Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge
In the smallholder, low-input farming systems widespread in sub-Saharan Africa, farmers select and propagate crop varieties based on their traditional knowledge and experience. A data-driven integration of their knowledge into breeding pipelines may support the sustainable intensification of local f...
| Main Authors: | , , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Inglés |
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National Academy of Sciences
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/129799 |
| _version_ | 1855520929819394048 |
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| author | Gesesse, Cherinet Alem Nigir, Bogale Sousa, Kauê de Gianfranceschi, Luca Gallo, Guido Roberto Poland, Jesse A. Gebrehawaryat, Yosef Kidane Desta, Ermias Abate Fadda, Carlo Pè, Mario Enrico Dell’Acqua, Matteo |
| author_browse | Dell’Acqua, Matteo Desta, Ermias Abate Fadda, Carlo Gallo, Guido Roberto Gebrehawaryat, Yosef Kidane Gesesse, Cherinet Alem Gianfranceschi, Luca Nigir, Bogale Poland, Jesse A. Pè, Mario Enrico Sousa, Kauê de |
| author_facet | Gesesse, Cherinet Alem Nigir, Bogale Sousa, Kauê de Gianfranceschi, Luca Gallo, Guido Roberto Poland, Jesse A. Gebrehawaryat, Yosef Kidane Desta, Ermias Abate Fadda, Carlo Pè, Mario Enrico Dell’Acqua, Matteo |
| author_sort | Gesesse, Cherinet Alem |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | In the smallholder, low-input farming systems widespread in sub-Saharan Africa, farmers select and propagate crop varieties based on their traditional knowledge and experience. A data-driven integration of their knowledge into breeding pipelines may support the sustainable intensification of local farming. Here, we combine genomics with participatory research to tap into traditional knowledge in smallholder farming systems, using durum wheat (Triticum durum Desf.) in Ethiopia as a case study. We developed and genotyped a large multiparental population, called the Ethiopian NAM (EtNAM), that recombines an elite international breeding line with Ethiopian traditional varieties maintained by local farmers. A total of 1,200 EtNAM lines were evaluated for agronomic performance and farmers’ appreciation in three locations in Ethiopia, finding that women and men farmers could skillfully identify the worth of wheat genotypes and their potential for local adaptation. We then trained a genomic selection (GS) model using farmer appreciation scores and found that its prediction accuracy over grain yield
(GY) was higher than that of a benchmark GS model trained on GY. Finally, we used forward genetics approaches to identify marker–trait associations for agronomic traits and farmer appreciation scores. We produced genetic maps for individual EtNAM families and used them to support the characterization of genomic loci of breeding relevance with pleiotropic effects on phenology, yield, and farmer preference. Our data show that farmers’ traditional knowledge can be integrated in genomics-driven breeding to support the selection of best allelic combinations for local adaptation. |
| format | Journal Article |
| id | CGSpace129799 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | National Academy of Sciences |
| publisherStr | National Academy of Sciences |
| record_format | dspace |
| spelling | CGSpace1297992025-12-08T10:29:22Z Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge Gesesse, Cherinet Alem Nigir, Bogale Sousa, Kauê de Gianfranceschi, Luca Gallo, Guido Roberto Poland, Jesse A. Gebrehawaryat, Yosef Kidane Desta, Ermias Abate Fadda, Carlo Pè, Mario Enrico Dell’Acqua, Matteo plant breeding marker-assisted selection genomic selection smallholders In the smallholder, low-input farming systems widespread in sub-Saharan Africa, farmers select and propagate crop varieties based on their traditional knowledge and experience. A data-driven integration of their knowledge into breeding pipelines may support the sustainable intensification of local farming. Here, we combine genomics with participatory research to tap into traditional knowledge in smallholder farming systems, using durum wheat (Triticum durum Desf.) in Ethiopia as a case study. We developed and genotyped a large multiparental population, called the Ethiopian NAM (EtNAM), that recombines an elite international breeding line with Ethiopian traditional varieties maintained by local farmers. A total of 1,200 EtNAM lines were evaluated for agronomic performance and farmers’ appreciation in three locations in Ethiopia, finding that women and men farmers could skillfully identify the worth of wheat genotypes and their potential for local adaptation. We then trained a genomic selection (GS) model using farmer appreciation scores and found that its prediction accuracy over grain yield (GY) was higher than that of a benchmark GS model trained on GY. Finally, we used forward genetics approaches to identify marker–trait associations for agronomic traits and farmer appreciation scores. We produced genetic maps for individual EtNAM families and used them to support the characterization of genomic loci of breeding relevance with pleiotropic effects on phenology, yield, and farmer preference. Our data show that farmers’ traditional knowledge can be integrated in genomics-driven breeding to support the selection of best allelic combinations for local adaptation. 2023-03-27 2023-03-29T14:50:46Z 2023-03-29T14:50:46Z Journal Article https://hdl.handle.net/10568/129799 en Open Access application/pdf National Academy of Sciences Gesesse, C.A.; Nigir, B.; de Sousa, K.; Gianfranceschi, L.; Gallo, G.R.; Poland, J.; Gebrehawaryat, Y.K.; Desta, E.A.; Fadda, C.; Pè, M.E.; Dell’Acqua, M. (2023) Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge. PNAS 120(14): e2205774119. 10 p. ISSN: 0027-8424 |
| spellingShingle | plant breeding marker-assisted selection genomic selection smallholders Gesesse, Cherinet Alem Nigir, Bogale Sousa, Kauê de Gianfranceschi, Luca Gallo, Guido Roberto Poland, Jesse A. Gebrehawaryat, Yosef Kidane Desta, Ermias Abate Fadda, Carlo Pè, Mario Enrico Dell’Acqua, Matteo Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge |
| title | Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge |
| title_full | Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge |
| title_fullStr | Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge |
| title_full_unstemmed | Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge |
| title_short | Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge |
| title_sort | genomics driven breeding for local adaptation of durum wheat is enhanced by farmers traditional knowledge |
| topic | plant breeding marker-assisted selection genomic selection smallholders |
| url | https://hdl.handle.net/10568/129799 |
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