding models developed without marker pre-selection. The highest prediction accuracy for SPW and FHB was achieved with tagged SNPs pruned at weak LD thresholds (r2 < 0.5), while stringent LD was required for spike length (SPL) and flag leaf area (FLA). Trait-linked SNPs identified only from training populations failed to improve the prediction accuracy of the four studied traits. Pre-selection of SNPs via LD-based haplotype-tagging could play a vital role in optimizing genomic selection and reducing genotyping costs. Furthermore, the method could pave the way for developing low-cost genotyping methods through customized genotyping platforms targeting key SNP markers tagged to essential haplotype blocks.
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| 5. |
- Abebe, Admas Alemu
(författare)
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Multi-model genome-wide association and genomic prediction analysis of 16 agronomic, physiological and quality related traits in ICARDA spring wheat
- 2021
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Ingår i: Euphytica. - : Springer Science and Business Media LLC. - 0014-2336 .- 1573-5060. ; 217
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Tidskriftsartikel (refereegranskat)abstract
- Identification and exploration of the genetic architecture of traits related to yield, quality, and drought and heat tolerance is important for yield and quality improvement of wheat through marker-assisted selection. One hundred and ninety-two spring wheat genotypes were tested at two heat-stress locations in Sudan (Wad Medani and Dongula), a drought stress site in Morocco (Marchouch) and a site with high yield potential in Egypt (Sids) in replicated trials during the 2015-2016 and 2016-2017 cropping seasons. A total of 10,577 single nucleotide polymorphism markers identified from the 15 K wheat SNP assay were used in a genome-wide association (GWA) study and genomic prediction for 16 phenotypic traits related to yield, quality and drought and heat tolerance. Significant marker-trait associations were detected across GWAS models for all traits. Most detected marker-trait associations (MTAs) were environment-specific, signifying the presence of high quantitative trait loci-by-environment (QTL x E) interaction. Chromosome arm 5AL had significant multi-model MTAs for grain yield and yield-related traits at the heat-stress locations. Highly significant QTLs were detected on chromosome 2D for waxiness. Homoeologous group 2 and 6 chromosomes were with significant MTAs for grain protein content, gluten content, alveograph strength and Zeleny sedimentation test while chromosome arm 3BL was significant for both Z and W traits. Genomic prediction analysis with ridge regression-best linear unbiased prediction model estimated the breeding values of the studied traits with prediction accuracies ranging from 0.16 for leaf rolling to 0.72 for peduncle length. The identified QTLs could be targeted for marker-assisted selection or further studies aimed at fine mapping and cloning the causative genes and detecting favorable haplotypes with positive effects for agronomic, physiological or quality-related traits.
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| 6. |
- Abebe, Admas Alemu
(författare)
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Single- and multi-trait genomic prediction and genome-wide association analysis of grain yield and micronutrient-related traits in ICARDA wheat under drought environment
- 2023
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Ingår i: Molecular Genetics and Genomics. - 1617-4615 .- 1617-4623. ; 298, s. 12-
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 7. |
- Abebe, Admas Alemu, et al.
(författare)
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Unraveling the Genetic Basis of Key Agronomic Traits of Wrinkled Vining Pea (Pisum sativum L.) for Sustainable Production
- 2022
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Ingår i: Frontiers in Plant Science. - : Frontiers Media SA. - 1664-462X. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Estimating the allelic variation and exploring the genetic basis of quantitatively inherited complex traits are the two foremost breeding scenarios for sustainable crop production. The current study utilized 188 wrinkled vining pea genotypes comprising historical varieties and breeding lines to evaluate the existing genetic diversity and to detect molecular markers associated with traits relevant to vining pea production, such as wrinkled vining pea yield (YTM100), plant height (PH), earliness (ERL), adult plant resistance to downy mildew (DM), pod length (PDL), numbers of pods per plant (PDP), number of peas per pod (PPD), and percent of small wrinkled vining peas (PSP). Marker-trait associations (MTAs) were conducted using 6902 quality single nucleotide polymorphism (SNP) markers generated from the diversity arrays technology sequencing (DArTseq) and Genotyping-by-sequencing (GBS) sequencing methods. The best linear unbiased prediction (BLUP) values were estimated from the two-decades-long (1999-2020) unbalanced phenotypic data sets recorded from two private breeding programs, the Findus and the Birds eye, now owned by Nomad Foods. Analysis of variance revealed a highly significant variation between genotypes and genotype-by-environment interactions for the ten traits. The genetic diversity and population structure analyses estimated an intermediate level of genetic variation with two optimal sub-groups within the current panel. A total of 48 significant (P < 0.0001) MTAs were identified for eight different traits, including five for wrinkled vining pea yield on chr2LG1, chr4LG4, chr7LG7, and scaffolds (two), and six for adult plant resistance to downy mildew on chr1LG6, chr3LG5 (two), chr6LG2, and chr7LG7 (two). We reported several novel MTAs for different crucial traits with agronomic importance in wrinkled vining pea production for the first time, and these candidate markers could be easily validated and integrated into the active breeding programs for marker-assisted selection.
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| 8. |
- Johansson, Eva, et al.
(författare)
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Marker-assisted selection for the improvement of cereals and pseudocereals
- 2023
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Ingår i: Developing Sustainable and Health Promoting Cereals and Pseudocereals : Conventional and Molecular Breeding. ; , s. 253-283
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Bokkapitel (refereegranskat)abstract
- Selection of the most suitable plants or germplasm to produce high quantity and quality of food has been ongoing since the domestication of the crops started almost 10,000 years ago. However, recent genome-based tools have opened opportunities that we could only dream about just 10 years ago. From the low-throughput molecular marker methods first employed in plants on maize in the 1980s, through medium- to high-throughput system marker-assisted selection (MAS) have revolutionized the breeding of the major cereal crops, i.e. wheat, maize, and rice, which are the largest (in terms of production and acreage) crops in the world. For pseudocereals and minor cereals, MAS has been adopted but not to the same extent as for the major crops. The present chapter is reviewing the development of MAS methods and the current state of the art of these methods while used to improve cereals’ and pseudocereals’ yield, resistance/tolerance, and quality.
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