Article ; Online: Genetic analysis of global faba bean diversity, agronomic traits and selection signatures.
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
2023 Volume 136, Issue 5, Page(s) 114
Abstract: Key message: We identified marker-trait associations for key faba bean agronomic traits and genomic signatures of selection within a global germplasm collection. Faba bean (Vicia faba L.) is a high-protein grain legume crop with great potential for ... ...
| Abstract | Key message: We identified marker-trait associations for key faba bean agronomic traits and genomic signatures of selection within a global germplasm collection. Faba bean (Vicia faba L.) is a high-protein grain legume crop with great potential for sustainable protein production. However, little is known about the genetics underlying trait diversity. In this study, we used 21,345 high-quality SNP markers to genetically characterize 2678 faba bean genotypes. We performed genome-wide association studies of key agronomic traits using a seven-parent-MAGIC population and detected 238 significant marker-trait associations linked to 12 traits of agronomic importance. Sixty-five of these were stable across multiple environments. Using a non-redundant diversity panel of 685 accessions from 52 countries, we identified three subpopulations differentiated by geographical origin and 33 genomic regions subjected to strong diversifying selection between subpopulations. We found that SNP markers associated with the differentiation of northern and southern accessions explained a significant proportion of agronomic trait variance in the seven-parent-MAGIC population, suggesting that some of these traits were targets of selection during breeding. Our findings point to genomic regions associated with important agronomic traits and selection, facilitating faba bean genomics-based breeding. |
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| MeSH term(s) | Vicia faba/genetics ; Genome-Wide Association Study ; Plant Breeding ; Phenotype ; Fabaceae/genetics |
| Language | English |
| Publishing date | 2023-04-19 |
| Publishing country | Germany |
| Document type | Journal Article |
| ZDB-ID | 2170-2 |
| ISSN | 1432-2242 ; 0040-5752 |
| ISSN (online) | 1432-2242 |
| ISSN | 0040-5752 |
| DOI | 10.1007/s00122-023-04360-8 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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