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Genetic analysis of global faba bean diversity, agronomic traits and selection signatures

Authors :
Cathrine Kiel Skovbjerg
Deepti Angra
Tom Robertson-Shersby-Harvie
Jonathan Kreplak
Gabriel Keeble-Gagnère
Sukhjiwan Kaur
Wolfgang Ecke
Alex Windhorst
Linda Kærgaard Nielsen
Andrea Schiemann
Jens Knudsen
Natalia Gutierrez
Vasiliki Tagkouli
Lavinia Ioana Fechete
Luc Janss
Jens Stougaard
Ahmed Warsame
Sheila Alves
Hamid Khazaei
Wolfgang Link
Ana Maria Torres
Donal Martin O’Sullivan
Stig Uggerhøj Andersen
Aarhus University [Aarhus]
University of Reading (UOR)
Agroécologie [Dijon]
Université de Bourgogne (UB)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon
Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Centre for AgriBioscience, Bundoora
Georg-August-University = Georg-August-Universität Göttingen
Sejet Planteforædling
Nordic Seed
IFAPA Centro Alameda del Obispo
Instituto Andaluz de Investigación y Formación Agraria y Pesquera (IFAPA)
Crops Research, Teagasc, Oak Park, Carlow
Natural Resources Institute Finland (LUKE)
Open access funding provided by Royal Danish Library. Thework was funded by the European Union’s Horizon 2020 Programmefor Research & Innovation (grant agreement no. 727312 for theEUCLEG project
the ERA-NET Cofund SusCrop (grant no. 771134),part of the Joint Programming Initiative on Agriculture, Food Security,and Climate Change (FACCE-JPI) for the ProFaba project)
InnovationFund Denmark (NORFAB: Protein for the Northern Hemisphere, grantno. 5158-00004B)
and UK Research and Innovation for BEANS4N.AFRICA (grant award BB/P023509/1). The VICCI population wasdeveloped under a doctoral project between the University of Readingand Teagasc and was supported by the Irish Department of Agriculture,Food and the Marine (DAFM), under project 14/S/819 (the VirtualIrish Centre for Crop Improvement). The RSBP population was developed with the support of a PhD fellowship to Ahmed Warsame fromthe Islamic Development Bank
European Project: 771134
European Project: 727312
Source :
Skovbjerg, C K, Angra, D, Robertson-Shersby-Harvie, T, Kreplak, J, Keeble-Gagnère, G, Kaur, S, Ecke, W, Windhorst, A, Nielsen, L K, Schiemann, A, Knudsen, J, Gutierrez, N, Tagkouli, V, Fechete, L I, Janss, L, Stougaard, J, Warsame, A, Alves, S, Khazaei, H, Link, W, Torres, A M, O'Sullivan, D M & Andersen, S U 2023, ' Genetic analysis of global faba bean diversity, agronomic traits and selection signatures ', Theoretical and Applied Genetics, vol. 136, no. 5, 114 . https://doi.org/10.1007/s00122-023-04360-8, TAG Theoretical and Applied Genetics, TAG Theoretical and Applied Genetics, 2023, 136 (114), ⟨10.1007/s00122-023-04360-8⟩
Publication Year :
2023
Publisher :
Springer Science and Business Media LLC, 2023.

Abstract

Key message We identified marker-trait associations for key faba bean agronomic traits and genomic signatures of selection within a global germplasm collection. Abstract 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.

Details

ISSN :
14322242 and 00405752
Volume :
136
Database :
OpenAIRE
Journal :
Theoretical and Applied Genetics
Accession number :
edsair.doi.dedup.....e8f184c9fd64bfcf65a5c21f50b53693
Full Text :
https://doi.org/10.1007/s00122-023-04360-8